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 Population Structure of Mycobacterium bovis in Germany: a Long-Term Study Using Whole-Genome Sequencing Combined with Conventional Molecular Typing Methods

2020 ◽  
Vol 58 (11) ◽  
Author(s):  
Thomas A. Kohl ◽  
Katharina Kranzer ◽  
Sönke Andres ◽  
Thierry Wirth ◽  
Stefan Niemann ◽  
...  
Keyword(s):  
Population Structure ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Mycobacterium Bovis ◽  
Variable Number Tandem Repeat ◽  
Epidemiological Surveillance ◽  
Whole Genome ◽  
Content Type ◽  
Long Term Study ◽  
Wide Range

ABSTRACT Mycobacterium bovis is the primary cause of bovine tuberculosis (bTB) and infects a wide range of domestic animal and wildlife species and humans. In Germany, bTB still emerges sporadically in cattle herds, free-ranging wildlife, diverse captive animal species, and humans. In order to understand the underlying population structure and estimate the population size fluctuation through time, we analyzed 131 M. bovis strains from animals (n = 38) and humans (n = 93) in Germany from 1999 to 2017 by whole-genome sequencing (WGS), mycobacterial interspersed repetitive-unit–variable-number tandem-repeat (MIRU-VNTR) typing, and spoligotyping. Based on WGS data analysis, 122 out of the 131 M. bovis strains were classified into 13 major clades, of which 6 contained strains from both human and animal cases and 7 only strains from human cases. Bayesian analyses suggest that the M. bovis population went through two sharp anticlimaxes, one in the middle of the 18th century and another one in the 1950s. WGS-based cluster analysis grouped 46 strains into 13 clusters ranging in size from 2 to 11 members and involving strains from distinct host types, e.g., only cattle and also mixed hosts. Animal strains of four clusters were obtained over a 9-year span, pointing toward autochthonous persistent bTB infection cycles. As expected, WGS had a higher discriminatory power than spoligotyping and MIRU-VNTR typing. In conclusion, our data confirm that WGS and suitable bioinformatics constitute the method of choice to implement prospective molecular epidemiological surveillance of M. bovis. The population of M. bovis in Germany is diverse, with subtle, but existing, interactions between different host groups.

scholarly journals Phylogenomics Sheds Light on the population structure of Mycobacterium bovis from a Multi-Host Tuberculosis System

2021 ◽  
Author(s):  
Ana C. Reis ◽  
Liliana C.M. Salvador ◽  
Suelee Robbe-Austerman ◽  
Rogério Tenreiro ◽  
Ana Botelho ◽  
...  
Keyword(s):  
Wild Boar ◽  
Mycobacterium Bovis ◽  
Red Deer ◽  
Evolutionary Dynamics ◽  
Genetic Relatedness ◽  
Variable Number Tandem Repeat ◽  
Variant Calling ◽  
Pathogen Transmission ◽  
Whole Genome ◽  
Host System

AbstractMolecular analyses of Mycobacterium bovis based on spoligotyping and Variable Number Tandem Repeat (MIRU-VNTR) brought 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. The genetic relatedness of M. bovis isolates from cattle and wildlife have also suggested sustained transmission within this multi-host system. However, while previous surveillance highlighted prevalent genotypes in areas where livestock and wild ungulates are sympatric and provided valuable information on the prevalence and spatial occurrence of TB, links at the wildlife-livestock interfaces were established mainly via genotype associations. Therefore, evidence at a local fine scale of transmission events linking wildlife hosts and cattle remains lacking. Here, we explore the advantages of whole genome sequencing (WGS) applied to cattle, red deer and wild boar isolates to reconstruct the evolutionary dynamics of M. bovis and to identify putative pathogen transmission events. 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 geographic specificities, as well as the establishment of a SNPs 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 reconstruct transmission networks, which together with inferred secondary cases, further structured this M. bovis population by host species and geographic location.WGS of M. bovis isolates from Portugal is reported for the first time, refining the spatiotemporal context of transmission events and providing further support to the key role of red deer and wild boar on the persistence of animal TB in this Iberian multi-host system.

scholarly journals Assessing genomic diversity and signatures of selection in Jiaxian Red cattle using whole-genome sequencing data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaoting Xia ◽  
Shunjin Zhang ◽  
Huaju Zhang ◽  
Zijing Zhang ◽  
Ningbo Chen ◽  
...  
Keyword(s):  
Population Structure ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genomic Variation ◽  
Genomic Diversity ◽  
System Response ◽  
Whole Genome ◽  
Population Structure Analysis ◽  
Native Cattle ◽  
Genomic Regions

Abstract Background Native cattle breeds are an important source of genetic variation because they might carry alleles that enable them to adapt to local environment and tough feeding conditions. Jiaxian Red, a Chinese native cattle breed, is reported to have originated from crossbreeding between taurine and indicine cattle; their history as a draft and meat animal dates back at least 30 years. Using whole-genome sequencing (WGS) data of 30 animals from the core breeding farm, we investigated the genetic diversity, population structure and genomic regions under selection of Jiaxian Red cattle. Furthermore, we used 131 published genomes of world-wide cattle to characterize the genomic variation of Jiaxian Red cattle. Results The population structure analysis revealed that Jiaxian Red cattle harboured the ancestry with East Asian taurine (0.493), Chinese indicine (0.379), European taurine (0.095) and Indian indicine (0.033). Three methods (nucleotide diversity, linkage disequilibrium decay and runs of homozygosity) implied the relatively high genomic diversity in Jiaxian Red cattle. We used θπ, CLR, FST and XP-EHH methods to look for the candidate signatures of positive selection in Jiaxian Red cattle. A total number of 171 (θπ and CLR) and 17 (FST and XP-EHH) shared genes were identified using different detection strategies. Functional annotation analysis revealed that these genes are potentially responsible for growth and feed efficiency (CCSER1), meat quality traits (ROCK2, PPP1R12A, CYB5R4, EYA3, PHACTR1), fertility (RFX4, SRD5A2) and immune system response (SLAMF1, CD84 and SLAMF6). Conclusion We provide a comprehensive overview of sequence variations in Jiaxian Red cattle genomes. Selection signatures were detected in genomic regions that are possibly related to economically important traits in Jiaxian Red cattle. We observed a high level of genomic diversity and low inbreeding in Jiaxian Red cattle. These results provide a basis for further resource protection and breeding improvement of this breed.

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 Whole Genome Sequencing for Determining the Source of Mycobacterium bovis Infections in Livestock Herds and Wildlife in New Zealand

2018 ◽  
Vol 5 ◽  
Author(s):  
Marian Price-Carter ◽  
Rudiger Brauning ◽  
Geoffrey W. de Lisle ◽  
Paul Livingstone ◽  
Mark Neill ◽  
...  
Keyword(s):  
New Zealand ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Mycobacterium Bovis ◽  
Whole Genome

scholarly journals Genetic Characterization of Brucella spp.: Whole Genome Sequencing-Based Approach for the Determination of Multiple Locus Variable Number Tandem Repeat Profiles

2021 ◽  
Vol 12 ◽  
Author(s):  
Ana Pelerito ◽  
Alexandra Nunes ◽  
Teresa Grilo ◽  
Joana Isidro ◽  
Catarina Silva ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
In Silico ◽  
Variable Number Tandem Repeat ◽  
Epidemiological Studies ◽  
Variable Number ◽  
Epidemiological Surveillance ◽  
Future Application ◽  
Whole Genome

Brucellosis is an important zoonosis that is emerging in some regions of the world, gaining increased relevance with the inclusion of the causing agent Brucella spp. in the class B bioterrorism group. Until now, multi-locus VNTR Analysis (MLVA) based on 16 loci has been considered as the gold standard for Brucella typing. However, this methodology is laborious, and, with the rampant release of Brucella genomes, the transition from the traditional MLVA to whole genome sequencing (WGS)-based typing is on course. Nevertheless, in order to avoid a disruptive transition with the loss of massive genetic data obtained throughout the last decade and considering that the transition timings will vary considerably among different countries, it is important to determine WGS-based MLVA alleles of the nowadays sequenced genomes. On this regard, we aimed to evaluate the performance of a Python script that had been previously developed for the rapid in silico extraction of the MLVA alleles, by comparing it to the PCR-based MLVA procedure over 83 strains from different Brucella species. The WGS-based MLVA approach detected 95.3% of all possible 1,328 hits (83 strains×16 loci) and showed an agreement rate with the PCR-based MLVA procedure of 96.4% for MLVA-16. According to our dataset, we suggest the use of a minimal depth of coverage of ~50x and a maximum number of ~200 contigs as guiding “boundaries” for the future application of the script. In conclusion, the evaluated script seems to be a very useful and robust tool for the in silico determination of MLVA profiles of Brucella strains, allowing retrospective and prospective molecular epidemiological studies, which are important for maintaining an active epidemiological surveillance of brucellosis.

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