Insertion variants missing in the human reference genome are widespread among human populations

Human pangenome analysis of sequences missing from the reference genome reveals their widespread evolutionary, phenotypic, and functional roles

Nonreference sequences (NRSs) are DNA sequences present in global populations but absent in the current human reference genome. However, the extent and functional significance of NRSs in the human genomes and populations remains unclear. Here, we de novo assembled 539 genomes from five genetically divergent human populations using long-read sequencing technology, resulting in the identification of 5.1 million NRSs. These were merged into 45284 unique NRSs, with 29.7% being novel discoveries. Among these NRSs, 38.7% were common across the five populations, and 35.6% were population specific. The use of a graph-based pangenome approach allowed for the detection of 565 transcript expression quantitative trait loci on NRSs, with 426 of these being novel findings. Moreover, 26 NRS candidates displayed evidence of adaptive selection within human populations. Genes situated in close proximity to or intersecting with these candidates may be associated with metabolism and type 2 diabetes. Genome-wide association studies revealed 14 NRSs to be significantly associated with eight phenotypes. Additionally, 154 NRSs were found to be in strong linkage disequilibrium with 258 phenotype-associated SNPs in the GWAS catalogue. Our work expands the understanding of human NRSs and provides novel insights into their functions, facilitating evolutionary and biomedical researches.

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.

Population-scale detection of non-reference sequence variants using colored de Bruijn graphs

MOTIVATION

With the increasing throughput of sequencing technologies, structural variant (SV) detection has become possible across tens of thousands of genomes. Non-reference sequence (NRS) variants have drawn less attention compared with other types of SVs due to the computational complexity of detecting them. When using short-read data, the detection of NRS variants inevitably involves a de novo assembly which requires high-quality sequence data at high coverage. Previous studies have demonstrated how sequence data of multiple genomes can be combined for the reliable detection of NRS variants. However, the algorithms proposed in these studies have limited scalability to larger sets of genomes.

RESULTS

We introduce PopIns2, a tool to discover and characterize NRS variants in many genomes, which scales to considerably larger numbers of genomes than its predecessor PopIns. In this article, we briefly outline the PopIns2 workflow and highlight our novel algorithmic contributions. We developed an entirely new approach for merging contig assemblies of unaligned reads from many genomes into a single set of NRS using a colored de Bruijn graph. Our tests on simulated data indicate that the new merging algorithm ranks among the best approaches in terms of quality and reliability and that PopIns2 shows the best precision for a growing number of genomes processed. Results on the Polaris Diversity Cohort and a set of 1000 Icelandic human genomes demonstrate unmatched scalability for the application on population-scale datasets.

AVAILABILITY AND IMPLEMENTATION

The source code of PopIns2 is available from https://github.com/kehrlab/PopIns2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Haplotype Shuffling and Dimorphic Transposable Elements in the Human Extended Major Histocompatibility Complex Class II Region

The major histocompatibility complex (MHC) on chromosome 6p21 is one of the most single-nucleotide polymorphism (SNP)-dense regions of the human genome and a prime model for the study and understanding of conserved sequence polymorphisms and structural diversity of ancestral haplotypes/conserved extended haplotypes. This study aimed to follow up on a previous analysis of the MHC class I region by using the same set of 95 MHC haplotype sequences downloaded from a publicly available BioProject database at the National Center for Biotechnology Information to identify and characterize the polymorphic human leukocyte antigen (HLA)-class II genes, the MTCO3P1 pseudogene alleles, the indels of transposable elements as haplotypic lineage markers, and SNP-density crossover (XO) loci at haplotype junctions in DNA sequence alignments of different haplotypes across the extended class II region (∼1 Mb) from the telomeric PRRT1 gene in class III to the COL11A2 gene at the centromeric end of class II. We identified 42 haplotypic indels (20 Alu, 7 SVA, 13 LTR or MERs, and 2 indels composed of a mosaic of different transposable elements) linked to particular HLA-class II alleles. Comparative sequence analyses of 136 haplotype pairs revealed 98 unique XO sites between SNP-poor and SNP-rich genomic segments with considerable haplotype shuffling located in the proximity of putative recombination hotspots. The majority of XO sites occurred across various regions including in the vicinity of MTCO3P1 between HLA-DQB1 and HLA-DQB3, between HLA-DQB2 and HLA-DOB, between DOB and TAP2, and between HLA-DOA and HLA-DPA1, where most XOs were within a HERVK22 sequence. We also determined the genomic positions of the PRDM9-recombination suppression sequence motif ATCCATG/CATGGAT and the PRDM9 recombination activation partial binding motif CCTCCCCT/AGGGGAG in the class II region of the human reference genome (NC_ 000006) relative to published meiotic recombination positions. Both the recombination and anti-recombination PRDM9 binding motifs were widely distributed throughout the class II genomic regions with 50% or more found within repeat elements; the anti-recombination motifs were found mostly in L1 fragmented repeats. This study shows substantial haplotype shuffling between different polymorphic blocks and confirms the presence of numerous putative ancestral recombination sites across the class II region between various HLA class II genes.

The genome atlas: navigating a new era of reference genomes

The reference genome serves two distinct purposes within the field of genomics. First, it provides a persistent structure against which findings can be reported, allowing for universal knowledge exchange between users. Second, it reduces the computational costs and time required to process genomic data by creating a scaffold that can be relied upon by analysis software. Here, we posit that current efforts to extend the linear reference to a graph-based structure while trying to fulfil both of these purposes concurrently will face a trade-off between comprehensiveness and computational efficiency. In this article, we explore how the reference genome is used and suggest an alternative structure, The Genome Atlas (TGA), to fulfil the bipartite role of the reference genome.