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The genetic sequence variation of people from the Indian subcontinent who comprise one-quarter of the world's population, is not well described. We carried out whole genome sequencing of 168 South Asians, along with whole-exome sequencing of 147 South Asians to provide deeper characterisation of coding regions. We identify 12,962,155 autosomal sequence variants, including 2,946,861 new SNPs and 312,738 novel indels. This catalogue of SNPs and indels amongst South Asians provides the first comprehensive map of genetic variation in this major human population, and reveals evidence for selective pressures on genes involved in skin biology, metabolism, infection and immunity. Our results will accelerate the search for the genetic variants underlying susceptibility to disorders such as type-2 diabetes and cardiovascular disease which are highly prevalent amongst South Asians.

Alternative splicing is tightly regulated in a spatio-temporal and quantitative manner. This regulation is achieved by a complex interplay between spliceosomal (trans) factors that bind to different sequence (cis) elements. cis-elements reside in both introns and exons and may either enhance or silence splicing. Differential combinations of cis-elements allows for a huge diversity of overall splicing signals, together comprising a complex 'splicing code'. Many cis-elements have been identified, and their effects on exon inclusion levels demonstrated in reporter systems. However, the impact of interspecific differences in these elements on the evolution of alternative splicing levels has not yet been investigated at genomic level. Here we study the effect of interspecific differences in predicted exonic splicing regulators (ESRs) on exon inclusion levels in human and chimpanzee. For this purpose, we compiled and studied comprehensive datasets of predicted ESRs, identified by several computational and experimental approaches, as well as microarray data for changes in alternative splicing levels between human and chimpanzee. Surprisingly, we found no association between changes in predicted ESRs and changes in alternative splicing levels. This observation holds across different ESR exon positions, exon lengths, and 5' splice site strengths. We suggest that this lack of association is mainly due to the great importance of context for ESR functionality: many ESR-like motifs in primates may have little or no effect on splicing, and thus interspecific changes at short-time scales may primarily occur in these effectively neutral ESRs. These results underscore the difficulties of using current computational ESR prediction algorithms to identify truly functionally important motifs, and provide a cautionary tale for studies of the effect of SNPs on splicing in human disease.

Comparative genomics has revealed the ubiquity of gene and genome duplication and subsequent gene loss. In the case of gene duplication and subsequent loss, gene trees can differ from species trees, thus frequent gene duplication poses a challenge for reconstruction of species relationships. Here I address the case of multi-gene sets of putative orthologs that include some unrecognized paralogs due to ancestral gene duplication, and ask how outgroups should best be chosen to reduce the degree of non-species tree (NST) signal. Consideration of expected internal branch lengths supports several conclusions: (i) when a single outgroup is used, the degree of NST signal arising from gene duplication is either independent of outgroup choice, or is minimized by use of a maximally closely related post-duplication (MCRPD) outgroup; (ii) when two outgroups are used, NST signal is minimized by using one MCRPD outgroup, while the position of the second outgroup is of lesser importance; and (iii) when two outgroups are used, the ability to detect gene trees that are inconsistent with known aspects of the species tree is maximized by use of one MCRPD, and is either independent of the position of the second outgroup, or is maximized for a more distantly related second outgroup. Overall, these results generalize the utility of closely-related outgroups for phylogenetic analysis.

The question of how organisms adapt is among the most fundamental in evolutionary biology. Two recent studies investigated the evolution of Escherichia coli in response to challenge with the antibiotic cefotaxime. Studying five mutations in the beta-lactamase gene that together confer significant antibiotic resistance, the authors showed a complex fitness landscape that greatly constrained the identity and order of intermediates leading from the initial wildtype genotype to the final resistant genotype. Out of 18 billion possible orders of single mutations leading from non-resistant to fully-resistant form, they found that only 27 (1.5x10(-7)%) pathways were characterized by consistently increasing resistance, thus only a tiny fraction of possible paths are accessible by positive selection. I further explore these data in several ways.Allowing neutral changes (those that do not affect resistance) increases the number of accessible pathways considerably, from 27 to 629. Allowing multiple simultaneous mutations also greatly increases the number of accessible pathways. Allowing a single case of double mutation to occur along a pathway increases the number of pathways from 27 to 259, and allowing arbitrarily many pairs of simultaneous changes increases the number of possible pathways by more than 100 fold, to 4800. I introduce the metric 'repeatability,' the probability that two random trials will proceed via the exact same pathway. In general, I find that while the total number of accessible pathways is dramatically affected by allowing neutral or double mutations, the overall evolutionary repeatability is generally much less affected.These results probe the conceivable pathways available to evolution. Even when many of the assumptions of the analysis of Weinreich et al. (2006) are relaxed, I find that evolution to more highly cefotaxime resistant beta-lactamase proteins is still highly repeatable.

The monocyte chemotactic protein-1 (MCP-1) is a chemokine that plays an important role in the recruitment of monocytes to M. tuberculosis infection sites, and previous studies have reported that genetic variants in MCP1 are associated with differential susceptibility to pulmonary tuberculosis (PTB). We examined eight MCP1 single nucleotide polymorphisms (SNPs) in a multi-ethnic, case-control design that included: 321 cases and 346 controls from Guinea-Bissau, 258 cases and 271 controls from The Gambia, 295 cases and 179 controls from the U.S. (African-Americans), and an additional set of 237 cases and 144 controls of European ancestry from the U.S. and Argentina. Two locus interactions were also examined for polymorphisms in MCP1 and interleukin 12B (IL12B), another gene implicated in PTB risk. Examination of previously associated MCP1 SNPs rs1024611 (-2581A/G), rs2857656 (-362G/C) and rs4586 (+900C/T) did not show evidence for association. One interaction between rs2857656 and IL12B SNP rs2288831 was observed among Africans but the effect was in the opposite direction in Guineans (OR = 1.90, p = 0.001) and Gambians (OR = 0.64, p = 0.024). Our data indicate that the effect of genetic variation within MCP1 is not clear cut and additional studies will be needed to elucidate its role in TB susceptibility. [ABSTRACT FROM AUTHOR]

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension., Competing Interests: The authors have read the journal's policy and the authors of this manuscript have the following competing interests: Bruce M. Psaty (BMP) serves on the DSMB of a clinical trial funded by Zoll Lifecor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Barbara V. Howard (BVH) has a contract from National Heart, Lung, and Blood Institute (NHLBI). Brenda W.J.H. Penninx (BWJHP) has received research funding (non-related to the work reported here) from Jansen Research and Boehringer Ingelheim. Mike A. Nalls (MAN) is supported by a consulting contract between Data Tecnica International LLC and the National Institute on Aging (NIA), National Institutes of Health (NIH), Bethesda, MD, USA. MAN also consults for Illumina Inc., the Michael J. Fox Foundation, and the University of California Healthcare. MAN also has commercial affiliation with Data Tecnica International, Glen Echo, MD, USA. Mark J. Caulfield (MJC) has commercial affiliation and is Chief Scientist for Genomics England, a UK government company. OHF is supported by grants from Metagenics (on women's health and epigenetics) and from Nestlé (on child health). Peter S. Sever (PSS) is financial supported from several pharmaceutical companies which manufacture either blood pressure lowering or lipid lowering agents, or both, and consultancy fees. Paul W. Franks (PWF) has been a paid consultant in the design of a personalized nutrition trial (PREDICT) as part of a private-public partnership at Kings College London, UK, and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Terho Lehtimäki (TL) is employed by Fimlab Ltd. Ozren Polašek (OP) is employed by Gen‐info Ltd. There are no patents, products in development, or marked products to declare. All the other authors have declared no competing interests exist. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.

Alzheimer disease (AD) is the most common cause of dementia. As with many complex diseases, the identified variants do not explain the total expected genetic risk that is based on heritability estimates for AD. Isolated founder populations, such as the Amish, are advantageous for genetic studies as they overcome heterogeneity limitations associated with complex population studies. We determined that Amish AD cases harbored a significantly higher burden of the known risk alleles compared to Amish cognitively normal controls, but a significantly lower burden when compared to cases from a dataset of unrelated individuals. Whole-exome sequencing of a selected subset of the overall study population was used as a screening tool to identify variants located in the regions of the genome that are most likely to contribute risk. By then genotyping the top candidate variants from the known AD genes and from linkage regions implicated previous studies in the full dataset, new associations could be confirmed. The most significant result (p = 0.0012) was for rs73938538, a synonymous variant in LAMA1 within the previously identified linkage peak on chromosome 18. However, this association is specific to the Amish and did not generalize when tested in a dataset of unrelated individuals. These results suggest that additional risk variation in the Amish remains to be identified and likely resides outside of the classical protein coding gene regions.