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Attention Score in Context
| Title |
Use of Genome Sequence Information for Meat Quality Trait QTL Mining for Causal Genes and Mutations on Pig Chromosome 17
|
|---|---|
| Published in |
Frontiers in Genetics, January 2011
|
| DOI | 10.3389/fgene.2011.00043 |
| Pubmed ID | |
| Authors |
Zhi-Liang Hu, Antonio M. Ramos, Sean J. Humphray, Jane Rogers, James M. Reecy, Max F. Rothschild |
| Abstract |
The newly available pig genome sequence has provided new information to fine map quantitative trait loci (QTL) in order to eventually identify causal variants. With targeted genomic sequencing efforts, we were able to obtain high quality BAC sequences that cover a region on pig chromosome 17 where a number of meat quality QTL have been previously discovered. Sequences from 70 BAC clones were assembled to form an 8-Mbp contig. Subsequently, we successfully mapped five previously identified QTL, three for meat color and two for lactate related traits, to the contig. With an additional 25 genetic markers that were identified by sequence comparison, we were able to carry out further linkage disequilibrium analysis to narrow down the genomic locations of these QTL, which allowed identification of the chromosomal regions that likely contain the causative variants. This research has provided one practical approach to combine genetic and molecular information for QTL mining. |
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 % |
|---|---|---|
| Australia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 14% |
| Uganda | 1 | 14% |
| Unknown | 5 | 71% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 29% |
| Researcher | 2 | 29% |
| Student > Doctoral Student | 2 | 29% |
| Student > Master | 1 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 86% |
| Biochemistry, Genetics and Molecular Biology | 1 | 14% |
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 06 February 2012.
All research outputs
#18,304,230
of 22,662,201 outputs
Outputs from Frontiers in Genetics
#6,961
of 11,727 outputs
Outputs of similar age
#159,924
of 180,278 outputs
Outputs of similar age from Frontiers in Genetics
#48
of 58 outputs
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