Options
Cook, Jim
- PublicationDevelopment of the beef genomic pipeline for BREEDPLAN single step evaluation(Association for the Advancement of Animal Breeding and Genetics (AAABG), 2017)
; ; ; ; ; ; Single step genomic BLUP (SS-GBLUP) for BREEDPLAN beef cattle evaluations is currently being tested for implementation across a number of breeds. A genomic data pipeline has been developed to enable efficient analysis of the industry-recorded SNP genotypes for incorporation in SS-GBLUP analyses. Complex data collection, along with format and/or naming convention inconsistencies challenges efficient data processing. This pipeline includes quality control of variable formatted data, and imputation of genotypes, for building the genomic relationship matrix required for implementation into single step evaluation. - PublicationBreedplan single-step genomic evaluations delivers increased accuracies across all breeds and EBVs(Association for the Advancement of Animal Breeding and Genetics (AAABG), 2023-07-26)
; ; ; ; ; Forward cross-validation analyses were used to quantify the changes in BREEDPLAN EBVs from single-step genetic evaluations compared to traditional pedigree-based evaluations for Angus, Brahman, Hereford, Santa Gertrudis and Wagyu breeds. EBVs were generated from full multi-trait evaluations for each breed and compared to EBVs from an evaluation where all the phenotypic records were removed from the last four year drops of animals (termed Validation). Results for the sub-set of validation animals that were SNP genotyped showed the population-based accuracy of single-step EBVs were higher than pedigree-based accuracies for all breeds and traits. However, the magnitudes of the accuracy increases differed across breeds and traits, and generally reflected differences in the size of the training populations for each trait. The largest increase in accuracy, averaged across all traits in a breed, was observed for Angus (24%) and the smallest for Santa Gertrudis (5%). Across breeds, the largest increases in accuracy occurred for the growth trait EBVs compared to smaller increases for abattoir carcase, female reproduction and NFI EBVs. This study has shown the benefits of single-step genomic evaluations, and the opportunity to increase rates of genetic progress, through the increased accuracy generated. The study also highlighted breeds and traits which could benefit from additional recording to increase accuracies from single-step.
- PublicationPolled Accelerator – a unique application of genomic technologies to address a beef breeding challenge
Genetic improvement requires selection for all traits in the breeding objective and increasingly this includes consideration of traits associated with animal welfare and social licence. A unique program called the 'Polled Accelerator' was developed for a large beef cattle population to rapidly increase the frequency of polledness. The program was constructed using a unique combination of existing and emerging genomic technologies and methods including DNA tests for polled/horn and Pompe's disease, DNA sire assignment, genomic breed composition, imputation and single-step genomic evaluation. Phenotypically polled young males were harvested from the commercial tier and through the program, high genetic merit polled animals were eligible for promotion to the multiplier and nucleus tiers of the breeding program. The application of multiple genomic technologies will allow the rapid introgression of polledness into this population without compromising the composite breed composition, breeding program structure, future genetic progress or genetic diversity.
- PublicationRemodelling the genetic evaluation of NFI in beef cattle - Part 1: Developing an equivalent genetic model(Association for the Advancement of Animal Breeding and Genetics (AAABG), 2023-07-26)
; ; ; ;Jeyaruban, G M; ; ; Net feed intake (NFI) is the residual portion of daily feed intake (DFI) not explained by growth or maintenance requirements. The NFI phenotype (NFIp) is based on a 70-day test period where DFI and fortnightly weights (to calculate average daily gain (ADG) and maintenance as metabolic mid-weight (MMWT)) are measured. Recording NFIp is costly, and shortening the test length would be advantageous. However, research has shown that ADG cannot be accurately measured from a shortened test. Genetic NFI EBVs (NFIg) were calculated using DFI EBV adjusted for ADG and MMWT EBV and were shown to have a Pearson correlation of 0.99 with the NFIp EBV from 3,088 Angus steers. The regression slope between NFIg and NFIp EBVs was 1.14. Alternative NFIg models where growth and maintenance requirements were obtained from BREEDPLAN live weight traits instead of live weights recorded in the test period, demonstrated high Pearson correlations (r=0.87 to 0.93) and regression slopes between 0.63 and 0.97 with NFIp EBVs. Results suggest that genetic NFI EBVs can be obtained, with growth and maintenance requirements being determined from BREEDPLAN live weight traits. This provides the opportunity to determine if the length of the test to measure DFI can be shortened, reducing the cost of recording NFI per animal.
- PublicationRemodelling the genetic evaluation of NFI in beef cattle - Part 2: Shortening the length of the feed intake test(Association for the Advancement of Animal Breeding and Genetics (AAABG), 2023-07-26)
; ; ; ; ; ; ; BREEDPLAN net feed intake (NFI) EBV is derived from a phenotypic regression based on a 70-day feed intake test. Genetic NFI (NFIg) EBVs have been proposed as an alternative EBV and this recent development may also allow for a shortened feed intake test period. This study used feed intake records of 3,088 Angus steers from the full 70-day test and compared them to daily feed intake (DFI) from shortened test periods. Results showed DFI from shortened test periods had similar means but increased phenotypic variation. Phenotypic correlation with DFI from the full test period decreased as the test period decreased in weekly intervals and ranged between 0.75 and 0.99. NFIg EBVs were predicted using DFI from different length tests. The mean of all NFIg EBVs was close to zero, but the EBV standard deviation increased as the test period decreased. Pearson correlations between NFIg EBVs from a full test period and reduced test periods ranged between 0.73 and 0.99, the regression slope of NFIg from reduced test periods on NFIg from the full test period ranged between 0.73 and 0.95, and the bias ranged between 0.00 and 0.02. These results indicate that as the test period decreases, the spread of EBVs increases, resulting in extreme animals having overestimated NFIg EBVs. A shortened DFI test period could be used to estimate NFIg EBVs.
- PublicationImplementation of single-step genomic BREEDPLAN evaluations in Australian beef cattle(Massey University, 2018)
; ; ; ; ; ; ; Single-step GBLUP (ssGBLUP) procedures have now been implemented into Australia's BREEDPLAN genetic evaluation system for beef cattle. This major remodelling required the development of many new features and modifications to existing procedures. The first requirement was the construction of a flexible but robust set of procedures for handling and processing of raw SNP genotypes to enable the construction of suitable genomic relationship matrices. The analytical processes were modified to replace with and for the explicit fitting of genetic groups. A new accuracy algorithm was developed and the solver was revised. Examples from Australian Angus and Brahman breeds comparing current BLUP evaluation with ssGBLUP are presented to show the resultant changes and effects of implementing the new genomic evaluations. - PublicationImputation of microsatellite alleles from dense SNP genotypes for parentage verification across multiple 'Bos taurus' and 'Bos indicus' breeds(Frontiers Research Foundation, 2013)
;McClure, M C ;Sonstegard, Tad S ;Regitano, Luciana C A ;Albuquerque, Milla ;Silva, Marcos V G B ;Machado, Marco A ;Coffey, Mike; ;Boscher, Marie-Yvonne ;Genestout, Lucie ;Mazza, Raffaele ;Taylor, Jeremy F ;Wiggans, George R ;Schnabel, Robert D ;Simpson, Barry ;Marques, Elisa ;McEwan, J C ;Cromie, A ;Coutinho, Luiz L ;Kuehn, Larry A ;Keele, J W ;Piper, Emily K; ;Van Eenennaam, Alison L ;Williams, Robert ;Bovine HapMap Consortium, ;Van Tassell, Curtis P ;Weber, Kristina L ;Penedo, Cecilia T ;Berry, Donagh P ;Flynn, John ;Garcia, Jose FCarmo, Adriana STo assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set ('N' = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds ('Bos taurus' and 'B. indicus') were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds ('N' = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ≤1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset.