A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs

Additive and Dominance Genome-Wide Association Studies Reveal the Genetic Basis of Heterosis Related to Growth Traits of Duhua Hybrid Pigs

Heterosis has been extensively used for pig genetic breeding and production, but the genetic basis of heterosis remains largely elusive. Crossbreeding between commercial and native breeds provides a good model to parse the genetic basis of heterosis. This study uses Duhua hybrid pigs, a crossbreed of Duroc and Liangguang small spotted pigs, as materials to explore the genetic basis underlying heterosis related to growth traits at the genomic level. The mid-parent heterosis (MPH) analysis showed heterosis of this Duhua offspring on growth traits. In this study, we examined the impact of additive and dominance effects on 100 AGE (age adjusted to 100 kg) and 100 BF (backfat thickness adjusted to 100 kg) of Duhua hybrid pigs. Meanwhile, we successfully identified SNPs associated with growth traits through both additive and dominance GWASs (genome-wide association studies). These findings will facilitate the subsequent in-depth studies of heterosis in the growth traits of Duhua pigs.

Livestock species as emerging models for genomic imprinting

Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.

Genome-wide association study reveals genetic loci and candidate genes for meat quality traits in a four-way crossbred pig population

Meat quality traits (MQTs) have gained more attention from breeders due to their increasing economic value in the commercial pig industry. In this genome-wide association study (GWAS), 223 four-way intercross pigs were genotyped using the specific-locus amplified fragment sequencing (SLAF-seq) and phenotyped for PH at 45 min post mortem (PH45), meat color score (MC), marbling score (MA), water loss rate (WL), drip loss (DL) in the longissimus muscle, and cooking loss (CL) in the psoas major muscle. A total of 227, 921 filtered single nucleotide polymorphisms (SNPs) evenly distributed across the entire genome were detected to perform GWAS. A total of 64 SNPs were identified for six meat quality traits using the mixed linear model (MLM), of which 24 SNPs were located in previously reported QTL regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43% to 16.32%. The genomic heritability estimates based on SNP for six meat-quality traits were low to moderate (0.07-0.47) being the lowest for CL and the highest for DL. A total of 30 genes located within 10 kb upstream or downstream of these significant SNPs were found. Furthermore, several candidate genes for MQTs were detected, including pH45 (GRM8), MC (ANKRD6), MA (MACROD2 and ABCG1), WL (TMEM50A), CL (PIP4K2A) and DL (CDYL2, CHL1, ABCA4, ZAG and SLC1A2). This study provided substantial new evidence for several candidate genes to participate in different pork quality traits. The identification of these SNPs and candidate genes provided a basis for molecular marker-assisted breeding and improvement of pork quality traits.

Polymorphisms in SHISA3 and RFC3 genes and their association with feed conversion ratio in Hu sheep

In animal husbandry, feed efficiency is a crucial economic trait. In this study, the general linear model was used to perform association analysis for various genotypes and feed conversion ratio (FCR)-related traits. Reverse transcription-quantitative PCR (RT-qPCR) was used to detect the expression of SHISA3 and RFC3 mRNA levels in 10 tissues from 6 sheep. The results showed that SNPs in the NC_040257.1:c.625 T > C and NC_040261.1:g.9905 T > C were analyzed whether they were associated to feed efficiency parameters in Hu sheep (body weight, feed intake, average daily growth, and feed conversion ratio). NC_040257.1:c.625 T > C was shown to be significantly associated with body weight at 80, 100, and 120 days as well as feed conversion ratio (P < 0.05), whereas NC_040261.1:g.9905 T > C was found to be significantly associated with average daily weight gain from 80-140 days (ADG80-140) and FCR (P < 0.05). In Hu sheep, the CC genotypes of SHISA3 and RFC3 were the most common genotypes related to feed efficiency traits. Furthermore, the feed conversion ratio of the combined genotypes TT ^SHISA3-CC ^RFC3, TT ^SHISA3-CT ^RFC3, TT ^SHISA3-TT ^RFC3, CT ^SHISA3-CC ^RFC3 and CT ^SHISA3-CT ^RFC3 was significantly better than the FCR of CC ^SHISA3-TT ^RFC3. RT-qPCR results showed that the expression levels of SHISA3 were lower in the lung than in spleen, kidney, muscle and lymph (P < 0.05), and RFC3 was the lung had a highly significant higher expression level than the heart, liver, spleen, and muscle (P < 0.01). In conclusion, SHISA3 and RFC3 polymorphisms can be used as genetic markers for improving feed conversion efficiency in Hu sheep.

Identification of Differentially Expressed miRNAs in Porcine Adipose Tissues and Evaluation of Their Effects on Feed Efficiency

Feed efficiency (FE) is a very important trait affecting the economic benefits of pig breeding enterprises. Adipose tissue can modulate a variety of processes such as feed intake, energy metabolism and systemic physiological processes. However, the mechanism by which microRNAs (miRNAs) in adipose tissues regulate FE remains largely unknown. Therefore, this study aimed to screen potential miRNAs related to FE through miRNA sequencing. The miRNA profiles in porcine adipose tissues were obtained and 14 miRNAs were identified differentially expressed in adipose tissues of pigs with extreme differences in FE, of which 9 were down-regulated and 5 were up-regulated. GO and KEGG analyses indicated that these miRNAs were significantly related to lipid metabolism and these miRNAs modulated FE by regulating lipid metabolism. Subsequently, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) of five randomly selected DEMs was used to verify the reliability of miRNA-seq data. Furthermore, 39 differentially expressed target genes of these DEMs were obtained, and DEMs-target mRNA interaction networks were constructed. In addition, the most significantly down-regulated miRNAs, ssc-miR-122-5p and ssc-miR-192, might be the key miRNAs for FE. Our results reveal the mechanism by which adipose miRNAs regulate feed efficiency in pigs. This study provides a theoretical basis for the further study of swine feed efficiency improvement.

Genome-Wide Association Study Reveals Additive and Non-Additive Effects on Growth Traits in Duroc Pigs

Growth rate plays a critical role in the pig industry and is related to quantitative traits controlled by many genes. Here, we aimed to identify causative mutations and candidate genes responsible for pig growth traits. In this study, 2360 Duroc pigs were used to detect significant additive, dominance, and epistatic effects associated with growth traits. As a result, a total number of 32 significant SNPs for additive or dominance effects were found to be associated with various factors, including adjusted age at a specified weight (AGE), average daily gain (ADG), backfat thickness (BF), and loin muscle depth (LMD). In addition, the detected additive significant SNPs explained 2.49%, 3.02%, 3.18%, and 1.96% of the deregressed estimated breeding value (DEBV) variance for AGE, ADG, BF, and LMD, respectively, while significant dominance SNPs could explain 2.24%, 13.26%, and 4.08% of AGE, BF, and LMD, respectively. Meanwhile, a total of 805 significant epistatic effects SNPs were associated with one of ADG, AGE, and LMD, from which 11 sub-networks were constructed. In total, 46 potential genes involved in muscle development, fat deposition, and regulation of cell growth were considered as candidates for growth traits, including CD55 and NRIP1 for AGE and ADG, TRIP11 and MIS2 for BF, and VRTN and ZEB2 for LMD, respectively. Generally, in this study, we detected both new and reported variants and potential candidate genes for growth traits of Duroc pigs, which might to be taken into account in future molecular breeding programs to improve the growth performance of pigs.

Genome-Wide Association Analysis and Genetic Parameters for Feed Efficiency and Related Traits in Yorkshire and Duroc Pigs

Simple Summary

Genetic improvements in feed efficiency (FE) and related traits could considerably reduce pig production costs and energy consumption. Thus, we performed a genetic parameter estimation and genome-wide association study of four FE and FE-related traits, namely, average daily feed intake, average daily gain, the feed conversion ratio, and residual feed intake, of two pig breeds, Yorkshire and Duroc. The results demonstrate the genetic relationships of FE and FE-related traits with two growth traits, age and backfat thickness at 100 kg. We also identified many single-nucleotide polymorphisms (SNPs) and novel candidate genes related to these traits. In addition, we found many pathways significantly associated with FE and FE-related traits, and they are generally involved in digestive and metabolic processes. The results of this study are expected to provide a valuable reference for the genomic selection of FE and FE-related traits in pigs.

Abstract

Feed efficiency (FE) traits are key factors that can influence the economic benefits of pig production. However, little is known about the genetic architecture of FE and FE-related traits. This study aimed to identify SNPs and candidate genes associated with FE and FE-related traits, namely, average daily feed intake (ADFI), average daily gain (ADG), the feed conversion ratio (FCR), and residual feed intake (RFI). The phenotypes of 5823 boars with genotyped data (50 K BeadChip) from 1365 boars from a nucleus farm were used to perform a genome-wide association study (GWAS) of two breeds, Duroc and Yorkshire. Moreover, we performed a genetic parameter estimation for four FE and FE-related traits. The heritabilities of the FE and FE-related traits ranged from 0.13 to 0.36, and there were significant genetic correlations (−0.69 to 0.52) of the FE and FE-related traits with two growth traits (age at 100 kg and backfat thickness at 100 kg). A total of 61 significant SNPs located on eight different chromosomes associated with the four FE and FE-related traits were identified. We further identified four regions associated with FE and FE-related traits that have not been previously reported, and they may be potential novel QTLs for FE. Considering their biological functions, we finally identified 35 candidate genes relevant for FE and FE-related traits, such as the widely reported MC4R and INSR genes. A gene enrichment analysis showed that FE and FE-related traits were highly enriched in the biosynthesis, digestion, and metabolism of biomolecules. This study deepens our understanding of the genetic mechanisms of FE in pigs and provides valuable information for using marker-assisted selection in pigs to improve FE.

Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency

Despite the significant improvement of feed efficiency (FE) in pigs over the past decades, feed costs remain a major challenge for producers profitability. Improving FE is a top priority for the global swine industry. A deeper understanding of the biology underlying FE is crucial for making progress in genetic improvement of FE traits. This review comprehensively discusses the topics related to the FE in pigs including: measurements, genetics, genomics, biological pathways and the advanced technologies and methods involved in FE improvement. We first provide an update of heritability for different FE indicators and then characterize the correlations of FE traits with other economically important traits. Moreover, we present the quantitative trait loci (QTL) and possible candidate genes associated with FE in pigs and outline the most important biological pathways related to the FE traits in pigs. Finally, we present possible ways to improve FE in swine including the implementation of genomic selection, new technologies for measuring the FE traits, and the potential use of genome editing and omics technologies.

A genome-wide association study of important reproduction traits in large white pigs

Augmenting the reproductive efficiency of sows remains the predominant challenge in the swine industry. This work was aimed at scrutinizing vital genetic markers for reproductive traits in this animal. This entailed probing of the records of vital attributes of Large White pigs (n = 695) inclusive of the total number of born (TNB), number of born alive (NBA), number of weaned pigs (NWP), number of healthy births (NHS), total litter weight of piglets born alive (BALWT), weaning litter weight (WNWT), and corrected litter weight at 21 days (W21). A genome-wide association study (GWAS) for the four litter traits and three traits of litter weight in the Denmark Large White population then ensued. We discovered seven significantly related SNPs and eleven potential candidate genes (e.g., TUSC3, THRB for TNB; STT3B for NBA). The subsequent functional enrichment analysis of these genes showed that the significant gene were associated with steroid hormone receptor activity. Our findings indicated that the genes TUSC3, THRB and STT3B probably contribute to litter traits in this population. This work reveals genetic mechanisms of reproduction traits and also supports ensuing genetic improvement employing marker-assisted selection in Large White pigs.

Genome-Wide Association Study of Feed Efficiency Related Traits in Ducks

Simple Summary

Good feed efficiency (FE) is an important trait to ensure the economic output of the livestock and poultry industries. Herein, a genome-wide association study was conducted to identify potential variants and genes associated with seven FE measures in ducks. Genomic DNA samples of 308 ducks were collected and sequenced. All animals were evaluated concerning body weight gain (BWG), feed intake (FI), residual feed intake (RFI), feed conversion ratio (FCR), and weight at 21 (BW21) and 42 days of age (BW42). Overall, 4 (FCR), 3 (FI), 36 (RFI), 6 (BWG), 8 (BW21), and 10 (BW42) single nucleotide polymorphisms (SNPs) were significantly associated with these FE traits, respectively. Moreover, candidate genes close to the identified variants were found to be mainly involved in key pathways and terms related to metabolism. In summary, these findings improve our understanding of poultry genetics and provide new foundations for breeding programs aimed at maximizing the economic potential of duck breeding and farming.

Abstract

Feed efficiency (FE) is the most important economic trait in the poultry and livestock industry. Thus, genetic improvement of FE may result in a considerable reduction of the cost and energy burdens. As genome-wide association studies (GWASs) can help identify candidate variants influencing FE, the present study aimed to analyze the phenotypic correlation and identify candidate variants of the seven FE traits in ducks. All traits were found to have significant positive correlations with varying degrees. In particular, residual feed intake presented correlation coefficients of 0.61, 0.54, and 0.13 with feed conversion ratio, and feed intake, respectively. Furthermore, data from seven FE-related GWAS revealed 4 (FCR), 3 (FI), 36 (RFI), 6 (BWG), 8 (BW21), and 10 (BW42) SNPs were significantly associated with body weight gain, feed intake, residual feed intake, feed conversion ratio, and weight at 21 and 42 days, respectively. Candidate SNPs of seven FE trait-related genes were involved in galactose metabolism, starch, propanoate metabolism, sucrose metabolism and etc. Taken together, these findings provide insight into the genetic mechanisms and genes involved in FE-related traits in ducks. However, further investigations are warranted to further validate these findings.

Genome-wide association studies identified loci associated with both feed conversion ratio and residual feed intake in Yorkshire pigs

Feed occupies a significant proportion in the production cost of pigs, and the feed efficiency (FE) in pigs are of utmost economic importance. Hence, the objective of this study is to identify single nucleotide polymorphisms (SNPs) and candidate genes associated with FE related traits, including feed conversion ratio (FCR) and residual feed intake (RFI). A genome-wide association study (GWAS) was conducted for FCR and RFI in 169 Yorkshire pigs using whole-genome sequencing data. A total of 23 and 33 suggestive significant SNPs (P<1×10^(-6)) were detected for FCR and RFI, respectively. However, none of the SNPs achieved the genome-wide significance threshold (P<5×10^(-8)). Importantly, three common SNPs (SSC7:7987268, SSC13:42350250, and SSC13:42551718) were associated with both FCR and RFI. Additionally, the NEDD9 gene related to FCR and RFI traits was overlapped. This study detected novel SNPs on SSC7 and SSC13 common for FCR and RFI. These results provide new insights into the genetic mechanisms and candidate genes of FE-related traits in pigs.

A High-Density Genetic Linkage Map and Fine Mapping of QTL For Feed Conversion Efficiency in Common Carp (Cyprinus carpio)

Feed conversion efficiency (FCE) is an economically crucial trait in fish, however, little progress has been made in genetics and genomics for this trait because phenotypes of the trait are difficult to measure. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,416 SNP markers for common carp (Cyprinus carpio) based on high throughput genotyping with the carp 250K single nucleotide polymorphism (SNP) array in a full-sib F1 family of mirror carp (Cyprinus carpio) consisting of 141 progenies. The linkage map contained 11,983 distinct loci and spanned 3,590.09 cM with an average locus interval of 0.33 cM. A total of 17 QTL for the FCE trait were detected on four LGs (LG9, LG20, LG28, and LG32), explaining 8.9-15.9% of the phenotypic variations. One major cluster containing eight QTL (qFCE1-28, qFCE2-28, qFCE3-28, qFCE4-28, qFCE5-28, qFCE6-28, qFCE7-28, and qFCE8-28) was detected on LG28. Two clusters consisting of four QTL (qFCE1-32, qFCE2-32, qFCE3-32, and qFCE4-32) and three QTL (qFCE1-20, qFCE2-20, and qFCE3-20) were detected on LG32 and LG20, respectively. Nine candidate genes (ACACA, SCAF4, SLC2A5, TNMD, PCDH1, FOXO, AGO1, FFAR3, and ARID1A) underlying the feed efficiency trait were also identified, the biological functions of which may be involved in lipid metabolism, carbohydrate metabolism, energy deposition, fat accumulation, digestion, growth regulation, and cell proliferation and differentiation according to GO (Gene Ontology). As an important tool, high-density and high-resolution genetic linkage maps play a crucial role in the QTL fine mapping of economically important traits. Our novel findings provided new insights that elucidate the genetic basis and molecular mechanism of feed efficiency and the subsequent marker-assisted selection breeding in common carp.

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; -0.60 and -0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.

Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs

Body length, body height, and total teat number are economically important traits in pig breeding, as these traits are usually associated with the growth, reproductivity, and longevity potential of piglets. Here, we report a genetic analysis of these traits using a population comprising 2,068 Large White pigs. A genotyping-by-sequencing (GBS) approach was used to provide high-density genome-wide SNP discovery and genotyping. Univariate and bivariate animal models were used to estimate heritability and genetic correlations. The results showed that heritability estimates for body length, body height, and total teat number were 0.25 ± 0.04, 0.11 ± 0.03, and 0.22 ± 0.04, respectively. The genetic correlation between body length and body height exhibited a strongly positive correlation (0.63 ± 0.15), while a positive but low genetic correlation was observed between total teat number and body length. Furthermore, we used two different genome-wide association study (GWAS) approaches: single-locus GWAS and weighted single-step GWAS (WssGWAS), to identify candidate genes for these traits. Single-locus GWAS detected 76, 13, and 29 significant single-nucleotide polymorphisms (SNPs) associated with body length, body height, and total teat number. Notably, the most significant SNP (S17_15781294), which is located 20 kb downstream of the BMP2 gene, explained 9.09% of the genetic variance for body length traits, and it also explained 9.57% of the genetic variance for body height traits. In addition, another significant SNP (S7_97595973), which is located in the ABCD4 gene, explained 8.92% of the genetic variance for total teat number traits. GWAS results for these traits identified some candidate genomic regions, such as SSC6: 14.96–15.02 Mb, SSC7: 97.18–98.18 Mb, SSC14: 128.29–131.15 Mb, SSC17: 15.39–17.27 Mb, and SSC17: 22.04–24.15 Mb, providing a starting point for further inheritance research. Most quantitative trait loci were detected by single-locus GWAS and WssGWAS. These findings reveal the complexity of the genetic mechanism of the three traits and provide guidance for subsequent genetic improvement through genome selection.

Mechanism of the growth and development of the posterior silk gland and silk secretion revealed by mutation of the fibroin light chain in silkworm

Silkworm, as a model organism, has very high economic value due to its silk secretion ability. Although a large number of studies have attempted to elucidate the mechanism of silk secretion, it remains unclear. In this study, the fibroin light chain (Fib-L) gene of silkworm was subjected to CRISPR/Cas9 editing, which yielded premature termination of translation at 135 aa. Compared with those of the wild type, the posterior silk glands (PSGs) of the homozygous mutants on the third day of the fifth instar showed obvious premature degeneration. Comparative transcriptome and proteomic analyses of the PSGs of wild-type individuals, heterozygous mutants and homozygous mutants were performed on the fourth day of the fifth instar. A GO enrichment analysis showed that the differentially expressed genes (DEGs) between homozygous mutants and wild-type individuals were enriched in cytoskeleton-related terms, and a KEGG enrichment analysis showed that the upregulated DEGs between homozygous mutants and wild-type individuals were enriched in the phagosome and apoptosis pathways. These results indicated that apoptosis was activated prematurely in the PSGs of homozygous mutants. Furthermore, autophagy and heat shock response were activated in the PSGs of homozygous mutants, as demonstrated by an analysis of the DEGs related to autophagy and heat shock. A comparative proteomic analysis further confirmed that autophagy, apoptosis and the heat shock response were activated in the PSGs of homozygous mutants, which led to premature degradation of the PSGs. These results provide insights for obtaining a more in-depth understanding of the mechanism of silk secretion in silkworms.

Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs

Background

Improving feed efficiency (FE) is an important goal due to its economic and environmental significance for farm animal production. The FE phenotype is complex and based on the measurements of the individual feed consumption and average daily gain during a test period, which is costly and time-consuming. The identification of reliable predictors of FE is a strategy to reduce phenotyping efforts.

Results

Gene expression data of the whole blood from three independent experiments were combined and analyzed by machine learning algorithms to propose molecular biomarkers of FE traits in growing pigs. These datasets included Large White pigs from two lines divergently selected for residual feed intake (RFI), a measure of net FE, and in which individual feed conversion ratio (FCR) and blood microarray data were available. Merging the three datasets allowed considering FCR values (Mean = 2.85; Min = 1.92; Max = 5.00) for a total of n = 148 pigs, with a large range of body weight (15 to 115 kg) and different test period duration (2 to 9 weeks). Random forest (RF) and gradient tree boosting (GTB) were applied on the whole blood transcripts (26,687 annotated molecular probes) to identify the most important variables for binary classification on RFI groups and a quantitative prediction of FCR, respectively. The dataset was split into learning (n = 74) and validation sets (n = 74). With iterative steps for variable selection, about three hundred’s (328 to 391) molecular probes participating in various biological pathways, were identified as important predictors of RFI or FCR. With the GTB algorithm, simpler models were proposed combining 34 expressed unique genes to classify pigs into RFI groups (100% of success), and 25 expressed unique genes to predict FCR values (R² = 0.80, RMSE = 8%). The accuracy performance of RF models was slightly lower in classification and markedly lower in regression.

Conclusion

From small subsets of genes expressed in the whole blood, it is possible to predict the binary class and the individual value of feed efficiency. These predictive models offer good perspectives to identify animals with higher feed efficiency in precision farming applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07843-4.

Genomic Prediction in Local Breeds: The Rendena Cattle as a Case Study

Simple Summary

Although genomic selection is being used in many livestock species, it has not yet been considered in local breeds due to the lower population size and the potential less effective impact on the genetic evaluation of these breeds. The current research aims to investigate how genomic data can impact the accuracy of genetic predictions for beef traits in Rendena, a small local cattle breed of the North-East of Italy selected for a dual purpose. Classical animal models using only phenotypic information were compared with two models that integrated genomic data with pedigree information. The genomic models presented better accuracy in estimated breeding values of the animals than the ‘classical’ animal model, especially the ‘simpler’ one assuming homogeneous variances of single nucleotide polymorphisms. Our results show that the inclusion of genomic information can be successfully applied to breeding selection scenarios even in small local cattle breeds such as Rendena.

Abstract

The maintenance of local cattle breeds is key to selecting for efficient food production, landscape protection, and conservation of biodiversity and local cultural heritage. Rendena is an indigenous cattle breed from the alpine North-East of Italy, selected for dual purpose, but with lesser emphasis given to beef traits. In this situation, increasing accuracy for beef traits could prevent detrimental effects due to the antagonism with milk production. Our study assessed the impact of genomic information on estimated breeding values (EBVs) in Rendena performance-tested bulls. Traits considered were average daily gain, in vivo EUROP score, and in vivo estimate of dressing percentage. The final dataset contained 1691 individuals with phenotypes and 8372 animals in pedigree, 1743 of which were genotyped. Using the cross-validation method, three models were compared: (i) Pedigree-BLUP (PBLUP); (ii) single-step GBLUP (ssGBLUP), and (iii) weighted single-step GBLUP (WssGBLUP). Models including genomic information presented higher accuracy, especially WssGBLUP. However, the model with the best overall properties was the ssGBLUP, showing higher accuracy than PBLUP and optimal values of bias and dispersion parameters. Our study demonstrated that integrating phenotypes for beef traits with genomic data can be helpful to estimate EBVs, even in a small local breed.