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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.

Improvements in long-read data and scaffolding technologies have enabled rapid generation of reference-quality assemblies for complex genomes. Still, an assessment of critical sequence depth and read length is important for allocating limited resources. To this end, we have generated eight assemblies for the complex genome of the maize inbred line NC358 using PacBio datasets ranging from 20 to 75 × genomic depth and with N50 subread lengths of 11–21 kb. Assemblies with ≤30 × depth and N50 subread length of 11 kb are highly fragmented, with even low-copy genic regions showing degradation at 20 × depth. Distinct sequence-quality thresholds are observed for complete assembly of genes, transposable elements, and highly repetitive genomic features such as telomeres, heterochromatic knobs, and centromeres. In addition, we show high-quality optical maps can dramatically improve contiguity in even our most fragmented base assembly. This study provides a useful resource allocation reference to the community as long-read technologies continue to mature., Sequence depth and read length determine the quality of genome assembly. Here, the authors leverage a set of PacBio reads to develop guidelines for sequencing and assembly of complex plant genomes in order to allocate finite resources using maize as an example.

The repetitive nature and complexity of multiple medically important genes make them intractable to accurate analysis, despite the maturity of short-read sequencing, resulting in a gap in clinical applications of genome sequencing. The Genome in a Bottle Consortium has provided benchmark variant sets, but these excluded some medically relevant genes due to their repetitiveness or polymorphic complexity. In this study, we characterize 273 of these 395 challenging autosomal genes that have multiple implications for medical sequencing. This extended, curated benchmark reports over 17,000 SNVs, 3,600 INDELs, and 200 SVs each for GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically important genes including CBS, CRYAA, and KCNE1. Our proposed solution improves variant recall in these genes from 8% to 100%. This benchmark will significantly improve the comprehensive characterization of these medically relevant genes and guide new method development.

In 2001, Celera Genomics and the International Human Genome Sequencing Consortium published their initial drafts of the human genome, which revolutionized the field of genomics. While these drafts and the updates that followed effectively covered the euchromatic fraction of the genome, the heterochromatin and many other complex regions were left unfinished or erroneous. Addressing this remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium has finished the first truly complete 3.055 billion base pair (bp) sequence of a human genome, representing the largest improvement to the human reference genome since its initial release. The new T2T-CHM13 reference includes gapless assemblies for all 22 autosomes plus Chromosome X, corrects numerous errors, and introduces nearly 200 million bp of novel sequence containing 2,226 paralogous gene copies, 115 of which are predicted to be protein coding. The newly completed regions include all centromeric satellite arrays and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies for the first time.

Haplotype-resolved or phased genome assembly provides a complete picture of genomes and their complex genetic variations. However, current algorithms for phased assembly either do not generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method named diploid assembly (DipAsm) that uses long, accurate reads and long-range conformation data for single individuals to generate a chromosome-scale phased assembly within 1 day. Applied to four public human genomes, PGP1, HG002, NA12878 and HG00733, DipAsm produced haplotype-resolved assemblies with minimum contig length needed to cover 50% of the known genome (NG50) up to 25 Mb and phased ~99.5% of heterozygous sites at 98–99% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies for the discovery of structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as the human leukocyte antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) regions. DipAsm will facilitate high-quality precision medicine and studies of individual haplotype variation and population diversity., Assembly of phased human genomes is achieved by combining long reads and long-range conformational data.

Background Modern sequencing technologies should make the assembly of the relatively small mitochondrial genomes an easy undertaking. However, few tools exist that address mitochondrial assembly directly. Results As part of the Vertebrate Genomes Project (VGP) we develop mitoVGP, a fully automated pipeline for similarity-based identification of mitochondrial reads and de novo assembly of mitochondrial genomes that incorporates both long (> 10 kbp, PacBio or Nanopore) and short (100–300 bp, Illumina) reads. Our pipeline leads to successful complete mitogenome assemblies of 100 vertebrate species of the VGP. We observe that tissue type and library size selection have considerable impact on mitogenome sequencing and assembly. Comparing our assemblies to purportedly complete reference mitogenomes based on short-read sequencing, we identify errors, missing sequences, and incomplete genes in those references, particularly in repetitive regions. Our assemblies also identify novel gene region duplications. The presence of repeats and duplications in over half of the species herein assembled indicates that their occurrence is a principle of mitochondrial structure rather than an exception, shedding new light on mitochondrial genome evolution and organization. Conclusions Our results indicate that even in the “simple” case of vertebrate mitogenomes the completeness of many currently available reference sequences can be further improved, and caution should be exercised before claiming the complete assembly of a mitogenome, particularly from short reads alone.

Genome in a Bottle (GIAB) benchmarks have been widely used to help validate clinical sequencing pipelines and develop new variant calling and sequencing methods. Here we use accurate long and linked reads to expand the prior benchmark to include difficult-to-map regions and segmental duplications that are not readily accessible to short reads. Our new benchmark adds more than 300,000 SNVs, 50,000 indels, and 16 % new exonic variants, many in challenging, clinically relevant genes not previously covered (e.g., PMS2). We increase coverage of the autosomal GRCh38 assembly from 85 % to 92 %, while excluding problematic regions for benchmarking small variants (e.g., copy number variants and assembly errors) that should not have been in the previous version. Our new benchmark reliably identifies both false positives and false negatives across multiple short-, linked-, and long-read based variant calling methods. As an example of its utility, this benchmark identifies eight times more false negatives in a short read variant call set relative to our previous benchmark, mostly in difficult-to-map regions. To enable robust small variant benchmarking, we still exclude 3.6% of GRCh37 and 5.0% of GRCh38 in (1) highly repetitive regions such as large, highly similar segmental duplications and the centromere not accessible to our data and (2) regions where our sample is highly divergent from the reference due to large indels, structural variation, copy number variation, and/or errors in the reference (e.g., some KIR genes that have duplications in HG002). We have demonstrated the utility of this benchmark to assess performance in more challenging regions, which enables benchmarking in more difficult genes and continued technology and bioinformatics development. The v4.2.1 benchmarks are available under ftp://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/AshkenazimTrio/.

Modern sequencing technologies should make the assembly of the relatively small mitochondrial genomes an easy undertaking. However, few tools exist that address mitochondrial assembly directly. As part of the Vertebrate Genomes Project (VGP) we have developed mitoVGP, a fully automated pipeline for similarity-based identification of mitochondrial reads and de novo assembly of mitochondrial genomes that incorporates both long (>10 kbp, PacBio or Nanopore) and short (100-300 bp, Illumina) reads. Our pipeline led to successful complete mitogenome assemblies of 100 vertebrate species of the VGP. We have observed that tissue type and library size selection have considerable impact on mitogenome sequencing and assembly. Comparing our assemblies to purportedly complete reference mitogenomes based on short-read sequencing, we have identified errors, missing sequences, and incomplete genes in those references, particularly in repeat regions. Our assemblies have also identified novel gene region duplications, shedding new light on mitochondrial genome evolution and organization.

Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct accurate, phased de novo assemblies. We focus on a medically important, highly variable, 5 million base-pair (bp) region where diploid assembly is particularly useful - the Major Histocompatibility Complex (MHC). Here, we develop a human genome benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle sample HG002. We assemble a single contig for each haplotype, align them to the reference, call phased small and structural variants, and define a small variant benchmark for the MHC, covering 94% of the MHC and 22368 variants smaller than 50 bp, 49% more variants than a mapping-based benchmark. This benchmark reliably identifies errors in mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks., Accurate, phased assemblies are a key tool in understanding the human genome, particularly in highly polymorphic regions like the medically important MHC. Here the authors provide an assembly-based benchmark for this difficult-to-characterize region.

We develop the first human benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle/Personal Genome Project Ashkenazi son (HG002). As a proof-of-principle, we focus on a medically important, highly variable, 5 million base-pair region - the Major Histocompatibility Complex (MHC). Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct base-level accurate, phased de novo assemblies from the reads. We assemble a single haplotig (haplotype-specific contig) for each haplotype, and align reads back to each assembled haplotig to identify two regions of lower confidence. We align the haplotigs to the reference, call phased small and structural variants, and define the first small variant benchmark for the MHC, covering 21496 small variants in 4.58 million base-pairs (92 % of the MHC). The assembly-based benchmark is 99.95 % concordant with a draft mapping-based benchmark from the same long and linked reads within both benchmark regions, but covers 50 % more variants outside the mapping-based benchmark regions. The haplotigs and variant calls are completely concordant with phased clinical HLA types for HG002. This benchmark reliably identifies false positives and false negatives from mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks. These methods demonstrate a path towards future diploid assembly-based benchmarks for other complex regions of the genome.

Haplotype-resolved or phased sequence assembly provides a complete picture of genomes and complex genetic variations. However, current phased assembly algorithms either fail to generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method that leverages long accurate reads and long-range conformation data for single individuals to generate chromosome-scale phased assembly within a day. Applied to three public human genomes, PGP1, HG002 and NA12878, our method produced haplotype-resolved assemblies with contig NG50 up to 25 Mb and phased ∼99.5% of heterozygous sites to 98–99% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies to discover structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as HLA and KIR. Our improved method will enable high-quality precision medicine and facilitate new studies of individual haplotype variation and population diversity.

The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions 15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.

The major DNA sequencing technologies in use today produce either highly-accurate short reads or noisy long reads. We developed a protocol based on single-molecule, circular consensus sequencing (CCS) to generate highly-accurate (99.8%) long reads averaging 13.5 kb and applied it to sequence the well-characterized human HG002/NA24385. We optimized existing tools to comprehensively detect variants, achieving precision and recall above 99.91% for SNVs, 95.98% for indels, and 95.99% for structural variants. We estimate that 2,434 discordances are correctable mistakes in the high-quality Genome in a Bottle benchmark. Nearly all (99.64%) variants are phased into haplotypes, which further improves variant detection. De novo assembly produces a highly contiguous and accurate genome with contig N50 above 15 Mb and concordance of 99.998%. CCS reads match short reads for small variant detection, while enabling structural variant detection and de novo assembly at similar contiguity and markedly higher concordance than noisy long reads.

Long read sequencing technology has allowed researchers to create de novo assemblies with impressive continuity[1,2]. This advancement has dramatically increased the number of reference genomes available and hints at the possibility of a future where personal genomes are assembled rather than resequenced. In 2016 Pacific Biosciences released the FALCON-Unzip framework, which can provide long, phased haplotype contigs from de novo assemblies. This phased genome algorithm enhances the accuracy of highly heterozygous organisms and allows researchers to explore questions that require haplotype information such as allele-specific expression and regulation. However, validation of this technique has been limited to small genomes or inbred individuals[3].As a roadmap to personal genome assembly and phasing, we assess the phasing accuracy of FALCON-Unzip in humans using publicly available data for the Ashkenazi trio from the Genome in a Bottle Consortium[4]. To assess the accuracy of the Unzip algorithm, we assembled the genome of the son using FALCON and FALCON Unzip, genotyped publicly available short read data for the mother and the father, and observed the inheritance pattern of the parental SNPs along the phased genome of the son. We found that 72.8% of haplotype contigs share SNPs with only one parent suggesting that these contigs are correctly phased. Most mis-phased SNPs are random but present in high frequency toward the end of haplotype contigs. Approximately 20.7% of mis-phased haplotype contigs contain clusters of mis-phased SNPs, suggesting that haplotypes were mis-joined by FALCON-Unzip. Mis-joined boundaries in those contigs are located in areas of low SNP density. This research demonstrates that the FALCON-Unzip algorithm can be used to create long and accurate haplotypes for humans and identifies problematic regions that could benefit in future improvement.

Short tandem repeats (STRs) are implicated in dozens of human genetic diseases and contribute significantly to genome variation and instability. Yet profiling STRs from short-read sequencing data is challenging because of their high sequencing error rates. Here, we developed STR-FM, short tandem repeat profiling using flank-based mapping, a computational pipeline that can detect the full spectrum of STR alleles from short-read data, can adapt to emerging read-mapping algorithms, and can be applied to heterogeneous genetic samples (e.g., tumors, viruses, and genomes of organelles). We used STR-FM to study STR error rates and patterns in publicly available human and in-house generated ultradeep plasmid sequencing data sets. We discovered that STRs sequenced with a PCR-free protocol have up to ninefold fewer errors than those sequenced with a PCR-containing protocol. We constructed an error correction model for genotyping STRs that can distinguish heterozygous alleles containing STRs with consecutive repeat numbers. Applying our model and pipeline to Illumina sequencing data with 100-bp reads, we could confidently genotype several disease-related long trinucleotide STRs. Utilizing this pipeline, for the first time we determined the genome-wide STR germline mutation rate from a deeply sequenced human pedigree. Additionally, we built a tool that recommends minimal sequencing depth for accurate STR genotyping, depending on repeat length and sequencing read length. The required read depth increases with STR length and is lower for a PCR-free protocol. This suite of tools addresses the pressing challenges surrounding STR genotyping, and thus is of wide interest to researchers investigating disease-related STRs and STR evolution.