Genetic parameters for feed efficiency traits and their relationships with growth and carcass traits in Duroc pigs

Pork carcass composition, meat and belly qualities as influenced by feed efficiency selection in replacement boars from Large White sire and dam lines

This study evaluated carcass attributes, meat and belly qualities in finisher boars (n = 79) selected for feed efficiency (low, intermediate and high) based on estimated breeding value for feed conversion ratio within a Large White dam and sire genetic lines. The sire line had lower trimmed fat proportions and higher lean than the dam line (P < 0.01). Genetic lines expressed slight colour changes and drip losses (P < 0.05), with no differences in pH, marbling and cooking traits (P > 0.05). High-efficient animals presented the highest lean yield (P < 0.01), the lowest trimmed fat proportion (P < 0.01) and no effect on meat and belly quality attributes (P > 0.05) compared with other efficient groups. Interaction between efficiency group and genetic line was only detected for belly weight and thickness (P < 0.01). High-efficient animals offer a greater leanness level, with minimal impact on meat and belly quality traits.

Genome-wide association study to reveal new candidate genes using single-step approaches for productive traits of Yorkshire pig in Korea

OBJECTIVE

The objective is to identify genomic regions and candidate genes associated with age to 105 kg (AGE), average daily gain (ADG), backfat thickness (BF), and eye muscle area (EMA) in Yorkshire pig.

METHODS

This study used a total of 104,380 records and 11,854 single nucleotide polymorphism (SNP) data obtained from Illumina porcine 60K chip. The estimated genomic breeding values (GEBVs) and SNP effects were estimated by single-step genomic best linear unbiased prediction (ssGBLUP).

RESULTS

The heritabilities of AGE, ADG, BF, and EMA were 0.50, 0.49, 0.49, and 0.23, respectively. We identified significant SNP markers surpassing the Bonferroni correction threshold (1.68×10-6), with a total of 9 markers associated with both AGE and ADG, and 4 markers associated with BF and EMA. Genome-wide association study (GWAS) analyses revealed notable chromosomal regions linked to AGE and ADG on Sus scrofa chromosome (SSC) 1, 6, 8, and 16; BF on SSC 2, 5, and 8; and EMA on SSC 1. Additionally, we observed strong linkage disequilibrium on SSC 1. Finally, we performed enrichment analyses using gene ontology and Kyoto encyclopedia of genes and genomes (KEGG), which revealed significant enrichments in eight biological processes, one cellular component, one molecular function, and one KEGG pathway.

CONCLUSION

The identified SNP markers for productive traits are expected to provide valuable information for genetic improvement as an understanding of their expression.

Genetic evaluation for production and body size traits using different animal models in purebred-Duroc pigs

Duroc pigs are popular crossbred terminal sires, and accurate assessment of genetic parameters in the population can help to rationalize breeding programmes. The principle aim of this study were to evaluate the genetic parameters of production (birth weight, BW; age at 115 kg, AGE; feed conversion ratio, FCR) and body size (body length, BL; body height, BH; front cannon circumference, FCC) traits of Duroc pigs. The second objective was to analyze the fit of different genetic assessment models. The variance components and correlations of BW (28,348 records), AGE (28,335 records), FCR (11,135 records), BL (31,544 records), BH (21,862 records), and FCC (14,684 records) traits were calculated by using DMU and AIREMLF90 from BLUPF90 package. In the common environment model, the heritability of BW, AGE, FCR, BL, BH, and FCC traits were 0.17 ± 0.014, 0.30 ± 0.019, 0.28 ± 0.024, 0.16 ± 0.013, 0.14 ± 0.017, and 0.081 ± 0.016, with common litter effect values of 0.25, 0.20, 0.18, 0.23, 0.19, and 0.16, respectively. According to the results of the Akaike information criterion (AIC) calculations, models with smaller AIC values have a better fit. We found that the common environment model with litter effects as random effects for estimating genetic parameters had a better fit. In this Model, the estimated genetic correlations between AGE with BW, FCR, BL, BH, and FCC traits were -0.28 (0.040), 0.76 (0.038), -0.71 (0.036), -0.44 (0.060), and -0.60 (0.073), respectively, with phenotypic correlations of -0.17, 0.52, -0.22, -0.13 and -0.24, respectively. In our analysis of genetic trends for six traits in the Duroc population from 2012 to 2021, we observed significant genetic trends for AGE, BL, and BH. Particularly noteworthy is the rapid decline in the genetic trend for AGE, indicating an enhancement in the pig's growth rate through selective breeding. Therefore, we believe that some challenging-to-select traits can benefit from the genetic correlations between traits. By selecting easily measurable traits, they can gain from synergistic selection effects, leading to genetic progress. Conducting population genetic parameter analysis can assist us in devising breeding strategies.

Comparative Serum Proteome Analysis Indicates a Negative Correlation between a Higher Immune Level and Feed Efficiency in Pigs

Identifying and verifying appropriate biomarkers is instrumental in improving the prediction of early-stage pig production performance while reducing the cost of breeding and production. The main factor that affects the production cost and environmental protection cost of the pig industry is the feed efficiency of pigs. This study aimed to detect the differentially expressed proteins in the early blood index determination serum between high-feed efficiency and low-feed efficiency pigs and to provide a basis for further identification of biomarkers using the isobaric tandem mass tag and parallel reaction monitoring approach. In total, 350 (age, 90 ± 2 d; body weight, 41.20 ± 4.60 kg) purebred Yorkshire pigs were included in the study, and their serum samples were obtained during the early blood index determination. The pigs were then arranged based on their feed efficiency; 24 pigs with extreme phenotypes were grouped as high-feed efficiency and low-feed efficiency, with 12 pigs in each group. A total of 1364 proteins were found in the serum, and 137 of them showed differential expression between the groups with high- and low-feed efficiency, with 44 of them being upregulated and 93 being downregulated. PRM (parallel reaction monitoring) was used to verify 10 randomly chosen differentially expressed proteins. The proteins that were differentially expressed were shown to be involved in nine pathways, including the immune system, digestive system, human diseases, metabolism, cellular processing, and genetic information processing, according to the KEGG and GO analyses. Moreover, all of the proteins enriched in the immune system were downregulated in the high-feed efficiency pigs, suggesting that a higher immune level may not be conducive to improving feed efficiency in pigs. This study provides insights into the important feed efficiency proteins and pathways in pigs, promoting the further development of protein biomarkers for predicting and improving porcine feed efficiency.

Genome-Wide Association Study of Growth Traits in a Four-Way Crossbred Pig Population

Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to analyze ten growth traits on 223 four-way intercross pigs. A total of 227,921 highly consistent single nucleotide polymorphisms (SNPs) uniformly dispersed throughout the entire genome were used to conduct GWAS. A total of 53 SNPs were identified for ten growth traits using the mixed linear model (MLM), of which 18 SNPs were located in previously reported quantitative trait loci (QTL) regions. Two novel QTLs on SSC4 and SSC7 were related to average daily gain from 30 to 60 kg (ADG30–60) and body length (BL), respectively. Furthermore, 13 candidate genes (ATP5O, GHRHR, TRIM55, EIF2AK1, PLEKHA1, BRAP, COL11A2, HMGA1, NHLRC1, SGSM1, NFATC2, MAML1, and PSD3) were found to be associated with growth traits in pigs. The GWAS findings will enhance our comprehension of the genetic architecture of growth traits. We suggested that these detected SNPs and corresponding candidate genes might provide a biological foundation for improving the growth and production performance of pigs in swine breeding.

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.

Comparison of genomic prediction methods for residual feed intake in broilers

Residual feed intake (RFI) is a measure of the feed efficiency of animals. Previous studies have identified SNPs associated with RFI. The objective of this study was to compare the GBLUP model with the GA-BLUP model including previously identified associated SNPs. The nine associated SNPs were obtained from the genome-wide association study on a discovery population as preselection information. These models were analysed using ASREML software using a 5-fold cross-validation method on a validation population. With the genetic architecture (GA) matrix used, which was conducted with the nine RFI-associated SNPs, the prediction accuracy of RFI was improved compared with the original GBLUP model. The calculated optimal ω was 0.981 for RFI, which is in line with the optimal range from 0.9 to 1.0 in the gradient test. The prediction accuracy increased by 2% in the GA-BLUP model with ω being 0.981 compared with the GBLUP model. In conclusion, the GA-BLUP with the nine RFI-associated SNPs and an optimal ω can improve the prediction accuracy for a specific trait compared with GBLUP.

Single-step genomic evaluation with metafounders for feed conversion ratio and average daily gain in Danish Landrace and Yorkshire pigs

Background

The single-step genomic best linear unbiased prediction (SSGBLUP) method is a popular approach for genetic evaluation with high-density genotype data. To solve the problem that pedigree and genomic relationship matrices refer to different base populations, a single-step genomic method with metafounders (MF-SSGBLUP) was put forward. The aim of this study was to compare the predictive ability and bias of genomic evaluations obtained with MF-SSGBLUP and standard SSGBLUP. We examined feed conversion ratio (FCR) and average daily gain (ADG) in DanBred Landrace (LL) and Yorkshire (YY) pigs using both univariate and bivariate models, as well as the optimal weighting factors (ω), which represent the proportions of the genetic variance not captured by markers, for ADG and FCR in SSGBLUP and MF-SSGBLUP.

Results

In general, SSGBLUP and MF-SSGBLUP showed similar predictive abilities and bias of genomic estimated breeding values (GEBV). In the LL population, the predictive ability for ADG reached 0.36 using uni- or bi-variate SSGBLUP or MF-SSGBLUP, while the predictive ability for FCR was highest (0.20) for the bivariate model using MF-SSGBLUP, but differences between analyses were very small. In the YY population, predictive ability for ADG was similar for the four analyses (up to 0.35), while the predictive ability for FCR was highest (0.36) for the uni- and bi-variate MF-SSGBLUP analyses. SSGBLUP and MF-SSGBLUP exhibited nearly the same bias. In general, the bivariate models had lower bias than the univariate models. In the LL population, the optimal ω for ADG was ~ 0.2 in the univariate or bivariate models using SSGBLUP or MF-SSGBLUP, and the optimal ω for FCR was 0.70 and 0.55 for SSGBLUP and MF-SSGBLUP, respectively. In the YY population, the optimal ω ranged from 0.25 to 0. 35 for ADG across the four analyses and from 0.10 to 0.30 for FCR.

Conclusions

Our results indicate that MF-SSGBLUP performed slightly better than SSGBLUP for genomic evaluation. There was little difference in the optimal weighting factors (ω) between SSGBLUP and MF-SSGBLUP. Overall, the bivariate model using MF-SSGBLUP is recommended for single-step genomic evaluation of ADG and FCR in DanBred Landrace and Yorkshire pigs.

Genetic Parameters for Different Measures of Feed Efficiency and Their Relationship to Production Traits in Three Purebred Pigs

Residual feed intake (RFI) gained attention as a potential alternative to the feed conversion ratio (FCR). Thus, this study aimed to estimate genetic parameters for different feed efficiency (FE) traits (FCR, RFI1 to RFI5) and their genetic correlation to on-test daily weight gain (ADG), backfat (BFT), loin muscle area (LMA), lean percentage (LP), and total feed intake (FI) for 603 Male Duroc (DD), 295 Landrace (LL), and 341 Yorkshire (YY). The common spatial pen effect was also estimated in these traits. Five RFI measures were estimated by regressing daily feed intake on initial testing age (ITA), initial testing weight (IBW), and ADG for RFI1; other models were the same as RFI1 except for additional BFT for RFI2; LMA for RFI3; BFT and LMA for RFI4; BFT, LMA, and average metabolic body weight (AMBW) instead of IBW for RFI5. Genetic parameters estimated using two animal models and the REML method showed moderate heritability for FCR in all breeds (0.22 and 0.28 for DD, 0.31 and 0.39 for LL, 0.17 and 0.22 for YY), low heritability for the majority of RFI measures in DD (0.15 to 0.23) and YY (0.14 to 0.20) and moderate heritability for all RFI measures in LL (0.31 to 0.34). Pen variance explained 7% to 22% for FE and 0% to 9% for production traits’ phenotypic variance. The genetic correlation revealed that selection against less complex RFI1 in DD and LL and RFI2 in YY would bring the most advantageous reduction to FI (0.71 for DD, 0.49 for LL, 0.43 YY) without affecting ADG in all breeds (0.06 for DD, −0.11 for LL, 0.05 for YY), decrease in BFT, and increase in LP in DD (0.51 in BFT, −0.77 in LP) and LL (0.45 in BFT, −0.83 in LP). Therefore, inclusion of these breed-specific RFI measures in the future selection criteria would help improve feed efficiency in the swine industry.

Effect of feed efficiency on growth performance, body composition, and fat deposition in growing Hu lambs

The present study aimed to investigate the relationship between growth performance, body composition, and fat deposition factors, and feed efficiency in growing lambs. We measured average daily feed intake (ADFI) and body weight (BW) from 653 Hu sheep that were fed a pellet diet. The residual feed intake (RFI) not significantly genetic and phenotypic correlated with the metabolic body weight (MBW) and average daily gain (ADG), but it was significantly genetic and phenotypic correlated with ADFI and the feed conversion ratio (FCR) (p < 0.01). However, the FCR was significantly associated with growth traits (p < 0.01). With the same ADG, body fat deposition was greater in animals with low feed efficiency compared with high feed efficiency. Therefore, excessive fat deposition can affect the feed efficiency of the body, and organ weight and gut-weight have a greater impact on the feed efficiency of lambs. The reticulum stomach and jejunum of lambs with a low RFI were smaller compared with that in the high RFI, indicating that lambs with a low RFI have less intake and a higher absorption rate. Small organs, such as the liver, of lambs with high FE might be associated with low energy expenditure and slow metabolism. This study provides a new perspective to study the biological processes responsible for feed efficiency variation in lambs.

Genetic Analysis of Major Production and Reproduction Traits of Korean Duroc, Landrace and Yorkshire Pigs

The study aimed to investigate the genetic parameters of the production and reproduction traits of Korean Duroc, Landrace, and Yorkshire pigs. Three production traits, namely average daily gain (ADG), age at 105 kg body weight (DAYS105) and backfat thickness (BFT), and three reproduction traits, namely age at first farrowing (AFF), total number of piglets born (TNB) and number of piglets born alive (NBA), were analyzed. The reproduction dataset was based on first-parity gilts only. However, the production dataset comprised pigs of both sexes. Genetic parameters were estimated from individual datasets using a multiple-trait animal model in AIREMLF90 software. The heritability values of ADG, DAYS105 and BFT were 0.34-0.36, 0.41-0.44 and 0.38-0.48, respectively, across breeds. Heritability values for AFF, TNB and NBA were 0.07-0.14, 0.09-0.11 and 0.09-0.10, respectively. Strong genetic correlations existed between ADG and DAYS105 (-0.97) and between TNB and NBA (0.90 to 0.96). In line with breeding goals, all productive traits in Duroc pigs, and all reproduction traits except AFF in Landrace and Yorkshire pigs, also showed noticeable improvements in recent years. In conclusion, we believe that our findings on economic traits would greatly assist future pig breeding decisions in Korea.

Weighted Single-Step GWAS Identified Candidate Genes Associated with Growth Traits in a Duroc Pig Population

Growth traits are important economic traits of pigs that are controlled by several major genes and multiple minor genes. To better understand the genetic architecture of growth traits, we performed a weighted single-step genome-wide association study (wssGWAS) to identify genomic regions and candidate genes that are associated with days to 100 kg (AGE), average daily gain (ADG), backfat thickness (BF) and lean meat percentage (LMP) in a Duroc pig population. In this study, 3945 individuals with phenotypic and genealogical information, of which 2084 pigs were genotyped with a 50 K single-nucleotide polymorphism (SNP) array, were used for association analyses. We found that the most significant regions explained 2.56–3.07% of genetic variance for four traits, and the detected significant regions (>1%) explained 17.07%, 18.59%, 23.87% and 21.94% for four traits. Finally, 21 genes that have been reported to be associated with metabolism, bone growth, and fat deposition were treated as candidate genes for growth traits in pigs. Moreover, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses implied that the identified genes took part in bone formation, the immune system, and digestion. In conclusion, such full use of phenotypic, genotypic, and genealogical information will accelerate the genetic improvement of growth traits in pigs.

The impact of training on data from genetically-related lines on the accuracy of genomic predictions for feed efficiency traits in pigs

Background

Most genomic predictions use a unique population that is split into a training and a validation set. However, genomic prediction using genetically heterogeneous training sets could provide more flexibility when constructing the training sets in small populations. The aim of our study was to investigate the potential of genomic prediction of feed efficiency related traits using training sets that combine animals from two different, but genetically-related lines. We compared realized prediction accuracy and prediction bias for different training set compositions for five production traits.

Results

Genomic breeding values (GEBV) were predicted using the single-step genomic best linear unbiased prediction method in six scenarios applied iteratively to two genetically-related lines (i.e. 12 scenarios). The objective for all scenarios was to predict GEBV of pigs in the last three generations (~ 400 pigs, G7 to G9) of a given line. For each line, a control scenario was set up with a training set that included only animals from that line (target line). For all traits, adding more animals from the other line to the training set did not increase prediction accuracy compared to the control scenario. A small decrease in prediction accuracies was found for average daily gain, backfat thickness, and daily feed intake as the number of animals from the target line decreased in the training set. Including more animals from the other line did not decrease prediction accuracy for feed conversion ratio and residual feed intake, which were both highly affected by selection within lines. However, prediction biases were systematic for these cases and might be reduced with bivariate analyses.

Conclusions

Our results show that genomic prediction using a training set that includes animals from genetically-related lines can be as accurate as genomic prediction using a training set from the target population. With combined reference sets, accuracy increased for traits that were highly affected by selection. Our results provide insights into the design of reference populations, especially to initiate genomic selection in small-sized lines, for which the number of historical samples is small and that are developed simultaneously. This applies especially to poultry and pig breeding and to other crossbreeding schemes.

Maternal effect on body measurement and meat production traits in purebred Duroc pigs

We investigated maternal effect on nine body measurement traits (body height, body length, front width (FW), chest width (CW), hind width (HW), chest depth, chest girth (CHG), front cannon circumference (FCC) and rear cannon circumference (RCC)) measured at the end of performance testing and five meat production traits (ages at the start and end of performance testing (D30 and D105), average daily gain (ADG), backfat thickness and loin muscle area) in purebred Duroc pigs. Genetic parameters for each trait were estimated by using six single-trait models with and without common litter environmental effect, maternal genetic effect and direct-maternal genetic correlation. The value of Akaike's information criterion was lowest with the model including direct additive genetic and common litter environmental effects for 10 traits. The estimated proportion of common litter environmental variance to phenotypic variance was approximately ≥0.1 for D30, D105, ADG, FW, CW, HW, CHG, FCC and RCC. Using a model without common litter environmental effect would overestimate the direct heritability of most traits. Standard errors of estimated genetic parameters tended to be larger in models including maternal genetic effect. The results indicate that a compromise could be made for accurate genetic parameter estimation for body measurement traits, as well as meat production traits, in pigs by considering common litter environmental effect.

Identification of Important Proteins and Pathways Affecting Feed Efficiency in DLY Pigs by iTRAQ-Based Proteomic Analysis

Simple Summary

Feed efficiency is one of the most valuable economic traits in the pig industry. The small intestine is the site where most of the nutrients are absorbed from ingested food. Here, we studied the relationship between small intestinal proteomics and feed efficiency in Duroc × (Landrace × Yorkshire) pigs, which is the most popular commercial pig in the Chinese pork market. Exploring the molecular mechanisms of feed efficiency will create great value for the pig industry. Our research provided a reference for further understanding of the key proteins that affect small intestinal microvilli formation and the important pathways related to feed efficiency in pigs.

Abstract

Feed efficiency is an economically important trait controlled by multiple genes in pigs. The small intestine is the main organ of digestion and nutrient absorption. To explore the biological processes by which small intestine proteomics affects feed efficiency (FE), we investigated the small intestinal tissue proteomes of high-FE and low-FE pigs by the isobaric tag for relative and absolute quantification (iTRAQ) method. In this study, a total of 225 Duroc × (Landrace × Yorkshire) (DLY) commercial pigs were ranked according to feed efficiency, which ranged from 30 kg to 100 kg, and six pigs with extreme phenotypes were selected, three in each of the high and low groups. A total of 1219 differentially expressed proteins (DEPs) were identified between the high-FE and low-FE groups (fold change ≥1.2 or ≤0.84; p ≤ 0.05), of which 785 were upregulated, and 484 were downregulated. Enrichment analysis indicated that the DEPs were mainly enriched in actin filament formation, microvilli formation, and small intestinal movement pathways. Protein functional analysis and protein interaction networks indicated that RHOA, HCLS1, EZR, CDC42, and RAC1 were important proteins that regulate FE in pigs. This study provided new insights into the important pathways and proteins involved in feed efficiency in pigs.

Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs

Improving feed efficiency (FE) is a major goal of pig breeding, reducing production costs and providing sustainability to the pig industry. Reliable predictors for FE could assist pig producers. We carried out untargeted blood metabolite profiling in uncastrated males from Danbred Duroc (n = 59) and Danbred Landrace (n = 50) pigs at the beginning and end of a FE testing phase to identify biomarkers and biological processes underlying FE and related traits. By applying linear modeling and clustering analyses coupled with WGCNA framework, we identified 102 and 73 relevant metabolites in Duroc and Landrace based on two sampling time points. Among them, choline and pyridoxamine were hub metabolites in Duroc in early testing phase, while, acetoacetate, cholesterol sulfate, xanthine, and deoxyuridine were identified in the end of testing. In Landrace, cholesterol sulfate, thiamine, L-methionine, chenodeoxycholate were identified at early testing phase, while, D-glutamate, pyridoxamine, deoxycytidine, and L-2-aminoadipate were found at the end of testing. Validation of these results in larger populations could establish FE prediction using metabolomics biomarkers. We conclude that it is possible to identify a link between blood metabolite profiles and FE. These results could lead to improved nutrient utilization, reduced production costs, and increased FE.

Genome-Wide Association Study Reveals Candidate Genes for Growth Relevant Traits in Pigs

Improvement of the growth rate is a challenge in the pig industry, the Average Daily Gain (ADG) and Days (AGE) to 100 kg are directly related to growth performance. We performed genome-wide association study (GWAS) and genetic parameters estimation for ADG and AGE using the genomic and phonemic from four breed (Duroc, Yorkshire, Landrace, and Pietrain) populations. All analyses were performed by a multi-loci GWAS model, FarmCPU. The GWAS results of all four breeds indicate that five genome-wide significant SNPs were associated with ADG, and the nearby genomic regions explained 4.08% of the genetic variance and 1.90% of the phenotypic variance, respectively. For AGE, six genome-wide significant SNPs were detected, and the nearby genomic regions explained 8.09% of the genetic variance and 3.52% of phenotypic variance, respectively. In total, nine candidate genes were identified to be associated with growth and metabolism. Among them, TRIB3 was reported to associate with pig growth, GRP, TTR, CNR1, GLP1R, BRD2, HCRTR2, SEC11C, and ssc-mir-122 were reported to associate with growth traits in human and mouse. The newly detected candidate genes will advance the understanding of growth related traits and the identification of the novel variants will suggest a potential use in pig genomic breeding programs.

Transcriptome Analysis of Adipose Tissue Indicates That the cAMP Signaling Pathway Affects the Feed Efficiency of Pigs

Feed efficiency (FE) is one of the main factors that determine the production costs in the pig industry. In this study, RNA Sequencing (RNA-seq) was applied to identify genes and long intergenic non-coding RNAs (lincRNAs) that are differentially expressed (DE) in the adipose tissues of Yorkshire pigs with extremely high and low FE. In total, 147 annotated genes and 18 lincRNAs were identified as DE between high- and low-FE pigs. Seventeen DE lincRNAs were significantly correlated with 112 DE annotated genes at the transcriptional level. Gene ontology (GO) analysis revealed that DE genes were significantly associated with cyclic adenosine monophosphate (cAMP) metabolic process and Ca²⁺ binding. cAMP, a second messenger has an important role in lipolysis, and its expression is influenced by Ca²⁺ levels. In high-FE pigs, nine DE genes with Ca²⁺ binding function, were down-regulated, whereas S100G, which encodes calbindin D9K that serve as a Ca²⁺ bumper, was up-regulated. Furthermore, ATP2B2, ATP1A4, and VIPR2, which participate in the cAMP signaling pathway, were down-regulated in the upstream of lipolysis pathways. In high-FE pigs, the key genes involved in the lipid biosynthetic process (ELOVL7 and B4GALT6), fatty acid oxidation (ABCD2 and NR4A3), and lipid homeostasis (C1QTNF3 and ABCB4) were down-regulated. These results suggested that cAMP was involved in the regulation on FE of pigs by affecting lipid metabolism in adipose tissues.

Genetic assessment of residual feed intake as a feed efficiency trait in the Pacific white shrimp Litopenaeus vannamei

BACKGROUND

Residual feed intake (RFI) was investigated as a measure of feed efficiency in a breeding population of Litopenaeus vannamei. Shrimp from 34 families were housed individually and feed efficiency and growth traits were recorded during two successive growth periods. The objectives of this study were (1) to estimate the heritability of RFI and related traits, including feed efficiency ratio (FER), average daily gain (ADG) and daily feed intake (DFI), (2) to determine the relationships between RFI and other traits, and (3) to evaluate the variation of these traits across two growth periods.

RESULTS

Shrimp displayed large inter-individual variation in RFI, FER, ADG and DFI during each growth period. Heritability estimates of all these traits during both periods reached high values (0.577 ± 0.232 to 0.707 ± 0.252). RFI showed weak and no genetic correlations with ADG during the two growth periods between days 1 to 21 (0.135 ± 0.204) and 22 to 42 (-0.018 ± 0.128), respectively, but high positive genetic correlations with DFI (>0.8). Weak and moderate negative genetic correlations were observed between RFI and FER during the two periods (-0.126 ± 0.208 and -0.387 ± 0.183). As evidenced by the high genetic correlations between the two periods for each trait (>0.6), trait performance of the shrimp tended to be consistent across periods.

CONCLUSIONS

For the first time, accurate measurement of individual feed efficiency on a large scale was achieved in shrimp. Although the estimated heritability reported here for RFI may be overestimated, it is a heritable trait in L. vannamei that can be improved by genetic improvement. For L. vannamei, the biggest potential advantage in using RFI as a measure of feed efficiency is that it is independent of growth rate, and thus genetic selection on RFI has the potential to improve feed efficiency and reduce feed intake, without compromising growth performance.

Genetic parameter estimation and evaluation of Duroc boars for feed efficiency and component traits

MacNeil, M. D. and Kemp, R. A. 2015. Genetic parameter estimation and evaluation of Duroc boars for feed efficiency and component traits. Can. J. Anim. Sci. 95: 155–159. The objective of this research was to produce a genetic evaluation for traits related to feed efficiency of Duroc boars. Meeting this objective required partitioning phenotypic (co)variance into additive genetic and environmental components for feed intake and traits indicative of growth and body composition. Boars (N=3291) were housed in group pens of 22 to 24 animals with two electronic feeders per pen and feed intake was recorded for 8 to 14 wk. Body weight was recorded for each boar at the start and end of test, at approximately 100 kg and at up to three times during the test. The pedigree used contained sire and dam of each boar with at least one recorded phenotype (N=4651) and their maternal and paternal grandsires. Variance components were estimated by restricted maximum likelihood for animal models in a series of uni-variate and bi-variate analyses. Two multiple trait genetic evaluations were conducted to predict estimated breeding value for feed intake using animal models. The first evaluation included feed intake (h2=0.33±0.05), age at 100 kg (h2=0.31±0.04), and subcutaneous fat depth (h2=0.47±0.05). The second genetic evaluation included feed intake, average daily gain (h2=0.27±0.04), mid-test weight (h2=0.33±0.05), and subcutaneous fat depth. Genetic correlations of feed intake with age at 100 kg and fat depth were –0.80±0.05 and 0.57±0.08, respectively. Estimated breeding values for measures of feed efficiency (residual feed intake and residual gain) were calculated from the results of the second analysis and the associated additive genetic (co)variance components.

Association of single nucleotide polymorphisms in the microRNA miR-1596 locus with residual feed intake in chickens

MicroRNAs are an abundant class of small non-coding RNAs that regulate gene expression. Genetic variations in microRNA sequences may be associated with phenotype differences by influencing the expression of microRNAs and/or their targets. This study identified two single nucleotide polymorphisms (SNPs) in the genomic region of the microRNA miR-1596 locus of chicken. Of the two SNPs, one was 95 bp upstream of miR-1596 (g.5678784A>T) and the other was in the middle of the sequence producing the mature microRNA gga-miR-1596-3p (g.5678944A>G). Genotypic distribution of the two SNPs had large differences among 12 chicken breeds (lines), especially between the fast-growing commercial lines and the slow-growing Chinese indigenous breeds for the g.5678784A>T SNP. Only the g.5678784A>T SNP was significantly associated with residual feed intake (RFI) in the F2 population derived from a fast-growing and a slow-growing broiler as well as in the pure Huiyang bearded chicken. The birds with the AA genotype of the g.5678784A>T SNP had lower RFI and higher expression of the mature gga-miR-1596-3p microRNA of miR-1596 than did those with the other genotypes of the same SNP. We also found that the expression of the mature gga-miR-1596-3p microRNA of miR-1596 was significantly associated with RFI. These findings suggest that miR-1596 can become a candidate gene related to RFI, and its genetic variation may contribute to changes in RFI by altering expression levels of the mature gga-miR-1596-3p microRNA in chicken.

Intermuscular and intramuscular adipose tissues: Bad vs. good adipose tissues

Human studies of the influence of aging and other factors on intermuscular fat (INTMF) were reviewed. Intermuscular fat increased with weight loss, weight gain, or with no weight change with age in humans. An increase in INTMF represents a similar threat to type 2 diabetes and insulin resistance as does visceral adipose tissue (VAT). Studies of INTMF in animals covered topics such as quantitative deposition and genetic relationships with other fat depots. The relationship between leanness and higher proportions of INTMF fat in pigs was not observed in human studies and was not corroborated by other pig studies. In humans, changes in muscle mass, strength and quality are associated with INTMF accretion with aging. Gene expression profiling and intrinsic methylation differences in pigs demonstrated that INTMF and VAT are primarily associated with inflammatory and immune processes. It seems that in the pig and humans, INTMF and VAT share a similar pattern of distribution and a similar association of components dictating insulin sensitivity. Studies on intramuscular (IM) adipocyte development in meat animals were reviewed. Gene expression analysis and genetic analysis have identified candidate genes involved in IM adipocyte development. Intramuscular (IM) adipocyte development in human muscle is only seen during aging and some pathological circumstance. Several genetic links between human and meat animal adipogenesis have been identified. In pigs, the Lipin1 and Lipin 2 gene have strong genetic effects on IM accumulation. Lipin1 deficiency results in immature adipocyte development in human lipodystrophy. In humans, overexpression of Perilipin 2 (PLIN2) facilitates intramyocellular lipid accretion whereas in pigs PLIN2 gene expression is associated with IM deposition. Lipins and perilipins may influence intramuscular lipid regardless of species.

Correlated responses in sow appetite, residual feed intake, body composition, and reproduction after divergent selection for residual feed intake in the growing pig

Residual feed intake (RFI) has been explored as an alternative selection criterion to feed conversion ratio to capture the fraction of feed intake not explained by expected production and maintenance requirements. Selection experiments have found that low RFI in the growing pig is genetically correlated with reduced fatness and feed intake. Selection for feed conversion ratio also reduces sow appetite and fatness, which, together with increased prolificacy, has been seen as a hindrance for sow lifetime performance. The aims of our study were to derive equations for sow RFI during lactation (SRFI) and to evaluate the effect of selection for RFI during growth on sow traits during lactation. Data were obtained on 2 divergent lines selected for 7 generations for low and high RFI during growth in purebred Large Whites. The RFI was measured on candidates for selection (1,065 pigs), and sow performance data were available for 480 sows having from 1 to 3 parities (1,071 parities). Traits measured were sow daily feed intake (SDFI); sow BW and body composition before farrowing and at weaning (28.4 ± 1.7d); number of piglets born total, born alive, and surviving at weaning; and litter weight, average piglet BW, and within-litter SD of piglet BW at birth, 21 d of age (when creep feeding was available), and weaning. Sow RFI was defined as the difference between observed SDFI and SDFI predicted for sow maintenance and production. Daily production requirements were quantified by litter size and daily litter BW gain as well as daily changes in sow body reserves. The SRFI represented 24% of the phenotypic variability of SDFI. Heritability estimates for RFI and SRFI were both 0.14. The genetic correlation between RFI and SRFI was 0.29 ± 0.23. Genetic correlations of RFI with sow traits were low to moderate, consistent with responses to selection; selection for low RFI during growth reduced SDFI and increased number of piglets and litter growth, but also increased mobilization of body reserves. No effect on rebreeding performance was found. Metabolic changes previously observed during growth in response to selection might explain part of the better efficiency of the low-RFI sows, decreasing basal metabolism and favoring rapid allocation of resources to lactation. We propose to consider SRFI as an alternative to SDFI to select for efficient sows with reduced input demands during lactation.

Muscle characteristics and meat quality traits are affected by divergent selection on residual feed intake in pigs

Residual feed intake (RFI) is defined as the difference between the observed feed intake and that expected based on requirements for maintenance and production. A divergent selection was conducted during 4 generations in Large White male pigs to produce low and high RFI lines. The present study aims at determining the influence of this selection on biochemical and histological traits of skeletal muscle, and relating these changes to correlated effects on growth, carcass composition, and meat quality traits. At 8 d preslaughter, biopsies from the LM were taken in the fed state on 14 females from each RFI line fed ad libitum. Animals were slaughtered at 107.8 ± 8.0 kg of BW without any previous fasting. Samples of LM, semimembranosus (SM), biceps femoris (BFM), and rhomboideus muscles were taken at both 30 min and 24 h postmortem. Myofiber typing was only assessed in LM. Low RFI pigs ("efficient") had leaner carcasses with greater muscle content (P < 0.001), less backfat thickness (P < 0.001), and less intramuscular fat content in all 4 muscles (P < 0.01 to P = 0.04). Their greater muscle content was associated with hypertrophy of all fast-twitch fibers. Glycogen content in all glycolytic muscles (i.e., LM, SM and BFM), was greater in low than high RFI pigs. The greater accumulation of glycogen in LM of low RFI pigs was specifically located in the fast-twitch glycolytic IIBW fibers, which correspond to fibers containing IIb, IIb + IIx, or IIx myosin heavy chains. The difference in muscle glycogen content between RFI line pigs was more significant in the living animals (P = 0.0003) than at 30 min postmortem (P = 0.08). This was associated with a decreased ultimate pH (P = 0.001), and greater lightness of color (P = 0.002) and drip loss (P = 0.04) in LM of low than high RFI line pigs, suggesting that selection for reduced RFI may impair some meat quality traits, such as water-holding capacity. Pigs from the low RFI line exhibited a greater (P = 0.02) percentage of IIBW fibers in LM and tended (P < 0.10) to have less lipid β-oxidative capacity in LM, SM, and BFM. In contrast, no difference (P > 0.10) between lines was found for citrate synthase and lactate dehydrogenase activities, mitochondrial activity, and expression of genes coding for uncoupling proteins 2 and 3. Differences between RFI pigs in plasma leptin, cortisol, and thyroid hormone concentrations are presented and discussed. In conclusion, selection for low RFI influenced muscle properties in a way favoring muscle mass, but likely impairing meat quality.

Measures of growth and feed efficiency and their relationships with body composition and carcass traits of growing pigs

Data from 53 hybrid (mainly Large White × Landrace) pigs, comprising 18 males, 18 females and 17 castrates, were used to examine the relationships among growth and feed efficiency traits measured in the growing animal, and their relationships with body composition and carcass traits at two target liveweight (90 and 120 kg) endpoints. The data were from individually penned pigs involved in a longitudinal experiment that started when the pigs were 32.4 ± 3.2 kg liveweight and 70 ± 1 days of age (mean ± s.d.). Weekly feed intake and liveweight, and body components data measured at 60, 90 and 120 kg by computed tomography scanning were used. Growth traits studied were: start of test liveweight, average daily gain (ADG), Kleiber ratio and relative growth rate. The feed efficiency traits were daily feed intake (DFI), feed conversion ratio (FCR) and residual feed intake. Body components and carcass traits were the weight of the body components (lean, fat, bone and skin tissues) and their percentages relative to liveweight. Three models were used for residual feed intake. The standard model (RFIstd) had metabolic weight and ADG as explanatory variables for feed intake, RFIadg had only ADG as explanatory variable, and the other (RFIfat) had percentage fat at 60 kg target liveweight included in the standard model. The RFIadg model resulted in R2 values of 36.9, 72.1 and 19.1% for males, females and castrates, respectively. The corresponding R2 values for the RFIstd model were 63.7, 72.1 and 37.1%, and those for the RFIfat model were 86.1, 80.0 and 71.9%. These results indicate that RFIfat may be a better trait to use for efficiency of feed utilisation, especially in castrates. There were significant interrelationships among growth traits (r = –0.46 to 0.98), and also among feed efficiency traits (r = 0.44 to 0.76). Of the feed efficiency traits studied, only FCR was significantly correlated with all the growth traits (r = 0.33 to –0.61), and DFI was correlated with start liveweight (r = 0.43) and ADG (r = 0.57). Growth traits per se were not correlated with body composition and carcass traits at each of the weight-constant target endpoints; however, feed intake was. High DFI was associated with high percentage fat (r = 0.39 to 0.49) and low percentage lean (r = –0.40 to –0.52) at both 90 and 120 kg target liveweights. As with DFI, high FCR, RFIadg and RFIstd were associated with high percentage fat and low percentage lean at both 90 and 120 kg target liveweights. There were no significant correlations between RFIfat and the body components and carcass traits. These results will enable the development of programs aimed at reducing feed costs and improving the economic value of the pig carcass.