Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1311753 | ENA |
REPOSITORIES: ENA
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Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9189 | biostudies-arrayexpress
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9191 | biostudies-arrayexpress
Project description:The mammary gland redeveloped to the pre-pregnancy state during involution, which shows that the mammary cells have the characteristics of remodeling. The rapidity and degree of mammary gland involution are different between mice and dairy livestock (dairy cows and dairy goats). However, the molecular genetic mechanism of miRNA in involution and remodeling of goat mammary gland has not yet been clarified. Therefore, this study carried out the RNA-sequencing of nonlactating mammary gland tissue of dairy goats in order to reveal the transcriptome characteristics of miRNA in nonlactating mammary tissues and clarify the molecular genetic mechanism of miRNA in mammary cell involution and remodeling.
2023-10-01 | GSE243232 | GEO
Project description:We applied metagenomic shotgun sequencing to investigate the effects of ZEA exposure on the change of mouse gut microbiota composition and function.
2019-11-09 | GSE140149 | GEO
Project description:The mammary gland redeveloped to the pre-pregnancy state during involution, which shows that the mammary cells have the characteristics of remodeling. The rapidity and degree of mammary gland involution are different between mice and dairy livestock (dairy cows and dairy goats). However, the molecular genetic mechanism of involution and remodeling of goat mammary gland has not yet been clarified. Therefore, this study carried out the RNA-sequencing of nonlactating mammary gland tissue of dairy goats in order to reveal the transcriptome characteristics of nonlactating mammary tissues and clarify the molecular genetic mechanism of mammary cell involution and remodeling.
2021-10-22 | GSE185981 | GEO
Project description:Five healthy Laoshan dairy goats (four years old, third lactation) from Qingdao Laoshan dairy goat primary farm (Shandong Province, China) were used. The mammary gland samples were collected surgically after general anaesthesia using Xylazine Hydrochloride injection solution (Huamu Animal Health Products Co., Ltd. China) at corresponding lactation stage, including early, peak and late lactations.
2020-02-22 | GSE135930 | GEO
Project description:Staphylococcus aureus is recognized worldwide as a major pathogen causing clinical or subclinical intramammary infections in all the dairy species (sheep, goats and cows). The present study was designed to comparatively investigate 65 S. aureus isolates recovered from dairy sheep and S. aureus suclinical mastitis from cows (n=21) and goats (n=22), for the presence of 190 putative virulence determinants with a single-dye DNA microarray and PCR. The probes (65 mer) were mainly designed from the S. aureus Mu50. The extracted DNA of each strain was labelled with Cy5. The microarray results were validated with PCR.The genomic comparative study with the DNA microarrays showed lineage and species specificity genes leading to the host-specific pathogenic traits of S. aureus in dairy species.
2008-07-01 | E-TABM-288 | biostudies-arrayexpress
Project description:Alpine goat phenotypes for quality components have been routinely recorded for many years and deposited in the Council on Dairy Cattle Breeding (CDCB) repository. The data collected were used to conduct an exploratory genome-wide association study (GWAS) from 72 female Alpine goats originating from locations throughout the U.S. Genotypes were identified with the Illumina Goat 50K single nucleotide polymorphisms (SNP) Beadchip. The analysis used a polygenic model where the dropping criteria was the Call Rate ≥ 0.95. The initial dataset was composed of ~ 60,000 rows of SNPs, 21 columns of phenotypic traits and composed of 53,384 scaffolds containing other informative data points used for genomic predictive power. Phenotypic association with the 50KBeadchip revealed 26,074 reads of candidate genes. These candidate genes segregated as separate novel SNPs and were identified as statistically significant regions for genome and chromosome level trait associations. Candidate genes associated differently for each of the following phenotypic traits: test day milk yield (13,469 candidate genes), test day protein yield (25,690 candidate genes), test day fat yield (25,690 candidate genes), percentage protein (25,690 candidate genes), percentage fat (25,690 candidate genes), and percentage lactose content (25,690 candidate genes). The outcome of this study supports elucidation of novel genes that are important for livestock species in association to key phenotypic traits. Validation towards the development of marker-based selection that provide precision breeding methods will thereby increase breeding value. Specific aims: 1) Improve on contributions to the phenotype repository, the Council on Dairy Cattle Breeding (CDCB) for milk quality traits that are economically important for goat production while developing a corresponding DNA repository for each of the animals with significant genotype-phenotype associations. 2) Develop genomic prediction tools and provide data for a better database for tools to predict phenotypic traits by initially using the high density Goat50KSNP BeadChip for the selection of more specific SNPs associated with select signatures (genes) for phenotypic traits in American Alpine goats. 3) To establish whether a low number of goat subjects (< 300 goats) will provide statistically significant (p < 0.05) predictive capabilities for desired breeding traits in American Alpine dairy goats.
2020-02-19 | GSE145419 | GEO