In PLoS Biology this week, researchers at the University of California, Berkeley, suggest that "gene clustering by expression discordance can be used to determine the genetic basis of phenotypic variation" based on the transcriptional data sets they report for Drosophila melanogaster and Anopheles gambiae during embryonic development. In both species, the researchers identified clusters of orthologous genes and found "a striking difference in the temporal expression of a subset of maternal genes" between them. In particular, the Berkeley team observed a "sharp reduction at the time of the maternal-zygotic transition in Drosophila display sustained expression in the Anopheles embryo."
Investigators in the UK report in this week's PLoS One their "genome-wide analysis of transcriptional reprogramming in mouse models of acute myeloid leukemia." Using gene expression profiling and ChIP-seq, the team "identified several thousand candidate regulatory regions with altered levels of histone acetylation that were characterized by differential distribution of consensus motifs for key hematopoietic transcription factors including Gata2," among others. Inducing Gata2 expression in the mouse models "was not compatible with sustained growth of leukemic cells, thus suggesting a previously unrecognized role for Gata2 in down-regulation during the development of AML," the authors write.
Researchers at the University of Iowa and the University of Colorado, Denver, report their use of bisulfite sequencing and methylated DNA enrichment methods, with which they observed "human PHD3 promoter hypermethylation in prostate, breast, melanoma, and renal carcinoma cell lines." In its subsequent analysis, the team shows that PHD3 expression "is silenced by aberrant CpG methylation of the PHD3 promoter in a subset of human carcinoma cell lines of diverse origin," which it suggests is the "mechanism by which these cancer cell lines fail to up-regulate PHD3 mRNA."
And in another PLoS One paper published this week, investigators at the UK's Babraham Institute report a "simple procedure" to recover low-diversity sequence data that is lost as a result of sequence bias when using the Illumina platform. The Babraham team's method involves deferring "the mapping of cluster coordinates until low-diversity sequences have been passed," which it says "can recover substantial amounts of next generation sequencing data that would otherwise be lost."