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More efficient and accurate dairy breeding

Genomic research in farm animals has the potential to make a substantial difference to New Zealand’s primary production.

Agricultural genomics is the study of the effects of genetic variation and selection used to propagate valuable heritable trait combinations in crop plants and farm animals. Genomic technology not only improves the precision of predicting the breeding values for livestock selection, but also allows the industry to evaluate an animal’s potential for traits that are difficult and/or expensive to measure in the live animal such as meat characteristics.

Based at both the AL Rae Centre of Massey University and Livestock Improvement Corporation (LIC), Yu Wang is working in the Genomics Aotearoa Better Breeding Values project with Dorian Garrick and Christine Couldrey to further develop and implement a pipeline to help selection decisions in the New Zealand dairy industry. The project involves imputation of low and high-density SNP chip data to whole genome sequence level, utilising these imputed data for genome-wide association studies and single-step genomic prediction.

Yu Wang

Yu Wang

Yu explains that traditionally genomic selection has been limited to a relatively small number of genetic markers genotyped on SNP chip arrays. Now, an increasing availability of next-generation technologies allows genomic prediction to be based on whole genome sequencing (WGS) data.

The use of tens of millions of SNPs from these whole genome sequences in animal breeding schemes is expected to improve predictive ability - SNPs (single nucleotide polymorphisms) being the most common type of genetic variation in DNA. But for genomic selection to be sufficiently accurate to be useful, thousands of animals may need to be genotyped per year, which may be cost prohibitive. Costs may be lowered considerably by using a combination of high and low-density SNP chip panels, where animals genotyped with the low-density SNP panel are imputed. Imputation is the process of replacing missing data with substituted values up to high density and whole genome sequence.

Yu is streamlining processes, including looking at what software to use and to produce the most accurate and efficient methodology. It’s hoped this will eventually help to make genomic selection more available to New Zealand farmers. The pipeline may then be suitable for other primary industries to use, and the tools and technologies will also potentially assist with genomic predictors to improve outcomes for endangered animal species.

About Yu Wang

Yu is originally from China. Prior to moving to New Zealand, she spent five years studying animal breeding and genetics in the Netherlands, Austria and Germany. Several of her research projects related to quantitative genetics and genomics in dairy cows. In 2018, she achieved her PhD at the University of Hohenheim; her project was aimed at developing selection methods in the production and conservation of local livestock populations.

Yu attended the 11th World Congress on Genetics Applied to Livestock Production in Auckland at the beginning of 2018, where she got the chance to have a closer look at the dairy industry and relevant research in New Zealand. She says she was then thrilled to get a job with Genomics Aotearoa, working again with cows and being at the forefront of genomic selection technologies.

“The most attractive point of this position to me is that I get the chance to work and collaborate with both the research institute and dairy industry, that I get to know how my knowledge can be directly used in practice. It is also a unique experience of working with scientists with variety of background and expertise, which is also a valuable opportunity to learn and improve myself.”

Yu’s areas of expertise:

  • Animal breeding and genetics
  • Quantitative genetics
  • Conservation genetics
  • Genomics