Bharatkalyan97

Abstract

The practice of Ayurveda, the traditional medicine of India, is based on the concept of three major constitutional types (Vata, Pitta and Kapha) defined as “Prakriti”. To the best of our knowledge, no study has convincingly correlated genomic variations with the classification of Prakriti. In the present study, we performed genome-wide SNP (single nucleotide polymorphism) analysis (Affymetrix, 6.0) of 262 well-classified male individuals (after screening 3416 subjects) belonging to three Prakritis. We found 52 SNPs (p ≤ 1 × 10−5) were significantly different between Prakritis, without any confounding effect of stratification, after 106permutations. Principal component analysis (PCA) of these SNPs classified 262 individuals into their respective groups (Vata, Pitta and Kapha) irrespective of their ancestry, which represent its power in categorization. We further validated our finding with 297 Indian population samples with known ancestry. Subsequently, we found that PGM1 correlates with phenotype of Pitta as described in the ancient text of Caraka Samhita, suggesting that the phenotypic classification of India’s traditional medicine has a genetic basis; and its Prakriti-based practice in vogue for many centuries resonates with personalized medicine.

Introduction

Among the traditional systems of medicine practiced all over the world, Ayurveda of India has a documented history dating back to 1500 BCE1,2. Though contemporary medicine is currently the mainstream of medical practice in India, Ayurveda is extensively used side by side and remains highly popular, especially in South Asia. The basic concepts of Ayurveda are; 1. five elements – panchabhuta – which constitute the physical universe including the human body and; 2. three doshas (Vata, Pitta and Kapha) or constitutional types of every human. These doshas refer broadly to the functions of motion, digestion and cumulation. Though all three doshas exist in every human being one is dominant based on which an individual’s Prakriti is determined. Prakritis are discreet phenotypes and they are determined on the basis of physical, psychological, physiological and behavioural traits, and independent of social, ethnic and geographical variables1,3,4. The etymology of these Sanskrit terms suggests that Vata originates from movement, Pitta from digestion and Kapha from cumulation. Since Prakritisunderlie an individual’s predisposition to disease as well as response to treatment, it is imperative in Ayurvedicpractice to identify the Prakriti of a patient before treatment5.

Concept of Prakriti in Ayurveda and its relationship with genomics was hypothesized over a decade ago6. Subsequent studies have attempted to correlate Prakriticlassification with genetic information and association of single nucleotide polymorphisms (SNPs) in HLA-DRB17,CYP2C198, EGLN19, inflammatory and oxidative stress related genes10, CD markers for various blood cells11,12, DNA methylation alterations13 and risk factors of cardiovascular or inflammatory diseases have been reported14. While these studies have shown the association of specific genes with the phenotype of a particular Prakriti, the association of genomic variations with Prakriti classification was lacking. This is the first attempt to classify the Prakritis using genome-wide SNP markers and to provide a scientific basis for Prakriticlassification.

Results and Discussions

A total of 3,416 normal healthy male subjects between 20–30 years of age were recruited by the Institute of Ayurveda and Integrative Medicine (IAIM), Bangalore, Karnataka (‘B’ in tables); Sinhgad College of Engineering (SCE) Pune, Maharashtra (‘P’ in tables); and Shri Dharmasthala Manjunatheshwara College of Ayurveda (SDMCA), Udupi, Karnataka (‘U’ in tables). Since the hormonal fluctuations during premenstrual and menstrual phases result in numerous physical and psychological disturbances, which may have confounding effect at the time of Prakriti assessment, we have excluded females from this study (detailed justification on inclusion of only males is given in the Methods section). However, several studies have included of both male and female subjects for Ayurveda-based studies7,8,15,16. The subjects belonged to diverse ethnic and linguistic groups, and inhabited different geographical regions. The health status of every individual was ascertained by modern as well asAyurvedic methods (details given in the Methods). The composition of Prakriti was determined by seniorAyurvedic physicians and confirmed independently by ‘AyuSoft’ (http://ayusoft.cdac.in), a software developed based on information from classical Ayurvedic literature. The subjects, whose Prakriti was in concordance between the assessment by Ayurvedic physicians and by AyuSoft were only selected for this study. Of the total 3,416 individuals evaluated, 971 had 60%–93% dominance of one Prakriti (Table S1), of which 262 individuals (94 Vata-dominant, 75 Pitta-dominant and 93 Kapha-dominant) with the highest proportion of one predominant Prakriti were randomly selected and subjected to genome-wide SNP analysis (Affymetrix array, 6.0) and genotypes were fetched using Birdsuite software17. The proportions of each dominant and co-dominant Prakritis are given in Fig. 1; Figure S1.

Figure 1: Box-plot representing the *Prakriti*proportion of subjects with Vata (94), Pitta (75) and Kapha (93) dominant characteristics.

Out of 262 individuals analyzed, 245 passed the quality controls (QC) with the call rate 0.966 ± 0.0162 (Table S2). In order to validate the high-throughput data set, we randomly selected 48 markers from Affymetrix array and genotyped 48 individuals using custom-designed VeraCode GoldenGate Genotyping Assay System (Illumina, San Diego, USA). The call rate of VeraCode analysis was 99.61% and the genotype matched with Affymetrix data set (Table S3), suggesting that the genotypes obtained from Affymetrix array was genuine with minimum error (0.39%). Further, to increase the statistical power, we used Indian population data set as reference and imputation analysis was performed using Beagle (v3.3.1) software18 (Figure S1). As we had demonstrated earlier that Indian population has unique genetic architecture, we were skeptical of using non-Indian samples as a reference for imputation19. To evaluate our assumption, we masked 2%, 5% and 10% genotype of 207 unrelated Dravidian and Indo-European population samples and performed 110 simulations on chromosome 22 with four-reference populations i.e.Indian population (28 trios of Dravidian and Indo-Europeans; IN), different HapMap populations (CEU, YRI, CHB, CHS and JPT; HM), different South-Asian populations of 1000 genome project (BEB, GIH, ITU, PJL and STU; SA) and Indian along with HapMap populations (IH). As expected, imputed genotypes were more accurate with Indian samples (IN) [2% (0.9518 ± 0.0012); 5% (0.95045 ± 0.00109); 10% (0.9476 ± 0.0005)] compared to HM [2% (0.9462 ± 0.0013); 5% (0.9436 ± 0.0017); 10% (0.9396 ± 0.0005)], IH [2% (0.9463 ± 0.0014); 5% (0.9448 ± 0.0016); 10% (0.9417 ± 0.00066)] and SA [2% (0.9481 ± 0.0013); 5% (0.9471 ± 0.00098); 10% (0.9441 ± 0.00061)] samples (Table S4; Figure S2). In all the three masked data (2%, 5% and 10%), IN showed high imputation performance compared to HM, SA and IH. Even with ~10% masked data, the imputed genotypes were more accurate with IN than other references, suggesting that it is appropriate to use Indian data set for imputation. The data set of Gujarati Indians in Houston (GIH) is the only one available in the public domain, which was admixed recently, and hence does not truly represent the ANI-ASI ancestry of Indian population19,20. As the data were not suitable reference for imputation, we prepared our own reference panel of Indian population (http://www.ccmb.res.in/bic/database_pagelink.php?page=snpdata). To achieve this, we followed two steps (i) imputation of 15 trios of Indo-European and 15 trios of Dravidian, and (ii) imputation of 229 unrelated individuals imputed with the reference genotype obtained from step-I. Further, we used this reference for imputing thePrakriti individuals. In the first step, we found 10.5% and 17.8% Mendelian inconsistency in two trios, (Kashmiri Pandit) (Table S5), which were removed from the analysis. Finally, we obtained 791186 SNP markers with 0.95 ≤ R2 ≤ 1, for further analysis.

To make sure that the Prakriti samples were collected randomly and there was no major ancestral bias while collecting samples, we performed the principal component analysis (PCA)21 of 245 Prakriti samples (Figure S3). PCA analysis revealed no significant overall differences among the Prakritis (ANOVA p-value on eigenvector 1 V vs. K-0.434; V vs. P-0.89; P vs. K-0.51; and eigenvector 2 V vs. K-0.09; V vs. P-0.06; P vs. K-0.02). In order to check the ancestry of Prakriti individuals, we used our published data set of 297 Indian population samples with known ancestry19,20. These 297 samples include; 150 Dravidians, 80 Indo-European, 35 Austro-Asiatic, 27 Tibeto-Burman and 5 Great Andamanese (Table S6). We found 7,89,309 SNPs were common between Prakriti and Indian ancestral samples. In order to remove the differentiation on spurious axes21, we pruned 3,76,138 SNPs, which were in strong linkage disequilibrium (LD) (r2 > 0.75), and performed PCA with 4,13,171 SNPs. Our analysis showed that most of thePrakriti samples clustered with Dravidian and Indo-European (the two major ancestral population of India), and only 3 samples seemed to be Tibeto-Burman and admixed recently (Figure S4). Previous studies have shown that stratification could cause spurious association22,23,24,25, hence, PCA was performed21 using 4,05,782 SNPs (3,85,404 SNPs were pruned with r2 > 0.75) for 245 Prakriti samples, of which 40 were outliers and have been removed in 10 iterations with σ ≥ 6 on eigenvector 1 to 10 (Table S7; Figure S3 and S5). ANOVA analysis revealed that the Prakriti groups were not significantly different (p-value: V vs. P - 0.40 ± 0.28; V vs.K - 0.51 ± 0.32 and P vs. K - 0.48 ± 0.29) (Table S8); and 205 Prakriti samples were used for further analysis (Figure S1).

Association analysis was performed using plink software26. Since the present study has no cases and controls (patients and healthy), we considered onePrakriti as case and the remaining two Prakritis as controls, and performed association analyses in three combinations: Vata vs. Kapha and Pitta (V vs. PK); Pitta vs. Kapha and Vata (P vs. VK); Kapha vs. Pitta and Vata (K vs.VP). Prior to association analysis, 3,890; 4,153 and 4,124, respectively, markers were removed from 791186 markers, which were not in Hardy-Weinberg equilibrium (HWE) i.e. p-value < 0.001 in controls of V vs. PK, P vs. VK and K vs. VP; respectively. The three combination association results were further used to identify the SNPs that were significant. Considering the fact that none of the samples represents 100% single Prakriti, we did not expect very low p-value in the association analysis. In this scenario, truly associated loci may co-exist with false positive markers and can be identified by permutation analysis. As expected, we observed that SNPs having approximately same p-value in the extreme tail of theoretical distribution failed to achieve 106permutations (Table 1). For example, rs2939743 having p-value 7.61 × 10−5 dropped at 142717th permutation while rs10197747 having p-value 2.50 × 10−5 achieved 106permutations, which of course revealed that rs2939743 is false positive. Similarly, we found 52 true positive SNPs achieved 1 million simulations with theoretical p-value ≤ 1 × 10−5 (details are given in Table 1; Figure S6).

Table 1: Empirical and theoretical distribution of the associated markers (p-value ≤1 × 10−5) of Vvs. PK, Pvs.VK and Kvs.VP.

Full size table

It is well known that some markers differ in allele frequency more across ancestral population, compared to other set of markers. Moreover, natural selection might be the reason for this phenomenon because it acts locus-specific manner21. We speculate that the above so-called true positive loci might be artifacts of population stratification because of high probability of false positive results at the p-value, which observed in association analysis. Hence, we performed extensive statistical analyses to control these confounding factors and/or population stratification. Prevailing methods include genomic control and EIGENSTRAT to find such confounding effect of stratification. Genomic control uses uniform inflation factor to correct stratification, which is not sufficient for those SNPs having high frequency differences between ancestors21. Hence, we proceeded with EIGENSTRAT and found p-value did not change drastically (Table S9). To further confirm, we used variance component model (implemented in EMMAX)27 and mixed-linear model of association analysis (implemented in GCTA)28, which can correct sample structure in association, but have different statistics comparative to eigenstrat. Intriguingly, even with this analysis, we did not observe any drastic change in the p-value (Table S9). This has proved that these 52 SNPs were genuine characteristics of Prakriti and not derived from ancestry. Moreover, we also explored the allele frequency differences between centers; however, we did not find any significant difference for these 52 SNPs (Table S10). We further explored the power of 52 SNPs in Prakritisgenetic differentiation (Figure S1). In principal component analysis, 19 SNPs were excluded with r2 > 0.75 and, as expected, we found striking separation of subjects according to their Prakriti (Fig. 2A). On eigenvector-1 (eigenvalue = 18.168248) Pitta significantly differentiated against Vata and Kapha (p-value = 1.11022 × 10−16, 4.44089 × 10−16, respectively); while on eigenvector 2 (eigenvalue = 15.890861) Kapha was significantly different compared to Vata and Pitta (p-value = 3.33067 × 10−16 and ~0 respectively).

To examine the statistical power of these 52 markers for categorizing the samples with unknown Prakriti, we generated a statistical model (see methods). Initially, we applied it on 205 samples and found 23.9% (49 out of 205) were explained by the proposed model (Table S11). Further, we applied it on 297 Indian (population) samples and found 37 individuals (5 Austro-Asiatic; 22 Dravidian; 8 Indo-European and 2 Tibeto-Burman) satisfying the model. According to the model, 7 individuals were Vata, 20 were Pitta and 11 were Kapha. Interestingly, Indian population samples, which belong to one Prakriti were from different ancestry (Table S12), suggesting that these makers could separate the Prakritis, irrespective of their ancestry. To confirm the proposed model, we projected these 37 individuals on eigenvector of Prakriti samples and found that these individuals clustered with Prakritias predicted in the model (Fig. 2B). It suggests that the cluster is based on Prakriti, and is not due to the ancestry of samples. That would also suggest that the phenotypic variations have a genetic basis, which would be shared by Prakritis of Ayurveda.

Further, we used these 52 markers to find the genotype-phenotype correlations. We observed that 2 markers (rs10518915 and rs986846) were associated with two different Prakriti; rs10518915 with Vata and Pitta, while rs986846 with Kapha and Vata. This observation prompted us to believe that different alleles of the same locus might be influencing different Prakriti (Table 1). In order to correlate the functional relevance of these SNPs, we divided them into genic and non-genic. The SNPs, which are within 10 kb of gene, were considered genic; while others as non-genic29,30. We found 28 were genic SNPs, of which 12 were in Vata (7 genes), 11 in Pitta (7 genes), and 6 in Kapha (7 genes) (Table 1). To correlate the function of these genes with respect to the characteristics of Prakritis, we searched in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Reactome event and found PGM1 gene associated with the Pitta phenotype. In Ayurveda, characteristics of Pitta include digestion, metabolism and energy production. Interestingly, we found PGM1 gene is in the center of many metabolic pathways i.e. glycolysis or gluconeogenesis (hsa00010); pentose phosphate pathway (hsa00030); galactose metabolism (hsa00052); purine metabolism (hsa00230) and; starch and sucrose metabolism (hsa00500) (Figure S7). Our finding suggests that the function of the gene directly correlates with the role of Pitta in metabolism as described in Ayurvedicliterature.

In addition, we have checked the PGM1 gene markers in Affymetrix data set and found 4 markers (rs2269241, rs2269240, rs2269239,and rs2269238) were associated with Pitta Prakriti and all are in strong Linkage Disequilibrium (LD) (Figure S8). Therefore, to find the functionally relevant variants, we sequenced the whole exons and UTRs of the PGM1 gene in 78 individuals using Ion Torrent PGM (Life Technologies, USA). We found 23 variations in the gene, of which 8 were novel (Table S13). Interestingly, one non-synonymous; c.1258T > C (p.Tyr420His) (rs11208257) variant was present in the LD block and found in association with Pitta Prakriti (p-value–7.049 × 10−3). The frequency of the mutant allele “C” was 5.8% in Pitta and 20% in Kapha Prakriti (Table S14). This result prompted us to replicate the marker (rs11208257) in additional samples. We genotyped this marker (rs11208257) for 665 Prakriti individuals (299 Vata, 164 Pitta and 202 Kapha) using Sanger sequencing method. Initially, we analyzed the distribution of the genotype among participating centres and found “U” samples (collected from Udupi centre) were not in HWE (p-value - 0.04) (Table S15). Hence, we excluded 169 “U” samples from the analysis. Association analysis revealed that allelic and genotype distribution of the marker rs11208257 is significantly different in Pitta Prakritiagainst Vata and Kapha with p-value- 2.06 × 10−2; p-value- 6.16 × 10−3, respectively. Further, we explored the association between P vs. V and P vs. K; and found significant p-value - 7.61 × 10−3 and 2.35 × 10−2, respectively. The results would therefore suggest that Vata differs more from the Pitta Prakriti than Kapha (Table S16). We further screened 1108 randomly selected Indians and 992 HapMap samples and found that the frequency of mutant allele “C” was 17.9% among Indians, 15.5–17.6% in the Europeans, 14.5–18.8% in East Asians, 42% in Mexican, 15.3% in admixed Indians (GIH) and 12.8–28.3% in Africans. Indians have comparable frequency with Europeans and GIH (Table S17). Interestingly, we found Pitta has less frequency of mutant “C” allele, and Vata and Kapha have comparable frequency with overall Indian population. To explore the functional relevance of the variant, we used SIFT software and found that the mutation is damaging with 0.01 score and thus substitution at this position may affect the protein function. Our data suggest that the SNP (rs11208257) inPGM1 gene is linked with one of the main features (energy production), which is more homogenous and constant in Pitta than with Vata and Kapha, and a genotype correlation exists for the characteristics ofPrakriti classification.

In conclusion, our preliminary study suggests that thePrakriti classification, as a foundation for the practice ofAyurveda, has a genetic basis and does provide clues for further studies.

Methods

Selection of subjects and Prakriti assessment

Selection of subjects and evaluation of the Prakriti (the human classification of Indian ancient medicine) were carried out at three centres; 1. Institute of Ayurveda and Intergrative Medicine (IAIM), Bangalore, Karnataka; 2. Sinhgad College of Engineering (SCE) Pune, Maharashtra; and 3. Shri Dharmasthala Manjunatheshwara College of Ayurveda (SDMCA) Udupi, Karnataka. This study was approved by Institutional Ethics Committees (IECs) of all the collaborative centres and the methods were carried out in accordance with the approved guidelines. We have screened normal and healthy male subjects, who were between 20–30 years. Although several Ayurveda-based studies have included both male and female subjects7,8,15,16, we have excluded female subjects from this study to minimize the confounding variations.Prakriti of an individual is determined based on defined anatomical, physiological psychological and behavioural characteristics. During actual assessment of Prakriti, theAyurvedic physician needs to factor in these characteristics. One such aspect is the cyclical hormonal changes that occur in women, particularly the menstrual cycle. The hormonal fluctuations result in numerous physical and psychological disturbances, which occur in the premenstrual and menstrual phases. Existing evidence suggest that about 97% of young nulliparous women experience varying degrees of such disturbances31. These elicitable and visible features can confound or obscure the Prakriti assessment process. For example, premenstrual irritability occurring in a woman of Kapha Prakriti is confounding, since KaphaPrakriti individuals normally possess low irritability. Although the Ayurvedic physicians routinely enquire about the menstrual habits of patients while assessing the Prakriti, it would have been difficult for us to make similar enquiries to young, healthy women who volunteered to join this study. The health status of an individual was assessed based on the Ayurvedic criteria, that include; normal desire for food, easy digestion of ingested food, excretion of feces, excretion of urine, excretion of flatus, functioning of sensory organs, comfortable sleep, easy awakening, and attainment of strength, bright complexion and longevity. Subjects with smoking habit, diabetes, hypertension and other chronic diseases were excluded from the study. Blood pressure (BP) was measured for each subject and BP > 130/90 mm of Hg were excluded from the study. Chronic systemic diseases such as rheumatoid arthritis, cancer, etc., and subjects having recent history of acute ailments such as fever due to infections were also excluded.

We followed three steps for the Prakriti assessment of each subjects. In the first stage, senior Ayurvedicphysicians assessed the Prakriti of the subjects, applying classical Ayurveda parameters of Prakriti determination. In second stage, the same subjects were assessed using Ayusoft, a Prakriti software (www.ayusoft.cdac.in), which contains a comprehensive questionnaire, which had been developed based on the information from originalAyurvedic literature. In the third stage, another team ofAyurvedic physicians, who were not aware of the outcomes of assessment by senior physicians and Ayusoft, compared the Prakritis analysis. Subjects with ≥60% of single Prakriti dominance and having concordance in all the three stages were selected for the genome-wide analysis. Quantitative analysis of Prakritiwas performed using Ayusoft along with traditional ayurvedic measures for the Prakriti assessment. The reason for considering ≥60% of a particular Prakritias a dominant was mainly due to feasibility and concordance. Single dosha Prakriti with high percentage of one dosha rarely exist, hence most of the individuals possess dual-dosha Prakriti12. Therefore, we have considered subjects with ≥60% as single dosha dominantPrakriti. Subjects ≥60% of one dominant Prakriti were selected and blood was drawn after obtaining their informed written consent. A total of 3,416 healthy individuals were screened for their Prakriti, as per the details given above. From the total, 971 subjects who showed a predominantPrakriti of ≥60% were included in the analysis (Figure S1).

High throughput genotyping, their quality control criteria and resequencing

Genotyping

DNA was isolated from the blood samples using standard protocol32. We randomly selected 262 Prakriti individuals for genotyping, using Genome-Wide Human SNP Array from Affymetrix (6.0), following manufacturer’s protocols. About 250 ng of genomic DNA was digested with Nsp Iand Sty I restriction enzymes, followed by ligation ofNsp/Styadaptors, using T4 DNA ligase. PCR was performed using the primers that are specific to these adopters. After checking the amplicons on 2% agarose gel, they were purified with deep-well plate using magnetic beads and the fragments were eluted using EB buffer, followed by quantification and fragmentation. The fragmented PCR products (<180 bp) were end-labeled using labeling kit. Labeled fragments were hybridized onto the Affymetrix (6.0) SNP arrays using hybridization cocktail. Hybridization was performed in hybridization oven for about 18 hrs at 50 °C. After hybridization, arrays were washed, stained, scanned and analyzed using Affymetrix Genotyping Console 2.0 and GeneChip® Operating Software (GCOS). The samples which passed the quality controls i.e. call rate >95% and CQC > 0.4 were considered. Affymetrix power tool (apt-geno-qc) was used for calculation of dm (dynamic model) value. The samples having dm.all_qc<0.83 were removed from further analysis and genotypes were fetched with Birdsuite software from Broad Institute17 (Figure S1).

Detection of technical artifacts

In order to validate the Affymetrix data set, we randomly selected 48 markers (Table S3) from Affymetrix array and genotyped 48 individuals, who were already genotyped by Affymetrix array, using custom-designed VeraCode GoldenGate Genotyping Assay System (Illumina, San Diego, USA). Genotyping was performed according to the manufacturer’s (Illumina, San Diego, USA) instructions. The genotypes obtained by both the platforms were compared and checked for accuracy (Figure S1).

Targeted resequencing

We sequenced the whole-exons and UTRs of PGM1 gene (Figure S1) for randomly selected 43 Pitta and 35 Kapha individuals using Ion Torrent (Life Technologies, USA), following protocols of the manufacturer. Primer sequences were manufactured specifically for use with Ion AmpliSeq kits. The costume Ion AmpliSeqTM primer contains 35 amplicons in a single pool. For preparing amplicon libraries, about 10 ng of DNA was amplified (PCR) using AmpliSeqTM primer pools and Ion AmpliSeqTM HiFi master mix (Ion AmpliSeq kit version 2.0 Beta). The amplified products were pooled and treated with 2 μl of FuPa reagent. The amplicons were then ligated with adapters from the Ion XpressTM barcoded adapters 17–64 kit according to the manufacturer’s instructions (Ion Torrent). After ligation, the amplicons were purified by Agencourt® AMPure® XP Reagent and additional amplification was performed to complete linkage between adapters and amplicons. In order to determine the library concentration, an Agilent 2100 Bioanalyzer high-sensitivity DNA kit (Agilent, Santa Clara, CA) was used to visualize the size range of the libraries. Equimolar concentrations of all the libraries were pooled and diluted. Using Ion One TouchTM 200 Template Kit v@ DL (Life Technologies, USA), emulsion PCR was carried out according to the manufacturer’s instructions. Ion Spheres (ISPs) were recovered according to the Ion Sphere Particles 200 recovery protocol. Sequencing was done following the Ion PGMTM 200 Sequencing Kit Protocol (version 6; Ion Torrent). The 318 sequencing chip was loaded and run on an Ion Torrent PGM (Ion Torrent). Base calling and alignment were performed using the Torrent Suite 3.0 software (Ion Torrent). In order to find the significant variation in the PGM1 whole exome data, we performed association analysis using plink software26 and variations are annotated on EnsEMBL-BioMart.

Sanger sequencing

To validate and replicate the Pitta associated SNP (rs11208257), Sanger sequencing was carried out for 496Prakriti samples (246 Vata, 116 Pitta and 134 Kapha) along with randomly selected 1108 Indian samples. Pair of primers (Forward primer: 5′- GCACGTTTCTTACAGCAGCT-3′ and Reverse primer: 5′-ACCTTACCTTGTACCCCAGC-3′) were designed, synthesized and PCR was performed on the GeneAmp 9700 Thermal Cycler (Applied Biosystems, Perkin-Elmer) using the following cycling conditions: 95 °C for 5 min, 35 cycles at 95 °C for 30 s, 58 °C for 30 s, 72 °C for 2 min and a final extension at 72 °C for 7 min. Amplicons were purified using with USB ExoSAP-IT (Affymetrix) according to the manufacturers instructions. The purified products were directly sequenced using the Big Dye Terminator cycle sequencing kit (Applied Biosystems, Foster City, CA, USA) and analyzed using 3730 DNA Analyzer (Applied Biosystems, Foster City, CA, USA)(Figure S1). The genotypes were noted, and statistical analysis was performed with plink26 and R.

Indian, HapMap and 1000 genome project sample details

For comparative analysis, we used Affymetrix (6.0) array data of 297 well-classified Indian samples with known lingustic and ethnic affiliations i.e. 150 Dravidians, 80 Indo-European, 35 Austro-Asiatic, 27 Tibeto-Burman and 5 Great Andamanese. In addition, 15 trios of Dravidian (Vysya, Madiga, Mala; 5 each) and 15 trios of Indo-European (Kshatriya, Brahmin and Kashmiri Pandit; 5 each) were used for imputation19,20. We followed the same procedure (mentioned above) for extraction of genotypes and CQC measures. The list of population and their details are given in Table S6. We have also used 1184 HapMap (ftp://ftp.ncbi.nlm.nih.gov/hapmap/genotypes/2009-01_phaseIII/plink_format/) and 1000 genome project data (ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/) for imputation and comparative analysis.

Imputation and their relationship with ancestry

Imputation was performed for the missing genotypes using Beagle-v3.3.2 software18. In order to check the power of correct imputation, we randomly masked 2%, 5% and 10% genotype of chromosome 22 in 207 unrelated Indian population samples. We imputed masked genotypes with four types of reference i.e. Indian triose (15 trios of Dravidian and 15 trios of Indo-European), HapMap samples (CEU, YRI, CHB, CHS and JPT), Indian + HapMap samples and samples of 1000 genome project with South-Asian ancestry (BEB, GIH, ITU, PJL and STU). Accuracy of imputation was calculated by comparing imputed and true genotype in 110 simulations for 2%, 5% and 10% masked data. To perform the above analysis, we used a perl script.

To impute missing genotype in Prakriti samples, we followed two steps; In the first step, imputation and phasing was done for 15 trios of Dravidian (Vysya, Madiga, Mala; 5 trios each) and 15 trios of Indo-European (Kshatriya, Brahmin and Kashmiri Pandit; 5 trios each) together without reference population. SNPs which do not follow Mendelian rule in trios were checked and masked with Beagle utility program18. Number of SNPs per family, which do not follow Mendelian consistency are given in Table S5. In the second step, we performed imputation of unrelated population samples (Dravidian, Indo-European and Austro-Asiatic), with imputed familial (trios) samples as reference. Further, we imputed Prakritisamples with reference of imputed trios and unrelated Indian population samples and selected only those markers which were having R2 > 0.95 for further analysis.

Population stratification

Principal component analysis was done with Eigensoft Package21. Convertf was used for converting plink ped file to Eigenstrat format. We pruned the SNPs on the basis of their Linkage Disequilibrium (r2 > 0.75) before running PCA by using Eigensoft’s killr2 option. Ten eigenvectors were fetched. To find the ancestry of 245 Prakritisamples, we used 297 known ancestry of Indian population dataset (previously published) and performed the PCA. Stratification was checked and 40 outlier samples were excluded with cutoff sigma value ≥0.6 (default value) on 1–10 eigenvectors in 10 iterations (Figure S1).

Association analysis

Plink was used for association analysis21. Imputed Beagle file were converted into plink ped file. Association analysis was performed for the Prakritis. Since there are no case control groups in the present study, we compared one Prakriti against the other two Prakritis (Vata vs. Pitta and Kapha, Pitta vs. Vata and Kapha, and Kapha vs. Vata and Pitta) and calculated p-value from theoretical distribution. In order to exclude the markers, which could be in association by chance, we also performed adaptive permutation approach (empirical distribution) for maximum 106 iteration withplink and considered only those markers who achieved maximum 106 permutations and have p-value ≤ 1 × 10−5 in theoretical distribution (Figure S1).

Addressing issue of population stratification as possible confounder in association analysis

Even subtle stratification can cause spurious association; hence we used EIGENSTRAT software21 for correcting association chi-square value on 10 eigenvector and to find its confounding effect. Initially we excluded 385, 404 SNPs with r2 > 0.75 and calculated eigenvector with remaining 405, 782 SNPs with SMARTPCA. Further we used these same 10 eigenvector for correction of chi-square value with EIGENSTRAT (Figure S1).

To address this issue, we also used EMMAX and GCTA tools27,28. Both statistical methods consider genetic structure in association analysis. Hence, we expected major changes in p-value of 52 SNPs. First, we generated IBS matrix implemented in EMMAX and then used it with 10 eigenvector (generated with SMARTPCA) as covariate to calculate p-value with variance component model (implemented in EMMAX). To calculate mixed-model association p-value (implemented in GCTA), first, we calculated genetic relationship matrix and 10 eigenvectors with GCTA; and used it in calculation of p-value (Figure S1).

Statistical determination of Prakriti in subjects

In order to prove the power of these markers in samples of unknown Prakriti percentage, we generated a statistical model (Figure S1). First, this model applied to 205 Ayur samples and then replicated in Indian population data set with unknown Prakriti. For this, we calculated the weight for the genotype of each marker associated with the Prakriti. Suppose, if the frequency of genotype g in Prakriti p is fp then the weight of g(Wgp) can be calculated with equation (1)

Un-standardized total weight of the Prakriti Wvs for a sample s with n number of associated markers for p Prakriti can be calculated using equation (2)

Hence, for a single sample there will be 3 weights Wvs, Wps and Wks corresponding to Vata, Pitta and Kapha using equation (2). For making weights comparable, we standardized by subtracting with mean and dividing it by standard deviation. Mean and standard deviation were calculated from total weight of each sample for each markers corresponding to each Prakriti. If total number of sample is N then standardized weight can be calculated using equation (3)

Prakriti is relative proposition (tridosha), so we calculated the differences of standardized weight for all 6 permutations; ΔVP, ΔVK, ΔPV, ΔPK, ΔKP and ΔKP for each samples and calculated representative statistics Rp. For example, representative statistics for Kapha Rk can be calculated using equation (4)

Since multiplication of 2 negative values is positive, the Rp value could be positive for 2 negative Δ values. Hence, we considered only those Rp values, which have both Δ value positive. Moreover, we consider only those samples which have Rp ≥ 3 to find dominant Prakriti. We applied this model to Indian population and selected 37 samples on the basis of Rp and Δ values.

Phenotype and genotype correlation

We considered markers within 10 kb flanking region of gene as genic and other as non-genic. Physical location of the genes (knownGene.txt.gz) and SNPs (snp135.txt.gz) were fetched fromhttp://hgdownload.soe.ucsc.edu/goldenPath/hg19/database/ and; windowbed(Bedtools:https://code.google.com/p/bedtools/) was used to find the SNPs within 10 kb flanking region of the genes. Only genic markers were used for genotype-phenotype correlation. Genic SNPs were selected and considered for further analysis. To correlate the function of associated markers with characteristics of the individualPrakriti, we checked in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Reactome event using NCBI2R R package.We used SIFT algorithm (http://sift.jcvi.org) for predicting the effects of non-synonomous variant (rs11208257) on protein function.

Additional Information

How to cite this article: Govindaraj, P. et al. Genome-wide analysis correlates Ayurveda Prakriti. Sci. Rep. 5, 15786; doi: 10.1038/srep15786 (2015).

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Acknowledgements

This work was supported by the Office of the Principal Scientific Advisor to the Government of India; Department of Science and Technology (DST), Government of India (PRNSA/ADV/AYURVEDA/4/2007). KT was also supported by CSIR Network project - GENESIS (BSC0121), Government of India. We acknowledge the help of Dr. Ketaki Bapat for her constant support throughout the project tenure. We thank Dr. David Reich for his valuable suggestions.

Author information

These authors contributed equally to this work.

Affiliations

CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India
School of Life Sciences, Manipal University, Manipal, Karnataka, India
Shri Dharmasthala Manjunatheshwara College of Ayurveda, Udupi, Karnataka, India
Sinhgad College of Engineering, Pune, Maharashtra, India
Foundation for Revitalization of Local Health Traditions, Bangalore, Karnataka, India
Department of Statistics, Manipal University, Manipal, Karnataka, India
- Sreekumaran Nair
Interdisciplinary School of Health Sciences, University of Pune, Pune, Maharashtra, India
- Bhushan Patwardhan
Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bangalore, Karnataka, India
- Paturu Kondaiah

Contributions

M.V.S.V., K.S. and K.T. conceived the idea. K.T. design the study and provided reagents. K.T., K.S., M.V.S.V., P.K., B.P. and P.M.G. supervised the study. J.N., B.K.B., B.V.P., A.P.D., R.B., G.G.G. and S.K.N. screened and selected thePrakriti samples. H.R., R.R., P.S., M.S. and K.S.J. collected blood samples and extracted DNA. P.G. performed genotyping and DNA sequencing with help of S.N., A.S. and V.J.. S.N. analyzed data under supervision of K.T.. P.G., S.N. and K.T. wrote manuscript and all the authors reviewed the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Kumarasamy Thangaraj.

Supplementary information

PDF files

1.
Supplementary Information

Mirror: http://tinyurl.com/nev29o2

In the laukika-lokottara research methodology -- a continuing tribute to Prof. Shrinivas Tilak -- of unraveling the traditions handed down to us from time immemorial, it is seen that the written documentation in Indus Script Corpora and the traditions enshrined in annual festivities of people in the Indian sprachbund continuum can be correlated.

This may perhaps provide clues to an understanding of why the unique iconography of Gaṇeśa emerged.

I do NOT know when the iconography of Gaṇeśa emerged.

There are intimations that the import of the word gaṇa a synonym of kula, 'troop', can be traced to the days of the Rigveda, to a period earlier than ca. 8th millennium BCE. The evidence of RV 2.23 sukta abounds in extraordinary metaphors and is presented herein based on Sayana's commentary. Clearly, a multi-disciplinary enquiry guided by savants of the yajna tradition and the pramāṇam of the Veda is needed to further explore this stupendous interpretative challenge.

In the Indus Script Corpora, pōḷā is a celebration of metalwork, magnetite ore is pōḷa. kul'winnowing fan' rebus: kul is a troop, kol'working in iron', a celebration of metalwork.

The tradition of invoking Gaṇeśa attested in Rigveda 2.23.1 gaṇānāṃ tvā gaṇapatiṃ havāmahe is a celebration of the kaví ʻ wise ʼ RV., m. ʻ wise man, poet ʼ RV., °ika -- m. lex. Pa. Pk. kavi -- m., Pk. kaï -- m., Si. kivi ES 25 but ← Pa.(CDIAL 2964). This tradition is attested in Indus Script Corpora by the engravers denoting their metalwork catalogues using animal (elephant) and other hieroglyphs.

Toy animals made for the Pola festival especially celebrated by the Dhanoje Kunbis. (Bemrose, Colo. Derby - Russell, Robert Vane (1916). The Tribes and Castes of the Central Provinces of India: volume IV. Descriptive articles on the principal castes and tribes of the Central Provinces. London: Macmillan and Co., limited. p. 40).

See: http://bharatkalyan97.blogspot.in/2015/08/zebu-archaeometallurgy-legacy-of-india.html?view=timeslide

This tradition is traceable to the toys of Daimabad with animals drawn on wheeled vehicles.

Harappan Chariot toy kept at the Brooklyn University Museum

Oxen pulled Bronze chariot found at Daimabad in Maharshtra

chandrashekharasandprints.wordpress.com

Daimabad bronze chariot. c. 1500 BCE. 22X52X17.5 cm.

Buffalo. Daimabad bronze. Prince of Wales Museum, Mumbai.

Daimabad bronzes. Buffalo on four-legged platform attached to four solid wheels 31X25 cm.; elephanton four-legged platform with axles 25 cm.; rhinoceros on axles of four solid wheels 25X19 cm. (MK Dhavalikar, 'Daimabad bronzes' in: Harappan civilization, ed. by GL Possehl, New Delhi, 1982, pp. 361-6; SA Sali, Daimabad 1976-1979, New Delhi, 1986).

Decipherment of Indus Script Corpora has demonstrated that the animals are hieroglyphs denoting metalwork.

Elephant as hieroglyph

ibha 'elephant' karibha 'trunk of elephant' Rebus: ib 'iron' karba 'iron'

Elephant-head of śri gaṇeśa is signified by the hieroglyph: sangaDa 'joined animal parts' rebus: sangara 'proclamation'.

The orthographic style of ligaturing animal parts is an Indus Script tradition as may be seen from the following examples.

Slide 88. Three objects (harappa.com) Three terra cotta objects that combine human and animal features. These objects may have been used to tell stories in puppet shows or in ritual performances. On the left is a seated animal figurine with female head. The manner of sitting suggests that this may be a feline, and a hole in the base indicates that it would have been raised on a stick as a standard or puppet. The head is identical to those seen on female figurines with a fan shaped headdress and two cup shaped side pieces. The choker with pendant beads is also common on female figurines.

Material: terra cotta

Dimensions: 7.1 cm height, 4.8 cm length, 3.5 cm width

Harappa, 2384 Harappa Museum, HM 2082 Vats 1940: 300, pl. LXXVII, 67

In the center is miniature mask of horned deity with human face and bared teeth of a tiger. A large mustache or divided upper lip frames the canines, and a flaring beard adds to the effect of rage. The eyes are defined as raised lumps that may have originally been painted. Short feline ears contrast with two short horns similar to a bull rather than the curving water buffalo horns. Two holes on either side allow the mask to be attached to a puppet or worn as an amulet.

Material: terra cotta

Dimensions: 5.24 height, 4.86 width

Harappa

Harappa Museum, H93-2093

Meadow and Kenoyer, 1994

On the right is feline figurine with male human face. The ears, eyes and mouth are filled with black pigment and traces of black are visible on the flaring beard that is now broken. The accentuated almond shaped eyes and wide mouth are characteristic of the bearded horned deity figurines found at Harappa and Mohenjo-daro (no. 122, 123). This figurine was found in a sump pit filled with discarded goblets, animal and female figurines and garbage. It dates to the final phase of the Harappan occupation, around 2000 B. C.

Harappa, Lot 5063-1 Harappa Museum, H94-2311

Material: terra cotta Dimensions: 5.5 cm height, 12.4 cm length, 4.3 cm width

http://www.harappa.com/indus/88.html

Nahali (kol ‘woman’) and Santali (kul ‘tiger’; kol ‘smelter’).

masks/amulets and

Slide72. Two composite anthropomorphic / animal figurines from Harappa.Whether or not the attachable water buffalo horns were used in magic or other rituals, unusual and composite animals and anthropomorphic/animal beings were clearly a part of Indus ideology. The ubiquitous "unicorn" (most commonly found on seals, but also represented in figurines), composite animals and animals with multiple heads, and composite anthropomorphic/animal figurines such as the seated quadruped figurines with female faces, headdresses and tails offer tantalizing glimpses into a rich ideology, one that may have been steeped in mythology, magic, and/or ritual transformation. Approximate dimensions (W x H(L) x D) of the larger figurine: 3.5 x 7.1 x 4.8 cm. (Photograph by Richard H. Meadow)

Ligatured glyph on copper tablet. m571B (serpent-like tail, horns, body of ram, elephant trunk, hindlegs of tiger). Indus Valley Figurines: Slide #44

44. Elephant figurine head with painted designs from Harappa. Elephant trunk ligatured to a winnowing fan.

It is unknown whether elephants were domesticated in the Indus Civilization. However, one of the few elephant figurines from Harappa is a head with large stylized ears and red and white stripes painted across the face. This may mirror the custom of decorating domesticated elephants (red and white are common colors) for ceremonies or rituals that is still practiced in South Asia. Elephant bones have also been found at Harappa. Approximate dimensions (W x H(L) x D): 5.4 x 4.8 x 4.6 cm. (Photograph by Richard H. Meadow)

kul 'winnowing fan': kulya n. ʻ receptacle for burnt bones of a corpse ʼ MBh., ʻ winnowing basket ʼ lex. [Prob. ← Drav.: see kulāˊya -- ]Pa. kulla -- m. ʻ raft of basket work, winnowing basket ʼ, °aka -- m. ʻ crate ʼ; Pk. kullaḍa -- n. ʻ packet ʼ; A. kulā ʻ winnowing fan, hood of a snake ʼ; B. kul, °lā ʻ winnowing basket or fan ʼ; Or. kulā ʻ winnowing fan ʼ, °lāi ʻ small do. ʼ; Si. kulla, st. kulu -- ʻ winnowing basket or fan ʼ.(CDIAL 3350) Rebus: kol 'working in iron' kolle 'blacksmith' kolhe 'smelters'.

kúla n. ʻ herd, troop ʼ RV., ʻ race, family ʼ Pāṇ., ʻ noble family ʼ Mn., ʻ house ʼ MBh.

Pa. kula -- n. ʻ clan, household ʼ, Pk. kula -- n.m. ʻ family, house ʼ; Dm. kul ʻ house ʼ; Sh. (Lor.) d*lda -- kul ʻ grandfather's relations ʼ; K. kŏl m. ʻ family, race ʼ; S.kuru m. ʻ tribe, family ʼ, L. kull m., P. kul f.; WPah. bhad. kul n. ʻ sub -- caste, family ʼ; N. A. B. kul ʻ clan, caste, family ʼ, Or. kuḷa, OMth. kula; H. kul m. ʻ herd, clan, caste, family ʼ, Marw. kul; G. kuḷ n. ʻ family, tribe ʼ, M. kūḷ n., °ḷī f.; OSi. -- kolaṭ dat. ʻ family ʼ; -- Si. kulaya ʻ family, caste ʼ ← Pa. or Sk. -- Deriv. Or. kuḷā ʻ of good family ʼ, akuḷā ʻ illegitimate (of birth) ʼ.(CDIAL 3330)

Thus, kula connotes a गण the word embedded in the phrase: Gaṇeśa lit. 'supreme leader of the troop'.

Ganesha, late 7th–8th century. Central Vietnam. Lent by Museum of Cham Sculpture, Da Nang, Vietnam (5.1) | This four-armed form of the elephant-headed son of Shiva and Parvati is among the most sophisticated early Cham sculptures. #LostKingdoms

A scupture of Ganapati was found in 2020, in Yogyakarta Islamic University dated to c. 9th century.

A stone sculpture of Ganapati is seen in Bujang Valley museum (Malaysia).

Can we trace this ligaturing tradition to Indus writing?

Elephant head with stylized wide spread ears. Traces of red and white paint bands are visible on the face. Painting of elephants for ritual processions is a common practice in traditional India and the main colors are red and white.

This figurine may represent a tame elephant or an elephant that is being marked for sacrifice. Hand formed and incised.

Material: terra cotta

Dimensions: 4.8 cm height, 5.4 cm width, 4.6 cm breadth

Harappa, Lot 800-01

Harappa Museum, H87-348

Elephant, trunk of elephant: kar-ibha, ib; rebus: karba 'iron'; ib 'iron'.

Une tête d'éléphant en terre cuite de Nausharo (Pakistan)

In: Arts asiatiques. Tome 47, 1992. pp. 132-136. Jarrige Catherine

http://www.persee.fr/web/revues/home/prescript/article/arasi_0004-3958_1992_num_47_1_1330

The elephant head ligatured with a buffalo at Nausharo is a curtain-raiser for the practice of ligaturing in Indian tradition for utsava bera 'idols carried on processions'. The phrase utsava bera denotes that processions of the type shown on Mesopotamian cylinder seals or Mohenjo-daro tablets are trade processions for bera 'bargaining, trade'. Thus, the processions with hieroglyphs may be part of trade-exchange fairs of ancient times. It is significant that the utsava bera of Ganesa is shown together with a rat or mouse -- as vāhana: ibha'elephant' Rebus: ib 'iron'. mūṣa 'rat, mouse' Rebus: mūṣa 'crucible'. Thus both rat/mouse and elephant face ligatured to a body, are Meluhha hieroglyphs related to metallurgical processes.

Utsava bera pōḷā (zebu, bos indicus) may be seen in the processions during festival days of Utsava Nandi and veneration in temples on days of pradosham.

బేరము [ bēramu ] bēramu. [Skt.] n. An image. ప్రతిమ. "పంకములోని హైమబేరము." పర. v.

బేరము [ bēramu ] bēramu. [Tel.] n. Trade, dealing, a bargain, బేరముసారము or బేరసారము trade, &c. (సారము being a mere expletive.)బేరకాడు bēra-kāḍu. n. One who makes a bargain, a purchaser, buyer. కొనువాడు, బేరమాడువాడు. బేరకత్తె bēra-katte. n. A woman who bargains or purchases. బేరమాడు or బేరముచేయు bēram-āḍu. v. n. To bargain. బేరముపోవు to go on a trading journey. బేరి bēri. n. A man of the Beri or merchant caste.

उत्-सव b [p= 182,2] m. enterprise , beginning RV. i , 100 , 8 ; 102 , 1

पोळा [ pōḷā ] m (पोळ) A festive day for cattle,--the day of new moon of श्रावण or of भाद्रपद. Bullocks are exempted from labor; variously daubed and decorated; and paraded about in worship. The festival is held annually with processions of toys of animals drawn on toy carts, an evocation of the animals on carts shown in Daimabad. पोळ [ pōḷa ] The word pōḷa denotes: m A bull dedicated to the gods, marked with a trident and discus, and set at large. That is bos indicus, zebu which is a hieroglyph on Indus Script Corpora to signify 'magnetite'. पोलाद [ pōlāda ] n ( or P) Steel. पोलादी a Of steel.

īśa ईश a. [ईश्-क] 1 Owning, possessing, sharing, master or lord of; see below. -2 One who is com- pletely master of anything. -3 Capable of (with gen.) -4 Powerful, supreme. -शः 1 A lord, master; with gen. or in comp.; कथंचिदीशामनसांबभूवुः Ku.3.34 with great difficulty controlled (were masters of) their minds; so वागीश, सुरेश&c. -2 A husband. -3 A Rudra. -4 The number 11 (derived from the eleven Rudras). -5 N. of Śiva (as regent of the north-east quarter. -6 The Supreme god (परमेश्वर); व्यक्ताव्यक्तंभरतेविश्वमीश- मीड्यम्Śevt. Up.1.8; प्रसादयेत्वामहमीशमीड्यम् Bg.11.44. श्रीवत्सधामापररात्रईशः Bhāg.6.8.22. -शा 1 Supremacy, power, dominion, greatness. Śvet. Up.4.7. īś ईश् 2 Ā. (ईष्टे, ईशाञ्चक्रे, ऐशिष्ट, ईशिता, ईशितुम्, ईशित) 1 To rule, be master of, govern, command (with gen.); नायंगात्राणामीष्टे K.312 v.l.; अर्थानामीशिषेत्वंवयमपिचगिरा- मीश्महेयावदर्थम् Bh.3.3; sometimes with acc.; इमाँल्लोका- नीशतईशनीभिःŚvet. Up.3.1 (also used in the Veda with gen. of an infinitive or loc. of an abstract noun). -2To be able, have power; expressed by 'can'; माधुर्यमीष्टेहरिणान्ग्रहीतुम् R.18.13,14.38; कमिवेशतेरमयितुंनगुणाः Ki.6.24; U.7.4; Śi.1.38; Māl.1.13. -3 To act like a master, allow. -4 To own, possess. -5 To belong to. m. A master, lord, the Supreme Spirit. ईशा- बास्यमिदंसर्वम्Īśop. īśāvāsyamईशावास्यम् N. of the ईशावास्योपनिषद्, also called ईशोप- निषद्; the only instance of an upaniṣad included in a Saṁhitā (Vāj.4.1). īśāna ईशान a. [ईश्ताच्छील्येचानश्] 1 Owning, possessing, master or lord. -2 Reigning, ruling. -3 Wealthy, rich. -नः 1 A ruler, master, lord; ईशानोभूतभव्यस्य Kaṭh. Up.4.12.-2 N. of Śiva; ईशानसंदर्शनलालसानाम् Ku.7.56; K.1. -3 The Ārdrā Nakṣtra. -4 One of the Rudras. -5 The number 'eleven'. -6 The sun as a form of Śiva. पर्जन्योयमोमृत्युरीशानः Bṛi. Up.1. 4.11. -7 A Sādhya. -8 N. of Viṣṇu.

Utsava bera

utsava-bera — the icon which is taken out in procession on festivals.

The Uthsava_bera at Tirumala shrine is named Malayappan, the earliest reference to which is found in an inscription dated 1369 AD. This idol might have entered into the temple regimen with the rise of the Pancharathra School of worship. Malayappan is a very skillfully crafted, beautiful image, made of panchloha, standing three feet tall on a pedestal of fourteen inches. It does not greatly resemble the dhruva_bera. Yet, it has a very pleasing disposition and is modestly ornamented. His consorts Sridevi and Bhudevi (of about twenty-nine inches height) are on his either side. All services, processions and celebrations conducted outside the sanctum are rendered to Malayappan.

http://sreenivasaraos.com/tag/temple-iconography/

Bera Utsav is a regional festival celebrated in the Murshidabad district of the state of West Bengal. The annual event is organized at the historical and picturesque location of Lalbagh, which at one time was the home of the Nawabs and is located on the banks of River Bhagirathi. People throng the district of Murshidabad to witness this magnificent event. The event is held on the last Thursday of the Bhadra month of the traditional Bengali calendar.

utsavá m. ʻ enterprise ʼ RV., ʻ festival ʼ MBh. [√sū] Pa. ussava -- m. ʻ festival ʼ, Pk. ucchava -- , °chaa -- , ussava -- , ūsa°, ōsa° m., K. wŏċhav, °ċhuwu m.; S. uchaü, och°, ocho m. ʻ feast given to brahmans ʼ; Or. ucha ʻ festival ʼ, osā ʻ festival, vow ʼ. dīpōtsava -- , mahōtsava -- .(CDIAL 1876) 9979 mahōtsava m. ʻ great festival ʼ MBh. [mahā -- , utsavá -- ]Pk. mahocchava -- , °hōsava -- , °hussava -- , °hūsava -- m.; P. mahocchā m. ʻ celebration, appointment of a new mahout ʼ; H. mahochā m. ʻ great festival ʼ, OG.mochava m.(CDIAL 9979)dīpōtsava m. ʻ festival of lights ʼ BhavP. [dīpa -- , utsavá -- ]

Pk. dīvūsava -- m. ʻ new moon of Kārtik ʼ; N. deusi ʻ festival beginning on the 5th day of Diwāli ʼ.(CDIAL 6359)

In the Vaikhanasa temple, the immovable (Dhruva-bimba or dhruva-bera) main idol that is installed in the sanctum and to which main worship is offered (archa-murti) represents the primary aspect of the deity known as Vishnu (Vishnu-tattva). The other images in the temple which are worshipped each day during the ritual sequences are but the variations of the original icon (adi-murti). These other forms are emanations of the main idol, in successive stages. And, within the temple complex, each form is accorded a specific location; successively away from the Dhruva bera.

Just as the Vishnu of Rig-Veda takes three strides (trini pada vi-chakrama Vishnuh), the main idol (Dhruva – bera) installed in the temple too takes three forms which are represented by Kautuka-bera, Snapana-bera and Utsava-bera.

The Kautuka –bera (usually made of gems, stone, copper, silver, gold or wood and about 1/3 to 5/9 the size of the Dhruva-bera)receives all the daily worship(nitya-archana); the Snapana-bera (usually made of metal and smaller than Kautuka) receives ceremonial bath (abhisheka) and the occasional ritual- worship sequences(naimitta-archana); and, the Utsava-bera ( always made of metal ) is for festive occasions and for taking out in processions . To this, another icon is added .This is Bali – bera ( always made of shiny metal) taken out , daily , around the central shrine when food offerings are made to Indra and other devas, as well as to Jaya and Vijaya the doorkeepers of the Lord ; and to all the elements.

And, on occasions when a movable icon is used for daily worship, special rituals, and processions and for food-offering, it is known as Bhoga-bera.

These five forms together make Pancha bera or Pancha murti.

And again it is said, Purusha is symbolized by Kautuka bera; Satya by Utsava bera; Acchuta by Snapana bera; and Aniruddha by Bali bera.

To put these together in a combined form:

The main idol (Dhruva-bera) which is immovable represents Vishnu (Vishnu-tattva).
Purusha symbolized by Kautuka-bera is an emanation of the Dhruva-bera. Kautuka-bera is next in importance, and is an exact replica of the Dhruva-bimba. it is placed in the sanctum very close to Dhruva bera.
Satya symbolized by Utsava-bera (processional deity) emanates from Purusha represented Kautuka-bera. And, Utsava-bera is placed in the next pavilion outside the sanctum.
Achyuta symbolized by Snapana-bera emanates from Satya represented by Utsava-bera. Snapana-bera receives Abhisheka, the ceremonial bath; and, it is placed outside the sanctum in snapana-mantapam enclosure.
Aniruddhda symbolized by Bali-bera emanates from Achyuta represented by Snapana-bera. The food offerings are submitted to Balibera. And, it is placed farthest from the Dhruva-bhera residing in the sanctum.

These different icons are not viewed as separate or independent deities; but are understood as emanations from the original icon, Dhruva–bimba.

Symbolisms

The symbolisms associated with the four murtis (chatur-murti) are many; and are interesting. As said earlier; the four are said to compare with the strides taken by Vishnu/Trivikrama. The main icon represents Vishnu who is all-pervasive, but, does not move about. When the worship sequences are conducted, the spirit (tejas) of the main idol moves into the Kautuka,-bera, which rests on the worship pedestal (archa-pitha). This is the first stride of Vishnu.Again, at the time of offering ritual bath, the tejas of the main idol moves into the Snapana-bera which is placed in the bathing-enclosure (snapana –mantapa). This is the second stride taken by Vishnu. And, the third stride is that when the Utsava-bera is taken out in processions. This is when the tejas of the Main idol reaches out to all.

In Marichi’s Vimana-archa-kalpa the five forms, five types of icons, the pancha-murti (when Vishnu is also counted along with the other four forms) are compared to five types of Vedic sacred fires (pancha-agni): garhapatya; ahavaniya; dakshinAgni; anvaharya; and sabhya. These in turn are compared to the primary elements (earth, water, fire, air, and space). And, the comparison is extended to five vital currents (prana, apana, vyana, udana and samana).

Further it is explained; the Vaikhanasa worship-tradition retained the concept of Pancha-Agni, but transformed them into five representations of Vishnu (pancha –murthi): Vishnu, Purusha, Satya, Achyuta and Aniruddha. And, that again was rendered into five types of temple deities as pancha-bera: Dhruva, Kautuka, Snapana, Utsava and Bali.

[The Vaikhanasa concept of five forms of Godhead parallels with that of Pancharatara which speaks of: Para, Vyuha, Vibhava, Antaryamin and Archa. Of these, Para is the absolute form, the cause of all existence and it is beyond intellect. Vyuha are the emanations from Para for sustaining creation. The Vyuha, in turn, assumes five worship-worthy forms: Vishnu, Purusha, Satya, Achyuta and Aniruddha. Vibhava represent the Avatars for destroying the evil, uplifting the virtuous and maintain balance in the world. Antaryamin is the inbeing who resides as jiva in all creatures. And, Archa is the most easily accessible form; the form which protects the devotees and eliminates their sorrows. This is the form that is worshipped in the temples.]

http://creative.sulekha.com/tantra-agama-part-four-vaikhanasa-continued_591617_blog

Source: agnyāyatanaṁ and agnihotrahomaḥ colophon: punarādheyam

http://muktalib5.org/VEDIC_ROOT/TEXTS/JOGLEKAR/JOGLEKAR-PDF/J0045.pdf

गणा f. N. of one of the mothers in स्कन्द's retinue MBh. ix , 2645 (cf. अहर्- , मर्/उद्- , व्/ऋष- , स्/अ- , सप्त्/अ- , स्/अर्व- ; देव-,महा- ,andविद-गण्/अ.) गण [p=343,1] m. a flock , troop , multitude , number , tribe , series , class (of animate or inanimate beings) , body of followers or attendants RV. AV.&c troops or classes of inferior deities (especially certain troops of demi-gods considered as शिव's attendants and under the special superintendence of the god गणे*श ; cf. -देवता) Mn. Ya1jn5. Lalit. &c a single attendant of शिव VarBr2S. Katha1s. Ra1jat. iii , 270N. of गणे*श W.a company , any assemblage or association of men formed for the attainment of the same aims Mn. Ya1jn5. Hit.m. a particular group of सामन्s La1t2y. i , 6 , 5 VarYogay. viii , 7

Source: http://muktalib5.org/VEDIC_ROOT/vedic_library.htm

  ।

   ॥
   ॥

RV_2,023.01a gaṇānāṃ tvā gaṇapatiṃ havāmahe kaviṃ kavīnām upamaśravastamam |
RV_2,023.01c jyeṣṭharājam brahmaṇām brahmaṇas pata ā naḥ śṛṇvann ūtibhiḥ sīda sādanam ||
RV_2,023.02a devāś cit te asurya pracetaso bṛhaspate yajñiyam bhāgam ānaśuḥ |
RV_2,023.02c usrā iva sūryo jyotiṣā maho viśveṣām ij janitā brahmaṇām asi ||
RV_2,023.03a ā vibādhyā parirāpas tamāṃsi ca jyotiṣmantaṃ ratham ṛtasya tiṣṭhasi |
RV_2,023.03c bṛhaspate bhīmam amitradambhanaṃ rakṣohaṇaṃ gotrabhidaṃ svarvidam ||
RV_2,023.04a sunītibhir nayasi trāyase janaṃ yas tubhyaṃ dāśān na tam aṃho aśnavat |
RV_2,023.04c brahmadviṣas tapano manyumīr asi bṛhaspate mahi tat te mahitvanam ||
RV_2,023.05a na tam aṃho na duritaṃ kutaś cana nārātayas titirur na dvayāvinaḥ |
RV_2,023.05c viśvā id asmād dhvaraso vi bādhase yaṃ sugopā rakṣasi brahmaṇas pate ||
RV_2,023.06a tvaṃ no gopāḥ pathikṛd vicakṣaṇas tava vratāya matibhir jarāmahe |
RV_2,023.06c bṛhaspate yo no abhi hvaro dadhe svā tam marmartu ducchunā harasvatī ||
RV_2,023.07a uta vā yo no marcayād anāgaso 'rātīvā martaḥ sānuko vṛkaḥ |
RV_2,023.07c bṛhaspate apa taṃ vartayā pathaḥ sugaṃ no asyai devavītaye kṛdhi ||
RV_2,023.08a trātāraṃ tvā tanūnāṃ havāmahe 'vaspartar adhivaktāram asmayum |
RV_2,023.08c bṛhaspate devanido ni barhaya mā durevā uttaraṃ sumnam un naśan ||
RV_2,023.09a tvayā vayaṃ suvṛdhā brahmaṇas pate spārhā vasu manuṣyā dadīmahi |
RV_2,023.09c yā no dūre taḷito yā arātayo 'bhi santi jambhayā tā anapnasaḥ ||
RV_2,023.10a tvayā vayam uttamaṃ dhīmahe vayo bṛhaspate papriṇā sasninā yujā |
RV_2,023.10c mā no duḥśaṃso abhidipsur īśata pra suśaṃsā matibhis tāriṣīmahi ||
RV_2,023.11a anānudo vṛṣabho jagmir āhavaṃ niṣṭaptā śatrum pṛtanāsu sāsahiḥ |
RV_2,023.11c asi satya ṛṇayā brahmaṇas pata ugrasya cid damitā vīḷuharṣiṇaḥ ||
RV_2,023.12a adevena manasā yo riṣaṇyati śāsām ugro manyamāno jighāṃsati |
RV_2,023.12c bṛhaspate mā praṇak tasya no vadho ni karma manyuṃ durevasya śardhataḥ ||
RV_2,023.13a bhareṣu havyo namasopasadyo gantā vājeṣu sanitā dhanaṃ-dhanam |
RV_2,023.13c viśvā id aryo abhidipsvo mṛdho bṛhaspatir vi vavarhā rathāṃ iva ||
RV_2,023.14a tejiṣṭhayā tapanī rakṣasas tapa ye tvā nide dadhire dṛṣṭavīryam |
RV_2,023.14c āvis tat kṛṣva yad asat ta ukthyam bṛhaspate vi parirāpo ardaya ||
RV_2,023.15a bṛhaspate ati yad aryo arhād dyumad vibhāti kratumaj janeṣu |
RV_2,023.15c yad dīdayac chavasa ṛtaprajāta tad asmāsu draviṇaṃ dhehi citram ||
RV_2,023.16a mā na stenebhyo ye abhi druhas pade nirāmiṇo ripavo 'nneṣu jāgṛdhuḥ |
RV_2,023.16c ā devānām ohate vi vrayo hṛdi bṛhaspate na paraḥ sāmno viduḥ ||
RV_2,023.17a viśvebhyo hi tvā bhuvanebhyas pari tvaṣṭājanat sāmnaḥ-sāmnaḥ kaviḥ |
RV_2,023.17c sa ṛṇacid ṛṇayā brahmaṇas patir druho hantā maha ṛtasya dhartari ||
RV_2,023.18a tava śriye vy ajihīta parvato gavāṃ gotram udasṛjo yad aṅgiraḥ |
RV_2,023.18c indreṇa yujā tamasā parīvṛtam bṛhaspate nir apām aubjo arṇavam ||
RV_2,023.19a brahmaṇas pate tvam asya yantā sūktasya bodhi tanayaṃ ca jinva |
RV_2,023.19c viśvaṃ tad bhadraṃ yad avanti devā bṛhad vadema vidathe suvīrāḥ ||

r.s.i: gr.tsamada (a_n:girasa s'aunahotra pas'ca_d) bha_rgava s'aunaka; devata_: br.haspati, 1-5,9,11,17,19 brahman.aspati; chanda: jagati_, 15,19 tris.t.up; Anuva_ka III

2.023.01 We invoke the Brahman.aspati, chief leaderof the (heavenly) bands; a sage of sage; abounding beyond measure in (every kind of) food;best lord of prayer; hearing our invocations, come with your protections, and sit down in the chamber of sacrifice. [Brahman.aspati = brahman.o annasya parivr.d.hasya karman.o va_ pa_layita_, the protector or cherisher of food,or of any great or solemn acts of devotion; he has other attributes in the text, as, gan.a_na_m gan.apatih, chief of the gan.as (inferior deities); jyes.t.hara_jam brahman.a_m, the best lord of mantras, or prayers: pras'asyam sva_minam mantra_n.a_m].
2.023.02 Br.haspati, destroyer of the asuras, through you the intelligent gods have obtained the sacrificialportion; in like manner as the adorable sun generates the (solar) rays by his radiance, so are you the generator of all prayers. [Br.haspati = Brahman.aspati; perhaps Br.haspati is of a more martial character; his protection is souhght for against enemies and evil spirits; perhaps, br.hata_m veda_na_m pa_lakah: br.hat = mantra, br.hato mantrasya, sva_min].
2.023.03 Having repelled revilers and (dispersed) the darkness you stand Br.haspati, on the radiant chariot of sacrifice, (which is) formidable (to foes), the humiliator of enemies, the destroyer of evil spirits, the cleaver of the clouds, the attainer of heaven.
2.023.04 You lead men, Br.haspati, by virtuous instructions; you preserve them (from calamity); sin will never overtake him who presents (offerings) to you; you are the afflicter of him who hates (holy) prayers; you are the punisher of wrath; such is your great mightiness. [Him who hates holy prayers: brahmadvis.ah = those who hate either the bra_hman.as,or the mantras or prayers].
2.023.05 The man whom you, Brahman.aspati, a kind protector, defend, neither sorrow nor sin, nor adversaries nor dissemblers ever harm, for you drive away from him all injurious (things).
2.023.06 You, Br.haspati, are our protector and the guide of (our) path; (you are) the discerner (of all things); we worship with praises for your adoration; may his own precipitate malice involve him (in destruction) who practises deceit against us.
2.023.07 Turn aside from (the true) path, Br.haspati, the arrogant and savage man who advances to injure us, although unoffending and keep us in the right way for (the completion of) this offering to the gods.
2.023.08 Br.haspati, defender (from calamity), we invoke you, the protector of our persons, the speaker of encouraging words and well disposed towards us; do you destroy the revilers of the gods; let not the malevolent attain supreme felicity.
2.023.09 Through you, Brahman.aspati, (our) benefactor, may we obtain desirable wealth from men destroy those (our) unrighteous enemies, whether nigh or far off, who prevail against us.
2.023.10 Through you, Br.haspati, (who are) the fulfiller of our desires; pure, and associated (with us), we possess excellent food; let not the wicked man who wishes to deceive us be our master; but let us, excelling in (pious) praises, attain (prosperity).
2.023.11 You, Brahman.aspati, who have no requiter (of your bounty), who are the showerer (of benefits), the repairer to combat, the consumer of foes, the victor in battles, you are true, the discharger of debts, the humiliator of the fierce and of the exulting.
2.023.12 Let not, Br.haspati, the murderous (weapon) of that man reach us, who, with unrighteous mind, seeks to harm us; who, fierce and arrogant, designs to kill (your) worshippers; may we baffle the wrath of the strong evil-doer].
2.023.13 Br.haspati is to be invoked in battles; he is to be approached with reverence; he who moves amidst combats, the distributor of repeated wealth; the lord Br.haspati has verily overturned all the assailing malignant (hosts), like chariots (overturned in battle).
2.023.14 Consume with your brightest (weapon) the ra_ks.asas, who have held your witnessed prowess in disdain; manifest, Br.haspati, your glorified (vigour), such as it was (of old), and destroy those who speak against you.
2.023.15 Br.haspati, born of truth, grant us that wonderful treasure, wherewith the pious man may worship exceedingly; that (wealth) which shines amongst men; which is endowed with lustre, (is) the means of (performing holy) rites, and invogirates (its possessor) with strength. [dravin.am citram = lit., various or wonderful wealth; in the Bra_hman.as it is interpreted as brahma varcas or tejas, brahmanical virtue or energy (cf. Yajus. 26.3; dravin.am = dhanam (Aitareya Bra_hman.a 4.11)].
2.023.16 Deliver us not to the thieves, the enemies delighting in violence, who seize ever upon the food (of others); those who cherish in their hearts the abandonment (of the gods); (they), Br.haspati, who do not know the extent of (your) power (against evil spirits). [Who do not know the extenf of your power: na parah sa_mno viduh = ye puma_msah sa_mnah sa_maya_t tvattah parah parasta_d anyadukr.s.t.am sa_ma yad raks.oghnam na ja_nanti, those men who do not know anything greater than the faculty of destroying ra_ks.asas, derived from you made up of that faculty; sa_ma vai raks.oha = sa_ma is the killer of ra_ks.asas].
2.023.17 Tvas.t.a_ engendered you (chief) amongst all beings, (whence) you are the reciter of many a holy hymn: Brahman.aspati acknowledges a debt to the performer of a sacred rite; he is the acquitter (of the debt), and the destoyer of the oppressor. [When you are the reciter: sa_mnah sa_mnah kavih, the reicter or another of every sa_ma, sarvasya sa_mnah ucca_rayita_ karta_si; or kavi refers to tvas.t.a_, further explained as the sage who created Brahman.aspati by the efficacy of the sa_ma: sa_mnah sa_ren.a tvam aji_janat; acknowledges a debt: r.n.acit stotr.ka_mam r.n.am iva cinoti, he takes the intention of the praiser as if it was a debt, or obligation; acquitter of the debt: r.n.aya is explained as the discharger or remover of the debt which is of the nature of sin: pa_paru_pasya r.n.asya pr.thak karta_].
2.023.18 When Br.haspati, descendant of An:giras, for your glory, Parvata had concealed the herd o fkine, you did set them free, and with thine associate, Indra, did send down the ocean of water which had been enveloped by darkness.
2.023.19 Brahman.aspati, who are the regulator of this (world), understand (the purport) of (our) hymn, and grant us posterity; for all is prosperous that the gods protect; (and therefore) may we blessed with excellent descendants, glorify you at this sacrifice. [Yajus. 34.58; vadema = may we declare or glorify you; or, let us speak, let what we ask be given to us;let it be enjoyed by us: di_yata_m bhujyata_m ucca_rayema].

Meaning:
1: Om, O Ganapati, To You Who are the Lord of the Ganas (Celestial Attendants or Followers), weOffer our Sacrificial Oblations,
2: You are the Wisdom of the Wise and the Uppermost in Glory,
3: You are the Eldest Lord (i.e. ever Unborn) and is of the Nature of Brahman (Absolute Consciousness); You are the Embodiment of the Sacred Pranava (Om),
4: Please come to us by Listening to our Prayers and be Present in the Seat of this Sacred Sacrificial Altar.
5: Om, our Prostrations to the Mahaganadhipati (the Great Lord of the Ganas).

http://www.greenmesg.org/mantras_slokas/sri_ganesha-gananam_tva_ganapatim.php

Pañcāyatana pūjā is worship of Gaṇeśa, Vishnu, Shiva, Devī, and Sūrya.

Gaṇeśa Nrtya Walters Art Museum.

S. Kalyanaraman
Sarasvati Research Center
November 2, 2015

CRY My Beloved Country

Dr Mrs Hilda Raja,

Vadodara, Gujarat.

South China Sea disputes increasing demand for US security presence: Pentagon chief

Ramayana, with a Mughal brush

Mughal rulers encouraged the creation of some of the most iconic Hindu art.

"Krishna Holds Up Mount Govardhan to Shelter the Villagers of Braj", Folio from a Harivamsa (The Legend of Hari (Krishna))

"A Muslim Pilgrim Learns a Lesson in Piety from a Brahman", Folio from a Khamsa (Quintet) of Amir Khusrau Dihlavi

The Goddess Bhairavi Devi with Shiva

Abstract

Introduction

Results and Discussions

Methods

Selection of subjects and Prakriti assessment

High throughput genotyping, their quality control criteria and resequencing

Genotyping

Detection of technical artifacts

Targeted resequencing

Sanger sequencing

Indian, HapMap and 1000 genome project sample details

Imputation and their relationship with ancestry

Population stratification

Association analysis

Addressing issue of population stratification as possible confounder in association analysis

Statistical determination of Prakriti in subjects

Phenotype and genotype correlation

Additional Information

References

Acknowledgements

Author information

Author notes

Affiliations

CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India

School of Life Sciences, Manipal University, Manipal, Karnataka, India

Shri Dharmasthala Manjunatheshwara College of Ayurveda, Udupi, Karnataka, India

Sinhgad College of Engineering, Pune, Maharashtra, India

Foundation for Revitalization of Local Health Traditions, Bangalore, Karnataka, India

Department of Statistics, Manipal University, Manipal, Karnataka, India

Interdisciplinary School of Health Sciences, University of Pune, Pune, Maharashtra, India

Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bangalore, Karnataka, India

Contributions

Competing interests

Corresponding author

Supplementary information

PDF files

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