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Transcriptomic response to selective breeding for fast growth in rainbow trout (Oncorhynchus mykiss)

dataset
posted on 2024-06-11, 07:13 authored by USDA/ARS
Genetic improvement for faster growth is a conventional approach to increase growth rates in aquaculture species, however the genetic and physiological factors regulating growth performance in fish are not fully characterized. The objective of this study was to identify physiological mechanisms associated with faster growth rates by comparing the liver and muscle transcriptome of a rainbow trout line selectively bred for fast growth (Growth Line, GL) and a contemporary randomly mated control line (Synthetic Control, SC) from the same selective breeding program. A third genetic line from a commercial egg supplier (Commercial A, CA) was also included to characterize differences in gene expression profiles between populations. Body weight of the GL at harvest was approximately 20% and 8% heavier (p < 0.05) than SC and CA, respectively. There were 145 and 36 differentially expressed genes (DEG) in liver and white muscle, respectively, between the GL and SC that were enriched for the growth hormone/ insulin-like growth factor axis (GH/IGF) and PI3K-Akt, JAK-STAT, MAPK, and cAMP signal transduction pathways. A greater concentration of plasma IGF-I was detected in the GL compared to SC (p < 0.05). A unique gene profile was detected in CA, with 11 and 210 DEG in liver and white muscle; these genes associated with innate immunity, complement systems, and metabolic pathways. Collectively, these findings provide a more extensive characterization of the fast-growth phenotype in fish that furthers knowledge of the physiological basis for genetic variation in growth performance in selectively bred rainbow trout.

History

Data contact name

BioProject Curation Staff

Publisher

National Center for Biotechnology Information

Temporal Extent Start Date

2020-04-04

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

sequence analysis

Pending citation

  • No

Public Access Level

  • Public

Accession Number

PRJNA623136

Preferred dataset citation

It is recommended to cite the accession numbers that are assigned to data submissions, e.g. the GenBank, WGS or SRA accession numbers. If individual BioProjects need to be referenced, state that "The data have been deposited with links to BioProject accession number PRJNA623136 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/)."

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