scholarly journals The population genomics of structural variation in a songbird genus

2019 ◽  
Author(s):  
Matthias H. Weissensteiner ◽  
Ignas Bunikis ◽  
Ana Catalán ◽  
Kees-Jan Francoijs ◽  
Ulrich Knief ◽  
...  
Keyword(s):  
Structural Variation ◽  
Population Genomics ◽  
De Novo ◽  
Natural Populations ◽  
Evolutionary Significance ◽  
Substantial Part ◽  
Sequencing Data ◽  
Premating Isolation ◽  
Population Genetic Analysis ◽  
Long Read

AbstractStructural variation (SV) accounts for a substantial part of genetic mutations segregating across eukaryotic genomes with important medical and evolutionary implications. Here, we characterized SV across evolutionary time scales in the songbird genus Corvus using de novo assembly and read mapping approaches. Combining information from short-read (N = 127) and long-read re-sequencing data (N = 31) as well as from optical maps (N = 16) revealed a total of 201,738 insertions, deletions and inversions. Population genetic analysis of SV in the Eurasian crow speciation model revealed an evolutionary young (~530,000 years) cis-acting 2.25-kb retrotransposon insertion reducing expression of the NDP gene with consequences for premating isolation. Our results attest to the wealth of SV segregating in natural populations and demonstrate its evolutionary significance.

scholarly journals Trio deep-sequencing does not reveal unexpected off-target and on-target mutations in Cas9-edited rhesus monkeys

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Xin Luo ◽  
Yaoxi He ◽  
Chao Zhang ◽  
Xiechao He ◽  
Lanzhen Yan ◽  
...  
Keyword(s):  
Rhesus Monkeys ◽  
De Novo ◽  
Preclinical Model ◽  
Structural Variants ◽  
Sequencing Data ◽  
De Novo Mutations ◽  
Target Region ◽  
Long Read ◽  
Target Effect

AbstractCRISPR-Cas9 is a widely-used genome editing tool, but its off-target effect and on-target complex mutations remain a concern, especially in view of future clinical applications. Non-human primates (NHPs) share close genetic and physiological similarities with humans, making them an ideal preclinical model for developing Cas9-based therapies. However, to our knowledge no comprehensive in vivo off-target and on-target assessment has been conducted in NHPs. Here, we perform whole genome trio sequencing of Cas9-treated rhesus monkeys. We only find a small number of de novo mutations that can be explained by expected spontaneous mutations, and no unexpected off-target mutations (OTMs) were detected. Furthermore, the long-read sequencing data does not detect large structural variants in the target region.

scholarly journals Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads

2020 ◽  
Author(s):  
David Porubsky ◽  
◽  
Peter Ebert ◽  
Peter A. Audano ◽  
Mitchell R. Vollger ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Assembly ◽  
De Novo ◽  
Error Rates ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
De Novo Genome Assembly ◽  
Parental Data ◽  
Human Genome Assembly ◽  
Long Read

AbstractHuman genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.

scholarly journals Closing Human Reference Genome Gaps: Identifying and Characterizing Gap-Closing Sequences

2020 ◽  
Vol 10 (8) ◽  
pp. 2801-2809 ◽  
Author(s):  
Tingting Zhao ◽  
Zhongqu Duan ◽  
Georgi Z. Genchev ◽  
Hui Lu
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Sequence Length ◽  
Sequencing Data ◽  
Human Reference Genome ◽  
Satellite Sequences ◽  
Long Read ◽  
Data Gap ◽  
Simple Repeats ◽  
Gap Closing

Despite continuous updates of the human reference genome, there are still hundreds of unresolved gaps which account for about 5% of the total sequence length. Given the availability of whole genome de novo assemblies, especially those derived from long-read sequencing data, gap-closing sequences can be determined. By comparing 17 de novo long-read sequencing assemblies with the human reference genome, we identified a total of 1,125 gap-closing sequences for 132 (16.9% of 783) gaps and added up to 2.2 Mb novel sequences to the human reference genome. More than 90% of the non-redundant sequences could be verified by unmapped reads from the Simons Genome Diversity Project dataset. In addition, 15.6% of the non-reference sequences were found in at least one of four non-human primate genomes. We further demonstrated that the non-redundant sequences had high content of simple repeats and satellite sequences. Moreover, 43 (32.6%) of the 132 closed gaps were shown to be polymorphic; such sequences may play an important biological role and can be useful in the investigation of human genetic diversity.

scholarly journals NanoGalaxy: Nanopore long-read sequencing data analysis in Galaxy

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Willem de Koning ◽  
Milad Miladi ◽  
Saskia Hiltemann ◽  
Astrid Heikema ◽  
John P Hays ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Bioinformatics Analysis ◽  
De Novo ◽  
Sequence Data ◽  
Ease Of Use ◽  
Easy Access ◽  
Complex Data ◽  
Sequencing Data ◽  
Long Read ◽  
Sequencing Platforms

Abstract Background Long-read sequencing can be applied to generate very long contigs and even completely assembled genomes at relatively low cost and with minimal sample preparation. As a result, long-read sequencing platforms are becoming more popular. In this respect, the Oxford Nanopore Technologies–based long-read sequencing “nanopore" platform is becoming a widely used tool with a broad range of applications and end-users. However, the need to explore and manipulate the complex data generated by long-read sequencing platforms necessitates accompanying specialized bioinformatics platforms and tools to process the long-read data correctly. Importantly, such tools should additionally help democratize bioinformatics analysis by enabling easy access and ease-of-use solutions for researchers. Results The Galaxy platform provides a user-friendly interface to computational command line–based tools, handles the software dependencies, and provides refined workflows. The users do not have to possess programming experience or extended computer skills. The interface enables researchers to perform powerful bioinformatics analysis, including the assembly and analysis of short- or long-read sequence data. The newly developed “NanoGalaxy" is a Galaxy-based toolkit for analysing long-read sequencing data, which is suitable for diverse applications, including de novo genome assembly from genomic, metagenomic, and plasmid sequence reads. Conclusions A range of best-practice tools and workflows for long-read sequence genome assembly has been integrated into a NanoGalaxy platform to facilitate easy access and use of bioinformatics tools for researchers. NanoGalaxy is freely available at the European Galaxy server https://nanopore.usegalaxy.eu with supporting self-learning training material available at https://training.galaxyproject.org.

scholarly journals Genotyping and De Novo Discovery of Allelic Variants at the Brassicaceae Self-Incompatibility Locus from Short-Read Sequencing Data

2019 ◽  
Vol 37 (4) ◽  
pp. 1193-1201 ◽  
Author(s):  
Mathieu Genete ◽  
Vincent Castric ◽  
Xavier Vekemans
Keyword(s):  
De Novo ◽  
Balancing Selection ◽  
Methodological Approach ◽  
Natural Populations ◽  
Sequence Divergence ◽  
Reference Database ◽  
Self Incompatibility ◽  
Sequencing Data ◽  
Allelic Series ◽  
S Alleles

Abstract Plant self-incompatibility (SI) is a genetic system that prevents selfing and enforces outcrossing. Because of strong balancing selection, the genes encoding SI are predicted to maintain extraordinarily high levels of polymorphism, both in terms of the number of functionally distinct S-alleles that segregate in SI species and in terms of their nucleotide sequence divergence. However, because of these two combined features, documenting polymorphism of these genes also presents important methodological challenges that have so far largely prevented the comprehensive analysis of complete allelic series in natural populations, and also precluded the obtention of complete genic sequences for many S-alleles. Here, we develop a powerful methodological approach based on a computationally optimized comparison of short Illumina sequencing reads from genomic DNA to a database of known nucleotide sequences of the extracellular domain of SRK (eSRK). By examining mapping patterns along the reference sequences, we obtain highly reliable predictions of S-genotypes from individuals collected from natural populations of Arabidopsis halleri. Furthermore, using a de novo assembly approach of the filtered short reads, we obtain full-length sequences of eSRK even when the initial sequence in the database was only partial, and we discover putative new SRK alleles that were not initially present in the database. When including those new alleles in the reference database, we were able to resolve the complete diploid SI genotypes of all individuals. Beyond the specific case of Brassicaceae S-alleles, our approach can be readily applied to other polymorphic loci, given reference allelic sequences are available.

scholarly journals A benchmark of structural variation detection by long reads through a realistic simulated model

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Nicolas Dierckxsens ◽  
Tong Li ◽  
Joris R. Vermeesch ◽  
Zhi Xie
Keyword(s):  
Structural Variation ◽  
New Method ◽  
Sequencing Data ◽  
Simulated Model ◽  
Long Reads ◽  
Long Read ◽  
Sequencing Platforms

AbstractAccurate simulations of structural variation distributions and sequencing data are crucial for the development and benchmarking of new tools. We develop Sim-it, a straightforward tool for the simulation of both structural variation and long-read data. These simulations from Sim-it reveal the strengths and weaknesses for current available structural variation callers and long-read sequencing platforms. With these findings, we develop a new method (combiSV) that can combine the results from structural variation callers into a superior call set with increased recall and precision, which is also observed for the latest structural variation benchmark set developed by the GIAB Consortium.

scholarly journals Germline mosaicism of a missense variant in KCNC2 in a multiplex family with autism and epilepsy

2021 ◽  
Author(s):  
Elvisa Mehinovic ◽  
Teddi Gray ◽  
Meghan Campbell ◽  
Jenny Ekholm ◽  
Aaron Wenger ◽  
...  
Keyword(s):  
De Novo ◽  
Copy Number Variants ◽  
Missense Variant ◽  
Missense Mutations ◽  
Sequencing Data ◽  
Multiplex Family ◽  
Protein Coding ◽  
Germline Mosaicism ◽  
Current Decay ◽  
Long Read

ABSTRACTCurrently, protein-coding de novo variants and large copy number variants have been identified as important for ∼30% of individuals with autism. One approach to identify relevant variation in individuals who lack these types of events is by utilizing newer genomic technologies. In this study, highly accurate PacBio HiFi long-read sequencing was applied to a family with autism, treatment-refractory epilepsy, cognitive impairment, and mild dysmorphic features (two affected female full siblings, parents, and one unaffected sibling) with no known clinical variant. From our long-read sequencing data, a de novo missense variant in the KCNC2 gene (encodes Kv3.2 protein) was identified in both affected children. This variant was phased to the paternal chromosome of origin and is likely a germline mosaic. In silico assessment of the variant revealed it was in the top 0.05% of all conserved bases in the genome, and was predicted damaging by Polyphen2, MutationTaster, and SIFT. It was not present in any controls from public genome databases nor in a joint-call set we generated across 49 individuals with publicly available PacBio HiFi data. This specific missense mutation (Val473Ala) has been shown in both an ortholog and paralog of Kv3.2 to accelerate current decay, shift the voltage dependence of activation, and prevent the channel from entering a long-lasting open state. Seven additional missense mutations have been identified in other individuals with neurodevelopmental disorders (p = 1.03 × 10−5). KCNC2 is most highly expressed in the brain; in particular, in the thalamus and is enriched in GABAergic neurons. Long-read sequencing was useful in discovering the relevant variant in this family with autism that had remained a mystery for several years and will potentially have great benefits in the clinic once it is widely available.

scholarly journals An exploration of assembly strategies and quality metrics on the accuracy of the Knightia excelsa (rewarewa) genome.

2021 ◽  
Author(s):  
Ann McCartney ◽  
Elena Hilario ◽  
Seung-Sub Choi ◽  
Joseph Guhlin ◽  
Jessie Prebble ◽  
...  
Keyword(s):  
New Zealand ◽  
De Novo ◽  
Quality Metrics ◽  
Read Length ◽  
Model Organisms ◽  
Sequencing Data ◽  
Contig Assembly ◽  
High Quality ◽  
Aotearoa New Zealand ◽  
Long Read

We used long read sequencing data generated from Knightia excelsaI R.Br, a nectar producing Proteaceae tree endemic to Aotearoa New Zealand, to explore how sequencing data type, volume and workflows can impact final assembly accuracy and chromosome construction. Establishing a high-quality genome for this species has specific cultural importance to Māori, the indigenous people, as well as commercial importance to honey producers in Aotearoa New Zealand. Assemblies were produced by five long read assemblers using data subsampled based on read lengths, two polishing strategies, and two Hi-C mapping methods. Our results from subsampling the data by read length showed that each assembler tested performed differently depending on the coverage and the read length of the data. Assemblies that used longer read lengths (>30 kb) and lower coverage were the most contiguous, kmer and gene complete. The final genome assembly was constructed into pseudo-chromosomes using all available data assembled with FLYE, polished using Racon/Medaka/Pilon combined, scaffolded using SALSA2 and AllHiC, curated using Juicebox, and validated by synteny with Macadamia. We highlighted the importance of developing assembly workflows based on the volume and type of sequencing data and establishing a set of robust quality metrics for generating high quality assemblies. Scaffolding analyses highlighted that problems found in the initial assemblies could not be resolved accurately by utilizing Hi-C data and that scaffolded assemblies were more accurate when the underlying contig assembly was of higher accuracy. These findings provide insight into what is required for future high-quality de-novo assemblies of non-model organisms.

scholarly journals Complete Genome Sequence of Acinetobacter baumannii Strain B8342, a Motility-Positive Clinical Isolate

2015 ◽  
Vol 3 (4) ◽  
Author(s):  
Saranya Vijaykumar ◽  
Veeraraghavan Balaji ◽  
Indranil Biswas
Keyword(s):  
Health Care ◽  
Acinetobacter Baumannii ◽  
Complete Genome Sequence ◽  
Complete Genome ◽  
De Novo ◽  
Clinical Strain ◽  
Sequencing Data ◽  
Gram Negative ◽  
Long Read ◽  
Health Care Associated Infections

Acinetobacter baumannii is an emerging Gram-negative pathogen responsible for health care–associated infections. In this study, we determined the genome of a motility-positive clinical strain, B8342, isolated from a hospital in southern India. The B8342 genome, which is 3.94 Mbp, was generated by de novo assembly of PacBio long-read sequencing data.

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