Wednesday, June 25, 2014

Indians are not descendants of Aryans, says new study

Indians are not descendants of Aryans, says new study
Widely believed theory of Indo-Aryan invasion, often used to explain early settlements in the Indian subcontinent is a myth, a new study by Indian geneticists says.
The origin of genetic diversity found in South Asia is much older than 3,500 years when the Indo-Aryans were supposed to have migrated to India, a new study led by scientists from the Centre for Cellular and Molecular Biology (CCMB), Hyderabad, says. The study appeared in American Journal of Human Genetics on Friday.
The theory of Indo-Aryan migration was proposed in mid-19th century by German linguist and Sanskrit scholar Max Muller.
He had suggested that 3,500 years ago, a dramatic migration of Indo-European speakers from Central Asia played a key role in shaping contemporary South Asian populations and this was responsible for introduction of the Indo-European language family and the caste system in India.
"Our study clearly shows that there was no genetic influx 3,500 years ago," said Dr Kumarasamy Thangaraj of CCMB, who led the research team, which included scientists from the University of Tartu, Estonia, Chettinad Academy of Research and Education, Chennai and Banaras Hindu University.
"It is high time we re-write India's prehistory based on scientific evidence," said Dr Lalji Singh, former director of CCMB. "There is no genetic evidence that Indo-Aryans invaded or migrated to India or even something such as Aryans existed". Singh, vice-chancellor of BHU, is a coauthor.
Researchers analysed some six lakh bits of genetic information in the form of SNPs drawn from DNA of over 1,300 individuals from 112 populations including 30 ethnic groups in India.
The comparison of this data with genetic data of other populations showed that South Asia harbours two major ancestry components. One is spread in populations of South and West Asia, Middle East, Near East and the Caucasus. The second component is more restricted to South Asia and accounts for more than 50 per cent of the ancestry in Indian populations.
"Both the ancestry components that dominate genetic variation in South Asia demonstrate much greater diversity than those that predominate West Eurasia. This is indicative of a more ancient demographic history and a higher long-term effective population size underlying South Asian genome variation compared to that of West Eurasia," researchers said.
"The genetic component which spread beyond India is significantly higher in India than in any other part of world. This implies that this genetic component originated in India and then spread to West Asia and Caucasus," said Gyaneshwar Chaube of University of Tartu, Estonia.
If any migration from Central Asia to South Asia took place, the study says, it should have introduced apparent signals of East Asian ancestry into India. "Because this ancestry component is absent from the region, we have to conclude that if such an event indeed took place, it occurred before the East Asian ancestry component reached central Asia," it said.
South Asia harbors one of the highest levels genetic diversity in Eurasia, which could be interpreted as a result of its long-term large effective population size and of admixture during its complex demographic history. In contrast to Pakistani populations, populations of Indian origin have been underrepresented in previous genomic scans of positive selection and population structure. Here we report data for more than 600,000 SNP markers genotyped in 142 samples from 30 ethnic groups in India. Combining our results with other available genome-wide data, we show that Indian populations are characterized by two major ancestry components, one of which is spread at comparable frequency and haplotype diversity in populations of South and West Asia and the Caucasus. The second component is more restricted to South Asia and accounts for more than 50% of the ancestry in Indian populations. Haplotype diversity associated with these South Asian ancestry components is significantly higher than that of the components dominating the West Eurasian ancestry palette. Modeling of the observed haplotype diversities suggests that both Indian ancestry components are older than the purported Indo-Aryan invasion 3,500 YBP. Consistent with the results of pairwise genetic distances among world regions, Indians share more ancestry signals with West than with East Eurasians. However, compared to Pakistani populations, a higher proportion of their genes show regionally specific signals of high haplotype homozygosity. Among such candidates of positive selection in India are MSTN and DOK5, both of which have potential implications in lipid metabolism and the etiology of type 2 diabetes.


Understanding the genetic structure of mankind globally and the role of natural selection in shaping it are complex tasks that require data from multiple populations to represent the geographic range and environmental diversity of the inhabited world. Previous studies on South Asia have highlighted this region as having one of the highest levels of genetic diversity, second only to Africa.1 and 2 Studies of haploid loci (mtDNA and the nonrecombining region of Y Chromosome [NRY]) have revealed that the South Asian genetic makeup is dominated by largely autochthonous lineages testifying for low levels of admixture with other parts of Eurasia because the peopling of the subcontinent some 50,000 to 70,000 years ago Notably, these genetic dates are earlier than the oldest confirmed human fossil in the subcontinent, found in Sri Lanka and dated to 31,000 years before present (YBP),7 but postdate the archaeological evidence below and above the layers of ash from the Mount Toba volcanic supereruption associated with the Middle Palaeolithic tools that could have been produced by anatomically modern humans Recent archaeological evidence from the Jebel Faya site in the Arabian Peninsula permitted the authors to consider that the manufacturers of these tools could have dispersed into India as early as 125,000 YBP. Whether the genes of the crafters of these Middle Palaeolithic tools still persist among modern populations is a lingering question.
Although the HapMap,he Human Genome Diversity Project, the 1000 Genomes Project and the Human Genome Organisation (HUGO) Pan-Asian SNP Consortium have all significantly improved our understanding of the global genetic diversity of humans, there are still significant gaps in their coverage. India remains one such region, where large genetic diversity and vast population sizes have so far gone underrepresented in genome-wide studies of human genetic diversity despite some important recent advances. Most studies highlight the elevated genetic diversity of the South Asian populations and their general clustering by language group and/or geography. Relying on extensive resequencing rather than on genotyping panel data1 showed that 30% of SNPs found in Indian populations were not seen in HapMap populations and that compared to these populations (including Africans) some Indian populations displayed higher levels of genetic variation, whereas some others showed unexpectedly low diversity. Operating with a thin set of genome-wide polymorphisms, identified lower than expected levels of variation across geographically and linguistically distinct populations when sampling Indian immigrants living in the USA. Others have, contrary to this finding, shown high levels of intergroup genetic differentiation of Indian populations sampled in India. Furthermore, Reich et al.reported higher than expected levels of homozygosity within Indian groups when examining a high density genome-wide SNP data set and attributed this pattern to population stratification born out of the endogamy associated with the caste system. Reich et al. have also made an argument for a sizeable contribution from West Eurasia to a putative ancestral north Indian (ANI) gene pool. Through admixture between an ancestral south Indian (ASI) gene pool, this ANI variation was found to have contributed significantly to the extant makeup of not only north (50%–70%) but also south Indian populations (>40%). This is in contrast with the results from mtDNA studies, where the percentage of West Eurasian maternal lineages is substantial (up to 50%) in Indus Valley populations but marginal (<10%) in the south of the subcontinent. Because any potential genetic impact into South Asia from the west would involve at least one of the immediately adjacent regions—Central Asia, the Caucasus, or West Asia (including Iran)—assessment of the extent of admixture in South Asia and its sources is crippled without genetic data from those regions. Genome-wide scans on the Human genome diversity panel (HGDP) data involving 51 global populations have revealed that South Asia, represented by Pakistani populations, shares most signals of recent positive selection with populations from Europe, the Near East, and North Africa. Given the environmental differences between Europe and Pakistan and the possible depth of human habitation in South Asia, this result is surprising, but considering the lack of Indian data it remains to be determined whether South Asian-specific signals of positive selection do exist.
To shed more light on the nature of genetic continuity and discontinuity between South and West Asia, the Near East, the Caucasus, and Central Asia, we applied FST, principal component analysis (PCA) and model-based structure-like approaches to a genome-wide sample of ca 530,000 SNPs in a sample set combining published data on India, relevant global reference populations, and 142 newly genotyped Indian individuals of various linguistic, geographic and social affiliations 

Material and Methods

Samples, Genotyping, and Quality Control

We introduce here 142 Indian samples from 30 populations that we have genotyped with Illumina 650K SNP array according to manufacturers' specifications. All subjects filled and signed personal informed consents and the study was approved by scientific council of the Estonian Biocentre. The data can be accessed through The National Center for Biotechnology Information -Gene Expression Omnibus (NCBI GEO) (GSE33489) and by request to the authors. We analyzed these data together with published data from on Indian and other populations used as background. The overlap of SNPs between the different Illumina (610K, 650K, and 660K) arrays in published and new data was ca. 530,000 SNPs; overlap between this data set and the HapMap 3 was 480,000 SNPs. Depending on the analyses (e.g., computational optimization), we included different number of reference populations from these sources . We excluded published data on South Asian populations genotyped on different platforms (Affimetrix) from most of the analyses because cross-platform overlap in SNPs is limited (ca. 95,000 SNP) for haplotype based analyses. However, we used data from Reich et al. to validate our FST and PCA results. Sampling locations for populations analyzed here are shown on (available online) together with a comparison to sampling from the previous study.
We filtered the combined data sets by using PLINK software 1.05 to include only SNPs on the 22 autosomal chromosomes with a minor allele frequency > 1% and genotyping success > 97%. Only individuals with a genotyping success rate > 97% were used. Because background linkage disequilibrium (LD) can affect both principal component and structure-like analysis, we thinned the marker set further by excluding SNPs in strong LD (pairwise genotypic correlation r2 > 0.4) in a window of 200 SNPs (sliding the window by 25 SNPs at a time). Depending on the number of reference populations, this yielded data sets of ca. 200,000 SNPs that were used for the respective analyses.

Phylodemographic Analyses

We calculated mean pairwise FST values between populations (and regional population groups) for all autosomal SNPs by using the approach of Weir et al.assembled into an in-house R script. For FST calculation, the combined data set was filtered to include only populations with n > 4. In some cases geographically close populations with a smaller sample size were grouped. Given the high levels of population structure within India, resulting from restricted gene flow between populations, genetic drift in small endogamous units, and our small sample sizes, the interpretation of FST distances between pools of samples from different, although genetically closely related, populations might not, necessarily, be straightforward. To validate our results, we recalculated FST values excluding population pools and setting a threshold of minimum of seven samples per population. To increase population coverage, we included here data from Reich et al. and the resulting cross-platform SNP panel consisted of 95,001 post quality control SNPs .
PCA was carried out in the smartpca program on the Eurasian populations. Here too, we repeated the analysis on the data set that included more Indian samples but fewer SNPs . Geographic spread of principal components ([PCs] averaged to population level) was visualized with kriging procedure in Surfer package of Golden Software. Spatial autocorrelation and modified t test that estimate correlation of spatially located variables and correct for spatial autocorrelation were carried out in Passage 2. Geographic distances between populations were calculated as Eucleidian distances between x and y coordinates on a Conformal Conic Asia Lambert projection.
To monitor convergence between individual runs, we ran ADMIXTURE 100 times at K = 2 to K = 18 . The lowest cross validation indexes that point to the best K were observed at K = 15, but there was no significant difference above K = 10 . However, judging by low level of variation in Loglikelihood scores (LLs < 1) within a fraction (10%) of runs with the highest LLs, we assume that the global maximum was reached at K = 2 to K = 8, K = 12, and K = 13  rendering these practical representations of genetic structure at different levels of resolution. We also verified that all runs within these 10% of runs at these values of K did indeed produce a very similar (indistinguishable) ancestry proportions pattern.

Haplotype Diversity Associated with Ancestry Informative Markers

We used the individual ancestry proportion inferred by using ADMIXTURE as a quantitative trait and tested for association. Allele dosage for an SNP associated with a given ancestry is expected to increase with an increasing proportion of ancestry. Assuming such a relationship between the genotype and trait value, we used regression analysis to estimate how strongly each SNP is associated with a given ancestry. We expected a large number of SNPs to be associated with a given ancestry component, therefore occasional false positive SNPs are negligible, and we chose not to apply any multiple testing correction procedures. Instead, we chose to filter out statistically significant regression coefficients (beta values) by using arbitrarily chosen significance threshold. In order to select only strongly associated SNPs, we further filtered SNPs to retain only those exceeding 90 or 95 percentile points of positive beta-value distribution. The haplotype diversity flanking each associated SNP was then summarized with the number of distinct haplotypes. A summary statistic derived from the number of distinct haplotypes across genomic windows has been shown to be informative about past population demography. In this study, Lohmueller et al. considered the joint distribution of two haplotype based statistics—the number of distinct haplotypes and the count of the most common haplotype. Here, we use only the number of distinct haplotypes to measure haplotype diversity. Genomic windows of different size—0.45, 0.33, 0.26, 0.1, and 0.05 centiMorgans—were defined around each associated SNP, and the number of distinct haplotypes within each window was counted. We followed and randomly selected a subset of nSNP SNPs from each window to ensure that all windows have the same number of SNPs and that the resulting statistics are not affected by the unequal distribution of markers across the genome. Within each window we randomly sampled nSNP SNPs multiple times, counted the number of distinct haplotypes each time, and took the average as a summary. For each population, we randomly chose ten individuals and counted the total number of windows having 0, 1, 2,.., nmax number of haplotypes and plotted this summary statistic by using heatmap.
Nucleotide substitutions arising in one population and then introduced to other populations are expected to show different levels of haplotype diversity in the source and recipient populations. However, this difference gets diluted because hybrid haplotypes arise through recombination in the recipient population. Their number will increase each generation, and it is therefore important to explore how the number of generations since the migration into new population will affect our ability to detect source and recipient populations for a given mutation on the basis of haplotype diversity differences.
We generated population samples by simulating admixture events between European and Asian populations as described in the next section. We explored haplotype diversity flanking SNPs associated with Asian ancestry in these samples from admixed populations. Our simulated data set shows that when European population is the recipient and Asian population the is source, then
Haplotype diversity flanking Asian alleles in admixed recipient populations is lower than in source Asian populations for all the simulated admixture events except for the oldest one that occurred 750 generations ago. The latter case confirms our expectation that immigrant alleles will be flanked with a higher number of hybrid haplotypes (those having both Asian and European ancestry blocks) with an increasing number of generations since admixture.
Haplotype diversity flanking European alleles in admixed populations can be comparable (for those populations having 70% of European ancestry) or even higher (for those having 90% European ancestry) than in the original European population despite the fact that admixed populations always have lower European ancestry (90% or 70%) than the original European population. This might be because of novel hybrid haplotypes produced by the recombination process. Our simulations show that haplotype diversity flanking autosomal SNPs can be used to infer source population even when populations dispersed these alleles 288, 400, or 500 generations ago. Assuming an average human generation interval of 25 years, this is 7,200, 10,000 or 12,500 years, which roughly overlaps with the Neolithic period.

Demographic Model for Simulations

We used MaCS coalescent simulator to generate simulated data for three nonadmixed and 18 admixed populations by modifying the demographic model originally published in. In this study a series of population genetic statistics were used to fit demographic history of simulated populations to those observed for African, Asian, and European populations. Here, we used these demographic parameters to simulate samples of sequences drawn from African, Asian, and European populations. An additional 18 admixed populations were generated by simulating admixture events between European and Asian populations at different times in the past (measured in generations) and using different proportions: 50/50, 70/30, and 90/10 of sequences from European and Asian populations, respectively:
Admixture 750 generations ago; assuming one generation to be 25 years, this is roughly 18,750 years ago
Admixture 500 generations, ∼12,500 years, ago
Admixture 400 generation,∼10,000 years, ago
Neolithic admixture 288 generations ago; that is 62 generations after Neolithic expansion in a European population as defined in the best fit model of Schaffner et al.
Late Bronze Age/Iron Age admixture 138 generations, ∼3,450 years, ago
Historical time admixture 70 generations, ∼1,750 years, ago
We used the recombination rate ratio (cM/Mb) mappings for the first chromosome from HapMap project to model variation in recombination rate in simulated sequences. The total physical length of simulated sequences was 250 megabases. From each simulated population a sample of 30 sequences were drawn to construct 15 genotypes that were then subjected to quality control and LD pruning steps as for the Illumina genotyped populations analyzed in this study. Admixture proportions for each simulated individual were then inferred with structure-like analysis assuming three populations. SNPs associated with Asian and European ancestry and haplotype diversity flanking them were identified as described above.

Testing for Selection

The combined data set was filtered to include Indian populations and a comprehensive set of reference populations that yielded a data set of 990 individuals and 531,315 autosomal SNPs  This data was phased with Beagle 3.1. Although integrated haplotype score (iHS) and cross population extended haplotype homozygosity (XP-EHH) have already been calculated for the HGDP-Centre d'Etude du Polymorphisme Humaine (CEPH) panel, we recalculated all statistics by using our 531,315 SNPs to allow for unbiased comparisons between India and other geographic regions. XP-EHH and iHS were calculated as previously described with tools provided by J. Pickrell. Genetic distances between markers were calculated with the HapMap genetic map. For iHS, ancestral and derived states for each SNP were established by comparison to the UCSC snp128OrthoPanTro2RheMac2 table. Where the chimpanzee allele was known, it was assumed to be the ancestral allele; where the allele was unknown (17,868 SNPs, 3.36% of the data), the SNP was excluded from all subsequent calculations. XP-EHH and FST require two populations. Because the Mandenka, Yoruba, and Bantu farmers have clustered together in previous analyses of population structure they were grouped together in our analyses and were used as the outgroup population for all comparisons; HGDP Europeans were used as the outgroup for analyses where the focal population was African farmers. Both XP-EHH and iHS scores were normalized and windowed as in Pickrell; however, we chose not merge any adjacent outlier windows because this procedure can be very conservative and significantly affect the ranking of windows (data not shown).

Enrichment Testing

We retrieved the list of RefSeq genes from the UCSC table browser and mapped the starting and ending coordinates of all genomic transcripts to our windows. The longest transcript length was used for genes with multiple transcripts. On the basis of this list, we performed searches for gene enrichment for all Gene Ontology (GO) terms by using DAVID 6.7 on all genes in the top 1% and 5% windows of the iHS and XP-EHH test statistic distributions.


We have based our analyses of human genetic variation on a sample of 1310 individuals that belong to 112 populations. The sample set includes 142 previously unpublished samples from India and published compatible data from South Asia and beyond , chosen to represent the global and regional contexts of human genetic variation. For some analyses we also included published data on Indian populations genotyped on a different platform; adding these sources yielded a combined data set of 1,442 individuals but only ca. 95,000 SNPs 
Mean pairwise FST values within and among continental regions  reveal that the South Asian autosomal gene pool falls into a distinct geographic cluster, characterized internally, like other continental regions, by short interpopulation genetic distances (<0.01). At the interregional scale, the South Asian cluster shows somewhat shorter genetic distances with West Eurasian (average FST = 0.042) than with East Asian (average FST = 0.051) populations. Importantly, the Pakistani (Indus Valley) populations differ substantially from most of the Indian populations and show comparably low genetic differentiation (within the FST range of 0.008–0.020) from European, Near Eastern, Caucasian, and Indian populations . In agreement with previous Y-chromosome studies, the Brahmin and Kshatriya from Uttar Pradesh stand out by being closer to Pakistani (FST = 0.006 on average) and West Eurasian populations (FST = 0.030) than to other Indian populations (average FSTs 0.017 and 0.046, respectively) from the same geographic area 
Full-size image (160 K)
Figure 1.
Matrix of Pairwise Mean FST Values of Regional Groupings of the Studied Populations
Average of intergroup FST values (where the regional group is composed of multiple populations) is given in the diagonal. Central India is itself a composite of two regional groupings of samples from different populations that makes the negative intergroup FST uninformative.
Similar to the patterns revealed by the pairwise FST results, PCA of the Eurasian populations clusters them by geographic proximity with the first component separating West from East Eurasia and the second component differentiating South Asian populations from the rest. Consistent with their geographic location, Pakistanis are positioned between Indian and West Eurasian populations on this plot. However, whereas Reich et al. identified a cline of Indian populations toward Europe with no corresponding cline within the Europeans, we observe a more complex picture. The inclusion of more populations from Europe and the Caucasus reveals a cline within the West Eurasian cluster on the PCA , where both PC1 (r = 0.59) and notably PC2 (r = 0.87) display significant correlation with distance from Spain and Iran, respectively . On this PC1 × PC2 composite cline, most of the Indian populations form a disperse cluster, an edge of which is formed by a subset of the Hapmap Gujaratis and Uttar Pradesh Brahmins and Kshatriyas. Compared to Gujaratis, the Uttar Pradesh samples are more widely dispersed, overlapping substantially with most of the samples from the southern, Dravidic speaking states of Tamil Nadu and Andhra Pradesh. Furthest on the PC2 axis lay samples from the southern Indian states of Karnataka, Kerala, and the Pulliyar population from Tamil Nadu.
Full-size image (197 K)
Figure 2.
Genome-Wide Structure of the Studied Populations Revealed by 530,000 SNPs
(A) principal component analysis of the Eurasian populations. The following abbreviations are used: IE, Indo European speakers; DR, Dravidic speakers; AA, Austroasiatic speakers; TB, Tibeto Burman speakers; , data from Hapmap.
(B) ADMIXTURE analysis at K = 8 and 12. The following symbols are used: , contains one Dhurwa; ∗∗, contains one Lambadi; 1, Rajasthan; 2, Chattisgarh and Jharkhand; 3, Chattisgarh, Orissa, and Madhya Pradesh. A.P., Andhra Pradesh; Kar, Karnataka; Ker, Kerala; T. Nadu, Tamil Nadu; #, Nihali language isolate speakers from Maharasthra; §, Tibeto Burman speakers from east Indian states Meghalaya and Nagaland; AA, Austroasiatic languages.
Notably, within South Asia (India and Pakistan), PC1 is strongly correlated (r = 0.69) with longitude and PC2 with latitude (r = 0.60). Both remain significant after correcting for spatial autocorrelation. These relations are identifiable also from spatial representations of the principal components . The third PC differentiates West Eurasia by latitude, and we find Bedouins and Lithuanians on either end of the PC3 axis . The fourth PC is of particular interest because it connects Baluchistan, the Caucasus, and Central Asia . The spread of PC4 in West Eurasia is not concentric and thus difficult to explain by correlation with geographic distance from any one point. The strongest correlation is with distance from Iran (r = 0.69), but this is to a large extent explained by spatial autocorrelation because correcting for that renders a p value slightly over 0.05. Notable, however, is that PC4 has nonmarginal values also in northeast China, which is difficult to absorb into current models of human demographic history. Overall, PCA reveals that the genetic landscape of South Asia is characterized by two principal components of which PC2 is specific to India and PC4 to a wider area encompassing Pakistan, the Caucasus, and Central Asia.
In order to study this duality in more detail, we used the model-based structure-like algorithm ADMIXTURE that computes quantitative estimates for individual ancestry in constructed hypothetical ancestral populations. Most South Asians bear membership in only two of the constructed ancestral populations at K = 8. These two main ancestry components—k5 and k6, colored light and dark green in —are observed at all K values between K = 6 and K = 17 These correlate (r > 0.9; p < 0.00001) perfectly with PC4 and PC2 in West Eurasia, respectively. Looking at the Pakistani populations (0.51) and Baluchistan (Balochi, Brahui, and Makrani) in particular (0.59), the proportion of the light green component (k5) is significantly higher than in the Indian populations, (on average 0.26)  Importantly, the share of this ancestry component in the Caucasus populations (0.50) is comparable to the Pakistani populations. There are a few populations in India who lack this ancestry signal altogether. These are the thus-far sampled Austroasiatic tribes from east India, who originated in Southeast Asia and represent an admixture of Indian and East Asian ancestry components,and two small Dravidian-speaking tribes from Tamil Nadu and Kerala. However, considering the geographic spread of this component within India, there is only a very weak correlation (r = 0.4) between probability of membership in this cluster and distance from its closest core area in Baluchistan . Instead, a more steady cline (correlation r = 0.7 with distance from Baluchistan) of decrease of probability for ancestry in the k5 light green ancestral population can be observed as one moves from Baluchistan toward north (north Pakistan and Central Asia) and west (Iran, the Caucasus, and, finally, the Near East and Europe).
If the k5 light green ancestry component  originated from a recent gene flow event (for example by a demic diffusion model) with a single center of dispersal where the underlying alleles emerged, then one would expect different levels of associated haplotypic diversity to suggest the point of origin of the migration. To assess diversity within the ancestry components revealed by the ADMIXTURE analyses at K = 8, we counted the number of unique haplotypes in genomic windows surrounding SNPs in strong positive association with this ancestry component. Because recombination on autosomal chromosomes will over time erase the signal and thus limit the utility of this approach, we used simulations to explore how deep in time one can go to trace directionality of migration . Our simulations show that differences in haplotype diversity between source and recipient populations can be detected even for migration events that occurred 500 generations ago (∼12,500 years ago assuming one generation to be 25 years). For alleles associated with k5, haplotype diversity is comparable among all studied populations across West Eurasia and the Indus basin . However, we found that haplotypic diversity of this ancestry component is much greater than that of those dominating in Europe (k4, depicted in dark blue) and the Near East (k3, depicted in light blue), thus pointing to an older age of the component and/or long-term higher effective population size . Haplotype diversity flanking Asian alleles (k7) is twice greater than that of European alleles—this is probably because the k7 ancestry component is a composite of two Asian components 
In contrast to widespread light green ancestry, the dark green ancestry component, k6 is primarily restricted to the Indian subcontinent with modest presence in Central Asia and Iran. Haplotype diversity associated with dark green ancestry is greatest in the south of the Indian subcontinent, indicating that the alleles underlying it most likely arose there and spread northwards. It is notable that this ancestry component also exhibits greater haplotype diversity than European or Near Eastern components despite the fact that the Illumina genotyped markers were principally ascertained in a sample of European individuals. This observation shows again that haplotype based measures of diversity can be relatively robust to ascertainment bias.
Long-standing human habitation of the Indian subcontinent should have provided ample opportunity for the action of positive selection and the emergence of adaptations to the local environment. To examine this possibility in greater detail, we calculated iHS and XP-EHH, two haplotype-based tests that detect positive natural selection, for all Dravidian and Indo-European speaking Indian individuals in our combined data set (n = 154). After dividing the autosomal genome into 13,274 nonoverlapping 200 kb windows covered by our SNP data set (see Material and Methods), we calculated the fraction of windows in the top 1% of the Indian test statistic distribution shared with the top 5% windows in other populations. Our results largely agree with the recent description of three main patterns underlying selective sweeps in continental Eurasian populations following the out-of-Africa event and suggest that Indian sweep signals have more in common with those detected in West rather than East Eurasia. However, when we compare the fraction of outlying Indian signals also found in European or East Asian populations to the fraction of outlying Pakistani signals shared with the same regions, we find Pakistan consistently appearing markedly more similar to West Eurasian than to Indian populations . This result remains when we examine signals of recent positive selection in north and south India separately. Combined with our ADMIXTURE and PCA results, this is powerful evidence that Pakistan is a poor proxy for South Asian genetic diversity, despite having often fulfilled this role in previous publications.
Full-size image (60 K)
Figure 3.
Sharing Signals for Selection between Continental Populations
(A) iHS signal sharing between continental populations. The fraction of signals found in the top 1% of iHS scores in population i and the top 5% of population j is given in cell (i,j). Africa refers to Yoruba, Mandenka, and Bantu individuals from the HGDP-CEPH panel.
(B) XP-EHH signal sharing between continental populations. The fraction of signals found in the top 1% of XP-EHH scores in population i and the top 5% of population j is given in cell (i,j). Africa refers to Yoruba, Mandenka, and Bantu individuals from the HGDP-CEPH panel.
To gain insight into the type of biological processes likely to have come under positive selection in India, we tested for overrepresentation of GO terms in the countrywide results. These analyses revealed that 20 GO terms were overrepresented in our windowed top 1% iHS results and 27 were overrepresented in the top 1% XP-EHH results when an individual 0.05 significance level was used (Table S2. Significantly Enriched GO Terms, Before FDR Correction, in the Top 1% iHS All India Results, Reported by DAVID Analysis and Table S3. Significantly Enriched GO Terms, Before FDR Correction, in the Top 1% XP-EHH All India Results, Reported by DAVID Analysis). These results include terms such as lipid metabolism and catabolism, which are associated with genes implicated in the etiology of type 2 diabetes (MIM 125853), the incidence of which is rapidly growing in India and could represent maladaptations to recent changes in the environment, diet, and lifestyle following industrialization. However, after false-discovery-rate (FDR) correction for multiple testing, no terms associated with genes found in the top 1% of either test remained significant. Nevertheless, and because positive selection does not necessarily entail pathway enrichment, we note that one of the strongest XP-EHH signals (Table S4. Top 20 Most Significant iHS Windows in the All India Results and Table S5. Top 20 Most Significant iHS Windows in the All India Results) is a region in chromosome 20 containing the DOK5 (MIM 608334), a member of the insulin signaling pathway.  A three SNP haplotype in this gene has been associated with increased risk of obesity and type 2 diabetes in a large homogeneous north Indian sample,  although this association has yet to be replicated in another cohort. The gene is the seventh strongest signal in the countrywide results (empirical p = 0.0007), and the seventh and 16th most significant signal in south and north Indian, respectively. Notably, the window is also present in the top 5% results in Europe and East Asia, but nowhere else is evidence for positive selection for this gene nearly as powerful as it is in the Indian subcontinent. Also strongly outlying (XP-EHH empirical p = 0.0015) is CLOCK (MIM 601851), a key regulator of circadian rhythms in humans, which shows strong evidence of selection in all populations, although principally in West Eurasia—it is also within the top 20 European windows but only at the tail end of the top 5% in East Asia. Its disruption has been shown to associate with the development of type 2 diabetes  and the etiology of metabolic syndrome (MIM 605552) as well as with general energy intake in overweight subjects.  Other genes in the window are TMEM165, a transmembrane protein of no known function and SRD5A3 (MIM 611715), a steroid reductase implicated in androgen signaling in some types of prostate cancer. Finally, an interesting candidate for selection according to both XP-EHH and iHS results is MSTN (MIM 601788), a negative regulator of skeletal muscle tissue development expressed in utero and also associated with body fat accumulation and expressed throughout gestation in the human placenta, where it plays a role in glucose uptake.The gene shares a window with an uncharacterized reading frame, C2orf88, and HIBCH (MIM 610690), a component in the propionate catabolism pathway; the window is associated with extremely significant empirical p values in both iHS and XP-EHH scans. MSTN has been identified as a target of strong positive selection twice already on the basis of an excess of derived alleles that indicate the action of positive diversifying selection, especially in African individuals,  although neither of the implicated SNPs are included in our data, rendering successful reconstruction of the haplotypes presented by Saunders in our data impossible without additional genotyping. Nonetheless, FST at the genomic window associated with MSTN is high when compared to genomic averages between Indians and Europeans, and between Indians and African farmers, although low between Indians and East Asians.


Relative to East and West Eurasia, the populations of the Indian subcontinent have been underrepresented in genome-wide data sets that have been compiled in attempts to address global patterns of variation at common SNPs. In this study we have asked how representative of South Asian genetic variation are the available and widely used data sets including populations of Pakistan from the HGDP and Gujaratis from HapMap Phase 3 data. While combining the new data we generated for north and south Indian populations with these public resources, we confirmed the existence of a general principal component cline stretching from Europe to south India. Pakistani populations are in the middle of this cline (Figure 1) and show similar FST distances both to populations of Europe and to those of south India, suggesting that they might represent only a fraction of genetic variation in South Asia just as they represent only a fraction of genetic variation in Europe. Additionally, the relatively low genetic diversity among Pakistani populations (average pairwise FST 0.0056, although this measure excludes the Hazara, who show substantial admixture with Central Asian populations; see Figure 2) is less than one third of the diversity observed among all South Asian populations (0.0184), even when excluding the most divergent Austroasiatic and Tibeto-Burman speaking groups of east India. Although the Pakistani and Indian populations have largely nonoverlapping distributions on our PC plot (Figure 2), the HapMap Gujaratis show genetic distances to other global populations, similar to those estimated for other populations of India and appear on the Indian cline between Pakistanis and south Indians, thus being better representatives of the genetic diversity of South Asia than Pakistanis. However, although the geographic representation of Indian populations on our PC plot is neither comprehensive nor balanced, we note that on average the Gujarati samples position 0.78 standard deviations from the location of the Indian mean (excluding the outlying Austroasiatic and Tibeto-Burman speakers). This is about five times more than the mean value from samples from Uttar Pradesh, for example, which appear very close to our all-Indian mean. For comparison, on average the Pakistani and Tamil Nadu samples are located 3.06 and 0.95 standard deviations away from the Indian mean, respectively.
Notably, all South Asian populations, except for Indian Tibeto-Burman speakers, show lower FST distances to Europe than to East Asia (Figure 1). This could be either because of Indian populations sharing a common ancestry with West Eurasian populations because of recent gene flow or because East Asian populations have relatively high pairwise FST with other non-African populations, probably because of their history of genetic bottlenecks.Similarly, the clines we detect between India and Europe (e.g., PC1 and PC2 in Figure 2 and Figure S2) might not necessarily reflect one major episode of gene flow but be rather a reflection of complex demographic processes involving drift and isolation by distance. Nevertheless, the correlation of PC1 with longitude within India might be interpreted as a signal of moderate introgression of West Eurasian genes into western India, which is consistent with previous studies on uniparental and autosomal markers. Overall, the contrasting spread patterns of PC2 and PC4, and of k5 and k6 in the ADMIXTURE analysis , could be seen as consistent with the recently advocated model where admixture between two inferred ancestral gene pools (ancestral northern Indians [ANI] and ancestral southern Indians [ASI]) gave rise to the extant South Asian populace. The geographic spread of the Indian-specific PC2 (or k6) could at least partly correspond to the genetic signal from the ASI and PC4 (or k5), distributed across the Indus Valley, Central Asia, and the Caucasus, might represent the genetic vestige of the ANI ). However, within India the geographic cline (the distance from Baluchistan) of the Indus/Caucasus signal (PC4 or k5) is very weak, which is unexpected under the ASI-ANI model, according to which the ANI contribution should decrease as one moves to the south of the subcontinent. This can be interpreted as prehistorical migratory complexity within India that has perturbed the geographic signal of admixture.
Overall, the locations of the Indian populations on the PC1/PC2 plotreflect the correlated interplay of geography and language. In concordance with the geographic spread of the respective language groups, the Indian Indo-European- and Dravidic-speaking populations are placed on a north to south cline. The Indian Austroasiatic-speaking populations are, in turn, in agreement with their suggested origin in Southeast Asia drawn away from their Indo-European speaking neighbors toward East Asian populations. In this respect, it is interesting to note that, although represented by only one sample each, the positions of Indo-European-speaking Bhunjia and Dhurwa amidst the Austroasiatic speakers probably corroborates the proposed language change for these populations.
In structure-like analyses, membership in multiple ancestry components can be interpreted as admixture, shared ancestry, or even unresolved ancestry. However, some heuristic interpretations of the ancestry proportions palette in terms of past migrations seem too obvious to be ignored. For example, it was first suggested by the German orientalist Max Müller that ca. 3,500 years ago a dramatic migration of Indo-European speakers from Central Asia (the putative Indo Aryan migration) played a key role in shaping contemporary South Asian populations and was responsible for the introduction of the Indo-European language family and the caste system in India. A few studies on mtDNA and Y-chromosome variation have interpreted their results in favor of the hypothesis, whereas others have found no genetic evidence to support it.However, any nonmarginal migration from Central Asia to South Asia should have also introduced readily apparent signals of East Asian ancestry into India . Because this ancestry component is absent from the region, we have to conclude that if such a dispersal event nevertheless took place, it occurred before the East Asian ancestry component reached Central Asia. The demographic history of Central Asia is, however, complex, and although it has been shown that demic diffusion coupled with influx of Turkic speakers during historical times has shaped the genetic makeup of Uzbeks (see also the double share of k7 yellow component in Uzbeks as compared to Turkmens and Tajiks , it is not clear what was the extent of East Asian ancestry in Central Asian populations prior to these events. Another example of an heuristic interpretation appears when we look at the two blue ancestry components  that explain most of the genetic diversity observed in West Eurasian populations (at K = 8), we see that only the k4 dark blue component is present in India and northern Pakistani populations, whereas, in contrast, the k3 light blue component dominates in southern Pakistan and Iran. This patterning suggests additional complexity of gene flow between geographically adjacent populations because it would be difficult to explain the western ancestry component in Indian populations by simple and recent admixture from the Middle East.
Several aspects of the nature of continuity and discontinuity of the genetic landscape of South Asia and West Eurasia still elude our understanding. Whereas the maternal gene pool of South Asia is dominated by autochthonous lineages, Y chromosome variants of the R1a clade are spread from India (ca 50%) to eastern Europe and their precise origin in space or time is still not well understood.In our analysis we find genetic ancestry signals in the autosomal genes with somewhat similar spread patterns. Both PC2 and k5 light green at K = 8 extend from South Asia to Central Asia and the Caucasus (but not into eastern Europe). In an attempt to explore diversity gradients within this signal, we investigated the haplotypic diversity associated with the ancestry components revealed by ADMIXTURE. Our simulations show that one can detect differences in haplotype diversity for a migration event that occurred 500 generations ago, but chances to distinguish signals for older events will apparently decrease with increasing age because of recombination. In terms of human population history, our oldest simulated migration event occurred roughly 12,500 years ago and predates or coincides with the initial Neolithic expansion in the Near East. Knowing whether signals associated with the initial peopling of Eurasia fall within our detection limits requires additional extensive simulations, but our current results indicate that the often debated episode of South Asian prehistory, the putative Indo-Aryan migration 3,500 years ago (see e.g., Abdulla) falls well within the limits of our haplotype-based approach. We found no regional diversity differences associated with k5 at K = 8. Thus, regardless of where this component was from (the Caucasus, Near East, Indus Valley, or Central Asia), its spread to other regions must have occurred well before our detection limits at 12,500 years. Accordingly, the introduction of k5 to South Asia cannot be explained by recent gene flow, such as the hypothetical Indo-Aryan migration. The admixture of the k5 and k6 components within India, however, could have happened more recently—our haplotype diversity estimates are not informative about the timing of local admixture.
Both k5 and k6 ancestry components that dominate genetic variation in South Asia at K = 8 demonstrate much greater haplotype diversity than those that predominate in West Eurasia. This pattern is indicative of a more ancient demographic history and/or a higher long-term effective population size underlying South Asian genome variation compared to that of West Eurasia. Given the close genetic relationships between South Asian and West Eurasian populations, as evidenced by both shared ancestry and shared selection signals, this raises the question of whether such a relationship can be explained by a deep common evolutionary history or secondary contacts between two distinct populations. Namely, did genetic variation in West Eurasia and South Asia accumulate separately after the out-of-Africa migration; do the observed instances of shared ancestry component and selection signals reflect secondary gene flow between two regions, or do the populations living in these two regions have a common population history, in which case it is likely that West Eurasian diversity is derived from the more diverse South Asian gene pool.
Similar to observed patterns of neutral genetic diversity, one could ask whether Indian populations contain a reservoir of selective signals hitherto unidentified in other Old World groups, akin to what has been found in uniparentally inherited markers, or whether the region fits into the Eurasian landscape of positive selection signals.At the global level, our haplotype-based scans of positive selection showed similar patterns of signal sharing to those revealed by FST comparisons, and Indian as well as Pakistani populations share more signals with West Eurasia than with the rest of the world. In fact, barring the actual numbers on them,  and  bear a striking similarity to each other. Despite this, the results leave ample room for the existence of local adaptation to the Indian environment, both recent and old. XP-EHH, by its nature, detects older or stronger sweeps acting on alleles that have reached high frequency in a given population. Previous studieshave shown that the vast majority of XP-EHH signals are shared across extended geographic distances. Compared to Pakistani populations (87%), both north (66%) and south Indian (52%) populations share substantially less signals of complete selective sweep with European populations Sharing of the complete sweep signals between India and East Asia is even lower (53%). In the case of iHS, Indian signals sharing with Europe and East Asia was less pronounced (37% and 32%, respectively), probably stemming from the nature of iHS, as it detects younger, on-going sweeps and is therefore more likely to highlight recent, private signals of local adaptation that have not yet become widespread by gene flow.
Our analysis of the genes contained within the top 1% of selective signals in the countrywide data suggested that 25 GO terms were overrepresented among our strongest selection candidates, although none were significant after Benjamini correction. We also tested the top 5% of results in the Indian data and found that five GO terms related to cell-cell binding and metal ion binding remained highly significant after multiple testing corrections (data not shown). However, examination of the genes associated with these terms revealed that all significant results could be ascribed to positional gene clustering, whereby multiple genes associated with the same GO term, generally members of a single gene family, fell within the same 200 kb window but were treated as independent findings by the gene set enrichment analysis tool we used. It is worth recalling that gene-enrichment tools were originally devised for the assessment of gene expression changes in microarray RNA work, where individual genes could be unequivocally identified. Given the degree of resolution provided by the data sets that we have used here, any attempts to use automated annotation tools to understand signals of positive selection extending over multiple genes is fraught with interpretative perils. Alternatives include the precise CMS test that often is applicable on dense HapMap2 dataor a windowing approach, whereby ontological associations are mapped not to individual genes, but rather to the windows they occupy. The latter approach could successfully correct for the clustering effect we identify and more generally for the effect of gene size on enrichment results, whereby long genes are more likely to be statistical outliers simply because they contain more SNPs than short genes, and GO categories associated with long genes are therefore more likely to appear enriched. We believe that collapsing annotations to the window level could reduce the false-positive rate in enrichment scans, although at the same time it would be far more conservative and risk obscuring genuine signals. In our data, for example, none of the five significant GO terms at the genic level are significant when examined at the windowed level (data not shown).
In the wake of these results, we chose to examine the contents of the 20 strongest iHS and XP-EHH signals, which can be expected to contain candidates for adaptation via classical sweeps. Within these regions we find four genes—DOK5, MSTN, CLOCK, and PPARA—implicated in lipid metabolism and etiology of type 2 diabetes, although one of them, PPARA, is in a window that contains seven other genes. Variation in DOK5 and CLOCK has been previously associated with type 2 diabetes and metabolic disorders, whereas MSTN is not an obvious candidate for involvement in disease etiology because its main function is negative regulation of muscle development in utero; it also plays a significant role in glucose uptake. Interestingly, Indian newborns weigh on average 700 g less than their European counterparts yet have a similar absolute fat mass. At birth, these children are already adipose and exhibit some degree of insulin resistance when compared to European babies; this difference persists into adulthood, such that the average age of diagnosis of diabetes in India is 10 years lower than in Europe.
It bears recalling that India has one of the world's fastest growing, and soon greatest in absolute terms, incidence of type 2 diabetes,as well as a sizeable number of cases of the metabolic syndrome, both of which have been linked to recent rapid urbanization.Phenotypically, even nonobese Asian Indians have been shown to exhibit increased levels of insulin resistance compared to European controls.They also have increased levels of both subcutaneous and visceral adipose tissue at the expense of lean tissue when compared to matched-age and -weight European controlsand show differences in adipocyte morphology.In this context, it is tempting to hypothesize that past natural selection might have influenced genetic variation at these loci to increase infant survival, a change that became disadvantageous after changes in diet and lifestyle. Therefore, the loci we identify could be theoretically considered responsible for some of the present type 2 diabetes epidemic in India, making them worthy candidates for further functional examination. However, because relevant life-history traits, lipid metabolism and type 2 diabetes are all complex traits and the effect of natural selection would be expected to be fragmented across multiple genes andit would be naive to expect that a relationship between past selective processes and present-day disease would be mechanistically simple and explainable by variation at a handful of genetic loci.
Summing up, our results confirm both ancestry and temporal complexity shaping the still on-going process of genetic structuring of South Asian populations. This intricacy cannot be readily explained by the putative recent influx of Indo-Aryans alone but suggests multiple gene flows to the South Asian gene pool, both from the west and east, over a much longer time span. We highlight a few genes as candidates of positive selection in South Asia that could have implications in lipid metabolism and etiology of type 2 diabetes. Further studies on data sets without ascertainment and allele frequency biases such as sequence data will be needed to validate the signals for selection.


We thank A. Migliano, S. Raj, and P. Underhill for discussion; J. Pickrell and J. Barna for help calculating iHS and XP-EHH scores; A. Aasa, I. Hilpus, T. Reisberg, V. Soo, and L. Anton for technical assistance. R.V., M.M., G.C. and C.B.M. thank the European Union European Regional Development Fund through the Centre of Excellence in Genomics to Estonian Biocentre, and University of Tartu. This research was supported by Estonian Basic Research grant SF0270177As08 to R.V. and SF0180026s09 to M.R. and R.M.; Tartu University grant (PBGMR06901) to T.K.; Estonian Science Foundation grants (7858) to E.M. and (8973) to M.M.; Estonian Ministry of Education and Research (0180142s08) and European Commission grant 245536 (OPENGENE) to M.N.; European Commission grant (ECOGENE 205419) to M.M., I.G.R., B.Y., G.H, R.M., and R.V.; and Council of Scientific and Industrial Research, Government of India to L.S. and K.T. Calculations were carried out in the High Performance Computing Center, University of Tartu and with University of Cambridge Bioinformatics and Computational Biology services.

Thursday, June 12, 2014

Vedic Physics of INDIA : The secret underlied

Vedic Physics of INDIA : The secret underlied

ImageI will mention some of the greatest achievements made by Ancient Indian Scholars in the field of Vedic Physics. Also shall be mentioned the translated versions of Nyaya-Vaisesika Darsana (school of logical physics) and related subjects. I would like to thank Indigo_child and Sbergman27 and many other who have motivated me to come up with this article. No starch, pressed and folded:
The Theological school
The entire universe/space is called Prakriti and manifests by a vibration of the Svra, a current of a life force or a super-string called the Parabrahman and the Purush. This in turns causes the subtle elements of the 5 ethers, or strings(the quality of ether is called sound) to vibrate, the distinct vibration causes the Pancha-Mahabhuttas, the five physical elements.
The five main elements occur in the following order of aggregation:
Akasha (Ether) Tejas (energy) Vayu (forces/fields) Pritvhi (Atomic elements) and Apas (fluid)
Except for ether, all of the elements are composed of discreet and distinct indivisible particles called Paramanu(beyond atoms) i.e. light is composed of discreet and distinct particles. Space, soul and time are eternal.
The Rationalist school
The Darsana’s were part of the six rationalist schools of the Vedas, the main schools were Nyaya(logic), Vaiseshika(physics), Yoga(metaphysics) and Sankhya(philosophy): Each school of thought is composed of it’s own Sutras or aphorisms, rules or formulas, that condense volumes of knowledge into a few sentences. They also contain Vriti(commentary), Bhaksha(explanations) by several teachers, making them selfcontained texts on their discipline. Each Darsana also has a Sutrakala, that is the first teacher that systematized the knowledge of the Vedic teachers into sutras.
The geneology of the teachers of the schools are mentioned and can be traced far into vedic times to the Krita Yuga, more than 5000 years ago. The NyayaVaisesika Sutra was founded by Rishi Gautama and Kanada. The Nyaya and Vaisesika schools originally started as separate schools, but then merged into one due to their common rational approach. The Nyaya-Vaiseshika Sutra consists of 373 Sutras and is composed of 12 chapters. It’s main postulates are:
  • All of the universe is composed of the 5 mahabhuttas and the 4 non physicals: that is Fluid, Atomic elements, fields/force, energy, ether and space, time, mind and soul.
  • Except ether, all of the physical elements are made of discreet and distinct paramanus or atoms
  • Space-time is a frame in which the physical universe exists
  • There are seven categories of experience, which are substance, quality, activity, generality, particularity, inherence, and nonexistence.
  • Energy and mass are equivalent.
The Vaiseshika Sutras deal with the investigation, observation and mechanics of the universe and the elements and the theory of space and time. A lot of the modern sciences are covered, including laws of motion, gravitation, thermodynamics, waves, hydrostatics and magnetism among others.
Here are some of the Sutras (The source is from an Indian microbiologist):
  • Force is that which displaces, holds together or moves things apart.V.S 1.1.20
  • In the absence of a force, a particle of matter experiences no change. V.S 1.1.6
  • The forces to be considered are an external force, gravity, that with causes attraction of particles, that which causes repulsion of particles and the internal movements of them in matter.
Thus, vaisheShika aims at understanding a substance in terms of the effect of external forces that act on it including gravity and the internal forces on its particles that cause their attraction, repulsion and vibrations. Then the text makes a rather interesting statement:
  • V.S 1.1.13  Action is opposed by an equivalent opposite reaction
  • V.S 5.1.1618  The diversities of the movement of an arrow are due to the consecutive changes in the components of the acting forces. The stored energy provides the propulsion to the arrow and this causes it move further to a high point. This component keeps reducing while that of gravity increases resulting in its fall.Once the work against gravity ceases then the body reaches an energyless state falling under gravity.
  • V.S 1.1.27 The force on a body is the resultant of gravity and the work done against it.
  • V.S 5.1.13 In the absence of all other forces (saMyogabindings) gravity exists.
  • V.S 5.1.7 The “guna” of forces (direction) prevents a magnitude from being obtained
  • V.S.1.1.20a The nature of physical changes in matter is the terms of work being done on the basic particles that constitute matter.
  • V.S 2.1.14  The particular nature of air is suggested by the mixing of gases that occurs on their collision. Despite of being made of atoms and occupying space air fails show orderly movement so its form cannot be perceived
  • V.S 4.1.8 Solids occupy space and assume form due to conglomeration of the constituent particles.
  • V.S 4.1.6 The (fluid’s) particles possess energy. This causes them to possess the property of fluidity. The heat bearing rays provide the particles with energy to form a gas and rise. The heated particles of air impact the vapor and with this energy it mixes with it. Freezing and melting of a liquid as being a result of heat being taken up or given up by its particles.
  • V.S 5.2.9 Some apparently solid substances like ghee, lac and wax are in reality liquids, as their particles are naturally “heat-conjoined” or disorganized as in water. Other true solid substances such as tin, lead, iron, silver and gold need their atoms to be supplied with external heat to disorder them before they become a fluid.
  • V.S 2.1.67 Any body’s mass needs to be wholly explained in terms of its constituent particles.
  • V.S 1.1.89 A substance can only emerge from another substance and not on its own eventhough its properties change from one to another.
  • V.S 9.1.9 Any fundamental particular entity can be a constituent multiple substances.
  • V.S 1.1.22 Any substance comprising of two or more primary particle types requires a chemical reaction to generate the conjoining and break up of preexisting molecules.
  • V.S 1.1.23 The “molecules” are stated as emerging from combinations between the fundamental entities.
  •  V.S 1.1.25 Forces are necessary to bring about combination and break up of molecules.
  •  V.S 1.1.28 The combinations of particles to produce molecules result in substances with states very different from those of the original particles.
Prashastpada, 5th century commentator on VS mentiond two forms of physical force:
  • Vega (mechanical)
  • sthitisthApakatA (elasticity)
Prashastpada has defined ‘Vega’ in the following ways:
  • It is as a result of mechanical force that action is produced.
  • Vega is proportional to the work produced and works in a given direction.
  • Vega opposes combination of matter and sometimes one Vega produces other Vegas in sequence.
The inference of the above definition is as follows:
  • Vega (mechanical force) is a special cause for action.
  • Vega is proportional to the action produced and works in a given direction.
  • Vega is opposed by an equivalent opposite reaction
Kanadas laws:
  • In the production or increment of karma (i.e. motion), the root cause is force. In other words, there is incremental or decremental change in motion.
  • This law is a law of the measure of force. According to this, so long mechanical force works, there is change in motion i.e. there is momentum. To find its value, it is calculated how much work it produces in a unit time.
Mathematically, the rate of change in momentum i.e. the increment in work in unit time is proportional to the force in action. Also, this change is in the direction of the force. Suppose that the mass of an object is ‘m’ and in time interval ‘t’, the velocity of the object changes from ‘u’ to ‘v’ due to the force acting on it. Then,
Initial momentum = mu
Final momentum = mv
Change in momentum = m(vu)
Therefore, the rate of change of momentum = m(vu)/
t = ma (from Kanada’s first law)
From Kandas second law,
force is proportional to the rate of change of momentum.
Or, p k ma
Or, p = kma (where k is a constant)
If m=1 and a=1, then
1 = k*1*1 or k = 1
Or, p = ma
Therefore, unit force is the one that produces unit acceleration in an object of unit mass. The VS then goes to say that force is a result of work and is not a physical quantity which is superior to Newtons law that measures it as a physical quantity.
The sutras on energy:
Vaiseshika defines energy as being a radiant thing(i.e. energy is radiation) and energy is related to
temperature and motion of a particle.
Prashatpad has discussed four kinds of energy: terrestrial, celestial, abdominal and Akaraj. These are
defined according to their source:
  • Terrestrial: When fuels are burnt “with a flame” such as wood or coal
  • Celestial: The energy produced by the sun and in electricity
  • Abdominal: The cause of the process of digestion or subphysical.
  • Akaraj: Paraphysical, metals like gold and platinum have this kind of energy.
There are material obstructions of two kinds:
  • That which absorbs energy.
  • That which refracts energy(the knowledge of refraction of energy is corroborated by the study of spectroscopy(Anshubodhini).
  • That unseen cause of the motion of an iron rod towards a magnet and the effects of electricity are different kinds of energies.
Sound(waves) is also an energy and there are many forms of sound:
  • Sound that is in matter.
  • Sound aspect of matter.
If would seem from the above, that not only are sound, light, heat, electricity and magnetism seen to the same, but particle-wave duality is also understood and the refraction of energy and matter. I wonder what kind of “para-physical” energy is in gold and platinum? Anyone got an idea?
The Physics of light
The first physics of light in the modern world was proposed by Sir Isac Newton, that demonstrated that light can be split by a prism into it’s component rays/colors, however he believed light to be of infinite speed. His physics of light was rejected by mainstream science at the time. However, in Vedic India, the physics of light was understood and accepted. We also know that they had calculated the speed of light. As we have demonstrated in the previous post, the Vedic Indians understood the process of refraction and absorbtion of energy by “material obstructions” and they understood heat, eletricity and magnetism to be forms of energy. It is already understood by the elemental theory that light is also an energy and is composed of discreet units. This was of course was not understood in modern times till Max Plank and Einstein in the 20th cetury devised quantum theory after the study of black body radiation and the photoelectric effect.
Proof of the understanding of the physics and properties of light from various schools of Vedas:
The Mimamsa school:
  • A flame is considered to comprise of light particles in constant motion and forming a radiation diffusing away from the wick. The field of vision of an eye extends out to in increasing circles and ends at the object. Cakrapani however felt that light rays move out in all directions much as sound waves do, the difference being that light travels faster.
The school of Ayurveda(medicine):
  • Light arriving at the retina serves both to illuminate the world world and thus become the faculty of vision. Varahamihira, the reflection of light is caused by light particles arriving on an object and then backscattering (kiranavighattana, murcchana). Vatsyayana refers to this phenomenon as rasmiparavartana and this explains the casting of shadows and opacity. Vacaspati interpreted light as composed of minute particles emitted by substances and striking the eyes. Refraction is caused by the ability of light to penetrate inter-atomic spaces of translucent or transparent materials. Uddyotakara drew a comparison with fluids moving through porous objects (tatra-parispandah tiryaggamanam parisravah pata iti).
  • Color recognition was understood by the Nyaya-Vaisesikas as being caused by the nature of human eyes.
  • The Eyes: were made up chiefly by unseen tejas particles(I suppose this refers to eye pigments). We already know they knew all the colors of visible light and their order in the electromagnetic spectrum, from the metaphysical charka system, of 7 main energy vorticies in the body from the base of the spine to the top of the head, each vibrating at a certain frequency and having a certain color. They are as follows: red, orange, yellow, green, blue, indigo, violet. This is also taught by Rama’s acharya(teacher) in the Ramayana when he is in school. This knowledge can also be found in the Vedas (it should not be surprising, as the schools are based on the Vedas):                                                                                                                                                                                                                                                   “Seven horses draw the chariot of the sun, tied by snakes” .Rg Veda 5. 45. 9                                                                                                                                                    The above poetic verse is extremely interesting, because not only does “horse” mean rays of light in this context, but the motion of a snake is curved, and it would therefore imply they knew light did not travel in straight lines, but in a curved path, which is a predicate of relativity that space-time is curved. This can be further corroborated by a verse in the Athara Veda, that says: there are seven types of sun’s rays” sapta surayasya rasmayah. “abilities to reflect and refract it, it would seem logical therefore that some kind of lens devices would have.
This a very modern scientific understanding of light. As, they understood light so well, as well as been devised, such as telescopes. It would certainly explain some of the astronomical data recorded in the Vedas. However, we will see later, that the understanding was so advanced that they could do light spectroscopy, which is part of the Amsu Bodhini by Maharishi Bhadarwaja(who also wrote the Vyaamnaika Shastra) and such a device has in fact been designed and tested by Indian scientists from directions in it.
The secrets of alchemy:
As has been discussed already in other threads, the knowledge of the atomic numbers  of elements is implied in the verse in Srimad Bhagvatam, where it said that bells metal is transmuted into gold through an alchemical process and bells metal is an alloy of copper and tin(Cu29 + Sn50 = Au79). As we know the science of alchemy originates in India, there is also some indications of alchemy in Egypt. In the above, we saw from the Vaiseseshika Sutras that certain metals are specified that are said to have a para-physical energy called Akaraj, and it mentions gold and platinum. We also know that Mercury had a very important role in vedic alchemy and is used in many devices, such as the mercury vortex ion engine.
There is something very astonishing about these metals: They belong to a rare group of metals called ORMES (Orbitally Rearranged Mono-atomic elements) that have only been recently discovered by high energy physicists and possess para-physical qualities:
The ORMES or m-state materials are thought to be the precious metal elements in a different atomic state. The following elements have been identified in this different state of matter:
Known ORMES Elements:
Element-Atomic Number
Cobalt 27
Nickel 28
Copper 29
Ruthenium 44
Rhodium 45
Palladium 46
Silver 47
Osmium 76
Iridium 77
Platinum 78
Gold 79
Mercury 80
These m-state elements have been observed to exhibit superconductivity, superfluidity, Josephson
tunneling and magnetic levitation. These m-state elements are also present in many biological systems. They may enhance energy flow in the microtubules inside every living cell. We are beginning to see now that the physics of Vedic times is extremely advanced and we also have proof of it. We may learn something new about physics yet.
Wave Mechanics:
Most of the modern physics of the nature of waves was discovered in the 17th century and the late 16th century. Galileo was the first to study the nature of sound and waves and later his contemporaries advanced it further. However, as we have seen from the mounting evidence, physics in vedic times was more advanced, so not surprisingly the physics of waves was also understood and to an astonishing level(can you expect less from a culture that says everything is vibrations) In fact we’ve seen it was also understood that particles have a wave nature. As with all vedic physics, this is all united into a metaphysical concept of soul and mind. Remember, in vedic physics the observer is united with the universe. There exists no duality and separation in the vedic model of the universe, it is only part of an illusion of the mind, and it called “maya” thus modern quantum mechanics is closer to the vedic model than the mechanistic wave or particle model is.
According to VS, there are two types of sound:
  • Musical sound
  • Vocal sound
The cause of sound is due to the result of oscillation of particles in the air causing by the sound wave and the particles working concurrently. The Mimamsaka school held that sound itself and its travel was the result of the condensation and rarefaction of air molecules. The intensity and timbre of sound was seen as varied and a consequence of the varying kampasantanasamskara (vibrations) of air molecules.
Sound are defined as waves and and there are two modes of waves according to the VS:
  • Traverse
  • Longitudanal
This is explained in ancient Indian literature on music. Musical pitches(sruti) are caused by momentum and frequency of vibrations. A svara, or tone(note, god is also called a svara in the Shiva Purnana) is said to consist of a sruiti(fundamental tone) and anuranana(harmonics) Note, while it defines anuranana as harmonics, the root anu means particles, however as this is defined as a wave and it is already understood that particle and waves dual, therefore it could also mean harmonics of wavicles.
The relationship between svara and sruti, that is momentum and frequency of vibrations and tone, can be understood as parinama(nodal change), vyanjana(manifestation) jativyaktyoriva tadatmyam (genus and species), vivartana(reflection) and karyakaranabhava(cause and effect). An example is given of a wave on the surface of water. When a disturbance is created(dropping a pebble for instance) it creates a wave, which creates another equal wave with the same motion and this creates another equal and this progression continues towards the end. This is very similar to Huygens Principle, which says that each point on a wave front are independent sources, which produce more wave fronts, called wavelets at the same velocity as the propagation wave.
According to VS, sound is the highest quality of the fourth state of matter(ether or akasha) The ether itself has 5 states. It would appear it is referring to the state of plasma. As it explains the first state of ether arises due to high vibrations of sound. It says that matter has a sound aspect, and when a vibration is caused it generates an acoustical wave which travels through the air working with it concurrently and resulting in oscillations of paticles in the air and this causes the intermolecular space of the air to rise in vibrations and causes the atoms to eventually work into the first state of the ether.
As we’ve learnt from the VS earlier the state of solids, liquids and gas were understood in terms of the kinetic energy i.e. vibrations. When a particle is supplied energy from the “heat bearing rays” it disorders and posses the quality of fluidity(kinetic energy) which then rises into a vapor and joins with gasses in the air and it says the first ether is then produced from further vibrations of air, which can only be caused by providing even more energy, therefore the ether is indeed plasma. Plasma IS produced by heating gas to the point where it starts to release electrons and become ionized; i.e. charged gas is plasma. I think this is interesting, because for the first time a clear link between plasma and the metaphysical ether has been made. Thus we learn from the VS, that beyond plasma there are four other states. The key is vibration in creating those. However, if we continue to increase the vibration of the frequency in this matter indefinitely, eventually it will cause space itself by causing the fabric of space-time to rupture! Now, that is very interesting because space and time are indeed mentioned as the nonphysical elements in the VS. And, please do excuse me for my excitement, it EXPLAINS the physics of the quantum vacuum.
Why does emptiness have such an amazing potential of energy? Because, to create space we need an amazing amount of energy, and therefore the viritual quanta that fluctuate in and out of existence, are actually nothing more than particles vibrating at an amazing rate. This ultimately brings us to the Vedic concept of the entire universe being the vibration of the life force. The physics in the Vedas is truly astonishing. And it is no wonder why so many quantum physicists, such as Bell, Bohr, Heisenberg, Schrodinger, Einstein adored it so much. As Einstein said
“when referring to how god created the universe in Bhagvad Gita everything else seemed superfluous.”
There are many famous people, writers and Nobel laureates that hold Vedic literature in high esteem. For example Nicola Tesla: he is undoubtedly one of the greatest physicists and inventors to have lived. Yet, little is known that Nicola Tesla was very strongly influenced by the vedic literature and actually used Sanskrit terminology in one of his unpublished articles. It is very likely his theory of free energy and wireless transmission of electricity was influenced by the vedic teachings:
“There manifests itself in the fully developed being , Man, a desire mysterious, inscrutable and irresistible: to imitate nature, to create, to work himself the wonders he perceives…”
Long ago he recognized that all perceptible matter comes from a primary substance, or tenuity beyond conception, filling all space, the Akasha or luminiferous ether, which is acted upon by the life giving Prana or creative force, calling into existence, in never ending cycles all things and phenomena. The primary substance, thrown into infinitesimal whirls of prodigious velocity, becomes gross matter; the force subsiding, the motion ceases and matter disappears, reverting to the primary substance.” According to Leland Anderson the article was written May 13th, 1907. Anderson also suggested that it was through association with Swami Vivekananda that Tesla may have come into contact with Sanskrit terminology and that John Dobson of the San Francisco Sidewalk Astronomers Association had researched that association. It is also interesting to note that Tesla tried to show that matter is just potential energy after a discourse with Swami Vivekanada:
Vivekananda met with many of the well known scientists of the time including Lord Kelvin and Nikola Tesla. According to Swami Nikhilananda: Nikola Tesla, the great scientist who specialized in the field of electricity, was much impressed to hear from the Swami his explanation of the Samkhya cosmogony and the theory of cycles given by the Hindus. He was particularly struck by the resemblance between the Samkhya theory of matter and energy and that of modern physics. The Swami also met in New York Sir William Thompson, afterwards Lord Kelvin, and Professor Helmholtz, two leading representatives of western science. Sarah Bernhardt, the famous French actress had an interview with the Swami and greatly admired his teachings.
In a letter to a friend, dated February 13th, 1896, Swami Vivekananda noted the following:
…Mr. Tesla was charmed to hear about the Vedantic Prana and Akasha and the Kalpas, which according to him are the only theories modern science can entertain…..Mr Tesla thinks he can demonstrate that mathematically that force and matter are reducible to potential energy. I am to go see him next week to get this mathematical demonstration. [10]

Swami Vivekananda was hopeful that Tesla would be able to show that what we call matter is simply potential energy because that would reconcile the teachings of the Vedas with modern science. The Swami realized that “In that case, the Vedantic cosmology [would] be placed on the surest of foundations”. The harmony between Vedantic theories and and western science was explained by the following diagram:
                   BRAHMAN          =          THE ABSOLUTE
                      |                              |
                      |                              |
                      |                              |
                 +---------+                    +---------+     
               PRANA and AKASHA     =        ENERGY and MATTER
It is not exactly known just how influenced Einstein was by the vedic literature. But, it is known that Einstein had actually been exposed to the Bhagvad Gita and held it in very high esteem. Remember, the relation between energy, mass and frequency and the relativity of time(we will cover this later) was already understood in the vedic literature and the speed of light was calculated and first mentioned in the 10th century by Sayana. Just before, Nicola Tesla was trying to relate energy and mass. So, Einstein could have indeed learnt it from the Vedas.
Erwin Schrodinger, famous for the physics paradox “schrodinger’s cat” and his works on wave theory of matter, the co-founder of quanum theory for which he was awarded the nobel prize for physics was obsessed with the Vedas. In fact he said in his autobiographical essay he explains that his discovery of quantum mechanics was an attempt to give form to central ideas of Vedanta which, in this indirect sense, has played a role in the birth of the subject. In 1925, before proposing theory was complete,
Erwin Schrodinger wrote:
“This life of yours which you are living is not merely apiece of this entire existence, but in a certain sense the whole; only this whole is not so constituted that it can be surveyed in one single glance. This, as we know, is what the Brahmins express in that sacred, mystic formula which is yet really so simple and so clear: [tat tvam asi], this is you.”
Even the famous Schrodinger cat’s paradox was an old Sankhya Vedic paradox that Schrodinger explains in his 1925 essay. In the 5th century a debate was held between the Hindus and Buddhists as to the nature of the universe flux, they said this:
“Buddists: The phenomena consist of an infinity of discrete moments following one another almost without intervals…. There is no matter at all, flashes of energy follow one another and produce the illusion of stabilized phenomena. The universe is a staccato movement.”
“Hindus: The phenomena are nothing but waves or fluctuations standing out upon the background of an eternal, all pervading undifferentiated Matter with which they are identical. The universe represents a legato movement.”
In 1925 Schrõdinger resolved that paradox the way the Vedantists did: he asserted that all consciousness is one. As he wrote:
“But it is quite easy to express the solution in words, thus: the plurality [of viewpoints] that we perceive is only an appearance; it is not real. Vedantic philosophy, in which this is a fundamental dogma, has sought to clarify it by a number of analogies, one of the most attractive being the many faceted crystal which, while showing hundreds of little pictures of what is in reality a single existent object, does not really multiply the object.”
Here is another quote from his essay:
“… you may suddenly come to see, in a flash, the profound rightness of the basic conviction of Vedanta:
… knowledge, feeling and choice are essentially eternal and unchangeable and numerically one in all men, nay in all sensitive beings.”
According to his biographer Walter Moore, there is a clear continuity between Schrodinger’s understanding of Vedanta and his research:
Schrodinger became a Vedantist, a Hindu, as a result of his studies in his search for the truth. Schrodinger kept a copy of the Hindu scriptures at his bedside. He read books on Vedas, yoga, and Sankhya philosophy and he reworked them into his own words, and ultimately came to believe them. The Upanishads and the Bhagavadgita were his favorite scriptures.
According to his biographer Moore, “His system or that of the Upanishads is delightful and consistent: the self and the world are one and they are all. In a famous essay on determinism and free will, he expressed very clearly the sense that consciousness is a unity, arguing that this “insight is not new… From the early great Upanishads the recognition [Atman = Brahman] (the personal self equals the omnipresent, all comprehending eternal self) was in Indian thought considered, far from being blasphemous, to represent the quintessence of deepest insight into the happenings of the world. The striving of all the scholars of Vedanta was, after having learnt to pronounce with their lips, really to assimilate in their minds this grandest of all thoughts.”
He considered the idea of pluralization of consciousness and the notion of many souls to be naive. He considered the notion of plurality to be a result of deception ([maya]):
“the same illusion is produced by a gallery of mirrors, and in the same way Gaurisankar and Mt. Everest turned out to be the same peak seen from different valleys.”
Schrodinger wrote a philosophical book later on called,’What is Life?’ which also used Vedic ideas. The co-discoverer of the DNA code was very inspired by Schrodinger’s book.
David Bohm: Bohm’s contributed on the work on the Manhattan project to devise the nuclear bomb. He contributed a lot of quantum mechanics and relativity theory, discovering the electron phenomena of the Bohm-diffusion. He also became very fascinated with the Vedas and was astounded to as how well his theories on quantum mechanics were consistent with the vedic views. Here is a transcript of a conversation between Bohm and Weber:
Bohm: Well, they say three persons, the Trinity, which are one. Anyway, it is something like a human being, or rather the other way around; that man is the image of God. That implies that there is a total significance. If you say Atman, in Hinduism, something similar is implied.
Weber: Atman and Brahman, seen as identical; the micro and the macrocosm.
Bohm: Yes, and Atman is from the side of meaning. You would say Atman is more like the meaning. But then what is meant would be Brahman, I suppose; the identity of consciousness and cosmos.
Weber: Looked at from the so called subjective side it would be Atman. And what is meant is the objective: meaning in this sense that somasignificant and signasomatic unite the two sides. This claims that the meaning and what is meant are ultimately one, which is the phrase ‘Atman equals Brahman’ of classical Hindu philosophy.
Weber: It’s an identity thesis claim. To relate this again to what some of the great philosophers of the past have said: soma-significant and signa-somatic aren’t they your way of working out your own creative concepts for what Spinioza meant by mind and body, and what Hegel meant by subject and substance?
Bohm: Yes, this is a way of understanding how these are related, extending the understanding, or extending the meaning.
Weber: It has plagued philosophers through the ages that there are these two ways of apprehending reality. You are proposing that signa [mind] and somatic [body] are somehow the very fabric of everything in the universe and that this gets expressed in appropriate ways at different levels of organization.

Bohm: Yes [meaning is relevance in a knowledge unit for producing the change that results in the emergence of the prime attribute, and the larger context in which it causes change]. and the bridge is the energy that creates the soma and regulates it and so on.
Weber: Let’s pursue this idea of the bridge of energy.
Bohm: The energy which is informed with meaning [potential relevance in this circumstance].
Weber: Could one put into words the idea of a meaning or a purpose for all this? You once suggested greater clarity of the universe about itself.
Bohm: That could be part of its end. Maybe an end of greater order, greater clarity, an end to create something.
Weber: So that meaning and being become transparently clear to the organism at all levels of itself?
Bohm: That would be part of the end. I don’t know how to put the end yet. The end could be said to be love, it could be said to be order, harmony, but the end could also be said to be the process itself.

Weber: Spinoza would have liked that. He said that the universe doesn’t have to have a reason, it is, and that’s enough. Although you start out from physics, your view seems to be similar to that.
Bohm: Yes, because it’s not to say that it has meaning, but that it is its meaning. We are trying to be more clear as to what this meaning is, because then it will have changed our being. [Since this meaning is the only one we have, it is good. Living in harmony with it is good. Living in disharmony with it is evil. [72798jb]
Weber: You are a physicist, yet so much of this sounds like what a mystic would say: that in the mystical experience there simply is profound and selfevident meaning, without utilitarian overtones. Isn’t that what you are saying?
Bohm: Yes,. utility is only a small part of meaning. Utility is a meaning, but its a rather restricted
meaning. The question is: Useful for what? It always occurs in some context without
the context we cannot discuss utility.
Weber: So concerning the question raised earlier, ‘Do we discover or do we create meaning?’ it is as if in discovering it we create it or create it in us.
Bohm: Not only that, but we enrich it; we create something which has not been there [but had the
potential to be there, if organized properly].
Weber: We add to it.
Bohm: Yes, we are part of it and it is part of us.

Weber: Since any meaning we grasp in it changes its being, this makes us partners in the evolution of the universe.

Bohm: Yes, that’s the proposal… p. 449.

Weber: Well what does all this imply for the human world? Looking at the universe in this way changes our lives in what way?

Bohm: It’s hard to say at first, but it will clearly imply something very different, a different attitude in the sense that we won’t give that much primary weight to the external and the mechanistic side the side of fragmentation and partiality [Slobadan Milosovich, us against them at all costs. They do not matter, because we are different from them and distant from them with no interaction with them determinism (separate and independent, fractured mentally (not integrated) and fractured socially (projecting out major parts of ourselves on to the "enemy"]. Also it encourages us much more toward a creative attitude, and fundamentally it opens the way to the transformation of the human being because a change of meaning is a change of being. At present we say because of the confused fragmentary meanings we have confused fragmentary being, both individually and socially. Therefore this opens the way to a whole being, in society and in the individual.

Weber: To relate it to human psychology and transformation, the key seems to be the Socratic maxim ‘Know yourself,’ go inward, and also ‘Observe’.
Bohm: And also outward. The outward and the inward are one part of one total meaning.
Robert Oppenhemier was a very famous nuclear physicist and also called the father of the nuclear bomb, he made many contributions to quantum mechanics and later his work lead to the quantum tunneling effect. He was also smitten by Vedic literature and used a passage from the Bhagvad Gita to describe the first nuclear bomb explosion. He even alluded to the belief that the the nuclear bomb is not the first in human history. Here are some of the things he said and wrote:
“Access to the Vedas is the greatest privilege this century may claim over all previous centuries.”
The general notions about human understanding… which are illustrated by discoveries in atomic physics are not in the nature of things wholly unfamiliar, wholly unheard of or new. Even in our own culture they have a history, and in Buddhist and Hindu thought a more considerable and central place. What we shall find [in modern physics] is an exemplification, an encouragement, and a refinement of old wisdom.”
He was asked by Christian Century magazine to list 10 books that have shaped his life and philosophy of the world. Two of those he mentioned were vedic texts and a third by T.S elliot(who was also a veda lover) which alluded to a lot of vedic literature. We therefore learn that a lot of modern quantum physics is based on the Vedas and many scientists and physicists appreciate them. Yet, it is not surprising, because the Vedas indeed are the fountain head of knowledge and we are seeing in this thread just how advanced Vedic physics is and hence why so many scientists resonate with them.
Space and time
The nature of space and time:
The science of space, time are amongst the highest science of the Vedas, and indeed space, time and consciousness, also called metaphysics, is what modern scientists are grappling with today. This is 21st century science and the ball was set into motion by Einstein’s theory of relativity. Relativites main postulates are that space and time are relative to the observer and energy and mass are equivalent and most cutting edge quantum physics has devised the model of observer dependent spacetime.
Slowly, we are coming towards the vedic model of the universe, though our understanding is still premature. The Vedic Indians already had figured it all out thousands of years before Einstein and modern quantum physicists. The argument between Schrodinger and Heisenberg had already taken place between the Buddhists and Hindus 1500 years ago. The particle-wave duality and the equivalence of energy and matter was already postulated in the Vaiseshikla sutra near 3000 years ago and all this knowledge is as ancient as the Vedas which could be more than 10,000 years old.
We will now cover space and timeseparately according to the vedic model. Space, time and mind are considered as nonphysical elements and seen as energies that are composed of particles. The nature of space, time and mind is fractal, like a molecule of DNA, that is that subset contains the entire set. This is surmised in this passage from the yoga sutra: the entire universe exists in one subatomic particle and the three worlds exist in one strand of hair.
There is space and there is Prakriti Prakriti is unmanifest infinite space. While, space, is the manifest state of Prakriti and is a form of energy, it is calleed akasha or ether. As we’ve seen earlier akasha exists in 5 states of energy and the first is plasma and beyond the plasma state exists space-energy. So Space is not a void, but rather a form of energy. It is composed of constituent particles in a constant state of flux. Further, space is not flat, rather it is curved and this is because of the high state of space energy and it’s universal gravitational field. Yes, space would thus have a univeral gravitational field, because it’s a high concentration of energy at a single point an because of the curved nature of space. Matter is not the cause of gravity, rather gravity is an effect of space. We learn this in the Shiva Purna where it tells us that the ethers shape Prakriti into a sphere. Space is defined as a frame in which matter exists in the Vaiseshika-Sutra, while the Srimad Bhagvatam define space as a bubble in which matter exists. Ultimately, it is called “maya” an illusion.
Time is called “samay” and is also a form of energy, one of the non physical elements, and the cause of all material nature. The factor of time affects all people in different ways. A difficult concept this maybe for some to grasp, but the past, present and the future are simply illusory and they all exist in one moment in the absolute reality of Mahavishnu. The time aspect of this universe(there are infinite universes) is seen as both relative to the observer and absolute to Brahmas reality the universal consciousness. The vedic time cycles are measured relative to Brahma. His time is as follows:
  • One day of Brahma: 4.32 billion years
  • One day and night of Brahma: 8.6 billion years
  • One life of Brahma: 133 trillion years
(According to 5th century Indians we are in the 51st year of Brahamas life, so the universe is some 600 billion years old. That is many times the current estimate).
The higher universes/worlds exist in a state of high energy and time is slower there. In the Purans it speaks of humans being that have gone to the higher universes/world for minutes and seconds and experienced time-dilation effects of thousands and millions of years.
One such account is given in the Srimad Bhagvatam Purana: A king of an submarine(underwater) civilization, maharishi Kakudmi and his Revati were a highly advanced race with great technology.
Kakudmi went on his spaceship to the Brahama’s world/universe. “O Maharaja Pariksit, subduer of enemies, Revata constructed a kingdom known as Kusasthali in the depths of the ocean. There he lived and ruled such tracts of land as Anarta, etc. He had one hundred very nice sons, of whom the eldest was Kakudmi. Taking his own daughter, Revati, Kakudmi went to Lord Brahma in Brahmaloka, which is transcendental to the three modes of material nature, and inquired about a husband for her.
When Kakudmi arrived there, Lord Brahma was engaged in hearing musical performances by the Gandharvas and had not a moment to talk to him. Therefore Kakudmi waited, and at the end of the musical performances he offered his obeisances to Lord Brahma and thus submitted his long standing desire. After hearing his words, Lord Brahma, who is most powerful, laughed loudly and said to Kakudmi, ‘O King, all those whom you may have decided within the core of your heart to accept as your son-in-law have passed away in the course of time. Twenty seven catur-yugas have already passed. Those upon whom you may have already decided are now gone, and so are their sons, grandsons and other descendants. You cannot even hear about their names.’ (SB 9.3.2832)
  • A caturyuga = 4,320,000 years
  • 27 catur yuga = 116,640,000
  • One second of Brahma = 100,000
Therefore Kakudmi was waiting for 19 min and 26 seconds and 116,640,000 years had elapsed on Earth. Experts from Vedic texts on time:
Srimad Bhagvatam Purana:
  • “The time factor, who causes the transformation of the various material manifestations, is another feature of the Supreme Personality of Godhead. Anyone who does not know that time is the same Supreme Personality is afraid of the time factor.” (SB 3.29.37)
  • “All these are considered the qualified Brahman. The mixing element, which is known as time, is counted as the twenty fifth element.” (SB 3.26.15)
  • “The influence of the Supreme Personality of Godhead is felt in the time factor, which causes fear of death due to the false ego of the deluded soul who has contacted material nature.” (SB 3.26.16).
  • “My dear mother, O daughter of Svayambhuva Manu, the time factor, as I have explained, is the Supreme Personality of Godhead, from whom the creation begins as a result of the agitation of the neutral, unmanifested nature.” (SB 3.26.17)
  • “By exhibiting His potencies, the Supreme Personality of Godhead adjusts all these different elements, keeping Himself within as the Supersoul and without as time.” (SB 3.26.18)
  • “The Supreme Personality of Godhead, in His feature of eternal time, is present in the material world and is neutral towards everyone. No one is His ally, and no one is His enemy. Within the jurisdiction of the time element, everyone enjoys or suffers the result of his own karma, or fruitive activities. As, when the wind blows, small particles of dust fly in the air, so, according to one’s particular karma, one suffers or enjoys material life.” (SB 4.11.20)”
This is a highly advanced understanding of space and time. We’ve seen that the nature of space and time as an energy, their relativity and the effects of time-dilation.
Vedic Spectroscopy
Here is the piece on the ancient light spectroscopy, and is the clearest proof yet of how
advanced vedic civilization were, and consistent with other vedic texts. I have worked very hard in getting the Hindi translated with my friend. Some parts still remain untranslated and I will not include them, as they are probably not necessary. They talk about prism settings, calculations and instructions on how to make the lens and prisms.
As was said, recently Indian scientists had constructed an ancient spectrometer/monochrometer from Maharishi Bharadwaja’s Amsu Bodhini.  Maharishi Bharadwaja is the same author of the Vymaanika Shastra, however unlike the Vyaamanika Shastra, the Amsu Bodhini has not been channeled psychically and was kept in a very old library at Oriental institute, Vadodara in India. It is the first chapter of Maharishi’s masterwork yantra Saraswana(all about machines) of which VS(science of aeronautics) is also a section.
This is a highly credible and technical text and supported by the biggest scientific institutes in India, including NML(National metallurgical lab) where it was constructed. It was also published in India’s prestigious scientific journal, INSA. I have also included the original Sanskrit, I don’t know what much good it will do, but for those who want to research this further, can do so. The information given in this
post on the spectrometer will probably not be sufficient to understand how it works or construct one from the directions. This is because this is not an engineering post, but a post to show that spectroscopy was practiced in Vedic India. For those who want the entire scientific papers, you will have to arrange for this yourself by either contacting NML or INSA. What is certain however, that they do exist.
We will also note that the theory of particle physics, radiation and quantum dynamics of ancient India, all that have been explained from their original source in this thread, were advanced enough to allow the empirical science of spectroscopy(heck, we’ve also learnt that some of modern physics is derived from the Vedas) The key knowledges are for any kind of spectroscopic knowledge are the following:
  • Energy and mass are equivalent
  • Heat and light are a form of energy; radiation
  • Light is composed of discreets units of quanta
  • A particle has a wave nature
  • The wave nature of radiation
  • A wave can be absorbed, reflected or refracted with certain materials
All of this is already understood by the Vedic Indians, this allows for lens devices (darpana yantras) that are actually talked about in the Vyaamanika Shastra. These devices could be telescopes, lasers, hologram projectors, microscopes, spectrometers and solar cells(talked about in various vedic literature)
Radiation Spectrometer: This is quite a novel spectrometer, it’s ancient name is, Dwanata Pramkar yantra, and you have never seen anything like it before. It is an astronomical instrument, that splits light rays with prisms into it’s components, due to dispersion of particles. It is analogue and measures all kinds of radiation of various wavelengths, based on the spectral deviation from a Vedic preset universal minimum deviation setting, which is a new concept for modern times which causes a reading of spectral lines on a dial, which is indexed with table which has the various readings for various kinds of radiation. The Amsu Bodhini is a cosmological text that deals with the evolution of the universe. It teaches that the evolution of the universes are caused by bindu vishput/maha vishput(big bang) which causes the solar systems and the suns( There are 5 types of spectrometers to measure radiation, the one we are discussing is a optical instrument and radiation is categorized into 3 types: infrared, visible and ultraviolet. If we recall, the maha vishput is also talked about in the Rig Veda.
Electromagnetic radiation is explained as frequency of the vibration and movement of high velocity positrons(anti electrons) and electrons and causes the three gunas, which here are defined as infrared, visible and ultraviolet. Now, that is interesting as it relates the cause of various kind of radiations to be simply the vibrations and movements of electrons and positrons, further still, electrons and positrons
would annihilate each other, and produce pure energy i.e radiation.
It would therefore mean that the Vedas are telling us that energy is simply the constant annihilation of particles and antiparticles. This would perhaps explain the state of the quantum vacuum and virtual particles, that are constantly fluctuating in and out of existence, in effect they are colliding with anti-particles and being annihilated,  therefore the resultant is always zero. However, what we perceive to be
zero, is actually space-energy.
This concept of the universe being in a state of perpetual annihilation is depicted by Shiva’s cosmic dance.
This is also consistent with vaiseshika Sutra view of all manifestations of nature, space, time, plasma, energy, matter is simply vibrations of particles(which are turn cause by vibrations of a superforce)
Summary of the Dwanata Pramkar Yantra: In the Yantra Saraswana there are 109 different machines, that are composed of 32 different components. Our spectrometer is composed of 13 components:
The components are prisms, windows, lens and various kinds of materials, they all have been fabricated from the metallurgical and chemical formulas given in the text. One such component, is a highly sensitive and transparent infrared glass, which is completely resistant to moisture. The refraction of the light is measured in ancient Vedic angle units, called kakshay(1 kakshay = 104 radian) and the action and motion of particles dispersed are counted. The data is analysed according to the mathematics of the deviations from the universal minimum deviation setting, for which a simple mathematics formula has been obtained.
Directions on building the device:
Note: The units that are used are angula (finger) and karmac. I am not sure what their equivalent is, but I estimate it as 1 finger = 2cm and 1 karmac = 1mm.
  • First and foremost. Make a 120 * 120 finger elipse from a mirror like glass of 106 karmac(mm) which will form the base. In the centre draw lines like a a 24 hour clock and two circles on both sides of it and making sections on it like a dial.                                                                                          यंत्रस्थद्वादशांगस्यपूर्वभागेस्थितेक्रमात्।
    पश्चाच्छायापकर्षणदर्पणे शास्त्र:क्रमात् -
    सर्वत्र रेखान्त्यभागेबिन्दुनेकसमन्वितान्।
  • After that, with a stony glass, make a 4 finger radius and 72 finger height pole and place it in the center of the base. Then from the start of the pole to the end, at 1212 finger distance apart make three holes, so that they will correspond to the electrical wiring to the sides. This is also called the principal pillar.                                                                                              चतुरंगुलमायामषड्वितस्त्युन्नतंतथा।
  • After that, make three holes on both sides and from principal pillar at 1010 finger distance, make a 60(4) finger height pole(from the same stony glass) so that it corresponds to the first hole. Then make an 88 distance from that at 50(5) finger height and finally at 66 distance make a 40 finger height pole(6). Fix these tightly. Then do the same with the right side, except make them slightly longer. The top of all the poles will have a chain and axle-mechanism.                                                          दृढंदशांगुलायामंक्रमात्यष्ट्यंगुलोन्नतम्।
    दंडानांमूलदेशेसंधारयेत्पार्श्वयो: क्रमात्।
  •  After that, 3030 lines on both sides make a 50 finger radius circular glass plate. On this, a 80 Surya Prism will be placed(a collminating lens) put in the third hole on the right(top) in such a manner, the corresponding pole on the right can turn it at 3 revolutions per cycle.                                 पंचाशदंगुलायामंविस्तीर्णतावदेवहि।
    प्रभाकरमणिं शुद्धमष्ठाशीत्यात्मकंलघु।।
    धारयन्तंमध्यभागे आतपोष्णादिभिर्युतम्।
  •  Make a 24 finger radius glass wheel of 206 karmac, on which CAOH and phosphoric acid ray absorbing prism will be placed. Join this to the corresponding chain and axle mechanism on the left.                                                                                         पश्चाद्दिवाकरादर्शवद्रेखाबिन्दुभिर्युतम्।
  • After that, with the Ushmapakshika material made of Madhuvaran, make a circular plate of 6 finger less radius, inscribed with points and indicators, so that two cavaties form on both sides of the plate. In the first cavaity place the 164 karmac infrared sensitive glass. Join this to the corresponding chain and axle mechanism on the right.                                              उष्णापकर्षकंनामलोहंस्यात्कृत्कंतत:।
    बिन्दुरेखांकनैर्युक्तं अवटद्वयसंयुतम्।।
  • After that, points, lines and indictators that have been made on a 173 karmac dhoom colour circular glass plate, on which is placed a 214 karmac lens suitable for ultraviolet radiation. Join this to the corresponding chain and axle mechanism on the left. When exposed to sun light, it will tell us about the ultraviolet radiation, according to the graduations. पश्चाच्चतुर्दशोत्तरद्विशतेनयथाविधि।
  • After that, a caliberated 96 karmac glass circular wheel, will be joined by a 42 karmac prism. Join this to the corresponding chain and axle mechanis, on the right. पश्चाद्द्विचत्वारिंशतिकप्रभामणिनायुतम्।
  • The above special lens that was made of 96 karmac on which graduations were made, on which a 9 karmac prism is seated. Join this to the first hole and corresponding rope axle mechanism. The reflective quality of the special lens, will cause the rays of the light to be mapped. एतद्भवेत्कृतकलोह:प्रकाशस्तंभनाभिद:।
  • After that, on the base an ultraviolet-visible differentiating glass display panel is made so that it can collect the projections on both sides of the wheels.            छायाप्रभाविभाजकलौहस्यात्कृतकस्तत:।
The mechanism of how it works:
When the rays of light enters the top wheel, on which is a collimation lens. By that, the rays coming
from through the lens enter the conical prism on the wheel underneath and continues cascading
downwards to component 2, which leaves a projection of a spectral ring, which can be measured
technically on the dials on the base. A reference table is given in the Amdu Bodhina for various radiation types, with technical names and radiation spectral kakshaya count(kakshaya units are vedic angle units):
Science is based on building blocks. There is yet another form of knowledge, that we sometimes call inspiration, intuition or revelations, that is not understood and in which parapsychological terms is called accessing a greater field of information and in vedic terms is called accessing the Akashic  records. That is that all knowledge is actually part of a universal field of information, which is where the Vedas have said to have originated. Einstein theory of relativity was one such revelation. Einstein himself said that this all came to him in an instant and came about from his imagination (right-brain). His asking questions like riding a beam of light to the past lead to relativity:
“I sometimes feel I am right, but do not know it. When two expeditions of scientists went to test my theory I was convinced they would confirm my theory. I wasn’t surprised when the results confirmed my intuition, but I would have been surprised had I been wrong. I’m enough of an artist to draw freely on my imagination, which I think is more important than knowledge. Knowledge is limited. Imagination encircles the world.”
For Newton, an apple falling on his head or so the story goes was a revelation of the laws of gravitation. Again, this was a moment of inspiration. Nobody knows how it happened how
an apple falling on his head would make him understand gravity; but it did.
Arguably the greatest mathematician in modern history and without whom string theory would not be possible, who formulated modular functions, but did not provide the proofs(an old Indian trait) said he learnt all his maths from a goddess who told him in his dreams.
In fact, the discovery of the structure of the molecule Benzene, came to it’s founder, Friedrich August von Kekule, in a dream, where he saw it as a coiled snake biting it’s own tail:
“I turned my chair to the fire [after having worked on the problem for some time] and dozed. Again the atoms were gamboling before my eyes. This time the smaller groups kept modestly to the background. My mental eye, rendered more acute by repeated vision of this kind, could not distinguish larger structures, of manifold conformation; long rows, sometimes more closely fitted together; all twining and twisting in snakelike motion. But look! What was that? One of the snakes had seized hold of its own tail, and the form whirled mockingly before my eyes. As if by a flash of lighting I awoke… Let us learn to dream, gentlemen.”
Even Archimedes “Eureka” moment, was not by cold logical thinking, but a flash of insight, so wonderful was that moment, he lept out naked onto the streets.
So you see, there is thinking and then there is knowing, and wouldn’t you agree, knowing is more powerful than thinking. The logical mind is limited by structure, beliefs, preconceptions, rigid patterns and a cloud of thoughts. The right-mind is unlimited.
It’s directly from the mind of the universe or god, which is the source of consciousness, however some of you do not believe this, and therefore I can only say that you don’t know where it comes from because if we did we would understand consciousness.
There is so much that happens to us in our life synchronistic events they usually have something very relevant for us. Sometimes, the right person comes along, sometime the clouds form in such ways that we see messages, sometimes a single fortune cookie, could bear a message that means a lot to us, and only to us, and we get a sense of knowingness. It is this knowingness that is mysterious well
at least for you.