SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification

McClure, Matthew; McCarthy, Jean; Flynn, Paul; McClure, Jennifer C.; Dair, Emma; OConnell, Donnamarie; Kearney, John F.

doi:10.3389/fgene.2018.00084

Cited by 43 publications

(31 citation statements)

References 33 publications

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“…The conflict rate for sires of cows in the Mexican population was similar to the 7 to 12% reported recently for other populations. An incorrect sire was detected for 7% of the German Angeln dairy cattle population (Sanders et al, 2006), and a rate of 7 to 9% was reported for pedigree errors nationally in Ireland (McClure et al, 2018). For Holstein cows sired by AI bulls, the error rate was 11% in the United States (Banos et al, 2001) and 12% in Israel (Weller et al, 2004).…”

Section: Parentage Validationmentioning

confidence: 97%

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population

García-Ruiz

Wiggans

Ruiz-López

2019

Journal of Dairy Science

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Genealogical information is an essential tool for carrying out any genetic improvement program. The objective of this study was to determine the accuracy of pedigree information in the Mexican registered Holstein population using genomic data available in Mexico and for the US Holstein population. The study included 7,508 animals (158 sires and 7,350 cows) that were born from 2002 through 2014, registered with Holstein de México, and genotyped with single nucleotide polymorphism arrays of different densities. Parentage could not be validated for 17% of sires of cows and 12% of sires of bulls. Most (79%) of the dams of cows and the dams of bulls had no genotype available and could not be validated. A parentage test was possible for only 6,104 sires of cows, 139 sires of bulls, 1,519 dams of cows, and 33 dams of bulls. Of the animals with a parentage test, parent assignment was confirmed for 89% of sires of cows, 92% of dams of cows, 95% of sires of bulls, and 97% of dams of bulls. Parent discovery was possible for some animals without confirmed parents: 17% for sires of cows, 2.5% for dams of cows, 43% for sires of bulls, and 0% for dams of bulls. Of the 7,795 progeny tests, 777 had parent conflicts, which is an error rate of 9.97% for parental recording in the population, a rate that is similar to those recently reported for other populations. True parents for some progeny conflicts (15%) were discovered for the Mexican population, and the remaining parents were assigned as unknown. Expected effects of misidentification on rate of genetic gain could be decreased by half if genealogical errors were decreased to 5%. This study indicates that genotyping and genealogy recovery may help in increasing rates of genetic improvement in the Mexican registered Holstein population.

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Section: Parentage Validationmentioning

confidence: 97%

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population

García-Ruiz

Wiggans

Ruiz-López

2019

Journal of Dairy Science

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“…This pattern is especially evident among breeders of domestic cattle and sheep (Table ). Not coincidentally, the cattle breeding field has arrived at a preliminary consensus that 500 or more SNPs are required to resolve parentage confidently (e.g., McClure et al, ; McClure et al, ), whereas fields using modern analytical methods tend to conclude that 100–200 SNPs are usually more than adequate (Abadía‐Cardoso, Anderson, Pearse, & Garza, ; Dussault & Boulding, ; Steele et al, ). The reason that exclusion performs less well than formal maximum‐likelihood approaches is that it requires implicit assumptions that are ill defined and it discards much of the data.…”

Section: Approaches To Parentage Analysismentioning

confidence: 99%

The future of parentage analysis: From microsatellites to SNPs and beyond

2019

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Parentage analysis is a cornerstone of molecular ecology that has delivered fundamental insights into behaviour, ecology and evolution. Microsatellite markers have long been the king of parentage, their hypervariable nature conferring sufficient power to correctly assign offspring to parents. However, microsatellite markers have seen a sharp decline in use with the rise of next‐generation sequencing technologies, especially in the study of population genetics and local adaptation. The time is ripe to review the current state of parentage analysis and see how it stands to be affected by the emergence of next‐generation sequencing approaches. We find that single nucleotide polymorphisms (SNPs), the typical next‐generation sequencing marker, remain underutilized in parentage analysis but are gaining momentum, with 58 SNP‐based parentage analyses published thus far. Many of these papers, particularly the earlier ones, compare the power of SNPs and microsatellites in a parentage context. In virtually every case, SNPs are at least as powerful as microsatellite markers. As few as 100–500 SNPs are sufficient to resolve parentage completely in most situations. We also provide an overview of the analytical programs that are commonly used and compatible with SNP data. As the next‐generation parentage enterprise grows, a reliance on likelihood and Bayesian approaches, as opposed to strict exclusion, will become increasingly important. We discuss some of the caveats surrounding the use of next‐generation sequencing data for parentage analysis and conclude that the future is bright for this important realm of molecular ecology.

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“…Since the availability of both the ISAG 100 and ISAG 200 panels for bovine parentage validation, more recent studies have highlighted the potential limitations of using a relatively small number of SNP (Strucken et al, 2016 ; McClure et al, 2018 ). Due to large-scale genotyping in most world countries the trend is toward large numbers of SNP in combination with different levels of quality control to ensure a high accuracy (McClure et al, 2018 ). The application of SNP based parentage is only cost-effective if it forms part of routine genotyping.…”

Section: Application Of Genomics In South Africamentioning

confidence: 99%

Genetic Improvement in South African Livestock: Can Genomics Bridge the Gap Between the Developed and Developing Sectors?

Marle-Köster

Visser

2018

Front. Genet.

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South Africa (SA) holds a unique position on the African continent with a rich diversity in terms of available livestock resources, vegetation, climatic regions and cultures. The livestock sector has been characterized by a dual system of a highly developed commercial sector using modern technology vs. a developing sector including emerging and smallholder farmers. Emerging farmers typically aim to join the commercial sector, but lag behind with regard to the use of modern genetic technologies, while smallholder farmers use traditional practices aimed at subsistence. Several factors influence potential application of genomics by the livestock industries, which include available research funding, socio-economic constraints and extension services. State funded Beef and Dairy genomic programs have been established with the aim of building reference populations for genomic selection with most of the potential beneficiaries in the well-developed commercial sector. The structure of the beef, dairy and small stock industries is fragmented and the outcomes of selection strategies are not perceived as an advantage by the processing industry or the consumer. The indigenous and local composites represent approximately 40% of the total beef and sheep populations and present valuable genetic resources. Genomic research has mostly provided insight on genetic biodiversity of these resources, with limited attention to novel phenotypes associated with adaptation or disease tolerance. Genetic improvement of livestock through genomic technology needs to address the role of adapted breeds in challenging environments, increasing reproductive and growth efficiency. National animal recording schemes contributed significantly to progress in the developed sector with regard to genetic evaluations and estimated breeding values (EBV) as a selection tool over the past three decades. The challenge remains on moving the focus to novel traits for increasing efficiency and addressing welfare and environmental issues. Genetic research programs are required that will be directed to bridge the gap between the elite breeders and the developing livestock sector. The aim of this review was to provide a perspective on the dichotomy in the South African livestock sector arguing that a realistic approach to the use of genomics in beef, dairy and small stock is required to ensure sustainable long term genetic progress.

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SNP Data Quality Control in a National Beef and Dairy Cattle System and Highly Accurate SNP Based Parentage Verification and Identification

Cited by 43 publications

References 33 publications

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population

Pedigree verification and parentage assignment using genomic information in the Mexican Holstein population

The future of parentage analysis: From microsatellites to SNPs and beyond

Genetic Improvement in South African Livestock: Can Genomics Bridge the Gap Between the Developed and Developing Sectors?

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