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RNA Sequencing to Study Gene Expression and SNP Variations Associated with Growth in Zebrafish Fed a Plant Protein-Based Diet

Overview of attention for article published in Marine Biotechnology, February 2015
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Title
RNA Sequencing to Study Gene Expression and SNP Variations Associated with Growth in Zebrafish Fed a Plant Protein-Based Diet
Published in
Marine Biotechnology, February 2015
DOI 10.1007/s10126-015-9624-1
Pubmed ID
Authors

Pilar E. Ulloa, Gonzalo Rincón, Alma Islas-Trejo, Cristian Araneda, Patricia Iturra, Roberto Neira, Juan F. Medrano

Abstract

The objectives of this study were to measure gene expression in zebrafish and then identify SNP to be used as potential markers in a growth association study. We developed an approach where muscle samples collected from low- and high-growth fish were analyzed using RNA-Sequencing (RNA-seq), and SNP were chosen from the genes that were differentially expressed between the low and high groups. A population of 24 families was fed a plant protein-based diet from the larval to adult stages. From a total of 440 males, 5 % of the fish from both tails of the weight gain distribution were selected. Total RNA was extracted from individual muscle of 8 low-growth and 8 high-growth fish. Two pooled RNA-Seq libraries were prepared for each phenotype using 4 fish per library. Libraries were sequenced using the Illumina GAII Sequencer and analyzed using the CLCBio genomic workbench software. One hundred and twenty-four genes were differentially expressed between phenotypes (p value < 0.05 and FDR < 0.2). From these genes, 164 SNP were selected and genotyped in 240 fish samples. Marker-trait analysis revealed 5 SNP associated with growth in key genes (Nars, Lmod2b, Cuzd1, Acta1b, and Plac8l1). These genes are good candidates for further growth studies in fish and to consider for identification of potential SNPs associated with different growth rates in response to a plant protein-based diet.

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The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Spain 1 1%
Unknown 65 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 21%
Student > Ph. D. Student 9 13%
Professor > Associate Professor 5 7%
Student > Bachelor 5 7%
Student > Master 5 7%
Other 14 21%
Unknown 15 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 46%
Biochemistry, Genetics and Molecular Biology 4 6%
Computer Science 2 3%
Neuroscience 2 3%
Business, Management and Accounting 1 1%
Other 9 13%
Unknown 18 27%