Search

Animal breeding programs can be improved by genetic markers associated with production and reproduction traits. Reproduction traits are important for economic success of pig production and therefore development of genetic tools for selection is of high interest to pig breeding. In this study our objective was to identify genomic regions associated with fertility traits in two Finnish pig breeds using large scale SNP genotyping and genome wide association analysis and characterization of copy number variations (CNV). Since CNVs are structural variations of the genome they potentially have a large effect on gene expression and protein function. We analyzed 1265 genotyped boars for nine different reproduction traits and identified 46 CNV regions encompassing 13 genes. 11 of the CNV regions were shared between the breeds, 20 were unique to the Finnish Yorkshire and 15 to the Finnish Landrace. The genome wide association (GWAS) analysis identified zero to five reproduction associated genomic regions per trait. Furthermore, we identified 23 genomic regions with 20 candidate genes associated with fertility traits using GWAS analysis. The identified CNV regions were compared against GWAS regions to detect candidate regions with an effect on reproduction traits. This study reports candidate genes and genomic regions within two Finnish pig breeds for reproduction traits, which can be utilized in breeding programs.

Mixed linear models have been applied for predicting breeding values of dairy cattle in most of the developed countries since the 1980s. However, the Russian Federation is still using the old contemporary comparison method. The objective of our study was to develop a best linear unbiased prediction (BLUP) for an animal model of breeding values for the Leningrad region. We tested both a first-lactation model (FLM) and a multi-lactation repeatability model (MLM). The data included milk records of 206 114 cows from 49 herds. Estimated heritabilities from FLM were 0.24, 0.20, and 0.20 for milk, protein, and fat yields, respectively, and 0.18, 0.19, and 0.20 from MLM. Repeatabilities were 0.34 for milk yield and 0.31 for both fat and protein yields. Genetic trends were similar for both models (FLM vs MLM): 59 vs 56 kg year-1 for milk, 1.90 vs 1.84 kg year-1 for fat, and 1.67 vs 1.62 kg year-1 for protein yield during 2000–2016. Based on the difference between the genetic trends in FLM and MLM, the applied BLUP method passed the validation method I by Interbull.

Holstein bulls and semen have been imported to Russia from Western countries since the 1970s. The objective of our study was to examine the effect of this introgression on genetic diversity between various commercial Holstein herds in the Leningrad region. A total of 803 Holstein cows from 13 herds were genotyped using the Illumina BovineSNP50 v.2 array. The pairwise Hudson’s estimator of Fst values between 13 herds varied from 0.002 to 0.015, which is less than values usually obtained between dairy cattle breeds (> 0.1). The mean of these pairwise Fst values revealed differences between herds depending, mainly, on the proportion of common sires shared between the herds. In addition, we investigated the cause of negative Fst values. Based on our results, these negative values could be interpreted as an excess of within-herd genetic diversity over the between-herds genetic diversity. Our results show that introgressions of Holstein genes into Russian Black and White cattle of the Leningrad region have created genetic separation between herds similar with those for Jersey cows in USA, Australia and New Zealand.

Agricultural research in boreal region today is more important than ever. Current challenges related to climate change, free market, common agricultural policy, food labelling and safety require new knowledge and solutions in farm and policy making levels. Also, global demand for safe and nutritious food and increased demand for animal products in developing countries give opportunities and poses responsibilities for food production in Northern hemisphere especially in boreal region where available water is not a limiting factor for food production. In order to fulfil the national and global demands, the long term goal of the agricultural research in boreal region should be the sustainable intensification of food production. In addition, a better use of by-products and efficient cycling of nutrients in all sectors of food chain is essential in the future. I hope Agricultural and Food Science is in the front line publishing the scientific articles related to these important topics.

The objective of this study was to estimate genetic parameters for longevity traits in Finnish pig populations. Analyzed traits were length of productive herd life (LPL), total number of parities (TNP), total number of piglets born (TNB), total number born alive (TBA) and stillborn (TSB), percentage stillborn (SB%), total number of piglets dead before weaning (TPM), mortality percentage (PM%), and total number weaned (TNW). Data contained litter records from 29 805 Finnish Landrace and 25 807 Finnish Yorkshire sows. Variance components were estimated using the AI-REML method. Heritability estimates varied from 0.06 to 0.11 in Finnish Landrace and from 0.09 to 0.12 in Finnish Yorkshire. Genetic correlations were high (> 0.9) between LPL, TNP, TNB, TBA, and TNW, and low between piglet mortality traits (SB% and PM%) and other longevity traits. The obtained heritability estimates indicate that there is sufficient genetic variation for selection.

The objective of the study was to relate estimated breeding values (EBVs) of the parents’ 305-days protein production and the bull dam herd-year characteristics to the empirical bias in pedigree indices (difference between the pedigree index and the final proof) of young bulls. Two animal model evaluations were carried out; one included records up to 1990 and the other up to spring 1992. The final data set included 242 bulls with pedigree indices, final proofs, parents’ EBVs, production and herd information (the size, the average production and the intraherd standard deviation) of the dams. The average empirical bias in pedigree indices was 13.6 kg. The correlation between the final proof of the bull and the EBVs of the bull sire or dam were 0.45 and 0.17, respectively. The low correlation with bull dam EBV indicates the unreliability of the bull dam EBVs. Size of the herd and the standard deviation of production in the herd when bull dam produced its third lactation were correlated with the empirical bias in pedigree index. Pedigree indices of the bulls coming from small herds with high intraherd standard deviation were more biased than those from the big herds with low intraherd standard deviation. The best bulls, when grouped according to their final proofs, were sons of the highest EBV sires. EBVs of bull dams did not differ in the highest and the lowest final proof groups, but the dams of the best bull group had a higher first lactation record than the dams of the other bull groups.