In 2012, NIST convened the Genome in a Bottle Consortium to develop the metrology infrastructure needed to enable confidence in human whole genome variant calls.
The Genome in a Bottle Consortium is developing the reference materials, reference methods , and reference data n
Purpose: Clinical laboratories, research laboratories and technology developers all need DNA samples with reliably known genotypes in order to help validate and improve their methods. The Genome in a Bottle Consortium (genomeinabottle.org) has been developing Reference Materials with high-accuracy whole genome sequences to support these efforts.Methodology: Our pilot reference material is based on Coriell sample NA12878 and was released in May 2015 as NIST RM 8398 (tinyurl.com/giabpilot). To minimize bias and improve accuracy, 11 whole-genome and 3 exome data sets produced using 5 different technologies were integrated using a systematic arbitration method . The Genome in a Bottle Analysis Group is adapting these methods and developing new methods to characterize 2 families, one Asian and one Ashkenazi Jewish from the Personal Genome Project, which are consented for public release of sequencing and phenotype data. We have generated a larger and even more diverse data set on these samples, including high-depth Illumina paired-end and mate-pair, Complete Genomics, and Ion Torrent short-read data, as well as Moleculo, 10X, Oxford Nanopore, PacBio, and BioNano Genomics long-read data. We are analyzing these data to provide an accurate assessment of not just small variants but also large structural variants (SVs) in both “easy” regions of the genome and in some “hard” repetitive regions. We have also made all of the input data sources publicly available for download, analysis, and publication.Results: Our arbitration method produced a reference data set of 2,787,291 single nucleotide variants (SNVs), 365,135 indels, 2744 SVs, and 2.2 billion homozygous reference calls for our pilot genome. We found that our call set is highly sensitive and specific in comparison to independent reference data sets. We have also generated preliminary assemblies and structural variant calls for the next 2 trios from long read data and are currently integrating and validating these.Discussion: We combined the strengths of each of our input datasets to develop a comprehensive and accurate benchmark call set. In the short time it has been available, over 20 published or submitted papers have used our data. Many challenges exist in comparing to our benchmark calls, and thus we have worked with the Global Alliance for Genomics and Health to develop standardized methods, performance metrics, and software to assist in its use. Zook et al, Nat Biotech. 2014.
In recent years, human genomic research has focused on comparing short-read data sets to a single human reference genome. However, it is becoming increasingly clear that significant structural variations present in individual human genomes are missed or ignored by this approach. Additionally, remapping short-read data limits the phasing of variation among individual chromosomes. This reduces the newly sequenced genome to a table of single nucleotide polymorphisms (SNPs) with little to no information as to the co-linearity (phasing) of these variants, resulting in a “mosaic” reference representing neither of the parental chromosomes. The variation between the homologous chromosomes is lost in this representation, including allelic variations, structural variations, or even genes present in only one chromosome, leading to lost information regarding allelic-specific gene expression and function. To address these limitations, we have made significant progress integrating haplotype information directly into genome assembly process with long reads. The FALCON-Unzip algorithm leverages a string graph assembly approach to facilitate identification and separation of heterozygosity during the assembly process to produce a highly contiguous assembly with phased haplotypes representing the genome in its diploid state. The outputs of the assembler are pairs of sequences (haplotigs) containing the allelic differences, including SNPs and structural variations, present in the two sets of chromosomes. The development and testing of our de-novo diploid assembler was facilitated and carefully validated using inbred reference model organisms and F1 progeny, which allowed us to ascertain the accuracy and concordance of haplotigs relative to the two inbred parental assemblies. Examination of the results confirmed that our haplotype-resolved assemblies are “Gold Level” reference genomes having a quality similar to that of Sanger-sequencing, BAC-based assembly approaches. We further sequenced and assembled two well-characterized human samples into their respective phased diploid genomes with gap-free contig N50 sizes greater than 23 Mb and haplotig N50 sizes greater than 380 kb. Results of these assemblies and a comparison between the haplotype sets are presented.
Effect of coverage depth and haplotype phasing on structural variant detection with PacBio long reads
Each human genome has thousands of structural variants compared to the reference assembly, up to 85% of which are difficult or impossible to detect with Illumina short reads and are only visible with long, multi-kilobase reads. The PacBio RS II and Sequel single molecule, real-time (SMRT) sequencing platforms have made it practical to generate long reads at high throughput. These platforms enable the discovery of structural variants just as short-read platforms did for single nucleotide variants. Numerous software algorithms call structural variants effectively from PacBio long reads, but algorithm sensitivity is lower for insertion variants and all heterozygous variants. Furthermore, the impact of coverage depth and read lengths on sensitivity is not fully characterized. To quantify how zygosity, coverage depth, and read lengths impact the sensitivity of structural variant detection, we obtained high coverage PacBio sequences for three human samples: haploid CHM1, diploid NA12878, and diploid SK-BR-3. For each dataset, reads were randomly subsampled to titrate coverage from 0.5- to 50-fold. The structural variants detected at each coverage were compared to the set at “full” 50-fold coverage. For the diploid samples, additional titrations were performed with reads first partitioned by phase using single nucleotide variants for essentially haploid structural variant discovery. Even at low coverages (1- to 5-fold), PacBio long reads reveal hundreds of structural variants that are not seen in deep 50-fold Illumina whole genome sequences. At moderate 10-fold PacBio coverage, a majority of structural variants are detected. Sensitivity begins to level off at around 40-fold coverage, though it does not fully saturate before 50-fold. Phasing improves sensitivity for all variant types, especially at moderate 10- to 20-fold coverage. Long reads are an effective tool to identify and phase structural variants in the human genome. The majority of variants are detected at moderate 10-fold coverage, and even extremely low long-read coverage (1- to 5-fold) reveals variants that are invisible to short-read sequencing. Performance will continue to improve with better software and longer reads, which will empower studies to connect structural variants to healthy and disease traits in the human population.
In this lecture Professor Carlos Bustamante from Stanford University describes the importance of expanding population genetic studies beyond a Northern European ancestry based approach into multi and trans-ethnic study designs.
Research into a bacterial sample from World War I has revealed secrets of the dysentery-causing strain’s success and uncovered the story of the soldier behind the sample.
ASHG Virtual Poster: Effect of coverage depth and haplotype phasing on structural variant detection with PacBio long reads
PacBio bioinformatician Aaron Wenger presents this ASHG 2016 poster demonstrating human structural variation detection at varying coverage levels with SMRT Sequencing on the Sequel System. Results were compared to truth…
New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls =50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.
Haplotype-resolved genome assemblies are important for understanding how combinations of variants impact phenotypes. These assemblies can be created in various ways, such as use of tissues that contain single-haplotype (haploid) genomes, or by co-sequencing of parental genomes, but these approaches can be impractical in many situations. We present FALCON-Phase, which integrates long-read sequencing data and ultra-long-range Hi-C chromatin interaction data of a diploid individual to create high-quality, phased diploid genome assemblies. The method was evaluated by application to three datasets, including human, cattle, and zebra finch, for which high-quality, fully haplotype resolved assemblies were available for benchmarking. Phasing algorithm accuracy was affected by heterozygosity of the individual sequenced, with higher accuracy for cattle and zebra finch (>97%) compared to human (82%). In addition, scaffolding with the same Hi-C chromatin contact data resulted in phased chromosome-scale scaffolds.
Whole-Genome Sequence of an Isogenic Haploid Strain, Saccharomyces cerevisiae IR-2idA30(MATa), Established from the Industrial Diploid Strain IR-2.
We present the draft genome sequence of an isogenic haploid strain, IR-2idA30(MATa), established from Saccharomyces cerevisiae IR-2. Assembly of long reads and previously obtained contigs from the genome of diploid IR-2 resulted in 50 contigs, and the variations and sequencing errors were corrected by short reads. Copyright © 2019 Fujimori et al.
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.
Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.
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.
Long-read assembly of the Chinese rhesus macaque genome and identification of ape-specific structural variants.
We present a high-quality de novo genome assembly (rheMacS) of the Chinese rhesus macaque (Macaca mulatta) using long-read sequencing and multiplatform scaffolding approaches. Compared to the current Indian rhesus macaque reference genome (rheMac8), rheMacS increases sequence contiguity 75-fold, closing 21,940 of the remaining assembly gaps (60.8 Mbp). We improve gene annotation by generating more than two million full-length transcripts from ten different tissues by long-read RNA sequencing. We sequence resolve 53,916 structural variants (96% novel) and identify 17,000 ape-specific structural variants (ASSVs) based on comparison to ape genomes. Many ASSVs map within ChIP-seq predicted enhancer regions where apes and macaque show diverged enhancer activity and gene expression. We further characterize a subset that may contribute to ape- or great-ape-specific phenotypic traits, including taillessness, brain volume expansion, improved manual dexterity, and large body size. The rheMacS genome assembly serves as an ideal reference for future biomedical and evolutionary studies.
The robust detection of structural variants in mammalian genomes remains a challenge. It is particularly difficult in the case of genetically unstable Chinese hamster ovary (CHO) cell lines with only draft genome assemblies available. We explore the potential of the CRISPR/Cas9 system for the targeted capture of genomic loci containing integrated vectors in CHO-K1-based cell lines followed by next generation sequencing (NGS), and compare it to popular target-enrichment sequencing methods and to whole genome sequencing (WGS). Three different CRISPR/Cas9-based techniques were evaluated; all of them allow for amplification-free enrichment of target genomic regions in the range from 5 to 60 fold, and for recovery of ~15 kb-long sequences with no sequencing artifacts introduced. The utility of these protocols has been proven by the identification of transgene integration sites and flanking sequences in three CHO cell lines. The long enriched fragments helped to identify Escherichia coli genome sequences co-integrated with vectors, and were further characterized by Whole Genome Sequencing (WGS). Other advantages of CRISPR/Cas9-based methods are the ease of bioinformatics analysis, potential for multiplexing, and the production of long target templates for real-time sequencing.