Reproductive productivity depend on a complex set of characteristics. The number of piglets at birth (Total number born, Litter size, TNB) and the number of alive piglets at birth (Total number born alive, NBA) are the main indicators of the reproductive productivity of sows in pig breeding. Great hopes are pinned on GWAS (Genome-Wide Association Studies) to solve the problems associated with studying the genetic architecture of reproductive traits of pigs. This paper provides an overview of international studies on SNP (Single nucleotide polymorphism) associated with TNB and NBA in pigs presented in PigQTLdb as “Genome map association”. Currently on the base of Genome map association results 306 SNPs associated with TNB (218 SNPs) and NBA (88 SNPs) have been identified and presented in the Pig QTLdb database. The results are based on research of pigs such as Large White, Yorkshire, Landrace, Berkshire, Duroc and Erhualian. The presented review shows that most SNPs found in chromosome areas where candidate genes or QTLs (Quantitative trait locus) have been identified. Further research in the given direction will allow to obtain new data that will become an impulse for creating breakthrough breeding technologies and increase the production efficiency in pig farming.

Reindeer herding is the historical branch of animal husbandry in the northern regions of the Russian Federation. There are four reindeer breeds, the most numerous of which is Nenets (with over 800,000 reindeer). For further development of the reindeer herding, in addition to traditional breeding methods, it is necessary to apply modern technologies, such as genetic analysis. The aim of the current work was to identify the possible association between microsatellites loci and phenotypic traits of the Nenets reindeer breed. DNA was extracted from tissue samples of 43 female individuals using Nextech column (Agrobiogen Biotechnologie GmbH, Munich, Germany) according to the manufacturer’s recommendations. Fourteen microsatellite loci (NVHRT21, NVHRT24, NVHRT76, RT1, RT6, RT7, RT9, RT27, RT30, RT25, RT13, NVHRT03, RT5, and NVHRT73) were selected to examine the associations between marker genotypes and eight phenotypic traits: height at the withers (HaW), chest depth (CD), chest width (CW), chest girth (CG), wrist girth (WG), body length (BL), head length (HL), and body weight (BW). Associations between the genotypes and the traits were evaluated using the one-way ANOVA model. Results were considered statistically significant if the P-value was less than 0.05. All of the microsatellites loci were polymorphic, and the number of alleles ranged from three (NVHRT03) to six (RT25 and NVHRT73). The RT6 marker was associated with four traits: BW (P < 0.001), CG (P < 0.05) BL (P < 0.01), HL (P < 0.01), whereas the RT27 marker was linked to three traits: HaW (P < 0.05), BW (P < 0.05), and HL (P < 0.01). The variability of the HL trait was also associated with two loci: RT25 (P < 0.05) and NV 24 (P < 0.001). The RT30 marker was only significantly associated with height at the withers (P < 0.05). Thus, our study revealed that five microsatellite loci were significantly associated with five phenotypically important traits (HaW, HL, BW, CG, and BL), and these markers could be potentially used for the improvement of the reindeer herding breeding program. This research was funded by Russian scientific foundation project No. 16-16-10068. Copyright © 2017. American Society of Animal Science .

Breeding practices adopted at different farms are aimed at maximizing the profitability of pig farming. In this work, we have analyzed the genetic diversity of Large White pigs in Russia. We compared genomes of historic and modern Large White Russian breeds using 271 pig samples. We have identified 120 candidate regions associated with the differentiation of modern and historic pigs and analyzed genomic differences between the modern farms. The identified genes were associated with height, fitness, conformation, reproductive performance, and meat quality.

Replacement pigs’ genomic prediction for reproduction (total number and born alive piglets in the first parity), meat, fatness and growth traits (muscle depth, days to 100 kg and backfat thickness over 6–7 rib) was tested using single-step genomic best linear unbiased prediction ssGBLUP methodology. These traits were selected as the most economically significant and different in terms of heritability. The heritability for meat, fatness and growth traits varied from 0.17 to 0.39 and for reproduction traits from 0.12 to 0.14. We confirm from our data that ssGBLUP is the most appropriate method of genomic evaluation. The validation of genomic predictions was performed by calculating the correlation between preliminary GEBV (based on pedigree and genomic data only) with high reliable conventional estimates (EBV) (based on pedigree, own phenotype and offspring records) of validating animals. Validation datasets include 151 and 110 individuals for reproduction, meat and fattening traits, respectively. The level of correlation (r) between EBV and GEBV scores varied from +0.44 to +0.55 for meat and fatness traits, and from +0.75 to +0.77 for reproduction traits. Average breeding value (EBV) of group selected on genomic evaluation basis exceeded the group selected on parental average estimates by 22, 24 and 66% for muscle depth, days to 100 kg and backfat thickness over 6–7 rib, respectively. Prediction based on SNP markers data and parental estimates showed a significant increase in the reliability of low heritable reproduction traits (about 40%), which is equivalent to including information about 10 additional descendants for sows and 20 additional descendants for boars in the evaluation dataset.

The aim of this study was to determine the associations between genotypes of the prolactin receptor gene (PRLR) and reproductive, growth, and meat traits in pigs. Genetic groups of sows were used: Large White (LW), Danish Landrace (LD), and Landrace × Yorkshire × Duroc hybrids (L × Y × D). Reproductive traits studied were the total number of born (TNB) and the number born alive (NBA). The growth traits were the number of days to 100 kg and the average daily gains (ADG). The meat traits were the average backfat thickness (BFT), half carcass weight (HCW), area of M. longissimus dorsi (MLT), and lean meat content (LM). The polymorphism was detected using the polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP) method. It was found that the genotype BB is associated with the best NBA. In sows LD, the AB genotype is associated with best number of days to 100 kg; in hybrids L × Y × D, the AA genotype is associated with better meat traits as compared to the genotype BB.

Intensive selection raises the efficiency of pig farming considerably, but it also promotes the accumulation of homozygosity, which can lead to an increase in inbreeding and the accumulation of deleterious variation. The analysis of segments homozygous-by-descent (HBD) and non-HBD segments in purebred and crossbred pigs is of great interest. Research was carried out on 657 pigs, of which there were Large White (LW, n = 280), Landrace (LR, n = 218) and F1 female (♂LR × ♀LW) (F1, n = 159). Genotyping was performed using the GeneSeek^® GGP Porcine HD Genomic Profiler v1 (Illumina Inc., USA). To identify HBD segments and estimate autozygosity (inbreeding coefficient), we used the multiple HBD classes model. LW pigs exhibited 50,420 HBD segments, an average of 180 per animal; LR pigs exhibited 33,586 HBD segments, an average of 154 per animal; F1 pigs exhibited 21,068 HBD segments, an average of 132 per animal. The longest HBD segments in LW were presented in SSC1, SSC13 and SSC15; in LR, in SSC1; and in F1, in SSC15. In these segments, 3898 SNPs localized in 1252 genes were identified. These areas overlap with 441 QTLs (SSC1—238 QTLs; SSC13—101 QTLs; and SSC15—102 QTLs), including 174 QTLs for meat and carcass traits (84 QTLs—fatness), 127 QTLs for reproduction traits (100 QTLs—litter traits), 101 for production traits (69 QTLs—growth and 30 QTLs—feed intake), 21 QTLs for exterior traits (9 QTLs—conformation) and 18 QTLs for health traits (13 QTLs—blood parameters). Thirty SNPs were missense variants. Whilst estimating the potential for deleterious variation, six SNPs localized in the NEDD4, SEC11C, DCP1A, CCT8, PKP4 and TENM3 genes were identified, which may show deleterious variation. A high frequency of potential deleterious variation was noted for LR in DCP1A, and for LW in TENM3 and PKP4. In all cases, the genotype frequencies in F1 were intermediate between LR and LW. The findings presented in our work show the promise of genome scanning for HBD as a strategy for studying population history, identifying genomic regions and genes associated with important economic traits, as well as deleterious variation.