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Attention Score in Context
| Title |
Screening of whole genome sequences identified high-impact variants for stallion fertility
|
|---|---|
| Published in |
BMC Genomics, April 2016
|
| DOI | 10.1186/s12864-016-2608-3 |
| Pubmed ID | |
| Authors |
Rahel Schrimpf, Maren Gottschalk, Julia Metzger, Gunilla Martinsson, Harald Sieme, Ottmar Distl |
| Abstract |
Stallion fertility is an economically important trait due to the increase of artificial insemination in horses. The availability of whole genome sequence data facilitates identification of rare high-impact variants contributing to stallion fertility. The aim of our study was to genotype rare high-impact variants retrieved from next-generation sequencing (NGS)-data of 11 horses in order to unravel harmful genetic variants in large samples of stallions. Gene ontology (GO) terms and search results from public databases were used to obtain a comprehensive list of human und mice genes predicted to participate in the regulation of male reproduction. The corresponding equine orthologous genes were searched in whole genome sequence data of seven stallions and four mares and filtered for high-impact genetic variants using SnpEFF, SIFT and Polyphen 2 software. All genetic variants with the missing homozygous mutant genotype were genotyped on 337 fertile stallions of 19 breeds using KASP genotyping assays or PCR-RFLP. Mixed linear model analysis was employed for an association analysis with de-regressed estimated breeding values of the paternal component of the pregnancy rate per estrus (EBV-PAT). We screened next generation sequenced data of whole genomes from 11 horses for equine genetic variants in 1194 human and mice genes involved in male fertility and linked through common gene ontology (GO) with male reproductive processes. Variants were filtered for high-impact on protein structure and validated through SIFT and Polyphen 2. Only those genetic variants were followed up when the homozygote mutant genotype was missing in the detection sample comprising 11 horses. After this filtering process, 17 single nucleotide polymorphism (SNPs) were left. These SNPs were genotyped in 337 fertile stallions of 19 breeds using KASP genotyping assays or PCR-RFLP. An association analysis in 216 Hanoverian stallions revealed a significant association of the splice-site disruption variant g.37455302G>A in NOTCH1 with the de-regressed estimated breeding values of the paternal component of the pregnancy rate per estrus (EBV-PAT). For 9 high-impact variants within the genes CFTR, OVGP1, FBXO43, TSSK6, PKD1, FOXP1, TCP11, SPATA31E1 and NOTCH1 (g.37453246G>C) absence of the homozygous mutant genotype in the validation sample of all 337 fertile stallions was obvious. Therefore, these variants were considered as potentially deleterious factors for stallion fertility. In conclusion, this study revealed 17 genetic variants with a predicted high damaging effect on protein structure and missing homozygous mutant genotype. The g.37455302G>A NOTCH1 variant was identified as a significant stallion fertility locus in Hanoverian stallions and further 9 candidate fertility loci with missing homozygous mutant genotypes were validated in a panel including 19 horse breeds. To our knowledge this is the first study in horses using next generation sequencing data to uncover strong candidate factors for stallion fertility. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
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 % |
|---|---|---|
| Unknown | 67 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 16% |
| Student > Bachelor | 10 | 15% |
| Researcher | 8 | 12% |
| Student > Master | 7 | 10% |
| Student > Doctoral Student | 4 | 6% |
| Other | 12 | 18% |
| Unknown | 15 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 37% |
| Veterinary Science and Veterinary Medicine | 14 | 21% |
| Biochemistry, Genetics and Molecular Biology | 6 | 9% |
| Computer Science | 2 | 3% |
| Business, Management and Accounting | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 18 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 April 2016.
All research outputs
#14,257,527
of 22,862,742 outputs
Outputs from BMC Genomics
#5,703
of 10,663 outputs
Outputs of similar age
#160,523
of 300,620 outputs
Outputs of similar age from BMC Genomics
#153
of 247 outputs
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So far Altmetric has tracked 10,663 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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We're also able to compare this research output to 247 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.