Deep whole-genome sequencing of 90 Han Chinese genomes

An effective strategy for assembling the sex-limited chromosome

BACKGROUND

Most currently available reference genomes lack the sequence map of sex-limited (such as Y and W) chromosomes, which results in incomplete assemblies that hinder further research on sex chromosomes. Recent advancements in long-read sequencing and population sequencing have provided the opportunity to assemble sex-limited chromosomes without the traditional complicated experimental efforts.

FINDINGS

We introduce the first computational method, Sorting long Reads of Y or other sex-limited chromosome (SRY), which achieves improved assembly results compared to flow sorting. Specifically, SRY outperforms in the heterochromatic region and demonstrates comparable performance in other regions. Furthermore, SRY enhances the capabilities of the hybrid assembly software, resulting in improved continuity and accuracy.

CONCLUSIONS

Our method enables true complete genome assembly and facilitates downstream research of sex-limited chromosomes.

Polymorphic USP8 allele promotes Parkinson's disease by inducing the accumulation of α-synuclein through deubiquitination

Parkinson's disease (PD) is one of the most common neuro-degenerative diseases characterized by α-synuclein accumulation and degeneration of dopaminergic neurons. Employing genome-wide sequencing, we identified a polymorphic USP8 allele (USP8D442G) significantly enriched in Chinese PD patients. To test the involvement of this polymorphism in PD pathogenesis, we derived dopaminergic neurons (DAn) from human-induced pluripotent stem cells (hiPSCs) reprogrammed from fibroblasts of PD patients harboring USP8D442G allele and their healthy siblings. In addition, we knock-in D442G polymorphic site into the endogenous USP8 gene of human embryonic stem cells (hESCs) and derived DAn from these knock-in hESCs to explore their cellular phenotypes and molecular mechanism. We found that expression of USP8D442G in DAn induces the accumulation and abnormal subcellular localization of α-Synuclein (α-Syn). Mechanistically, we demonstrate that D442G polymorphism enhances the interaction between α-Syn and USP8 and thus increases the K63-specific deubiquitination and stability of α-Syn . We discover a pathogenic polymorphism for PD that represent a promising therapeutic and diagnostic target for PD.

Core promoter in TNBC is highly mutated with rich ethnic signature

The core promoter plays an essential role in regulating transcription initiation by controlling the interaction between transcriptional factors and sequence motifs in the core promoter. Although mutation in core promoter sequences is expected to cause abnormal gene expression leading to pathogenic consequences, limited supporting evidence showed the involvement of core promoter mutation in diseases. Our previous study showed that the core promoter is highly polymorphic in worldwide human ethnic populations in reflecting human history and adaptation. Our recent characterization of the core promoter in triple-negative breast cancer (TNBC), a subtype of breast cancer, in a Chinese TNBC cohort revealed the wide presence of core promoter mutation in TNBC. In the current study, we analyzed the core promoter in a Thai TNBC cohort. We also observed rich core promoter mutation in the Thai TNBC patients. We compared the core promoter mutations between Chinese and Thai TNBC cohorts. We observed substantial differences of core promoter mutation in TNBC between the two cohorts, as reflected by the mutation spectrum, mutation-effected gene and functional category, and altered gene expression. Our study confirmed that the core promoter in TNBC is highly mutable, and is highly ethnic-specific.

Development of a multiplex panel with 31 multi-allelic InDels for forensic DNA typing

Insertion/Deletion (InDel) polymorphic genetic markers are abundant in human genomes. Diallelic InDel markers have been widely studied for forensic purposes, yet the low polymorphic information content limits their application and current InDel panels remain to be improved. In this study, multi-allelic InDels located out of low complexity sequence regions were selected in the datasets from East Asian populations, and a multiplex amplification system containing 31 multi-allelic InDel markers and the Amelogenin marker (FA-HID32plex) was constructed and optimized. The preliminary study on sensitivity, species specificity, inhibitor tolerance, mixture resolution, and the detection of degraded samples demonstrates that the FA-HID32plex is highly sensitive, specific, and robust for traces and degraded samples. The combined power of discrimination (CPD) of 31 multi-allelic InDel markers was 0.999 999 999 999 999 999 85, and the cumulative probability of exclusion (CPE) was 0.999 920 in a Chinese Han population, which indicates a high discrimination power. Altogether, the FA-HID32plex panel could provide reliable supplements or stand-alone information in individual identification and paternity testing, especially for challenging samples.

Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis

Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.

Pangenomic analysis of Chinese gastric cancer

Pangenomic study might improve the completeness of human reference genome (GRCh38) and promote precision medicine. Here, we use an automated pipeline of human pangenomic analysis to build gastric cancer pan-genome for 185 paired deep sequencing data (370 samples), and characterize the gene presence-absence variations (PAVs) at whole genome level. Genes ACOT1, GSTM1, SIGLEC14 and UGT2B17 are identified as highly absent genes in gastric cancer population. A set of genes from unaligned sequences with GRCh38 are predicted. We successfully locate one of predicted genes GC0643 on chromosome 9q34.2. Overexpression of GC0643 significantly inhibits cell growth, cell migration and invasion, cell cycle progression, and induces cell apoptosis in cancer cells. The tumor suppressor functions can be reversed by shGC0643 knockdown. The GC0643 is approved by NCBI database (GenBank: MW194843.1). Collectively, the robust pan-genome strategy provides a deeper understanding of the gene PAVs in the human cancer genome.

Human pan-genomics are increasing our knowledge of genomic diversity and genetic factors in disease. Here, the authors built a gastric cancer pan-genome that included the sequences of Chinese Han patients, and predicted putative and previously unaligned genes associated with gastric cancer.

Robust and accurate estimation of paralog-specific copy number for duplicated genes using whole-genome sequencing

The human genome contains hundreds of low-copy repeats (LCRs) that are challenging to analyze using short-read sequencing technologies due to extensive copy number variation and ambiguity in read mapping. Copy number and sequence variants in more than 150 duplicated genes that overlap LCRs have been implicated in monogenic and complex human diseases. We describe a computational tool, Parascopy, for estimating the aggregate and paralog-specific copy number of duplicated genes using whole-genome sequencing (WGS). Parascopy is an efficient method that jointly analyzes reads mapped to different repeat copies without the need for global realignment. It leverages multiple samples to mitigate sequencing bias and to identify reliable paralogous sequence variants (PSVs) that differentiate repeat copies. Analysis of WGS data for 2504 individuals from diverse populations showed that Parascopy is robust to sequencing bias, has higher accuracy compared to existing methods and enables prioritization of pathogenic copy number changes in duplicated genes.

Population-scale genotyping of structural variation in the era of long-read sequencing

Population-scale studies of structural variation (SV) are growing rapidly worldwide with the development of long-read sequencing technology, yielding a considerable number of novel SVs and complete gap-closed genome assemblies. Herein, we highlight recent studies using a hybrid sequencing strategy and present the challenges toward large-scale genotyping for SVs due to the reference bias. Genotyping SVs at a population scale remains challenging, which severely impacts genotype-based population genetic studies or genome-wide association studies of complex diseases. We summarize academic efforts to improve genotype quality through linear or graph representations of reference and alternative alleles. Graph-based genotypers capable of integrating diverse genetic information are effectively applied to large and diverse cohorts, contributing to unbiased downstream analysis. Meanwhile, there is still an urgent need in this field for efficient tools to construct complex graphs and perform sequence-to-graph alignments.

Crohn's Disease and Early Exposure to Thiopurines are Independent Risk Factors for Mosaic Chromosomal Alterations in Patients with Inflammatory Bowel Diseases

BACKGROUND AND AIMS

Mosaic chromosomal alterations [mCAs] increase the risk for haematopoietic malignancies and may be risk factors for several other diseases. Inflammatory bowel diseases [IBDs], including Crohn's disease [CD] and ulcerative colitis [UC], are associated with mCAs, and patients may be at risk for haematopoietic malignancy development and/or modification of IBD phenotypes. In the present study, we screened patients with IBD for the presence of mCAs and explored the possible pathophysiological and genetic risk factors for mCAs.

METHODS

We analysed mCAs in peripheral blood from 3339 patients with IBD and investigated the clinical and genetic risk factors for mCAs.

RESULTS

CD and exposure to thiopurines before the age of 20 years were identified as novel independent risk factors for mCAs [odds ratio = 2.15 and 5.68, p = 1.17e-2 and 1.60e-3, respectively]. In contrast, there were no significant associations of disease duration, anti-tumour necrosis factor alpha antibodies, or other clinical factors with mCAs. Gene ontology enrichment analysis revealed that genes specifically located in the mCAs in patients with CD were significantly associated with factors related to mucosal immune responses. A genome-wide association study revealed that ERBIN, CD96, and AC068672.2 were significantly associated with mCAs in patients with CD [p = 1.56e-8, 1.65e-8, and 4.92e-8, respectively].

CONCLUSIONS

The difference in mCAs between patients with CD and UC supports the higher incidence of haematopoietic malignancies in CD. Caution should be exercised when using thiopurines in young patients with IBD, particularly CD, in light of possible chromosomal alterations.

Etiological roles of core promoter variation in triple-negative breast cancer

Abnormal gene expression plays key role in cancer development. A core promoter is located around the transcriptional start site. Through interaction between core promoter sequences and transcriptional factors, core promoter controls transcriptional initiation. We hypothesized that in cancer, core promoter sequences could be mutated to interfere the interaction with transcriptional factors, resulting in altered transcriptional initiation and abnormal gene expression and cancer development. We used triple-negative breast cancer (TNBC) as a model to test our hypothesis. We collected genome-wide core promoter variants from 279 TNBC genomes. After extensive filtering of normal genomic polymorphism, we identified 19,427 recurrent somatic variants in 1,238 core promoters of 1,274 genes and 1,694 recurrent germline variants in 272 core promoters of 294 genes. Many of the affected genes were oncogenes and tumor suppressors. Analysis of RNA-seq data from the same patient cohort identified increased or decreased gene expression in 439 somatic and 85 germline variants-affected genes, and the results were validated by luciferase reporter assay. By comparing with the core promoter variation data from 610 unclassified breast cancer, we observed that core promoter variants in TNBC were highly TNBC-specific. We further identified the drugs targeting the genes with core promoter variation. Our study demonstrates that core promoter is highly mutable in cancer, and can play etiological roles in TNBC and other types of cancer through influencing transcriptional initiation.

Genetic architecture of gene regulation in Indonesian populations identifies QTLs associated with global and local ancestries

Lack of diversity in human genomics limits our understanding of the genetic underpinnings of complex traits, hinders precision medicine, and contributes to health disparities. To map genetic effects on gene regulation in the underrepresented Indonesian population, we have integrated genotype, gene expression, and CpG methylation data from 115 participants across three island populations that capture the major sources of genomic diversity in the region. In a comparison with European datasets, we identify eQTLs shared between Indonesia and Europe as well as population-specific eQTLs that exhibit differences in allele frequencies and/or overall expression levels between populations. By combining local ancestry and archaic introgression inference with eQTLs and methylQTLs, we identify regulatory loci driven by modern Papuan ancestry as well as introgressed Denisovan and Neanderthal variation. GWAS colocalization connects QTLs detected here to hematological traits, and further comparison with European datasets reflects the poor overall transferability of GWAS statistics across diverse populations. Our findings illustrate how population-specific genetic architecture, local ancestry, and archaic introgression drive variation in gene regulation across genetically distinct and in admixed populations and highlight the need for performing association studies on non-European populations.

Genetic Background of Mesalamine-induced Fever and Diarrhea in Japanese Patients with Inflammatory Bowel Disease

BACKGROUND

Some patients with inflammatory bowel disease (IBD) who were under mesalamine treatment develop adverse reactions called "mesalamine allergy," which includes high fever and worsening diarrhea. Currently, there is no method to predict mesalamine allergy. Pharmacogenomic approaches may help identify these patients. Here we analyzed the genetic background of mesalamine intolerance in the first genome-wide association study of Japanese patients with IBD.

METHODS

Two independent pharmacogenetic IBD cohorts were analyzed: the MENDEL (n = 1523; as a discovery set) and the Tohoku (n = 788; as a replication set) cohorts. Genome-wide association studies were performed in each population, followed by a meta-analysis. In addition, we constructed a polygenic risk score model and combined genetic and clinical factors to model mesalamine intolerance.

RESULTS

In the combined cohort, mesalamine-induced fever and/or diarrhea was significantly more frequent in ulcerative colitis vs Crohn's disease. The genome-wide association studies and meta-analysis identified one significant association between rs144384547 (upstream of RGS17) and mesalamine-induced fever and diarrhea (P = 7.21e-09; odds ratio = 11.2). The estimated heritability of mesalamine allergy was 25.4%, suggesting a significant correlation with the genetic background. Furthermore, a polygenic risk score model was built to predict mesalamine allergy (P = 2.95e-2). The combined genetic/clinical prediction model yielded a higher area under the curve than did the polygenic risk score or clinical model alone (area under the curve, 0.89; sensitivity, 71.4%; specificity, 90.8%).

CONCLUSIONS

Mesalamine allergy was more common in ulcerative colitis than in Crohn's disease. We identified a novel genetic association with and developed a combined clinical/genetic model for this adverse event.

Prioritising positively selected variants in whole-genome sequencing data using FineMAV

Background

In population genomics, polymorphisms that are highly differentiated between geographically separated populations are often suggestive of Darwinian positive selection. Genomic scans have highlighted several such regions in African and non-African populations, but only a handful of these have functional data that clearly associates candidate variations driving the selection process. Fine-Mapping of Adaptive Variation (FineMAV) was developed to address this in a high-throughput manner using population based whole-genome sequences generated by the 1000 Genomes Project. It pinpoints positively selected genetic variants in sequencing data by prioritizing high frequency, population-specific and functional derived alleles.

Results

We developed a stand-alone software that implements the FineMAV statistic. To graphically visualise the FineMAV scores, it outputs the statistics as bigWig files, which is a common file format supported by many genome browsers. It is available as a command-line and graphical user interface. The software was tested by replicating the FineMAV scores obtained using 1000 Genomes Project African, European, East and South Asian populations and subsequently applied to whole-genome sequencing datasets from Singapore and China to highlight population specific variants that can be subsequently modelled. The software tool is publicly available at https://github.com/fadilla-wahyudi/finemav.

Conclusions

The software tool described here determines genome-wide FineMAV scores, using low or high-coverage whole-genome sequencing datasets, that can be used to prioritize a list of population specific, highly differentiated candidate variants for in vitro or in vivo functional screens. The tool displays these scores on the human genome browsers for easy visualisation, annotation and comparison between different genomic regions in worldwide human populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04506-9.

NyuWa Genome resource: A deep whole-genome sequencing-based variation profile and reference panel for the Chinese population

The lack of haplotype reference panels and whole-genome sequencing resources specific to the Chinese population has greatly hindered genetic studies in the world's largest population. Here, we present the NyuWa genome resource, based on deep (26.2×) sequencing of 2,999 Chinese individuals, and construct a NyuWa reference panel of 5,804 haplotypes and 19.3 million variants, which is a high-quality publicly available Chinese population-specific reference panel with thousands of samples. Compared with other panels, the NyuWa reference panel reduces the Han Chinese imputation error rate by a margin ranging from 30% to 51%. Population structure and imputation simulation tests support the applicability of one integrated reference panel for northern and southern Chinese. In addition, a total of 22,504 loss-of-function variants in coding and noncoding genes are identified, including 11,493 novel variants. These results highlight the value of the NyuWa genome resource in facilitating genetic research in Chinese and Asian populations.

Building a Chinese pan-genome of 486 individuals

Pan-genome sequence analysis of human population ancestry is critical for expanding and better defining human genome sequence diversity. However, the amount of genetic variation still missing from current human reference sequences is still unknown. Here, we used 486 deep-sequenced Han Chinese genomes to identify 276 Mbp of DNA sequences that, to our knowledge, are absent in the current human reference. We classified these sequences into individual-specific and common sequences, and propose that the common sequence size is uncapped with a growing population. The 46.646 Mbp common sequences obtained from the 486 individuals improved the accuracy of variant calling and mapping rate when added to the reference genome. We also analyzed the genomic positions of these common sequences and found that they came from genomic regions characterized by high mutation rate and low pathogenicity. Our study authenticates the Chinese pan-genome as representative of DNA sequences specific to the Han Chinese population missing from the GRCh38 reference genome and establishes the newly defined common sequences as candidates to supplement the current human reference.

Characterization of structural variation in Tibetans reveals new evidence of high-altitude adaptation and introgression

BACKGROUND

Structural variation (SV) acts as an essential mutational force shaping the evolution and function of the human genome. However, few studies have examined the role of SVs in high-altitude adaptation and little is known of adaptive introgressed SVs in Tibetans so far.

RESULTS

Here, we generate a comprehensive catalog of SVs in a Chinese Tibetan (n = 15) and Han (n = 10) population using nanopore sequencing technology. Among a total of 38,216 unique SVs in the catalog, 27% are sequence-resolved for the first time. We systematically assess the distribution of these SVs across repeat sequences and functional genomic regions. Through genotyping in additional 276 genomes, we identify 69 Tibetan-Han stratified SVs and 80 candidate adaptive genes. We also discover a few adaptive introgressed SV candidates and provide evidence for a deletion of 335 base pairs at 1p36.32.

CONCLUSIONS

Overall, our results highlight the important role of SVs in the evolutionary processes of Tibetans' adaptation to the Qinghai-Tibet Plateau and provide a valuable resource for future high-altitude adaptation studies.

A data set of variants derived from 1455 clinical and research exomes is efficient in variant prioritization for early-onset monogenic disorders in Indians

Given the genomic uniqueness, a local data set is most desired for Indians, who are underrepresented in existing public databases. We hypothesize patients with rare monogenic disorders and their family members can provide a reliable source of common variants in the population. Exome sequencing (ES) data from families with rare Mendelian disorders was aggregated from five centers in India. The dataset was refined by excluding related individuals and removing the disease-causing variants (refined cohort). The efficiency of these data sets was assessed in a new set of 50 exomes against gnomAD and GenomeAsia. Our original cohort comprised 1455 individuals from 1203 families. The refined cohort had 836 unrelated individuals that retained 1,251,064 variants with 181,125 population-specific and 489,618 common variants. The allele frequencies from our cohort helped to define 97,609 rare variants in gnomAD and 44,520 rare variants in GenomeAsia as common variants in our population. Our variant dataset provided an additional 1.7% and 0.1% efficiency for prioritizing heterozygous and homozygous variants respectively for rare monogenic disorders. We observed additional 19 genes/human knockouts. We list carrier frequency for 142 recessive disorders. This is a large and useful resource of exonic variants for Indians. Despite limitations, datasets from patients are efficient tools for variant prioritization in a resource-limited setting.

Structural variation of the malaria-associated human glycophorin A-B-E region

BACKGROUND

Approximately 5% of the human genome shows common structural variation, which is enriched for genes involved in the immune response and cell-cell interactions. A well-established region of extensive structural variation is the glycophorin gene cluster, comprising three tandemly-repeated regions about 120 kb in length and carrying the highly homologous genes GYPA, GYPB and GYPE. Glycophorin A (encoded by GYPA) and glycophorin B (encoded by GYPB) are glycoproteins present at high levels on the surface of erythrocytes, and they have been suggested to act as decoy receptors for viral pathogens. They are receptors for the invasion of the protist parasite Plasmodium falciparum, a causative agent of malaria. A particular complex structural variant, called DUP4, creates a GYPB-GYPA fusion gene known to confer resistance to malaria. Many other structural variants exist across the glycophorin gene cluster, and they remain poorly characterised.

RESULTS

Here, we analyse sequences from 3234 diploid genomes from across the world for structural variation at the glycophorin locus, confirming 15 variants in the 1000 Genomes project cohort, discovering 9 new variants, and characterising a selection of these variants using fibre-FISH and breakpoint mapping at the sequence level. We identify variants predicted to create novel fusion genes and a common inversion duplication variant at appreciable frequencies in West Africans. We show that almost all variants can be explained by non-allelic homologous recombination and by comparing the structural variant breakpoints with recombination hotspot maps, confirm the importance of a particular meiotic recombination hotspot on structural variant formation in this region.

CONCLUSIONS

We identify and validate large structural variants in the human glycophorin A-B-E gene cluster which may be associated with different clinical aspects of malaria.

Legacy Data Confound Genomics Studies

Recent reports have identified differences in the mutational spectra across human populations. Although some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data are used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower quality data from the early phases of the 1kGP thus continue to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.

RETRACTED: CGVD: a genomic variation database for Chinese populations

Precision medicine calls upon deeper coverage of population-based sequencing and thorough gene-content and phenotype-based analysis, which lead to a population-associated genomic variation map or database. The Chinese Genomic Variation Database (CGVD; https://bigd.big.ac.cn/cgvd/) is such a database that has combined 48.30 million (M) SNVs and 5.77 M small indels, identified from 991 Chinese individuals of the Chinese Academy of Sciences Precision Medicine Initiative Project (CASPMI) and 301 Chinese individuals of the 1000 Genomes Project (1KGP). The CASPMI project includes whole-genome sequencing data (WGS, 25–30×) from ∼1000 healthy individuals of the CASPMI cohort. To facilitate the usage of such variations for pharmacogenomics studies, star-allele frequencies of the drug-related genes in the CASPMI and 1KGP populations are calculated and provided in CGVD. As one of the important database resources in BIG Data Center, CGVD will continue to collect more genomic variations and to curate structural and functional annotations to support population-based healthcare projects and studies in China and worldwide.

PGG.Han: the Han Chinese genome database and analysis platform

As the largest ethnic group in the world, the Han Chinese population is nonetheless underrepresented in global efforts to catalogue the genomic variability of natural populations. Here, we developed the PGG.Han, a population genome database to serve as the central repository for the genomic data of the Han Chinese Genome Initiative (Phase I). In its current version, the PGG.Han archives whole-genome sequences or high-density genome-wide single-nucleotide variants (SNVs) of 114 783 Han Chinese individuals (a.k.a. the Han100K), representing geographical sub-populations covering 33 of the 34 administrative divisions of China, as well as Singapore. The PGG.Han provides: (i) an interactive interface for visualization of the fine-scale genetic structure of the Han Chinese population; (ii) genome-wide allele frequencies of hierarchical sub-populations; (iii) ancestry inference for individual samples and controlling population stratification based on nested ancestry informative markers (AIMs) panels; (iv) population-structure-aware shared control data for genotype-phenotype association studies (e.g. GWASs) and (v) a Han-Chinese-specific reference panel for genotype imputation. Computational tools are implemented into the PGG.Han, and an online user-friendly interface is provided for data analysis and results visualization. The PGG.Han database is freely accessible via http://www.pgghan.org or https://www.hanchinesegenomes.org.

Genotype imputation and reference panel: a systematic evaluation on haplotype size and diversity

Here, 622 imputations were conducted with 394 customized reference panels for Han Chinese and European populations. Besides validating the fact that imputation accuracy could always benefit from the increased panel size when the reference panel was population specific, the results brought two new thoughts. First, when the haplotype size of the reference panel was fixed, the imputation accuracy of common and low-frequency variants (Minor Allele Frequency (MAF) > 0.5%) decreased while the population diversity of the reference panel increased, but for rare variants (MAF < 0.5%), a small fraction of diversity in panel could improve imputation accuracy. Second, when the haplotype size of the reference panel was increased with extra population-diverse samples, the imputation accuracy of common variants (MAF > 5%) for the European population could always benefit from the expanding sample size. However, for the Han Chinese population, the accuracy of all imputed variants reached the highest when reference panel contained a fraction of an extra diverse sample (8-21%). In addition, we evaluated the imputation performances in the existing reference panels, such as the Haplotype Reference Consortium (HRC), 1000 Genomes Project Phase 3 and the China, Oxford and Virginia Commonwealth University Experimental Research on Genetic Epidemiology (CONVERGE). For the European population, the HRC panel showed the best performance in our analysis. For the Han Chinese population, we proposed an optimum imputation reference panel constituent ratio if researchers would like to customize their own sequenced reference panel, but a high-quality and large-scale Chinese reference panel was still needed. Our findings could be generalized to the other populations with conservative genome; a tool was provided to investigate other populations of interest (https://github.com/Abyss-bai/reference-panel-reconstruction).

NARD: whole-genome reference panel of 1779 Northeast Asians improves imputation accuracy of rare and low-frequency variants

Here, we present the Northeast Asian Reference Database (NARD), including whole-genome sequencing data of 1779 individuals from Korea, Mongolia, Japan, China, and Hong Kong. NARD provides the genetic diversity of Korean (n = 850) and Mongolian (n = 384) ancestries that were not present in the 1000 Genomes Project Phase 3 (1KGP3). We combined and re-phased the genotypes from NARD and 1KGP3 to construct a union set of haplotypes. This approach established a robust imputation reference panel for Northeast Asians, which yields the greatest imputation accuracy of rare and low-frequency variants compared with the existing panels. NARD imputation panel is available at https://nard.macrogen.com/ .

Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome

To unravel the genetic mechanisms of disease and physiological traits, it requires comprehensive sequencing analysis of large sample size in Chinese populations. Here, we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative (CASPMI) project launched by the Chinese Academy of Sciences, including the de novo assembly of a northern Han reference genome (NH1.0) and whole genome analyses of 597 healthy people coming from most areas in China. Given the two existing reference genomes for Han Chinese (YH and HX1) were both from the south, we constructed NH1.0, a new reference genome from a northern individual, by combining the sequencing strategies of PacBio, 10× Genomics, and Bionano mapping. Using this integrated approach, we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1. In order to generate a genomic variation map of Chinese populations, we performed the whole-genome sequencing of 597 participants and identified 24.85 million (M) single nucleotide variants (SNVs), 3.85 M small indels, and 106,382 structural variations. In the association analysis with collected phenotypes, we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males. Moreover, significant genetic diversity in MTHFR, TCN2, FADS1, and FADS2, which associate with circulating folate, vitamin B12, or lipid metabolism, was observed between northerners and southerners. Especially, for the homocysteine-increasing allele of rs1801133 (MTHFR 677T), we hypothesize that there exists a "comfort" zone for a high frequency of 677T between latitudes of 35-45 degree North. Taken together, our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine.

HUPAN: a pan-genome analysis pipeline for human genomes

The human reference genome is still incomplete, especially for those population-specific or individual-specific regions, which may have important functions. Here, we developed a HUman Pan-genome ANalysis (HUPAN) system to build the human pan-genome. We applied it to 185 deep sequencing and 90 assembled Han Chinese genomes and detected 29.5 Mb novel genomic sequences and at least 188 novel protein-coding genes missing in the human reference genome (GRCh38). It can be an important resource for the human genome-related biomedical studies, such as cancer genome analysis. HUPAN is freely available at http://cgm.sjtu.edu.cn/hupan/ and https://github.com/SJTU-CGM/HUPAN .

A Vietnamese human genetic variation database

Large scale human genome projects have created tremendous human genome databases for some well-studied populations. Vietnam has about 95 million people (the 14th largest country by population in the world) of which more than 86% are Kinh people. To date, genetic studies for Vietnamese people mostly rely on genetic information from other populations. Building a Vietnamese human genetic variation database is a must for properly interpreting Vietnamese genetic variants. To this end, we sequenced 105 whole genomes and 200 whole exomes of 305 unrelated Kinh Vietnamese (KHV) people. We also included 101 other previously published KHV genomes to build a Vietnamese human genetic variation database of 406 KHV people. The KHV database contains 24.81 million variants (22.47 million single nucleotide polymorphisms (SNPs) and 2.34 million indels) of which 0.71 million variants are novel. It includes more than 99.3% of variants with a frequency of >1% in the KHV population. Noticeably, the KHV database revealed 107 variants reported in the human genome mutation database as pathological mutations with a frequency above 1% in the KHV population. The KHV database (available at https://genomes.vn) would be beneficial for genetic studies and medical applications not only for the Vietnamese population but also for other closely related populations.

Models of archaic admixture and recent history from two-locus statistics

We learn about population history and underlying evolutionary biology through patterns of genetic polymorphism. Many approaches to reconstruct evolutionary histories focus on a limited number of informative statistics describing distributions of allele frequencies or patterns of linkage disequilibrium. We show that many commonly used statistics are part of a broad family of two-locus moments whose expectation can be computed jointly and rapidly under a wide range of scenarios, including complex multi-population demographies with continuous migration and admixture events. A full inspection of these statistics reveals that widely used models of human history fail to predict simple patterns of linkage disequilibrium. To jointly capture the information contained in classical and novel statistics, we implemented a tractable likelihood-based inference framework for demographic history. Using this approach, we show that human evolutionary models that include archaic admixture in Africa, Asia, and Europe provide a much better description of patterns of genetic diversity across the human genome. We estimate that an unidentified, deeply diverged population admixed with modern humans within Africa both before and after the split of African and Eurasian populations, contributing 4 - 8% genetic ancestry to individuals in world-wide populations.

Deep whole-genome sequencing of 90 Han Chinese genomes

Next-generation sequencing provides a high-resolution insight into human genetic information. However, the focus of previous studies has primarily been on low-coverage data due to the high cost of sequencing. Although the 1000 Genomes Project and the Haplotype Reference Consortium have both provided powerful reference panels for imputation, low-frequency and novel variants remain difficult to discover and call with accuracy on the basis of low-coverage data. Deep sequencing provides an optimal solution for the problem of these low-frequency and novel variants. Although whole-exome sequencing is also a viable choice for exome regions, it cannot account for noncoding regions, sometimes resulting in the absence of important, causal variants. For Han Chinese populations, the majority of variants have been discovered based upon low-coverage data from the 1000 Genomes Project. However, high-coverage, whole-genome sequencing data are limited for any population, and a large amount of low-frequency, population-specific variants remain uncharacterized. We have performed whole-genome sequencing at a high depth (∼×80) of 90 unrelated individuals of Chinese ancestry, collected from the 1000 Genomes Project samples, including 45 Northern Han Chinese and 45 Southern Han Chinese samples. Eighty-three of these 90 have been sequenced by the 1000 Genomes Project. We have identified 12 568 804 single nucleotide polymorphisms, 2 074 210 short InDels, and 26 142 structural variations from these 90 samples. Compared to the Han Chinese data from the 1000 Genomes Project, we have found 7 000 629 novel variants with low frequency (defined as minor allele frequency < 5%), including 5 813 503 single nucleotide polymorphisms, 1 169 199 InDels, and 17 927 structural variants. Using deep sequencing data, we have built a greatly expanded spectrum of genetic variation for the Han Chinese genome. Compared to the 1000 Genomes Project, these Han Chinese deep sequencing data enhance the characterization of a large number of low-frequency, novel variants. This will be a valuable resource for promoting Chinese genetics research and medical development. Additionally, it will provide a valuable supplement to the 1000 Genomes Project, as well as to other human genome projects.

Population-wide sampling of retrotransposon insertion polymorphisms using deep sequencing and efficient detection

Active retrotransposons play important roles during evolution and continue to shape our genomes today, especially in genetic polymorphisms underlying a diverse set of diseases. However, studies of human retrotransposon insertion polymorphisms (RIPs) based on whole-genome deep sequencing at the population level have not been sufficiently undertaken, despite the obvious need for a thorough characterization of RIPs in the general population. Herein, we present a novel and efficient computational tool called Specific Insertions Detector (SID) for the detection of non-reference RIPs. We demonstrate that SID is suitable for high-depth whole-genome sequencing data using paired-end reads obtained from simulated and real datasets. We construct a comprehensive RIP database using a large population of 90 Han Chinese individuals with a mean ×68 depth per individual. In total, we identify 9342 recent RIPs, and 8433 of these RIPs are novel compared with dbRIP, including 5826 Alu, 2169 long interspersed nuclear element 1 (L1), 383 SVA, and 55 long terminal repeats. Among the 9342 RIPs, 4828 were located in gene regions and 5 were located in protein-coding regions. We demonstrate that RIPs can, in principle, be an informative resource to perform population evolution and phylogenetic analyses. Taking the demographic effects into account, we identify a weak negative selection on SVA and L1 but an approximately neutral selection for Alu elements based on the frequency spectrum of RIPs. SID is a powerful open-source program for the detection of non-reference RIPs. We built a non-reference RIP dataset that greatly enhanced the diversity of RIPs detected in the general population, and it should be invaluable to researchers interested in many aspects of human evolution, genetics, and disease. As a proof of concept, we demonstrate that the RIPs can be used as biomarkers in a similar way as single nucleotide polymorphisms.