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.
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.
Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.
Project description:The goal of this study was to find the differentially expressed circRNAs/linear RNA in AKI mice model compared to normal mice. We established cisplatin-induced AKI mice models and then extracted RNAs from isolated renal tubular tissues for Next Generation Sequencing(NGS) at different time points during early stage of AKI. CircRNA library was constructed by NEB Next®Ultra™ small RNA Sample Library Prep Kit for Illumina®. NGS was performed by using Illumina HiSeq 2500 Genome Sequencers.The original image data file was transformed into Raw Data by Base Calling. Clean Data was obtained by removing reads that containing joints and more than 5% N (undetermined base information). Mapped Reads were obtained by sequence alignment between Clean Reads and reference genome sequenced using BWA software package. CIRI software was used to predict circRNAs. Finally, we identified 2162 circRNAs and our study represents the first detailed analysis of AKI mice circRNA transcriptomes, which provide a framework for investigations of circRNAs expression profiles in AKI
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived PG and their healthy progenitor lines transcriptome profiling (RNA-seq) to proteomic methods (iTRAQ) and to evaluate these protocols for optimal high-throughput data analysis Methods: The raw RNA-Seq reads for each sample were aligned to the reference human genome browser (GRCh38.p12 assembly) using Bowtie2 and Tophat2. Results: An average of 23 million paired-end 100-bp reads was obtained per sample. After alignment, raw sequence read depths were converted to estimate transcript abundance measured as fragments per kilobase of exons per million (FPKM), and the cuffinks of differentially expressed genes and transcripts were calculate with Cuffdidd. Conclusions: Our study represents a detailed analysis of human PG lines transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell pathological line. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
Project description:A cDNA library was constructed by Novogene (CA, USA) using a Small RNA Sample Pre Kit, and Illumina sequencing was conducted according to company workflow, using 20 million reads. Raw data were filtered for quality as determined by reads with a quality score > 5, reads containing N < 10%, no 5' primer contaminants, and reads with a 3' primer and insert tag. The 3' primer sequence was trimmed and reads with a poly A/T/G/C were removed
Project description:Purpose: In order to understand the functional significance of sperm transcriptome in stallion fertility, the aim of this study was to generate a detailed body of knowledge about the sperm RNA profile that defines a normal fertile stallion. Methods: The 50 bp single-end ABI SOLiD raw reads were directly aligned with the horse reference sequence EcuCab2 using ABI aligner software (NovoalignCS version 1.00.09, novocraft.com) which uses multiple indexes in the reference genome, identifies candidate alignment locations for each primary read, and allows completion of the alignment. Results: Next generation sequencing (NGS) of total RNA from the sperm of two reproductively normal stallions generated about 70 million raw reads and more than 3 Gb of sequence per sample; over half of these aligned with the EcuCab2 reference genome. Altogether, 19,257 sequence tags with average coverage ?1 (normalized number of transcripts) were mapped in the horse genome. Conclusion: The sequence of stallion sperm transcriptome is an important foundation for the discovery of transcripts of known and novel genes, and non-coding RNAs, thus improving the annotation of the horse genome sequence draft and providing markers for evaluating stallion fertility. Reproductively fertile Stallion sperm transcriptome as revealed by RNA sequencing