Litter Size In Pigs Research Articles

Information of Growth Traits Is Helpful for Genetic Evaluation of Litter Size in Pigs.

Litter size is an important trait in pig production. But selection accuracy for this trait is relatively low, compared with production traits. This study, for the first time, investigated the improvement of genetic evaluation of reproduction traits such as litter size in pigs using data of production traits as an additional information source. The data of number of piglets born alive per litter (NBA), age at 100 kg of body weight (Age100), and lean meet percentage (LMP) in a Yorkshire population were analyzed, using either a single-trait model or the multitrait model that allows us to account for environmental correlation between reproduction and production traits in the situation that one individual has only one record for a production trait while multiple records for a reproduction trait. Accuracy of genetic evaluation using single-trait and multitrait models were assessed by model-based accuracy (Rm) and validation accuracy (Rv). Two validation scenarios were considered. One scenario (Valid_r1) was that the individuals did not have a record of NBA, but Age100 and LMP. The other (Valid_r2) was that the individuals did not have a record for all the three traits. The estimate of heritability was 0.279 for Age100, 0.371 for LMP, and 0.076 for NBA. Genetic correlation was 0.308 between Age100 and LMP, 0.369 between Age100 and NBA, and 0.022 between LMP and NBA. Compared with the single-trait model, the multitrait model including Age100 increased prediction accuracy for NBA by 3.6 percentage points in Rm and 5.9 percentage points in Rv for the scenario of Valid_r1. The increase was 1.8 percentage points in Rm and 3.8 percentage points in Rv for the scenario of Valid_r2. Age100 also gained in the multitrait model but was smaller than NBA. However, LMP did not benefit from a multitrait model and did not have a positive contribution to genetic evaluation for NBA. In addition, the multitrait model, in general, slightly reduced level bias but not dispersion bias of genetic evaluation. According to these results, it is recommended to predict breeding values using a multitrait model including growth and reproduction traits.

116 Contribution of X-chromosome to the genetic variance of litter size and stillbirth in pigs

Abstract Genes with important roles in reproduction traits have been described in pig X-chromosome (SSCX), which may contribute considerably to genetic variance and could impact the accuracy of genomic prediction. The phenotypic data set includes information on 82,580 litter size records from 34,346 sows. Additionally, there were 108,006 in the pedigree, and genotypes for 41,492 SNPs, of which 1,435 in SSCX, were available for 30,000 animals. Three different approaches were used to estimate variance components for the total number born and number of stillborn. In the first approach, only SNPs in the autosomes were used and the model included the additive genetic (u), permanent environment (p), and residual (e) random effects. In the second approach, the same model was adopted; however, the data included SNPs in the autosomes and in the X chromosome. For both models, it was assumed that u~N(0,H⊗Vu), e~N(0,I⊗Ve) and p~N(0,I⊗Vp), wherein H is a relationship matrix that combines pedigree and genomic information; and, Vu, Vp, and Ve are the (co)variance matrices for the random additive genetic, permanent environment, and residual effects, respectively. In the third approach, the random additive genetic effects associated with the X-chromosome (s) were included in the model described before. Then, it was assumed that s~N(0,Hx⊗Vs), where Hx is the genomic relationship matrix for the X-chromosome and Vs is the additive genetic variance associated with the SSCX. All analyses were carried out using GIBBSF90+. Table 1 shows variance components for the three approaches. For both traits, additive genetic variance and heritabilities were similar across the approaches. The additive genetic variance for the SSCX was small, accounting for approximately two percent of the total additive genetic variance. Including the X chromosome as a separate effect and using Hx as a covariance matrix captured only a small part of the additive genetic variance. The additive variance across approaches did not differ. For total number born and number of stillborn, using the SSCX SNPs to build Hx did not provide extra benefit compared with fitting those SNP in the regular H matrix.

Association between polymorphisms in NOBOX and litter size traits in Xiangsu pigs.

The newborn ovary homeobox gene (NOBOX) regulates ovarian and early oocyte development, and thus plays an essential role in reproduction. In this study, the mRNA expression level and single nucleotide polymorphism (SNP) of NOBOX in various tissues of Xiangsu pigs were studied to explore the relationship between its polymorphism and litter size traits. Also, bioinformatics was used to evaluate the effects of missense substitutions on protein structure and function. The results revealed that NOBOX is preferentially expressed in the ovary. Six mutations were detected in the NOBOX sequence, including g.1624 T>C, g.1858 G>A, g.2770 G>A, g.2821 A>G, g.5659 A>G, and g.6025 T>A, of which g.1858 G>A was a missense mutation. However, only g.1858 G>A, g.5659 A>G, and g.6025 T>A were significantly associated with litter size traits (p < 0.05). Further prediction of the effect of the missense mutation g.1858 G>A on protein function revealed that p.V82M is a non-conservative mutation that significantly reduces protein stability and thus alters protein function. Overall, these findings suggest that NOBOX polymorphism is closely related to the litter size of Xiangsu pigs, which may provide new insights into pig breeding.

Deciphering Estrus Expression in Gilts: The Role of Alternative Polyadenylation and LincRNAs in Reproductive Transcriptomics.

The fertility rate and litter size of female pigs are critically affected by the expression of estrus. The objective of this study was to elucidate the regulatory mechanisms of estrus expression by analyzing the differential expression of genes and long intergenic non-coding RNAs (lincRNA), as well as the utilization of alternative polyadenylation (APA) sites, in the vulva and vagina during the estrus and diestrus stages of Large White and indigenous Chinese Mi gilts. Our study revealed that the number of differentially expressed genes (DEG) in the vulva was less than that in the vagina, and the DEGs in the vulva were enriched in pathways such as "neural" pathways and steroid hormone responses, including the "Calcium signaling pathway" and "Oxytocin signaling pathway". The DEGs in the vagina were enriched in the "Metabolic pathways" and "VEGF signaling pathway". Furthermore, 27 and 21 differentially expressed lincRNAs (DEL), whose target genes were enriched in the "Endocrine resistance" pathway, were identified in the vulva and vagina, respectively. Additionally, we observed that 63 and 618 transcripts of the 3'-untranslated region (3'-UTR) were lengthened during estrus in the vulva and vagina, respectively. Interestingly, the genes undergoing APA events in the vulva exhibited species-specific enrichment in neural or steroid-related pathways, whereas those in the vagina were enriched in apoptosis or autophagy-related pathways. Further bioinformatic analysis of these lengthened 3'-UTRs revealed the presence of multiple miRNAs binding sites and cytoplasmic polyadenylation element (CPE) regulatory aspects. In particular, we identified more than 10 CPEs in the validated lengthened 3'-UTRs of the NFIX, PCNX4, CEP162 and ABHD2 genes using RT-qPCR. These findings demonstrated the involvement of APA and lincRNAs in the regulation of estrus expression in female pigs, providing new insights into the molecular mechanisms underlying estrus expression in pigs.

Genome-wide association studies for the number of piglets born alive and dead in Dongliao black pigs.

Litter size (total number born) trait has a great impact on the economic success of pork production. The total number born consists of the number of piglets born alive and dead. To clarify the genetic background of litter size, genome-wide association studies were undertaken in the present study. Samples of DNA were collected and genotyped using the Porcine 50K BeadChip from 723 Dongliao Black sows. Using three different models (BLINK, FarmCPU, and MLM), a total of 155 significant SNPs were discovered, six of which had been reported in previous pig reproduction association studies. We suggest that rs81318434, located in the GLI3 gene, might be the promising candidate affecting litter size trait. Our findings may provide insights for uncovering the genetic mechanisms for the litter size of pigs.

Genetic and phenotypic time trends of litter size, piglet mortality, and birth weight in pigs

IntroductionLitter size in pigs has increased steadily since 1990. Because of unfavorable genetic correlations with piglet mortality, breeding goals should include survival traits next to litter size. Unbalanced breeding programs that neglect this requirement have produced increased mortality levels, attracting negative public attention. Balanced breeding does not have this disadvantage, but the general public is largely unaware of this.MethodsWe present long-term time trends as realized in commercial breeding. The data includes (i) phenotypes of litter size, piglet birth weight, and piglet mortality, as used in routine breeding value estimation; and (ii) the genomic Best Linear Unbiased Prediction (gBLUP) estimated breeding values thus obtained. Piglet mortality (2001–2022) and birth weight (2009–2022) phenotypes were related to litter size by recording year. Estimated breeding values (EBVs) for the mortality traits were regressed on those for litter size by birth year (2012–2022).ResultsAverage litter size is very weakly correlated to the mortality (R2 ≤ 0.06) and birth weight (0.07 ≤ R2 ≤ 0.26) traits, and those correlations are unfavorable (antagonistic) within each year. However, all traits analyzed here show favorable simultaneous phenotypic and genetic trends over time: the antagonisms are neutralized by balanced breeding. Above the annual mean litter size level, farrowing and lactation mortality rates increased with increasing litter size in every year (unfavorable), but the annual intercepts and the slopes decreased from 2001 to 2022 (favorable). Average litter birth weight decreased with litter size in every year (unfavorable), but the annual intercepts increased and the slopes decreased from 2009 to 2022 (favorable). The within-litter birth weight variation coefficient increased with litter size in every year (unfavorable), but the annual intercepts decreased from 2009 to 2022 (favorable). The proportion of low birth weights (i.e.,&amp;lt; 0.9 kg) for a given litter size is decreasing over time, and the critical birth weight level (below which lactation mortality increases strongly) is clearly population dependent and changes over time too.DiscussionThe increases in litter size and piglet survival rates due to balanced breeding policies lead to reduced total numbers of dead piglets (i.e., per country, per year) coinciding with a certain pig production volume (i.e., with a certain total number of weaned piglets).

Genetic diversity of porcine PRLR gene and its relationship to litter size in Large White pigs

Improving the litter performance of sows is one of the main challenges in the current pig industry. In this study, single nucleotide polymorphisms (SNPs) of the PRLR gene were performed, in order to test whether they are associated with the reproductive performance of Large White pigs. In total, we discovered nine SNP loci (g. C260G, g. C362T, g. C527G, g. A540G, g. A584G, g. A673T, g. A745G, g. C765T and g. A934G) in exon 10 of PRLR. The result showed that genotypes CC and CT at the g. C362T locus and genotype AG at g. A584G could significantly increase the litter size of different strains of Large White pigs (p &lt; 0.05). In addition, the genotype CC at the g. C765T locus and the genotype AA at g. A934G could also increase the litter size (TNB could be increased by 1.5 piglets per year; while NBA could be increased by 0.98 piglets per year, p &lt; 0.01). Furthermore, the haplotype combinations of H2H7 and H4H4 were the dominant combinations and contributed to larger litter sizes in the Large White pigs. In conclusion, there were dominant genotypes in the related SNP loci in the PRLR gene that were beneficial to improving the litter traits of sows. These findings will provide a reference for screening the molecular markers of a high reproductive performance in sows, and are helpful for genetic breeding and the reproductive improvement of pigs. Key words: sow, prolactin, polymorphism, reproduction, association analysis.

The impact of Box-Cox transformation on phenotypic and genomic characteristics of litter size variability in Landrace pigs

The genetic background of variability remains of interest especially in traits of high economic importance, e.g. litter size in pigs. It has been indicated that the data transformation can affect the variability phenotype. This study aims to evaluate the phenotypic and genomic background of variability of litter size obtained from data before and after the Box-Cox transformation. In total, 67 500 records on the total number born (TNB) in Landrace pig population were used. Since the data presented skewness, the decision was made to perform Box-Cox transformation on TNB and obtain bcTNB. Next, the phenotypic variability was estimated as log-transformed variance of residuals (LnVar) for both TNB (LnVar_TNB) and bcTNB (LnVar_bcTNB). The variability traits were further used in the genome-wide association study (GWAS) performed on 10 688 sows genotyped with Axiom porcine 660 K or imputed to 660 K SNP-chip. The substantial difference in skewness was observed after data transformation, represented as a change from −0.46 to −0.02. Heritability for TNB was 0.118 vs 0.125 for bcTNB. The heritability for LnVar_TNB was 0.0025 vs 0.0037 for LnVar_bcTNB. The change in the genetic variance was confirmed when genetic coefficients on SD level were compared: 2% for LnVar_TNB vs 4% for LnVar_bcTNB. In bivariate analysis, the genetic correlation between the additive genetic effects of the mean TNB and its variability changed from 0.38 to 0.63. The observed positive genetic correlations indicated that selection focused on increasing the litter size will simultaneously cause an increase in litter size variability. Based on GWAS, 14 SNPs were detected for LnVar_TNB and eight for LnVar_bcTNB, with two of them indicating the most promising candidate genes. First candidate gene located on Sus scrofa chromosome (SSC) 3 is STAG3, which plays an essential role in gametogenesis. Second gene located on SSC 10 is ESRRG, which affects placenta development. The additional post-GWAS analysis indicated even more candidate genes for LnVar_TNB and LnVar_bcTNB. The most promising candidate gene was located on SSC 13 – MFN1, which is involved in embryonic development. The results of this study indicated a substantial change in variance components for variability when the Box-Cox transformation was applied to data presenting skewness. Moreover, the data transformation changed the phenotype substantially enough that only part of SNP overlapped between two variability traits. Our investigation shows that it is essential to perform Box-Cox transformation for skewed data in order to properly describe phenotypic and genomic properties of litter size variability in Landrace pigs.

Effect of NLR family pyrin domain containing 9 gene polymorphism on litter size in large white pigs

NLR family pyrin domain containing 9 (NLRP9) is a mammalian reproduction-related gene. In this study, we researched the associations between polymorphisms located in the coding sequence (CDS) of the NLRP9 gene, and both the total number of piglets born per litter (TNB) and the number of piglets born alive per litter (NBA) in Canada Large White pigs (CLW). We detected a single nucleotide polymorphism (SNP) within exon 3 (g.10910C > T). The allele frequencies at the NLRP9 locus were 0.474 for the C allele and 0.526 for the T allele. Three genotypes, CC, CT, and TT, occurred with frequencies of 0.216, 0.515, and 0.269, respectively. Sows with the CC genotype had the largest TNB and NBA, sows with TT had the smallest, and those with CT were in-between. This difference was statistically significant (p < 0.05). Furthermore, CC females grew faster than CT or TT females, and there was a significant relationship between NLRP9 polymorphism and the average daily gain (p < 0.05). Here, we provide the first evidence for a novel SNP in NLRP9 associated with litter size in CLW sows, which could be used as a genetic marker to improve litter size in pig breeding and production.

Evaluation of the phenotypic and genomic background of variability based on litter size of Large White pigs

BackgroundThe genetic background of trait variability has captured the interest of ecologists and animal breeders because the genes that control it could be involved in buffering various environmental effects. Phenotypic variability of a given trait can be assessed by studying the heterogeneity of the residual variance, and the quantitative trait loci (QTL) that are involved in the control of this variability are described as variance QTL (vQTL). This study focuses on litter size (total number born, TNB) and its variability in a Large White pig population. The variability of TNB was evaluated either using a simple method, i.e. analysis of the log-transformed variance of residuals (LnVar), or the more complex double hierarchical generalized linear model (DHGLM). We also performed a single-SNP (single nucleotide polymorphism) genome-wide association study (GWAS). To our knowledge, this is only the second study that reports vQTL for litter size in pigs and the first one that shows GWAS results when using two methods to evaluate variability of TNB: LnVar and DHGLM.ResultsBased on LnVar, three candidate vQTL regions were detected, on Sus scrofa chromosomes (SSC) 1, 7, and 18, which comprised 18 SNPs. Based on the DHGLM, three candidate vQTL regions were detected, i.e. two on SSC7 and one on SSC11, which comprised 32 SNPs. Only one candidate vQTL region overlapped between the two methods, on SSC7, which also contained the most significant SNP. Within this vQTL region, two candidate genes were identified, ADGRF1, which is involved in neurodevelopment of the brain, and ADGRF5, which is involved in the function of the respiratory system and in vascularization. The correlation between estimated breeding values based on the two methods was 0.86. Three-fold cross-validation indicated that DHGLM yielded EBV that were much more accurate and had better prediction of missing observations than LnVar.ConclusionsThe results indicated that the LnVar and DHGLM methods resulted in genetically different traits. Based on their validation, we recommend the use of DHGLM over the simpler method of log-transformed variance of residuals. These conclusions can be useful for future studies on the evaluation of the variability of any trait in any species.

ESR1 Candidate Marker Gene Associated with Litter Size in the Philippine Native Pigs (Sus philippensis)

ESR1 Candidate Marker Gene Associated with Litter Size in the Philippine Native Pigs (Sus philippensis)

Estimation of Genetic Parameters for Birth Weight, within Litter Variation of Birth Weight and Litter Size in Landrace and Yorkshire Pigs

Estimation of Genetic Parameters for Birth Weight, within Litter Variation of Birth Weight and Litter Size in Landrace and Yorkshire Pigs

Polymorphism of OPN and AREG Genes in Relation to Transcript Expression of a Panel of 12 Genes Controlling Reproduction Processes and Litter Size in Pigs

Abstract The aim of this study was to define the transcript expression of 12 genes, identify new polymorphisms in selected 2 genes and to estimate the association between the level of expression, gene polymorphism and litter size in sows. Two groups of sows were selected: 71 crossbred sows and 328 purebred sows. For transcript analysis endometrial tissue samples were collected, while blood was sampled for the purpose of DNA polymorphism analysis. For all animals data on litter size and weaned piglets were obtained. Transcript analysis of 12 genes was performed in the uterine endometrium of sows in the luteal and follicular phases. Eight out of 12 genes showed higher mRNA expression levels during the luteal phase (AREG, FABP3, IL1A, ITGAV, ITGB3, NMB, OPN, RBP4). In turn, higher expression levels in the follicular phase were observed for 4 genes (IL1B, PPARG, S100A8, SELL). Analysis of six new polymorphic sites within the OPN and AREG genes revealed the highest heterozygosity for OPNe6_Knoll, OPNp3_617 and AREGe2_317 polymorphisms and the lowest heterozygosity in the AREGe3_561 locus. Association analyses concerning transcript expression levels of the 12 genes and the OPN and AREG genotypes in the two groups of sows showed a significant relationship between the IL1A, ITGB3 transcript expression and the OPNe7_603 genotype also between OPNp3_617 genotype and ITGB3 transcript expression. With regard to the litter size and the number of weaned piglets a significant relation with the OPNp3_617, OPNe6_462 and AREGe2_317 genotypes was observed only in the purebred sows. Transcript expression of the genes encoding osteopontin and amphiregulin in the uterus of the sows affect reproductive traits by preparing the uterus for embryo reception.

Selection for litter size and litter birthweight in Large White pigs: Maximum, mean and variability of reproduction traits

Gradually increasing trend of litter size poses a challenge to pig farmers in terms of managing larger litters. Therefore, it seems that a balanced approach that optimises litter size, litter birthweight, and uniformity of those traits is needed in order to address animal welfare and farm management concerns. This study aimed to investigate this issue by defining several traits for total number born (TNB), number born alive (NBA) and litter birthweight (LW). First, the highest value from at least five records per sow was selected as maximum (max) value for each reproduction trait. Second, a mean (mean) for each reproduction trait was calculated per sow. Last, the variability of reproduction traits between parities of the sow was calculated as log-transformed variance of residuals of all observations per sow for each reproduction trait (LnVar). In total, 23 193 Large White sows from Topigs Norsvin with 152 282 litter records were used for analysis in ASReml 4.1. Also, a simulation of breeding schemes was performed with the use of SelAction 2.1 and estimates from genetic analysis. Maximum value of reproductive traits had a much higher heritability than repeated observations or mean of reproduction traits, e.g., 0.31 for maxTNB vs. 0.12 for TNB and 0.07 for meanTNB, which allows for a faster response under selection. The maximum value traits, however, were found to carry more risks, i.e. higher ratio of stillborn (not for maxNBA) and increased variability of traits. Thus, using them in breeding programme should be carefully considered. The genetic coefficient of variation on SD level estimated to indicate the genetic magnitude for variability phenotypes indicated a maximum change of 6–9% in genetic SD of TNB, NBA and LW. The genetic correlations between mean and corresponding variability traits varied from 0.66 to 0.74, whereas the correlation between other mean and variability traits ranged from 0.33 to 0.99. The simulation indicated that even with selection targeted against the variability of reproduction traits, a very limited change should be expected due to a complex genetic and phenotypic relationship between the traits. In the scenarios with selection against LnVarTNB and LnVarLW, this was a decrease of 0.1–0.6% per year, whereas in scenario with selection against LnVarNBA, the range was 0.6–1.1% per year. It is still possible to increase litter size and birthweight further, however, a balance between mean and variability of reproduction traits is required, which can be obtained only by a very well designed breeding programme.

Differences in gene expression and variable splicing events of ovaries between large and small litter size in Chinese Xiang pigs

BackgroundAlthough lots of quantitative trait loci (QTLs) and genes present roles in litter size of some breeds, the information might not make it clear for the huge diversity of reproductive capability in pig breeds. To elucidate the inherent mechanisms of heterogeneity of reproductive capability in litter size of Xiang pig, we performed transcriptome analysis for the expression profile in ovaries using RNA-seq method.ResultsWe identified 1,419 up-regulated and 1,376 down-regulated genes in Xiang pigs with large litter size. Among them, 1,010 differentially expressed genes (DEGs) were differently spliced between two groups with large or small litter sizes. Based on GO and KEGG analysis, numerous members of genes were gathered in ovarian steroidogenesis, steroid biosynthesis, oocyte maturation and reproduction processes.ConclusionsCombined with gene biological function, twelve genes were found out that might be related with the reproductive capability of Xiang pig, of which, eleven genes were recognized as hub genes. These genes may play a role in promoting litter size by elevating steroid and peptide hormones supply through the ovary and facilitating the processes of ovulation and in vivo fertilization.

Pregnancy in pigs: the journey of an early life

Embryo mortality is responsible for greater losses in litter size in pigs. It is well known that pregnancy establishment is a complex process, and important changes occur continuously in both the corpora lutea and the endometrium, which varies depending on the pre-natal development phase: embryonic, pre-implantation or fetal stages. The placenta is a key organ responsible for the exchange of nutrients, metabolites and respiratory gases between mother and fetuses. The porcine placenta is diffuse, epitheliochorial, and placentation begins with implantation, which involves specialized cell adhesion and cell migration, leading to the attachment of the trophectoderm to the uterine endometrial lumen epithelium. The efficiency with which the placenta provides adequate amounts of nutrients and oxygen to the fetus is crucial for proper fetal growth and development. In the last decades, emphasis on selection for sow prolificacy has resulted in a substantial increase in the number of piglets born per litter, which had a direct effect on piglet quality, compromising birth weight and litter uniformity. Placental insufficiency will lead to fetal intrauterine growth restriction. This review addresses the main events of early embryo development, including preimplantation and implantation periods. In addition, placentation and its role on fetal development are covered, as well as intrauterine growth restriction, as it is a natural condition in the pig, with long lasting detrimental effects to the production chain.

52 Ovarian Follicular Profiling of High- and Low-immunocrit Gilts on Postnatal Day 14

Abstract Colostrum intake by neonatal piglets can be measured using the immunoglobulin immunocrit assay (iCrit). Lactocrine effects occur when maternally derived, milk-borne bioactive factors are transferred to the neonatal circulation with consumption of colostrum during nursing and affect development of somatic tissues, which can have long-term consequences in adulthood. Lactocrine deficiency, indicated by low neonatal iCrit, altered uterine gene expression and reduced fecundity in adult, neonatally lactocrine-deficient gilts. Litter size in pigs is dependent on both ovarian and uterine function. It was hypothesized that lactocrine deficiency affects development of ovarian follicles in gilts. The objective was to determine the number of primordial, primary, and secondary follicles in ovaries of gilts with high (12% ± 0.5; n = 10) or low (1.9% ± 0.4; n = 10) iCrit, determined on postnatal day (PND) 1 after birth. Paired high- and low-iCrit gilts were chosen from the same litters (birth weight; 3.1 ± 0.2 lbs). On PND 14, ovaries were collected and histological sections prepared (3 sections per animal; 30–150 µm apart). Ovarian follicles in each section were staged and the number of follicles in each category were quantified and subjected to ANOVA. Total number of ovarian follicles did not differ with iCrit (P = 0.55; 1,370.6 ± 147.8 follicles per section). The proportion of primordial, primary, and secondary follicles was 89.6 ± 1.15%, 7.7 ± 0.87%, 2.7 ± 0.51%, respectively. The number of primordial (P = 0.55), primary (P = 0.64), and secondary (P = 0.93) follicles did not differ with iCrit. Results indicate that ovarian follicular development of neonatal gilts is not sensitive to immunocrit status. Although lactocrine deficiency did not influence the ovarian follicular profile at PND 14, it remains unknown whether lactocrine programming alters ovarian follicular dynamics in neonatally lactocrine-deficient adults. USDA is an equal opportunity provider and employer.

A nonsense mutation of bone morphogenetic protein-15 (BMP15) causes both infertility and increased litter size in pigs

BackgroundAtypical external genitalia are often a sign of reproductive organ pathologies and infertility with both environmental or genetic causes, including karyotypic abnormalities. Genome-wide association studies (GWAS) provide a means for identifying chromosomal regions harboring deleterious DNA-variants causing such phenotypes. We performed a GWAS to unravel the causes of incidental cases of atypically small vulvae in German Landrace gilts.ResultsA case-control GWAS involving Illumina porcine SNP60 BeadChip-called genotypes of 17 gilts with atypically small vulvae and 1818 control animals (fertile German Landrace sows) identified a significantly associated region on the X-chromosome (P = 8.81 × 10− 43). Inspection of whole-genome sequencing data in the critical area allowed us to pinpoint a likely causal variant in the form of a nonsense mutation of bone morphogenetic protein-15 (BMP15; Sscrofa11.1_X:g.44618787C>T, BMP15:p.R212X). The mutant allele occurs at a frequency of 6.2% in the German Landrace breeding population. Homozygous gilts exhibit underdeveloped, most likely not functional ovaries and are not fertile. Male carriers do not seem to manifest defects. Heterozygous sows produce 0.41±0.02 (P=4.5 × 10-83) piglets more than wildtype animals. However, the mutant allele’s positive effect on litter size accompanies a negative impact on lean meat growth.ConclusionOur results provide an example for the power of GWAS in identifying the genetic causes of a fuzzy phenotype and add to the list of natural deleterious BMP15 mutations that affect fertility in a dosage-dependent manner, the first time in a poly-ovulatory species. We advise eradicating the mutant allele from the German Landrace breeding population since the adverse effects on the lean meat growth outweigh the larger litter size in heterozygous sows.

GENETIC ANALYSIS OF UKRAINIAN LARGE WHITE PIG BREED BY POLYMORPHISMS IN RYR1, ESR1 AND PRLR GENES

Marker-Assisted Selection is getting increasing attention in Ukrainian animal breeding as an effective tool for choosing animals with desirable traits. Identification of molecular markers which are related to major genes is a promising approach for improving economic traits and has to be checked for further gene-trait associations. Single nucleotide polymorphisms are genetic markers that can be associated with production traits. SNP genotyping has to be done additionally for each breed to see if they are polymorphic and have significant associations with certain traits. Among the candidate genes that influence the expression of productive traits, special attention is drawn to RYR1, ESR1 and PRLR genes. Gene RYR1 is associated with muscle hypertrophy and other meat quality defects in pigs. ESR1 and PRLR genes influence reproduction and affect the litter size in pigs. SNPs RYR1 g.1843 C&gt;T, ESR1 SNP c.1227 C&gt;T and PRLR g. 1789 G&gt;A have been receiving increasing attention as potential markers for improving quality and pig performance traits. This study investigated the allele variants in three genes (RYR1, ESR1 and PRLR) in Ukrainian Large White pigs of different inside breed types (ULW-1 and ULW-2). The study was performed on 200 pigs. Genotyping was performed using PCR–RFLP method. SNP RYR1 g.1843 C&gt;T was not polymorphic in ULW-1 and ULW-2 inside breed types, when ESR1 SNP c.1227 C&gt; T and PRLR g. 1789 G&gt;A were highly polymorphic. SNPs in ESR1 and PRLR genes had high PIC and χ2 values which indicates the relevance of further associative studies in ULW-1 and ULW-2. Informativeness of the genetic markers in ESR1 and PRLR genes was optimal for associative studies in Ukrainian Large White pig breed of first and second inside breed type.

Influence of Litter Size at Birth on Productive Parameters in Guinea Pigs (Cavia porcellus).

Simple SummaryCavia porcellus is an autochthonous species of the high Andean region of countries such as Ecuador, Bolivia, Colombia, and Peru. Several works have been conducted to create programs aimed at improving their productive characteristics. Thus, breeding and conservation are very important for an animal species of high precocity and prolificacy, providing a source of protein of high biological value and for being part of the cultural legacy of many of these countries. Currently, this species is part of the food security in high Andean areas, and technology is being incorporated into its production at an industrial level, also establishing marketing channels. Herein, we conclude that the best productive responses regarding weight were in the litters of three guinea pigs. Furthermore, with respect to sex, the males presented better productive performance than the females.A study was conducted at the Escuela Superior Politècnica de Chimborazo, Ecuador, to evaluate the influence of litter size of guinea pigs (Cavia porcellus) on their development and to establish the economic profitability of the production system. Forty-eight animals were used, distributed into litters of two, three, and four rodents per litter, with a balanced diet and green fresh alfalfa for the weaning, growth, and fattening stage, the rodents and litters were randomly selected, applying the statistical model completely randomly and evaluating different variables across 120 days. The litters of three guinea pigs obtained the best productive responses and economic profitability. With respect to sex, the males presented better productive behavior, greater economic increase, and less cost, evidencing that mixed feeding influences the number of guinea pigs per birth in terms of growth and development. The results serve to improve guinea pig meat production for the rural population.