Transcriptome Analysis of Transparent Gill Covers of Pterophyllum scalare

【Objective】The transparent traits in Pterophyllum scalare has high economic and scientific value. This article aims to explore the differential expression genes (DEG) between transparent gill cover (TGC) and opaque gill cover (OGC) tissues of P. scalare, and explore the relevant signaling pathways a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Guangdong nong ye ke xue 2024-04, Vol.51 (4), p.54-64
Hauptverfasser: Weiyu ZHANG, Zaizhong CHEN, Bin WEN, Jianzhong GAO
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:【Objective】The transparent traits in Pterophyllum scalare has high economic and scientific value. This article aims to explore the differential expression genes (DEG) between transparent gill cover (TGC) and opaque gill cover (OGC) tissues of P. scalare, and explore the relevant signaling pathways affecting the transparent gill cover traits of P. scalare, so as to provide a theoretical basis for the subsequent screening of key genes regulating the transparent gill cover trait of P. scalare and related mechanism studies.【Method】The gill cover tissue of P. scalare (strain: red-topped tri-color) was selected as the research material, and 6 samples were selected from each group of OGC and TGC. Transcriptomic sequencing was carried out based on the Illumina Novaseq 6000 sequencing platform with using Fastp to perform quality control on raw sequencing data. The transcript and the corresponding single gene (Unigene) were obtained by de novo assembling of quality control data by Trinity software, and the initial assembly sequence was deredundancy analysis and result evaluation by CD-HIT software and BUSCO software, respectively. After redundancy, unigene were functionally annotated based on sequence homology. RSEM software was used to calculate the expression of unigene in each sample. DEGs between OGC and TGC were calculated using DESeq2 software. GO and KEGG pathway enrichment analysis was performed on DEGs using Goatools software and KOBAS software, respectively.【Result】(1) After quality control of sequencing data, the average error rate of each sample sequencing base was less than 0.1%, Q20 was higher than 97.78%, and Q30 was higher than 93.58%, and the sequencing quality was reliable. After de novo assembling, 200 303 transcripts were obtained, corresponding to 123 178 unigenes. After deredundancy analysis, a total of 147 932 transcripts are obtained, corresponding to 108 070 unigenes, with an average length of 991.85 bp and N50 is 2 430 bp. (2) A total of 40 180 unigenes were annotated in the NR, KEGG, eggNOG, GO, Pfam, and Swiss-Prot databases, accounting for 37.98% of the total, of which 10 747 genes were annotated simultaneously in 6 databases, accounting for 26.75% of the total. (3) TGC relative to OGC has a total of 432 DEGs, of which TGC significantly up-regulated 267 genes and down-regulated 165 genes relative to OGC. (4) GO enrichment results showed that 432 DEGs were mainly enriched in 5 biological pathways: IMP biosynthesis, IMP metabolism, "de nov
ISSN:1004-874X
DOI:10.16768/j.issn.1004-874X.2024.04.005