Bioinformatic analysis of lameness and hoof disease traits in dairy cattle with the emphasis on epistasis

Leader investigator: Joanna Szyda
Period of work: 36 months
Funded: National Science Centre

Objectives

The aim of the project was to a better understanding of genetics underlying hoof diseases and lameness. Traits related to hoof diseases and lameness are called novel traits since their phenotypes have been collected only recently, and thus their genetic background has not yet been extensively studied. However, this group of traits play important role in breeding and management. Lameness can cause economic losses due to lower production and fertility. Therefore, the objective of the project is to analyze the genetic determinants of traits describing hoof and leg quality in the context of the causes lameness of dairy cattle, with particular emphasis on epistatic effects. Traits inclueded in this project were : hoof health status defined by a veterinarian (HSV) (heritabilitiy of 25%), by a claw trimmer (HSC) (heritabilitiy of 28%), and the total number of hoof disorders (NHD) (heritabilitiy of 8%).

The dataset consists of hoof and leg quality trait values and 76 934 SNP genotypes for 985 Braunvieh cows and 1998 Fleckvieh cows. Moreover, we also have the information about SNP locations, pedigree and culling of individuals (the number of culled animals ad culling reasons), some additional variables such as the date of birth and the number of finished lactations are available as well. The data set was made available by the courtesy of ZuchtData EDV-Dienstleistungen GmbH.

The preliminary analysis of available data showed that 2.04% all culled cows and 4.80% of cows culled due to health problems or low productivity were removed from herds because of hoof hood or leg disorders. The main causes of culling are age (48.97%), low fertility (24.50%) and udder diseases (13.07%).

annotation

fig1. Significant epistatic effects for the number of claw disorders.

 

fig 2 . A,B before removing polymorphisms with the call rate below 95% and polymorphisms with the minor allele frequency below 5%. C,D after removing polymorphisms with the call rate below 95% and polymorphisms with the minor allele frequency below 5%

Methodology
1) dataset

The analyzed data set contain iformation of hoof disorders scored for Braunvieh and Fleckvieh cows durring different parities within the frame of the “Efficient Cow” project. For each individual, three lameness-related traits collected scored until 100th of lactation: hoof health status defined by a veterinarian (HSV) [binary], hoof health status defined by a claw trimmer (HSC) [binary], and the total number of hoof disorders (NHD) [discrete values between 0 and 5].  2,977 cows (including both breeds) had records for HSV trait and 1,513 for HSC and NHD. For each individual breeding values were estimated (EV). Each individual was genotyped with the GeneSeek® Genomic ProfilerTM HD panel consisting of 76,934 SNPs. After quality contror of a minor allele frequency (MAF) of at least 0.01 and technical quality of genotyping expressed by a minimum call rate of 99%, 74,762 SNPs remained for further analysis.

fig.3 The indicidents rate of found nr of hoof disorders in two cattle populations from none leg disdorder:0, to more then five: >=5

2) whole genome analysis

We applied first-stage genome-wide analysis study (GWAS) usuing SNPs from HD panel. Second-stage GWAS was done based on SNPs from whole genome sequence, where significant region identied from first-stage GWAS were imputed separately for each breed using Beagle 4 software. We also performed a GWAS were phenotypic values were represented by pseudophenotypes, which were estimated breeding values (EV) for each individual estimated for the total number of leg disorders. EV were estimated by using ASReml software.

Results

Based on the first-stage GWAS with SNPS from the HD panel, seven significant genomic regions were defined identified: BTA1 including the TOPBP1 gene; BTA7 including the RIOK2 and RGMB genes; BTA13 including the C13H20orf194; regions on BTA14 which inclued RRM2B and NCALD genes on first and STK3 gene on second region; BTA15 including FAM168A and PLEKHB1 genes; BTA22 including PTPRG gene. Based on the results from second-stage GWAS 23 SNPs were defined as significant located region on BTA15. Results from last GWAS where as phenotypes were resperented by pseudophenotypes of EV, showed that Based on the false discovery rate of maximum 10%, 16 SNPs located on BTA1, BTA4, BTA5, BTA6, BTA13, BTA14, BTA16 and BTA24.

fig.4  The X-axis marks SNP positions in bp, the Y-axis represents –log10(P), visualize genomic context was done for the most significant SNPs for hoof HSC mapped to ARS-UCD1.2 assembly.

Conclusions

Genomic regions with significant SNP effects on hoof health status and potential candidate genes were found, throughout different analysis.

Acknowledgements

NCN grant No. 2015/19/B/NZ9/03725 as well as by the Efficient Cow and the Gene2Farm projects