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Updated: May 11, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Gene-based single nucleotide polymorphism discovery in bovine muscle using next-generation transcriptomic sequencing.

Anis Djari¹, Diane Esquerré, Bernard Weiss

¹INRA, UMR 1313 GABI, Unité Génétique Animale et Biologie Intégrative, Domaine de Vilvert, 78352 Jouy-en-Josas, France.

|May 9, 2013

Summary

This study used RNA-sequencing to discover novel genetic markers in cattle muscle, identifying thousands of single nucleotide polymorphisms (SNPs). These findings enhance genomic resources for cattle breeding and meat quality trait research.

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Area of Science:

Animal Genetics
Molecular Biology
Genomics

Background:

Genetic markers are crucial for cattle breeding, improving upon traditional phenotypic selection.
Identifying causative genetic variants for economic traits has been challenging.
Transcriptomic sequencing (RNA-Seq) offers a cost-effective method for discovering genetic variants.

Purpose of the Study:

To perform gene-based single nucleotide polymorphism (SNP) discovery in bovine Longissimus thoraci muscle using RNA-Seq.
To identify novel coding SNPs for improving cattle genomic resources.
To explore the utility of identified SNPs for breed discrimination.

Main Methods:

High-throughput sequencing of messenger RNAs from Limousin bull calf Longissimus thoraci.
Bioinformatic analysis to identify transcripts and single nucleotide polymorphisms (SNPs).
Validation of high-confidence SNPs using genotyping across nine major French bovine breeds.

Main Results:

Identified 19,752 transcripts and 34,376 SNPs, with 55% in coding regions.
Detected 8,407 high-confidence SNPs, including 18% non-synonymous coding SNPs.
Genotyping confirmed SNP accuracy and demonstrated clear breed separation via principal component analysis.

Conclusions:

RNA-Seq data and novel coding SNPs significantly enhance cattle genomic resources, particularly for beef breeds.
The identified variations, especially non-synonymous coding SNPs, are valuable for studying meat quality trait variability.
The discovered SNPs can aid in understanding genetic mechanisms influencing economically important traits in cattle.