Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees.

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

Next-generation sequencing of disseminated tumor cells.

Disseminated tumor cells (DTCs) detected in the bone marrow have been shown as an independent prognostic factor for women with breast cancer. However, the mechanisms behind the tumor cell dissemination are still unclear and more detailed knowledge is needed to fully understand why some cells remain dormant and others metastasize. Sequencing of single cells has opened for the possibility to dissect the genetic content of subclones of a primary tumor, as well as DTCs. Previous studies of genetic changes in DTCs have employed single-cell array comparative genomic hybridization which provides information about larger aberrations. To date, next-generation sequencing provides the possibility to discover new, smaller, and copy neutral genetic changes. In this study, we performed whole-genome amplification and subsequently next-generation sequencing to analyze DTCs from two breast cancer patients. We compared copy-number profiles of the DTCs and the corresponding primary tumor generated from sequencing and SNP-comparative genomic hybridization (CGH) data, respectively. While one tumor revealed mostly whole-arm gains and losses, the other had more complex alterations, as well as subclonal amplification and deletions. Whole-arm gains or losses in the primary tumor were in general also observed in the corresponding DTC. Both primary tumors showed amplification of chromosome 1q and deletion of parts of chromosome 16q, which was recaptured in the corresponding DTCs. Interestingly, clear differences were also observed, indicating that the DTC underwent further evolution at the copy-number level. This study provides a proof-of-principle for sequencing of DTCs and correlation with primary copy-number profiles. The analyses allow insight into tumor cell dissemination and show ongoing copy-number evolution in DTCs compared to the primary tumors.

Transcript annotation prioritization and screening system (TrAPSS) for mutation screening.

When searching for disease-causing mutations with polymerase chain reaction (PCR)-based methods, candidate genes are usually screened in their entirety, exon by exon. Genomic resources (i.e. www.ncbi.nih.gov, www.ensembl.org, and genome.ucsc.edu) largely support this paradigm for mutation screening by making it easy to view and access sequence data associated with genes in their genomic context. However, the administrative burden of conducting mutation screening in potentially hundreds of genes and thousands of exons in thousands of patients is significant, even with the use of public genome resources. For example, the manual design of oligonucleotide primers for all exons of the 10 Leber's congenital amaurosis (LCA) genes (149 exons) represents a significant information management challenge. The Transcript Annotation Prioritization and Screening System (TrAPSS) is designed to accelerate mutation screening by (1) providing a gene-based local cache of candidate disease genes in a genomic context, (2) automating tasks associated with optimizing candidate disease gene screening and information management, and (3) providing the implementation of an algorithmic technique to utilize large amounts of heterogeneous genome annotation (e.g. conserved protein functional domains) so as to prioritize candidate genes.

Protein expression in a transformed trabecular meshwork cell line: proteome analysis.

PURPOSE: Characterization of the human trabecular meshwork (TM) proteome is hindered by the small mass of intact tissue and the slow growth of cultured cell strains. We have previously characterized a transformed TM cell strain (GTM3) that demonstrates many of the same protein expression and cell signaling systems of nontransformed cell strains. The aim of this study was to initiate a proteomic survey of GTM3 cells as the initial step toward characterization of the complete human TM proteome. METHODS: GTM3 cells were cultured to confluence, harvested and solubilized in urea/Nonidet. The protein extract (600 mug) was focused in immobilized isoelectric focusing (IEF) strips, separated by 10% SDS PAGE, and visualized with colloidal Coomassie Blue. Spots of interest were excised, destained, and the contained proteins subjected to in-gel reduction, derivatization, and tryptic digestion. Tryptic peptides were extracted and analyzed by electrospray LC/MS/MS. Protein identification was made using the TurboSequest search algorithm and a recent version of the nonredundant human protein database downloaded from the National Center for Biotechnology Information (NCBI). RESULTS: Eighty-seven (87) primary proteins and 93 variants of these proteins were identified. A website was created (TM proteome) that combines data such as graphic spot location within the gel, peptide sequence, apparent and calculated pI, apparent and calculated mass, percentage of coverage, and protein informatic website links. CONCLUSIONS: Proteomic analysis of a transformed human TM cell line has been initiated combining preparative two-dimensional PAGE separation, LC/MS/MS analysis of major proteins, and bioinformatic cataloging of the data. Further investigation of data from the transformed cell strain will be used in a comparative fashion for spot identification of analytical proteomic gels of human TM tissue and cultured normal cells. These initial data will form the base from which the characterization of protein expression in the normal and glaucomatous TM can be accomplished.