scholarly journals Whole-Genome Sequence of a Pantoea sp. Strain Isolated from an Olive (Olea europaea L.) Knot

2019 ◽  
Vol 8 (42) ◽  
Author(s):  
Gabriela Vuletin Selak ◽  
Marina Raboteg ◽  
Audrey Dubost ◽  
Danis Abrouk ◽  
Katja Žanić ◽  
...  

Here, we present the total genome sequence of Pantoea sp. strain paga, a plant-associated bacterium isolated from knots present on olive trees grown on the Adriatic Coast. The genome size of Pantoea sp. paga is 5.08 Mb, with a G+C content of 54%. The genome contains 4,776 predicted coding DNA sequences (CDSs), including 70 tRNA genes and 1 ribosomal operon. Obtained genome sequence data will provide insight on the physiology, ecology, and evolution of Pantoea spp.

Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci

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


Data in Brief ◽  
2020 ◽  
Vol 33 ◽  
pp. 106416
Author(s):  
Asset Daniyarov ◽  
Askhat Molkenov ◽  
Saule Rakhimova ◽  
Ainur Akhmetova ◽  
Zhannur Nurkina ◽  
...  

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Lynsey K. Whitacre ◽  
Jesse L. Hoff ◽  
Robert D. Schnabel ◽  
Sara Albarella ◽  
Francesca Ciotola ◽  
...  

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 25-25
Author(s):  
Muhammad Yasir Nawaz ◽  
Rodrigo Pelicioni Savegnago ◽  
Cedric Gondro

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.


BMC Genomics ◽  
2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Shuto Hayashi ◽  
Rui Yamaguchi ◽  
Shinichi Mizuno ◽  
Mitsuhiro Komura ◽  
Satoru Miyano ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shashi Sharma ◽  
Paban Kumar Dash ◽  
Sushil Kumar Sharma ◽  
Ambuj Srivastava ◽  
Jyoti S. Kumar ◽  
...  

AbstractCOVID-19 has emerged as global pandemic with largest damage to the public health, economy and human psyche.The genome sequence data obtained during the ongoing pandemic are valuable to understand the virus evolutionary patterns and spread across the globe. Increased availability of genome information of circulating SARS-CoV-2 strains in India will enable the scientific community to understand the emergence of new variants and their impact on human health. The first case of COVID-19 was detected in Chambal region of Madhya Pradesh state in mid of March 2020 followed by multiple introduction events and expansion of cases within next three months. More than 5000 COVID-19 suspected samples referred to Defence Research and Development Establishment, Gwalior, Madhya Pradesh were analyzed during the nation -wide lockdown and unlock period. A total of 136 cases were found positive over a span of three months that included virus introduction to the region and its further spread. Whole genome sequences employing Oxford nanopore technology were generated for 26 SARS-CoV-2 circulating in 10 different districts in Madhya Pradesh state of India. This period witnessed index cases with multiple travel histories responsible for introduction of COVID-19 followed by remarkable expansion of virus. The genome wide substitutions including in important viral proteins were identified. The detailed phylogenetic analysis revealed the circulating SARS-CoV-2 clustered in multiple clades including A2a, A4 and B. The cluster-wise segregation was observed, suggesting multiple introduction links and subsequent evolution of virus in the region. This is the first comprehensive whole genome sequence analysis from central India, which revealed the emergence and evolution of SARS-CoV-2 during thenation-wide lockdown and unlock.


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