An efficient algorithm for segregation analysis in large populations

Kerr, Richard J.; Kinghorn, Brian

doi:10.1111/j.1439-0388.1996.tb00636.x

Cited by 71 publications

(90 citation statements)

References 12 publications

(16 reference statements)

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“…Genotype probabilities for ABCG2(2) were determined for the entire Israeli Holstein milk-recorded population, including 600,478 cows and 1670 bulls, using the segregation analysis algorithm of Kerr and Kinghorn (1996), based on the 335 bulls with valid genotypes. Finally, the QTL effects for milk, fat, and protein yield were estimated from the entire Israeli Holstein milkrecorded population based on the genotyped cows, as proposed by Israel and Weller (1998).…”

mentioning

confidence: 99%

Identification of a missense mutation in the bovine ABCG2 gene with a major effect on the QTL on chromosome 6 affecting milk yield and composition in Holstein cattle

Cohen¹,

Seroussi²,

Larkin³

et al. 2005

Genome Res.

346

341

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We previously localized a quantitative trait locus (QTL) on chromosome 6 affecting milk fat and protein concentration to a 4-cM confidence interval, centered on the microsatellite BM143. We characterized the genes and sequence variation in this region and identified common haplotypes spanning five polymorphic sites in the genes IBSP, SPP1, PKD2, and ABCG2 for two sires heterozygous for this QTL. Expression of SPP1 and ABCG2 in the bovine mammary gland increased from parturition through lactation. SPP1 and all the coding exons of ABCG2 and PKD2 were sequenced for these two sires. The single nucleotide change capable of encoding a substitution of tyrosine-581 to serine (Y581S) in the ABCG2 transporter was the only polymorphism corresponding to the segregation status of all 3 heterozygous and 15 homozygous sires for the QTL in the Israeli and U.S. Holstein populations. The allele substitution fixed effects on the genetic evaluations of 335 Israeli sires were −341 kg milk, +0.16% fat, and +0.13% protein (F-value = 200). No other polymorphism gave significant effect for fat and protein concentration in models that also included Y581S. The allele substitution effects on the genetic evaluations of 670 cows, daughters of two heterozygous sires, were −226 kg milk, 0.09% fat, and 0.08% protein (F-value = 394), with partial dominance towards the 581S homozygotes. We therefore propose that Y581S in ABCG2 is the causative site for this QTL.

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mentioning

confidence: 99%

Identification of a missense mutation in the bovine ABCG2 gene with a major effect on the QTL on chromosome 6 affecting milk yield and composition in Holstein cattle

Cohen¹,

Seroussi²,

Larkin³

et al. 2005

Genome Res.

346

341

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“…For animals that were genotyped, we assumed that all genotypes were determined without error. Probabilities of genotypes for all other animals were computed based on the algorithm of Kerr and Kinghorn (1996). For animals with unknown parents, genotype probabilities were assumed to be equal to the mean probabilities in the entire sample of genotyped bulls.…”

Section: Methodsmentioning

confidence: 99%

A simple method for genomic selection of moderately sized dairy cattle populations

Weller

Maymon

Glick

et al. 2012

Animal

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An efficient algorithm for genomic selection of moderately sized populations based on single nucleotide polymorphism chip technology is described. A total of 995 Israeli Holstein bulls with genetic evaluations based on daughter records were genotyped for either the BovineSNP50 BeadChip or the BovineSNP50 v2 BeadChip. Milk, fat, protein, somatic cell score, female fertility, milk production persistency and herd-life were analyzed. The 400 markers with the greatest effects on each trait were first selected based on individual analysis of each marker with the genetic evaluations of the bulls as the dependent variable. The effects of all 400 markers were estimated jointly using a 'cow model,' estimated from the data truncated to exclude lactations with freshening dates after September 2006. Genotype probabilities for each locus were computed for all animals with missing genotypes. In Method I, genetic evaluations were computed by analysis of the truncated data set with the sum of the marker effects subtracted from each record. Genomic estimated breeding values for the young bulls with genotypes, but without daughter records, were then computed as their parent averages combined with the sum of each animal's marker effects. Method II genomic breeding values were computed based on regressions of estimated breeding values of bulls with daughter record on their parent averages, sum of marker effects and birth year. Method II correlations of the current breeding values of young bulls without daughter records in the truncated data set were higher than the correlations of the current breeding values with the parent averages for fat and protein production, persistency and herd-life. Bias of evaluations, estimated as a difference between the mean of current breeding values of the young bulls and their genomic evaluations, was reduced for milk production traits, persistency and herd-life. Bias for milk production traits was slightly negative, as opposed to the positive bias of parent averages. Correlations of Method II with the means of daughter records adjusted for fixed effects were higher than parent averages for fat, protein, fertility, persistency and herd-life. Reducing the number of markers included in the analysis from 400 to 300 did not reduce correlations of genomic breeding values for protein with current breeding values, but did slightly reduce correlations with means of daughter records. Method II has the advantages as compared with the method of VanRaden in that genotypes of cows can be readily incorporated into the Method II analysis, and it is more effective for moderately sized populations.Keywords: genomic selection, quantitative trait loci, single nucleotide polymorphisms, dairy cattle breeding ImplicationsTwo algorithms for genomic selection of moderately sized populations are described, and applied to the analysis of milk, fat and protein production; somatic cell score (SCS); female fertility; persistency; and herd-life of Israeli Holsteins. Method II genomic evaluations were less biased and more accurate ...

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“…The method of Kerr and Kinghorn [14] was used to calculate genotype probabilities for individuals in the SEGR scheme. This iterative method handles the many loops in the pedigree.…”

Section: Genetic Evaluation Methodsmentioning

confidence: 99%

“…The algorithm by Kerr and Kinghorn [14] was used to calculate genotype probabilities of each animal. It is an algorithm based on iterative peeling [2,13] and it takes account of effects of selection.…”

Section: Segregation Analysismentioning

confidence: 99%

“…For a recessive trait, P(y i = 0|XX i ) is 0.0, 0.0 and 1.0 for genotypes aa, Aa and AA, respectively, and again P(y i = 1|XX i ) = 1 − P(y i = 0|XX i ). From these penetrance probabilities, the algorithm by Kerr and Kinghorn [14] calculates the probability that the individual i has genotype XX, P(XX) i . The P(XX) i are used to calculate EBV as:…”

Section: Segregation Analysismentioning

confidence: 99%

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Selection against genetic defects in conservation schemes while controlling inbreeding

Sonesson

Janss²,

Meuwissen³

2003

Genet. Sel. Evol.

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-We studied different genetic models and evaluation systems to select against a genetic disease with additive, recessive or polygenic inheritance in genetic conservation schemes. When using optimum contribution selection with a restriction on the rate of inbreeding (∆F) to select against a disease allele, selection directly on DNA-genotypes is, as expected, the most efficient strategy. Selection for BLUP or segregation analysis breeding value estimates both need 1-2 generations more to halve the frequency of the disease allele, while these methods do not require knowledge of the disease mutation at the DNA level. BLUP and segregation analysis methods were equally efficient when selecting against a disease with single gene or complex polygene inheritance, i.e. knowledge about the mode of inheritance of the disease was not needed for efficient selection against the disease. Smaller schemes or schemes with a more stringent restriction on ∆F needed more generations to halve the frequency of the disease alleles or the fraction of diseased animals. Optimum contribution selection maintained ∆F at its predefined level, even when selection of females was at random. It is argued that in the investigated small conservation schemes with selection against a genetic defect, control of ∆F is very important. genetic defects / selection / inbreeding / conservation

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An efficient algorithm for segregation analysis in large populations

Cited by 71 publications

References 12 publications

Identification of a missense mutation in the bovine ABCG2 gene with a major effect on the QTL on chromosome 6 affecting milk yield and composition in Holstein cattle

Identification of a missense mutation in the bovine ABCG2 gene with a major effect on the QTL on chromosome 6 affecting milk yield and composition in Holstein cattle

A simple method for genomic selection of moderately sized dairy cattle populations

Selection against genetic defects in conservation schemes while controlling inbreeding

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