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Stem cell transcriptional profiles from mouse subspecies reveal cis-regulatory evolution at ribosomal large-subunit genes

ABSTRACT: A key goal of evolutionary genomics is to harness molecular data from wild isolates to draw inferences about selective forces that have acted on genomes. The field progresses in large part through the development and benchmarking of advanced molecular-evolution analysis methods. Here we evaluated the rigor and performance of a test of directional, cis-regulatory evolution across genes in pathways, using stem cells across Mus musculus subspecies as a model. We discovered a unique program of induction of translation-related genes in stem cells of the Southeast Asian mouse M. m. castaneus relative to its sister taxa, driven in part by cis-regulatory variation. As a complement, we used sequence analyses to find population- and comparative-genomic signatures of selection in M. m. castaneus, at the upstream regions of the ribosomal gene cohort. The unique high-expression program for these loci in M. m. castaneus was recapitulated in stem cell-derived neurons. We interpret our data under a model of changes in lineage-specific pressures across Mus musculus for high translational capacity in stem cells and their descendant cells. Together, our findings underscore the rigor of integrating expression and sequence-based methods to generate hypotheses about evolutionary events from long ago.

ORGANISM(S): Mus musculus domesticus Mus musculus castaneus

PROVIDER: GSE234761 | GEO | 2024/11/06

REPOSITORIES: GEO

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Project description:Recent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across many species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: identifying truly non-coding genes from de novo reconstructed transcriptomes, and prioritizing the hundreds of resulting putative lncRNAs for downstream experimental interrogation. We present slncky, a computational lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-sequencing data and further uses evolutionary constraint to prioritize lncRNAs that are likely to be functionally important. Our automated filtering pipeline is comparable to manual curation efforts and more sensitive than previously published computational approaches. Furthermore, we develop a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for analyzing sequence and transcript evolution. Our analysis reveals that evolutionary selection acts in several distinct patterns, and uncovers two notable classes of intergenic lncRNAs: one showing strong purifying selection on RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript. To study a comprehensive and comparable set of lncRNAs expressed in the pluripotent state, we analyzed RNA-Seq data from pluripotent cells derived from several strains and species, and grown in two physiological conditions. First we derived ânaÃ¯veâ ES cells (ESCs) from each of three different mice strains: 129SvEv, NOD, and Mus musculus castaneus (cast) mouse, a wild mouse subspecies originally from Thailand, as well as naÃ¯ve induced pluripotent stem (iPS) cells from rat and human. Next, to facilitate comparisons across pluripotent cells from different species, we also cultured mouse and rat cells in âprimedâ epiblast stem cell (EpiSC) culture conditions, since human iPS cells in culture are much more similar molecularly and functionally to mouse primed EpiSCs rather than to a ground state naÃ¯ve ESCs. We polyA selected RNA from each cell type and deeply sequenced on HiSeq2500

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Stem cell transcriptional profiles from mouse subspecies reveal cis-regulatory evolution at ribosomal large-subunit genes

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