The complete sequence of a human Y chromosome.

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure that includes long palindromes, tandem repeats and segmental duplications1-3. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished4,5. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029-base-pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, showing the complete ampliconic structures of gene families TSPY, DAZ and RBMY; 41 additional protein-coding genes, mostly from the TSPY family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a previous assembly of the CHM13 genome4 and mapped available population variation, clinical variants and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

UniAligner: a parameter-free framework for fast sequence alignment.

Even though the recent advances in 'complete genomics' revealed the previously inaccessible genomic regions, analysis of variations in centromeres and other extra-long tandem repeats (ETRs) faces an algorithmic challenge since there are currently no tools for accurate sequence comparison of ETRs. Counterintuitively, the classical alignment approaches, such as the Smith-Waterman algorithm, fail to construct biologically adequate alignments of ETRs. We present UniAligner-the parameter-free sequence alignment algorithm with sequence-dependent alignment scoring that automatically changes for any pair of compared sequences. UniAligner prioritizes matches of rare substrings that are more likely to be relevant to the evolutionary relationship between two sequences. We apply UniAligner to estimate the mutation rates in human centromeres, and quantify the extremely high rate of large duplications and deletions in centromeres. This high rate suggests that centromeres may represent some of the most rapidly evolving regions of the human genome with respect to their structural organization.

Fast and accurate mapping of long reads to complete genome assemblies with VerityMap.

Recent advancements in long-read sequencing have enabled the telomere-to-telomere (complete) assembly of a human genome and are now contributing to the haplotype-resolved complete assemblies of multiple human genomes. Because the accuracy of read mapping tools deteriorates in highly repetitive regions, there is a need to develop accurate, error-exposing (detecting potential assembly errors), and diploid-aware (distinguishing different haplotypes) tools for read mapping in complete assemblies. We describe the first accurate, error-exposing, and partially diploid-aware VerityMap tool for long-read mapping to complete assemblies.

Automated annotation of human centromeres with HORmon.

Recent advances in long-read sequencing opened a possibility to address the long-standing questions about the architecture and evolution of human centromeres. They also emphasized the need for centromere annotation (partitioning human centromeres into monomers and higher-order repeats [HORs]). Although there was a half-century-long series of semi-manual studies of centromere architecture, a rigorous centromere annotation algorithm is still lacking. Moreover, an automated centromere annotation is a prerequisite for studies of genetic diseases associated with centromeres and evolutionary studies of centromeres across multiple species. Although the monomer decomposition (transforming a centromere into a monocentromere written in the monomer alphabet) and the HOR decomposition (representing a monocentromere in the alphabet of HORs) are currently viewed as two separate problems, we show that they should be integrated into a single framework in such a way that HOR (monomer) inference affects monomer (HOR) inference. We thus developed the HORmon algorithm that integrates the monomer/HOR inference and automatically generates the human monomers/HORs that are largely consistent with the previous semi-manual inference.

Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies.

Advances in long-read sequencing technologies and genome assembly methods have enabled the recent completion of the first telomere-to-telomere human genome assembly, which resolves complex segmental duplications and large tandem repeats, including centromeric satellite arrays in a complete hydatidiform mole (CHM13). Although derived from highly accurate sequences, evaluation revealed evidence of small errors and structural misassemblies in the initial draft assembly. To correct these errors, we designed a new repeat-aware polishing strategy that made accurate assembly corrections in large repeats without overcorrection, ultimately fixing 51% of the existing errors and improving the assembly quality value from 70.2 to 73.9 measured from PacBio high-fidelity and Illumina k-mers. By comparing our results to standard automated polishing tools, we outline common polishing errors and offer practical suggestions for genome projects with limited resources. We also show how sequencing biases in both high-fidelity and Oxford Nanopore Technologies reads cause signature assembly errors that can be corrected with a diverse panel of sequencing technologies.

Complete genomic and epigenetic maps of human centromeres.

Existing human genome assemblies have almost entirely excluded repetitive sequences within and near centromeres, limiting our understanding of their organization, evolution, and functions, which include facilitating proper chromosome segregation. Now, a complete, telomere-to-telomere human genome assembly (T2T-CHM13) has enabled us to comprehensively characterize pericentromeric and centromeric repeats, which constitute 6.2% of the genome (189.9 megabases). Detailed maps of these regions revealed multimegabase structural rearrangements, including in active centromeric repeat arrays. Analysis of centromere-associated sequences uncovered a strong relationship between the position of the centromere and the evolution of the surrounding DNA through layered repeat expansions. Furthermore, comparisons of chromosome X centromeres across a diverse panel of individuals illuminated high degrees of structural, epigenetic, and sequence variation in these complex and rapidly evolving regions.

The complete sequence of a human genome.

Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.

Multiplex de Bruijn graphs enable genome assembly from long, high-fidelity reads.

Although most existing genome assemblers are based on de Bruijn graphs, the construction of these graphs for large genomes and large k-mer sizes has remained elusive. This algorithmic challenge has become particularly pressing with the emergence of long, high-fidelity (HiFi) reads that have been recently used to generate a semi-manual telomere-to-telomere assembly of the human genome. To enable automated assemblies of long, HiFi reads, we present the La Jolla Assembler (LJA), a fast algorithm using the Bloom filter, sparse de Bruijn graphs and disjointig generation. LJA reduces the error rate in HiFi reads by three orders of magnitude, constructs the de Bruijn graph for large genomes and large k-mer sizes and transforms it into a multiplex de Bruijn graph with varying k-mer sizes. Compared to state-of-the-art assemblers, our algorithm not only achieves five-fold fewer misassemblies but also generates more contiguous assemblies. We demonstrate the utility of LJA via the automated assembly of a human genome that completely assembled six chromosomes.

A scalable model for simulating multi-round antibody evolution and benchmarking of clonal tree reconstruction methods.

Affinity maturation (AM) of B cells through somatic hypermutations (SHMs) enables the immune system to evolve to recognize diverse pathogens. The accumulation of SHMs leads to the formation of clonal lineages of antibody-secreting b cells that have evolved from a common naïve B cell. Advances in high-throughput sequencing have enabled deep scans of B cell receptor repertoires, paving the way for reconstructing clonal trees. However, it is not clear if clonal trees, which capture microevolutionary time scales, can be reconstructed using traditional phylogenetic reconstruction methods with adequate accuracy. In fact, several clonal tree reconstruction methods have been developed to fix supposed shortcomings of phylogenetic methods. Nevertheless, no consensus has been reached regarding the relative accuracy of these methods, partially because evaluation is challenging. Benchmarking the performance of existing methods and developing better methods would both benefit from realistic models of clonal lineage evolution specifically designed for emulating B cell evolution. In this paper, we propose a model for modeling B cell clonal lineage evolution and use this model to benchmark several existing clonal tree reconstruction methods. Our model, designed to be extensible, has several features: by evolving the clonal tree and sequences simultaneously, it allows modeling selective pressure due to changes in affinity binding; it enables scalable simulations of large numbers of cells; it enables several rounds of infection by an evolving pathogen; and, it models building of memory. In addition, we also suggest a set of metrics for comparing clonal trees and measuring their properties. Our results show that while maximum likelihood phylogenetic reconstruction methods can fail to capture key features of clonal tree expansion if applied naively, a simple post-processing of their results, where short branches are contracted, leads to inferences that are better than alternative methods.

CentromereArchitect: inference and analysis of the architecture of centromeres.

MOTIVATION: Recent advances in long-read sequencing technologies led to rapid progress in centromere assembly in the last year and, for the first time, opened a possibility to address the long-standing questions about the architecture and evolution of human centromeres. However, since these advances have not been yet accompanied by the development of the centromere-specific bioinformatics algorithms, even the fundamental questions (e.g. centromere annotation by deriving the complete set of human monomers and high-order repeats), let alone more complex questions (e.g. explaining how monomers and high-order repeats evolved) about human centromeres remain open. Moreover, even though there was a four-decade-long series of studies aimed at cataloging all human monomers and high-order repeats, the rigorous algorithmic definitions of these concepts are still lacking. Thus, the development of a centromere annotation tool is a prerequisite for follow-up personalized biomedical studies of centromeres across the human population and evolutionary studies of centromeres across various species. RESULTS: We describe the CentromereArchitect, the first tool for the centromere annotation in a newly sequenced genome, apply it to the recently generated complete assembly of a human genome by the Telomere-to-Telomere consortium, generate the complete set of human monomers and high-order repeats for 'live' centromeres, and reveal a vast set of hybrid monomers that may represent the focal points of centromere evolution. AVAILABILITY AND IMPLEMENTATION: CentromereArchitect is publicly available on https://github.com/ablab/stringdecomposer/tree/ismb2021. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The structure, function and evolution of a complete human chromosome 8.

The complete assembly of each human chromosome is essential for understanding human biology and evolution1,2. Here we use complementary long-read sequencing technologies to complete the linear assembly of human chromosome 8. Our assembly resolves the sequence of five previously long-standing gaps, including a 2.08-Mb centromeric α-satellite array, a 644-kb copy number polymorphism in the ß-defensin gene cluster that is important for disease risk, and an 863-kb variable number tandem repeat at chromosome 8q21.2 that can function as a neocentromere. We show that the centromeric α-satellite array is generally methylated except for a 73-kb hypomethylated region of diverse higher-order α-satellites enriched with CENP-A nucleosomes, consistent with the location of the kinetochore. In addition, we confirm the overall organization and methylation pattern of the centromere in a diploid human genome. Using a dual long-read sequencing approach, we complete high-quality draft assemblies of the orthologous centromere from chromosome 8 in chimpanzee, orangutan and macaque to reconstruct its evolutionary history. Comparative and phylogenetic analyses show that the higher-order α-satellite structure evolved in the great ape ancestor with a layered symmetry, in which more ancient higher-order repeats locate peripherally to monomeric α-satellites. We estimate that the mutation rate of centromeric satellite DNA is accelerated by more than 2.2-fold compared to the unique portions of the genome, and this acceleration extends into the flanking sequence.

TandemTools: mapping long reads and assessing/improving assembly quality in extra-long tandem repeats.

MOTIVATION: Extra-long tandem repeats (ETRs) are widespread in eukaryotic genomes and play an important role in fundamental cellular processes, such as chromosome segregation. Although emerging long-read technologies have enabled ETR assemblies, the accuracy of such assemblies is difficult to evaluate since there are no tools for their quality assessment. Moreover, since the mapping of error-prone reads to ETRs remains an open problem, it is not clear how to polish draft ETR assemblies. RESULTS: To address these problems, we developed the TandemTools software that includes the TandemMapper tool for mapping reads to ETRs and the TandemQUAST tool for polishing ETR assemblies and their quality assessment. We demonstrate that TandemTools not only reveals errors in ETR assemblies but also improves the recently generated assemblies of human centromeres. AVAILABILITY AND IMPLEMENTATION: https://github.com/ablab/TandemTools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The string decomposition problem and its applications to centromere analysis and assembly.

MOTIVATION: Recent attempts to assemble extra-long tandem repeats (such as centromeres) faced the challenge of translating long error-prone reads from the nucleotide alphabet into the alphabet of repeat units. Human centromeres represent a particularly complex type of high-order repeats (HORs) formed by chromosome-specific monomers. Given a set of all human monomers, translating a read from a centromere into the monomer alphabet is modeled as the String Decomposition Problem. The accurate translation of reads into the monomer alphabet turns the notoriously difficult problem of assembling centromeres from reads (in the nucleotide alphabet) into a more tractable problem of assembling centromeres from translated reads. RESULTS: We describe a StringDecomposer (SD) algorithm for solving this problem, benchmark it on the set of long error-prone Oxford Nanopore reads generated by the Telomere-to-Telomere consortium and identify a novel (rare) monomer that extends the set of known X-chromosome specific monomers. Our identification of a novel monomer emphasizes the importance of identification of all (even rare) monomers for future centromere assembly efforts and evolutionary studies. To further analyze novel monomers, we applied SD to the set of recently generated long accurate Pacific Biosciences HiFi reads. This analysis revealed that the set of known human monomers and HORs remains incomplete. SD opens a possibility to generate a complete set of human monomers and HORs for using in the ongoing efforts to generate the complete assembly of the human genome. AVAILABILITY AND IMPLEMENTATION: StringDecomposer is publicly available on https://github.com/ablab/stringdecomposer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Automated assembly of centromeres from ultra-long error-prone reads.

Centromeric variation has been linked to cancer and infertility, but centromere sequences contain multiple tandem repeats and can only be assembled manually from long error-prone reads. Here we describe the centroFlye algorithm for centromere assembly using long error-prone reads, and apply it to assemble human centromeres on chromosomes 6 and X. Our analyses reveal putative breakpoints in the manual reconstruction of the human X centromere, demonstrate that human X chromosome is partitioned into repeat subfamilies and provide initial insights into centromere evolution. We anticipate that centroFlye could be applied to automatically close remaining multimegabase gaps in the reference human genome.

Telomere-to-telomere assembly of a complete human X chromosome.

After two decades of improvements, the current human reference genome (GRCh38) is the most accurate and complete vertebrate genome ever produced. However, no single chromosome has been finished end to end, and hundreds of unresolved gaps persist1,2. Here we present a human genome assembly that surpasses the continuity of GRCh382, along with a gapless, telomere-to-telomere assembly of a human chromosome. This was enabled by high-coverage, ultra-long-read nanopore sequencing of the complete hydatidiform mole CHM13 genome, combined with complementary technologies for quality improvement and validation. Focusing our efforts on the human X chromosome3, we reconstructed the centromeric satellite DNA array (approximately 3.1 Mb) and closed the 29 remaining gaps in the current reference, including new sequences from the human pseudoautosomal regions and from cancer-testis ampliconic gene families (CT-X and GAGE). These sequences will be integrated into future human reference genome releases. In addition, the complete chromosome X, combined with the ultra-long nanopore data, allowed us to map methylation patterns across complex tandem repeats and satellite arrays. Our results demonstrate that finishing the entire human genome is now within reach, and the data presented here will facilitate ongoing efforts to complete the other human chromosomes.

Reconstructing Antibody Repertoires from Error-Prone Immunosequencing Reads.

Transforming error-prone immunosequencing datasets into Ab repertoires is a fundamental problem in immunogenomics, and a prerequisite for studies of immune responses. Although various repertoire reconstruction algorithms were released in the last 3 y, it remains unclear how to benchmark them and how to assess the accuracy of the reconstructed repertoires. We describe an accurate IgReC algorithm for constructing Ab repertoires from high-throughput immunosequencing datasets and a new framework for assessing the quality of reconstructed repertoires. Surprisingly, Ab repertoires constructed by IgReC from barcoded immunosequencing datasets in the blind mode (without using information about unique molecular identifiers) improved upon the repertoires constructed by the state-of-the-art tools that use barcoding. This finding suggests that IgReC may alleviate the need to generate repertoires using the barcoding technology (the workhorse of current immunogenomics efforts) because our computational approach to error correction of immunosequencing data is nearly as powerful as the experimental approach based on barcoding.