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Origins and functional evolution of Y chromosome gene repertoires across the class Mammalia

ABSTRACT: We collected (Illumina) RNA-seq data (polyadenylated RNA fraction) for a number of tissue samples from common marmoset and elephant. We developed a subtraction approach based on male/female RNA-seq data, Illumina genomic data and available genomes to identify and assemble Y transcripts. For marmoset samples, we added Y coding genes and noncoding sequences to the reference genomes in order to assess their expression levels. We then mapped all RNA-seq reads with TopHat 1.4.0 and used Cufflinks 2.0.0 (all mapped reads, embedded multi-read and fragment bias correction) to calculate the FPKM (Fragments Per Kilobase of transcript per Million mapped reads) values for all genes in the genomes with our refined annotations.

ORGANISM(S): Callithrix jacchus Rattus norvegicus Notamacropus eugenii Loxodonta africana

PROVIDER: GSE50747 | GEO | 2014/04/15

SECONDARY ACCESSION(S): PRJNA218629

REPOSITORIES: GEO

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Project description:Purpose: The goal of this study are to investigate the TRPM1-regulated genes using RNAseq to compare the transcriptome profiling between 661W cells expressing TRPM1 and control vectors Methods: RNAs were isolatedusing the RNeasy Mini kit (Qiagen). RNA-seq libraries were prepared using the KAPA mRNA HyperPrep Kit (KAPA Biosystems, Roche, Basel, Switzerland) and validated using the Qsep 100 DNA/RNA Analyzer (BiOptic Inc., Taiwan). Libraries were sequenced on a NovaSeq 6000 sequencer (Illumina, CA, USA). Clean reads were aligned to the mouse genome (GRCm38) using HISAT2 (version 2.1.0) after removing low-quality reads. The differential expression of genes between TRPM1-overexpression and control cells was computed using the fragments per kilobase of transcript per million mapped reads calculated by featureCounts (version 2.0.0). Raw read counts were imported into edgeR (version 3.28.1) and analyzed by using R package of DESeq (version 1.40.0). Genes with false discovery rate (FDR) p-value < 0.05 adjusted by using Benjamini–Hochberg (BH) method were considered as differentially expressed genes (DEGs). Gene set enrichment analysis of the genes differentially expressed upon TRPM1 expression was done using the Gene Set Knowledgebase（GSKB）hallmark gene sets. Results: We had 40,922,040 clean reads in the control group and 44,244,608 clean reads in the TRPM1-overexpressing group. We mapped 43,253, 668 (97.76%) sequence reads in the control group and 39,942,649 (97.6%) sequence reads in the TRPM1-overexpressing group. We identified 16,014 transcripts. 76 transcripts showed differential expression between the vector control group and TRPM1-expressing group, with a fold change ≥1.5 and p value <0.01. Gene set enrichment analysis of the genes differentially expressed upon TRPM1 expression uncovered several TRPM1-regulated genes that may contribute to photoreceptor function, such as retina morphogenesis and JAK-STAT cascade. Conclusions: Our study represents the genes associated with TRPM1 overexpression in 661W photoreceptor cells using RNA-seq approach. The overexpression of TRPM1 may contribute to regulate the photoreceptor morphogenesis and function

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Origins and functional evolution of Y chromosome gene repertoires across the class Mammalia

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