Deep Whole-Genome Sequencing of 100 Southeast Asian Malays

Abstract

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.

Whole-genome sequencing analysis of phenotypic heterogeneity and anticipation in Li–Fraumeni cancer predisposition syndrome

“…SNV found in II:1, III:1, and III:4 (but not found in III:5 and III:6) were identified and are listed in Table S3. The whole-genome list of rare SNV was narrowed down to 11 candidate genes by selecting only exonic or splicing variants in conserved regions and by removing nonsynonymous variants and common variants found in dbSNP, 1000 Genome, and 100 Southeast Asian Malay whole-genome databases (13). Additionally, we detected one nonsynonymous de novo SNV in the child with adrenocortical carcinoma (ACC) (III:4), which was not present in any other member of the family.…”

“…1) (11). This family showed a clear tendency for accelerated cancer onset over three successive generations, with a probable (unconfirmed) carrier grandmother who developed breast cancer at age 38, a carrier mother who developed bilateral breast cancer at age 26-27, and a sister who developed osteosarcoma at age 26, and carrier children who developed rhabdomyosarcoma at age 8 mo and adrenal cortical carcinoma at age 6 mo, whereas two other siblings and two cousins are carriers who have yet to develop a cancer (current ages [6][7][8][9][10][11][12][13][14].…”

New insights into the genetics of X-linked dystonia-parkinsonism (XDP, DYT3)

“…Irregularities, however, have contested the accuracy of these oral histories, and they are currently not considered reliable from an anthropological point of view. 18 Nevertheless, we looked at publicly available genome sequences, 19 including those from a cohort of 100 Malaysians, 20 but found none of the XDP-associated genetic variants in these data sets, although one has to keep in mind the limited number of individuals investigated in these studies against the rarity of XDP-associated alleles.…”

Reconstructing genetic history of Siberian and Northeastern European populations

“…To examine the genetic relationships of Siberian and Eastern European populations relative to other populations in the world, we integrated publicly available raw sequencing data from 32 high-coverage modern genomes representing 18 populations (Supplemental Table S2; Wong et al 2013Wong et al , 2014Zhou et al 2013;Jeong et al 2014;Prufer et al 2014), ancient genomes (Supplemental Table S3), and variant calls from the two hominin genomes, the Neanderthal and Denisova individuals (Meyer et al 2012) in our analysis. We sought to minimize potential biases stemming from the use of different sequencing platforms, different read mapping tools, different SNP calling tools, and downstream variant filters.…”

“…To further understand the genetic relationships and ancient history of indigenous Northeastern European and Siberian populations, spanning thousands to tens of thousands of years, we performed deep genome sequencing of 28 individuals (with an average sequence coverage depth of 38×), representing 14 major ethnic groups from Northeastern Europe and Siberia, including undersurveyed Western Siberian groups (Table 1), and compared them to 32 publicly available high-coverage modern genomes from 18 populations (Supplemental Table S2; Wong et al 2013Wong et al , 2014Zhou et al 2013;Jeong et al 2014;Prufer et al 2014), two hominin genomes, the Neanderthal , and Denisova genomes (Meyer et al 2012), as well as 46 publicly available ancient genomes from other studies (Supplemental Table S3). …”