New Zealand cooperative Livestock Improvement Company has identified genetic variations affecting milk composition in dairy cows.
All cows carry the so-called ‘fat gene’ known as AGPAT6, but LIC senior scientist Dr Matt Littlejohn says the variances they’ve found give a genetic explanation as to why some cows produce higher fat content in their milk than others.
“If you think of milk production in the cow’s udder as a factory assembly line, this variation is one of a few workers in the ‘fat chain’, with that worker being very efficient in some cows, and a bit lazy in others.
“The finding of AGPAT6 helps us to better understand what goes on in a cow’s mammary gland and how milk composition is regulated by genes,” said Dr Littlejohn.
The finding, published by leading international scientific journal PLOS ONE, will be used to help further improve the accuracy of the farmer-owned co-operative’s genomic selection programme for AB sires, and to further drive genetic gain improvements of the NZ dairy herd.
The finding is one of only a few examples worldwide where the underlying gene leading to differences in milk composition has been identified.
The variation was identified as part of LIC’s DNA sequencing program, that seeks to map variations in genes of a cow’s DNA that affect production and health. This will create a bank of variations to be used to increase the accuracy of genomic selection.
Included in its earlier discoveries are the Small Calf Syndrome gene and one causing loss of pregnancy in cows. It utilises part of a large sequencing dataset developed by LIC scientists and co-funded by Ministry for Primary Industries through the Transforming the Dairy Value Chain Primary Growth Partnership programme, led by Fonterra and DairyNZ.
Dr Littlejohn says the sequencing work is a bit like putting together the pieces of a cow puzzle – the more you put together, the clearer the overall picture becomes for genomic selection and identification of which sires are likely to perform best.
“The real gains will come when we can work out more of the genes and variants that we know are out there. Pile them all together and you can have quite big effects, especially in the context of genomic selection.”