Genomics DataPub Date : 2017-06-01Epub Date: 2017-02-28DOI: 10.1016/j.gdata.2017.02.010
Subhadipa Sengupta , Sayak Ganguli , Pankaj K Singh
{"title":"Metagenome analysis of the root endophytic microbial community of Indian rice (O. sativa L.)","authors":"Subhadipa Sengupta , Sayak Ganguli , Pankaj K Singh","doi":"10.1016/j.gdata.2017.02.010","DOIUrl":"10.1016/j.gdata.2017.02.010","url":null,"abstract":"<div><p>This study reports the root endophytic microbial community profile in rice (<em>Oryza sativa</em> L.), the largest food crop of Asia, using 16S rRNA gene amplicon sequencing. Metagenome of OS01 and OS04 consisted of 11,17,900 sequences with 300<!--> <!-->Mbp size and average 55.6% G<!--> <!-->+<!--> <!-->C content. Data of this study are available at NCBI Bioproject (PRJNA360379). The taxonomic analysis of 843 OTU's showed that the sequences belonged to four major phyla revealing dominance of Proteobacteria, Firmicutes, Cyanobacteria and Actinobacteria. Results reveal the dominance of <em>Bacillus</em> as major endophytic genera in rice roots, probably playing a key role in Nitrogen fixation.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 41-43"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.02.010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34809367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genomics DataPub Date : 2017-06-01Epub Date: 2017-03-03DOI: 10.1016/j.gdata.2017.03.001
Ramprasad Kuncham , Thiyagarajan Sivaprakasam , Puneeth Kumar R , Sreenath P , Ravi Nayak , Tha. Thayumanavan , Gopireddy V. Subba Reddy
{"title":"Bacterial fauna associating with chironomid larvae from lakes of Bengaluru city, India - A 16s rRNA gene based identification","authors":"Ramprasad Kuncham , Thiyagarajan Sivaprakasam , Puneeth Kumar R , Sreenath P , Ravi Nayak , Tha. Thayumanavan , Gopireddy V. Subba Reddy","doi":"10.1016/j.gdata.2017.03.001","DOIUrl":"10.1016/j.gdata.2017.03.001","url":null,"abstract":"<div><p>Chironomid larvae that inhabit in aquatic sediments play an important role as vector for bacterial pathogens. Its life cycle consists of four stages i.e. eggs, larvae, pupae and adult. In the present study we identified bacterial species associated with whole larvae of chironomids from 11 lake sediments of Bangalore region using 16s rRNA gene Sanger sequencing. We found that larvae from all lake sediments associated with bacterial species which include key pathogens. Totally we identified 65 bacterial isolates and obtained GenBank accession numbers (KX980423 - KX980487). Phylogenetic tree constructed using MEGA 7 software and tree analysis highlight the predominant bacterial community associated with larvae which include <em>Enterobacteriaceae</em> (43.08%; 28 isolates) and <em>Aeromonas</em> (24.62%; 16 isolates), <em>Shewanella</em>, <em>Delftia</em>, <em>Bacillus</em> (6.15%; 4 isolates each), <em>Pseudomonas</em> (4.62%; 3 isolates) and <em>Exiguobacterium</em> (3.08%; 2 isolates). Current findings state that among bacterial population <em>Aeromonas</em>, <em>Enterobacter</em> and <em>Escherichia</em> with serotypes are commonly associated with larvae in maximum lake points. In other hand <em>Vibrio</em>, <em>Pseudomonas</em>, <em>Klebsiella</em>, <em>Shigella</em>, <em>Bacillus</em>, and other bacterial species were identified moderately in all lakes. Interestingly, we identified first time <em>Shigella</em> Gram negative, rod shaped pathogenic organism of <em>Enterobacteriaceae</em> and <em>Rheinheimera</em> Gram negative, rod shaped organism associating chironomid larvae.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 44-48"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.03.001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34833192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genomics DataPub Date : 2017-06-01Epub Date: 2017-02-05DOI: 10.1016/j.gdata.2017.02.002
Ichiro Akagi , Osamu Ishibashi
{"title":"RNA-Seq analysis of human cell lines established from normal and neoplastic esophageal squamous epithelium","authors":"Ichiro Akagi , Osamu Ishibashi","doi":"10.1016/j.gdata.2017.02.002","DOIUrl":"10.1016/j.gdata.2017.02.002","url":null,"abstract":"<div><p>Esophageal cancer (EC) is the eighth most common cancer globally in 2012 and predominantly occurs in the man (Enzinger and Mayer, 2003; Conteduca et al., 2012). EC is classified mainly into two types, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma, accounting for 60–70% and 20–30% of all EC cases, respectively. In a previous statistical study it was reported that the numbers of new EC cases and EC-related deaths worldwide in 2008 were estimated to be 482,300 and 406,800, respectively (Jemal et al., 2011). This high mortality rate is largely due to the characteristics of EC such as frequent distant/local metastasis and poor subjective symptoms leading to difficulty with early diagnosis. Patients affected with EC diagnosed at late stages mostly have unsatisfactory prognosis, even though various therapeutic options are available. Therefore, there is an urgent need to develop effective methods that enable the early detection of EC (Orringer, 1993), prompting us to search for novel biomarkers for EC. Here, we provide datasets from RNA-Seq analysis of Het-1A, a normal human esophageal squamous cell line (Stoner et al., 1991), and TE-1, TE-5, and TE-8, which are well-, poorly-, and moderately-differentiated ESCC-derived cell lines, respectively (Nishihira et al., 1993). The raw data of these experiments have been deposited at DNA Data Bank of Japan (DDBJ) under the accession IDs DRR084199, DRR084200, DRR084201, and DRR084202.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 4-6"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.02.002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48071930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Draft genome sequence of Bacillus oleronius DSM 9356 isolated from the termite Reticulitermes santonensis","authors":"Rodney Owusu-Darko , Mushal Allam , Senzo Mtshali , Arshad Ismail , Elna Maria Buys","doi":"10.1016/j.gdata.2017.03.005","DOIUrl":"10.1016/j.gdata.2017.03.005","url":null,"abstract":"<div><p><em>Bacillus oleronius</em> strain DSM 9356 isolated from the termite <em>Reticulitermes santonensis</em> was sequenced to gain insights in relation to its closest phylogenetic neighbor <em>Bacillus sporothermodurans</em>. The draft genome of strain DSM 9356 contains 5,083,966<!--> <!-->bp with an estimated G<!--> <!-->+<!--> <!-->C content of 35%, 4899 protein-coding genes, 116 tRNAs and 18 rRNAs. The RAST annotation assigned these genes into 462 subsystems, with the maximum number of genes associated with amino acids and derivatives metabolism (14.84%), followed by carbohydrates (13.89%) and protein metabolism subsystems (9.10%). The draft genome sequence and annotation has been deposited at NCBI under the accession number MTLA00000000.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 76-78"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.03.005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34892889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genomics DataPub Date : 2017-06-01Epub Date: 2017-03-29DOI: 10.1016/j.gdata.2017.03.009
Vijay Lakhujani, Chandan Badapanda
{"title":"prepare_taxa_charts.py: A Python program to automate generation of publication ready taxonomic pie chart images from QIIME","authors":"Vijay Lakhujani, Chandan Badapanda","doi":"10.1016/j.gdata.2017.03.009","DOIUrl":"10.1016/j.gdata.2017.03.009","url":null,"abstract":"<div><p>QIIME (Quantitative Insights Into Microbial Ecology) is one of the most popular open-source bioinformatics suite for performing metagenome, 16S rRNA amplicon and Internal Transcribed Spacer (ITS) data analysis. Although, it is very comprehensive and powerful tool, it lacks a method to provide publication ready taxonomic pie charts. The script <em>plot_taxa_summary</em>.<em>py</em> bundled with QIIME generate a html file and a folder containing taxonomic pie chart and legend as separate images. The images have randomly generated alphanumeric names. Therefore, it is difficult to associate the pie chart with the legend and the corresponding sample identifier. Even if the option to have the legend within the html file is selected while executing <em>plot_taxa_summary</em>.<em>py</em>, it is very tedious to crop a complete image (having both the pie chart and the legend) due to unequal image sizes. It requires a lot of time to manually prepare the pie charts for multiple samples for publication purpose. Moreover, there are chances of error while identifying the pie chart and legend pair due to random alphanumeric names of the images. To bypass all these bottlenecks and make this process efficient, we have developed a python based program, <em>prepare_taxa_charts</em>.<em>py</em>, to automate the renaming, cropping and merging of taxonomic pie chart and corresponding legend image into a single, good quality publication ready image. This program not only augments the functionality of <em>plot_taxa_summary</em>.<em>py</em> but is also very fast in terms of CPU time and user friendly.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 97-101"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.03.009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34913532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genomics DataPub Date : 2017-06-01Epub Date: 2017-03-21DOI: 10.1016/j.gdata.2017.03.004
Shih Keng Loong , Kim-Kee Tan , Syuhaida Sulaiman , Pooi Fong Wong , Sazaly AbuBakar
{"title":"Draft genome of Bordetella pseudohinzii BH370 isolated from trachea and lung tissues of a laboratory mouse","authors":"Shih Keng Loong , Kim-Kee Tan , Syuhaida Sulaiman , Pooi Fong Wong , Sazaly AbuBakar","doi":"10.1016/j.gdata.2017.03.004","DOIUrl":"10.1016/j.gdata.2017.03.004","url":null,"abstract":"<div><p>In this study, we present the draft genome sequence of <em>B. pseudohinzii</em> BH370 recovered from the trachea and lung tissues of an ICR mouse in Malaysia. The genome consists of 4,474,040<!--> <!-->bp with a GC content of 66.4%. Annotation using RAST algorithm displayed 5119 protein encoding and 52 RNA genes. The CRISPR-<em>cas</em> genomic sequences previously reported in <em>B. pseudohinzii</em> were identified. The nucleotide sequences of BH370 was deposited into the European Nucleotide Archive under the genome assembly accession number FPJN01000000.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 69-70"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.03.004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34887241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Gene expression in rat striatum following carbon monoxide poisoning","authors":"Shuichi Hara , Masamune Kobayash , Fumi Kuriiwa , Kunihiko Kurosaki , Hajime Mizukami","doi":"10.1016/j.gdata.2017.03.007","DOIUrl":"10.1016/j.gdata.2017.03.007","url":null,"abstract":"<div><p>Carbon monoxide (CO) poisoning causes brain damage, which is attenuated by treatment with hydrogen <span>[1]</span>, <span>[2]</span>, a scavenger selective to hydroxyl radical (<img>OH) [3]. This suggests a role of <img>OH in brain damage due to CO poisoning. Studies have shown strong enhancement of <img>OH production in rat striatum by severe CO poisoning with a blood carboxyhemoglobin (COHb) level ><!--> <!-->70% due to 3000<!--> <!-->ppm CO, but not less severe CO poisoning with a blood COHb level at approximately 50% due to 1000<!--> <!-->ppm CO [4]. Interestingly, 5% O<sub>2</sub> causes hypoxia comparable with that by 3000<!--> <!-->ppm CO and produces much less <sup>•</sup>OH than 3000<!--> <!-->ppm CO does [4]. In addition, cAMP production in parallel with <img>OH production <span>[5]</span> might contribute to <img>OH production <span>[6]</span>. It is likely that mechanisms other than hypoxia contribute to brain damage due to CO poisoning <span>[7]</span>. To search for the mechanisms, we examined the effects of 1000<!--> <!-->ppm CO, 3000<!--> <!-->ppm CO and 5% O<sub>2</sub> on gene expression in rat striatum. All array data have been deposited in the Gene Expression Omnibus (GEO) database under accession number GSE94780.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 74-75"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.03.007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34892888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genomics DataPub Date : 2017-06-01Epub Date: 2017-03-27DOI: 10.1016/j.gdata.2017.03.011
Yong Huang, Xiao Chan Gao, Jian Li Xiong, Hong Tao Ren, Xi Hong Sun
{"title":"Sequencing and de novo transcriptome assembly of the Chinese giant salamander (Andrias davidianus)","authors":"Yong Huang, Xiao Chan Gao, Jian Li Xiong, Hong Tao Ren, Xi Hong Sun","doi":"10.1016/j.gdata.2017.03.011","DOIUrl":"https://doi.org/10.1016/j.gdata.2017.03.011","url":null,"abstract":"<div><p>Next-generation technologies for determination of genomics and transcriptomics composition have a wide range of applications. <em>Andrias davidianus</em>, has become an endangered amphibian species of salamander endemic in China. However, there is a lack of the molecular information. In this study, we obtained the RNA-Seq data from a pool of <em>A. davidianus</em> tissue including spleen, liver, muscle, kidney, skin, testis, gut and heart using Illumina HiSeq 2500 platform. A total of 15,398,997,600<!--> <!-->bp were obtained, corresponding to 102,659,984 raw reads. A total of 102,659,984 reads were filtered after removing low-quality reads and trimming the adapter sequences. The Trinity program was used to de novo assemble 132,912 unigenes with an average length of 690<!--> <!-->bp and N50 of 1263<!--> <!-->bp. Unigenes were annotated through number of databases. These transcriptomic data of <em>A. davidianus</em> should open the door to molecular evolution studies based on the entire transcriptome or targeted genes of interest to sequence. The raw data in this study can be available in NCBI SRA database with accession number of SRP099564.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 109-110"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.03.011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92030635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genomics DataPub Date : 2017-06-01Epub Date: 2017-03-30DOI: 10.1016/j.gdata.2017.03.013
Saurav Das , Sudipta Sankar Bora , R.N.S. Yadav , Madhumita Barooah
{"title":"A metagenomic approach to decipher the indigenous microbial communities of arsenic contaminated groundwater of Assam","authors":"Saurav Das , Sudipta Sankar Bora , R.N.S. Yadav , Madhumita Barooah","doi":"10.1016/j.gdata.2017.03.013","DOIUrl":"10.1016/j.gdata.2017.03.013","url":null,"abstract":"<div><p>Metagenomic approach was used to understand the structural and functional diversity present in arsenic contaminated groundwater of the Ganges Brahmaputra Delta aquifer system. A metagene dataset (coded as TTGW1) of 89,171 sequences (totaling 125,449,864 base pairs) with an average length of 1406<!--> <!-->bps was annotated. About 74,478 sequences containing 101,948 predicted protein coding regions passed the quality control. Taxonomical classification revealed abundance of bacteria that accounted for 98.3% of the microbial population of the metagenome. Eukaryota had an abundance of 1.1% followed by archea that showed 0.4% abundance. In phylum based classification, Proteobacteria was dominant (62.6%) followed by Bacteroidetes (11.7%), Planctomycetes (7.7%), Verrucomicrobia (5.6%), Actinobacteria (3.7%) and Firmicutes (1.9%). The Clusters of Orthologous Groups (COGs) analysis indicated that the protein regulating the metabolic functions constituted a high percentage (18,199 reads; 39.3%) of the whole metagenome followed by the proteins regulating the cellular processes (22.3%). About 0.07% sequences of the whole metagenome were related to genes coding for arsenic resistant mechanisms. Nearly 50% sequences of these coded for the arsenate reductase enzyme (EC. 1.20.4.1), the dominant enzyme of <em>ars</em> operon. Proteins associated with iron acquisition and metabolism were coded by 2% of the metagenome as revealed through SEED analysis. Our study reveals the microbial diversity and provides an insight into the functional aspect of the genes that might play crucial role in arsenic geocycle in contaminated ground water of Assam.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 89-96"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.03.013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34913592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genomics DataPub Date : 2017-06-01Epub Date: 2017-05-05DOI: 10.1016/j.gdata.2017.04.003
Mohd Razik Midin , Kok-Keong Loke , Maria Madon , Mohd Shukor Nordin , Hoe-Han Goh , Normah Mohd Noor
{"title":"SMRT sequencing data for Garcinia mangostana L. variety Mesta","authors":"Mohd Razik Midin , Kok-Keong Loke , Maria Madon , Mohd Shukor Nordin , Hoe-Han Goh , Normah Mohd Noor","doi":"10.1016/j.gdata.2017.04.003","DOIUrl":"https://doi.org/10.1016/j.gdata.2017.04.003","url":null,"abstract":"<div><p>The “Queen of Fruits” mangosteen (<em>Garcinia mangostana</em> L.) produces commercially important fruits with desirable taste of flesh and pericarp rich in xanthones with medicinal properties. To date, only limited knowledge is available on the cytogenetics and genome sequences of a common variety of mangosteen (Abu Bakar et al., 2016 <span>[1]</span>). Here, we report the first single-molecule real-time (SMRT) sequencing data from whole genome sequencing of mangosteen of Mesta variety. Raw reads of the SMRT sequencing project can be obtained from SRA database with the accession numbers SRX2718652 until SRX2718659.</p></div>","PeriodicalId":56340,"journal":{"name":"Genomics Data","volume":"12 ","pages":"Pages 134-135"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.gdata.2017.04.003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92077598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}