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Attention Score in Context
| Title |
Non-synonymous mutations mapped to chromosome X associated with andrological and growth traits in beef cattle
|
|---|---|
| Published in |
BMC Genomics, May 2015
|
| DOI | 10.1186/s12864-015-1595-0 |
| Pubmed ID | |
| Authors |
Gregório Miguel Ferreira de Camargo, Laercio R Porto-Neto, Matthew J Kelly, Rowan J Bunch, Sean M McWilliam, Humberto Tonhati, Sigrid A Lehnert, Marina R S Fortes, Stephen S Moore |
| Abstract |
Previous genome-wide association analyses identified QTL regions in the X chromosome for percentage of normal sperm and scrotal circumference in Brahman and Tropical Composite cattle. These traits are important to be studied because they are indicators of male fertility and are correlated with female sexual precocity and reproductive longevity. The aim was to investigate candidate genes in these regions and to identify putative causative mutations that influence these traits. In addition, we tested the identified mutations for female fertility and growth traits. Using a combination of bioinformatics and molecular assay technology, twelve non-synonymous SNPs in eleven genes were genotyped in a cattle population. Three and nine SNPs explained more than 1% of the additive genetic variance for percentage of normal sperm and scrotal circumference, respectively. The SNPs that had a major influence in percentage of normal sperm were mapped to LOC100138021 and TAF7L genes; and in TEX11 and AR genes for scrotal circumference. One SNP in TEX11 was explained ~13% of the additive genetic variance for scrotal circumference at 12 months. The tested SNP were also associated with weight measurements, but not with female fertility traits. The strong association of SNPs located in X chromosome genes with male fertility traits validates the QTL. The implicated genes became good candidates to be used for genetic evaluation, without detrimentally influencing female fertility traits. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 20% |
| Student > Ph. D. Student | 5 | 13% |
| Student > Doctoral Student | 4 | 10% |
| Researcher | 4 | 10% |
| Professor | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 40% |
| Veterinary Science and Veterinary Medicine | 3 | 8% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Unspecified | 2 | 5% |
| Mathematics | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 12 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 January 2016.
All research outputs
#20,302,535
of 22,840,638 outputs
Outputs from BMC Genomics
#9,282
of 10,655 outputs
Outputs of similar age
#222,095
of 264,669 outputs
Outputs of similar age from BMC Genomics
#228
of 247 outputs
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