Biology subjects

Human Genome Structural Variation Consortium,

Publications and source records attributed to Human Genome Structural Variation Consortium,.

7 recordsLinked to original sources

bioRxiv2026

HORoSCOPE: Decoding human centromere architecture from short reads using k-mer signatures

Centromeres safeguard genome integrity, yet their roles in human disease remain understudied because of their repetitive sequence. We present HOROSCOPE, a k-mer-based framework that infers centromere architecture and generates centromere length estimates directly from short-read data. Using a reference atlas of 11,836 centromeres from telomere-to-telomere haplotypes, we derive diagnostic k-mer signatures that classify chromosome-specific architectures with 98.2% precision and 99.1% recall. Applied to 4,029 genomes from 80 populations, HOROSCOPE uncovers continental centromeric structure and African-enriched rare architectures. Across 1,359 cancer genomes, HOROSCOPE reveals a dependency of chromosomal rearrangement locations on the kinetochore attachment site position.

genomics↗

bioRxiv2025

A global view of human centromere variation and evolution

Centromeres are essential for accurate chromosome segregation during cell division, yet their highly repetitive sequence has historically hindered their complete assembly and characterization. Consequently, the full spectrum of centromere diversity across individuals, populations, and evolutionary contexts remains largely unexplored. Here, we address this gap in knowledge by assembling and characterizing 2,110 complete human centromeres from a diverse cohort of individuals representing 5 continental and 28 population groups. By developing a novel suite of bioinformatic tools tailored for centromeric regions, we uncover previously unknown variation within centromeres, including 226 novel centromere haplotypes and 1,870 new -satellite higher-order repeat (HOR) variants. We find that mobile element insertions are present in 30% of centromeres, with chromosome 16 harboring Alu elements within the kinetochore site at an 11-fold higher frequency than expected. While most centromeres have a single kinetochore site, 6% of them have di-kinetochores, and <<1% have tri-kinetochores, which we confirm with long-read CENP-A CUT&RUN, DiMeLo-seq, and multi-generational inheritance. We further show that the position of the kinetochore is not random and is, instead, closely associated with the underlying sequence and structure of the centromere. To understand the nature of evolutionary change, we compared 2,110 complete human centromeres to 5,747 complete centromeres recently assembled from the Human Pangenome Reference Consortium. We show that centromeres have a >50-fold variation in mutation rate, with the most rapidly mutating centromeres on chromosome 1 and the slowest mutating centromeres on chromosome Y. Additionally, a subset of centromeres show evidence of introgression from archaic hominins, shaping their sequence, structure, and evolutionary history. We validate these centromere mutation rates in a four-generation family, spanning 28 family members and 483 accurately assembled centromeres, and show that the kinetochore site is the most rapidly mutating region in the centromere, with twofold more single-nucleotide variants than the rest of the centromeric -satellite HOR array on average. We propose a model that reveals an arms race between centromeric sequence and proteins, with frequent mutations within the site of the kinetochore that lead to changes in genetic and epigenetic landscapes and, ultimately, rapid evolution of these critically important regions.

genomics↗

bioRxiv2025

TRUHiC: A TRansformer-embedded U-2 Net to enhance Hi-C data for 3D chromatin structure characterization

High-throughput chromosome conformation capture sequencing (Hi-C) is a key technology for studying the three-dimensional (3D) structure of genomes and chromatin folding. Hi-C data reveals underlying patterns of genome organization, such as topologically associating domains (TADs) and chromatin loops, with critical roles in transcriptional regulation and disease etiology and progression. However, the sparsity of existing Hi-C data often hinders robust and reliable inference of 3D structures. Hence, we propose TRUHiC, a new computational method that leverages recent state-of-the-art deep generative modeling to augment low-resolution Hi-C data for the characterization of 3D chromatin structures. By applying TRUHiC to real low-resolution Hi-C data from the GM12329 cell line and across other publicly available Hi-C data for human and mice, we demonstrate that the augmented data significantly improve the characterization of TADs and loops across diverse cell lines and species. We further present a pre-trained TRUHiC on human lymphoblastoid cell lines that can be adaptable and transferable to improve chromatin characterization of various cell lines, tissues, and species.

bioinformatics↗

bioRxiv2023

Ancient AMY1 gene duplications primed the amylase locus for adaptive evolution upon the onset of agriculture

Starch digestion is a cornerstone of human nutrition. The amylase genes code for the starch-digesting amylase enzyme. Previous studies suggested that the salivary amylase (AMY1) gene copy number increased in response to agricultural diets. However, the lack of nucleotide resolution of the amylase locus hindered detailed evolutionary analyses. Here, we have resolved this locus at nucleotide resolution in 98 present-day humans and identified 30 distinct haplotypes, revealing that the coding sequences of all amylase gene copies are evolving under negative selection. The phylogenetic reconstruction suggested that haplotypes with three AMY1 gene copies, prevalent across all continents and constituting about 70% of observed haplotypes, originated before the out-of-Africa migrations of ancestral modern humans. Using thousands of unique 25 base pair sequences across the amylase locus, we showed that additional AMY1 gene copies existed in the genomes of four archaic hominin genomes, indicating that the initial duplication of this locus may have occurred as far back 800,000 years ago. We similarly analyzed 73 ancient human genomes dating from 300 - 45,000 years ago and found that the AMY1 copy number variation observed today existed long before the advent of agriculture ([~]10,000 years ago), predisposing this locus to adaptive increase in the frequency of higher amylase copy number with the spread of agriculture. Mechanistically, the common three-copy haplotypes seeded non-allelic homologous recombination events that appear to be occurring at one of the fastest rates seen for tandem repeats in the human genome. Our study provides a comprehensive population-level understanding of the genomic structure of the amylase locus, identifying the mechanisms and evolutionary history underlying its duplication and copy number variability in relation to the onset of agriculture.

evolutionary biology↗

bioRxiv2021

Haplotype-resolved inversion landscape reveals hotspots of mutational recurrence associated with genomic disorders

Unlike copy number variants (CNVs), inversions remain an underexplored genetic variation class. By integrating multiple genomic technologies, we discover 729 inversions in 41 human genomes. Approximately 85% of inversions <2 kbp form by twin-priming during L1-retrotransposition; 80% of the larger inversions are balanced and affect twice as many base pairs as CNVs. Balanced inversions show an excess of common variants, and 72% are flanked by segmental duplications (SDs) or mobile elements. Since this suggests recurrence due to non-allelic homologous recombination, we developed complementary approaches to identify recurrent inversion formation. We describe 40 recurrent inversions encompassing 0.6% of the genome, showing inversion rates up to 2.7x10-4 per locus and generation. Recurrent inversions exhibit a sex- chromosomal bias, and significantly co-localize to the critical regions of genomic disorders. We propose that inversion recurrence results in an elevated number of heterozygous carriers and structural SD diversity, which increases mutability in the population and predisposes to disease- causing CNVs.

genomics↗

bioRxiv2019

A fully phased accurate assembly of an individual human genome

The prevailing genome assembly paradigm is to produce consensus sequences that "collapse" parental haplotypes into a consensus sequence. Here, we leverage the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing (Strand-seq)1,2 and combine them with high-fidelity (HiFi) long sequencing reads3, in a novel reference-free workflow for diploid de novo genome assembly. Employing this strategy, we produce completely phased de novo genome assemblies separately for each haplotype of a single individual of Puerto Rican origin (HG00733) in the absence of parental data. The assemblies are accurate (QV > 40), highly contiguous (contig N50 > 25 Mbp) with low switch error rates (0.4%) providing fully phased single-nucleotide variants (SNVs), indels, and structural variants (SVs). A comparison of Oxford Nanopore and PacBio phased assemblies identifies 150 regions that are preferential sites of contig breaks irrespective of sequencing technology or phasing algorithms.

bioinformatics↗

bioRxiv2018

Identification of meiotic recombination through gamete genome reconstruction using whole genome linked-reads

Meiotic recombination (MR), which transmits exchanged genetic materials between homologous chromosomes to offspring, plays a crucial role in shaping genomic diversity in eukaryotic organisms. In humans, thousands of meiotic recombination hotspots have been mapped by population genetics approaches. However, direct identification of MR events for individuals is still challenging due to the difficulty in resolving the haplotypes of homologous chromosomes and reconstructing the gamete genome. Whole genome linked-read sequencing (lrWGS) can generate haplotype sequences of mega-base pairs (N50 ~2.5Mb) after computational phasing. However, the haplotype information is still isolated in a large number of fragmented genomic regions and limited by switch errors, impeding its further application in the chromosome-scale analysis. In this study, we developed a tool MRLR (Meiotic Recombination identification by Linked-Read sequencing) for the analysis of individual MR events. By leveraging trio pedigree information with lrWGS haplotypes, our pipeline is sufficient to reconstruct the whole human gamete genome with 99.8% haplotyping accuracy. By analyzing the haplotype exchange between homologous chromosomes, MRLR identified 462 high-resolution MR events in 6 human trio samples from the Genome In A Bottle (GIAB) and the Human Genome Structural Variation Consortium (HGSVC). In three datasets of the HGSVC, our results recapitulated 149 (92%) previously identified high-confident MR events and discovered 85 novel events. About half (40) of the new events are supported by single-cell template strand sequencing (Strand-seq) results. We found that 332 (71.9%) MR events co-localize with recombination hotspots (>10 cM/Mb) in human populations, and MR breakpoint regions are enriched in PRDM9 and DMC1 binding sites. In addition, 48% (221) breakpoint regions were detected inside a gene, indicating these MRs can directly affect the haplotype diversity of genic regions. Taken together, our approach provides new opportunities in the haplotype-based genomic analysis of individual meiotic recombination. The MRLR software is implemented in Perl and is freely available at https://github.com/ChongLab/MRLR.

genomics↗