Taxonomic revision of Harveyi clade bacteria (family Vibrionaceae) based on analysis of whole genome sequences

Use of inadequate methods for classification of bacteria in the so-called Harveyi clade (family Vibrionaceae, Gammaproteobacteria) has led to incorrect assignment of strains and proliferation of synonymous species. In order to resolve taxonomic ambiguities within the Harveyi clade and to test usefulness of whole genome sequence data for classification of Vibrionaceae, draft genome sequences of 12 strains were determined and analysed. The sequencing included type strains of seven species: Vibrio sagamiensis NBRC 104589T, Vibrio azureus NBRC 104587T, Vibrio harveyi NBRC 15634T, Vibrio rotiferianus LMG 21460T, Vibrio campbellii NBRC 15631T, Vibrio jasicida LMG 25398T, and Vibrio owensii LMG 25443T. Draft genome sequences of strain LMG 25430, previously designated the type strain of [Vibrio communis], and two strains (MWB 21 and 090810c) from the ‘beijerinckii’ lineage were also determined. Whole genomes of two additional strains (ATCC 25919 and 200612B) that previously could not be assigned to any Harveyi clade species were also sequenced. Analysis of the genome sequence data revealed a clear case of synonymy between V. owensii and [V. communis], confirming an earlier proposal to synonymize both species. Both strains from the ‘beijerinckii’ lineage were classified as V. jasicida, while the strains ATCC 25919 and 200612B were classified as V. owensii and V. campbellii, respectively. We also found that two strains, AND4 and Ex25, are closely related to Harveyi clade bacteria, but could not be assigned to any species of the family Vibrionaceae. The use of whole genome sequence data for the taxonomic classification of the Harveyi clade bacteria and other members of the family Vibrionaceae is also discussed.

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Faculty Opinions recommendation of Optimal algorithms for haplotype assembly from whole-genome sequence data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.13339986.14707085 ◽

2011 ◽

Author(s):

Alejandro Schaffer

Keyword(s):

Genome Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Whole Genome ◽

Optimal Algorithms ◽

Genome Sequence Data ◽

Haplotype Assembly

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TIGER: inferring DNA replication timing from whole-genome sequence data

Bioinformatics ◽

10.1093/bioinformatics/btab166 ◽

2021 ◽

Cited By ~ 1

Author(s):

Amnon Koren ◽

Dashiell J Massey ◽

Alexa N Bracci

Keyword(s):

Dna Replication ◽

Genome Sequence ◽

Genomic Dna ◽

Sequence Data ◽

Replication Timing ◽

Whole Genome Sequence ◽

Supplementary Information ◽

Whole Genome ◽

Genome Sequence Data ◽

Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

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Whole genome sequence data of Bacillus australimaris strain B28A, isolated from Marine Water in India

Data in Brief ◽

10.1016/j.dib.2021.107240 ◽

2021 ◽

pp. 107240

Author(s):

Wael Ali Mohammed Hadi ◽

Boby T Edwin ◽

A Jayakumaran Nair

Keyword(s):

Genome Sequence ◽

Sequence Data ◽

Marine Water ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genome Sequence Data

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Whole genome sequence data of Mycobacterium tuberculosis XDR strain, isolated from patient in Kazakhstan

Data in Brief ◽

10.1016/j.dib.2020.106416 ◽

2020 ◽

Vol 33 ◽

pp. 106416

Author(s):

Asset Daniyarov ◽

Askhat Molkenov ◽

Saule Rakhimova ◽

Ainur Akhmetova ◽

Zhannur Nurkina ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Genome Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genome Sequence Data

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Elucidating the genetic basis of an oligogenic birth defect using whole genome sequence data in a non-model organism, Bubalus bubalis

Scientific Reports ◽

10.1038/srep39719 ◽

2017 ◽

Vol 7 (1) ◽

Cited By ~ 10

Author(s):

Lynsey K. Whitacre ◽

Jesse L. Hoff ◽

Robert D. Schnabel ◽

Sara Albarella ◽

Francesca Ciotola ◽

...

Keyword(s):

Genome Sequence ◽

Birth Defect ◽

Genetic Basis ◽

Sequence Data ◽

Model Organism ◽

Bubalus Bubalis ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genome Sequence Data

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Whole genome characterization of strains belonging to the Ralstonia solanacearum species complex and in silico analysis of TaqMan assays for detection in this heterogenous species complex

European Journal of Plant Pathology ◽

10.1007/s10658-020-02190-8 ◽

2021 ◽

Author(s):

Viola Kurm ◽

Ilse Houwers ◽

Claudia E. Coipan ◽

Peter Bonants ◽

Cees Waalwijk ◽

...

Keyword(s):

Ralstonia Solanacearum ◽

In Silico ◽

Species Complex ◽

Sequence Data ◽

In Silico Analysis ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genome Sequences ◽

Pcr Assays

AbstractIdentification and classification of members of the Ralstonia solanacearum species complex (RSSC) is challenging due to the heterogeneity of this complex. Whole genome sequence data of 225 strains were used to classify strains based on average nucleotide identity (ANI) and multilocus sequence analysis (MLSA). Based on the ANI score (>95%), 191 out of 192(99.5%) RSSC strains could be grouped into the three species R. solanacearum, R. pseudosolanacearum, and R. syzygii, and into the four phylotypes within the RSSC (I,II, III, and IV). R. solanacearum phylotype II could be split in two groups (IIA and IIB), from which IIB clustered in three subgroups (IIBa, IIBb and IIBc). This division by ANI was in accordance with MLSA. The IIB subgroups found by ANI and MLSA also differed in the number of SNPs in the primer and probe sites of various assays. An in-silico analysis of eight TaqMan and 11 conventional PCR assays was performed using the whole genome sequences. Based on this analysis several cases of potential false positives or false negatives can be expected upon the use of these assays for their intended target organisms. Two TaqMan assays and two PCR assays targeting the 16S rDNA sequence should be able to detect all phylotypes of the RSSC. We conclude that the increasing availability of whole genome sequences is not only useful for classification of strains, but also shows potential for selection and evaluation of clade specific nucleic acid-based amplification methods within the RSSC.

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46 Footprints of Selection in Angus and Hanwoo Beef Cattle Using Imputed Whole Genome Sequence Data

Journal of Animal Science ◽

10.1093/jas/skab235.042 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 25-25

Author(s):

Muhammad Yasir Nawaz ◽

Rodrigo Pelicioni Savegnago ◽

Cedric Gondro

Keyword(s):

Beef Cattle ◽

Genome Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Fixation Index ◽

Whole Genome ◽

Extended Haplotype Homozygosity ◽

Extended Haplotype ◽

Genome Sequence Data ◽

Genomic Regions

Abstract In this study, we detected genome wide footprints of selection in Hanwoo and Angus beef cattle using different allele frequency and haplotype-based methods based on imputed whole genome sequence data. Our dataset included 13,202 Angus and 10,437 Hanwoo animals with 10,057,633 and 13,241,550 imputed SNPs, respectively. A subset of data with 6,873,624 common SNPs between the two populations was used to estimate signatures of selection parameters, both within (runs of homozygosity and extended haplotype homozygosity) and between (allele fixation index, extended haplotype homozygosity) the breeds in order to infer evidence of selection. We observed that correlations between various measures of selection ranged between 0.01 to 0.42. Assuming these parameters were complementary to each other, we combined them into a composite selection signal to identify regions under selection in both beef breeds. The composite signal was based on the average of fractional ranks of individual selection measures for every SNP. We identified some selection signatures that were common between the breeds while others were independent. We also observed that more genomic regions were selected in Angus as compared to Hanwoo. Candidate genes within significant genomic regions may help explain mechanisms of adaptation, domestication history and loci for important traits in Angus and Hanwoo cattle. In the future, we will use the top SNPs under selection for genomic prediction of carcass traits in both breeds.

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