2015 SMRT Informatics Developers Conference Presentation Slides: Ali Bashir of Mount Sinai School of Medicine discussed methods for characterizing structural variation in human genomes across a variety of coverage levels.
Characterizing haplotype diversity at the immunoglobulin heavy chain locus across human populations using novel long-read sequencing and assembly approaches
The human immunoglobulin heavy chain locus (IGH) remains among the most understudied regions of the human genome. Recent efforts have shown that haplotype diversity within IGH is elevated and exhibits population specific patterns; for example, our re-sequencing of the locus from only a single chromosome uncovered >100 Kb of novel sequence, including descriptions of six novel alleles, and four previously unmapped genes. Historically, this complex locus architecture has hindered the characterization of IGH germline single nucleotide, copy number, and structural variants (SNVs; CNVs; SVs), and as a result, there remains little known about the role of IGH polymorphisms in inter-individual antibody repertoire variability and disease. To remedy this, we are taking a multi-faceted approach to improving existing genomic resources in the human IGH region. First, from whole-genome and fosmid-based datasets, we are building the largest and most ethnically diverse set of IGH reference assemblies to date, by employing PacBio long-read sequencing combined with novel algorithms for phased haplotype assembly. In total, our effort will result in the characterization of >15 phased haplotypes from individuals of Asian, African, and European descent, to be used as a representative reference set by the genomics and immunogenetics community. Second, we are utilizing this more comprehensive sequence catalogue to inform the design and analysis of novel targeted IGH genotyping assays. Standard targeted DNA enrichment methods (e.g., exome capture) are currently optimized for the capture of only very short (100’s of bp) DNA segments. Our platform uses a modified bench protocol to pair existing capture-array technologies with the enrichment of longer fragments of DNA, enabling the use of PacBio sequencing of DNA segments up to 7 Kb. This substantial increase in contiguity disambiguates many of the complex repeated structures inherent to the locus, while yielding the base pair fidelity required to call SNVs. Together these resources will establish a stronger framework for further characterizing IGH genetic diversity and facilitate IGH genomic profiling in the clinical and research settings, which will be key to fully understanding the role of IGH germline variation in antibody repertoire development and disease.
PacBio SMRT Sequencing is fast changing the genomics space with its long reads and high consensus sequence accuracy, providing the most comprehensive view of the genome and transcriptome. In this…
Chlorella vulgaris genome assembly and annotation reveals the molecular basis for metabolic acclimation to high light conditions.
Chlorella vulgaris is a fast-growing fresh-water microalga cultivated at the industrial scale for applications ranging from food to biofuel production. To advance our understanding of its biology and to establish genetics tools for biotechnological manipulation, we sequenced the nuclear and organelle genomes of Chlorella vulgaris 211/11P by combining next generation sequencing and optical mapping of isolated DNA molecules. This hybrid approach allowed to assemble the nuclear genome in 14 pseudo-molecules with an N50 of 2.8 Mb and 98.9% of scaffolded genome. The integration of RNA-seq data obtained at two different irradiances of growth (high light-HL versus low light -LL) enabled to identify 10,724 nuclear genes, coding for 11,082 transcripts. Moreover 121 and 48 genes were respectively found in the chloroplast and mitochondrial genome. Functional annotation and expression analysis of nuclear, chloroplast and mitochondrial genome sequences revealed peculiar features of Chlorella vulgaris. Evidence of horizontal gene transfers from chloroplast to mitochondrial genome was observed. Furthermore, comparative transcriptomic analyses of LL vs HL provide insights into the molecular basis for metabolic rearrangement in HL vs. LL conditions leading to enhanced de novo fatty acid biosynthesis and triacylglycerol accumulation. The occurrence of a cytosolic fatty acid biosynthetic pathway can be predicted and its upregulation upon HL exposure is observed, consistent with increased lipid amount under HL. These data provide a rich genetic resource for future genome editing studies, and potential targets for biotechnological manipulation of Chlorella vulgaris or other microalgae species to improve biomass and lipid productivity.This article is protected by copyright. All rights reserved.
Motivation: Third-generation sequencing technologies can sequence long reads, which is advancing the frontiers of genomics research. However, their high error rates prohibit accurate and efficient downstream analysis. This difficulty has motivated the development of many long read error correction tools, which tackle this problem through sampling redundancy and/or leveraging accurate short reads of the same biological samples. Existing studies to asses these tools use simulated data sets, and are not sufficiently comprehensive in the range of software covered or diversity of evaluation measures used. Results: In this paper, we present a categorization and review of long read error correction methods, and provide a comprehensive evaluation of the corresponding long read error correction tools. Leveraging recent real sequencing data, we establish benchmark data sets and set up evaluation criteria for a comparative assessment which includes quality of error correction as well as run-time and memory usage. We study how trimming and long read sequencing depth affect error correction in terms of length distribution and genome coverage post-correction, and the impact of error correction performance on an important application of long reads, genome assembly. We provide guidelines for practitioners for choosing among the available error correction tools and identify directions for future research.
Supernumerary B chromosomes (Bs) are extra karyotype units in addition to A chromosomes, and are found in some fungi and thousands of animals and plant species. Bs are uniquely characterized due to their non-Mendelian inheritance, and represent one of the best examples of genomic conflict. Over the last decades, their genetic composition, function and evolution have remained an unresolved query, although a few successful attempts have been made to address these phenomena. A classical concept based on cytogenetics and genetics is that Bs are selfish and abundant with DNA repeats and transposons, and in most cases, they do not carry any function. However, recently, the modern quantum development of high scale multi-omics techniques has shifted B research towards a new-born field that we call “B-omics”. We review the recent literature and add novel perspectives to the B research, discussing the role of new technologies to understand the mechanistic perspectives of the molecular evolution and function of Bs. The modern view states that B chromosomes are enriched with genes for many significant biological functions, including but not limited to the interesting set of genes related to cell cycle and chromosome structure. Furthermore, the presence of B chromosomes could favor genomic rearrangements and influence the nuclear environment affecting the function of other chromatin regions. We hypothesize that B chromosomes might play a key function in driving their transmission and maintenance inside the cell, as well as offer an extra genomic compartment for evolution.
Tandem repeat (TR) expansions have been implicated in dozens of genetic diseases, including Huntington’s Disease, Fragile X Syndrome, and hereditary ataxias. Furthermore, TRs have recently been implicated in a range of complex traits, including gene expression and cancer risk. While the human genome harbors hundreds of thousands of TRs, analysis of TR expansions has been mainly limited to known pathogenic loci. A major challenge is that expanded repeats are beyond the read length of most next-generation sequencing (NGS) datasets and are not profiled by existing genome-wide tools. We present GangSTR, a novel algorithm for genome-wide genotyping of both short and expanded TRs. GangSTR extracts information from paired-end reads into a unified model to estimate maximum likelihood TR lengths. We validate GangSTR on real and simulated data and show that GangSTR outperforms alternative methods in both accuracy and speed. We apply GangSTR to a deeply sequenced trio to profile the landscape of TR expansions in a healthy family and validate novel expansions using orthogonal technologies. Our analysis reveals that healthy individuals harbor dozens of long TR alleles not captured by current genome-wide methods. GangSTR will likely enable discovery of novel disease-associated variants not currently accessible from NGS. © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
The commercial release of third-generation sequencing technologies (TGSTs), giving long and ultra-long sequencing reads, has stimulated the development of new tools for assembling highly contiguous genome sequences with unprecedented accuracy across complex repeat regions. We survey here a wide range of emerging sequencing platforms and analytical tools for de novo assembly, provide background information for each of their steps, and discuss the spectrum of available options. Our decision tree recommends workflows for the generation of a high-quality genome assembly when used in combination with the specific needs and resources of a project.Copyright © 2019 Elsevier Ltd. All rights reserved.
Detecting a long insertion variant in SAMD12 by SMRT sequencing: implications of long-read whole-genome sequencing for repeat expansion diseases.
Long-read sequencing technology is now capable of reading single-molecule DNA with an average read length of more than 10?kb, fully enabling the coverage of large structural variations (SVs). This advantage may pave the way for the detection of unprecedented SVs as well as repeat expansions. Pathogenic SVs of only known genes used to be selectively analyzed based on prior knowledge of target DNA sequence. The unbiased application of long-read whole-genome sequencing (WGS) for the detection of pathogenic SVs has just begun. Here, we apply PacBio SMRT sequencing in a Japanese family with benign adult familial myoclonus epilepsy (BAFME). Our SV selection of low-coverage WGS data (7×) narrowed down the candidates to only six SVs in a 7.16-Mb region of the BAFME1 locus and correctly determined an approximately 4.6-kb SAMD12 intronic repeat insertion, which is causal of BAFME1. These results indicate that long-read WGS is potentially useful for evaluating all of the known SVs in a genome and identifying new disease-causing SVs in combination with other genetic methods to resolve the genetic causes of currently unexplained diseases.
TSD: A Computational Tool To Study the Complex Structural Variants Using PacBio Targeted Sequencing Data.
PacBio sequencing is a powerful approach to study DNA or RNA sequences in a longer scope. It is especially useful in exploring the complex structural variants generated by random integration or multiple rearrangement of endogenous or exogenous sequences. Here, we present a tool, TSD, for complex structural variant discovery using PacBio targeted sequencing data. It allows researchers to identify and visualize the genomic structures of targeted sequences by unlimited splitting, alignment and assembly of long PacBio reads. Application to the sequencing data derived from an HBV integrated human cell line(PLC/PRF/5) indicated that TSD could recover the full profile of HBV integration events, especially for the regions with the complex human-HBV genome integrations and multiple HBV rearrangements. Compared to other long read analysis tools, TSD showed a better performance for detecting complex genomic structural variants. TSD is publicly available at: https://github.com/menggf/tsd. Copyright © 2019 Meng et al.
Since the dawn of the bioinformatics field, sequence alignment scores have been the main method for comparing sequences. However, alignment algorithms are quadratic, requiring long execution time. As alternatives, scientists have developed tens of alignment-free statistics for measuring the similarity between two sequences.We surveyed tens of alignment-free k-mer statistics. Additionally, we evaluated 33 statistics and multiplicative combinations between the statistics and/or their squares. These statistics are calculated on two k-mer histograms representing two sequences. Our evaluations using global alignment scores revealed that the majority of the statistics are sensitive and capable of finding similar sequences to a query sequence. Therefore, any of these statistics can filter out dissimilar sequences quickly. Further, we observed that multiplicative combinations of the statistics are highly correlated with the identity score. Furthermore, combinations involving sequence length difference or Earth Mover’s distance, which takes the length difference into account, are always among the highest correlated paired statistics with identity scores. Similarly, paired statistics including length difference or Earth Mover’s distance are among the best performers in finding the K-closest sequences. Interestingly, similar performance can be obtained using histograms of shorter words, resulting in reducing the memory requirement and increasing the speed remarkably. Moreover, we found that simple single statistics are sufficient for processing next-generation sequencing reads and for applications relying on local alignment. Finally, we measured the time requirement of each statistic. The survey and the evaluations will help scientists with identifying efficient alternatives to the costly alignment algorithm, saving thousands of computational hours.The source code of the benchmarking tool is available as Supplementary Materials. © The Author 2017. Published by Oxford University Press.
Chromosome-level genome assembly of Triplophysa tibetana, a fish adapted to the harsh high-altitude environment of the Tibetan Plateau.
Triplophysa is an endemic fish genus of the Tibetan Plateau in China. Triplophysa tibetana, which lives at a recorded altitude of ~4,000 m and plays an important role in the highland aquatic ecosystem, serves as an excellent model for investigating high-altitude environmental adaptation. However, evolutionary and conservation studies of T. tibetana have been limited by scarce genomic resources for the genus Triplophysa. In the present study, we applied PacBio sequencing and the Hi-C technique to assemble the T. tibetana genome. A 652-Mb genome with 1,325 contigs with an N50 length of 3.1 Mb was obtained. The 1,137 contigs were further assembled into 25 chromosomes, representing 98.7% and 80.47% of all contigs at the base and sequence number level, respectively. Approximately 260 Mb of sequence, accounting for ~39.8% of the genome, was identified as repetitive elements. DNA transposons (16.3%), long interspersed nuclear elements (12.4%) and long terminal repeats (11.0%) were the most repetitive types. In total, 24,372 protein-coding genes were predicted in the genome, and ~95% of the genes were functionally annotated via a search in public databases. Using whole genome sequence information, we found that T. tibetana diverged from its common ancestor with Danio rerio ~121.4 million years ago. The high-quality genome assembled in this work not only provides a valuable genomic resource for future population and conservation studies of T. tibetana, but it also lays a solid foundation for further investigation into the mechanisms of environmental adaptation of endemic fishes in the Tibetan Plateau. © 2019 John Wiley & Sons Ltd.
Whole Genome Sequencing of the Mutamouse Model Reveals Strain- and Colony-Level Variation, and Genomic Features of the Transgene Integration Site.
The MutaMouse transgenic rodent model is widely used for assessing in vivo mutagenicity. Here, we report the characterization of MutaMouse’s whole genome sequence and its genetic variants compared to the C57BL/6 reference genome. High coverage (>50X) next-generation sequencing (NGS) of whole genomes from multiple MutaMouse animals from the Health Canada (HC) colony showed ~5 million SNVs per genome, ~20% of which are putatively novel. Sequencing of two animals from a geographically separated colony at Covance indicated that, over the course of 23 years, each colony accumulated 47,847 (HC) and 17,677 (Covance) non-parental homozygous single nucleotide variants. We found no novel nonsense or missense mutations that impair the MutaMouse response to genotoxic agents. Pairing sequencing data with array comparative genomic hybridization (aCGH) improved the accuracy and resolution of copy number variants (CNVs) calls and identified 300 genomic regions with CNVs. We also used long-read sequence technology (PacBio) to show that the transgene integration site involved a large deletion event with multiple inversions and rearrangements near a retrotransposon. The MutaMouse genome gives important genetic context to studies using this model, offers insight on the mechanisms of structural variant formation, and contributes a framework to analyze aCGH results alongside NGS data.
Long-read assembly of the Chinese rhesus macaque genome and identification of ape-specific structural variants.
We present a high-quality de novo genome assembly (rheMacS) of the Chinese rhesus macaque (Macaca mulatta) using long-read sequencing and multiplatform scaffolding approaches. Compared to the current Indian rhesus macaque reference genome (rheMac8), rheMacS increases sequence contiguity 75-fold, closing 21,940 of the remaining assembly gaps (60.8 Mbp). We improve gene annotation by generating more than two million full-length transcripts from ten different tissues by long-read RNA sequencing. We sequence resolve 53,916 structural variants (96% novel) and identify 17,000 ape-specific structural variants (ASSVs) based on comparison to ape genomes. Many ASSVs map within ChIP-seq predicted enhancer regions where apes and macaque show diverged enhancer activity and gene expression. We further characterize a subset that may contribute to ape- or great-ape-specific phenotypic traits, including taillessness, brain volume expansion, improved manual dexterity, and large body size. The rheMacS genome assembly serves as an ideal reference for future biomedical and evolutionary studies.
The robust detection of structural variants in mammalian genomes remains a challenge. It is particularly difficult in the case of genetically unstable Chinese hamster ovary (CHO) cell lines with only draft genome assemblies available. We explore the potential of the CRISPR/Cas9 system for the targeted capture of genomic loci containing integrated vectors in CHO-K1-based cell lines followed by next generation sequencing (NGS), and compare it to popular target-enrichment sequencing methods and to whole genome sequencing (WGS). Three different CRISPR/Cas9-based techniques were evaluated; all of them allow for amplification-free enrichment of target genomic regions in the range from 5 to 60 fold, and for recovery of ~15 kb-long sequences with no sequencing artifacts introduced. The utility of these protocols has been proven by the identification of transgene integration sites and flanking sequences in three CHO cell lines. The long enriched fragments helped to identify Escherichia coli genome sequences co-integrated with vectors, and were further characterized by Whole Genome Sequencing (WGS). Other advantages of CRISPR/Cas9-based methods are the ease of bioinformatics analysis, potential for multiplexing, and the production of long target templates for real-time sequencing.