| Title |
From genetical genomics to systems genetics: potential applications in quantitative genomics and animal breeding
|
|---|---|
| Published in |
Mammalian Genome, June 2006
|
| DOI | 10.1007/s00335-005-0169-x |
| Pubmed ID | |
| Authors |
Haja N. Kadarmideen, Peter von Rohr, Luc L.G. Janss |
| Abstract |
This article reviews methods of integration of transcriptomics (and equally proteomics and metabolomics), genetics, and genomics in the form of systems genetics into existing genome analyses and their potential use in animal breeding and quantitative genomic modeling of complex traits. Genetical genomics or the expression quantitative trait loci (eQTL) mapping method and key findings in this research are reviewed. Various procedures and potential uses of eQTL mapping, global linkage clustering, and systems genetics are illustrated using actual analysis on recombinant inbred lines of mice with data on gene expression (for diabetes- and obesity-related genes), pathway, and single nucleotide polymorphism (SNP) linkage maps. Experimental and bioinformatics difficulties and possible solutions are discussed. The main uses of this systems genetics approach in quantitative genomics were shown to be in refinement of the identified QTL, candidate gene and SNP discovery, understanding gene-environment and gene-gene interactions, detection of candidate regulator genes/eQTL, discriminating multiple QTL/eQTL, and detection of pleiotropic QTL/eQTL, in addition to its use in reconstructing regulatory networks. The potential uses in animal breeding are direct selection on heritable gene expression measures, termed "expression assisted selection," and genetical genomic selection of both QTL and eQTL based on breeding values of the respective genes, termed "expression-assisted evaluation." |
Mendeley readers
The data shown below were compiled from readership statistics for 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 1% |
| Sweden | 2 | 1% |
| Norway | 1 | <1% |
| Finland | 1 | <1% |
| China | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 134 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 42 | 30% |
| Student > Ph. D. Student | 27 | 19% |
| Student > Master | 13 | 9% |
| Professor > Associate Professor | 12 | 8% |
| Student > Postgraduate | 7 | 5% |
| Other | 26 | 18% |
| Unknown | 15 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 87 | 61% |
| Biochemistry, Genetics and Molecular Biology | 15 | 11% |
| Medicine and Dentistry | 6 | 4% |
| Veterinary Science and Veterinary Medicine | 5 | 4% |
| Computer Science | 3 | 2% |
| Other | 9 | 6% |
| Unknown | 17 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 12 July 2011.
All research outputs
#7,455,523
of 22,792,160 outputs
Outputs from Mammalian Genome
#318
of 1,126 outputs
Outputs of similar age
#22,585
of 64,261 outputs
Outputs of similar age from Mammalian Genome
#3
of 10 outputs
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