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Reducing calf mortality by identifying lethal genes and improving survival index

  • AU project leader: Goutam Sahana
  • Funded by: VikingGenetics
  • Total budget: 2,925,792.00 DKK (GUDP’s contribution 2,768,813.00 DKK)
  • Project duration: 1st January 2017 – 31st December 2018.

Project description

In Denmark, 30,849 stillbirths (died within 24 hours of birth) were recorded out of total 572,498 calving in 2014 (Årsstatistik Avl 2014/2015). The juvenile death rates among heifer calves born between 2008 and 2012 varied from 7.5% for Holstein to 14.0% in Jersey; the figures for bull claves are 10% and 21.3% respectively (Årsstatistik Avl 2014/2015). In total there are about 40,000 young calves’ mortality (excluding stillbirths) per year in Denmark (Jørn Pedersen, SEGES, pers. comm.). Part of these deaths is due to gene mutations which are lethal when present in homozygous state, i.e. both copies of the gene are defective. The cost of losing a dairy calf during the rearing period is relatively high compared to early embryo loss. Loss of calves and young stock during the rearing period result in loss of revenue for the farmer due to e.g. fewer heifers available for replacement in the production system, fewer male calves for slaughter, higher veterinarian cost and cost related to disposal of dead calf. In addition, it poses a serious animal welfare issue and, thereby, a risk to the dairy industry. The success of the dairy industry depends on the public perception of its products and production methods, and increased public concerns regarding modern animal production, particularly animal welfare, may put the future of dairy industry at risk.

The overall goal of this project is to reduce calf mortality in cattle and during the rearing period. The goal will be achieved by: 1) removing harmful mutations causing stillbirth, calf and young stock mortality, and 2) increasing reliability of breeding values for survival by including genetic markers for survival related phenotypes namely calving, young-stock survival, fertility and longevity.

During recent years, the number of Danish dairy cattle with genotype information has increased rapidly. In combination with the latest developments in genetic evaluation for young stock survival creates an opportunity to identify harmful mutations causing stillbirth and young-stock mortality. Following identification, it is possible to remove the mutations from populations. The removal of harmful mutations from the dairy cattle population will reduce in calves and young-stocks mortality, and thereby reduce the costs per live cattle produced for the farmer. The increased reliability of breeding values for survival will increase the genetic improvement of survival. Since November 2014, Nordic Cattle Genetic Evaluation publishes 4 indexes for young-stock survival (YSS). A one percent unit increase in survival rate for all the 4 indices would be worth 36 million Danish Kroner (Jørn Pedersen, SEGES pers. Comm.). The successful implementation of this project is expected to increase the survival rate by 0.2% per year translating 7.3 million DKK more profit per year for the Danish dairy cattle farmers. In addition, better survival will reduce the climate and environmental impact per unit of product in addition to increasing animal welfare and sustainable use of resources.


The goal of the project will be obtained through three objectives, which are:

  1. To identify causal mutations / diagnostic SNPs for stillbirth and young-stock mortality
  2. To improve genomic prediction models for survival related phenotypes by incorporating information about identified genes/markers to 50k genotype data
  3. To adapt a breeding plan to reduce the frequencies of the deleterious mutations.

Work packages

The project is divided into three work packages (WPs), each addressing one of the objectives above:

  1. WP1 will identify deleterious mutations causing stillbirth and young-stock mortality; and identify the diagnostic markers which can determine the carrier status of the animals.
  2. WP2 will improve genomic prediction models by including QTL-markers in order to increase the reliability of breeding values
  3. WP3 will implement a breeding strategy to reduce the frequency of deleterious mutations responsible for stillbirth and young-stock mortality