De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

http://genomebio.org/wp-content/uploads/2013/08/Haas_2013_Nature_Protocols-1.pdf

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

Since the completion of the human genome project in 2003, extraordinary progress has been made in genome sequencing technologies, which has led to a decreased cost per megabase and an increase in the number and diversity of sequenced genomes. An astonishing complexity of genome architecture has been revealed, bringing these sequencing technologies to even greater advancements. Some approaches maximize the number of bases sequenced in the least amount of time, generating a wealth of data that can be used to understand increasingly complex phenotypes. Alternatively, other approaches now aim to sequence longer contiguous pieces of DNA, which are essential for resolving structurally complex regions. These and other strategies are providing researchers and clinicians a variety of tools to probe genomes in greater depth, leading to an enhanced understanding of how genome sequence variants underlie phenotype and disease.

Coming of age: ten years of next-generation sequencing technologies

Relation between the gut microbiota and human health is being increasingly recognised It is now well established that a healthy gut flora is largely responsible for overall health of the host The normal human gut microbiota comprises of two major phyla, namely Bacteroidetes and Firmicutes Though the gut microbiota in an infant appears haphazard, it starts resembling the adult flora by the age of 3 years Nevertheless, there exist temporal and spatial variations in the microbial distribution from esophagus to the rectum all along the individual's life span Developments in genome sequencing technologies and bioinformatics have now enabled scientists to study these microorganisms and their function and microbe-host interactions in an elaborate manner both in health and disease The normal gut microbiota imparts specific function in host nutrient metabolism, xenobiotic and drug metabolism, maintenance of structural integrity of the gut mucosal barrier, immunomodulation, and protection against pathogens Several factors play a role in shaping the normal gut microbiota They include (1) the mode of delivery (vaginal or caesarean); (2) diet during infancy (breast milk or formula feeds) and adulthood (vegan based or meat based); and (3) use of antibiotics or antibiotic like molecules that are derived from the environment or the gut commensal community A major concern of antibiotic use is the long-term alteration of the normal healthy gut microbiota and horizontal transfer of resistance genes that could result in reservoir of organisms with a multidrug resistant gene pool

Role of the normal gut microbiota

PacBio Sequencing and Its Applications.

Ten years of next-generation sequencing technology.

With fast development and wide applications of next-generation sequencing (NGS) technologies, genomic sequence information is within reach to aid the achievement of goals to decode life mysteries, make better crops, detect pathogens, and improve life qualities. NGS systems are typically represented by SOLiD/Ion Torrent PGM from Life Sciences, Genome Analyzer/HiSeq 2000/MiSeq from Illumina, and GS FLX Titanium/GS Junior from Roche. Beijing Genomics Institute (BGI), which possesses the world's biggest sequencing capacity, has multiple NGS systems including 137 HiSeq 2000, 27 SOLiD, one Ion Torrent PGM, one MiSeq, and one 454 sequencer. We have accumulated extensive experience in sample handling, sequencing, and bioinformatics analysis. In this paper, technologies of these systems are reviewed, and first-hand data from extensive experience is summarized and analyzed to discuss the advantages and specifics associated with each sequencing system. At last, applications of NGS are summarized.

/pdf/comparison-of-next-generation-sequencing-systems-3d4puxkmer.pdf

Yinhu Li

Papers

Comparison of Next-Generation Sequencing Systems