New method to combine molecular and pedigree relationships.
Abstract: Relationship coefficients are traditionally based on pedigree data. Today, with the development of molecular techniques, they are often completely replaced by coefficients calculated from molecular data. Examples are relationships from microsatellites for biodiversity studies but also genomic relationships from SNP as currently used in genomic prediction of breeding values. There are, however, many situations in which optimal combination of both sources would be the best solutions. Obviously, this is the case for incompletely genotyped populations, but also when pedigree information is sparse. Also, markers, even dense ones, do not reflect the whole genome and therefore give only an incomplete picture of relationships. The main objective of this study was therefore to develop a method to calculate a relationship matrix by the combination of molecular and pedigree data. It will be useful for all situations where pedigree and molecular data are available. In this study, based on simulations of pedigree and marker data, we used partial least squares regression and linear regression to combine total allelic relationship coefficients calculated for each marker with additive relationship coefficients calculated from incomplete pedigree. The results showed that the greatest advantage of this method, compared with the one that replaces a part of the pedigree-based relationship matrix by a genomic relationship matrix, is that adding the partial pedigree data allows for the correction of the molecular coefficient for the ungenotyped part of the genome.
Publication Date: 2010-11-19 PubMed ID: 21097686DOI: 10.2527/jas.2010-3135Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
- Research Support
- Non-U.S. Gov't
Summary
This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.
This research is aimed at developing a more comprehensive method for calculating relationship coefficients by combining both pedigree data and molecular data, which could be beneficial in contexts where both data types are available and situations of incomplete genotyping or sparse pedigree information.
Understanding the Research
- The study delves into the subject of relationship coefficients, which have traditionally been derived from pedigree data. However, with technological advancements, these coefficients are increasingly determined from molecular data, such as the relationship derived from microsatellites for biodiversity studies or genomic relationships from SNP (Single Nucleotide Polymorphism) used for genomic prediction of breeding values.
- The researchers note that in various scenarios, an optimal combination of pedigree and molecular data could give a more accurate solution than relying on either data in isolation.
- Situations where combined data approach could prove beneficial include cases of incomplete genotyping, sparse pedigree information, or when even a wealth of markers may not fully reflect the genome, offering only a partial view of relationships.
Method Development
- The main objective of this study was to develop an effective method for computing a relationship matrix that combines both pedigree and molecular data.
- Partial least squares regression and linear regression were used to combine total allelic relationship coefficients calculated for each marker with additive relationship coefficients determined from incomplete pedigree.
- This research is based on the simulation of pedigree and marker data.
Findings and Benefits of the Method
- The results demonstrate that combining pedigree and molecular data allows for a more comprehensive and thorough understanding of genomic relationships.
- This new method seems better than the approach of replacing a part of a pedigree-based relationship matrix with a genomic relationship matrix.
- One of the significant advantages of this new method is that it allows for correction of the molecular coefficient, accounting for the ungenotyped part of the genome through the addition of partial pedigree data.
- The method developed through this study is especially useful in situations where both pedigree and molecular data are accessible.
Cite This Article
APA
Bömcke E, Soyeurt H, Szydlowski M, Gengler N.
(2010).
New method to combine molecular and pedigree relationships.
J Anim Sci, 89(4), 972-978.
https://doi.org/10.2527/jas.2010-3135 Publication
Researcher Affiliations
- University of Liege, Gembloux Agro-Bio Tech, Animal Science Unit, 5030 Gembloux, Belgium. elisabeth.bomcke@ulg.ac.be
MeSH Terms
- Animals
- Biodiversity
- Computer Simulation
- Genetic Markers
- Genetics, Population / methods
- Genotype
- Horses / genetics
- Least-Squares Analysis
- Linear Models
- Microsatellite Repeats
- Models, Genetic
- Pedigree
Citations
This article has been cited 1 times.- Vychodilova L, Necesankova M, Albrechtova K, Hlavac J, Modry D, Janova E, Vyskocil M, Mihalca AD, Kennedy LJ, Horin P. Genetic diversity and population structure of African village dogs based on microsatellite and immunity-related molecular markers.. PLoS One 2018;13(6):e0199506.
Use Nutrition Calculator
Check if your horse's diet meets their nutrition requirements with our easy-to-use tool Check your horse's diet with our easy-to-use tool
Talk to a Nutritionist
Discuss your horse's feeding plan with our experts over a free phone consultation Discuss your horse's diet over a phone consultation
Submit Diet Evaluation
Get a customized feeding plan for your horse formulated by our equine nutritionists Get a custom feeding plan formulated by our nutritionists
