Read clouds uncover variation in complex regions of the human genome

Hybridization of Atlantic puffins in the Arctic coincides with 20th-century climate change

The Arctic is experiencing the fastest rates of global warming, leading to shifts in the distribution of its biota and increasing the potential for hybridization. However, genomic evidence of recent hybridization events in the Arctic remains unexpectedly rare. Here, we use whole-genome sequencing of contemporary and 122-year-old historical specimens to investigate the origin of an Arctic hybrid population of Atlantic puffins (Fratercula arctica) on Bjørnøya, Norway. We show that the hybridization between the High Arctic, large-bodied subspecies F. a. naumanni and the temperate, smaller-sized subspecies F. a. arctica began as recently as six generations ago due to an unexpected southward range expansion of F. a. naumanni. Moreover, we find a significant temporal loss of genetic diversity across Arctic and temperate puffin populations. Our observations provide compelling genomic evidence of the impacts of recent distributional shifts and loss of diversity in Arctic communities during the 20th century.

Co-evolution of AR gene copy number and structural complexity in endocrine therapy resistant prostate cancer

Androgen receptor (AR) inhibition is standard of care for advanced prostate cancer (PC). However, efficacy is limited by progression to castration-resistant PC (CRPC), usually due to AR re-activation via mechanisms that include AR amplification and structural rearrangement. These two classes of AR alterations often co-occur in CRPC tumors, but it is unclear whether this reflects intercellular or intracellular heterogeneity of AR. Resolving this is important for developing new therapies and predictive biomarkers. Here, we analyzed 41 CRPC tumors and 6 patient-derived xenografts (PDXs) using linked-read DNA-sequencing, and identified 7 tumors that developed complex, multiply-rearranged AR gene structures in conjunction with very high AR copy number. Analysis of PDX models by optical genome mapping and fluorescence in situ hybridization showed that AR residing on extrachromosomal DNA (ecDNA) was an underlying mechanism, and was associated with elevated levels and diversity of AR expression. This study identifies co-evolution of AR gene copy number and structural complexity via ecDNA as a mechanism associated with endocrine therapy resistance.

Genome graphs detect human polymorphisms in active epigenomic state during influenza infection

Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that genome graphs, which encapsulate genetic diversity, could reveal missing epigenomic signals. To test this, we sequenced the epigenome of monocyte-derived macrophages from 35 ancestrally diverse individuals before and after influenza infection, allowing us to investigate the role of MEIs in immunity. We characterized genetic variants and MEIs using linked reads and built a genome graph. Mapping epigenetic data revealed 2.3%-3% novel peaks for H3K4me1, H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq), and ATAC-seq. Additionally, the use of a genome graph modified some quantitative trait loci estimates and revealed 375 polymorphic MEIs in an active epigenomic state. Among these is an AluYh3 polymorphism whose chromatin state changed after infection and was associated with the expression of TRIM25, a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.

FarGen: Elucidating the distribution of coding variants in the isolated population of the Faroe Islands

Here we present results from FarGen Phase I exomes. This dataset is based on the FarGen cohort, which consists of 1,541 individuals from the isolated population of the Faroe Islands. The purpose of this cohort is to serve as a reference catalog of coding variants, and to conduct population genetic studies to better understand the genetic contribution to various diseases in the Faroese population. The first whole-exome data set comprise 465 individuals and a total of 148,267 genetic variants were discovered. Principle Component Analysis indicates that the population is isolated and weakly structured. The distribution of variants in various functional classes was compared with populations in the gnomAD dataset; the results indicated that the proportions were consistent across the cohorts, but probably due to a small sample size, the FarGen dataset contained relatively few rare variants. We identified 19 variants that are classified as pathogenic or likely pathogenic in ClinVar; several of these variants are associated with monogenetic diseases with increased prevalence in the Faroe Islands. The results support previous studies, which indicate that the Faroe Islands is an isolated and weakly structured population. Future studies may elucidate the significance of the 19 pathogenic variants that were identified. The FarGen Phase I dataset is an important step for genetic research in the Faroese population, and the next phase of FarGen will increase the sample size and broaden the scope.

MetaTrass: A high-quality metagenome assembler of the human gut microbiome by cobarcoding sequencing reads

Metagenomic evidence of great genetic diversity within the nonconserved regions of the human gut microbial genomes appeals for new methods to elucidate the species-level variability at high resolution. However, current approaches cannot satisfy this methodologically challenge. In this study, we proposed an efficient binning-first-and-assembly-later strategy, named MetaTrass, to recover high-quality species-resolved genomes based on public reference genomes and the single-tube long fragment read (stLFR) technology, which enables cobarcoding. MetaTrass can generate genomes with longer contiguity, higher completeness, and lower contamination than those produced by conventional assembly-first-and-binning-later strategies. From a simulation study on a mock microbial community, MetaTrass showed the potential to improve the contiguity of assembly from kb to Mb without accuracy loss, as compared to other methods based on the next-generation sequencing technology. From four human fecal samples, MetaTrass successfully retrieved 178 high-quality genomes, whereas only 58 ones were provided by the optimal performance of other conventional strategies. Most importantly, these high-quality genomes confirmed the high level of genetic diversity among different samples and unveiled much more. MetaTrass was designed to work with metagenomic reads sequenced by stLFR technology, but is also applicable to other types of cobarcoding libraries. With the high capability of assembling high-quality genomes of metagenomic data sets, MetaTrass seeks to facilitate the study of spatial characters and dynamics of complex microbial communities at enhanced resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass.

A high-quality, long-read genome assembly of the endangered ring-tailed lemur (Lemur catta)

BACKGROUND

The ring-tailed lemur (Lemur catta) is a charismatic strepsirrhine primate endemic to Madagascar. These lemurs are of particular interest, given their status as a flagship species and widespread publicity in the popular media. Unfortunately, a recent population decline has resulted in the census population decreasing to <2,500 individuals in the wild, and the species's classification as an endangered species by the IUCN. As is the case for most strepsirrhine primates, only a limited amount of genomic research has been conducted on L. catta, in part owing to the lack of genomic resources.

RESULTS

We generated a new high-quality reference genome assembly for L. catta (mLemCat1) that conforms to the standards of the Vertebrate Genomes Project. This new long-read assembly is composed of Pacific Biosciences continuous long reads (CLR data), Optical Mapping Bionano reads, Arima HiC data, and 10X linked reads. The contiguity and completeness of the assembly are extremely high, with scaffold and contig N50 values of 90.982 and 10.570 Mb, respectively. Additionally, when compared to other high-quality primate assemblies, L. catta has the lowest reported number of Alu elements, which results predominantly from a lack of AluS and AluY elements.

CONCLUSIONS

mLemCat1 is an excellent genomic resource not only for the ring-tailed lemur community, but also for other members of the Lemuridae family, and is the first very long read assembly for a strepsirrhine.

Local selection signals in the genome of Blue tits emphasize regulatory and neuronal evolution

Understanding the genomic landscape of adaptation is central to the understanding of microevolution in wild populations. Genomic targets of selection and the underlying genomic mechanisms of adaptation can be elucidated by genome-wide scans for past selective sweeps or by scans for direct fitness associations. We sequenced and assembled 150 haplotypes of 75 Blue tits (Cyanistes caeruleus) of a single central-European population by a linked-read technology. We used these genome data in combination with coalescent simulations (1) to estimate an historical effective population size of ~250,000, which recently declined to ~10,000, and (2) to identify genome-wide distributed selective sweeps of beneficial variants most likely originating from standing genetic variation (soft sweeps). The genes linked to these soft sweeps, but also the ones linked to hard sweeps based on new beneficial mutants, showed a significant enrichment for functions associated with gene expression and transcription regulation. This emphasizes the importance of regulatory evolution in the population's adaptive history. Soft sweeps were further enriched for genes related to axon and synapse development, indicating the significance of neuronal connectivity changes in the brain potentially linked to behavioural adaptations. A previous scan of heterozygosity-fitness correlations revealed a consistent negative effect on arrival date at the breeding site for a single microsatellite in the MDGA2 gene. Here, we used the haplotype structure around this microsatellite to explain the effect as a local and direct outbreeding effect of a gene involved in synapse development.

A pan-cancer landscape of somatic mutations in non-unique regions of the human genome

A substantial fraction of the human genome displays high sequence similarity with at least one other genomic sequence, posing a challenge for the identification of somatic mutations from short-read sequencing data. Here we annotate genomic variants in 2,658 cancers from the Pan-Cancer Analysis of Whole Genomes (PCAWG) cohort with links to similar sites across the human genome. We train a machine learning model to use signals distributed over multiple genomic sites to call somatic events in non-unique regions and validate the data against linked-read sequencing in an independent dataset. Using this approach, we uncover previously hidden mutations in ~1,700 coding sequences and in thousands of regulatory elements, including in known cancer genes, immunoglobulins and highly mutated gene families. Mutations in non-unique regions are consistent with mutations in unique regions in terms of mutation burden and substitution profiles. The analysis provides a systematic summary of the mutation events in non-unique regions at a genome-wide scale across multiple human cancers.

Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

ARBitR: an overlap-aware genome assembly scaffolder for linked reads

Summary

Linked genomic sequencing reads contain information that can be used to join sequences together into scaffolds in draft genome assemblies. Existing software for this purpose performs the scaffolding by joining sequences with a gap between them, not considering potential overlaps of contigs. We developed ARBitR to create scaffolds where overlaps are taken into account and show that it can accurately recreate regions where draft assemblies are broken.

Availability and implementation

ARBitR is written and implemented in Python3 for Unix-based operative systems. All source code is available at https://github.com/markhilt/ARBitR under the GNU General Public License v3.

Supplementary information

Supplementary data are available at Bioinformatics online.

Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology

Short-read, high-throughput sequencing (HTS) methods have yielded numerous important insights into microbial ecology and function. Yet, in many instances short-read HTS techniques are suboptimal, for example, by providing insufficient phylogenetic resolution or low integrity of assembled genomes. Single-molecule and synthetic long-read (SLR) HTS methods have successfully ameliorated these limitations. In addition, nanopore sequencing has generated a number of unique analysis opportunities, such as rapid molecular diagnostics and direct RNA sequencing, and both Pacific Biosciences (PacBio) and nanopore sequencing support detection of epigenetic modifications. Although initially suffering from relatively low sequence quality, recent advances have greatly improved the accuracy of long-read sequencing technologies. In spite of great technological progress in recent years, the long-read HTS methods (PacBio and nanopore sequencing) are still relatively costly, require large amounts of high-quality starting material, and commonly need specific solutions in various analysis steps. Despite these challenges, long-read sequencing technologies offer high-quality, cutting-edge alternatives for testing hypotheses about microbiome structure and functioning as well as assembly of eukaryote genomes from complex environmental DNA samples.

Evolutionary and biomedical insights from a marmoset diploid genome assembly

The accurate and complete assembly of both haplotype sequences of a diploid organism is essential to understanding the role of variation in genome functions, phenotypes and diseases¹. Here, using a trio-binning approach, we present a high-quality, diploid reference genome, with both haplotypes assembled independently at the chromosome level, for the common marmoset (Callithrix jacchus), an primate model system that is widely used in biomedical research^2,3. The full spectrum of heterozygosity between the two haplotypes involves 1.36% of the genome-much higher than the 0.13% indicated by the standard estimation based on single-nucleotide heterozygosity alone. The de novo mutation rate is 0.43 × 10^-8 per site per generation, and the paternal inherited genome acquired twice as many mutations as the maternal. Our diploid assembly enabled us to discover a recent expansion of the sex-differentiation region and unique evolutionary changes in the marmoset Y chromosome. In addition, we identified many genes with signatures of positive selection that might have contributed to the evolution of Callithrix biological features. Brain-related genes were highly conserved between marmosets and humans, although several genes experienced lineage-specific copy number variations or diversifying selection, with implications for the use of marmosets as a model system.

Towards complete and error-free genome assemblies of all vertebrate species

High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species1-4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences.

SLR-superscaffolder: a de novo scaffolding tool for synthetic long reads using a top-to-bottom scheme

Background

Synthetic long reads (SLR) with long-range co-barcoding information are now widely applied in genomics research. Although several tools have been developed for each specific SLR technique, a robust standalone scaffolder with high efficiency is warranted for hybrid genome assembly.

Results

In this work, we developed a standalone scaffolding tool, SLR-superscaffolder, to link together contigs in draft assemblies using co-barcoding and paired-end read information. Our top-to-bottom scheme first builds a global scaffold graph based on Jaccard Similarity to determine the order and orientation of contigs, and then locally improves the scaffolds with the aid of paired-end information. We also exploited a screening algorithm to reduce the negative effect of misassembled contigs in the input assembly. We applied SLR-superscaffolder to a human single tube long fragment read sequencing dataset and increased the scaffold NG50 of its corresponding draft assembly 1349 fold. Moreover, benchmarking on different input contigs showed that this approach overall outperformed existing SLR scaffolders, providing longer contiguity and fewer misassemblies, especially for short contigs assembled by next-generation sequencing data. The open-source code of SLR-superscaffolder is available at https://github.com/BGI-Qingdao/SLR-superscaffolder.

Conclusions

SLR-superscaffolder can dramatically improve the contiguity of a draft assembly by integrating a hybrid assembly strategy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04081-z.

Accurate Haplotype-Resolved Assembly Reveals The Origin Of Structural Variants For Human Trios

MOTIVATION

Achieving a near complete understanding of how the genome of an individual affects the phenotypes of that individual requires deciphering the order of variations along homologous chromosomes in species with diploid genomes. However, true diploid assembly of long-range haplotypes remains challenging.

RESULTS

To address this, we have developed Haplotype-resolved Assembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental information to classify reads into maternal or paternal. Once sorted, these reads are used to independently de novo assemble the parent-specific haplotypes. We applied HAST to co-barcoded second-generation sequencing data from an Asian individual, resulting in a haplotype assembly covering 94.7% of the reference genome with a scaffold N50 longer than 11 Mb. The high haplotyping precision (∼99.7%) and recall (∼95.9%) represents a substantial improvement over the commonly used tool for assembling co-barcoded reads (Supernova), and is comparable to a trio-binning-based third generation long-read based assembly method (TrioCanu) but with a significantly higher single-base accuracy (up to 99.99997% (Q65)). This makes HAST a superior tool for accurate haplotyping and future haplotype-based studies.

AVAILABILITY

The code of the analysis is available at https://github.com/BGI-Qingdao/HAST.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Noninvasive prenatal test of single-gene disorders by linked-read direct haplotyping: application in various diseases

Direct haplotyping enables noninvasive prenatal testing (NIPT) without analyzing proband, which is a promising strategy for pregnancies at risk of an inherited single-gene disorder. Here, we aimed to expand the scope of single-gene disorders that NIPT using linked-read direct haplotyping would be applicable to. Three families at risk of myotonic dystrophy type 1, lipoid congenital adrenal hyperplasia, and Fukuyama congenital muscular dystrophy were recruited. All cases exhibited distinct characteristics that are often encountered as hurdles (i.e., repeat expansion, identical variants in both parents, and novel variants with retrotransposon insertion) in the universal clinical application of NIPT. Direct haplotyping of parental genomes was performed by linked-read sequencing, combined with allele-specific PCR, if necessary. Target DMPK, STAR, and FKTN genes in the maternal plasma DNA were sequenced. Posterior risk calculations and an Anderson-Darling test were performed to deduce the maternal and paternal inheritance, respectively. In all cases, we could predict the inheritance of maternal mutant allele with > 99.9% confidence, while paternal mutant alleles were not predicted to be inherited. Our study indicates that direct haplotyping and posterior risk calculation can be applied with subtle modifications to NIPT for the detection of an expanded range of diseases.

Strain-resolved microbiome sequencing reveals mobile elements that drive bacterial competition on a clinical timescale

BACKGROUND

Populations of closely related microbial strains can be simultaneously present in bacterial communities such as the human gut microbiome. We recently developed a de novo genome assembly approach that uses read cloud sequencing to provide more complete microbial genome drafts, enabling precise differentiation and tracking of strain-level dynamics across metagenomic samples. In this case study, we present a proof-of-concept using read cloud sequencing to describe bacterial strain diversity in the gut microbiome of one hematopoietic cell transplantation patient over a 2-month time course and highlight temporal strain variation of gut microbes during therapy. The treatment was accompanied by diet changes and administration of multiple immunosuppressants and antimicrobials.

METHODS

We conducted short-read and read cloud metagenomic sequencing of DNA extracted from four longitudinal stool samples collected during the course of treatment of one hematopoietic cell transplantation (HCT) patient. After applying read cloud metagenomic assembly to discover strain-level sequence variants in these complex microbiome samples, we performed metatranscriptomic analysis to investigate differential expression of antibiotic resistance genes. Finally, we validated predictions from the genomic and metatranscriptomic findings through in vitro antibiotic susceptibility testing and whole genome sequencing of isolates derived from the patient stool samples.

RESULTS

During the 56-day longitudinal time course that was studied, the patient's microbiome was profoundly disrupted and eventually dominated by Bacteroides caccae. Comparative analysis of B. caccae genomes obtained using read cloud sequencing together with metagenomic RNA sequencing allowed us to identify differences in substrain populations over time. Based on this, we predicted that particular mobile element integrations likely resulted in increased antibiotic resistance, which we further supported using in vitro antibiotic susceptibility testing.

CONCLUSIONS

We find read cloud assembly to be useful in identifying key structural genomic strain variants within a metagenomic sample. These strains have fluctuating relative abundance over relatively short time periods in human microbiomes. We also find specific structural genomic variations that are associated with increased antibiotic resistance over the course of clinical treatment.

Structural variation in the sequencing era

Identifying structural variation (SV) is essential for genome interpretation but has been historically difficult due to limitations inherent to available genome technologies. Detection methods that use ensemble algorithms and emerging sequencing technologies have enabled the discovery of thousands of SVs, uncovering information about their ubiquity, relationship to disease and possible effects on biological mechanisms. Given the variability in SV type and size, along with unique detection biases of emerging genomic platforms, multiplatform discovery is necessary to resolve the full spectrum of variation. Here, we review modern approaches for investigating SVs and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

De novo diploid genome assembly for genome-wide structural variant detection

Detection of structural variants (SVs) on the basis of read alignment to a reference genome remains a difficult problem. De novo assembly, traditionally used to generate reference genomes, offers an alternative for SV detection. However, it has not been applied broadly to human genomes because of fundamental limitations of short-fragment approaches and high cost of long-read technologies. We here show that 10× linked-read sequencing supports accurate SV detection. We examined variants in six de novo 10× assemblies with diverse experimental parameters from two commonly used human cell lines: NA12878 and NA24385. The assemblies are effective for detecting mid-size SVs, which were discovered by simple pairwise alignment of the assemblies’ contigs to the reference (hg38). Our study also shows that the base-pair level SV breakpoint accuracy is high, with a majority of SVs having precisely correct sizes and breakpoints. Setting the ancestral state of SV loci by comparing to ape orthologs allows inference of the actual molecular mechanism (insertion or deletion) causing the mutation. In about half of cases, the mechanism is the opposite of the reference-based call. We uncover 214 SVs that may have been maintained as polymorphisms in the human lineage since before our divergence from chimp. Overall, we show that de novo assembly of 10× linked-read data can achieve cost-effective SV detection for personal genomes.

LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data

Linked-read sequencing provides long-range information on short-read sequencing data by barcoding reads originating from the same DNA molecule, and can improve detection and breakpoint identification for structural variants (SVs). Here we present LinkedSV for SV detection on linked-read sequencing data. LinkedSV considers barcode overlapping and enriched fragment endpoints as signals to detect large SVs, while it leverages read depth, paired-end signals and local assembly to detect small SVs. Benchmarking studies demonstrate that LinkedSV outperforms existing tools, especially on exome data and on somatic SVs with low variant allele frequencies. We demonstrate clinical cases where LinkedSV identifies disease-causal SVs from linked-read exome sequencing data missed by conventional exome sequencing, and show examples where LinkedSV identifies SVs missed by high-coverage long-read sequencing. In summary, LinkedSV can detect SVs missed by conventional short-read and long-read sequencing approaches, and may resolve negative cases from clinical genome/exome sequencing studies.

Statistical Binning for Barcoded Reads Improves Downstream Analyses

Sequencing technologies are capturing longer-range genomic information at lower error rates, enabling alignment to genomic regions that are inaccessible with short reads. However, many methods are unable to align reads to much of the genome, recognized as important in disease, and thus report erroneous results in downstream analyses. We introduce EMA, a novel two-tiered statistical binning model for barcoded read alignment, that first probabilistically maps reads to potentially multiple "read clouds" and then within clouds by newly exploiting the non-uniform read densities characteristic of barcoded read sequencing. EMA substantially improves downstream accuracy over existing methods, including phasing and genotyping on 10x data, with fewer false variant calls in nearly half the time. EMA effectively resolves particularly challenging alignments in genomic regions that contain nearby homologous elements, uncovering variants in the pharmacogenomically important CYP2D region, and clinically important genes C4 (schizophrenia) and AMY1A (obesity), which go undetected by existing methods. Our work provides a framework for future generation sequencing.

Current and Promising Approaches to Identify Horizontal Gene Transfer Events in Metagenomes

High-throughput shotgun metagenomics sequencing has enabled the profiling of myriad natural communities. These data are commonly used to identify gene families and pathways that were potentially gained or lost in an environment and which may be involved in microbial adaptation. Despite the widespread interest in these events, there are no established best practices for identifying gene gain and loss in metagenomics data. Horizontal gene transfer (HGT) represents several mechanisms of gene gain that are especially of interest in clinical microbiology due to the rapid spread of antibiotic resistance genes in natural communities. Several additional mechanisms of gene gain and loss, including gene duplication, gene loss-of-function events, and de novo gene birth are also important to consider in the context of metagenomes but have been less studied. This review is largely focused on detecting HGT in prokaryotic metagenomes, but methods for detecting these other mechanisms are first discussed. For this article to be self-contained, we provide a general background on HGT and the different possible signatures of this process. Lastly, we discuss how improved assembly of genomes from metagenomes would be the most straight-forward approach for improving the inference of gene gain and loss events. Several recent technological advances could help improve metagenome assemblies: long-read sequencing, determining the physical proximity of contigs, optical mapping of short sequences along chromosomes, and single-cell metagenomics. The benefits and limitations of these advances are discussed and open questions in this area are highlighted.

Samovar: Single-Sample Mosaic Single-Nucleotide Variant Calling with Linked Reads

Linked-read sequencing enables greatly improves haplotype assembly over standard paired-end analysis. The detection of mosaic single-nucleotide variants benefits from haplotype assembly when the model is informed by the mapping between constituent reads and linked reads. Samovar evaluates haplotype-discordant reads identified through linked-read sequencing, thus enabling phasing and mosaic variant detection across the entire genome. Samovar trains a random forest model to score candidate sites using a dataset that considers read quality, phasing, and linked-read characteristics. Samovar calls mosaic single-nucleotide variants (SNVs) within a single sample with accuracy comparable with what previously required trios or matched tumor/normal pairs and outperforms single-sample mosaic variant callers at minor allele frequency 5%-50% with at least 30X coverage. Samovar finds somatic variants in both tumor and normal whole-genome sequencing from 13 pediatric cancer cases that can be corroborated with high recall with whole exome sequencing. Samovar is available open-source at https://github.com/cdarby/samovar under the MIT license.

Piercing the dark matter: bioinformatics of long-range sequencing and mapping

Several new genomics technologies have become available that offer long-read sequencing or long-range mapping with higher throughput and higher resolution analysis than ever before. These long-range technologies are rapidly advancing the field with improved reference genomes, more comprehensive variant identification and more complete views of transcriptomes and epigenomes. However, they also require new bioinformatics approaches to take full advantage of their unique characteristics while overcoming their complex errors and modalities. Here, we discuss several of the most important applications of the new technologies, focusing on both the currently available bioinformatics tools and opportunities for future research.

A chromosome-scale assembly of the major African malaria vector Anopheles funestus

BACKGROUND

Anopheles funestus is one of the 3 most consequential and widespread vectors of human malaria in tropical Africa. However, the lack of a high-quality reference genome has hindered the association of phenotypic traits with their genetic basis in this important mosquito.

FINDINGS

Here we present a new high-quality A. funestus reference genome (AfunF3) assembled using 240× coverage of long-read single-molecule sequencing for contigging, combined with 100× coverage of short-read Hi-C data for chromosome scaffolding. The assembled contigs total 446 Mbp of sequence and contain substantial duplication due to alternative alleles present in the sequenced pool of mosquitos from the FUMOZ colony. Using alignment and depth-of-coverage information, these contigs were deduplicated to a 211 Mbp primary assembly, which is closer to the expected haploid genome size of 250 Mbp. This primary assembly consists of 1,053 contigs organized into 3 chromosome-scale scaffolds with an N50 contig size of 632 kbp and an N50 scaffold size of 93.811 Mbp, representing a 100-fold improvement in continuity versus the current reference assembly, AfunF1.

CONCLUSION

This highly contiguous and complete A. funestus reference genome assembly will serve as an improved basis for future studies of genomic variation and organization in this important disease vector.

Comparative analysis of de novo assemblers for variation discovery in personal genomes

Current variant discovery approaches often rely on an initial read mapping to the reference sequence. Their effectiveness is limited by the presence of gaps, potential misassemblies, regions of duplicates with a high-sequence similarity and regions of high-sequence divergence in the reference. Also, mapping-based approaches are less sensitive to large INDELs and complex variations and provide little phase information in personal genomes. A few de novo assemblers have been developed to identify variants through direct variant calling from the assembly graph, micro-assembly and whole-genome assembly, but mainly for whole-genome sequencing (WGS) data. We developed SGVar, a de novo assembly workflow for haplotype-based variant discovery from whole-exome sequencing (WES) data. Using simulated human exome data, we compared SGVar with five variation-aware de novo assemblers and with BWA-MEM together with three haplotype- or local de novo assembly-based callers. SGVar outperforms the other assemblers in sensitivity and tolerance of sequencing errors. We recapitulated the findings on whole-genome and exome data from a Utah residents with Northern and Western European ancestry (CEU) trio, showing that SGVar had high sensitivity both in the highly divergent human leukocyte antigen (HLA) region and in non-HLA regions of chromosome 6. In particular, SGVar is robust to sequencing error, k-mer selection, divergence level and coverage depth. Unlike mapping-based approaches, SGVar is capable of resolving long-range phase and identifying large INDELs from WES, more prominently from WGS. We conclude that SGVar represents an ideal platform for WES-based variant discovery in highly divergent regions and across the whole genome.

Resolving the full spectrum of human genome variation using Linked-Reads

Large-scale population analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short-read whole-genome sequencing. However, these short-read approaches fail to give a complete picture of a genome. They struggle to identify structural events, cannot access repetitive regions, and fail to resolve the human genome into haplotypes. Here, we describe an approach that retains long range information while maintaining the advantages of short reads. Starting from ∼1 ng of high molecular weight DNA, we produce barcoded short-read libraries. Novel informatic approaches allow for the barcoded short reads to be associated with their original long molecules producing a novel data type known as "Linked-Reads". This approach allows for simultaneous detection of small and large variants from a single library. In this manuscript, we show the advantages of Linked-Reads over standard short-read approaches for reference-based analysis. Linked-Reads allow mapping to 38 Mb of sequence not accessible to short reads, adding sequence in 423 difficult-to-sequence genes including disease-relevant genes STRC, SMN1, and SMN2 Both Linked-Read whole-genome and whole-exome sequencing identify complex structural variations, including balanced events and single exon deletions and duplications. Further, Linked-Reads extend the region of high-confidence calls by 68.9 Mb. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

Extensive and deep sequencing of the Venter/HuRef genome for developing and benchmarking genome analysis tools

We produced an extensive collection of deep re-sequencing datasets for the Venter/HuRef genome using the Illumina massively-parallel DNA sequencing platform. The original Venter genome sequence is a very-high quality phased assembly based on Sanger sequencing. Therefore, researchers developing novel computational tools for the analysis of human genome sequence variation for the dominant Illumina sequencing technology can test and hone their algorithms by making variant calls from these Venter/HuRef datasets and then immediately confirm the detected variants in the Sanger assembly, freeing them of the need for further experimental validation. This process also applies to implementing and benchmarking existing genome analysis pipelines. We prepared and sequenced 200 bp and 350 bp short-insert whole-genome sequencing libraries (sequenced to 100x and 40x genomic coverages respectively) as well as 2 kb, 5 kb, and 12 kb mate-pair libraries (49x, 122x, and 145x physical coverages respectively). Lastly, we produced a linked-read library (128x physical coverage) from which we also performed haplotype phasing.

High-quality genome sequences of uncultured microbes by assembly of read clouds

Although shotgun metagenomic sequencing of microbiome samples enables partial reconstruction of strain-level community structure, obtaining high-quality microbial genome drafts without isolation and culture remains difficult. Here, we present an application of read clouds, short-read sequences tagged with long-range information, to microbiome samples. We present Athena, a de novo assembler that uses read clouds to improve metagenomic assemblies. We applied this approach to sequence stool samples from two healthy individuals and compared it with existing short-read and synthetic long-read metagenomic sequencing techniques. Read-cloud metagenomic sequencing and Athena assembly produced the most comprehensive individual genome drafts with high contiguity (>200-kb N50, fewer than ten contigs), even for bacteria with relatively low (20×) raw short-read-sequence coverage. We also sequenced a complex marine-sediment sample and generated 24 intermediate-quality genome drafts (>70% complete, <10% contaminated), nine of which were complete (>90% complete, <5% contaminated). Our approach allows for culture-free generation of high-quality microbial genome drafts by using a single shotgun experiment.

HAPDeNovo: a haplotype-based approach for filtering and phasing de novo mutations in linked read sequencing data

BACKGROUND

De novo mutations (DNMs) are associated with neurodevelopmental and congenital diseases, and their detection can contribute to understanding disease pathogenicity. However, accurate detection is challenging because of their small number relative to the genome-wide false positives in next generation sequencing (NGS) data. Software such as DeNovoGear and TrioDeNovo have been developed to detect DNMs, but at good sensitivity they still produce many false positive calls.

RESULTS

To address this challenge, we develop HAPDeNovo, a program that leverages phasing information from linked read sequencing, to remove false positive DNMs from candidate lists generated by DNM-detection tools. Short reads from each phasing block are allocated to each of the two haplotypes followed by generating a haploid genotype for each putative DNM. HAPDeNovo removes variants that are called as heterozygous in one of the haplotypes because they are almost certainly false positives. Our experiments on 10X Chromium linked read sequencing trio data reveal that HAPDeNovo eliminates 80 to 99% of false positives regardless of how large the candidate DNM set is.

CONCLUSIONS

HAPDeNovo leverages the haplotype information from linked read sequencing to remove spurious false positive DNMs effectively, and it increases accuracy of DNM detection dramatically without sacrificing sensitivity.

An accurate algorithm for the detection of DNA fragments from dilution pool sequencing experiments

Motivation

The short read lengths of current high-throughput sequencing technologies limit the ability to recover long-range haplotype information. Dilution pool methods for preparing DNA sequencing libraries from high molecular weight DNA fragments enable the recovery of long DNA fragments from short sequence reads. These approaches require computational methods for identifying the DNA fragments using aligned sequence reads and assembling the fragments into long haplotypes. Although a number of computational methods have been developed for haplotype assembly, the problem of identifying DNA fragments from dilution pool sequence data has not received much attention.

Results

We formulate the problem of detecting DNA fragments from dilution pool sequencing experiments as a genome segmentation problem and develop an algorithm that uses dynamic programming to optimize a likelihood function derived from a generative model for the sequence reads. This algorithm uses an iterative approach to automatically infer the mean background read depth and the number of fragments in each pool. Using simulated data, we demonstrate that our method, FragmentCut, has 25-30% greater sensitivity compared with an HMM based method for fragment detection and can also detect overlapping fragments. On a whole-genome human fosmid pool dataset, the haplotypes assembled using the fragments identified by FragmentCut had greater N50 length, 16.2% lower switch error rate and 35.8% lower mismatch error rate compared with two existing methods. We further demonstrate the greater accuracy of our method using two additional dilution pool datasets.

Availability and implementation

FragmentCut is available from https://bansal-lab.github.io/software/FragmentCut.

Contact

vibansal@ucsd.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Bat Biology, Genomes, and the Bat1K Project: To Generate Chromosome-Level Genomes for All Living Bat Species

Bats are unique among mammals, possessing some of the rarest mammalian adaptations, including true self-powered flight, laryngeal echolocation, exceptional longevity, unique immunity, contracted genomes, and vocal learning. They provide key ecosystem services, pollinating tropical plants, dispersing seeds, and controlling insect pest populations, thus driving healthy ecosystems. They account for more than 20% of all living mammalian diversity, and their crown-group evolutionary history dates back to the Eocene. Despite their great numbers and diversity, many species are threatened and endangered. Here we announce Bat1K, an initiative to sequence the genomes of all living bat species (n∼1,300) to chromosome-level assembly. The Bat1K genome consortium unites bat biologists (>148 members as of writing), computational scientists, conservation organizations, genome technologists, and any interested individuals committed to a better understanding of the genetic and evolutionary mechanisms that underlie the unique adaptations of bats. Our aim is to catalog the unique genetic diversity present in all living bats to better understand the molecular basis of their unique adaptations; uncover their evolutionary history; link genotype with phenotype; and ultimately better understand, promote, and conserve bats. Here we review the unique adaptations of bats and highlight how chromosome-level genome assemblies can uncover the molecular basis of these traits. We present a novel sequencing and assembly strategy and review the striking societal and scientific benefits that will result from the Bat1K initiative.

Identifying structural variants using linked-read sequencing data

MOTIVATION

Structural variation, including large deletions, duplications, inversions, translocations and other rearrangements, is common in human and cancer genomes. A number of methods have been developed to identify structural variants from Illumina short-read sequencing data. However, reliable identification of structural variants remains challenging because many variants have breakpoints in repetitive regions of the genome and thus are difficult to identify with short reads. The recently developed linked-read sequencing technology from 10X Genomics combines a novel barcoding strategy with Illumina sequencing. This technology labels all reads that originate from a small number (∼5 to 10) DNA molecules ∼50 Kbp in length with the same molecular barcode. These barcoded reads contain long-range sequence information that is advantageous for identification of structural variants.

RESULTS

We present Novel Adjacency Identification with Barcoded Reads (NAIBR), an algorithm to identify structural variants in linked-read sequencing data. NAIBR predicts novel adjacencies in an individual genome resulting from structural variants using a probabilistic model that combines multiple signals in barcoded reads. We show that NAIBR outperforms several existing methods for structural variant identification-including two recent methods that also analyze linked-reads-on simulated sequencing data and 10X whole-genome sequencing data from the NA12878 human genome and the HCC1954 breast cancer cell line. Several of the novel somatic structural variants identified in HCC1954 overlap known cancer genes.

AVAILABILITY AND IMPLEMENTATION

Software is available at compbio.cs.brown.edu/software.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome assembly from synthetic long read clouds

MOTIVATION

Despite rapid progress in sequencing technology, assembling de novo the genomes of new species as well as reconstructing complex metagenomes remains major technological challenges. New synthetic long read (SLR) technologies promise significant advances towards these goals; however, their applicability is limited by high sequencing requirements and the inability of current assembly paradigms to cope with combinations of short and long reads.

RESULTS

Here, we introduce Architect, a new de novo scaffolder aimed at SLR technologies. Unlike previous assembly strategies, Architect does not require a costly subassembly step; instead it assembles genomes directly from the SLR's underlying short reads, which we refer to as read clouds This enables a 4- to 20-fold reduction in sequencing requirements and a 5-fold increase in assembly contiguity on both genomic and metagenomic datasets relative to state-of-the-art assembly strategies aimed directly at fully subassembled long reads.

AVAILABILITY AND IMPLEMENTATION

Our source code is freely available at https://github.com/kuleshov/architect

CONTACT

kuleshov@stanford.edu.

Genome-wide reconstruction of complex structural variants using read clouds

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.

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations

Advances in genome sequencing and assembly technologies are generating many high-quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimized data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents >78% of the genome with a scaffold N50 of 88.8 kb that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNA-seq and Pacific Biosciences (PacBio) full-length cDNAs to identify 104,091 high-confidence protein-coding genes and 10,156 noncoding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop.

Human Y chromosome copy number variation in the next generation sequencing era and beyond

The human Y chromosome provides a fertile ground for structural rearrangements owing to its haploidy and high content of repeated sequences. The methodologies used for copy number variation (CNV) studies have developed over the years. Low-throughput techniques based on direct observation of rearrangements were developed early on, and are still used, often to complement array-based or sequencing approaches which have limited power in regions with high repeat content and specifically in the presence of long, identical repeats, such as those found in human sex chromosomes. Some specific rearrangements have been investigated for decades; because of their effects on fertility, or their outstanding evolutionary features, the interest in these has not diminished. However, following the flourishing of large-scale genomics, several studies have investigated CNVs across the whole chromosome. These studies sometimes employ data generated within large genomic projects such as the DDD study or the 1000 Genomes Project, and often survey large samples of healthy individuals without any prior selection. Novel technologies based on sequencing long molecules and combinations of technologies, promise to stimulate the study of Y-CNVs in the immediate future.

Haplotype-Phased Synthetic Long Reads from Short-Read Sequencing

Next-generation DNA sequencing has revolutionized the study of biology. However, the short read lengths of the dominant instruments complicate assembly of complex genomes and haplotype phasing of mixtures of similar sequences. Here we demonstrate a method to reconstruct the sequences of individual nucleic acid molecules up to 11.6 kilobases in length from short (150-bp) reads. We show that our method can construct 99.97%-accurate synthetic reads from bacterial, plant, and animal genomic samples, full-length mRNA sequences from human cancer cell lines, and individual HIV env gene variants from a mixture. The preparation of multiple samples can be multiplexed into a single tube, further reducing effort and cost relative to competing approaches. Our approach generates sequencing libraries in three days from less than one microgram of DNA in a single-tube format without custom equipment or specialized expertise.