Haplotype frequencies in a sub-region of chromosome 19q13.3, related to risk and prognosis of cancer, differ dramatically between ethnic groups

<p>Abstract</p> <p>Background</p> <p>A small region of about 70 kb on human chromosome 19q13.3 encompasses 4 genes of which 3, <it>ERCC1</it>, <it>ERCC2</it>, and <it>PPP1R13L </it>(aka <it>RAI</it>) are related to DNA repair and cell survival, and one, <it>CD3EAP</it>, aka <it>ASE1</it>, may be related to cell proliferation. The whole region seems related to the cellular response to external damaging agents and markers in it are associated with risk of several cancers.</p> <p>Methods</p> <p>We downloaded the genotypes of all markers typed in the 19q13.3 region in the HapMap populations of European, Asian and African descent and inferred haplotypes. We combined the European HapMap individuals with a Danish breast cancer case-control data set and inferred the association between HapMap haplotypes and disease risk.</p> <p>Results</p> <p>We found that the susceptibility haplotype in our European sample had increased from 2 to 50 percent very recently in the European population, and to almost the same extent in the Asian population. The cause of this increase is unknown. The maximal proportion of overall genetic variation due to differences between groups for Europeans versus Africans and Europeans versus Asians (the F_stvalue) closely matched the putative location of the susceptibility variant as judged from haplotype-based association mapping.</p> <p>Conclusion</p> <p>The combined observation that a common haplotype causing an increased risk of cancer in Europeans and a high differentiation between human populations is highly unusual and suggests a causal relationship with a recent increase in Europeans caused either by genetic drift overruling selection against the susceptibility variant or a positive selection for the same haplotype. The data does not allow us to distinguish between these two scenarios. The analysis suggests that the region is not involved in cancer risk in Africans and that the susceptibility variants may be more finely mapped in Asian populations.</p

Identifying Highly Conserved and Highly Differentiated Gene Ontology Categories in Human Populations

Detecting and interpreting certain system-level characteristics associated with human population genetic differences is a challenge for human geneticists. In this study, we conducted a population genetic study using the HapMap genotype data to identify certain special Gene Ontology (GO) categories associated with high/low genetic difference among 11 Hapmap populations. Initially, the genetic differences in each gene region among these populations were measured using allele frequency, linkage disequilibrium (LD) pattern, and transferability of tagSNPs. The associations between each GO term and these genetic differences were then identified. The results showed that cellular process, catalytic activity, binding, and some of their sub-terms were associated with high levels of genetic difference, and genes involved in these functional categories displayed, on average, high genetic diversity among different populations. By contrast, multicellular organismal processes, molecular transducer activity, and some of their sub-terms were associated with low levels of genetic difference. In particular, the neurological system process under the multicellular organismal process category had low levels of genetic difference; the neurological function also showed high evolutionary conservation between species in some previous studies. These results may provide a new insight into the understanding of human evolutionary history at the system-level

Signatures of Environmental Genetic Adaptation Pinpoint Pathogens as the Main Selective Pressure through Human Evolution

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes

Population and genomic lessons from genetic analysis of two Indian populations

Indian demographic history includes special features such as founder effects, interpopulation segregation, complex social structure with a caste system and elevated frequency of consanguineous marriages. It also presents a higher frequency for some rare mendelian disorders and in the last two decades increased prevalence of some complex disorders. Despite the fact that India represents about one-sixth of the human population, deep genetic studies from this terrain have been scarce. In this study, we analyzed high-density genotyping and whole-exome sequencing data of a North and a South Indian population. Indian populations show higher differentiation levels than those reported between populations of other continents. In this work, we have analyzed its consequences, by specifically assessing the transferability of genetic markers from or to Indian populations. We show that there is limited genetic marker portability from available genetic resources such as HapMap or the 1,000 Genomes Project to Indian populations, which also present an excess of private rare variants. Conversely, tagSNPs show a high level of portability between the two Indian populations, in contrast to the common belief that North and South Indian populations are genetically very different. By estimating kinship from mates and consanguinity in our data from trios, we also describe different patterns of assortative mating and inbreeding in the two populations, in agreement with distinct mating preferences and social structures. In addition, this analysis has allowed us to describe genomic regions under recent adaptive selection, indicating differential adaptive histories for North and South Indian populations. Our findings highlight the importance of considering demography for design and analysis of genetic studies, as well as the need for extending human genetic variation catalogs to new populations and particularly to those with particular demographic histories.International fellowship funded by Center for Neurogenomics and Cognitive Research (CNCR), VU, Amsterdam, The Netherlands to GJ; Research grant from J C Bose fellowship to BKT; grant # BT/01/COE/07/UDSC to BKT and salary support to GJ are gratefully acknowledged. FC was supported by a Beatriu de Pinós (2010-BP- B-00128) fellowship and MM by a PhD grant both from AGAUR (Generalitat de Catalunya). Funding to FC by grant SAF2012-35025 from the Ministerio de Economía y Competitividad (Spain); Funding to JB by grants BFU2010-19443 from the Ministerio de Ciencia y Tecnología (Spain), PRI-PIBIN-2011-0942 from the Ministerio de Economía y Competitividad (Spain), and from the Direcció General de Recerca, Generalitat de Catalunya (Grup de Recerca Consolidat 2009 SGR 1101).Peer Reviewe