Project description:Currently, most tools utilized in host-pathogen interaction studies depend on the use of human or mouse (Mus musculus) cells and tissues. While these species have led to countless breakthroughs in our understanding of infectious disease, there are undoubtably important biological processes that are missed by limiting studies to these two vertebrate species. For instance, it is well-established that the most common North American rodent, the Peromyscus leucopus deermouse, has unique interactions with microbes, which likely shape its ability to serve as a critical reservoir for at numerous zoonotic pathogens—including a Lyme disease spirochete, Borrelia burgdorferi. In this work, we expand the immunological toolkit to study P. leucopus biology by performing the first differentiation of deermouse bone marrow to macrophages using P. leucopus M-CSF producing HEK293T cells.
Project description:Analysis of gene expression can be challenging, especially if it involves genetically diverse populations that exhibit high variation in their individual expression profile. Despite this variation though, it is conceivable that in the same individuals a high degree of coordination is maintained between transcripts that belong to the same signaling modules and are associated with related biological functions. To explore this further, we calculated the correlation in the expression levels between each of ATF4, CHOP (DDIT3), GRP94, DNAJB9 (ERdj4), DNAJ3C (p58IPK) and HSPA5 (BiP/GRP78) with the whole transcriptome in primary fibroblasts from deer mice following induction of endoplasmic reticulum (ER) stress. Since these genes are associated with different transducers of the unfolded protein response (UPR) we postulated that their profile, in terms of correlation of transcripts, reflects distinct UPR branches engaged and therefore different biological processes. Standard gene ontology analysis was able to predict major functions associated with the corresponding transcript, and of the UPR arm related to that, namely regulation of the apoptotic response by ATF4 (PERK arm) and the ER stress associated degradation for GRP94 (IRE1). BiP, being a global regulator of the UPR, was associated with activation of ER stress in a rather global manner. Pairwise comparison in the correlation coefficients for these genes’ associated transcriptome showed the relevance of selected genes in terms of expression profiles.
Project description:Whole transcriptome RNA sequencing in brain tissue was generated to explore differences between young and old animals of two closely related species of deer mice (genus Peromyscus) that reportedly differ in their lifespans: P. leucopus that lives for up to 8 years and P. maniculatus that exhibits a lifespan of about 4 years.
Project description:Kinship relationships between parents affect offspring fitness. Beyond its effects in heterozygosity or its impact in deleterious alleles that can be reduced to homozygosity and decrease the individuals’ fitness, the consequences of parental relatedness in the offspring remain understudied. By leveraging the availability of detailed pedigrees of captive Peromyscus we explored how parental relatedness impacts the methylome and the epigenetic age estimation of the offspring. Global CpG methylation analysis showed that parental relatedness positively impacts lifespan expectancy and reduces epigenetic aging, contributing about 13% of variation in epigenetic age estimation. Global hypermethylation due to relatedness was considerably higher than hypomethylation, was more pronounced in the male offspring, and mainly affected chromosomal loci associated with development. A relatedness-associated methylation signature was described that predicts parental relatedness with high accuracy, providing the proof of concept that kinship relationships can be inferred by epigenetic analyses. These findings identify parental relatedness as a modifier of epigenetic aging and global methylation, suggesting that kinship relations should be considered when epigenetic, and potentially transcriptomic data are interpreted in the context of aging and of other pathophysiological processes.