Analysis of Transposable Elements in the Genome of Asparagus officinalis from High Coverage Sequence Data

Abstract Background The main goal of this collaborative effort is to provide genome-wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for public data release. BGISEQ-500 sequence data and genotypes by an Illumina GWAS chip were cross-validated on multiple samples and additionally referenced to 1 sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage. Results The genome data have been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, copy number variations, single-nucletide polymorphisms, and microsatellites. To our knowledge, this study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for medical research in a large understudied population. Conclusions Our results indicate that the genetic diversity of the Ukrainian population is uniquely shaped by evolutionary and demographic forces and cannot be ignored in future genetic and biomedical studies. These data will contribute a wealth of new information bringing forth a wealth of novel, endemic and medically related alleles.

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A long reads-based de-novo assembly of the genome of the Arlee homozygous line reveals chromosomal rearrangements in rainbow trout

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab052 ◽

2021 ◽

Author(s):

Guangtu Gao ◽

Susana Magadan ◽

Geoffrey C Waldbieser ◽

Ramey C Youngblood ◽

Paul A Wheeler ◽

...

Keyword(s):

Rainbow Trout ◽

Chromosome Number ◽

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Sequence Data ◽

Structural Variations ◽

High Coverage ◽

Haploid Chromosome Number ◽

Long Reads

Abstract Currently, there is still a need to improve the contiguity of the rainbow trout reference genome and to use multiple genetic backgrounds that will represent the genetic diversity of this species. The Arlee doubled haploid line was originated from a domesticated hatchery strain that was originally collected from the northern California coast. The Canu pipeline was used to generate the Arlee line genome de-novo assembly from high coverage PacBio long-reads sequence data. The assembly was further improved with Bionano optical maps and Hi-C proximity ligation sequence data to generate 32 major scaffolds corresponding to the karyotype of the Arlee line (2 N = 64). It is composed of 938 scaffolds with N50 of 39.16 Mb and a total length of 2.33 Gb, of which ∼95% was in 32 chromosome sequences with only 438 gaps between contigs and scaffolds. In rainbow trout the haploid chromosome number can vary from 29 to 32. In the Arlee karyotype the haploid chromosome number is 32 because chromosomes Omy04, 14 and 25 are divided into six acrocentric chromosomes. Additional structural variations that were identified in the Arlee genome included the major inversions on chromosomes Omy05 and Omy20 and additional 15 smaller inversions that will require further validation. This is also the first rainbow trout genome assembly that includes a scaffold with the sex-determination gene (sdY) in the chromosome Y sequence. The utility of this genome assembly is demonstrated through the improved annotation of the duplicated genome loci that harbor the IGH genes on chromosomes Omy12 and Omy13.

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A curated dataset of modern and ancient high-coverage shotgun human genomes

Scientific Data ◽

10.1038/s41597-021-00980-1 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Pierpaolo Maisano Delser ◽

Eppie R. Jones ◽

Anahit Hovhannisyan ◽

Lara Cassidy ◽

Ron Pinhasi ◽

...

Keyword(s):

Sequence Data ◽

Whole Genome ◽

Reference Dataset ◽

High Coverage ◽

Sample Distribution ◽

Human Samples ◽

Human Genomes ◽

Genome Wide ◽

Genome Wide Data ◽

Computationally Intensive

AbstractOver the last few years, genome-wide data for a large number of ancient human samples have been collected. Whilst datasets of captured SNPs have been collated, high coverage shotgun genomes (which are relatively few but allow certain types of analyses not possible with ascertained captured SNPs) have to be reprocessed by individual groups from raw reads. This task is computationally intensive. Here, we release a dataset including 35 whole-genome sequenced samples, previously published and distributed worldwide, together with the genetic pipeline used to process them. The dataset contains 72,041,355 sites called across 19 ancient and 16 modern individuals and includes sequence data from four previously published ancient samples which we sequenced to higher coverage (10–18x). Such a resource will allow researchers to analyse their new samples with the same genetic pipeline and directly compare them to the reference dataset without re-processing published samples. Moreover, this dataset can be easily expanded to increase the sample distribution both across time and space.

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ntEdit: scalable genome sequence polishing

Bioinformatics ◽

10.1093/bioinformatics/btz400 ◽

2019 ◽

Vol 35 (21) ◽

pp. 4430-4432 ◽

Cited By ~ 8

Author(s):

René L Warren ◽

Lauren Coombe ◽

Hamid Mohamadi ◽

Jessica Zhang ◽

Barry Jaquish ◽

...

Keyword(s):

Human Genome ◽

Genome Sequence ◽

Sequence Data ◽

Bloom Filter ◽

Supplementary Information ◽

Routine Practice ◽

High Coverage ◽

Illumina Sequence ◽

Genome Assemblies ◽

Indel Rate

Abstract Motivation In the modern genomics era, genome sequence assemblies are routine practice. However, depending on the methodology, resulting drafts may contain considerable base errors. Although utilities exist for genome base polishing, they work best with high read coverage and do not scale well. We developed ntEdit, a Bloom filter-based genome sequence editing utility that scales to large mammalian and conifer genomes. Results We first tested ntEdit and the state-of-the-art assembly improvement tools GATK, Pilon and Racon on controlled Escherichia coli and Caenorhabditis elegans sequence data. Generally, ntEdit performs well at low sequence depths (<20×), fixing the majority (>97%) of base substitutions and indels, and its performance is largely constant with increased coverage. In all experiments conducted using a single CPU, the ntEdit pipeline executed in <14 s and <3 m, on average, on E.coli and C.elegans, respectively. We performed similar benchmarks on a sub-20× coverage human genome sequence dataset, inspecting accuracy and resource usage in editing chromosomes 1 and 21, and whole genome. ntEdit scaled linearly, executing in 30–40 m on those sequences. We show how ntEdit ran in <2 h 20 m to improve upon long and linked read human genome assemblies of NA12878, using high-coverage (54×) Illumina sequence data from the same individual, fixing frame shifts in coding sequences. We also generated 17-fold coverage spruce sequence data from haploid sequence sources (seed megagametophyte), and used it to edit our pseudo haploid assemblies of the 20 Gb interior and white spruce genomes in <4 and <5 h, respectively, making roughly 50M edits at a (substitution+indel) rate of 0.0024. Availability and implementation https://github.com/bcgsc/ntedit Supplementary information Supplementary data are available at Bioinformatics online.

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Evaluating sequence data quality from the Swift Accel-Amplicon CFTR Panel

Scientific Data ◽

10.1038/s41597-019-0339-4 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Marco L. Leung ◽

Deborah J. Watson ◽

Courtney N. Vaccaro ◽

Fernanda Mafra ◽

Adam Wenocur ◽

...

Keyword(s):

Cystic Fibrosis ◽

Screening Program ◽

Sequence Data ◽

Genetic Diseases ◽

Control Sample ◽

Gc Content ◽

Carrier Status ◽

Sequencing Data ◽

High Coverage ◽

Detection Rates

AbstractCystic fibrosis (CF) is one of the most common genetic diseases worldwide with high carrier frequencies across different ethnicities. Next generation sequencing of the cystic fibrosis transmembrane conductance regulator (CFTR) gene has proven to be an effective screening tool to determine carrier status with high detection rates. Here, we evaluate the performance of the Swift Biosciences Accel-Amplicon CFTR Capture Panel using CFTR-positive DNA samples. This assay is a one-day protocol that allows for one-tube reaction of 87 amplicons that span all coding regions, 5′ and 3′UTR, as well as four intronic regions. In this study, we provide the FASTQ, BAM, and VCF files on seven unique CFTR-positive samples and one normal control sample (14 samples processed including repeated samples). This method generated sequencing data with high coverage and near 100% on-target reads. We found that coverage depth was correlated with the GC content of each exon. This dataset is instrumental for clinical laboratories that are evaluating this technology as part of their carrier screening program.

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Estimating genotype error rates from high-coverage next-generation sequence data

Genome Research ◽

10.1101/gr.168393.113 ◽

2014 ◽

Vol 24 (11) ◽

pp. 1734-1739 ◽

Cited By ~ 84

Author(s):

Jeffrey D. Wall ◽

Ling Fung Tang ◽

Brandon Zerbe ◽

Mark N. Kvale ◽

Pui-Yan Kwok ◽

...

Keyword(s):

Sequence Data ◽

Error Rates ◽

Next Generation ◽

High Coverage

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A curated dataset of modern and ancient high-coverage shotgun human genomes

10.1101/2020.10.27.351692 ◽

2020 ◽

Author(s):

Pierpaolo Maisano Delser ◽

Eppie R. Jones ◽

Anahit Hovhannisyan ◽

Lara Cassidy ◽

Ron Pinhasi ◽

...

Keyword(s):

Sequence Data ◽

Whole Genome ◽

Reference Dataset ◽

High Coverage ◽

Sample Distribution ◽

Human Samples ◽

Human Genomes ◽

Genome Wide ◽

Genome Wide Data ◽

Computationally Intensive

AbstractOver the last few years, genome-wide data for a large number of ancient human samples have been collected. Whilst datasets of capture SNPs have been collated, high coverage shotgun genomes (which are relatively few but allow certain type of analyses not possible with ascertained captured SNPs) have to be reprocessed by individual groups from raw reads. This task is computationally intensive. Here, we release a dataset including 34 whole-genome sequenced samples, previously published and distributed worldwide, together with the genetic pipeline used to process them. The dataset contains 73,435,604 sites called across 18 ancient and 16 modern individuals and includes sequence data from four previously published ancient samples which we sequenced to higher coverage (10-18x). Such a resource will allow researchers to analyse their new samples with the same genetic pipeline and directly compare them to the reference dataset without re-processing published samples. Moreover, this dataset can be easily expanded to increase the sample distribution both across time and space.

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High coverage whole genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios

10.1101/2021.02.06.430068 ◽

2021 ◽

Cited By ~ 4

Author(s):

Marta Byrska-Bishop ◽

Uday S. Evani ◽

Xuefang Zhao ◽

Anna O. Basile ◽

Haley J. Abel ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Sequence Data ◽

Whole Genome ◽

1000 Genomes Project ◽

Phase 3 ◽

High Coverage ◽

Entire Cohort ◽

1000 Genomes ◽

Low Coverage

ABSTRACTThe 1000 Genomes Project (1kGP), launched in 2008, is the largest fully open resource of whole genome sequencing (WGS) data consented for public distribution of raw sequence data without access or use restrictions. The final (phase 3) 2015 release of 1kGP included 2,504 unrelated samples from 26 populations, representing five continental regions of the world and was based on a combination of technologies including low coverage WGS (mean depth 7.4X), high coverage whole exome sequencing (mean depth 65.7X), and microarray genotyping. Here, we present a new, high coverage WGS resource encompassing the original 2,504 1kGP samples, as well as an additional 698 related samples that result in 602 complete trios in the 1kGP cohort. We sequenced this expanded 1kGP cohort of 3,202 samples to a targeted depth of 30X using Illumina NovaSeq 6000 instruments. We performed SNV/INDEL calling against the GRCh38 reference using GATK’s HaplotypeCaller, and generated a comprehensive set of SVs by integrating multiple analytic methods through a sophisticated machine learning model, upgrading the 1kGP dataset to current state-of-the-art standards. Using this strategy, we defined over 111 million SNVs, 14 million INDELs, and ∼170 thousand SVs across the entire cohort of 3,202 samples with estimated false discovery rate (FDR) of 0.3%, 1.0%, and 1.8%, respectively. By comparison to the low-coverage phase 3 callset, we observed substantial improvements in variant discovery and estimated FDR that were facilitated by high coverage re-sequencing and expansion of the cohort. Specifically, we called 7% more SNVs, 59% more INDELs, and 170% more SVs per genome than the phase 3 callset. Moreover, we leveraged the presence of families in the cohort to achieve superior haplotype phasing accuracy and we demonstrate improvements that the high coverage panel brings especially for INDEL imputation. We make all the data generated as part of this project publicly available and we envision this updated version of the 1kGP callset to become the new de facto public resource for the worldwide scientific community working on genomics and genetics.

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Chromosome-level assembly of the common lizard (Zootoca vivipara) genome

10.1101/520528 ◽

2019 ◽

Cited By ~ 1

Author(s):

Andrey A. Yurchenko ◽

Hans Recknagel ◽

Kathryn R. Elmer

Keyword(s):

Sequence Data ◽

Multiple Paternity ◽

Single Copy ◽

High Quality ◽

High Coverage ◽

Squamate Reptiles ◽

Common Lizard ◽

Zootoca Vivipara ◽

The Common ◽

Chromosome Level

ABSTRACTSquamate reptiles exhibit high variation in their traits and geographical distribution and are therefore fascinating taxa for evolutionary and ecological research. However, high-quality genomic recourses are very limited for this group of species, which inhibits some research efforts. To address this gap, we assembled a high-quality genome of the common lizard Zootoca vivipara (Lacertidae) using a combination of high coverage Illumina (shotgun and mate-pair) and PacBio sequence data, with RNAseq data and genetic linkage maps. The 1.46 Gbp genome assembly has scaffold N50 of 11.52 Mbp with N50 contig size of 220.4 Kbp and only 2.96% gaps. A BUSCO analysis indicates that 97.7% of the single-copy Tetrapoda orthologs were recovered in the assembly. In total 19,829 gene models were annotated in the genome using a combination of three ab initio and homology-based methods. To improve the chromosome-level assembly, we generated a high-density linkage map from wild-caught families and developed a novel analytical pipeline to accommodate multiple paternity and unknown father genotypes. We successfully anchored and oriented almost 90% of the genome on 19 linkage groups. This annotated and oriented chromosome-level reference genome represents a valuable resource to facilitate evolutionary studies in squamate reptiles.

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Classic and introgressed selective sweeps shape mimicry loci across a butterfly adaptive radiation

10.1101/685685 ◽

2019 ◽

Cited By ~ 2

Author(s):

Markus Moest ◽

Steven M. Van Belleghem ◽

Jennifer E. James ◽

Camilo Salazar ◽

Simon H. Martin ◽

...

Keyword(s):

Adaptive Radiation ◽

Sequence Data ◽

Colour Pattern ◽

Stabilizing Selection ◽

High Coverage ◽

Adaptive Introgression ◽

Wing Patterns ◽

History Of ◽

Colour Patterns ◽

Turn Over

AbstractNatural selection leaves distinct signatures in the genome that can reveal the targets and history of adaptive evolution. By analysing high-coverage genome sequence data from four major colour pattern loci sampled from nearly 600 individuals in 53 populations, we show pervasive selection on wing patterns across the Heliconius adaptive radiation. The strongest signatures correspond to loci with the greatest phenotypic effects, consistent with visual selection by predators, and are found in colour patterns with geographically restricted distributions. These recent sweeps are similar between co-mimics and indicate colour pattern turn-over events despite strong stabilizing selection. Using simulations we compare sweep signatures expected under classic hard sweeps with those resulting from adaptive introgression, an important aspect of mimicry evolution in Heliconius. Simulated recipient populations show a distinct ‘volcano’ pattern with peaks of increased genetic diversity around the selected target, consistent with patterns found in some populations. Our genomic data provide unprecedented insights into the recent history of selection across the Heliconius adaptive radiation.

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