QTL detection for milk production traits in goats using a longitudinal model

Summary Eight paternal half-sib families were used to identify chromosomal regions associated with variation in the lactation curves of dairy goats. DNA samples from 162 animals were amplified by PCR for 37 microsatellite markers, from Capra hircus autosomes CHI3, CHI6, CHI14 and CHI20. Milk samples were collected during 6 years, and there were 897 records for milk yield (MY) and 814 for fat (FP) and protein percentage (PP). The analysis was conducted in two stages. First, a random regression model with several fixed effects was fitted to describe the lactation function, using a scale (α) plus four shape parameters: β and γ, both associated with a decrease in the slope of the curve, and δ and φ that are related to the increase in slope. Predictions of α, β, γ, δ and φ were regressed using an interval mapping model, and F-tests were used to test for quantitative trait loci (QTL) effects. Significant (p < 0.05) QTLs were found for: (i) MY: CHI6 at 70-80 cM for all parameters; CHI14 at 14 cM for δ and φ; (ii) FP: CHI14, at 63 cM was associated with β; CHI20, at 72 cM, showed association with α; (iii) PP: chromosomal regions associated with β were found at 59 cM in CHI3 and at 55 cM in CHI20 with α and γ. Analyses using more families and more animals will be useful to confirm or to reject these findings. © 2008 Blackwell Verlag, Berlin.Fil: Roldán, D.L.. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Genética; ArgentinaFil: Rabasa, Alicia Elvira. Universidad Nacional de Tucumán. Facultad de Agronomía y Zootecnia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Saldaño, S.. Universidad Nacional de Tucumán. Facultad de Agronomía y Zootecnia; ArgentinaFil: Holgado, F.. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Tucuman-santiago del Estero. Campo Experimental Regional Leales; ArgentinaFil: Poli, M. A.. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Genética; ArgentinaFil: Cantet, Rodolfo Juan Carlos. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Animal; Argentin

Genomic characterisation of CC398 MRSA causing severe disease in Australia

Clonal complex 398 (CC398) livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) has been reported worldwide in a variety of food-animal species. Although CC398 is synonymous with LA-MRSA, community-associated MRSA (CA-MRSA) variants have emerged, including the Panton–Valentine leukocidin (PVL)-positive ST398-V and ST398 single-locus variant ST1232-V, and the PVL-negative ST398-V clones. Using comparative genomic analysis, we determined whether ten CC398 MRSA bacteraemia episodes recently identified in Australia were due to LA-MRSA or CA-MRSA CC398. Isolates were sourced from the Australian Group on Antimicrobial Resistance S. aureus surveillance programme and episodes occurred across Australia. Whole-genome sequencing (WGS) and phylogenetic comparison of the ten CC398 bacteraemia isolates with previously published CC398 MRSA whole-genome sequences identified that the Australian CC398 isolates were closely related to the human-associated II-GOI clade and the livestock-associated IIa clade. The identified CC398 MRSA clones were: PVL-positive ST1232-V (5C2&5), PVL-negative community-associated ST398-V (5C2&5) and livestock-associated ST398-V (5C2&5). Our findings demonstrate the importance of using WGS and comparing the sequences with international sequences to distinguish between CC398 CA-MRSA and LA-MRSA and to determine the isolates’ origin. Furthermore, our findings suggest that CC398 CA-MRSA has become established in the Australian community and that ST398-V (5C2&5) LA-MRSA is now widespread in Australian piggeries. Our study emphasises the need for national One Health antimicrobial resistance surveillance programmes to assist in monitoring the ongoing epidemiology of MRSA and other clinically significant antimicrobial-resistant organisms

1000 Bull Genomes Consortium Project

Genomic selection, where selection decisions are based on estimates of breeding value from genome wide-marker effects, has enormous potential to improve genetic gain in dairy and beef cattle. Although successful in dairy cattle, some major challenges remain 1) only a proportion of the genetic variance is captured, particularly for some traits 2) marker effects are rarely consistent across breeds, 3) accuracy of genomic predictions decays rapidly over time. Using full genome sequences rather than DNA markers in genomic selection could address these challenges. However, sequencing all individuals in the very large resource populations required to estimate the typically small effects of mutations on target traits would be prohibitively expensive. An alternative is to sequence key ancestors contributing most of the genetic material of the current population, and to use this reference for imputation of sequence from SNP chip data. The reference set must still be large, in order to capture for example, rare variants which are likely to explain some of the variation in our target traits. Recognising the need for a comprehensive “reference set” of key ancestors by many groups undertaking cattle research and cattle breeding programs, we have initiated the 1000 bull genomes project. The project will assemble whole genome sequences of cattle from institutions around the world, to provide an extended data base for imputation of genetic variants. This will enable the bovine genomics community to impute full genome sequence from SNP genotypes, and then use this data for genomic selection, and rapid discovery of causal mutations. Some preliminary results from the variant detection pipeline will be reported

1000 Bull Genomes Consortium Project

Genomic selection, where selection decisions are based on estimates of breeding value from genome wide-marker effects, has enormous potential to improve genetic gain in dairy and beef cattle. Although successful in dairy cattle, some major challenges remain 1) only a proportion of the genetic variance is captured, particularly for some traits 2) marker effects are rarely consistent across breeds, 3) accuracy of genomic predictions decays rapidly over time. Using full genome sequences rather than DNA markers in genomic selection could address these challenges. However, sequencing all individuals in the very large resource populations required to estimate the typically small effects of mutations on target traits would be prohibitively expensive. An alternative is to sequence key ancestors contributing most of the genetic material of the current population, and to use this reference for imputation of sequence from SNP chip data. The reference set must still be large, in order to capture for example, rare variants which are likely to explain some of the variation in our target traits. Recognising the need for a comprehensive “reference set” of key ancestors by many groups undertaking cattle research and cattle breeding programs, we have initiated the 1000 bull genomes project. The project will assemble whole genome sequences of cattle from institutions around the world, to provide an extended data base for imputation of genetic variants. This will enable the bovine genomics community to impute full genome sequence from SNP genotypes, and then use this data for genomic selection, and rapid discovery of causal mutations. Some preliminary results from the variant detection pipeline will be reported