Quantitative trait loci variation for growth and obesity between and within lines of pigs (Sus scrofa)

The hypothesis that quantitative trait loci (QTL) that explain variation between divergent populations also account for genetic variation within populations was tested using pig populations. Two regions of the porcine genome that had previously been reported to harbor QTL with allelic effects that differed between the modern pig and its wild-type ancestor and between the modern pig and a more distantly related population of Asian pigs were studied. QTL for growth and obesity traits were mapped using selectively genotyped half-sib families from five domesticated modern populations. Strong support was found for at least one QTL segregating in each population. For all five populations there was evidence of a segregating QTL affecting fatness in a region on chromosome 7. These findings confirm that QTL can be detected in highly selected commercial populations and are consistent with the hypothesis that the same chromosome locations that account for variation between populations also explain genetic variation within populations.     

Force production by single kinesin motors

Motor proteins such as kinesin, myosin and polymerase convert chemical energy into work through a cycle that involves nucleotide hydrolysis. Kinetic rates in the cycle that depend upon load identify transitions at which structural changes, such as power strokes or diffusive motions, are likely to occur. Here we show, by modelling data obtained with a molecular force clamp, that kinesin mechanochemistry can be characterized by a mechanism in which a load-dependent isomerization follows ATP binding. This model quantitatively accounts for velocity data over a wide range of loads and ATP levels, and indicates that movement may be accomplished through two sequential 4-nm substeps. Similar considerations account for kinesin processivity, which is found to obey a load-dependent Michaelis-Menten relationship.     

Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples

We have recently developed analysis methods (GREML) to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP) data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (co)variation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases) in particular when the traits (diseases) are not measured on the same samples.     

Diet of bluegill Lepomis macrochirus in a South African reservoir during winter and summer

Alien fishes are considered a major threat to aquatic biodiversity in South Africa, yet relatively little regional information on their biology and ecology is available for many of these species. Seasonal changes in the diet of the bluegill Lepomis macrochirus in Howieson’s Poort Dam, Grahamstown, were assessed during summer and winter in 2014–2015, using stomach content analysis. In winter, juvenile and adult fish diets were dominated by crustacean zooplankton and insects, respectively. In summer, juvenile fish fed on crustaceans and insects, whereas adults consumed mostly fish eggs, indicating a potential impact by these invasive fish on native fish through oophagy.     

Microbial diversity in modern marine stromatolites, Highborne Cay, Bahamas

Living marine stromatolites at Highborne Cay, Bahamas, are formed by microbial mat communities that facilitate precipitation of calcium carbonate and bind and trap small carbonate sand grains. This process results in a laminated structure similar to the layering observed in ancient stromatolites. In the modern marine system at Highborne Cay, lamination, lithification and stromatolite formation are associated with cycling between three types of microbial communities at the stromatolite surface (Types 1, 2 and 3, which range from a leathery microbial mat to microbially fused sediment). Examination of 923 universal small-subunit rRNA gene sequences from these communities reveals that taxonomic richness increases during transition from Type 1 to Type 3 communities, supporting a previous model that proposed that the three communities represent different stages of mat development. The phylogenetic composition also changes significantly between these community types and these community changes occur in concert with variation in biogeochemical rates. The dominant bacterial groups detected in the stromatolites include Alphaproteobacteria , Planctomycetes , Cyanobacteria and Bacteroidetes . In addition, the stromatolite communities were found to contain novel cyanobacteria that may be uniquely associated with modern marine stromatolites. The implications of these findings are discussed in the context of current models for stromatolite formation.