A Novel Prostate Cancer Risk Variant in African Americans, Dynamics of the Human Gut Microbiome, and Geno-Pheno Maps for Digital Organisms: the PLOS Comp Biol February Issue
Check out our highlights from the PLOS Computational Biology February issue:
ALKBH7 variant related to prostate cancer exhibits altered substrate binding
The search for prostate cancer biomarkers has received increased attention and several DNA repair related enzymes have been linked to this dysfunction. Gerardo Andrés Cisneros and colleagues report a targeted search for single nucleotide polymorphisms (SNPs) and functional impact characterization of human ALKBH family dioxygenases. Their results uncovered a SNP in ALKBH7, rs7540, which is associated with prostate cancer disease in a statistically significantly manner in two separate cohorts, and maintained in African American men. Although the natural substrate of ALKBH7 is unknown, this variant is expected to affect binding of its co-factor.
Two dynamic regimes in the human gut microbiome
The gut microbiome is a dynamic system that changes with host development, health, behaviour, diet, and microbe-microbe interactions. In this study, Eric J. Alm and colleagues develop an approach for disentangling two types of dynamics within the human gut microbiome; autoregressive and non-autoregressive. The authors find that despite frequently observed disruptions to the gut ecosystem, there exists a returning force that continually pushes the gut microbiome back towards its steady-state configuration.
The genotype-phenotype map of an evolving digital organism
The phenotype of an organism comprises the set of morphological and functional traits encoded by its genome. In natural evolving systems, phenotypes are organized into mutationally connected networks of genotypes, which increase the likelihood of an evolving population encountering novel adaptive phenotypes (i.e., its evolvability). We do not know whether artificial systems, such as self-replicating and evolving computer programs, are more or less evolvable than natural systems. By studying how genotypes map onto phenotypes in digital organisms, Miguel A. Fortuna and colleagues characterize many commonalities between natural and artificial evolving systems.
Header Image Credit: Walker et al.