Search bioRxivSearch

Biology subjects

Dou, J.

Publications and source records attributed to Dou, J..

3 recordsLinked to original sources

Large-scale whole-genome sequencing of three diverse Asian populations in Singapore

Asian populations are currently underrepresented in human genetics research. Here we present whole-genome sequencing data of 4,810 Singaporeans from three diverse ethnic groups: 2,780 Chinese, 903 Malays, and 1,127 Indians. Despite a medium depth of 13.7x, we achieved essentially perfect (>99.8%) sensitivity and accuracy for detecting common variants and good sensitivity (>89%) for detecting extremely rare variants with <0.1% allele frequency. We found 89.2 million single-nucleotide polymorphisms (SNPs) and 9.1 million small insertions and deletions (INDELs), more than half of which have not been cataloged in dbSNP. In particular, we found 126 common deleterious mutations (MAF>0.01) that were absent in the existing public databases, highlighting the importance of local population reference for genetic diagnosis. We describe fine-scale genetic structure of Singapore populations and their relationship to worldwide populations from the 1000 Genomes Project. In addition to revealing noticeable amounts of admixture among three Singapore populations and a Malay-related novel ancestry component that has not been captured by the 1000 Genomes Project, our analysis also identified some fine-scale features of genetic structure consistent with two waves of prehistoric migration from south China to Southeast Asia. Finally, we demonstrate that our data can substantially improve genotype imputation not only for Singapore populations, but also for populations across Asia and Oceania. These results highlight the genetic diversity in Singapore and the potential impacts of our data as a resource to empower human genetics discovery in a broad geographic region.

genetics

DNA methylation signature of smoking in lung cancer is enriched for exposure signatures in newborn and adult blood.

BackgroundSmoking impacts DNA methylation genome-wide in blood of both newborns from maternal smoking during pregnancy and adults from personal smoking. Smoking causes lung cancer which involves aberrant methylation. We examined whether DNA methylation smoking signatures identified in blood of newborns and adults are detectable in lung tumors.\n\nMethodsWe compared smoking-related DNA methylation in lung adenocarcinomas (61 never smokers, 91 current smokers, and 238 former smokers) quantified with the Illumina450k BeadArray in The Cancer Genome Atlas with published large consortium meta-analyses of newborn and adult blood. We assessed whether CpG sites related to smoking in blood from newborns and adults were enriched in lung adenocarcinoma.\n\nResultsTesting CpGs differentially methylated by smoke exposure (P<10-4) we identified 296 in lung tumors, while previous meta-analyses (False Discovery Rate (FDR)<0.05) identified 6,073 in newborn blood, and for adult smoking, 18,760 in blood. The lung signals were highly enriched for those seen in newborn (32 overlapping, Penrichment=1.2x10-19) and adult blood (86 overlapping, Penrichment = 9.5x10-49). The 65 genes annotated to CpGs differentially methylated in lung tumors, but not blood, were enriched for RNA processing ontologies.\n\nConclusionsWe found highly significant overlap between smoking-related DNA methylation signals in lung cancer and those seen in blood from newborns, from in utero exposure, or adults, from their own exposure. These results suggest that some epigenetic alterations associated with cigarette smoke exposure are tissue specific, but others are common across tissues. These findings support the value of blood-based methylation biomarkers for assessing exposure effects in target tissues.

cancer biology

Cord blood buffy coat DNA methylation is comparable to whole cord blood methylation

BackgroundCord blood DNA methylation is associated with numerous health outcomes and environmental exposures. Whole cord blood DNA reflects all nucleated blood cell types, while centrifuging whole blood separates red blood cells by generating a white blood cell buffy coat. Both sample types are used in DNA methylation studies. Cell types have unique methylation patterns and processing can impact cell distributions, which may influence comparability.\n\nObjectivesTo evaluate differences in cell composition and DNA methylation between buffy coat and whole cord blood samples.\n\nMethodsCord blood DNA methylation was measured with the Infinium EPIC BeadChip (Illumina) in 8 individuals, each contributing buffy coat and whole blood samples. We analyzed principal components (PC) of methylation, performed hierarchical clustering, and computed correlations of mean-centered methylation between pairs. We conducted moderated t-tests on single sites and estimated cell composition.\n\nResultsDNA methylation PCs were associated with individual (PPC1=1.4x10-9; PPC2=2.9x10-5; PPC3=3.8x10-5; PPC4=4.2x10-6; PPC5=9.9x10-13), and not with sample type (PPC1-5>0.7). Samples hierarchically clustered by individual. Pearson correlations of mean-centered methylation between paired individual samples ranged from r=0.66 to r=0.87. No individual site significantly differed between buffy coat and whole cord blood when adjusting for multiple comparisons (5 sites had unadjusted P<10-5). Estimated cell type proportions did not differ by sample type (P=0.86), and estimated cell counts were highly correlated between paired samples (r=0.99).\n\nConclusionsDifferences in methylation and cell composition between buffy coat and whole cord blood are much lower than inter-individual variation, demonstrating that both sample preparation types can be analytically combined and compared.

epidemiology