Using mapped quantitative trait loci in improving genetic evaluation

dc.contributor.advisor Albert E. Freeman
dc.contributor.author Abdel Azim, Gamal
dc.contributor.department Animal Science
dc.date 2018-08-25T04:36:48.000
dc.date.accessioned 2020-07-02T05:44:05Z
dc.date.available 2020-07-02T05:44:05Z
dc.date.copyright Mon Jan 01 00:00:00 UTC 2001
dc.date.issued 2001-01-01
dc.description.abstract <p>The benefit of using QTL information in dairy cattle breeding schemes by means of computer simulation is investigated. In addition, algorithms to overcome computational problems arising when marker data are included in mixed linear models were proposed.;Computer simulation was conducted with parameters relative to the Holstein population of the United States. Superiority of QTL-assisted selection (QAS) over QTL-free selection was studied in four pathways of selection, namely active sires, young bulls, bull dams, and cows, for cumulative genetic response, accuracy of evaluation, and selection pressure on the QTL.;Further, breeding scheme as a factor was studied. The breeding scheme was the most effective factor in increasing the superiority of QAS. As it agreed with many previous studies, nucleus breeding schemes were found to be promising systems to implement QTL information. On the other hand, benefits of QAS in conventional two stage selection programs were limited.;The interaction between the type of QTL information available and the breeding system was found important. Using a highly polymorphic QTL in nucleus schemes was found very effective. Effects of different number of alleles per locus and different number of loci on the superiority of QAS were studied.;An algorithm to directly build the inverse of a conditional gametic relationship matrix, given marker data, was developed. The inverse algorithm is based on matrix decomposition instead of partitioned matrix theory. Numerical techniques that greatly improved computing performance were introduced.;Appropriate modifications to the conventional breeding schemes that are currently in use are highly recommended. Further, attention should be paid to the characteristics of the QTL and how they may interact with the breeding system, e.g., number of loci and alleles. Finally, the study found that the use of marked or known QTL information in genetic evaluation is computationally possible and generally useful.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/rtd/471/
dc.identifier.articleid 1470
dc.identifier.contextkey 6073818
dc.identifier.doi https://doi.org/10.31274/rtd-180813-12099
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath rtd/471
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/77374
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/rtd/471/r_3016685.pdf|||Sat Jan 15 00:25:23 UTC 2022
dc.subject.disciplines Agriculture
dc.subject.disciplines Animal Sciences
dc.subject.disciplines Biostatistics
dc.subject.disciplines Genetics
dc.subject.keywords Animal science
dc.subject.keywords Animal breeding and genetics
dc.title Using mapped quantitative trait loci in improving genetic evaluation
dc.type article
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 85ecce08-311a-441b-9c4d-ee2a3569506f
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
File
Original bundle
Now showing 1 - 1 of 1
Name:
r_3016685.pdf
Size:
2.72 MB
Format:
Adobe Portable Document Format
Description: