scholarly journals de novo variant calling identifies cancer mutation profiles in the 1000 Genomes Project

2021 ◽  
Author(s):  
Jeffrey K. Ng ◽  
Pankaj Vats ◽  
Elyn Fritz-Waters ◽  
Evin M. Padhi ◽  
Zachary L. Payne ◽  
...  
Keyword(s):  
Cell Line ◽  
De Novo ◽  
Variant Calling ◽  
B Cell Lymphoma ◽  
Bimodal Distribution ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Age Related ◽  
Detailed Assessment ◽  
Paternal Parent

Detection of de novo variants (DNVs) is critical for studies of disease-related variation and mutation rates. We developed a GPU-based workflow to call DNVs, using 602 trios from the 1000 Genomes Project as a control. We detected 445,711 DNVs, having a bimodal distribution, with peaks at 200 and 2000 DNVs. The excess DNVs are cell line artifacts that are increasing with cell passage. Reduction in DNVs at CpG sites and in percent of DNVs with a paternal parent-of-origin with increasing number of DNVs supports this finding. Detailed assessment of individual NA12878 across multiple genome datasets from 2012 to 2020 reveals increasing number of DNVs over time. Mutation signature analysis across the set revealed individuals had either 1) age-related, 2) B-cell lymphoma, or 3) no prominent signatures. Our approach provides an important advancement for DNV detection and shows cell line artifacts present in lymphoblastoid cell lines are not always random.

scholarly journals Variant calling on the GRCh38 assembly with the data from phase three of the 1000 Genomes Project

2019 ◽  
Vol 4 ◽  
pp. 50 ◽  
Author(s):  
Ernesto Lowy-Gallego ◽  
Susan Fairley ◽  
Xiangqun Zheng-Bradley ◽  
Magali Ruffier ◽  
Laura Clarke ◽  
...  
Keyword(s):  
De Novo ◽  
Variant Calling ◽  
Final Phase ◽  
1000 Genomes Project ◽  
Data Set ◽  
1000 Genomes ◽  
Project Data

We present a set of biallelic SNVs and INDELs, from 2,548 samples spanning 26 populations from the 1000 Genomes Project, called de novo on GRCh38. We believe this will be a useful reference resource for those using GRCh38. It represents an improvement over the “lift-overs” of the 1000 Genomes Project data that have been available to date by encompassing all of the GRCh38 primary assembly autosomes and pseudo-autosomal regions, including novel, medically relevant loci. Here, we describe how the data set was created and benchmark our call set against that produced by the final phase of the 1000 Genomes Project on GRCh37 and the lift-over of that data to GRCh38.

scholarly journals Evaluation of serverless computing for scalable execution of a joint variant calling workflow

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254363
Author(s):  
Aji John ◽  
Kathleen Muenzen ◽  
Kristiina Ausmees
Keyword(s):  
Genetic Information ◽  
Best Practice ◽  
Workflow Management ◽  
Variant Calling ◽  
Phase Iii ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Genomics Research ◽  
The Cost ◽  
Analysis Of Performance

Advances in whole-genome sequencing have greatly reduced the cost and time of obtaining raw genetic information, but the computational requirements of analysis remain a challenge. Serverless computing has emerged as an alternative to using dedicated compute resources, but its utility has not been widely evaluated for standardized genomic workflows. In this study, we define and execute a best-practice joint variant calling workflow using the SWEEP workflow management system. We present an analysis of performance and scalability, and discuss the utility of the serverless paradigm for executing workflows in the field of genomics research. The GATK best-practice short germline joint variant calling pipeline was implemented as a SWEEP workflow comprising 18 tasks. The workflow was executed on Illumina paired-end read samples from the European and African super populations of the 1000 Genomes project phase III. Cost and runtime increased linearly with increasing sample size, although runtime was driven primarily by a single task for larger problem sizes. Execution took a minimum of around 3 hours for 2 samples, up to nearly 13 hours for 62 samples, with costs ranging from $2 to $70.

scholarly journals Accurate, scalable cohort variant calls using DeepVariant and GLnexus

2020 ◽  
Author(s):  
Taedong Yun ◽  
Helen Li ◽  
Pi-Chuan Chang ◽  
Michael F. Lin ◽  
Andrew Carroll ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Best Practices ◽  
Open Source ◽  
Variant Calling ◽  
Cost Savings ◽  
Quality Improvements ◽  
1000 Genomes Project ◽  
Genetic Analyses ◽  
1000 Genomes ◽  
Population Scale

AbstractPopulation-scale sequenced cohorts are foundational resources for genetic analyses, but processing raw reads into analysis-ready variants remains challenging. Here we introduce an open-source cohort variant-calling method using the highly-accurate caller DeepVariant and scalable merging tool GLnexus. We optimized callset quality based on benchmark samples and Mendelian consistency across many sample sizes and sequencing specifications, resulting in substantial quality improvements and cost savings over existing best practices. We further evaluated our pipeline in the 1000 Genomes Project (1KGP) samples, showing superior quality metrics and imputation performance. We publicly release the 1KGP callset to foster development of broad studies of genetic variation.

scholarly journals Inference of candidate germline mutator loci in humans from genome-wide haplotype data

2016 ◽  
Author(s):  
Cathal Seoighe ◽  
Aylwyn Scally
Keyword(s):  
Dna Damage ◽  
Dna Repair ◽  
Mutation Rate ◽  
Germline Mutation ◽  
De Novo ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
A Genome ◽  
Haplotype Data ◽  
Candidate Loci

AbstractThe rate of germline mutation varies widely between species but little is known about the extent of variation in the germline mutation rate between individuals of the same species. Here we demonstrate that an allele that increases the rate of germline mutation can result in a distinctive signature in the genomic region linked to the affected locus, characterized by a number of haplotypes with a locally high proportion of derived alleles, against a background of haplotypes carrying a typical proportion of derived alleles. We searched for this signature in human haplotype data from phase 3 of the 1000 Genomes Project and report a number of candidate mutator loci, several of which are located close to or within genes involved in DNA repair or the DNA damage response. To investigate whether mutator alleles remained active at any of these loci, we used de novo mutation counts from human parent-offspring trios in the 1000 Genomes and Genome of the Netherlands cohorts, looking for an elevated number of de novo mutations in the offspring of parents carrying a candidate mutator haplotype at each of these loci. We found some support for two of the candidate loci, including one locus just upstream of the BRSK2 gene, which is expressed in the testis and has been reported to be involved in the response to DNA damage.Author SummaryEach time a genome is replicated there is the possibility of error resulting in the incorporation of an incorrect base or bases in the genome sequence. When these errors occur in cells that lead to the production of gametes they can be incorporated into the germline. Such germline mutations are the basis of evolutionary change; however, to date there has been little attempt to quantify the extent of genetic variation in human populations in the rate at which they occur. This is particularly important because new spontaneous mutations are thought to make an important contribution to many human diseases. Here we present a new way to identify genetic loci that may be associated with an elevated rate of germline mutation and report the application of this method to data from a large number of human genomes, generated by the 1000 Genomes Project. Several of the candidate loci we report are in or near genes involved in DNA repair and some were supported by direct measurement of the mutation rate obtained from parent-offspring trios.

scholarly journals Variant calling on the GRCh38 assembly with the data from phase three of the 1000 Genomes Project

2019 ◽  
Vol 4 ◽  
pp. 50 ◽  
Author(s):  
Ernesto Lowy-Gallego ◽  
Susan Fairley ◽  
Xiangqun Zheng-Bradley ◽  
Magali Ruffier ◽  
Laura Clarke ◽  
...  
Keyword(s):  
Variant Calling ◽  
Final Phase ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Project Data

We present biallelic SNVs called from 2,548 samples across 26 populations from the 1000 Genomes Project, called directly on GRCh38. We believe this will be a useful reference resource for those using GRCh38, representing an improvement over the “lift-overs” of the 1000 Genomes Project data that have been available to date and providing a resource necessary for the full adoption of GRCh38 by the community. Here, we describe how the call set was created and provide benchmarking data describing how our call set compares to that produced by the final phase of the 1000 Genomes Project on GRCh37.

scholarly journals In trans variant calling reveals enrichment for compound heterozygous variants in genes involved in neuronal development and growth.

2019 ◽  
Vol 101 ◽  
Author(s):  
Allison J. Cox ◽  
Fillan Grady ◽  
Gabriel Velez ◽  
Vinit B. Mahajan ◽  
Polly J. Ferguson ◽  
...  
Keyword(s):  
Multiple Testing ◽  
Variant Calling ◽  
Epileptic Encephalopathy ◽  
European Ancestry ◽  
Compound Heterozygous ◽  
Recessive Trait ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Project Participants ◽  
Compound Heterozygous Variants

Abstract Compound heterozygotes occur when different variants at the same locus on both maternal and paternal chromosomes produce a recessive trait. Here we present the tool VarCount for the quantification of variants at the individual level. We used VarCount to characterize compound heterozygous coding variants in patients with epileptic encephalopathy and in the 1000 Genomes Project participants. The Epi4k data contains variants identified by whole exome sequencing in patients with either Lennox-Gastaut Syndrome (LGS) or infantile spasms (IS), as well as their parents. We queried the Epi4k dataset (264 trios) and the phased 1000 Genomes Project data (2504 participants) for recessive variants. To assess enrichment, transcript counts were compared between the Epi4k and 1000 Genomes Project participants using minor allele frequency (MAF) cutoffs of 0.5 and 1.0%, and including all ancestries or only probands of European ancestry. In the Epi4k participants, we found enrichment for rare, compound heterozygous variants in six genes, including three involved in neuronal growth and development – PRTG (p = 0.00086, 1% MAF, combined ancestries), TNC (p = 0.022, 1% MAF, combined ancestries) and MACF1 (p = 0.0245, 0.5% MAF, EU ancestry). Due to the total number of transcripts considered in these analyses, the enrichment detected was not significant after correction for multiple testing and higher powered or prospective studies are necessary to validate the candidacy of these genes. However, PRTG, TNC and MACF1 are potential novel recessive epilepsy genes and our results highlight that compound heterozygous variants should be considered in sporadic epilepsy.

scholarly journals Haplotype-resolved de novo assembly of the Vero cell line genome

npj Vaccines ◽  
2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Marie-Angélique Sène ◽  
Sascha Kiesslich ◽  
Haig Djambazian ◽  
Jiannis Ragoussis ◽  
Yu Xia ◽  
...  
Keyword(s):  
Vero Cell ◽  
Cell Line ◽  
De Novo ◽  
Variant Calling ◽  
High Yield ◽  
Vaccine Production ◽  
Emerging Pathogens ◽  
Structural Variations ◽  
Vero Cell Line ◽  
Viral Vaccine

AbstractThe Vero cell line is the most used continuous cell line for viral vaccine manufacturing with more than 40 years of accumulated experience in the vaccine industry. Additionally, the Vero cell line has shown a high affinity for infection by MERS-CoV, SARS-CoV, and recently SARS-CoV-2, emerging as an important discovery and screening tool to support the global research and development efforts in this COVID-19 pandemic. However, the lack of a reference genome for the Vero cell line has limited our understanding of host–virus interactions underlying such affinity of the Vero cell towards key emerging pathogens, and more importantly our ability to redesign high-yield vaccine production processes using Vero genome editing. In this paper, we present an annotated highly contiguous 2.9 Gb assembly of the Vero cell genome. In addition, several viral genome insertions, including Adeno-associated virus serotypes 3, 4, 7, and 8, have been identified, giving valuable insights into quality control considerations for cell-based vaccine production systems. Variant calling revealed that, in addition to interferon, chemokines, and caspases-related genes lost their functions. Surprisingly, the ACE2 gene, which was previously identified as the host cell entry receptor for SARS-CoV and SARS-CoV-2, also lost function in the Vero genome due to structural variations.

scholarly journals Improving variant calling using population data and deep learning

2021 ◽  
Author(s):  
Nae-Chyun Chen ◽  
Alexey Kolesnikov ◽  
Sidharth Goel ◽  
Taedong Yun ◽  
Pi-Chuan Chang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Variant Calling ◽  
Population Data ◽  
Training Data ◽  
1000 Genomes Project ◽  
1000 Genomes ◽  
Population Information ◽  
Scale Population ◽  
The Impact

Large-scale population variant data is often used to filter and aid interpretation of variant calls in a single sample. These approaches do not incorporate population information directly into the process of variant calling, and are often limited to filtering which trades recall for precision. In this study, we modify DeepVariant to add a new channel encoding population allele frequencies from the 1000 Genomes Project. We show that this model reduces variant calling errors, improving both precision and recall. We assess the impact of using population-specific or diverse reference panels. We achieve the greatest accuracy with diverse panels, suggesting that large, diverse panels are preferable to individual populations, even when the population matches sample ancestry. Finally, we show that this benefit generalizes to samples with different ancestry from the training data even when the ancestry is also excluded from the reference panel.

scholarly journals The quiescent X, the replicative Y and the Autosomes

2018 ◽  
Author(s):  
Guillaume Achaz ◽  
Serge Gangloff ◽  
Benoit Arcangioli
Keyword(s):  
De Novo ◽  
Yeast Cells ◽  
Simple Pattern ◽  
Maternal Lineage ◽  
1000 Genomes Project ◽  
Phase 3 ◽  
X Chromosomes ◽  
1000 Genomes ◽  
Y Chromosomes ◽  
Human Genomes

AbstractFrom the analysis of the mutation spectrum in the 2,504 sequenced human genomes from the 1000 genomes project (phase 3), we show that sexual chromosomes (X and Y) exhibit a different proportion of indel mutations than autosomes (A), ranking them X>A>Y. We further show that X chromosomes exhibit a higher ratio of deletion/insertion when compared to autosomes. This simple pattern shows that the recent report that non-dividing quiescent yeast cells accumulate relatively more indels (and particularly deletions) than replicating ones also applies to metazoan cells, including humans. Indeed, the X chromosomes display more indels than the autosomes, having spent more time in quiescent oocytes, whereas the Y chromosomes are solely present in the replicating spermatocytes. From the proportion of indels, we have inferred that de novo mutations arising in the maternal lineage are twice more likely to be indels than mutations from the paternal lineage. Our observation, consistent with a recent trio analysis of the spectrum of mutations inherited from the maternal lineage, is likely a major component in our understanding of the origin of anisogamy.

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