scholarly journals Pilot Screening of Cell-Free mtDNA in NIPT: Quality Control, Variant Calling, and Haplogroup Determination

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 743
Author(s):  
Alisa Morshneva ◽  
Polina Kozyulina ◽  
Elena Vashukova ◽  
Olga Tarasenko ◽  
Natalia Dvoynova ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Variant Calling ◽  
Prenatal Testing ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Whole Genome ◽  
Clinical Tests ◽  
Non Invasive

Clinical tests based on whole-genome sequencing are generally focused on a single task approach, testing one or several parameters, although whole-genome sequencing (WGS) provides us with large data sets that can be used for many supportive analyses. In spite of low genome coverage, data of WGS-based non-invasive prenatal testing (NIPT) contain fully sequenced mitochondrial DNA (mtDNA). This mtDNA can be used for variant calling, ancestry analysis, population studies and other approaches that extend NIPT functionality. In this study, we analyse mtDNA pool from 645 cell-free DNA (cfDNA) samples of pregnant women from different regions of Russia, explore the effects of transportation and storing conditions on mtDNA content, analyse effects, frequency and location of mitochondrial variants called from samples and perform haplogroup analysis, revealing the most common mitochondrial superclades. We have shown that, despite the relatively low sequencing depth of unamplified mtDNA from cfDNA samples, the mtDNA analysis in these samples is still an informative instrument suitable for research and screening purposes.

Isolation and whole genome sequencing of fetal cells from maternal blood towards the ultimate non-invasive prenatal testing

2017 ◽  
Vol 37 (13) ◽  
pp. 1311-1321 ◽  
Author(s):  
Fang Chen ◽  
Ping Liu ◽  
Ying Gu ◽  
Zhu Zhu ◽  
Amulya Nanisetti ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Prenatal Testing ◽  
Maternal Blood ◽  
Whole Genome ◽  
Fetal Cells ◽  
Non Invasive

scholarly journals Secondary findings from non-invasive prenatal testing for common fetal aneuploidies by whole genome sequencing as a clinical service

2013 ◽  
Vol 33 (6) ◽  
pp. 602-608 ◽  
Author(s):  
Tze Kin Lau ◽  
Fu Man Jiang ◽  
Robert J. Stevenson ◽  
Tsz Kin Lo ◽  
Lin Wai Chan ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Prenatal Testing ◽  
Clinical Service ◽  
Whole Genome ◽  
Secondary Findings ◽  
Non Invasive ◽  
Fetal Aneuploidies

scholarly journals Whole Genome Sequencing Refines Knowledge on the Population Structure of Mycobacterium bovis from a Multi-Host Tuberculosis System

2021 ◽  
Vol 9 (8) ◽  
pp. 1585
Author(s):  
Ana C. Reis ◽  
Liliana C. M. Salvador ◽  
Suelee Robbe-Austerman ◽  
Rogério Tenreiro ◽  
Ana Botelho ◽  
...  
Keyword(s):  
Population Structure ◽  
Whole Genome Sequencing ◽  
Wild Boar ◽  
Genome Sequencing ◽  
Mycobacterium Bovis ◽  
Red Deer ◽  
Variable Number Tandem Repeat ◽  
Variant Calling ◽  
Whole Genome ◽  
Network Analyses

Classical molecular analyses of Mycobacterium bovis based on spoligotyping and Variable Number Tandem Repeat (MIRU-VNTR) brought the first insights into the epidemiology of animal tuberculosis (TB) in Portugal, showing high genotypic diversity of circulating strains that mostly cluster within the European 2 clonal complex. Previous surveillance provided valuable information on the prevalence and spatial occurrence of TB and highlighted prevalent genotypes in areas where livestock and wild ungulates are sympatric. However, links at the wildlife–livestock interfaces were established mainly via classical genotype associations. Here, we apply whole genome sequencing (WGS) to cattle, red deer and wild boar isolates to reconstruct the M. bovis population structure in a multi-host, multi-region disease system and to explore links at a fine genomic scale between M. bovis from wildlife hosts and cattle. Whole genome sequences of 44 representative M. bovis isolates, obtained between 2003 and 2015 from three TB hotspots, were compared through single nucleotide polymorphism (SNP) variant calling analyses. Consistent with previous results combining classical genotyping with Bayesian population admixture modelling, SNP-based phylogenies support the branching of this M. bovis population into five genetic clades, three with apparent geographic specificities, as well as the establishment of an SNP catalogue specific to each clade, which may be explored in the future as phylogenetic markers. The core genome alignment of SNPs was integrated within a spatiotemporal metadata framework to further structure this M. bovis population by host species and TB hotspots, providing a baseline for network analyses in different epidemiological and disease control contexts. WGS of M. bovis isolates from Portugal is reported for the first time in this pilot study, refining the spatiotemporal context of TB at the wildlife–livestock interface and providing further support to the key role of red deer and wild boar on disease maintenance. The SNP diversity observed within this dataset supports the natural circulation of M. bovis for a long time period, as well as multiple introduction events of the pathogen in this Iberian multi-host system.

scholarly journals Clinical-grade whole-genome sequencing and 3′ transcriptome analysis of colorectal cancer patients

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Agata Stodolna ◽  
Miao He ◽  
Mahesh Vasipalli ◽  
Zoya Kingsbury ◽  
Jennifer Becq ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Transcriptome Analysis ◽  
Variant Calling ◽  
Standard Of Care ◽  
Genomic Variation ◽  
Whole Genome ◽  
Clinical Grade ◽  
Pathway Gene

Abstract Background Clinical-grade whole-genome sequencing (cWGS) has the potential to become the standard of care within the clinic because of its breadth of coverage and lack of bias towards certain regions of the genome. Colorectal cancer presents a difficult treatment paradigm, with over 40% of patients presenting at diagnosis with metastatic disease. We hypothesised that cWGS coupled with 3′ transcriptome analysis would give new insights into colorectal cancer. Methods Patients underwent PCR-free whole-genome sequencing and alignment and variant calling using a standardised pipeline to output SNVs, indels, SVs and CNAs. Additional insights into the mutational signatures and tumour biology were gained by the use of 3′ RNA-seq. Results Fifty-four patients were studied in total. Driver analysis identified the Wnt pathway gene APC as the only consistently mutated driver in colorectal cancer. Alterations in the PI3K/mTOR pathways were seen as previously observed in CRC. Multiple private CNAs, SVs and gene fusions were unique to individual tumours. Approximately 30% of patients had a tumour mutational burden of > 10 mutations/Mb of DNA, suggesting suitability for immunotherapy. Conclusions Clinical whole-genome sequencing offers a potential avenue for the identification of private genomic variation that may confer sensitivity to targeted agents and offer patients new options for targeted therapies.

scholarly journals Estimating sequencing error rates using families

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Kelley Paskov ◽  
Jae-Yoon Jung ◽  
Brianna Chrisman ◽  
Nate T. Stockham ◽  
Peter Washington ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Genome Sequencing ◽  
Variant Calling ◽  
Error Rates ◽  
Sequencing Error ◽  
Whole Genome ◽  
Sequencing Data ◽  
Sequencing Platform ◽  
Whole Exome

Abstract Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.

scholarly journals Variant calling in low-coverage whole genome sequencing of a Native American population sample

BMC Genomics ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 85 ◽  
Author(s):  
Chris Bizon ◽  
Michael Spiegel ◽  
Scott A Chasse ◽  
Ian R Gizer ◽  
Yun Li ◽  
...  
Keyword(s):  
Native American ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Population Sample ◽  
Variant Calling ◽  
Whole Genome ◽  
American Population ◽  
Native American Population ◽  
Low Coverage

scholarly journals Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: a Population Snapshot of InvasiveStaphylococcus aureusin Europe

mBio ◽  
2016 ◽  
Vol 7 (3) ◽  
Author(s):  
David M. Aanensen ◽  
Edward J. Feil ◽  
Matthew T. G. Holden ◽  
Janina Dordel ◽  
Corin A. Yeats ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Bacterial Pathogens ◽  
Epidemiological Surveillance ◽  
Data Sets ◽  
Whole Genome ◽  
Bioinformatic Tools ◽  
Road Map

ABSTRACTThe implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasiveStaphylococcus aureusisolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http://www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show thatin silicopredictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) community-oriented database infrastructure and analysis tools.IMPORTANCEThe spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine whole-genome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.

Sign in / Sign up

Export Citation Format

Share Document