Development and validation of next generation sequencing based 35-gene hereditary cancer panel.

Background: Understanding the genetic basis of cancer risk is a major international endeavor. The emergence of next-generation sequencing (NGS) in late 2000's has further accelerated the discovery of many cancer susceptibility genes. The use of targeted NGS-based multigene testing panels to provide comprehensive analysis of cancer susceptible genes has proven to be a viable option, with the accurate and robust detection of a wide range of clinically relevant variants in the targeted genes being crucial.

Fast and accurate HLA typing from short-read next-generation sequence data with xHLA.

The HLA gene complex on human chromosome 6 is one of the most polymorphic regions in the human genome and contributes in large part to the diversity of the immune system. Accurate typing of HLA genes with short-read sequencing data has historically been difficult due to the sequence similarity between the polymorphic alleles. Here, we introduce an algorithm, xHLA, that iteratively refines the mapping results at the amino acid level to achieve 99-100% four-digit typing accuracy for both class I and II HLA genes, taking only [Formula: see text]3 min to process a 30× whole-genome BAM file on a desktop computer.

Detecting novel genetic variants associated with isoniazid-resistant Mycobacterium tuberculosis.

Background: Isoniazid (INH) is a highly effective antibiotic central for the treatment of Mycobacterium tuberculosis (MTB). INH-resistant MTB clinical isolates are frequently mutated in the katG gene and the inhA promoter region, but 10 to 37% of INH-resistant clinical isolates have no detectable alterations in currently known gene targets associated with INH-resistance. We aimed to identify novel genes associated with INH-resistance in these latter isolates.

Evaluation and optimisation of indel detection workflows for ion torrent sequencing of the BRCA1 and BRCA2 genes.

Background: The Ion Torrent PGM is a popular benchtop sequencer that shows promise in replacing conventional Sanger sequencing as the gold standard for mutation detection. Despite the PGM's reported high accuracy in calling single nucleotide variations, it tends to generate many false positive calls in detecting insertions and deletions (indels), which may hinder its utility for clinical genetic testing.

Results: Recently, the proprietary analytical workflow for the Ion Torrent sequencer, Torrent Suite (TS), underwent a series of upgrades.

Predicting spatial and temporal gene expression using an integrative model of transcription factor occupancy and chromatin state.

Precise patterns of spatial and temporal gene expression are central to metazoan complexity and act as a driving force for embryonic development. While there has been substantial progress in dissecting and predicting cis-regulatory activity, our understanding of how information from multiple enhancer elements converge to regulate a gene's expression remains elusive. This is in large part due to the number of different biological processes involved in mediating regulation as well as limited availability of experimental measurements for many of them.

Improving indel detection specificity of the Ion Torrent PGM benchtop sequencer.

The emergence of benchtop sequencers has made clinical genetic testing using next-generation sequencing more feasible. Ion Torrent's PGM™ is one such benchtop sequencer that shows clinical promise in detecting single nucleotide variations (SNVs) and microindel variations (indels). However, the large number of false positive indels caused by the high frequency of homopolymer sequencing errors has impeded PGM™'s usage for clinical genetic testing.

Development of a next-generation sequencing method for BRCA mutation screening: a comparison between a high-throughput and a benchtop platform.

In a clinical setting, next-generation sequencing (NGS) approaches for the enrichment and resequencing of DNA targets may have limitations in throughput, cost, or accuracy. We evaluated an NGS workflow for targeted DNA sequencing for mutation detection. Targeted sequence data of the BRCA1 and BRCA2 genes, generated using a PCR-based, multiplexed NGS approach using the SOLiD 4 (n = 24) and Ion Torrent PGM (n = 20) next-generation sequencers, were evaluated against sequence data obtained by Sanger sequencing.

Inferring direct regulatory targets of a transcription factor in the DREAM2 challenge.

In the DREAM2 community-wide experiment on regulatory network inference, one of the challenges was to identify which genes, in a list of 200, are direct regulatory targets of the transcription factor BCL6. The organizers of the challenge defined targets based on gene expression and chromatin immunoprecipitation experiments (ChIP-chip). The expression data were publicly available; the ChIP-chip data were not.

Inferring transcription factor targets from gene expression changes and predicted promoter occupancy.

We have developed a method for inferring condition-specific targets of transcription factors based on ranking genes by gene expression change and ranking genes based on predicted transcription factor occupancy. The average of these two ranks, used as a test statistic, allows target genes to be inferred in a stringent manner. The method complements chromatin immunoprecipitation experiments by predicting targets under many conditions for which ChIP experiments have not been performed.

A library of yeast transcription factor motifs reveals a widespread function for Rsc3 in targeting nucleosome exclusion at promoters.

The sequence specificity of DNA-binding proteins is the primary mechanism by which the cell recognizes genomic features. Here, we describe systematic determination of yeast transcription factor DNA-binding specificities. We obtained binding specificities for 112 DNA-binding proteins representing 19 distinct structural classes.

Integration of external signaling pathways with the core transcriptional network in embryonic stem cells.

Transcription factors (TFs) and their specific interactions with targets are crucial for specifying gene-expression programs. To gain insights into the transcriptional regulatory networks in embryonic stem (ES) cells, we use chromatin immunoprecipitation coupled with ultra-high-throughput DNA sequencing (ChIP-seq) to map the locations of 13 sequence-specific TFs (Nanog, Oct4, STAT3, Smad1, Sox2, Zfx, c-Myc, n-Myc, Klf4, Esrrb, Tcfcp2l1, E2f1, and CTCF) and 2 transcription regulators (p300 and Suz12). These factors are known to play different roles in ES-cell biology as components of the LIF and BMP signaling pathways, self-renewal regulators, and key reprogramming factors.

Sequential logic model deciphers dynamic transcriptional control of gene expressions.

Background: Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here.

In silico analysis of p53 using the p53 knowledgebase: mutations, polymorphisms, microRNAs and pathways.

P53 is probably the most important tumor suppressor known. Over the years, information about this gene has increased dramatically. We have built a comprehensive knowledgebase of p53, which aims to facilitate wet-lab biologists to formulate their experiments and new-comers to learn whatever they need about the gene and bioinformaticians to make new discoveries through data analysis.