|
1
|
Schaub D, Posbergh CJ. A Genomic and Phenotypic Investigation of Feed Efficiency and Growth Traits in Targhee and Rambouillet Sheep. Animals (Basel) 2025; 15:783. [PMID: 40150312 PMCID: PMC11939469 DOI: 10.3390/ani15060783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2025] [Revised: 02/12/2025] [Accepted: 03/08/2025] [Indexed: 03/29/2025] Open
Abstract
The U.S. range sheep industry uses estimated breeding values (EBVs) as part of their breeding objectives to increase post-weaning weight. The study objective was to quantify the relationship between lamb growth EBVs, feed intake, and feed efficiency. Eighty-one range ewe lambs were enrolled in the study to measure residual feed intake (RFI) over two 42-d periods at both the weaning and yearling stages. The ewe lambs' post-weaning weight EBVs (PWWT EBVs) were linearly associated with their phenotypic traits. Preliminary genome wide associations (GWAs) were also performed with Dry Matter Intake (DMI), RFI, mid-test body size, and average daily gain (ADG) and Ovine 50K SNP genotypes. Post-weaning weight EBVs were associated with dry matter intake (DMI) (p < 0.05) but had no association with residual feed intake (RFI) (p > 0.05) in both experimental periods. However, PWWT EBV was predictive of mid-test body weight in both periods (p < 0.05). A single SNP at Oar2:68,812,505, located within DMRT2, was associated with DMI and RFI in the second experimental period (Bonferroni corrected p <0.05). While selecting for higher post-weaning weight range ewes may increase feed consumed due to a larger body size, it was not associated with feed efficiency.
Collapse
Affiliation(s)
| | - Christian J. Posbergh
- Department of Animal and Range Sciences, Montana State University, Bozeman, MT 59717, USA;
| |
Collapse
|
|
2
|
Shirzadifar A, Manafiazar G, Davoudi P, Do D, Hu G, Miar Y. Prediction of growth and feed efficiency in mink using machine learning algorithms. Animal 2025; 19:101330. [PMID: 39862571 DOI: 10.1016/j.animal.2024.101330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 09/06/2024] [Accepted: 09/10/2024] [Indexed: 01/27/2025] Open
Abstract
The feed efficiency (FE) expresses as the amount of feed required per unit of BW gain. Since feed cost is the major input cost in the mink industry, evaluating of FE is a crucial step for competitiveness of the mink industry. However, the FE measures have not been widely adopted for the mink due to the high cost of periodically measuring BW and daily feed intake. Measuring individual daily feed intake and BW is time-consuming, labor-intensive, and stressful for the animals and mink producers. The main objectives of this study were to (1) evaluate the application of machine learning (ML) algorithms to predict the average daily gain (ADG), feed conversion ratio (FCR), and residual feed intake (RFI) values during the whole growing and furring period (15 weeks from August 1st to November 14th) using less expensive features such as sex, color type, age, BW and length; (2) find the most significant contributing feature within the growth and furring period to predict the ADG, FCR and RFI. The color and sex features were recorded on 1 088 mink and mink's age, BW and length were measured every 3 weeks from August 1st to November 14th which is called P1-P5. The ADG, FCR, and RFI were then predicted by the selected ML algorithms using multiple combinations of the observed and measured features from P1 to P5. By comparing the calculated ADG, FCR, and RFI values with the predicted values, it was determined that the most accurate combination of features was to include all features such as sex, color, age, BW and body length on August 1st (at the beginning of the P1). Among selected ML algorithms, the extreme gradient boosting (XGB) algorithm provided the most accurate and reliable prediction for the ADG (R2 = 0.71, RMSE = 0.10), FCR (R2 = 0.74, RMSE = 0.14), and RFI (R2 = 0.76, RMSE = 0.10). The XGB algorithm can be an accurate algorithm to predict the ADG, FCR, and RFI values without measuring costly daily feed intake. In addition, sex was identified as the most significant feature to predict the ADG, FCR, and RFI values with the importance scores of 0.85, 0.67, and 0.79, respectively.
Collapse
Affiliation(s)
- A Shirzadifar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, Nova Scotia B2N 5E3, Canada; Biosystems Engineering Department, Shiraz University, Shiraz, Iran
| | - G Manafiazar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, Nova Scotia B2N 5E3, Canada
| | - P Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, Nova Scotia B2N 5E3, Canada
| | - D Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, Nova Scotia B2N 5E3, Canada
| | - G Hu
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, Nova Scotia B2N 5E3, Canada
| | - Y Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, Nova Scotia B2N 5E3, Canada.
| |
Collapse
|
|
3
|
Sun J, Ibragimov E, Luigi-Sierra MG, Fredholm M, Karlskov-Mortensen P. Investigation of the effect of missense mutations in AHR and DNAH11 on feed conversion ratio and average daily residual feed intake in Duroc, Landrace and Yorkshire pigs. Anim Genet 2025; 56:e13492. [PMID: 39561984 DOI: 10.1111/age.13492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 11/06/2024] [Accepted: 11/07/2024] [Indexed: 11/21/2024]
Abstract
Feed efficiency (FE) in pigs is an important factor in the profitability of pig farming operations. It refers to the ability of a pig to convert the feed it consumes into body weight. We used two metrics to measure FE: feed conversion ratio and average daily residual feed intake. A previous genome-wide association study and transcriptome study in crossbred pigs identified two QTL regions on SSC9 associated with residual feed intake and pointed out two candidate genes of interest: (a) the gene encoding the Aryl Hydrocarbon Receptor gene (AHR) transcription factor; and (b) the Dynein, Axonemal, Heavy Polypeptide 11 gene (DNAH11). The previous study identified missense mutations in both genes leading to a conservative substitution of glycine to cysteine in AHR (AHR_rs339939442) and two non-conservative substitutions in DNAH11, where arginine is replaced by threonine (DNAH11_rs325475644) and alanine is replaced by threonine (DNAH11_rs346074031). We have now genotyped the missense mutations in independent cohorts of 107 Duroc, 155 Landrace and 160 Yorkshire pigs to substantiate further if these variants directly impact FE-related phenotypes. We verified that allele T of AHR_rs339939442 in AHR improves FE in Yorkshire pigs. Genotype GG of AHR_rs339939442 was fixed in Duroc pigs. We also confirmed that the variants rs325475644 and rs346074031 in DNAH11 did not affect FE. The findings contribute valuable insights into the genetic mechanisms governing FE in pigs, potentially offering contributions for future enhancements of FE.
Collapse
Affiliation(s)
- Jiahong Sun
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
| | - Emil Ibragimov
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
| | - Maria Gracia Luigi-Sierra
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
| | - Merete Fredholm
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
| | - Peter Karlskov-Mortensen
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg C, Denmark
| |
Collapse
|
|
4
|
Zhang S, Xiang Y, Jian Y, Zhao Q, Sun J, Huang Y, Xu J, Qi X, Li J, Zheng Z, Fu L, Liu Y, Li X. Uncovering Molecular Mechanisms of Feed Efficiency in Pigs Through Multi-Omics Analysis of the Jejunum. Animals (Basel) 2025; 15:137. [PMID: 39858137 PMCID: PMC11758640 DOI: 10.3390/ani15020137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Revised: 12/28/2024] [Accepted: 01/07/2025] [Indexed: 01/27/2025] Open
Abstract
Feed efficiency (FE) is a crucial trait in pig production that influences both economic viability and environmental sustainability. The jejunum, an essential organ for nutrient absorption, plays a significant role in determining FE by affecting how pigs process and utilize feed. To explore the genetic and regulatory mechanisms behind FE, we conducted an integrative multi-omics study using RNA sequencing (RNA-seq) and ATAC sequencing (ATAC-seq) on pigs with high and low FE. By comparing gene expression and chromatin accessibility profiles in the jejunum, we identified key differentially expressed genes (DEGs) and differentially accessible regions (DARs) associated with lipid metabolism and immune function, both of which are critical pathways for efficient growth. Notably, we identified transcription factors such as GATA4 and EHF and genes like SCARB1 and GRXCR1 that may play regulatory roles in FE. Our findings provide novel insights into the molecular mechanisms governing FE in pigs, offering potential targets for genetic selection and nutritional interventions to enhance feed efficiency and sustainability in pig production.
Collapse
Affiliation(s)
- Saixian Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; (S.Z.); (X.Q.); (J.L.)
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Yue Xiang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Yaobang Jian
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Qiulin Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Jiahui Sun
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Yi Huang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Jing Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Xiaolong Qi
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; (S.Z.); (X.Q.); (J.L.)
| | - Jingjin Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; (S.Z.); (X.Q.); (J.L.)
| | - Zhuqing Zheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Liangliang Fu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| | - Yuwen Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China; (S.Z.); (X.Q.); (J.L.)
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (Y.X.); (Y.J.); (Q.Z.); (J.S.); (Y.H.); (J.X.); (Z.Z.); (L.F.)
| |
Collapse
|
|
5
|
Lu Z, Zhang T, Zhao Y, Pang Y, Guo M, Zhu X, Li Y, Li Z. The influence of host genotype and gut microbial interactions on feed efficiency traits in pigs. Front Microbiol 2024; 15:1459773. [PMID: 39606106 PMCID: PMC11599184 DOI: 10.3389/fmicb.2024.1459773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Accepted: 10/23/2024] [Indexed: 11/29/2024] Open
Abstract
Feed efficiency and growth performance are economically important traits in pigs. Precious studies have been revealed that both genetics and gut microbes could influence host phenotypes, however, the mechanisms by which they affect pig growth and feed efficiency remain poorly understood. In this study, 361 crossbred Duroc × (Landrace × Yorkshire) commercial pigs were genotyped using GeneSeek Porcine SNP50K BeadChip, and the microbiotas from fecal samples were acquired using microbial 16S rRNA gene sequencing technology to investigate the impact of host genetics and gut microorganisms on growth and feed efficiency. The results showed that the heritability and enterobacterial force ranged from 0.27 to 0.46 and 0 to 0.03, respectively. Genome-wide association studies (GWAS) identified seven significant SNPs to be associated with growth and feed efficiency, and several genes, including AIF1L, ASS1, and QRFP were highlighted as candidates for the analyzed traits. Additionally, microbiome-genome-wide association studies GWAS revealed potential links between CCAR2, EGR3, GSTM3, and GPR61 genes and the abundance of microorganisms, such as Trueperella, Victivallis, and Erysipelatoclostridium. In addition, six microbial genera linked to growth and feed efficiency were identified as follows Lachnospiraceae_UCG-005, Prevotellaceae_UCG-003, Prevotellaceae_NK3B31_group, Prevotella_1, Prevotella_9, and Veillonella. Our findings provide novel insights into the factors influencing host phenotypic complexity and identify potential microbial targets for enhancing pig feed efficiency through selective breeding. This could aid in the development of strategies to manipulate the gut microbiota to optimize growth rates and feed efficiency in pig breeding.
Collapse
Affiliation(s)
- Zhuoda Lu
- School of Animal Science and Technology, Foshan University, Foshan, China
| | - Tao Zhang
- School of Animal Science and Technology, Foshan University, Foshan, China
| | - Yunxiang Zhao
- Guangxi Yangxiang Co., Ltd., Guigang, China
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Yanqin Pang
- College of Animal Science and Technology, Guangxi University, Nanning, China
| | - Meng Guo
- Guangxi Yangxiang Co., Ltd., Guigang, China
| | - Xiaoping Zhu
- School of Animal Science and Technology, Foshan University, Foshan, China
| | - Ying Li
- School of Animal Science and Technology, Foshan University, Foshan, China
| | - Zhili Li
- School of Animal Science and Technology, Foshan University, Foshan, China
| |
Collapse
|
|
6
|
Mondin C, Faggion S, Giannuzzi D, Gallo L, Schiavon S, Carnier P, Bonfatti V. Genetic merit of sires for ad libitum residual feed intake affects feed efficiency of restricted-fed heavy pigs but not body weight gain tissue composition. PLoS One 2024; 19:e0312307. [PMID: 39418252 PMCID: PMC11486364 DOI: 10.1371/journal.pone.0312307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 10/03/2024] [Indexed: 10/19/2024] Open
Abstract
The study aimed at evaluating how sires, classified for their additive genetic effects on residual feed intake (RFI) of ad libitum-fed progeny, influence growth performance, tissue accretion, and gain composition in restricted-fed offspring (96-168 kg body weight, BW). A total of 416 purebred C21 Goland pigs, offspring of 23 sires, were randomly allocated to three feeding groups: ad libitum, restricted medium-protein, or restricted low-protein. Empty BW, body lipid mass and body protein mass were estimated from individual BW and backfat measures using literature equations. Residuals of a linear regression of average daily feed intake on average empty BW, body lipid and protein daily gains were used as estimates of individual RFI in ad libitum-fed pigs. Additive genetic effects of sires on RFI of ad libitum-fed pigs were estimated with a linear animal model and solutions of the model were used to allocate the sires to low- (LRFI), medium- (MRFI), or high-RFI (HRFI) groups. Restricted-fed progeny of LRFI sires exhibited reduced average daily feed intake (-3%) compared to MRFI and HRFI progeny. This indicates that LRFI progeny make a more efficient use of energy intake and implies that variation in RFI across families, assessed under ad libitum feeding, is related to the across-family variation in feed efficiency detected under restricted feeding. LRFI progeny exhibited also a lower feed conversion ratio (-11%), partially resulting from of a 3% increase in growth rate compared with HRFI. Thus, LRFI progeny consumed less feed, while growing at a similar or slightly higher rate than MRFI or HRFI. No significant differences across sire classes were observed for daily tissue accretion and gain composition. Hence, we can hypothesise that efficient sires would not affect carcass leanness of heavy pig progeny fed restricted.
Collapse
Affiliation(s)
- Chiara Mondin
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro (Padova), Italy
| | - Sara Faggion
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro (Padova), Italy
| | - Diana Giannuzzi
- Department of Agronomy, Food, Natural Resource, Animals and Environment, University of Padova, Legnaro (Padova), Italy
| | - Luigi Gallo
- Department of Agronomy, Food, Natural Resource, Animals and Environment, University of Padova, Legnaro (Padova), Italy
| | - Stefano Schiavon
- Department of Agronomy, Food, Natural Resource, Animals and Environment, University of Padova, Legnaro (Padova), Italy
| | - Paolo Carnier
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro (Padova), Italy
| | - Valentina Bonfatti
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro (Padova), Italy
| |
Collapse
|
|
7
|
Xiang Y, Sun J, Ma G, Dai X, Meng Y, Fu C, Zhang Y, Zhao Q, Li J, Zhang S, Zheng Z, Li X, Fu L, Li K, Qi X. Integrating Multi-Omics Data to Identify Key Functional Variants Affecting Feed Efficiency in Large White Boars. Genes (Basel) 2024; 15:980. [PMID: 39202341 PMCID: PMC11353296 DOI: 10.3390/genes15080980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Revised: 07/22/2024] [Accepted: 07/23/2024] [Indexed: 09/03/2024] Open
Abstract
Optimizing feed efficiency through the feed conversion ratio (FCR) is paramount for economic viability and sustainability. In this study, we integrated RNA-seq, ATAC-seq, and genome-wide association study (GWAS) data to investigate key functional variants associated with feed efficiency in pigs. Identification of differentially expressed genes in the duodenal and muscle tissues of low- and high-FCR pigs revealed that pathways related to digestion of dietary carbohydrate are responsible for differences in feed efficiency between individuals. Differential open chromatin regions identified by ATAC-seq were linked to genes involved in glycolytic and fatty acid processes. GWAS identified 211 significant single-nucleotide polymorphisms associated with feed efficiency traits, with candidate genes PPP1R14C, TH, and CTSD. Integration of duodenal ATAC-seq data and GWAS data identified six key functional variants, particularly in the 1500985-1509676 region on chromosome 2. In those regions, CTSD was found to be highly expressed in the duodenal tissues of pigs with a high feed conversion ratio, suggesting its role as a potential target gene. Overall, the integration of multi-omics data provided insights into the genetic basis of feed efficiency, offering valuable information for breeding more efficient pig breeds.
Collapse
Affiliation(s)
- Yue Xiang
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China; (Y.X.); (Y.M.); (J.L.); (S.Z.); (K.L.)
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Jiahui Sun
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Guojian Ma
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Xueting Dai
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Yuan Meng
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China; (Y.X.); (Y.M.); (J.L.); (S.Z.); (K.L.)
| | - Chong Fu
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Yan Zhang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Qiulin Zhao
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Jingjin Li
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China; (Y.X.); (Y.M.); (J.L.); (S.Z.); (K.L.)
| | - Saixian Zhang
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China; (Y.X.); (Y.M.); (J.L.); (S.Z.); (K.L.)
| | - Zhuqing Zheng
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Xinyun Li
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Liangliang Fu
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education and Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; (J.S.); (G.M.); (X.D.); (C.F.); (Y.Z.); (Q.Z.); (Z.Z.); (X.L.); (L.F.)
| | - Kui Li
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China; (Y.X.); (Y.M.); (J.L.); (S.Z.); (K.L.)
| | - Xiaolong Qi
- Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518000, China; (Y.X.); (Y.M.); (J.L.); (S.Z.); (K.L.)
| |
Collapse
|
|
8
|
Payen C, Kerouanton A, Novoa J, Pazos F, Benito C, Denis M, Guyard M, Moreno FJ, Chemaly M. Effects of Major Families of Modulators on Performances and Gastrointestinal Microbiota of Poultry, Pigs and Ruminants: A Systematic Approach. Microorganisms 2023; 11:1464. [PMID: 37374967 DOI: 10.3390/microorganisms11061464] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 05/25/2023] [Accepted: 05/26/2023] [Indexed: 06/29/2023] Open
Abstract
Considering the ban on the use of antibiotics as growth stimulators in the livestock industry, the use of microbiota modulators appears to be an alternative solution to improve animal performance. This review aims to describe the effect of different families of modulators on the gastrointestinal microbiota of poultry, pigs and ruminants and their consequences on host physiology. To this end, 65, 32 and 4 controlled trials or systematic reviews were selected from PubMed for poultry, pigs and ruminants, respectively. Microorganisms and their derivatives were the most studied modulator family in poultry, while in pigs, the micronutrient family was the most investigated. With only four controlled trials selected for ruminants, it was difficult to conclude on the modulators of interest for this species. For some modulators, most studies showed a beneficial effect on both the phenotype and the microbiota. This was the case for probiotics and plants in poultry and minerals and probiotics in pigs. These modulators seem to be a good way for improving animal performance.
Collapse
Affiliation(s)
- Cyrielle Payen
- French Agency for Food, Environmental and Occupational Health and Safety, ANSES, Hygiene and Quality of Poultry, Pig Products Unit, 22440 Ploufragan, France
| | - Annaëlle Kerouanton
- French Agency for Food, Environmental and Occupational Health and Safety, ANSES, Hygiene and Quality of Poultry, Pig Products Unit, 22440 Ploufragan, France
| | - Jorge Novoa
- Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), Darwin 3, 28049 Madrid, Spain
| | - Florencio Pazos
- Computational Systems Biology Group, National Centre for Biotechnology (CNB-CSIC), Darwin 3, 28049 Madrid, Spain
| | - Carlos Benito
- Instituto de Gestión de la Innovación y del Conocimiento, INGENIO (CSIC and U. Politécnica de Valencia), Edificio 8E, Cam. de Vera, 46022 Valencia, Spain
| | - Martine Denis
- French Agency for Food, Environmental and Occupational Health and Safety, ANSES, Hygiene and Quality of Poultry, Pig Products Unit, 22440 Ploufragan, France
| | - Muriel Guyard
- French Agency for Food, Environmental and Occupational Health and Safety, ANSES, Hygiene and Quality of Poultry, Pig Products Unit, 22440 Ploufragan, France
| | - F Javier Moreno
- Instituto de Investigación en Ciencias de la Alimentación (CIAL), CSIC-UAM, CEI (UAM + CSIC), Nicolás Cabrera 9, 28049 Madrid, Spain
| | - Marianne Chemaly
- French Agency for Food, Environmental and Occupational Health and Safety, ANSES, Hygiene and Quality of Poultry, Pig Products Unit, 22440 Ploufragan, France
| |
Collapse
|
|
9
|
Genome-Wide Association Analysis and Genetic Parameters for Feed Efficiency and Related Traits in Yorkshire and Duroc Pigs. Animals (Basel) 2022; 12:ani12151902. [PMID: 35892552 PMCID: PMC9329986 DOI: 10.3390/ani12151902] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/04/2022] [Accepted: 07/20/2022] [Indexed: 11/17/2022] Open
Abstract
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.
Collapse
|