Long-range Haplotype Research Articles

MiniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data.

Nanopore sequence technology has demonstrated a longer read length and enabled to potentially address the limitations of short-read sequencing including long-range haplotype phasing and accurate variant calling. However, there is still room for improvement in terms of the performance of single nucleotide variant (SNV) identification and computing resource usage for the state-of-the-art approaches. In this work, we introduce miniSNV, a lightweight SNV calling algorithm that simultaneously achieves high performance and yield. miniSNV utilizes known common variants in populations as variation backgrounds and leverages read pileup, read-based phasing, and consensus generation to identify and genotype SNVs for Oxford Nanopore Technologies (ONT) long reads. Benchmarks on real and simulated ONT data under various error profiles demonstrate that miniSNV has superior sensitivity and comparable accuracy on SNV detection and runs faster with outstanding scalability and lower memory than most state-of-the-art variant callers. miniSNV is available from https://github.com/CuiMiao-HIT/miniSNV.

PSV-8 Investigation of a haplotype and eQTL analysis of the LCORL-NCAPG locus associated with increased lean growth in beef cattle

Abstract Numerous studies have shown genetic variation at the LCORL-NCAPG locus is strongly associated with growth traits in beef cattle. However, a causative molecular variant has yet to be identified. To define all possible candidate variants, Charolais-sired calves (n = 34) were whole genome sequenced including 17 homozygous for a long-range haplotype associated with increased growth (QQ), and 17 homozygous for potential ancestral haplotypes for this region (qq). The Q haplotype was refined to an 814-kb region between chr6:37,199,897-38,014,080 and contained 218 variants not found in qq individuals. These variants include an insertion in an intron of NCAPG, a previously documented mutation in NCAPG (rs109570900), two coding sequence mutations in LCORL (rs109696064 and rs384548488), and 15 variants located within ATAC peaks that were predicted to affect transcription factor binding. Notably, rs384548488 is a frameshift variant likely resulting in loss of function for long isoforms of LCORL. To test the association of the coding sequence variants of LCORL with phenotype, 405 cattle from five populations were genotyped. The two variants were in complete linkage disequilibrium. Statistical analysis of the three populations that contained QQ animals revealed significant (P < 0.05) associations with genotype and birth weight, body weight, carcass weight, hip height, and average daily gain. Additionally, an RNAseq analysis was performed using 22 of the Charolais-sired calves. This, in conjunction with the WGS data, was used to run an eQTL analysis, which revealed 256 genes whose expression were impacted by eQTL in the region (FDR < 0.05). These findings affirm the link between this locus and growth in beef cattle and describe DNA variants that define the haplotype. However, further studies will be required to define the true causative mutation.

Common and rare genetic variants predisposing females to unexplained recurrent pregnancy loss

Recurrent pregnancy loss (RPL) is a major reproductive health issue with multifactorial causes, affecting 2.6% of all pregnancies worldwide. Nearly half of the RPL cases lack clinically identifiable causes (e.g., antiphospholipid syndrome, uterine anomalies, and parental chromosomal abnormalities), referred to as unexplained RPL (uRPL). Here, we perform a genome-wide association study focusing on uRPL in 1,728 cases and 24,315 female controls of Japanese ancestry. We detect significant associations in the major histocompatibility complex (MHC) region at 6p21 (lead variant=rs9263738; P = 1.4 × 10−10; odds ratio [OR] = 1.51 [95% CI: 1.33–1.72]; risk allele frequency = 0.871). The MHC associations are fine-mapped to the classical HLA alleles, HLA-C*12:02, HLA-B*52:01, and HLA-DRB1*15:02 (P = 1.1 × 10−10, 1.5 × 10−10, and 1.2 × 10−9, respectively), which constitute a population-specific common long-range haplotype with a protective effect (P = 2.8 × 10−10; OR = 0.65 [95% CI: 0.57–0.75]; haplotype frequency=0.108). Genome-wide copy-number variation (CNV) calling demonstrates rare predicted loss-of-function (pLoF) variants of the cadherin-11 gene (CDH11) conferring the risk of uRPL (P = 1.3 × 10−4; OR = 3.29 [95% CI: 1.78–5.76]). Our study highlights the importance of reproductive immunology and rare variants in the uRPL etiology.

Harnessing landrace diversity empowers wheat breeding

Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A. E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, by whole-genome re-sequencing of 827 Watkins landraces and 208 modern cultivars and in-depth field evaluation spanning a decade. We found that modern cultivars are derived from two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium-based haplotypes and association genetics analyses link Watkins genomes to the thousands of identified high-resolution quantitative trait loci and significant marker–trait associations. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritized quantitative trait loci in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilizing genetic diversity in crop improvement to achieve sustainable food security.

CD59 gene: 143 haplotypes of 22,718 nucleotides length by computational phasing in 113 individuals from different ethnicities.

CD59 deficiency due to rare germline variants in the CD59 gene causes disabilities, ischemic strokes, neuropathy, and hemolysis. CD59 deficiency due to common somatic variants in the PIG-A gene in hematopoietic stem cells causes paroxysmal nocturnal hemoglobinuria. The ISBT database lists one nonsense and three missense germline variants that are associated with the CD59-null phenotype. To analyze the genetic diversity of the CD59 gene, we determined long-range CD59 haplotypes among individuals from different ethnicities. We determined a 22.7 kb genomic fragment of the CD59 gene in 113 individuals using next-generation sequencing (NGS), which covered the whole NM_203330.2 mRNA transcript of 7796 base pairs. Samples came from an FDA reference repository and our Ethiopia study cohorts. The raw genotype data were computationally phased into individual haplotype sequences. Nucleotide sequencing of the CD59 gene of 226 chromosomes identified 216 positions with single nucleotide variants. Only three haplotypes were observed in homozygous form, which allowed us to assign them unambiguously as experimentally verified CD59 haplotypes. They were also the most frequent haplotypes among both cohorts. An additional 140 haplotypes were imputed computationally. We provided a large set of haplotypes and proposed three verified long-range CD59 reference sequences, based on a population approach, using a generalizable rationale for our choice. Correct long-range haplotypes are useful as template sequences for allele calling in high-throughput NGS and precision medicine approaches, thus enhancing the reliability of clinical diagnostics. Long-range haplotypes can also be used to evaluate the influence of genetic variation on the risk of transfusion reactions or diseases.

Defining a Haplotype Encompassing the LCORL-NCAPG Locus Associated with Increased Lean Growth in Beef Cattle.

Numerous studies have shown genetic variation at the LCORL-NCAPG locus is strongly associated with growth traits in beef cattle. However, a causative molecular variant has yet to be identified. To define all possible candidate variants, 34 Charolais-sired calves were whole-genome sequenced, including 17 homozygous for a long-range haplotype associated with increased growth (QQ) and 17 homozygous for potential ancestral haplotypes for this region (qq). The Q haplotype was refined to an 814 kb region between chr6:37,199,897-38,014,080 and contained 218 variants not found in qq individuals. These variants include an insertion in an intron of NCAPG, a previously documented mutation in NCAPG (rs109570900), two coding sequence mutations in LCORL (rs109696064 and rs384548488), and 15 variants located within ATAC peaks that were predicted to affect transcription factor binding. Notably, rs384548488 is a frameshift variant likely resulting in loss of function for long isoforms of LCORL. To test the association of the coding sequence variants of LCORL with phenotype, 405 cattle from five populations were genotyped. The two variants were in complete linkage disequilibrium. Statistical analysis of the three populations that contained QQ animals revealed significant (p < 0.05) associations with genotype and birth weight, live weight, carcass weight, hip height, and average daily gain. These findings affirm the link between this locus and growth in beef cattle and describe DNA variants that define the haplotype. However, further studies will be required to define the true causative mutation.

Implementation of Nanopore sequencing as a pragmatic workflow for copy number variant confirmation in the clinic

BackgroundDiagnosis of rare genetic diseases can be a long, expensive and complex process, involving an array of tests in the hope of obtaining an actionable result. Long-read sequencing platforms offer the opportunity to make definitive molecular diagnoses using a single assay capable of detecting variants, characterizing methylation patterns, resolving complex rearrangements, and assigning findings to long-range haplotypes. Here, we demonstrate the clinical utility of Nanopore long-read sequencing by validating a confirmatory test for copy number variants (CNVs) in neurodevelopmental disorders and illustrate the broader applications of this platform to assess genomic features with significant clinical implications.MethodsWe used adaptive sampling on the Oxford Nanopore platform to sequence 25 genomic DNA samples and 5 blood samples collected from patients with known or false-positive copy number changes originally detected using short-read sequencing. Across the 30 samples (a total of 50 with replicates), we assayed 35 known unique CNVs (a total of 55 with replicates) and one false-positive CNV, ranging in size from 40 kb to 155 Mb, and assessed the presence or absence of suspected CNVs using normalized read depth.ResultsAcross 50 samples (including replicates) sequenced on individual MinION flow cells, we achieved an average on-target mean depth of 9.5X and an average on-target read length of 4805 bp. Using a custom read depth-based analysis, we successfully confirmed the presence of all 55 known CNVs (including replicates) and the absence of one false-positive CNV. Using the same CNV-targeted data, we compared genotypes of single nucleotide variant loci to verify that no sample mix-ups occurred between assays. For one case, we also used methylation detection and phasing to investigate the parental origin of a 15q11.2-q13 duplication with implications for clinical prognosis.ConclusionsWe present an assay that efficiently targets genomic regions to confirm clinically relevant CNVs with a concordance rate of 100%. Furthermore, we demonstrate how integration of genotype, methylation, and phasing data from the Nanopore sequencing platform can potentially simplify and shorten the diagnostic odyssey.

NanoSNP: a progressive and haplotype-aware SNP caller on low-coverage nanopore sequencing data.

Oxford Nanopore sequencing has great potential and advantages in population-scale studies. Due to the cost of sequencing, the depth of whole-genome sequencing for per individual sample must be small. However, the existing single nucleotide polymorphism (SNP) callers are aimed at high-coverage Nanopore sequencing reads. Detecting the SNP variants on low-coverage Nanopore sequencing data is still a challenging problem. We developed a novel deep learning-based SNP calling method, NanoSNP, to identify the SNP sites (excluding short indels) based on low-coverage Nanopore sequencing reads. In this method, we design a multi-step, multi-scale and haplotype-aware SNP detection pipeline. First, the pileup model in NanoSNP utilizes the naive pileup feature to predict a subset of SNP sites with a Bi-long short-term memory (LSTM) network. These SNP sites are phased and used to divide the low-coverage Nanopore reads into different haplotypes. Finally, the long-range haplotype feature and short-range pileup feature are extracted from each haplotype. The haplotype model combines two features and predicts the genotype for the candidate site using a Bi-LSTM network. To evaluate the performance of NanoSNP, we compared NanoSNP with Clair, Clair3, Pepper-DeepVariant and NanoCaller on the low-coverage (∼16×) Nanopore sequencing reads. We also performed cross-genome testing on six human genomes HG002-HG007, respectively. Comprehensive experiments demonstrate that NanoSNP outperforms Clair, Pepper-DeepVariant and NanoCaller in identifying SNPs on low-coverage Nanopore sequencing data, including the difficult-to-map regions and major histocompatibility complex regions in the human genome. NanoSNP is comparable to Clair3 when the coverage exceeds 16×. https://github.com/huangnengCSU/NanoSNP.git. Supplementary data are available at Bioinformatics online.

Long-read sequencing for molecular diagnostics in constitutional genetic disorders.

Long-read sequencing (LRS) has been around for more than a decade, but widespread adoption of the technology has been slow due to the perceived high error rates and high sequencing cost. This is changing due to the recent advancements to produce highly accurate sequences and the reducing costs. LRS promises significant improvement over short read sequencing in four major areas: (1) better detection of structural variation (2) better resolution of highly repetitive or nonunique regions (3) accurate long-range haplotype phasing and (4) the detection of base modifications natively from the sequencing data. Several successful applications of LRS have demonstrated its ability to resolve molecular diagnoses where short-read sequencing fails to identify a cause. However, the argument for increased diagnostic yield from LRS remains to be validated. Larger cohort studies may be required to establish the realistic boundaries of LRS's clinical utility and analytical validity, as well as the development of standards for clinical applications. We discuss the limitations of the current standard of care, and contrast with the applications and advantages of two major LRS platforms, PacBio and Oxford Nanopore, for molecular diagnostics of constitutional disorders, and present a critical argument about the potential of LRS in diagnostic settings.

Dynamic molecular evolution of a supergene with suppressed recombination in white-throated sparrows.

In white-throated sparrows, two alternative morphs differing in plumage and behavior segregate with a large chromosomal rearrangement. As with sex chromosomes such as the mammalian Y, the rearranged version of chromosome two (ZAL2m) is in a near-constant state of heterozygosity, offering opportunities to investigate both degenerative and selective processes during the early evolutionary stages of 'supergenes.' Here, we generated, synthesized, and analyzed extensive genome-scale data to better understand the forces shaping the evolution of the ZAL2 and ZAL2m chromosomes in this species. We found that features of ZAL2m are consistent with substantially reduced recombination and low levels of degeneration. We also found evidence that selective sweeps took place both on ZAL2m and its standard counterpart, ZAL2, after the rearrangement event. Signatures of positive selection were associated with allelic bias in gene expression, suggesting that antagonistic selection has operated on gene regulation. Finally, we discovered a region exhibiting long-range haplotypes inside the rearrangement on ZAL2m. These haplotypes appear to have been maintained by balancing selection, retaining genetic diversity within the supergene. Together, our analyses illuminate mechanisms contributing to the evolution of a young chromosomal polymorphism, revealing complex selective processes acting concurrently with genetic degeneration to drive the evolution of supergenes.

Genomic Signatures of a Major Adaptive Event in the Pathogenic Fungus Melampsora larici-populina.

The recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in nonmodel organisms. Host–pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. Using an array of genome scan methods based on different features of nucleotide diversity, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype–phenotype statistical association, and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although our samples are nearly contemporary to the selective sweep, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus, which can be explained by a soft selective sweep (where selection acts on standing variation) and by the impact of recombination in mitigating the impact of selection. Therefore, it seems that properties of the life cycle of M. larici-populina, which entails both high genetic diversity and outbreeding, has facilitated its adaptation.

A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response.

Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large (n = 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in Admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study (GWAS) data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide binding groove, explaining 12.9% of trait variance.

NanoCaller for accurate detection of SNPs and indels in difficult-to-map regions from long-read sequencing by haplotype-aware deep neural networks

Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep learning method NanoCaller, which detects SNPs using long-range haplotype information, then phases long reads with called SNPs and calls indels with local realignment. Evaluation on 8 human genomes demonstrates that NanoCaller generally achieves better performance than competing approaches. We experimentally validate 41 novel variants in a widely used benchmarking genome, which could not be reliably detected previously. In summary, NanoCaller facilitates the discovery of novel variants in complex genomic regions from long-read sequencing.

Highly Selective, CRISPR/Cas9-Mediated Isolation of Genes and Genomic Loci from Complex Genomes by TAR Cloning in Yeast.

Here we describe an updated TAR cloning protocol for the selective and efficient isolation of any genomic fragment or gene of interest up to 280 kb in size from genomic DNA. The method exploits the special recombination machinery of the yeast Saccharomyces cerevisiae. TAR cloning is based on the high level of in vivo recombination that occurs between a specific genomic DNA fragment of interest and targeting sequences (hooks) in a TAR vector that are homologous to the 5′ and 3′ ends of the targeted region. Upon co‐transformation into yeast, this results in the isolation of the chromosomal region of interest as a circular YAC molecule, which then propagates and segregates in yeast cells and can be selected for. In the updated TAR cloning protocol described here, the fraction of region‐positive clones typically obtained is increased from 1% up to 35% by pre‐treatment of the genomic DNA with specifically designed CRISPR/Cas9 endonucleases that create double‐strand breaks (DSBs) bracketing the target genomic DNA sequence, thereby making the ends of the chromosomal region of interest highly recombinogenic. In addition, a new TAR vector was constructed that contains YAC and BAC cassettes, permitting direct transfer of a TAR‐cloned DNA from yeast to bacterial cells. Once the TAR vector with the hooks is constructed and genomic DNA is prepared, the entire procedure takes 3 weeks to complete. The updated TAR protocol does not require significant yeast experience or extensively time‐consuming yeast work because screening only about a dozen yeast transformants is typically enough to find a clone with the region of interest. TAR cloning of chromosomal fragments, individual genes, or gene families can be used for functional, structural, and population studies, for comparative genomics, and for long‐range haplotyping, and has potential for gene therapy. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of CRISPR/Cas9‐treated genomic DNA for TAR cloning Basic Protocol 2: Isolation of a gene or genomic locus by TAR cloning Basic Protocol 3: Transfer of TAR/YAC/BAC isolates from yeast to E. coli

Analysis of Evolution and Ethnic Diversity at Glucose-Associated SNPs of Circadian Clock-Related Loci with Cryptochrome 1, Cryptochrome 2, and Melatonin receptor 1B.

Diabetes shows high heritability and, worldwide, causes significant health problems including cardiovascular disease and stroke. There is significant variation in the frequency of diabetes between different populations. Both Cryptochromes and Melatonin have a major role to regulate the circadian clock. Circadian clock failure causes metabolic dysfunctions including diabetes and obesity. Variations in the Cryptochrome 1, the Cryptochrome 2, and the Melatonin receptor 1B (MTNR1B) genes show associations with fasting glucose, and are also related to circadian clock. Here, we analyzed evidence for genetic selection and ethnic diversity at circadian clock- and glucose-related gene loci associated with Cryptochrome 1, Cryptochrome 2, and MTNR1B. We carried out a 3-step genetic method to investigate genetic selection at the Cryptochrome 1, Cryptochrome 2, and MTNR1B on four populations from the 1000 Genomes Project and HapMap. First we used F-statistics to quantify genetic population differences and find ethnic diversity. Then we applied a long-range haplotype test to detect significant extreme long haplotypes, and then the integrated haplotype score (iHS) to find genetic selection at Cryptochrome 1, Cryptochrome 2, and MTNR1B. We observed genetic population differences and ethnic diversity at one glucose-associated Cryptochrome 1 single-nucleotide polymorphism (SNP) (rs8192440), one glucose-associated Cryptochrome 2 SNP (rs11605924), and one glucose-associated MTNR1B SNP (rs10830963) by F-statistics. Both Cryptochrome 1 and MTNR1B also showed selection by the iHS. These observations show new evidence for evolution at Cryptochrome 1, Cryptochrome 2 and MTNR1B. Further investigation should continue to examine the evolution of circadian clock- and glucose-related genes.

Accurate haplotype-resolved assembly reveals the origin of structural variants for human trios.

MotivationAchieving a near complete understanding of how the genome of an individual affects the phenotypes of that individual requires deciphering the order of variations along homologous chromosomes in species with diploid genomes. However, true diploid assembly of long-range haplotypes remains challenging.ResultsTo address this, we have developed Haplotype-resolved Assembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental information to classify reads into maternal or paternal. Once sorted, these reads are used to independently de novo assemble the parent-specific haplotypes. We applied HAST to cobarcoded second-generation sequencing data from an Asian individual, resulting in a haplotype assembly covering 94.7% of the reference genome with a scaffold N50 longer than 11 Mb. The high haplotyping precision (∼99.7%) and recall (∼95.9%) represents a substantial improvement over the commonly used tool for assembling cobarcoded reads (Supernova), and is comparable to a trio-binning-based third generation long-read-based assembly method (TrioCanu) but with a significantly higher single-base accuracy [up to 99.99997% (Q65)]. This makes HAST a superior tool for accurate haplotyping and future haplotype-based studies.Availability and implementationThe code of the analysis is available at https://github.com/BGI-Qingdao/HASTSupplementary informationSupplementary data are available at Bioinformatics online.

Analysis of genetic selection at insulin receptor substrate-2 gene loci.

Type 2 diabetes mellitus (T2DM) is highly heritable and exhibits significant variability in prevalence between different populations. Prevalence of T2DM is higher in Asian and African relative to European populations. During evolution, traditional feast-famine cycles likely led to significant natural selection impacting metabolic genes. Human adaptation to environmental changes (food supply, lifestyle, climate, and geography) likely influenced differential selection of T2DM-associated genes. Together, insulin receptor substrate-1 and -2 (IRS1 and IRS2) genes encode the major ligands of insulin and IGF1 receptors. Irs2-deficient mice exhibit a T2DM phenotype with severe insulin resistance, and a common IRS2 polymorphism is associated with T2DM. Therefore, the present study sought evidence of natural selection at IRS2 loci. Data were sourced from the HapMap and 1000 Genomes projects, comprising four different populations with distinct ancestries: European, Yoruba, Han Chinese, and Japanese. A three-step method was applied to detect IRS2 locus selection. The long-range haplotype (LRH) test detected unusual extended haplotypes, the integrated haplotype score (iHS) detected selection, and Wright's F-statistics (particularly Wright's fixation index: FST) were calculated as a measure of population differentiation. The African population exhibited highly significant LRH findings (percentile >99.9, p = 0.005-0.0009), while both the European and African populations exhibited extreme positive iHS test scores ([iHS] >2.5). These findings indicate that genetic selection has occurred at the IRS2 locus, warranting further research into the adaptive evolution of metabolic disorder-associated genes. The online version contains supplementary material available at 10.1007/s40200-021-00745-y.

Simulation of African and non-African low and high coverage whole genome sequence data to assess variant calling approaches

Current variant calling (VC) approaches have been designed to leverage populations of long-range haplotypes and were benchmarked using populations of European descent, whereas most genetic diversity is found in non-European such as Africa populations. Working with these genetically diverse populations, VC tools may produce false positive and false negative results, which may produce misleading conclusions in prioritization of mutations, clinical relevancy and actionability of genes. The most prominent question is which tool or pipeline has a high rate of sensitivity and precision when analysing African data with either low or high sequence coverage, given the high genetic diversity and heterogeneity of this data. Here, a total of 100 synthetic Whole Genome Sequencing (WGS) samples, mimicking the genetics profile of African and European subjects for different specific coverage levels (high/low), have been generated to assess the performance of nine different VC tools on these contrasting datasets. The performances of these tools were assessed in false positive and false negative call rates by comparing the simulated golden variants to the variants identified by each VC tool. Combining our results on sensitivity and positive predictive value (PPV), VarDict [PPV = 0.999 and Matthews correlation coefficient (MCC) = 0.832] and BCFtools (PPV = 0.999 and MCC = 0.813) perform best when using African population data on high and low coverage data. Overall, current VC tools produce high false positive and false negative rates when analysing African compared with European data. This highlights the need for development of VC approaches with high sensitivity and precision tailored for populations characterized by high genetic variations and low linkage disequilibrium.

State-of-the-art genome inference in the human MHC.

The Major Histocompatibility Complex (MHC) on the short arm of chromosome 6 is associated with more diseases than any other region of the genome; it encodes the antigen-presenting Human Leukocyte Antigen (HLA) proteins and is one of the key immunogenetic regions of the genome. Accurate genome inference and interpretation of MHC association signals have traditionally been hampered by the region's uniquely complex features, such as high levels of polymorphism; inter-gene sequence homologies; structural variation; and long-range haplotype structures. Recent algorithmic and technological advances have, however, significantly increased the accessibility of genetic variation in the MHC; these developments include (i) accurate SNP-based HLA type imputation; (ii) genome graph approaches for variation-aware genome inference from next-generation sequencing data; (iii) long-read-based diploid de novo assembly of the MHC; (iv) cost-effective targeted MHC sequencing methods. Applied to hundreds of thousands of samples over the last years, these technologies have already enabled significant biological discoveries, for example in the field of autoimmune disease genetics. Remaining challenges concern the development of integrated methods that leverage haplotype-resolved de novo assembly of the MHC for the development of improved MHC genotyping methods for short reads and the construction of improved reference panels for SNP-based imputation. Improved genome inference in the MHC can crucially contribute to an improved genetic and functional understanding of many immune-related phenotypes and diseases.

Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People.

The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.