Dense and accurate whole-chromosome haplotyping of individual genomes

Accurate, scalable and integrative haplotype estimation

The number of human genomes being genotyped or sequenced increases exponentially and efficient haplotype estimation methods able to handle this amount of data are now required. Here we present a method, SHAPEIT4, which substantially improves upon other methods to process large genotype and high coverage sequencing datasets. It notably exhibits sub-linear running times with sample size, provides highly accurate haplotypes and allows integrating external phasing information such as large reference panels of haplotypes, collections of pre-phased variants and long sequencing reads. We provide SHAPEIT4 in an open source format and demonstrate its performance in terms of accuracy and running times on two gold standard datasets: the UK Biobank data and the Genome In A Bottle.

Integrating read-based and population-based phasing for dense and accurate haplotyping of individual genomes

MOTIVATION

Reconstruction of haplotypes for human genomes is an important problem in medical and population genetics. Hi-C sequencing generates read pairs with long-range haplotype information that can be computationally assembled to generate chromosome-spanning haplotypes. However, the haplotypes have limited completeness and low accuracy. Haplotype information from population reference panels can potentially be used to improve the completeness and accuracy of Hi-C haplotyping.

RESULTS

In this paper, we describe a likelihood based method to integrate short-range haplotype information from a population reference panel of haplotypes with the long-range haplotype information present in sequence reads from methods such as Hi-C to assemble dense and highly accurate haplotypes for individual genomes. Our method leverages a statistical phasing method and a maximum spanning tree algorithm to determine the optimal second-order approximation of the population-based haplotype likelihood for an individual genome. The population-based likelihood is encoded using pseudo-reads which are then used as input along with sequence reads for haplotype assembly using an existing tool, HapCUT2. Using whole-genome Hi-C data for two human genomes (NA19240 and NA12878), we demonstrate that this integrated phasing method enables the phasing of 97-98% of variants, reduces the switch error rates by 3-6-fold, and outperforms an existing method for combining phase information from sequence reads with population-based phasing. On Strand-seq data for NA12878, our method improves the haplotype completeness from 71.4 to 94.6% and reduces the switch error rate 2-fold, demonstrating its utility for phasing using multiple sequencing technologies.

AVAILABILITY AND IMPLEMENTATION

Code and datasets are available at https://github.com/vibansal/IntegratedPhasing.

Long-read based de novo assembly of low-complexity metagenome samples results in finished genomes and reveals insights into strain diversity and an active phage system

BACKGROUND

Complete and contiguous genome assemblies greatly improve the quality of subsequent systems-wide functional profiling studies and the ability to gain novel biological insights. While a de novo genome assembly of an isolated bacterial strain is in most cases straightforward, more informative data about co-existing bacteria as well as synergistic and antagonistic effects can be obtained from a direct analysis of microbial communities. However, the complexity of metagenomic samples represents a major challenge. While third generation sequencing technologies have been suggested to enable finished metagenome-assembled genomes, to our knowledge, the complete genome assembly of all dominant strains in a microbiome sample has not been demonstrated. Natural whey starter cultures (NWCs) are used in cheese production and represent low-complexity microbiomes. Previous studies of Swiss Gruyère and selected Italian hard cheeses, mostly based on amplicon metagenomics, concurred that three species generally pre-dominate: Streptococcus thermophilus, Lactobacillus helveticus and Lactobacillus delbrueckii.

RESULTS

Two NWCs from Swiss Gruyère producers were subjected to whole metagenome shotgun sequencing using the Pacific Biosciences Sequel and Illumina MiSeq platforms. In addition, longer Oxford Nanopore Technologies MinION reads had to be generated for one to resolve repeat regions. Thereby, we achieved the complete assembly of all dominant bacterial genomes from these low-complexity NWCs, which was corroborated by a 16S rRNA amplicon survey. Moreover, two distinct L. helveticus strains were successfully co-assembled from the same sample. Besides bacterial chromosomes, we could also assemble several bacterial plasmids and phages and a corresponding prophage. Biologically relevant insights were uncovered by linking the plasmids and phages to their respective host genomes using DNA methylation motifs on the plasmids and by matching prokaryotic CRISPR spacers with the corresponding protospacers on the phages. These results could only be achieved by employing long-read sequencing data able to span intragenomic as well as intergenomic repeats.

CONCLUSIONS

Here, we demonstrate the feasibility of complete de novo genome assembly of all dominant strains from low-complexity NWCs based on whole metagenomics shotgun sequencing data. This allowed to gain novel biological insights and is a fundamental basis for subsequent systems-wide omics analyses, functional profiling and phenotype to genotype analysis of specific microbial communities.

Haplotype-aware diplotyping from noisy long reads

Current genotyping approaches for single-nucleotide variations rely on short, accurate reads from second-generation sequencing devices. Presently, third-generation sequencing platforms are rapidly becoming more widespread, yet approaches for leveraging their long but error-prone reads for genotyping are lacking. Here, we introduce a novel statistical framework for the joint inference of haplotypes and genotypes from noisy long reads, which we term diplotyping. Our technique takes full advantage of linkage information provided by long reads. We validate hundreds of thousands of candidate variants that have not yet been included in the high-confidence reference set of the Genome-in-a-Bottle effort.

Multi-platform discovery of haplotype-resolved structural variation in human genomes

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Multi-platform discovery of haplotype-resolved structural variation in human genomes

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

Contemporary pharmacogenetic assays in view of the PharmGKB database

AIM

Six modern PGx assays were compared with the Pharmacogenomics Knowledge Base (PharmGKB) to determine the proportion of the currently known PGx genotypes that are assessed by these assays.

MATERIALS & METHODS

Investigated assays were 'Ion AmpliSeq Pharmacogenomics', 'iPLEX PGx Pro', 'DMET Plus,' 'PharmcoScan,' 'Living DNA' and '23andMe.'

RESULTS

PharmGKB contains 3474 clinical annotations of which 75, 70 and 45% can be determined by PharmacoScan, Living DNA and 23andMe, respectively. The other assays are designed to test a specific subset of PGx variants.

CONCLUSION

Assaying all known PGx variants would only comprise a minor fraction of the current assays' capacity. Unfortunately, this is not achieved. Moreover, not necessarily the variants with the highest effects or the highest evidence are selected.

HAHap: a read-based haplotyping method using hierarchical assembly

BACKGROUND

The need for read-based phasing arises with advances in sequencing technologies. The minimum error correction (MEC) approach is the primary trend to resolve haplotypes by reducing conflicts in a single nucleotide polymorphism-fragment matrix. However, it is frequently observed that the solution with the optimal MEC might not be the real haplotypes, due to the fact that MEC methods consider all positions together and sometimes the conflicts in noisy regions might mislead the selection of corrections. To tackle this problem, we present a hierarchical assembly-based method designed to progressively resolve local conflicts.

RESULTS

This study presents HAHap, a new phasing algorithm based on hierarchical assembly. HAHap leverages high-confident variant pairs to build haplotypes progressively. The phasing results by HAHap on both real and simulated data, compared to other MEC-based methods, revealed better phasing error rates for constructing haplotypes using short reads from whole-genome sequencing. We compared the number of error corrections (ECs) on real data with other methods, and it reveals the ability of HAHap to predict haplotypes with a lower number of ECs. We also used simulated data to investigate the behavior of HAHap under different sequencing conditions, highlighting the applicability of HAHap in certain situations.

De novo assembly of haplotype-resolved genomes with trio binning

Complex allelic variation hampers the assembly of haplotype-resolved sequences from diploid genomes. We developed trio binning, an approach that simplifies haplotype assembly by resolving allelic variation before assembly. In contrast with prior approaches, the effectiveness of our method improved with increasing heterozygosity. Trio binning uses short reads from two parental genomes to first partition long reads from an offspring into haplotype-specific sets. Each haplotype is then assembled independently, resulting in a complete diploid reconstruction. We used trio binning to recover both haplotypes of a diploid human genome and identified complex structural variants missed by alternative approaches. We sequenced an F1 cross between the cattle subspecies Bos taurus taurus and Bos taurus indicus and completely assembled both parental haplotypes with NG50 haplotig sizes of >20 Mb and 99.998% accuracy, surpassing the quality of current cattle reference genomes. We suggest that trio binning improves diploid genome assembly and will facilitate new studies of haplotype variation and inheritance.

A Statistical Method for Observing Personal Diploid Methylomes and Transcriptomes with Single-Molecule Real-Time Sequencing

We address the problem of observing personal diploid methylomes, CpG methylome pairs of homologous chromosomes that are distinguishable with respect to phased heterozygous variants (PHVs), which is challenging due to scarcity of PHVs in personal genomes. Single molecule real-time (SMRT) sequencing is promising as it outputs long reads with CpG methylation information, but a serious concern is whether reliable PHVs are available in erroneous SMRT reads with an error rate of ∼15%. To overcome the issue, we propose a statistical model that reduces the error rate of phasing CpG site to 1%, thereby calling CpG hypomethylation in each haplotype with >90% precision and sensitivity. Using our statistical model, we examined GNAS complex locus known for a combination of maternally, paternally, or biallelically expressed isoforms, and observed allele-specific methylation pattern almost perfectly reflecting their respective allele-specific expression status, demonstrating the merit of elucidating comprehensive personal diploid methylomes and transcriptomes.

HapCHAT: adaptive haplotype assembly for efficiently leveraging high coverage in long reads

Background

Haplotype assembly is the process of assigning the different alleles of the variants covered by mapped sequencing reads to the two haplotypes of the genome of a human individual. Long reads, which are nowadays cheaper to produce and more widely available than ever before, have been used to reduce the fragmentation of the assembled haplotypes since their ability to span several variants along the genome. These long reads are also characterized by a high error rate, an issue which may be mitigated, however, with larger sets of reads, when this error rate is uniform across genome positions. Unfortunately, current state-of-the-art dynamic programming approaches designed for long reads deal only with limited coverages.

Results

Here, we propose a new method for assembling haplotypes which combines and extends the features of previous approaches to deal with long reads and higher coverages. In particular, our algorithm is able to dynamically adapt the estimated number of errors at each variant site, while minimizing the total number of error corrections necessary for finding a feasible solution. This allows our method to significantly reduce the required computational resources, allowing to consider datasets composed of higher coverages. The algorithm has been implemented in a freely available tool, HapCHAT: Haplotype Assembly Coverage Handling by Adapting Thresholds. An experimental analysis on sequencing reads with up to 60 × coverage reveals improvements in accuracy and recall achieved by considering a higher coverage with lower runtimes.

Conclusions

Our method leverages the long-range information of sequencing reads that allows to obtain assembled haplotypes fragmented in a lower number of unphased haplotype blocks. At the same time, our method is also able to deal with higher coverages to better correct the errors in the original reads and to obtain more accurate haplotypes as a result.

Availability

HapCHAT is available at http://hapchat.algolab.euunder the GNU Public License (GPL).

Strand-seq enables reliable separation of long reads by chromosome via expectation maximization

Motivation

Current sequencing technologies are able to produce reads orders of magnitude longer than ever possible before. Such long reads have sparked a new interest in de novo genome assembly, which removes reference biases inherent to re-sequencing approaches and allows for a direct characterization of complex genomic variants. However, even with latest algorithmic advances, assembling a mammalian genome from long error-prone reads incurs a significant computational burden and does not preclude occasional misassemblies. Both problems could potentially be mitigated if assembly could commence for each chromosome separately.

Results

To address this, we show how single-cell template strand sequencing (Strand-seq) data can be leveraged for this purpose. We introduce a novel latent variable model and a corresponding Expectation Maximization algorithm, termed SaaRclust, and demonstrates its ability to reliably cluster long reads by chromosome. For each long read, this approach produces a posterior probability distribution over all chromosomes of origin and read directionalities. In this way, it allows to assess the amount of uncertainty inherent to sparse Strand-seq data on the level of individual reads. Among the reads that our algorithm confidently assigns to a chromosome, we observed more than 99% correct assignments on a subset of Pacific Bioscience reads with 30.1× coverage. To our knowledge, SaaRclust is the first approach for the in silico separation of long reads by chromosome prior to assembly.

Availability and implementation

https://github.com/daewoooo/SaaRclust.

A graph-based approach to diploid genome assembly

Motivation

Constructing high-quality haplotype-resolved de novo assemblies of diploid genomes is important for revealing the full extent of structural variation and its role in health and disease. Current assembly approaches often collapse the two sequences into one haploid consensus sequence and, therefore, fail to capture the diploid nature of the organism under study. Thus, building an assembler capable of producing accurate and complete diploid assemblies, while being resource-efficient with respect to sequencing costs, is a key challenge to be addressed by the bioinformatics community.

Results

We present a novel graph-based approach to diploid assembly, which combines accurate Illumina data and long-read Pacific Biosciences (PacBio) data. We demonstrate the effectiveness of our method on a pseudo-diploid yeast genome and show that we require as little as 50× coverage Illumina data and 10× PacBio data to generate accurate and complete assemblies. Additionally, we show that our approach has the ability to detect and phase structural variants.

Availability and implementation

https://github.com/whatshap/whatshap.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Third Revolution in Sequencing Technology

Forty years ago the advent of Sanger sequencing was revolutionary as it allowed complete genome sequences to be deciphered for the first time. A second revolution came when next-generation sequencing (NGS) technologies appeared, which made genome sequencing much cheaper and faster. However, NGS methods have several drawbacks and pitfalls, most notably their short reads. Recently, third-generation/long-read methods appeared, which can produce genome assemblies of unprecedented quality. Moreover, these technologies can directly detect epigenetic modifications on native DNA and allow whole-transcript sequencing without the need for assembly. This marks the third revolution in sequencing technology. Here we review and compare the various long-read methods. We discuss their applications and their respective strengths and weaknesses and provide future perspectives.

Current Strategies of Polyploid Plant Genome Sequence Assembly

Polyploidy or duplication of an entire genome occurs in the majority of angiosperms. The understanding of polyploid genomes is important for the improvement of those crops, which humans rely on for sustenance and basic nutrition. As climate change continues to pose a potential threat to agricultural production, there will increasingly be a demand for plant cultivars that can resist biotic and abiotic stresses and also provide needed and improved nutrition. In the past decade, Next Generation Sequencing (NGS) has fundamentally changed the genomics landscape by providing tools for the exploration of polyploid genomes. Here, we review the challenges of the assembly of polyploid plant genomes, and also present recent advances in genomic resources and functional tools in molecular genetics and breeding. As genomes of diploid and less heterozygous progenitor species are increasingly available, we discuss the lack of complexity of these currently available reference genomes as they relate to polyploid crops. Finally, we review recent approaches of haplotyping by phasing and the impact of third generation technologies on polyploid plant genome assembly.