Multiple loci contribute to genome-wide recombination levels in male mice

Recent linkage-based studies in humans suggest the presence of loci that affect either genome-wide recombination rates, utilization of recombination hotspots, or both. We have been interested in utilizing cytological methodology to directly assess recombination in mammalian meiocytes and to identify recombination-associated loci. In the present report we summarize studies in which we combined a cytological assay of recombination in mouse pachytene spermatocytes with QTL analyses to identify loci that contribute to genome-wide levels of recombination in male meiosis. Specifically, we analyzed MLH1 foci, a marker of crossovers, in 194 F2 male mice derived from a subspecific cross between CAST/EiJ and C57BL/6J parental strains. We then used these data to uncover loci associated with individual variation in mean MLH1 values. We identified seven recombination-associated loci across the genome (on chromosomes 2, 3, 4, 14, 15, 17, and X), indicating that there are multiple recombination “setting” loci in mammalian male meiosis.     

A Simple Regression-Based Method to Map Quantitative Trait Loci Underlying Function-Valued Phenotypes

Most statistical methods for quantitative trait loci (QTL) mapping focus on a single phenotype. However, multiple phenotypes are commonly measured, and recent technological advances have greatly simplified the automated acquisition of numerous phenotypes, including function-valued phenotypes, such as growth measured over time. While methods exist for QTL mapping with function-valued phenotypes, they are generally computationally intensive and focus on single-QTL models. We propose two simple, fast methods that maintain high power and precision and are amenable to extensions with multiple-QTL models using a penalized likelihood approach. After identifying multiple QTL by these approaches, we can view the function-valued QTL effects to provide a deeper understanding of the underlying processes. Our methods have been implemented as a package for R, funqtl.     

R/qtlcharts: Interactive Graphics for Quantitative Trait Locus Mapping

Every data visualization can be improved with some level of interactivity. Interactive graphics hold particular promise for the exploration of high-dimensional data. R/qtlcharts is an R package to create interactive graphics for experiments to map quantitative trait loci (QTL) (genetic loci that influence quantitative traits). R/qtlcharts serves as a companion to the R/qtl package, providing interactive versions of R/qtl’s static graphs, as well as additional interactive graphs for the exploration of high-dimensional genotype and phenotype data.     

Fossilized Life in Subseafloor Ultramafic Rocks

Ultramafic rocks are hypothesized to support a subseafloor hydrogen-driven biosphere because of extensive production of bioavailable energy sources like H₂ or CH₄ from fluid-rock interactions. Hence, the apparent lack of microbial remains in subseafloor ultramafic rocks, in contrast to their frequent observation in subseafloor basalts, is somewhat of a paradox. Here we report fossilized microbial remains in aragonite veins in ultramafic rocks from the 15°20′N Fracture Zone area on the Mid-Atlantic Ridge (MAR), collected during Ocean Drilling Program (ODP) Leg 209. The microbial remains consist of filamentous structures associated with biofilms. The young age (<1 Myr) and absence of diagenesis result in fossilized microbial communities with a pristine composition characterized by carbonaceous matter (CM) and the enrichment in trace elements such as Ni, Co, Mo and Mn. Our study confirms the presence of the hypothesized deep subseafloor biosphere hosted in ultramafic rocks. We further show that host rock composition may influence the microbial elemental composition, which is recorded during the fossilization.