Genome of Serratia plymuthica UBCF_13, Insight into diverse unique traits

Background: Whole genome sequencing is become an essential tool to explore potential of microorganism and evolutionary study. The Serratia plymuthica UBCF_13 is one of phylloplane associated plant bacteria showing antifungal activity. For that reason, its complete genome information is necessary to enhance its potential as biocontrol against plant pathogenic fungal. Here, we report the genome sequence of Serratia plymuthica UBCF_13 to understand the molecular mechanism regarding its biocontrol ability. Methods: Continuous short reads were attained from Illumina sequencing runs and reads 150 bp were merged into a single dataset. Pan-genome based method was used to identify core-genome of S. plymuthica species and unique gene in UBCF_13. Results: Assambled Illumina reads of S. plymuthica strain UBCF_13 genome was produced a 5.46 Mb circular genome sequence. It was found 3321 genes belong to the core-genome sheared by the 18 strains evaluated. The UBCF_13 genome harbor 485 unique genes, where 300 of them only can be found in this strain Conclusions: The sequence of UBCF_13 genome sequence data will contribute for further exploration of the potential of S. plymuthica UBCF_13 as bacteria producing antibiotic.

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Defining and Evaluating a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Listeria monocytogenes

Journal of Clinical Microbiology ◽

10.1128/jcm.01193-15 ◽

2015 ◽

Vol 53 (9) ◽

pp. 2869-2876 ◽

Cited By ~ 143

Author(s):

Werner Ruppitsch ◽

Ariane Pietzka ◽

Karola Prior ◽

Stefan Bletz ◽

Haizpea Lasa Fernandez ◽

...

Keyword(s):

Listeria Monocytogenes ◽

Genome Sequence ◽

Core Genome ◽

Target Genes ◽

Sequence Data ◽

Whole Genome Sequence ◽

Whole Genome ◽

Content Type ◽

Typing Scheme ◽

Reference Strains

Whole-genome sequencing (WGS) has emerged today as an ultimate typing tool to characterizeListeria monocytogenesoutbreaks. However, data analysis and interlaboratory comparability of WGS data are still challenging for most public health laboratories. Therefore, we have developed and evaluated a newL. monocytogenestyping scheme based on genome-wide gene-by-gene comparisons (core genome multilocus the sequence typing [cgMLST]) to allow for a unique typing nomenclature. Initially, we determined the breadth of theL. monocytogenespopulation based on MLST data with a Bayesian approach. Based on the genome sequence data of representative isolates for the whole population, cgMLST target genes were defined and reappraised with 67L. monocytogenesisolates from two outbreaks and serotype reference strains. The Bayesian population analysis generated fiveL. monocytogenesgroups. Using all available NCBI RefSeq genomes (n= 36) and six additionally sequenced strains, all genetic groups were covered. Pairwise comparisons of these 42 genome sequences resulted in 1,701 cgMLST targets present in all 42 genomes with 100% overlap and ≥90% sequence similarity. Overall, ≥99.1% of the cgMLST targets were present in 67 outbreak and serotype reference strains, underlining the representativeness of the cgMLST scheme. Moreover, cgMLST enabled clustering of outbreak isolates with ≤10 alleles difference and unambiguous separation from unrelated outgroup isolates. In conclusion, the novel cgMLST scheme not only improves outbreak investigations but also enables, due to the availability of the automatically curated cgMLST nomenclature, interlaboratory exchange of data that are crucial, especially for rapid responses during transsectorial outbreaks.

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Household Clustering of Escherichia coli Sequence Type 131 Clinical and Fecal Isolates According to Whole Genome Sequence Analysis

Open Forum Infectious Diseases ◽

10.1093/ofid/ofw129 ◽

2016 ◽

Vol 3 (3) ◽

Cited By ~ 31

Author(s):

James R. Johnson ◽

Gregg Davis ◽

Connie Clabots ◽

Brian D. Johnston ◽

Stephen Porter ◽

...

Keyword(s):

Escherichia Coli ◽

Genome Sequence ◽

Core Genome ◽

Sequence Type ◽

Whole Genome Sequence ◽

Whole Genome ◽

The Core ◽

Genome Phylogeny ◽

Genome Level ◽

Repeated Infections

Abstract Background. Within-household sharing of strains from the resistance-associated H30R1 and H30Rx subclones of Escherichia coli sequence type 131 (ST131) has been inferred based on conventional typing data, but it has been assessed minimally using whole genome sequence (WGS) analysis. Methods. Thirty-three clinical and fecal isolates of ST131-H30R1 and ST131-H30Rx, from 20 humans and pets in 6 households, underwent WGS analysis for comparison with 52 published ST131 genomes. Phylogenetic relationships were inferred using a bootstrapped maximum likelihood tree based on core genome sequence polymorphisms. Accessory traits were compared between phylogenetically similar isolates. Results. In the WGS-based phylogeny, isolates clustered strictly by household, in clades that were distributed widely across the phylogeny, interspersed between H30R1 and H30Rx comparison genomes. For only 1 household did the core genome phylogeny place epidemiologically unlinked isolates together with household isolates, but even there multiple differences in accessory genome content clearly differentiated these 2 groups. The core genome phylogeny supported within-household strain sharing, fecal-urethral urinary tract infection pathogenesis (with the entire household potentially providing the fecal reservoir), and instances of host-specific microevolution. In 1 instance, the household's index strain persisted for 6 years before causing a new infection in a different household member. Conclusions. Within-household sharing of E coli ST131 strains was confirmed extensively at the genome level, as was long-term colonization and repeated infections due to an ST131-H30Rx strain. Future efforts toward surveillance and decolonization may need to address not just the affected patient but also other human and animal household members.

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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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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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