Bruno VM, Wang Z, Marjani SL, et al. (2010). Comprehensive annotation of the transcriptome of the human fungal pathogen Candida albicans using RNA-seq. Genome Research. Epub: doi 10.1101/gr.109553.110.
A team led by investigators at Yale University reports on a high-resolution map of the Candida albicans transcriptome under nine different environmental conditions, generated using RNA-seq. In interrogating the resulting transcriptome data, the team identified 602 novel, transcriptionally active regions that appear to be regulated in a condition-specific manner in addition to 41 novel introns, which were verified using qRT-PCR. "This comprehensive transcriptome analysis significantly enhances the current genome annotation of C. albicans," the authors write.
Enhanced eQTL Identification
Michaelson JJ, Alberts R, Schugart K, Beyer A. (2010). Data-driven assessment of eQTL mapping methods. BMC Genomics. 11: 502.
Citing researchers' need to exploit expression quantitative trait loci data sets for all they are worth, Technische Universität Dresden's Jacob Michaelson and his team compared legacy QTL mapping methods to modern multi-locus methods, such as sparse partial least squares, lasso, and elastic net, among others. The newer approaches "clearly outperformed the legacy QTL methods … in terms of biological relevance," the team writes. Michaelson et al. also report a novel approach, based on Random Forests, which they suggest identifies eQTLs "that are more likely to be validated by independent data" than alternative methods.
Ohta S, Bukowski-Wills J, Sanchez-Pulido L, et al. (2010). The protein composition of mitotic chromosomes determined using multiclassifier combinational proteomics. Cell. 142(5): 810-821.
An international research team led by investigators at the Wellcome Trust Centre for Cell Biology reports a "series of independent classifiers that describe the [more than] 4,000 proteins identified in isolated mitotic chromosomes," which were generated by using a combination of quantitative proteomics and bioinformatic analyses. The team found that 30 of the 34 predicted chromosomal proteins tagged with GFP are indeed chromosomal; 13 of those are centromere-associated. "Of 16 GFP-tagged predicted non-chromosomal proteins, 14 were confirmed," the team writes, adding the hypothesis that "up to 97 new centromere-associated proteins remain to be discovered" in the extensive data set.
Attolini CS, Chenga Y, Beroukhim R, Getz G, et al. (2010). A mathematical framework to determine the temporal sequence of somatic genetic events in cancer. PNAS. Epub: doi 10.1073/pnas.1009117107.
Researchers at Memorial Sloan-Kettering Cancer Center and their colleagues report a computational approach to "deduce the temporal sequence of genetic events during tumorigenesis from cross-sectional genomic data of tumors at their fully transformed stage." Using the RESIC approach — retracing the evolutionary steps in cancer — on a set of 70 advanced colorectal cancers, the team was able to accurately predict the sequence in which APC, KRAS, and TP53 mutations appeared. The team also applied RESIC to glioblastoma sample data and found that "high-level EGFR amplification appears to be a late event."