Xuanyao Liu

Deep whole-genome sequencing of 100 southeast Asian Malays.

Whole-genome sequencing across multiple samples in a population provides an unprecedented opportunity for comprehensively characterizing the polymorphic variants in the population. Although the 1000 Genomes Project (1KGP) has offered brief insights into the value of population-level sequencing, the low coverage has compromised the ability to confidently detect rare and low-frequency variants. In addition, the composition of populations in the 1KGP is not complete, despite the fact that the study design has been extended to more than 2,500 samples from more than 20 population groups. The Malays are one of the Austronesian groups predominantly present in Southeast Asia and Oceania, and the Singapore Sequencing Malay Project (SSMP) aims to perform deep whole-genome sequencing of 100 healthy Malays. By sequencing at a minimum of 30× coverage, we have illustrated the higher sensitivity at detecting low-frequency and rare variants and the ability to investigate the presence of hotspots of functional mutations. Compared to the low-pass sequencing in the 1KGP, the deeper coverage allows more functional variants to be identified for each person. A comparison of the fidelity of genotype imputation of Malays indicated that a population-specific reference panel, such as the SSMP, outperforms a cosmopolitan panel with larger number of individuals for common SNPs. For lower-frequency (<5%) markers, a larger number of individuals might have to be whole-genome sequenced so that the accuracy currently afforded by the 1KGP can be achieved. The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing, especially in populations that are poorly represented in population-genetics studies.

Comparing methods for performing trans-ethnic meta-analysis of genome-wide association studies

Genome-wide association studies (GWASs) have discovered thousands of variants that are associated with human health and disease. Whilst early GWASs have primarily focused on genetically homogeneous populations of European, East Asian and South Asian ancestries, the next-generation genome-wide surveys are starting to pool studies from ethnically diverse populations within a single meta-analysis. However, classical epidemiological strategies for meta-analyses that assume fixed- or random-effects may not be the most suitable approaches to combine GWAS findings as these either confer low statistical power or identify mostly loci where the variants carry homogeneous effect sizes that are present in most of the studies. In a trans-ethnic meta-analysis, it is likely that some genetic loci will exhibit heterogeneous effect sizes across the populations. This may be due to differences in study designs, differences arising from the interactions with other genetic variants, or genuine biological differences attributed to environmental, dietary or lifestyle factors that modulate the influence of the genes. Here we compare different strategies for meta-analyzing GWAS across genetically diverse populations, where we intentionally vary the effect sizes present across the different populations. We subsequently applied the methods that yielded the highest statistical power to a trans-ethnic meta-analysis of seven GWAS in type 2 diabetes, and showed that these methods identified bona fide associations that would otherwise have been missed by the classical strategies.

Detecting and Characterizing Genomic Signatures of Positive Selection in Global Populations

Natural selection is a significant force that shapes the architecture of the human genome and introduces diversity across global populations. The question of whether advantageous mutations have arisen in the human genome as a result of single or multiple mutation events remains unanswered except for the fact that there exist a handful of genes such as those that confer lactase persistence, affect skin pigmentation, or cause sickle cell anemia. We have developed a long-range-haplotype method for identifying genomic signatures of positive selection to complement existing methods, such as the integrated haplotype score (iHS) or cross-population extended haplotype homozygosity (XP-EHH), for locating signals across the entire allele frequency spectrum. Our method also locates the founder haplotypes that carry the advantageous variants and infers their corresponding population frequencies. This presents an opportunity to systematically interrogate the whole human genome whether a selection signal shared across different populations is the consequence of a single mutation process followed subsequently by gene flow between populations or of convergent evolution due to the occurrence of multiple independent mutation events either at the same variant or within the same gene. The application of our method to data from 14 populations across the world revealed that positive-selection events tend to cluster in populations of the same ancestry. Comparing the founder haplotypes for events that are present across different populations revealed that convergent evolution is a rare occurrence and that the majority of shared signals stem from the same evolutionary event.

Insights into the Genetic Structure and Diversity of 38 South Asian Indians from Deep Whole-Genome Sequencing

South Asia possesses a significant amount of genetic diversity due to considerable intergroup differences in culture and language. There have been numerous reports on the genetic structure of Asian Indians, although these have mostly relied on genotyping microarrays or targeted sequencing of the mitochondria and Y chromosomes. Asian Indians in Singapore are primarily descendants of immigrants from Dravidian-language–speaking states in south India, and 38 individuals from the general population underwent deep whole-genome sequencing with a target coverage of 30X as part of the Singapore Sequencing Indian Project (SSIP). The genetic structure and diversity of these samples were compared against samples from the Singapore Sequencing Malay Project and populations in Phase 1 of the 1,000 Genomes Project (1 KGP). SSIP samples exhibited greater intra-population genetic diversity and possessed higher heterozygous-to-homozygous genotype ratio than other Asian populations. When compared against a panel of well-defined Asian Indians, the genetic makeup of the SSIP samples was closely related to South Indians. However, even though the SSIP samples clustered distinctly from the Europeans in the global population structure analysis with autosomal SNPs, eight samples were assigned to mitochondrial haplogroups that were predominantly present in Europeans and possessed higher European admixture than the remaining samples. An analysis of the relative relatedness between SSIP with two archaic hominins (Denisovan, Neanderthal) identified higher ancient admixture in East Asian populations than in SSIP. The data resource for these samples is publicly available and is expected to serve as a valuable complement to the South Asian samples in Phase 3 of 1 KGP.

Efficiency of trans-ethnic genome-wide meta-analysis and fine-mapping

Genome-wide association studies have seen unprecedented success in identifying genetic loci that correlate with disease susceptibility and severity. Early phases of these studies have predominantly been performed in the Caucasian populations. The next phase in medical genetics is to extend the exploration across genetically diverse populations to leverage on larger sample sizes for locating smaller effects that may be present in most human populations. However, discoveries from these studies do not actually reveal the underlying functional changes to the human genome, but only point to broad regions stipulated by the extent of linkage disequilibrium (LD). Fine-mapping the functional variants can, however, be hampered by extensive LD, which can yield multiple perfect surrogates that are not distinguishable from the underlying causal variants, although several studies have illustrated the value of relying on multiple genetically diverse populations to narrow the candidate regions where the functional variants can be found in. Here, we explore the efficiency of trans-ethnic meta-analysis in discovering genetic association and in fine-mapping the causal variants by asking: are there any population diversity metrics that will be useful for: (i) identifying the populations or genomic regions where meta-analysis are likely to be more successful for discovering associations?; (ii) identifying the populations or loci to perform deep targeted sequencing for the purpose of fine-mapping causal variants? Our results indicate that simple metrics like the FST or the population specificity of haplotypes are useful in trans-ethnic meta-analyses, while the degree of haplotype sharing and LD variation are informative of the efficiency in trans-ethnic fine-mapping.

A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse populations.

Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium.

Differential positive selection of malaria resistance genes in three indigenous populations of Peninsular Malaysia

The indigenous populations from Peninsular Malaysia, locally known as Orang Asli, continue to adopt an agro-subsistence nomadic lifestyle, residing primarily within natural jungle habitats. Leading a hunter-gatherer lifestyle in a tropical jungle environment, the Orang Asli are routinely exposed to malaria. Here we surveyed the genetic architecture of individuals from four Orang Asli tribes with high-density genotyping across more than 2.5 million polymorphisms. These tribes reside in different geographical locations in Peninsular Malaysia and belong to three main ethno-linguistic groups, where there is minimal interaction between the tribes. We first dissect the genetic diversity and admixture between the tribes and with neighboring urban populations. Later, by implementing five metrics, we investigated the genome-wide signatures for positive natural selection of these Orang Asli, respectively. Finally, we searched for evidence of genomic adaptation to the pressure of malaria infection. We observed that different evolutionary responses might have emerged in the different Orang Asli communities to mitigate malaria infection.

Detecting signatures of positive selection associated with musical aptitude in the human genome

Abilities related to musical aptitude appear to have a long history in human evolution. To elucidate the molecular and evolutionary background of musical aptitude, we compared genome-wide genotyping data (641 K SNPs) of 148 Finnish individuals characterized for musical aptitude. We assigned signatures of positive selection in a case-control setting using three selection methods: haploPS, XP-EHH and FST. Gene ontology classification revealed that the positive selection regions contained genes affecting inner-ear development. Additionally, literature survey has shown that several of the identified genes were known to be involved in auditory perception (e.g. GPR98, USH2A), cognition and memory (e.g. GRIN2B, IL1A, IL1B, RAPGEF5), reward mechanisms (RGS9), and song perception and production of songbirds (e.g. FOXP1, RGS9, GPR98, GRIN2B). Interestingly, genes related to inner-ear development and cognition were also detected in a previous genome-wide association study of musical aptitude. However, the candidate genes detected in this study were not reported earlier in studies of musical abilities. Identification of genes related to language development (FOXP1 and VLDLR) support the popular hypothesis that music and language share a common genetic and evolutionary background. The findings are consistent with the evolutionary conservation of genes related to auditory processes in other species and provide first empirical evidence for signatures of positive selection for abilities that contribute to musical aptitude.

Can Evidence from Genome-Wide Association Studies and Positive Natural Selection Surveys Be Used to Evaluate the Thrifty Gene Hypothesis in East Asians?

Body fat deposition and distribution differ between East Asians and Europeans, and for the same level of obesity, East Asians are at higher risks of Type 2 diabetes (T2D) and other metabolic disorders. This observation has prompted the reclassifications of body mass index thresholds for the definitions of “overweight” and “obese” in East Asians. However, the question remains over what evolutionary mechanisms have driven the differences in adiposity morphology between two population groups that shared a common ancestor less than 80,000 years ago. The Thrifty Gene hypothesis has been suggested as a possible explanation, where genetic factors that allowed for efficient food-energy conversion and storage are evolutionarily favoured by conferring increased chances of survival and fertility. Here, we leveraged on the existing findings from genome-wide association studies and large-scale surveys of positive natural selection to evaluate whether there is currently any evidence to support the Thrifty Gene hypothesis. We first assess whether the existing genetic associations with obesity and T2D are located in genomic regions that are reported to be under positive selection, and if so, whether the risk alleles sit on the extended haplotype forms. In addition, we interrogate whether these risk alleles are the derived forms that differ from the ancestral alleles, and whether there is significant evidence of population differentiation at these SNPs between East Asian and European populations. Our systematic survey did not yield conclusive evidence to support the Thrifty Gene hypothesis as a possible explanation for the differences observed between East Asians and Europeans.

Evaluating the possibility of detecting evidence of positive selection across Asia with sparse genotype data from the HUGO Pan-Asian SNP Consortium

BackgroundThe HUGO Pan-Asian SNP Consortium (PASNP) has generated a genetic resource of almost 55,000 autosomal single nucleotide polymorphisms (SNPs) across more than 1,800 individuals from 73 urban and indigenous populations in Asia. This has offered valuable insights into the correlation between the genetic ancestry of these populations with major linguistic systems and geography. Here, we attempt to understand whether adaptation to local climate, diet and environment partly explains the genetic variation present in these populations by investigating the genomic signatures of positive selection.ResultsTo evaluate the impact to the selection analyses due to the considerably lower SNP density as compared to other population genetics resources such as the International HapMap Project (HapMap) or the Singapore Genome Variation Project, we evaluated the extent of haplotype phasing switch errors and the consistency of selection signals from three haplotype-based approaches (iHS, XP-EHH, haploPS) when the HapMap data is thinned to a similar density as PASNP. We subsequently applied haploPS to detect and characterize positive selection in the PASNP populations, identifying 59 genomics regions that were selected in at least one PASNP populations. A cluster analysis on the basis of these 59 signals showed that indigenous populations such as the Negrito from Malaysia and Philippines, the China Hmong, and the Taiwan Ami and Atayal shared more of these signals. We also reported evidence of a positive selection signal encompassing the beta globin gene in the Taiwan Ami and Atayal that was distinct from the signal in the HapMap Africans, suggesting the possibility of convergent evolution at this locus due to malarial selection.ConclusionsWe established that the lower SNP content of the PASNP data conferred weaker ability to detect signatures of positive selection, but the availability of the new approach haploPS retained modest power. Out of all the populations in PASNP, we identified only 59 signals, suggesting a strong need for high-density population-level genotyping data or sequencing data in order to achieve a comprehensive survey of positive selection in Asian populations.