Project description:In the present study, a quantitative proteomic approach was used to analyse and compare the proteome in horns from endangered species (rhinoceros, Saiga antelope, and Tibetan antelope) and common species (yak, water buffalo, and goat) based on the isobaric tag for relative and absolute quantification (iTRAQ) techniques. In total, 591 proteins were identified, and 321 were quantified and categorised based on molecular function, cellular component, and biological process. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) results based on differences in the amount of protein identified three major clusters, and proteins including transglutaminase, desmocollin, and elongation factors were selected as trait components from proteomic patterns of horn samples from different species. Quantitative proteomic analysis-based strategies can therefore provide further evidence for sustainable alternatives to replace animal horn from threatened species.
2022-03-02 | PXD010901 | Pride
Project description:ITS gene sequencing of Domestic yak, Tibetan antelope, and Tibetan wild ass
| PRJNA1131646 | ENA
Project description:16s rRNA gene sequencing of Domestic yak, Tibetan antelope, and Tibetan wild ass
| PRJNA1131634 | ENA
Project description:metagenome data of sable antelope feces
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.
