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Guang, A.

Publications and source records attributed to Guang, A..

2 recordsLinked to original sources

Ethylene Glycol Monomethyl Ether Altered Rat Sperm Small RNAs with Critical Developmental Roles

Abstract/SummaryEthylene glycol monomethyl ether (EGME) is a testicular germ cell toxicant that selectively targets spermatocytes. In rats, male-only EGME exposure reduces mating success and can lead to an increase in resorbed fetuses. In a previous study, five-day exposure to 50, 60, or 75 mg/kg/d EGME in male rats led to a decrease in sperm motility and increase in retained spermatid heads with a lowest observed adverse effect level (LOAEL) of 75 mg/kg/d. At 60 mg/kg/d, EGME exposure altered the proportion of sperm small RNA reads mapped to different small RNA categories and the distribution of read lengths. To understand the possible role of sperm sncRNAs in EGME-mediated reduction in spermatogenesis, fertility, and embryonic development, we analyzed sperm sncRNA data from EGME-treated male rats to identify differential expression at the individual RNA level. EGME treatment resulted in dose-dependent increases in the expression levels of microRNAs (miRNAs), piRNAs, and tRNA-derived small RNAs (tsRNAs), and mixture of dose-dependent increases and decreases in abundance of rsRNA reads. We identified 12 miRNAs that were differentially expressed at all EGME doses, with a monotonic, dose-dependent increase. High-confidence targets of these 12 miRNAs are known to be expressed in pre-implantation embryos and statistically enriched for Gene Ontology (GO) biological processes related to early development, such as cell fate commitment and regulation of developmental growth. These results demonstrated that the EGME-induced changes in sperm sncRNA levels were reproducible, dose-dependent, and provided a putative mechanism of paternal EGME effects on embryonic development, which will be investigated in future studies.

pharmacology and toxicology↗

Revising transcriptome assemblies with phylogenetic information in Agalma1.0

MotivationOne of the most common transcriptome assembly errors is to mistake different transcripts of the same gene as transcripts from multiple closely related genes. It is difficult to identify these errors during assembly, but in a phylogenetic analysis these errors can be diagnosed from gene trees containing clades of tips from the same species with improbably short branch lengths.\n\nResultstreeinform is a module implemented in Agalma1.0 that uses phylogenetic analyses across species to refine transcriptome assemblies. It identifies transcripts of the same gene that were incorrectly assigned to multiple genes and reassign them as transcripts of the same gene.\n\nAvailability and Implementationtreeinform is implemented in Agalma1.0, available at https://bitbucket.org/caseywdunn/agalma.\n\nContactaugust_guang@brown.edu\n\nSupplementary informationSupplementary information is available at bioRxiv.

bioinformatics↗