Benchmark small variant calls are required for developing, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) ...Consortium, we apply a reproducible, cloud-based pipeline to integrate multiple short- and linked-read sequencing datasets and provide benchmark calls for human genomes. We generate benchmark calls for one previously analyzed GIAB sample, as well as six genomes from the Personal Genome Project. These new genomes have broad, open consent, making this a 'first of its kind' resource that is available to the community for multiple downstream applications. We produce 17% more benchmark single nucleotide variations, 176% more indels and 12% larger benchmark regions than previously published GIAB benchmarks. We demonstrate that this benchmark reliably identifies errors in existing callsets and highlight challenges in interpreting performance metrics when using benchmarks that are not perfect or comprehensive. Finally, we identify strengths and weaknesses of callsets by stratifying performance according to variant type and genome context.
Thousands of experiments and studies use the human reference genome as a resource each year. This single reference genome, GRCh38, is a mosaic created from a small number of individuals, representing ...a very small sample of the human population. There is a need for reference genomes from multiple human populations to avoid potential biases.
Here, we describe the assembly and annotation of the genome of an Ashkenazi individual and the creation of a new, population-specific human reference genome. This genome is more contiguous and more complete than GRCh38, the latest version of the human reference genome, and is annotated with highly similar gene content. The Ashkenazi reference genome, Ash1, contains 2,973,118,650 nucleotides as compared to 2,937,639,212 in GRCh38. Annotation identified 20,157 protein-coding genes, of which 19,563 are > 99% identical to their counterparts on GRCh38. Most of the remaining genes have small differences. Forty of the protein-coding genes in GRCh38 are missing from Ash1; however, all of these genes are members of multi-gene families for which Ash1 contains other copies. Eleven genes appear on different chromosomes from their homologs in GRCh38. Alignment of DNA sequences from an unrelated Ashkenazi individual to Ash1 identified ~ 1 million fewer homozygous SNPs than alignment of those same sequences to the more-distant GRCh38 genome, illustrating one of the benefits of population-specific reference genomes.
The Ash1 genome is presented as a reference for any genetic studies involving Ashkenazi Jewish individuals.
Clinical adoption of human genome sequencing requires methods that output genotypes with known accuracy at millions or billions of positions across a genome. Because of substantial discordance among ...calls made by existing sequencing methods and algorithms, there is a need for a highly accurate set of genotypes across a genome that can be used as a benchmark. Here we present methods to make high-confidence, single-nucleotide polymorphism (SNP), indel and homozygous reference genotype calls for NA12878, the pilot genome for the Genome in a Bottle Consortium. We minimize bias toward any method by integrating and arbitrating between 14 data sets from five sequencing technologies, seven read mappers and three variant callers. We identify regions for which no confident genotype call could be made, and classify them into different categories based on reasons for uncertainty. Our genotype calls are publicly available on the Genome Comparison and Analytic Testing website to enable real-time benchmarking of any method.
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.
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 <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.
In read cloud approaches, microfluidic partitioning of long genomic DNA fragments and barcoding of shorter fragments derived from these fragments retains long-range information in short sequencing ...reads. This combination of short reads with long-range information represents a powerful alternative to single-molecule long-read sequencing. We develop Genome-wide Reconstruction of Complex Structural Variants (GROC-SVs) for SV detection and assembly from read cloud data and apply this method to Illumina-sequenced 10x Genomics sarcoma and breast cancer data sets. Compared with short-fragment sequencing, GROC-SVs substantially improves the specificity of breakpoint detection at comparable sensitivity. This approach also performs sequence assembly across multiple breakpoints simultaneously, enabling the reconstruction of events exhibiting remarkable complexity. We show that chromothriptic rearrangements occurred before copy number amplifications, and that rates of single-nucleotide variants and SVs are not correlated. Our results support the use of read cloud approaches to advance the characterization of large and complex structural variation.
Abstract Tandem repeats are frequent across the human genome, and variation in repeat length has been linked to a variety of traits. Recent improvements in long read sequencing technologies have the ...potential to greatly improve tandem repeat analysis, especially for long or complex repeats. Here, we introduce LongTR, which accurately genotypes tandem repeats from high-fidelity long reads available from both PacBio and Oxford Nanopore Technologies. LongTR is freely available at https://github.com/gymrek-lab/longtr and https://zenodo.org/doi/10.5281/zenodo.11403979 .
De novo assembly of a human genome using nanopore long-read sequences has been reported, but it used more than 150,000 CPU hours and weeks of wall-clock time. To enable rapid human genome assembly, ...we present Shasta, a de novo long-read assembler, and polishing algorithms named MarginPolish and HELEN. Using a single PromethION nanopore sequencer and our toolkit, we assembled 11 highly contiguous human genomes de novo in 9 d. We achieved roughly 63× coverage, 42-kb read N50 values and 6.5× coverage in reads >100 kb using three flow cells per sample. Shasta produced a complete haploid human genome assembly in under 6 h on a single commercial compute node. MarginPolish and HELEN polished haploid assemblies to more than 99.9% identity (Phred quality score QV = 30) with nanopore reads alone. Addition of proximity-ligation sequencing enabled near chromosome-level scaffolds for all 11 genomes. We compare our assembly performance to existing methods for diploid, haploid and trio-binned human samples and report superior accuracy and speed.
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.
Standardized benchmarking approaches are required to assess the accuracy of variants called from sequence data. Although variant-calling tools and the metrics used to assess their performance ...continue to improve, important challenges remain. Here, as part of the Global Alliance for Genomics and Health (GA4GH), we present a benchmarking framework for variant calling. We provide guidance on how to match variant calls with different representations, define standard performance metrics, and stratify performance by variant type and genome context. We describe limitations of high-confidence calls and regions that can be used as truth sets (for example, single-nucleotide variant concordance of two methods is 99.7% inside versus 76.5% outside high-confidence regions). Our web-based app enables comparison of variant calls against truth sets to obtain a standardized performance report. Our approach has been piloted in the PrecisionFDA variant-calling challenges to identify the best-in-class variant-calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and evaluating the results.
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