Rajgopal Srinivasan, Ph.D.
Principal Scientist & Head Bio IT R&D, TCS Innovation Labs, India
Interpretation of Genomic Variation – Identifying Rare Variations Leading to Disease
Genome sequencing technologies are generating an abundance of data on human genetic variations. A big challenge lies in interpreting the functional relevance of such variations, especially in clinical settings. A first step in understanding the clinical relevance of genetic variations is to annotate the variants for region of occurrence, degree of conservation both within and across species, pattern of variation across related individuals, novelty of the variation and know effects of related variations. Several tools already exist for this purpose. However, these tools have their strengths and weaknesses. A second issue is the development of algorithms, which, given a rich annotation of variants are able to prioritize the variants as being relevant to the phenotype under investigation.
In my talk I will detail work that has been done in our labs to address both of the above problems. I will also illustrate the application of these tools that helped identify a rare mutation in the ATM gene leading to a diagnosis of AT in two infants.
Akhilesh Pandey, Ph.D.
Professor, Johns Hopkins University School of Medicine, Baltimore, USA
A draft map of the human proteome
We have generated a draft map of the human proteome through a systematic and comprehensive analysis of normal human adult tissues, fetal tissues and hematopoietic cells as an India-US initiative. This unique dataset was generated from 30 histologically normal adult tissues, fetal tissues and purified primary hematopoietic cells that were analyzed at high resolution in the MS mode and by HCD fragmentation in the MS/MS mode on LTQ-Orbitrap Velos/Elite mass spectrometers. This dataset was searched against a 6-frame translation of the human genome and RNA-Seq transcripts in addition to standard protein databases. In addition to confirming a large majority (>16,000) of the annotated protein-coding genes in humans, we obtained novel information at multiple levels: novel protein-coding genes, unannotated exons, novel splice sites, proof of translation of pseudogenes (i.e. genes incorrectly annotated as pseudogenes), fused genes, SNPs encoded in proteins and novel N-termini to name a few. Many proteins identified in this study were identified by proteomic methods for the first time (e.g. hypothetical proteins or proteins annotated based solely on their chromosomal location). We have generated a catalog of proteins that show a more tissue-restricted pattern of expression, which should serve as the basis for pursuing biomarkers for diseases pertaining to specific organs. This study also provides one of the largest sets of proteotypic peptides for use in developing MRM assays for human proteins. Identification of several novel protein-coding regions in the human genome underscores the importance of systematic characterization of the human proteome and accurate annotation of protein-coding genes. This comprehensive dataset will complement other global HUPO initiatives using antibody-based as well as MRM mass spectrometry-based strategies. Finally, we believe that this dataset will become a reference set for use as a spectral library as well as for interesting interrogations pertaining to biomedical as well as bioinformatics questions.
