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June 1, 2021  |  

Building a platinum human genome assembly from single haplotype human genomes generated from long molecule sequencing

The human reference sequence has provided a foundation for studies of genome structure, human variation, evolutionary biology, and disease. At the time the reference was originally completed there were some loci recalcitrant to closure; however, the degree to which structural variation and diversity affected our ability to produce a representative genome sequence at these loci was still unknown. Many of these regions in the genome are associated with large, repetitive sequences and exhibit complex allelic diversity such producing a single, haploid representation is not possible. To overcome this challenge, we have sequenced DNA from two hydatidiform moles (CHM1 and CHM13), which are essentially haploid. CHM13 was sequenced with the latest PacBio technology (P6-C5) to 52X genome coverage and assembled using Daligner and Falcon v0.2 (GCA_000983455.1, CHM13_1.1). Compared to the first mole (CHM1) PacBio assembly (GCA_001007805.1, 54X) contig N50 of 4.5Mb, the contig N50 of CHM13_1.1 is almost 13Mb, and there is a 13-fold reduction in the number of contigs. This demonstrates the improved contiguity of sequence generated with the new chemistry. We annotated 50,188 RefSeq transcripts of which only 0.63% were split transcripts, and the repetitive and segmental duplication content was within the expected range. These data all indicate an extremely high quality assembly. Additionally, we sequenced CHM13 DNA using Illumina SBS technology to 60X coverage, aligned these reads to the GRCh37, GRCh38, and CHM13_1.1 assemblies and performed variant calling using the SpeedSeq pipeline. The number of single nucleotide variants (SNV) and indels was comparable between GRCh37 and GRCh38. Regions that showed increased SNV density in GRCh38 compared to GRCh37 could be attributed to the addition of centromeric alpha satellite sequence to the reference assembly. Alternatively, regions of decreased SNV density in GRCh38 were concentrated in regions that were improved from BAC based sequencing of CHM1 such as 1p12 and 1q21 containing the SRGAP2 gene family. The alignment of PacBio reads to GRCh37 and GRCh38 assemblies allowed us to resolve complex loci such as the MHC region where the best alignment was to the DBB (A2-B57-DR7) haplotype. Finally, we will discuss how combining the two high quality mole assemblies can be used for benchmarking and novel bioinformatics tool development.

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June 1, 2021  |  

Highly accurate read mapping of third generation sequencing reads for improved structural variation analysis

Characterizing genomic structural variations (SV) is vital for understanding how genomes evolve. Furthermore, SVs are known for playing a role in a wide range of diseases including cancer, autism, and schizophrenia. Nevertheless, due to their complexity they remain harder to detect and less understood than single nucleotide variations. Recently, third-generation sequencing has proven to be an invaluable tool for detecting SVs. The markedly higher read length not only allows single reads to span a SV, it also enables reliable mapping to repetitive regions of the genome. These regions often contain SVs and are inaccessible to short-read mapping. However, current sequencing technologies like PacBio show a raw read error rate of 10% or more consisting mostly of insertions and deletions. Especially in repetitive regions the high error rate causes current mapping methods to fail finding exact borders for SVs, to split up large deletions and insertions into several small ones, or in some cases, like inversions, to fail reporting them at all. Furthermore, for complex SVs it is not possible to find one end-to-end alignment for a given read. The decision of when to split a read into two or more separate alignments without knowledge of the underlying SV poses an even bigger challenge to current read mappers. Here we present NextGenMap-LR for long single molecule PacBio reads which addresses these issues. NextGenMap-LR uses a fast k-mer search to quickly find anchor regions between parts of a read and the reference and evaluates them using a vectorized implementation of the Smith-Waterman (SW) algorithm. The resulting high-quality anchors are then used to determine whether a read spans an SV and has to be split or can be aligned contiguously. Finally, NextGenMap-LR uses a banded SW algorithm to compute the final alignment(s). In this last step, to account for both the sequencing error and real genomic variations, we employ a non-affine gap model that penalizes gap extensions for longer gaps less than for shorter ones. Based on simulated as well as verified human breast cancer SV data we show how our approach significantly improves mapping of long reads around SVs. The non-affine gap model is especially effective at more precisely identifying the position of the breakpoint, and the enhanced scoring scheme enables subsequent variation callers to identify SVs that would have been missed otherwise.

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June 1, 2021  |  

Detection of structural variants using third generation sequencing

Structural Variants (SVs), which include deletions, insertions, duplications, inversions and chromosomal rearrangements, have been shown to effect organism phenotypes, including changing gene expression, increasing disease risk, and playing an important role in cancer development. Still it remains challenging to detect all types of SVs from high throughput sequencing data and it is even harder to detect more complex SVs such as a duplication nested within an inversion. To overcome these challenges we developed algorithms for SV analysis using longer third generation sequencing reads. The increased read lengths allow us to span more complex SVs and accurately assess SVs in repetitive regions, two of the major limitations when using short Illumina data. Our enhanced open-source analysis method Sniffles accurately detects structural variants based on split read mapping and assessment of the alignments. Sniffles uses a self-balancing interval tree in combination with a plane sweep algorithm to manage and assess the identified SVs. Central to its high accuracy is its advanced scoring model that can distinguish erroneous alignments from true breakpoints flanking SVs. In experiments with simulated and real genomes (e.g human breast cancer), we find that Sniffles outperforms all other SV analysis approaches in both the sensitivity of finding events as well as the specificity of those events. Sniffles is available at: https://github.com/fritzsedlazeck/Sniffles

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June 1, 2021  |  

Comprehensive genome and transcriptome structural analysis of a breast cancer cell line using PacBio long read sequencing

Genomic instability is one of the hallmarks of cancer, leading to widespread copy number variations, chromosomal fusions, and other structural variations. The breast cancer cell line SK-BR-3 is an important model for HER2+ breast cancers, which are among the most aggressive forms of the disease and affect one in five cases. Through short read sequencing, copy number arrays, and other technologies, the genome of SK-BR-3 is known to be highly rearranged with many copy number variations, including an approximately twenty-fold amplification of the HER2 oncogene. However, these technologies cannot precisely characterize the nature and context of the identified genomic events and other important mutations may be missed altogether because of repeats, multi-mapping reads, and the failure to reliably anchor alignments to both sides of a variation. To address these challenges, we have sequenced SK-BR-3 using PacBio long read technology. Using the new P6-C4 chemistry, we generated more than 70X coverage of the genome with average read lengths of 9-13kb (max: 71kb). Using Lumpy for split-read alignment analysis, as well as our novel assembly-based algorithms for finding complex variants, we have developed a detailed map of structural variations in this cell line. Taking advantage of the newly identified breakpoints and combining these with copy number assignments, we have developed an algorithm to reconstruct the mutational history of this cancer genome. From this we have discovered a complex series of nested duplications and translocations between chr17 and chr8, two of the most frequent translocation partners in primary breast cancers, resulting in amplification of HER2. We have also carried out full-length transcriptome sequencing using PacBio’s Iso-Seq technology, which has revealed a number of previously unrecognized gene fusions and isoforms. Combining long-read genome and transcriptome sequencing technologies enables an in-depth analysis of how changes in the genome affect the transcriptome, including how gene fusions are created across multiple chromosomes. This analysis has established the most complete cancer reference genome available to date, and is already opening the door to applying long-read sequencing to patient samples with complex genome structures.

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June 1, 2021  |  

The resurgence of reference quality genome

Several new 3rd generation long-range DNA sequencing and mapping technologies have recently become available that are starting to create a resurgence in genome sequence quality. Unlike their 2nd generation, shortread counterparts that can resolve a few hundred or a few thousand basepairs, the new technologies can routinely sequence 10,000 bp reads or map across 100,000 bp molecules. The substantially greater lengths are being used to enhance a number of important problems in genomics and medicine, including de novo genome assembly, structural variation detection, and haplotype phasing. Here we discuss the capabilities of the latest technologies, and show how they will improve the “3Cs of Genome Assembly”: the contiguity, completeness, and correctness. We derive this analysis from (1) a metaanalysis of the currently available 3rd generation genome assemblies, (2) a retrospective analysis of the evolution of the reference human genome, and (3) extensive simulations with dozens of species across the tree of life. We also propose a model using support vector regression (SVR) that predicts genome assembly performance using four features: read lengths(L) and coverage values(C) that can be used for evaluating potential technologies along with genome size(G) and repeats(R) that present species specific characteristics. The proposed model significantly improves genome assembly performance prediction by adopting data-driven approach and addressing limitations of the previous hypothesis-driven methodology. Overall, we anticipate these technologies unlock the genomic “dark matter”, and provide many new insights into evolution, agriculture, and human diseases.

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June 1, 2021  |  

Profiling metagenomic communities using circular consensus and Single Molecule, Real-Time Sequencing

There are many sequencing-based approaches to understanding complex metagenomic communities, spanning targeted amplification to whole-sample shotgun sequencing. While targeted approaches provide valuable data at low sequencing depth, they are limited by primer design and PCR amplification. Whole-sample shotgun experiments require a high depth of coverage. As such, rare community members may not be represented in the resulting assembly. Circular-consensus, Single Molecule, Real-Time (SMRT) Sequencing reads in the 1-2 kb range, with >99% consensus accuracy, can be efficiently generated for low amounts of input DNA, e.g. as little as 10 ng of input DNA sequenced in 4 SMRT Cells can generate >100,000 such reads. While throughput is low compared to second-generation sequencing, the reads are a true random sampling of the underlying community. Long read lengths translate to a high number of the reads harboring full genes or even full operons for downstream analysis. Here we present the results of circular-consensus sequencing on a mock metagenomic community with an abundance range of multiple orders of magnitude, and compare the results with both 16S and shotgun assembly methods. We show that even with relatively low sequencing depth, the long-read, assembly-free, random sampling allows to elucidate meaningful information from the very low-abundance community members. For example, given the above low-input sequencing approach, a community member at 1/1,000 relative abundance would generate 100 1-2 kb sequence fragments having 99% consensus accuracy, with a high probability of containing a gene fragment useful for taxonomic classification or functional insight.

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June 1, 2021  |  

Cogent: Reconstructing the coding genome from full-length transcriptome sequences

For highly complex and large genomes, a well-annotated genome may be computationally challenging and costly, yet the study of alternative splicing events and gene annotations usually rely on the existence of a genome. Long-read sequencing technology provides new opportunities to sequence full-length cDNAs, avoiding computational challenges that short read transcript assembly brings. The use of single molecule, real-time sequencing from Pacific Biosciences to sequence transcriptomes (the Iso-SeqTM method), which produces de novo, high-quality, full-length transcripts, has revealed an astonishing amount of alternative splicing in eukaryotic species. With the Iso-Seq method, it is now possible to reconstruct the transcribed regions of the genome using just the transcripts themselves. We present Cogent, a tool for finding gene families and reconstructing the coding genome in the absence of a reference genome. Cogent uses k-mer similarities to first partition the transcripts into different gene families. Then, for each gene family, the transcripts are used to build a splice graph. Cogent identifies bubbles resulting from sequencing errors, minor variants, and exon skipping events, and attempts to resolve each splice graph down to the minimal set of reconstructed contigs. We apply Cogent to a Cuttlefish Iso-Seq dataset, for which there is a highly fragmented, Illumina-based draft genome assembly and little annotation. We show that Cogent successfully discovers gene families and can reconstruct the coding region of gene loci. The reconstructed contigs can then be used to visualize alternative splicing events, identify minor variants, and even be used to improve genome assemblies.

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June 1, 2021  |  

An update on goat genomics

Goats are specialized in dairy, meat and fiber production, being adapted to a wide range of environmental conditions and having a large economic impact in developing countries. In the last years, there have been dramatic advances in the knowledge of the structure and diversity of the goat genome/transcriptome and in the development of genomic tools, rapidly narrowing the gap between goat and related species such as cattle and sheep. Major advances are: 1) publication of a de novo goat genome reference sequence; 2) Development of whole genome high density RH maps, and; 3) Design of a commercial 50K SNP array. Moreover, there are currently several projects aiming at improving current genomic tools and resources. An improved assembly of the goat genome using PacBio reads is being produced, and the design of new SNP arrays is being studied to accommodate the specific needs of this species in the context of very large scale genotyping projects (i.e. breed characterization at an international scale and genomic selection) and parentage analysis. As in other species, the focus has now turned to the identification of causative mutations underlying the phenotypic variation of traits. In addition, since 2014, the ADAPTmap project (www.goatadaptmap.org) has gathered data to explore the diversity of caprine populations at a worldwide scale by using a wide variety of approaches and data.

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June 1, 2021  |  

Improving the goat long-read assembly with optical mapping and Hi-C scaffolding

Reference genome assemblies provide important context in genetics by standardizing the order of genes and providing a universal set of coordinates for individual nucleotides. Often due to the high complexity of genic regions and higher copy number of genes involved in immune function, immunity-related genes are often misassembled in current reference assemblies. This problem is particularly ubiquitous in the reference genomes of non-model organisms as they often do not receive the years of curation necessary to resolve annotation and assembly errors. In this study, we reassemble a reference genome of the goat (Capra hircus) using modern PacBio technology in tandem with BioNano Genomics Irys optical maps and Lachesis clustering in order to provide a high quality reference assembly without the need for extensive filtering. Initial PacBio assemblies using P5C4 chemistry achieved contig N50’s of 4 Megabases and a BUSCO completion score of 84.0%, which is comparable to several finished model organism reference assemblies. We used BioNano Genomics’ Irys platform to generate 336 scaffolds from this data with a scaffold N50 of 24 megabases and total genome coverage of 98%. Lachesis interaction maps were used with a clustering algorithm to associate Irys scaffolds into the expected 30 chromosome physical maps. Comparisons of the initial hybrid scaffolds generated from the long read contigs and optical map information to a previously generated RH map revealed that the entirety of the Goat autosome 20 physical map was contained within one scaffold. Additionally, the BioNano scaffolding resolved several difficult regions that contained genes related to innate immunity which were problem regions in previous reference genome assemblies.

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June 1, 2021  |  

A comprehensive study of the sugar pine (Pinus lambertiana) transcriptome implemented through diverse next-generation sequencing approaches

The assembly, annotation, and characterization of the sugar pine (Pinus lambertiana Dougl.) transcriptome represents an opportunity to study the genetic mechanisms underlying resistance to the invasive white pine blister rust (Cronartium ribicola) as well as responses to other abiotic stresses. The assembled transcripts also provide a resource to improve the genome assembly. We selected a diverse set of tissues allowing the first comprehensive evaluation of the sugar pine gene space. We have combined short read sequencing technologies (Illumina MiSeq and HiSeq) with the relatively new Pacific Biosciences Iso-Seq approach. From the 2.5 billion and 1.6 million Illumina and PacBio (46 SMRT cells) reads, 33,720 unigenes were de novo assembled. Comparison of sequencing technologies revealed improved coverage with Illumina HiSeq reads and better splice variant detection with PacBio Iso-Seq reads. The genes identified as unique to each library ranges from 199 transcripts (basket seedling) to 3,482 transcripts (female cones). In total, 10,026 transcripts were shared by all libraries. Genes differentially expressed in response to these provided insight on abiotic and biotic stress responses. To analyze orthologous sequences, we compared the translated sequences against 19 plant species, identifying 7,229 transcripts that clustered uniquely among the conifers. We have generated here a high quality transcriptome from one WPBR susceptible and one WPBR resistant sugar pine individual. Through the comprehensive tissue sampling and the depth of the sequencing achieved, detailed information on disease resistance can be further examined.

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June 1, 2021  |  

From Sequencing to Chromosomes: New de novo assembly and scaffolding methods improve the goat reference genome

Single-molecule sequencing is now routinely used to assemble complete, high-quality microbial genomes, but these assembly methods have not scaled well to large genomes. To address this problem, we previously introduced the MinHash Alignment Process (MHAP) for overlapping single-molecule reads using probabilistic, locality-sensitive hashing. Integrating MHAP with Celera Assembler (CA) has enabled reference-grade assemblies of model organisms, revealing novel heterochromatic sequences and filling low-complexity gap sequences in the GRCh38 human reference genome. We have applied our methods to assemble the San Clemente goat genome. Combining single-molecule sequencing from Pacific Biosciences and BioNano Genomics generates and assembly that is over 150-fold more contiguous than the latest Capra hircus reference. In combination with Hi-C sequencing, the assembly surpasses reference assemblies, de novo, with minimal manual intervention. The autosomes are each assembled into a single scaffold. Our assembly provides a more complete gene reconstruction, better alignments with Goat 52k chip, and improved allosome reconstruction. In addition to providing increased continuity of sequence, our assembly achieves a higher BUSCO completion score (84%) than the existing goat reference assembly suggesting better quality annotation of gene models. Our results demonstrate that single-molecule sequencing can produce near-complete eukaryotic genomes at modest cost and minimal manual effort.

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June 1, 2021  |  

Progress Toward a Low Budget Reference Grade Genome Assembly

Reference quality de novo genome assemblies were once solely the domain of large, well-funded genome projects. While next-generation short read technology removed some of the cost barriers, accurate chromosome-scale assembly remains a real challenge. Here we present efforts to de novo assemble the goat (Capra hircus) genome. Through the combination of single-molecule technologies from Pacific Biosciences (sequencing) and BioNano Genomics (optical mapping) coupled with high-throughput chromosome conformation capture sequencing (Hi-C), an inbred San Clemente goat genome has been sequenced and assembled to a high degree of completeness at a relatively modest cost. Starting with 38 million PacBio reads, we integrated the MinHash Alignment Process (MHAP) with the Celera Assembler (CA) to produce an assembly composed of 3110 contigs with a contig N50 size of 4.7 Mb. This assembly was scaffolded with BioNano genome maps derived from a single IrysChip into 333 scaffolds with an N50 of 23.1 Mb including the complete scaffolding of chromosome 20. Finally, cis-chromosome associations were determined by Hi-C, yielding complete reconstruction of all autosomes into single scaffolds with a final N50 of 91.7 Mb. We hope to demonstrate that our methods are not only cost effective, but improve our ability to annotate challenging genomic regions such as highly repetitive immune gene clusters.

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June 1, 2021  |  

How to Compare and Cluster Every Known Genome in about an Hour

Given a massive collection of sequences, it is infeasible to perform pairwise alignment for basic tasks like sequence clustering and search. To address this problem, we demonstrate that the MinHash technique, first applied to clustering web pages, can be applied to biological sequences with similar effect, and extend this idea to include biologically relevant distance and significance measures. Our new tool, Mash, uses MinHash locality-sensitive hashing to reduce large sequences to a representative sketch and rapidly estimate pairwise distances between genomes or metagenomes. Using Mash, we explored several use cases, including a 5,000-fold size reduction and clustering of all 55,000 NCBI RefSeq genomes in 46 CPU hours. The resulting 93 MB sketch database includes all RefSeq genomes, effectively delineates known species boundaries, reconstructs approximate phylogenies, and can be searched in seconds using assembled genomes or raw sequencing runs from Illumina, Pacific Biosciences, and Oxford Nanopore. For metagenomics, Mash scales to thousands of samples and can replicate Human Microbiome Project and Global Ocean Survey results in a fraction of the time. Other potential applications include any problem where an approximate, global sequence distance is acceptable, e.g. to triage and cluster sequence data, assign species labels to unknown genomes, quickly identify mis- tracked samples, and search massive genomic databases. In addition, the Mash distance metric is based on simple set intersections, which are compatible with homomorphic encryption schemes. To facilitate integration with other software, Mash is implemented as a lightweight C++ toolkit and freely released under a BSD license athttps://github.com/marbl/mash

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June 1, 2021  |  

Comparative Studies of Mammalian Sex Chromosomes: From Cytogenetics to NGS

It is a common knowledge that sex chromosome mutations are better tolerated and more viable compared to changes in autosomes. This is explained by relatively low gene density in both the X and the Y chromosome and by random X chromosome inactivation in mammalian females buffering the effect of X-aneuploidies. However, it is not well understood why apparently similar sex chromosome abnormalities, such as X-monosomy or certain Y chromosome rearrangements, result in different phenotypic effects in different species. It is thought that this is due to species differences in the organization of the Y chromosome, differences in the set of genes escaping X-inactivation, and the presence of species/lineage specific sex-linked genes with functions in development and reproduction. Current knowledge about the species differences in sex chromosome organization and function is limited, this despite the availability of reference genome assemblies for most domestic species. It appears that sequence assembly of the X chromosome in most species is rather patchy containing multiple gaps and possible misassemblies, being the poorest in the pseudoautosomal region and in regions containing putative lineage-specific sequences. The Y chromosome, on the other hand, is typically not included in the reference genome and is studied separately, whereas complete sequence assembly of the male-specific portion of the Y is not yet available for any domestic species. In this talk I will discuss comparative organization and function of animal sex chromosomes and related phenotypes proceeding from our research in horses.

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June 1, 2021  |  

MaSuRCA Mega-Reads Assembly Technique for haplotype resolved genome assembly of hybrid PacBio and Illumina Data

The developments in DNA sequencing technology over the past several years have enabled large number of scientists to obtain sequences for the genomes of their interest at a fairly low cost. Illumina Sequencing was the dominant whole genome sequencing technology over the past few years due to its low cost. The Illumina reads are short (up to 300bp) and thus most of those draft genomes produced from Illumina data are very fragmented which limits their usability in practical scenarios. Longer reads are needed for more contiguous genomes. Recently Pacbio sequencing made significant advances in developing cost-effective long-read (>10000bp) sequencing technology and their data, although several times more expensive than Illumina, can be used to produce high quality genomes. Pacbio data can be used for de novo assembly, however due to its high error rate high coverage of the genome is required this raising the cost barrier. A solution for cost-effective genomes is to combine Pacbio and Illumina data leveraging the low error rates of the short Illumina reads and the length of the Pacbio reads. We have developed MaSuRCA mega-reads assembler for efficient assembly of hybrid data sets and we demonstrate that it performs well compared to the other published hybrid techniques. Another important benefit of the long reads is their ability to link the haplotype differences. The mega-reads approach corrects each Pacbio read independently and thus haplotype differences are preserved. Thus, leveraging the accuracy of the Illumina data and the length of the Pacbio reads, MaSuRCA mega-reads can produce haplotype-resolved genome assemblies, where each contig has sequence from a single haplotype. We present preliminary results on haplotype-resolved genome assemblies of faux (proof-of-concept) and real data.

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