In Nature this week, researchers from Columbia University analyzed 3D structures of protein-DNA complexes, learning that having arginine bind to narrow minor grooves is a "widely used mode for protein-DNA recognition." Seeing variability in DNA shape and electrostatic potential, they say, "is a general mechanism that enables proteins to use information in the minor groove." A News and Views story from Boston University's Tom Tullius adds perspective.
A collaboration between Korean and Michigan State University scientists took a look at genome evolution in Escherichia coli. Sequencing genomes sampled through 40,000 generations from a laboratory population of E. coli, they found "clock-like regularity" in genomic evolution. However, they also found that almost all of the mutations were beneficial – not neutral – and that, later, the population acquired hundreds of additional neutral mutations. The work suggests that "the coupling between genomic and adaptive evolution is complex and can be counterintuitive even in a constant environment," they write in the abstract.
The November issue of Nature Genetics is out, and several papers showcase GWAS meta-analyses. Wellcome Trust Sanger Institute's Nicole Soranzo was one of several first authors on work that used a genome-wide meta-analysis of the HaemGen consortium to find, among other things, 22 loci that are associated with eight "clinically relevant hematological parameters, including hemoglobin levels, red and white blood cell counts, and platelet counts and volume." In other work, Santhi Ganesh of the NHGRI helped lead work that studied GWAS from the CHARGE Consortium and the HaemGen Consortium. In a meta-analysis, they found 23 loci to be significantly associated with six erythrocyte traits, "including hemoglobin concentration, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, and red blood cell count."
Finally, another study appearing in Nature Genetics has found microduplications at chromosome 16p11.2 that are associated with schizophrenia. The researchers, led by senior author Jonathan Sebat at Cold Spring Harbor Laboratory, found the 16p11.2 microduplication to be associated with a 14.5-fold increased risk of schizophrenia while the "reciprocal microdeletion" at the same place was only associated with autism developmental disorders.