aTAP: automated transcriptome analysis platform for processing RNA-seq data by de novo assembly.

RNA-seq is a sequencing technique that uses next-generation sequencing (NGS) to explore and study the entire transcriptome of a biological sample. NGS-based analyses are mostly performed via command-line interfaces, which is an obstacle for molecular biologists and researchers. Therefore, the higher throughputs from NGS can only be accessed with the help of bioinformatics and computer science expertise. As the cost of sequencing is continuously falling, the use of RNA-seq seems certain to increase. To minimize the problems encountered by biologists and researchers in RNA-seq data analysis, we propose an automated platform with a web application that integrates various bioinformatics pipelines. The platform is intended to enable academic users to more easily analyze transcriptome datasets. Our automated Transcriptome Analysis Platform (aTAP) offers comprehensive bioinformatics workflows, including quality control of raw reads, trimming of low-quality reads, de novo transcriptome assembly, transcript expression quantification, differential expression analysis, and transcript annotation. aTAP has a user-friendly graphical interface, allowing researchers to interact with and visualize results in the web browser. This project offers an alternative way to analyze transcriptome data, by integrating efficient and well-known tools, that is simpler and more accessible to research communities. aTAP is freely available to academic users at https://atap.psu.ac.th/.

Transcriptomic study of Salmonella enterica subspecies enterica serovar Typhi biofilm.

BACKGROUND: Typhoid fever is an acute systemic infection of humans caused by Salmonella enterica subspecies enterica serovar Typhi (S. Typhi). In chronic carriers, the bacteria survive the harsh environment of the gallbladder by producing biofilm. The phenotype of S. Typhi biofilm cells is significantly different from the free-swimming planktonic cells, and studies have shown that they are associated with antibiotic resistance, immune system evasion, and bacterial persistence. However, the mechanism of this transition and the events leading to biofilm formation are unknown. High throughput sequencing was performed to identify the genes involved in biofilm formation and to postulate the mechanism of action. RESULTS: Planktonic S. Typhi cells were cultured using standard nutrient broth whereas biofilm cells were cultured in a stressful environment using high shearing-force and bile to mimic the gallbladder. Sequencing libraries were prepared from S. Typhi planktonic cells and mature biofilm cells using the Illumina HiSeq 2500 platform, and the transcriptome data obtained were processed using Cufflinks bioinformatics suite of programs to investigate differential gene expression between the two phenotypes. A total of 35 up-regulated and 29 down-regulated genes were identified. The identities of the differentially expressed genes were confirmed using NCBI BLAST and their functions were analyzed. The results showed that the genes associated with metabolic processes and biofilm regulations were down-regulated while those associated with the membrane matrix and antibiotic resistance were highly up-regulated. CONCLUSIONS: It is proposed that the biofilm phenotype of S. Typhi allows the bacteria to increase production of the membrane matrix in order to serve as a physical shield and to adhere to surfaces, and enter an energy conservation state in response to the stressful environment. Conversely, the planktonic phenotype allows the bacteria to produce flagella and increase metabolic activity to enable the bacteria to migrate and form new colonies of infection. This data provide a basis for further studies to uncover the mechanism of biofilm formation in S. Typhi and to discover novel genes or pathways associated with the development of the typhoid carrier state.

After 'completion': the changing face of human chromosomes 21 and 22.

In the four years since the publication of the first two 'complete' human chromosome sequences the type of research being done on each has shifted subtly, reflecting the impact of genomic data on biological science in general. There is now considerably more gene-expression evidence to support predicted genes, and the annotation of functions for previously unknown genes, including those implicated in disease, is gradually improving.