In PLoS Computational Biology this week, Stanford's Atul Butte and his colleagues identify diagnostic serum protein biomarkers "indicating acute rejection across different types of transplanted solid organs," which they found by mining public repositories of microarray data. Butte et al. identified 45 genes upregulated in AR from pediatric renal, adult renal, and adult cardiac transplantation. From there, they performed ELISA on proteins from 39 renal transplant patients. Serum PECAM1, the authors write, "identified renal AR with 89 percent sensitivity and 75 percent specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies." See our sister publication GenomeWeb Daily News' coverage of the study, here.
In PLoS Genetics, a team led by researchers at the Wellcome Trust Centre for Cell Biology show that about half of mammalian CpG islands are "orphans" in that they are not associated with annotated promoters. "Unlike CGIs at known promoters, orphan CGIs are frequently subject to DNA methylation during development, and this is accompanied by loss of their active promoter features," the authors write. The team suggests that the undetected promoters with which orphan CGIs correspond may be subject to transcriptional activity that could play a functional role during development.
Yichuan Liu and Aydin Tozeren at Drexel University report in PLoS One this week that "SNPs that fall on protein domains are highly statistically enriched among SNPs linked to hereditary disorders and complex diseases." Liu and Tozeren show that "proteins with domain-altering SNPs comprise highly connected nodes in cellular pathways such as the focal adhesion, the axon guidance pathway and the autoimmune disease pathways." In their analyses, the duo also found an "extensive loss of connectivity of cell signaling pathways due to domain-altering SNPs," they write.
Also in PLoS One this week, investigators at the University of Melbourne and their colleagues describe analytical methods for the "reference-free validation of short read data" based on analysis of base calls, analysis of k-mers, and analysis of distributions of k-mers. When applied to a range of short read data, the team's methodology highlighted "gross over-representation of some poly-base sequences, per-position biases towards some bases, and apparent preferences for some starting positions over others," they write. The authors suggest that statistical analysis of short reads can help researchers identify such issues before beginning assembly or re-sequencing tasks.