000			03395nam a22003257a 4500
999			_c111166 _d111166
003			IE-CoIT
005			20210921062546.0
007			ta
008			180323s2017 ie ||||| |||| 00| 0|eng||
040			_aIE-CoIT
082			_aTHESES PRESS
100	1		_9123984 _aJudge, Michelle _eauthor
245	1	0	_aLow cost, multi-purpose genotyping panels for dairy and beef cattle / _cMichelle Judge.
264		1	_aCork : _bCork Institute of Technology, _c2017.
300			_axi, 174 pages : _billustrations (some color) ; _c30 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490		0	_aPh. D - Biological Sciences
500			_aThe selection of animals based on DNA has revolutionised animal breeding, but the associated high cost of obtaining genotypes has limited its uptake. The object of this thesis was to develop a low-cost, low-density, multi-purpose genotyping panel for the procurement of reliable genotype information, and to quantify the long-term consequences of using such low-density genotype panels in breeding programs. The objectives were achieved through a combination of real-time cattle genotype data and simulations to mimic a cattle population. The in-silico development of genotype panels was based on actual genotypes from up to 58,705 beef cattle. Alternative novel strategies were used to identify informative single nucleotide polymorphisms (SNPs) with the purpose of developing a low density genotype panel which, once imputed to higher density, could be used in genomic evaluations. A minimum of 3,000 carefully selected SNPs were required if selected for use in a single breed, but this recommendation increased to 6,000 SNPs if the panel was to be applicable for imputation across breeds. Analysis using simulations suggest that successive imputation across generations, using approaches currently adopted globally, was suboptjmal with an accumulation of errors over generations ; an approach based on stepwise generational imputation was recommended to reduce the erosion in accuracy of imputed genotypes over generations. Results also indicated that a minimum of 300 SNPs were required to accurately predict breed composition with a mean standard error of prediction of 0.036. The advent of genomic evaluations has reduced generation intervals intensifying the importance of screening for DNA variants contributing to congenital defects. Using high density genotype data from 45 phenotypically normal calves and 23 half-sib contemporaries with a missing cleft pallet phenotype, a region on chromosome 13 was identified to harbour the underlying mutation. Analysis of sequence data from a selection of these animals identified putative causal mutations. In conclusion, appropriately designed genotype panels, coupled with optimised imputations strategies, can facilitate the widespread adoption of low-cost accurate genome-based breed programs - (Abstract)
500			_aThis Ph.D is a joint research project between Teagasc Moorepark and Cork Institute of Technology.
502			_aThesis _b(Ph. D.) - _cCork Institute of Technology, _d2017.
504			_aBibliography: (pages 153-166)
650		0	_9122069 _aBreeding
650		0	_946042 _aDNA microarrays
650		0	_9122068 _aAnimal genetics
650		0	_934544 _aBeef cattle
650		0	_aDairy cattle _9115201
942			_2ddc