Gerstein Lab Experience in Transcriptome Analysis

 

Experience in the Development of Analysis Tools Relevant to Transcriptome Analysis. The advent of new sequencing technology is outpacing the computational tools needed to harness the power of this technology. We believe that this critical Specific Aim will allow us to optimally use the RNA-Seq data. Dr. Mark Gerstein’s group has extensive knowledge in the field of complex transcriptome and high-throughput data analysis, including next-generation sequencing applications.

 

Transcriptome analysis: The Gerstein group has been actively involved in the ENCODE and modENCODE projects, among others, developing new tools for the analysis of transcribed regions of the human genome(Bertone et al., 2004; Birney et al., 2007; Harrison et al., 2005; Celniker et al., 2009; Encode Consortium, 2005). Results of this research activity have helped elucidate the complexity of the transcriptional machinery, identifying novel transcriptionally active loci and novel non-exonic transcripts(Gerstein et al., 2007; Washietl et al., 2007; Wu et al., 2008; Zheng et al., 2007). Most of the research required the use of high-throughput experimental platforms, such as tiling arrays and next-generation sequencing, which needed the development of proper computational tools for their analysis, a task the group has successfully accomplished(Bertone et al., 2006; Du et al., 2006; Emanuelsson et al., 2007; Royce et al., 2007; Royce et al., 2005). Results of this research have been made available to the scientific community through several web applications (dart.gersteinlab.org, tilescope.gersteinlab.org, and pseudogene.org)(Karro et al., 2007; Rozowsky et al., 2007; Zhang et al., 2007) .

 

Next-generation sequencing: The Gerstein group has considerable expertise in the management and analysis of the huge amount of data generated by the platforms for transcriptome analysis (RNA-Seq) as well as for binding site analysis (ChIP-Seq)(Lefrancois et al., 2009; Wang et al., 2009). Indeed, the group was involved in the analysis of yeast transcriptome using RNA-Seq, demonstrating the high level of transcription of the yeast genome as well as providing novel indications for its complexity(Nagalakshmi et al., 2008). Building on their experience in analyzing ChIP-chip experiments(Du et al., 2006), the group has developed new computational tools for the identification of transcription factor binding sites using ChIP-Seq(Rozowsky et al., 2009) as well as proper simulation approaches to optimize the amount of information that can be obtained from these experiments(Zhang et al., 2008).