Dataset Information

Identification and quantitative mRNA analysis of a novel splice variant of GPIHBP1 in dairy cattle.

ABSTRACT: BACKGROUND:Identification of functional genes affecting milk production traits is very crucial for improving breeding efficiency in dairy cattle. Many potential candidate genes have been identified through our previous genome wide association study (GWAS). Of these, GPIHBP1 is an important novel candidate gene for milk production traits. However, the mRNA structure of the bovine GPIHBP1 gene is not fully determined up to now. RESULTS:In this study, we identified a novel alternatively splice transcript variant (X5) which leads to a 31 bp insertion in exon 3 and also confirmed the other four existed transcripts (X1, X2, X3 and X4) of the bovine GPIHBP1 gene. We showed that transcript X5 with a 31 bp insertion and transcript X1 with an 8 bp deletion might have tremendous effect on the protein function and structure of GPIHBP1, respectively. With semi-quantitative PCR and quantitative real-time RT-PCR, we found that the mRNA expression of GPIHBP1, GPIHBP1-X1 and GPIHBP1-X5 in mammary gland of lactating cows were much higher than that in other tissues. CONCLUSIONS:Our study reports a novel alternative splicing of GPIHBP1 in bovine for the first time and provide useful information for the further functional analyses of GPIHBP1 in dairy cattle.

SUBMITTER: Yang J

PROVIDER: S-EPMC4373091 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Identification and quantitative mRNA analysis of a novel splice variant of GPIHBP1 in dairy cattle.

Yang Jie J Liu Xuan X Zhang Qin Q Jiang Li L

Journal of animal science and biotechnology 20141105 1

<h4>Background</h4>Identification of functional genes affecting milk production traits is very crucial for improving breeding efficiency in dairy cattle. Many potential candidate genes have been identified through our previous genome wide association study (GWAS). Of these, GPIHBP1 is an important novel candidate gene for milk production traits. However, the mRNA structure of the bovine GPIHBP1 gene is not fully determined up to now.<h4>Results</h4>In this study, we identified a novel alternativ ...[more]

PMID: 25810903

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Project description:BACKGROUND: Advances in human genomics have allowed unprecedented productivity in terms of algorithms, software, and literature available for translating raw next-generation sequence data into high-quality information. The challenges of variant identification in organisms with lower quality reference genomes are less well documented. We explored the consequences of commonly recommended preparatory steps and the effects of single and multi sample variant identification methods using four publicly available software applications (Platypus, HaplotypeCaller, Samtools and UnifiedGenotyper) on whole genome sequence data of 65 key ancestors of Swiss dairy cattle populations. Accuracy of calling next-generation sequence variants was assessed by comparison to the same loci from medium and high-density single nucleotide variant (SNV) arrays. RESULTS: The total number of SNVs identified varied by software and method, with single (multi) sample results ranging from 17.7 to 22.0 (16.9 to 22.0) million variants. Computing time varied considerably between software. Preparatory realignment of insertions and deletions and subsequent base quality score recalibration had only minor effects on the number and quality of SNVs identified by different software, but increased computing time considerably. Average concordance for single (multi) sample results with high-density chip data was 58.3% (87.0%) and average genotype concordance in correctly identified SNVs was 99.2% (99.2%) across software. The average quality of SNVs identified, measured as the ratio of transitions to transversions, was higher using single sample methods than multi sample methods. A consensus approach using results of different software generally provided the highest variant quality in terms of transition/transversion ratio. CONCLUSIONS: Our findings serve as a reference for variant identification pipeline development in non-human organisms and help assess the implication of preparatory steps in next-generation sequencing pipelines for organisms with incomplete reference genomes (pipeline code is included). Benchmarking this information should prove particularly useful in processing next-generation sequencing data for use in genome-wide association studies and genomic selection.

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Dataset Information

Identification and quantitative mRNA analysis of a novel splice variant of GPIHBP1 in dairy cattle.

Publications

Identification and quantitative mRNA analysis of a novel splice variant of GPIHBP1 in dairy cattle.

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