2026-10-14T20:09:01Z https://www.scidb.cn/oai

10.11922/sciencedb.o00019.00014 2022-02-25T08:00:00Z

2022-02-25 Data and code for the comparison of gene expression patterns between the spider venom glands and other tissues doi:10.11922/sciencedb.o00019.00014 en We integrated the genomes and RNA-seq datasets from various lineages, containing spiders, scorpions, ticks, mites, centipedes and insects. We updated the genome of a model spider, common house spider (Parasteatoda tepidariorum), to chromosome-level assembly for better comparative analysis. We examined module preservation among tissues by acquiring the gene co-expression networks of spider venom glands; we then estimated the similarities among tissues by calculating Gene ontology (GO) semantic similarity and similarity of differentially up-regulated genes (DUGs). To explore the specificity of expression in spider venom glands, we obtained the up-regulated genes and specific transcription modules of venom glands, as well as examined the influence of gene duplication and selection pressure on the expression variations.(1) This dataset includes three matrices for manuscript "Genomic and transcriptomic analyses shed light on the origin and evolution of spider venom glands".The detailed introduction of matrices are listed below:1.Ortholog_expression matrices_TPM_value.xlsx:We obtained ortholog expression matrix which had high-confidence alignments across the multiple taxa based on the one-to-one orthologs. We calculated gene expression values by mapping all of the RNA reads back to the trimmed orthologs of each species using RSEM v1.3.1, with the exception of Trichonephila clavipes, which was mapped to Trichonephila antipodiana, and Rhipicephalus evertsi which was mapped to Hyalomma asiaticum. To allow the comparison of these data among biological replicates, tissues and species, we normalized gene expression data by transforming transcripts per million (TPM) scores to log2(N+1) values. The transformed data were then quantile normalized among samples by R package limma v3.40.6. We next removed the batch effects by ComBat function in R package sva v3.32.1.2.Tissue_RNA-Seq_expression_Matrice_for_multiple_species.xlsx:To attain the complete expressed information of transcriptome samples, we also aligned all RNA-Seq data of each speicies to their own genome using HISAT2 v2.1.0. Read counts per gene were counted in HTSeq framework v0.11.2 Gene counts of all samples were then normalized to TPM values based on total reads per sample and effective gene length. A total of seven TPM matrice were obtained.3.Orthogroup_of_ten_species_from_Orthofinder_program.txt:Gene families of ten species across arthropods were inferred with Orthofinder program, composed of gene counts and gene id for each gene orthogroup.(2) This dataset also contains chromosome-level assembly of common house spider (Parasteatoda tepidariorum), which we generated in our study.Parasteatoda tepidariorum_4.0_IZCAS.gff.zip: GFF annotation file;Parasteatoda tepidariorum_4.0_IZCAS_cds.fa.zip: fasta file of coding gene sequences;Parasteatoda tepidariorum_4.0_IZCAS_genomics.fasta.zip: whole genome sequence file.(3) This dataset contains the codes and scripts we used.4.code and script.zip: including 13 files of code or script.  RNA expression; read counts; genome; annotation; code Bingyue Zhu Pengyu Jin Yiming Zhang Yunxiao Shen Wei Wang Shuqiang Li PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank