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Skelly, D. A.

Publications and source records attributed to Skelly, D. A..

3 recordsLinked to original sources

Single cell transcriptional profiling reveals cellular diversity, communication, and sexual dimorphism in the mouse heart

INTRODUCTORY PARAGRAPHCharacterization of the cardiac cellulome--the network of cells that form the heart--is essential for understanding cardiac development and normal organ function, and for formulating precise therapeutic strategies to combat heart disease. Recent studies have challenged assumptions about both the cellular composition1 and functional significance of the cardiac non-myocyte cell pool, with unexpected roles identified for resident fibroblasts2 and immune cell populations3,4. In this study, we characterized single-cell transcriptional profiles of the murine non-myocyte cardiac cellular landscape using single-cell RNA sequencing (scRNA-Seq). Detailed molecular analyses revealed the diversity of the cardiac cellulome and facilitated the development of novel techniques to isolate understudied cardiac cell populations such as mural cells and glia. Our analyses also revealed networks of intercellular communication as well as extensive sexual dimorphism in gene expression in the heart, most notably demonstrated by the upregulation of immune-sensing and pro-inflammatory genes in male cardiac macrophages. This study offers new insights into the structure and function of the mammalian cardiac cellulome and provides an important resource that will stimulate new studies in cardiac cell biology.

cell biology

Private haplotype barcoding facilitates inexpensive high-resolution genotyping of multiparent crosses

Inexpensive, high-throughput sequencing has led to the generation of large numbers of sequenced genomes representing diverse lineages in both model and non-model organisms. Such resources are well suited for the creation of new multiparent populations to identify quantitative trait loci that contribute to variation in phenotypes of interest. However, despite significant drops in per-base sequencing costs, the costs of sample handling and library preparation remain high, particularly when many samples are sequenced. We describe a novel method for pooled genotyping of offspring from multiple genetic crosses, such as those that that make up multiparent populations. Our approach, which we call \"private haplotype barcoding\" (PHB), utilizes private haplotypes to deconvolve patterns of inheritance in individual offspring from mixed pools composed of multiple offspring. We demonstrate the efficacy of this approach by applying the PHB method to whole genome sequencing of 96 segregants from 12 yeast crosses, achieving over a 90% reduction in sample preparation costs relative to non-pooled sequencing. In addition, we implement a hidden Markov model to calculate genotype probabilities for a generic PHB run and a specialized hidden Markov model for the yeast crosses that improves genotyping accuracy by making use of tetrad information. Private haplotype barcoding holds particular promise for facilitating inexpensive genotyping of large pools of offspring in diverse non-model systems.

genetics

The effect of known mutator alleles in a cluster of clinical Saccharomyces cerevisiae strains

Natural selection has the potential to act on all phenotypes, including genomic mutation rate. Classic evolutionary theory predicts that in asexual populations, mutator alleles, which cause high mutation rates, can fix due to linkage with beneficial mutations. This phenomenon has been demonstrated experimentally and may explain the frequency of mutators found in bacterial pathogens. In contrast, in sexual populations, recombination decouples mutator alleles from beneficial mutations, preventing mutator fixation. In the facultatively sexual yeast Saccharomyces cerevisiae, segregating alleles of MLH1 and PMS1 have been shown to be incompatible, causing a high mutation rate when combined. These alleles had never been found together naturally, but were recently discovered in a cluster of clinical isolates. Here we report that the incompatible mutator allele combination only marginally elevates mutation rate in these clinical strains. Genomic and phylogenetic analyses provide no evidence of a historically elevated mutation rate. We conclude that the effect of the mutator alleles is dampened by background genetic modifiers. Thus, the relationship between mutation rate and microbial pathogenicity may be more complex than once thought. Our findings provide rare observational evidence that supports evolutionary theory suggesting that sexual organisms are unlikely to harbor alleles that increase their genomic mutation rate.

evolutionary biology