In Genome Research online, researchers from the University of California, Los Angeles, introduce a scheme intended to help find related individuals from genomic data without compromising privacy. The team customized a new cryptographic method to pursue that goal, providing proof-of-principle demonstrations that the technique allows individuals to explore their own relationships without releasing data to third party individuals. "We show in HapMap and 1000 Genomes data that our method can recover first- and second-order genetic relationships and, through simulations, show that our method can identify relationships as distant as third cousins while preserving privacy," the researchers say.
A Stanford University team takes a look at positive selection and its potential role in human evolution. Using information on polymorphisms picked up through the 1000 Genomes Project, the investigators weeded out background signals of selection to identify apparently authentic signatures of positive selection. An analysis of those regions indicated that adaptive changes tend to be found near variants that produce substitutions in the resulting amino acid sequence. Positive selection signatures also tended to turn up near regulatory sequences, the study's authors say. "Our results suggest that adaptation was frequent in human evolution and provide support for the hypothesis … that adaptive divergence is primarily driven by regulatory changes," they add.
Researchers from the US and France used chromosome conformation capture and high-throughput sequencing to track genome architecture and gene expression in Plasmodium falciparum parasites during different stages of red blood cell infection. Together with documented gene expression patterns for P. falciparum, the three-dimensional consensus maps of genome structure they obtained highlighted chromatin conformation dynamics in the malaria-causing parasite, as well as the associations between the parasite's genome organization over time and its gene expression.