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Alves AAC, Fernandes AFA, Lopes FB, Breen V, Hawken R, Rosa GJM. Genetic analysis of feed efficiency and novel feeding behavior traits measured in group-housed broilers using electronic feeders. Poult Sci 2024; 103:103737. [PMID: 38669821 PMCID: PMC11063640 DOI: 10.1016/j.psj.2024.103737] [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: 11/13/2023] [Revised: 03/26/2024] [Accepted: 04/03/2024] [Indexed: 04/28/2024] Open
Abstract
This study aimed to estimate genetic parameters for feeding behavior (FB) traits and to assess their genetic relationship with performance traits in group-housed broilers. In total, 99,472,151 visits were recorded for 95,711 birds between 2017 and 2022 using electronic feeders. The visits were first clustered into 2,667,617 daily observations for ten FB traits: daily feed intake (DFI), daily number of visits (NVIS), time spent at the feeders (TSF), number of visited feeders (NVF), visiting activity interval (VAI), feeding rate (FR), daily number of meals (NMEAL), average intake per meal (INTMEAL), number of visits per meal (VISMEAL) and interval between meals (MEALIVL). All FB traits were then considered as the average per bird across the feeding test period. Three growth traits (body weight at the start - SBW and at the end of the feeding test - FBW, and weight gain over the test period - BWG), and 2 feed efficiency (FE) traits (Feed Conversion Rate - FCR and Residual Feed Intake - RFI) were also recorded. The (co)variance components were estimated using multitrait animal mixed models. For growth and FE, the heritability (h2) estimates were moderate, ranging from 0.20 ± 0.01 (BWG) to 0.32 ± 0.02 (RFI). Overall, the h2 estimates for FB traits were higher than for productive traits, ranging from 0.31 ± 0.01 (DFI) to 0.56 ± 0.02 (TSF). DFI presented high genetic correlations (0.53-0.86) with all performance traits. Conversely, the remaining FB traits presented null to moderate genetic correlations with these traits, ranging from -0.38 to 0.42 for growth traits and between -0.14 and 0.25 for FE traits. Genetic selection for favorable feeding behavior is expected to exhibit a fast genetic response. The results suggest that it is possible to consider different feeding strategies without compromising the genetic progress of FE. Conversely, breeding strategies prioritizing a higher bird activity might result in lighter broiler lines in the long term, given the negative genetic correlations between visit-related traits (NV, NVF, and NMEAL) and growth traits (SBW and FBW).
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Affiliation(s)
- Anderson A C Alves
- Department of Animal and Dairy Sciences, University of Wisconsin, 53705, Madison, USA
| | | | | | | | | | - Guilherme J M Rosa
- Department of Animal and Dairy Sciences, University of Wisconsin, 53705, Madison, USA.
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Jie Y, Wen C, Huang Q, Gu S, Sun C, Li G, Yan Y, Wu G, Yang N. Distinct patterns of feed intake and their association with growth performance in broilers. Poult Sci 2024; 103:103974. [PMID: 38972283 PMCID: PMC11264188 DOI: 10.1016/j.psj.2024.103974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 06/07/2024] [Accepted: 06/07/2024] [Indexed: 07/09/2024] Open
Abstract
Improving feed utilization is a vital strategy to meet the growing global demand for meat and promote sustainable food production. Over the past few decades, significant improvements in the feed intake (FI) and feed utilization efficiency of broilers have been achieved through advanced breeding procedures, although dynamic changes in FI and their effects on the feed conversion ratio (FCR) have remained unclear. In this study, we measured individual weekly FI and body weight of 274 male broilers to characterize the dynamic FI patterns and investigate their relationship with growth performance. The broilers were from 2 purebred lines and their crossbreed and measurements were collected from 4 to 6 wk of age. Overall, a continuous increase in the weekly FI occurred from 4 to 6 wk of age, whereas the body weight gain (BWG) reached an inflection point in wk 5. The dynamic change in weekly FI was observed to follow 3 distinct FI patterns: pattern 1, a continuous weekly increase in FI; pattern 2, an increase followed by a plateau; pattern 3, an increase followed by a decrease. The prevalence of these patterns was similar in the purebred and crossbred populations: pattern 2 was most frequent, followed by a moderate proportion of pattern 1, and the lowest proportion of pattern 3. Broilers following pattern 1 displayed significantly better growth performance and feed utilization efficiency than those following pattern 3, emphasizing the importance of maintaining good appetite in the last stage of broiler production. In summary, this study has characterized the dynamic patterns of FI and their association with growth performance. Our results offer a new foundation for improving feed utilization efficiency and investigating feeding regulation in broilers.
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Affiliation(s)
- Yuchen Jie
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Chaoliang Wen
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Sanya Institute of China Agricultural University, Hainan, 572025, China
| | - Qiang Huang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shuang Gu
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Congjiao Sun
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Sanya Institute of China Agricultural University, Hainan, 572025, China
| | - Guangqi Li
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Yiyuan Yan
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Guiqin Wu
- Beijing Huadu Yukou Poultry Industry Co. Ltd., Beijing, 101206, China
| | - Ning Yang
- State Key Laboratory of Animal Biotech Breeding and Frontier Science Center for Molecular Design Breeding, China Agricultural University, Beijing, 100193, China; National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Department of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Sanya Institute of China Agricultural University, Hainan, 572025, China.
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3
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Mariandayani HN, Darwati S, Khaerunnisa I, Prasasty VD. Growth performance of Indonesian three-breed cross chicken associated with growth hormone and insulin-like growth factor 2 genes. Vet World 2023; 16:2471-2478. [PMID: 38328357 PMCID: PMC10844795 DOI: 10.14202/vetworld.2023.2471-2478] [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: 07/17/2023] [Accepted: 11/15/2023] [Indexed: 02/09/2024] Open
Abstract
Background and Aim Poultry, such as chickens, is an important source of animal protein, producing eggs and meat. Local chickens are able to adapt to the hot weather and become more resistant to disease. However, it has relatively slow growth and low egg production. These problems can be overcome through holding selection and crossing. Local chicken productivity is slow and low based on chicken growth. There is a need to examine the factors that influence growth and productivity. Therefore, this study aimed to evaluate crossbreed chicken growth performance, including body weight (BW), BW gain, feed intake, and feed conversion. Materials and Methods DNA was extracted from 40 chickens with the growth hormone (GH) gene and 40 chickens with the insulin-like growth factor 2 (IGF2) gene, followed by a polymerase chain reaction. Genotyping was performed using restriction fragment length polymorphism analysis. In animal selection and phenotypic data collection, 80 chickens from Sentul, Kampung, and Kedu were used to produce the second-generation three-crossbreed chickens (F2) using the GH gene. Results Growth hormone is a very relevant gene in chicken performance traits. Growth hormone and IGF2 genes regulate chicken production. This study presents the second-generation growth features of three-crossbreed chickens derived from Sentul, Kampung, and Kedu, all of which are native to Indonesia (F2). A statistically significant (p = 0.05) improvement in BW, weight gain, feed intake, and feed conversion over a 12-week period was observed when the animals were allowed free access to regular feed. Analysis of variance results indicated a significant (p = 0.0001) interaction between the 12-week period and GH and IGF2 gene sensitivities of different chicken breeds. Conclusion Crossbreed chicken growth performance increased within 12 weeks. This study highlighted the need to improve the productivity and breeding of domestic crossbred chickens to contribute to the Indonesian conservation and genetic diversity program.
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Affiliation(s)
| | - Sri Darwati
- Department of Animal Production and Technology, Faculty of Animal Husbandry, Bogor Agricultural University, Bogor, West Java 16680, Indonesia
| | - Isyana Khaerunnisa
- Research Center for Applied Zoology, National Research and Innovation Agency, Bogor, West Java 16912, Indonesia
| | - Vivitri Dewi Prasasty
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, Louisiana 70803, USA
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Sosa-Madrid BS, Maniatis G, Ibáñez-Escriche N, Avendaño S, Kranis A. Genetic Variance Estimation over Time in Broiler Breeding Programmes for Growth and Reproductive Traits. Animals (Basel) 2023; 13:3306. [PMID: 37958060 PMCID: PMC10649193 DOI: 10.3390/ani13213306] [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: 08/18/2023] [Revised: 10/12/2023] [Accepted: 10/19/2023] [Indexed: 11/15/2023] Open
Abstract
Monitoring the genetic variance of traits is a key priority to ensure the sustainability of breeding programmes in populations under directional selection, since directional selection can decrease genetic variation over time. Studies monitoring changes in genetic variation have typically used long-term data from small experimental populations selected for a handful of traits. Here, we used a large dataset from a commercial breeding line spread over a period of twenty-three years. A total of 2,059,869 records and 2,062,112 animals in the pedigree were used for the estimations of variance components for the traits: body weight (BWT; 2,059,869 records) and hen-housed egg production (HHP; 45,939 records). Data were analysed with three estimation approaches: sliding overlapping windows, under frequentist (restricted maximum likelihood (REML)) and Bayesian (Gibbs sampling) methods; expected variances using coefficients of the full relationship matrix; and a "double trait covariances" analysis by computing correlations and covariances between the same trait in two distinct consecutive windows. The genetic variance showed marginal fluctuations in its estimation over time. Whereas genetic, maternal permanent environmental, and residual variances were similar for BWT in both the REML and Gibbs methods, variance components when using the Gibbs method for HHP were smaller than the variances estimated when using REML. Large data amounts were needed to estimate variance components and detect their changes. For Gibbs (REML), the changes in genetic variance from 1999-2001 to 2020-2022 were 82.29 to 93.75 (82.84 to 93.68) for BWT and 76.68 to 95.67 (98.42 to 109.04) for HHP. Heritability presented a similar pattern as the genetic variance estimation, changing from 0.32 to 0.36 (0.32 to 0.36) for BWT and 0.16 to 0.15 (0.21 to 0.18) for HHP. On the whole, genetic parameters tended slightly to increase over time. The expected variance estimates were lower than the estimates when using overlapping windows. That indicates the low effect of the drift-selection process on the genetic variance, or likely, the presence of genetic variation sources compensating for the loss. Double trait covariance analysis confirmed the maintenance of variances over time, presenting genetic correlations >0.86 for BWT and >0.82 for HHP. Monitoring genetic variance in broiler breeding programmes is important to sustain genetic progress. Although the genetic variances of both traits fluctuated over time, in some windows, particularly between 2003 and 2020, increasing trends were observed, which warrants further research on the impact of other factors, such as novel mutations, operating on the dynamics of genetic variance.
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Affiliation(s)
- Bolívar Samuel Sosa-Madrid
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
- Institute for Animal Science and Technology, Universitat Politècnica de València, P.O. Box 2201, 46071 Valencia, Spain;
| | | | - Noelia Ibáñez-Escriche
- Institute for Animal Science and Technology, Universitat Politècnica de València, P.O. Box 2201, 46071 Valencia, Spain;
| | | | - Andreas Kranis
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
- Aviagen Ltd., Newbridge, Edinburgh EH28 8SZ, UK; (G.M.); (S.A.)
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Mahmoudi Zarandi M, Faraji-Arough H, Rokouei M, Mehri M. Residual feed intake breeding value associated with growth, carcass traits, meat quality, bone properties and humoral immunity in Japanese quail. Trop Anim Health Prod 2023; 55:139. [PMID: 37000287 DOI: 10.1007/s11250-023-03527-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 03/06/2023] [Indexed: 04/01/2023]
Abstract
Improved feed efficiency (FE) is one of the most important achievements in animal breeding programs. The present investigation aimed to determine the phenotypic correlations of residual feed intake (RFI) breeding value with some traits in growing Japanese quail. A total of 48 birds (24 males and 24 females) were selected from 220 quail chicks divided into three classes based on breeding values (BV) for RFI including low (LBV; n = 16), medium (MBV; n = 16), and high-BV (HBV; n = 16) were used to test FE. The effects of three groups of BV on the studied traits including carcass traits, meat quality, humoral immunity, and bone properties were evaluated. The BV for RFI was positively correlated with feed conversion ratio (FCR) and feed intake (FI) but not with metabolic BW (MBW0.75). Live body weight, carcass, breast, and thigh weight in the LBV-RFI group were significantly greater than those in the HBV-RFI group. The BV for RFI had a negative correlation with live body weight and thigh weight. Our findings suggested that the selection of LBV-RFI quails may be useful to increase live body weight without any adverse impact on meat quality and bone properties, and live body weight can be implemented in breeding programs as an indirect selection indicator for improvement of FE in quails.
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Affiliation(s)
| | - Hadi Faraji-Arough
- Department of Ostrich, Special Domestic Animals Institute, Research Institute of Zabol, Zabol, Iran
| | - Mohammad Rokouei
- Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Iran
| | - Mehran Mehri
- Department of Animal Science, Faculty of Agriculture, University of Zabol, Zabol, Iran
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Liu GY, Shi L, Chen YF, Chen H, Zhang C, Wang YT, Ning ZH, Wang DH. Estimation of genetic parameters of eggshell translucency and production traits in different genotypes of laying hens. Poult Sci 2023; 102:102616. [PMID: 37004251 PMCID: PMC10091017 DOI: 10.1016/j.psj.2023.102616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 02/16/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023] Open
Abstract
The translucency of eggshells is a ubiquitous appearance problem caused by moisture translocation and the accumulation of egg contents into the eggshell ultrastructure. Previous studies have mainly investigated the causes of eggshell translucency from nutritional and environmental perspectives. However, little is known of the effect of genetics the causes of eggshell translucency on hen production performance. To evaluate the genetic parameters of eggshell translucency and other production performance indicators, we performed an experiment on 3 pure hen lines: 624 Dwarf Layer-White, 1,612 Rhode Island Red, and 813 Rhode Island Red-White. We collected eggs from each hen over 5 d and measured eggshell translucent level (TL) using the grading method. Additionally we measured indicators of each hen during the laying period, including age at laying of the first egg (AFE), body weight at laying of the first egg (BWFE), weight of the first egg (FEW), body weight at 40 wk (BW40), egg weight at 40 wk (EW40), egg production up to 40 wk of age (EN), and calculated the genetic parameters among the indicators. The results showed that the estimated heritability of TL in the 3 genotypes were 0.30, 0.24, and 0.20, respectively, suggesting a low or moderate level of heritability. We found a positive correlation between TL and AFE, with genetic correlation coefficients 0.19 to 0.41, and negative genetic correlation between TL and EN, with correlation coefficient -0.36 to -0.19. Additionally, we observed positive correlation exists between AFE and FEW, BWFE and FEW, and BW40 and EW40; and negative correlation between AFE and EN in the 3 pure lines. These results enriched the research on heritability of eggshell translucency in different hen breeds and demonstrated moderate or low heritability of the indicator. Furthermore, eggshell translucency was negatively affected by AFE and EN. Our results provide a valuable reference for predicting selection response of eggshell translucency and production performance in brood hens, and locating the genes regulating eggshell translucency.
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7
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Davoudi P, Do DN, Colombo SM, Rathgeber B, Hu G, Sargolzaei M, Wang Z, Plastow G, Miar Y. Genetic and phenotypic parameters for feed efficiency and component traits in American mink. J Anim Sci 2022; 100:6633851. [PMID: 35801647 DOI: 10.1093/jas/skac216] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/08/2022] [Indexed: 11/15/2022] Open
Abstract
Feed cost is the largest expense of mink production systems, and therefore, improvement of feed efficiency (FE) through selection for high feed efficient mink is a practical way to increase the mink industry's sustainability. In this study, we estimated the heritability, phenotypic and genetic correlations for different FE measures and component traits, including harvest weight (HW), harvest length (HL), final body length (FBL), final body weight (FBW), average daily gain (ADG), daily feed intake (DFI), feed conversion ratio (FCR), residual feed intake (RFI), residual gain (RG), residual intake and gain (RIG), and Kleiber ratio (KR), using data from 2,288 American mink (for HW and HL), and 1,038-1,906 American mink (for other traits). Significance (P < 0.05) of fixed effects (farm, sex, and color-type), a covariate (age of animal), and random effects (additive genetic, maternal, and common litter) were evaluated through univariate models implemented in ASReml-R version 4. Genetic parameters were estimated via fitting a set of bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.28±0.06, 0.23±0.06, 0.28±0.10, 0.27±0.11, 0.25±0.09, 0.26±0.09, 0.20±0.09, 0.23±0.09, 0.21±0.10, 0.25±0.10, and 0.26±0.10 for HW, HL, FBL, FBW, ADG, DFI, FCR, RFI, RG, RIG, and KR, respectively. RIG had favorable genetic correlations with DFI (-0.62±0.24) and ADG (0.58±0.21), and non-significant (P > 0.05) genetic correlations with FBW (0.14±0.31) and FBL (-0.15±0.31). These results revealed that RIG might be superior trait as it guarantees reduced feed intake with faster-growing mink yet with no negative impacts on body weight and length. In addition, the strong positive genetic correlations (±SE) between KR with component traits (0.88±0.11 with FBW; 0.68±0.17 with FBL; and 0.97±0.02 with ADG) suggested KR as an applicable indirect measure of FE for improvement of component traits as it did not require the individual feed intake to be measured. Overall, our results confirmed the possibility of including FE traits in mink breeding programs to effectively select feed-efficient animals.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie M Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Guoyu Hu
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Mehdi Sargolzaei
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada.,Select Sires Inc., Plain City, OH, United States
| | - Zhiquan Wang
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Graham Plastow
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
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Bai H, Guo Q, Yang B, Dong Z, Li X, Song Q, Jiang Y, Wang Z, Chang G, Chen G. Effects of residual feed intake divergence on growth performance, carcass traits, meat quality, and blood biochemical parameters in small-sized meat ducks. Poult Sci 2022; 101:101990. [PMID: 35841639 PMCID: PMC9289854 DOI: 10.1016/j.psj.2022.101990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/10/2022] [Accepted: 05/29/2022] [Indexed: 11/28/2022] Open
Abstract
Feed efficiency (FE) is a major economic trait of meat duck. This study aimed to evaluate the effects of residual feed intake (RFI) divergence on growth performance, carcass traits, meat quality, and blood biochemical parameters in small-sized meat ducks. A total of 500 healthy 21-day-old male ducks were housed in individual cages until slaughter at 63 d of age. The growth performance was determined for all the ducks. The carcass yield, meat quality, and blood biochemical parameters were determined for the selected 30 high-RFI (HRFI) and 30 low-RFI (LRFI) ducks. In terms of growth performance, the RFI, feed conversion ratio (FCR), and average daily feed intake (ADFI) were found to be significantly lower in the LRFI group (P < 0.01), whereas no differences were observed in the BW and body weight gain (P > 0.05). For slaughter performance, no differences were observed in the carcass traits between the LRFI and HRFI groups (P > 0.05). For meat quality, the shear force of breast muscle was significantly lower in the LRFI group (P < 0.05), while the other meat quality traits of breast and thigh muscles demonstrated no differences (P > 0.05). For blood biochemical parameters, the serum concentrations of triglycerides (TG) and glucose (GLU) were significantly lower in the LRFI group (P < 0.05), while the other parameters showed no differences (P > 0.05). The correlation analysis demonstrated a high positive correlation between RFI, FCR, and ADFI (P < 0.01). The RFI demonstrated a negative effect on the breast muscle and lean meat yields, but a positive effect on the shear force of breast muscle (P < 0.05). Further, the RFI demonstrated a positive effect on the TG and GLU levels (P < 0.05). These results indicate that the selection for low RFI could improve the FE of small-sized meat ducks without affecting the production performance. This study provides valuable insight into the biological processes underlying the variations in FE in small-sized meat ducks.
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Affiliation(s)
- H Bai
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Jiangsu Yangzhou 225009, China
| | - Q Guo
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - B Yang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Z Dong
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - X Li
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Q Song
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Y Jiang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - Z Wang
- Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - G Chang
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Jiangsu Yangzhou 225009, China; Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China
| | - G Chen
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, The Ministry of Education of China, Institutes of Agricultural Science and Technology Development, Yangzhou University, Jiangsu Yangzhou 225009, China; Key Laboratory of Animal Genetics and Breeding and Molecular Design of Jiangsu Province, Yangzhou University, Yangzhou 225009, China.
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9
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He Z, Li S, Li W, Ding J, Zheng M, Li Q, Fahey AG, Wen J, Liu R, Zhao G. Comparison of genomic prediction methods for residual feed intake in broilers. Anim Genet 2022; 53:466-469. [PMID: 35292985 DOI: 10.1111/age.13186] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 02/24/2022] [Accepted: 02/28/2022] [Indexed: 11/30/2022]
Abstract
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.
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Affiliation(s)
- Zhengxiao He
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.,School of Agriculture and Food Science, University College Dublin, Dublin, Ireland
| | - Sen Li
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Wei Li
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Jiqiang Ding
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Maiqing Zheng
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Qinghe Li
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Alan G Fahey
- School of Agriculture and Food Science, University College Dublin, Dublin, Ireland
| | - Jie Wen
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Ranran Liu
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Guiping Zhao
- State Key Laboratory of Animal Nutrition, Key Laboratory of Animal (Poultry) Genetics Breeding and Reproduction, Ministry of Agriculture, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
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10
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Wang Y, Diao C, Kang H, Hao W, Mrode R, Chen J, Liu J, Zhou L. A Random Regression Model Based on a Single-Step Method for Improving the Genomic Prediction Accuracy of Residual Feed Intake in Pigs. Front Genet 2022; 12:769849. [PMID: 35178070 PMCID: PMC8843929 DOI: 10.3389/fgene.2021.769849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 12/29/2021] [Indexed: 11/13/2022] Open
Abstract
Residual feed intake (RFI) is considered as a measurement of feed efficiency, which is greatly related to the growth performance in pigs. Daily feeding records can be obtained from automatic feeders. In general, RFI is usually calculated from the total measurement records during the whole test period. This measurement cannot reflect genetic changes in different growth periods during the test. A random regression model (RRM) provides a method to model such type of longitudinal data. To improve the accuracy of genetic prediction for RFI, the RRM and regular animal models were applied in this study, and their prediction performances were compared. Both traditional pedigree-based relationship matrix (A matrix) and pedigree and genomic information-based relationship matrix (H matrix) were applied for these two models. The results showed that, the prediction accuracy of the RRM was higher than that of the animal model, increasing 24.2% with A matrix and 40.9% with H matrix. Furthermore, genomic information constantly improved the accuracy of evaluation under each evaluation model. In conclusion, longitudinal traits such as RFI can describe feed efficiency better, and the RRM with both pedigree and genetic information was superior to the animal model. These results provide a feasible method of genomic prediction using longitudinal data in animal breeding.
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Affiliation(s)
- Ye Wang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.,MARA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Chenguang Diao
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.,MARA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Huimin Kang
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan, China
| | - Wenjie Hao
- Best Genetic Breeding Farm, Inner Mongolia, China
| | - Raphael Mrode
- Animal Biosciences, International Livestock Research Institute, Nairobi, Kenya
| | - Junhai Chen
- Shenzhen Kingsino Technology Co., Ltd., Shenzhen, China
| | - Jianfeng Liu
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.,MARA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Lei Zhou
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China.,MARA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
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11
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Zhang X, Luan P, Cao D, Hu G. A High-Density Genetic Linkage Map and Fine Mapping of QTL For Feed Conversion Efficiency in Common Carp ( Cyprinus carpio). Front Genet 2021; 12:778487. [PMID: 34868267 PMCID: PMC8633483 DOI: 10.3389/fgene.2021.778487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 10/22/2021] [Indexed: 12/02/2022] Open
Abstract
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.
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Affiliation(s)
- Xiaofeng Zhang
- National and Local United Engineering Laboratory for Freshwater Fish Breeding, Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin, China
| | | | | | - Guo Hu
- National and Local United Engineering Laboratory for Freshwater Fish Breeding, Heilongjiang River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Harbin, China
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12
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Red milkwood ( Mimusops zeyheri) seed meal can replace maize meal in Japanese quail finisher diets without compromising growth performance, feed economy and carcass yield. Vet Anim Sci 2020; 10:100128. [PMID: 32734028 PMCID: PMC7386713 DOI: 10.1016/j.vas.2020.100128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 06/08/2020] [Accepted: 06/18/2020] [Indexed: 11/28/2022] Open
Abstract
Mimusops zeyheri seed meal has a higher energy content compared to maize meal. Its potential as a dietary energy source in Japanese quail finisher feeds was evaluated. Dietary Mimusops zeyheri seed meal did not compromise growth performance and feed utilisation efficiency of the quail. Mimusops zeyheri seed meal did not have a negative impact carcass (meat) yield. The seed meal reduced the quail's abdominal fat mass which can potentially result in the production of lean meat. Mimusops zeyheri seed meal can partially replace maize meal as a dietary energy source in male Japanese quail finisher feeds.
Mimusops zeyheri is widely distributed in sub-Saharan Africa and its seed meal (MZSM) has a higher energy content than maize meal (MM). We evaluated the potential of MZSM to substitute MM in Japanese quail finisher diets by determining its effects on growth performance, feed intake (FI) and feed utilisation efficiency, abdominal fat deposition and carcass yield. In a completely randomised design thirty-two 5-weeks old male Japanese quail were allocated to four diets wherein MZSM replaced MM at 0%, 12.5%, 25% and 37.5% (gross energy basis) and fed ad libitum for 4 weeks. Initial and weekly body weight, final body weight (FBW) and daily FI were measured. Body weight gain (BWG), average daily gain (ADG) and feed conversion ratio (FRC) were computed. At the end of the trial, following a 4-hour fast, the quail were weighed then humanely slaughtered and dressed. Carcass weight and dressing percent were determined. Abdominal fat was weighed. MZSM did not affect (P>0.05) the quail's FBW, BWG, ADG, FCR, carcass weight and dressing percent. MZSM at 37.5% inclusion decreased (P<0.0001) FI in weeks 1 and 2 and total FI of the quail. Dietary M. zeyheri seed meal decreased (P<0.0001) abdominal fat mass. Use of MZSM would be most economic at 37.5% inclusion because despite decreasing total FI, growth performance was similar to control. M. zeyheri seed meal can be used as a dietary energy source in Japanese quail finisher diets without compromising growth performance, feed utilisation efficiency and carcass yield.
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13
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GAUR GK, SAHOO NR, BHARTI PK, SINGH MUKESH, DUTT TRIVENI. Random regression models for genetic analysis of body weight in crossbred pigs. THE INDIAN JOURNAL OF ANIMAL SCIENCES 2019. [DOI: 10.56093/ijans.v89i10.95012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Body weight of an animal is represented by a continuous function of time (longitudinal trait) and can be characterized by a trajectory with number of measurements. The present study was carried out to determine heritability estimates of body weight in crossbred pigs (75% Landrace + 25% Bareilly local) using random regression model with Legendre polynomials of quadratic power. Data of 9044 records of 1,292 crossbred piglets, progeny of 86 boars and 98 sows; born in 184 parities between 5 years from 2013–17 was used for the study. Records on weight at birth and at 1 week interval up to 6 week were used. Model included sex, year of birth, season of birth and parity as fixed effect, age of dam at farrowing as co-variable and direct additive genetic effect and maternal permanent environmental effect as random regression. There was a steady increase in body weight over the age from birth (0.96 kg) to 6th week (9.0 kg). Direct additive genetic (0.006 to 7.37 kg2), maternal permanent environment (0.053 to 70.07 kg2) and total phenotypic (0.18 to 77.56 kg2) variance increased continuously from birth to 6 week of age. In general, heritability estimates of body weight at different ages of pre-weaning stage were low ranging from 0.031 to 0.12. The estimate increased up to 1st week (0.119±0.025) with very low value at birth (0.031±0.015) and decreased thereafter to 0.095±0.022 at 6 week. Relative importance of each order of Legendre polynomials showed that quadratic Legendre polynomials with three regression coefficients were enough to capture almost all variability in the model to explain all additive genetic and maternal permanent environment variability. Hence, use of random regression model with quadratic Legendre polynomials was suggested for genetic analysis of pig data for growth.
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14
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Chu TT, Madsen P, Norberg E, Wang L, Marois D, Henshall J, Jensen J. Genetic analysis on body weight at different ages in broiler chicken raised in commercial environment. J Anim Breed Genet 2019; 137:245-259. [PMID: 31621116 DOI: 10.1111/jbg.12448] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 08/12/2019] [Accepted: 09/19/2019] [Indexed: 10/25/2022]
Abstract
A multivariate model was developed and used to estimate genetic parameters of body weight (BW) at 1-6 weeks of age of broilers raised in a commercial environment. The development of model was based on the predictive ability of breeding values evaluated from a cross-validation procedure that relied on half-sib correlation. The multivariate model accounted for heterogeneous variances between sexes through standardization applied to male and female BWs differently. It was found that the direct additive genetic, permanent environmental maternal and residual variances for BW increased drastically as broilers aged. The drastic increase in variances over weeks of age was mainly due to scaling effects. The ratio of the permanent environmental maternal variance to phenotypic variance decreased gradually with increasing age. Heritability of BW traits ranged from 0.28 to 0.33 at different weeks of age. The direct genetic effects on consecutive weekly BWs had high genetic correlations (0.85-0.99), but the genetic correlations between early and late BWs were low (0.32-0.57). The difference in variance components between sexes increased with increasing age. In conclusion, the permanent environmental maternal effect on broiler chicken BW decreased with increasing age from weeks 1 to 6. Potential bias of the model that considered identical variances for sexes could be reduced when heterogeneous variances between sexes are accounted for in the model.
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Affiliation(s)
- Thinh Tuan Chu
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark.,Animal Breeding and Genomics, Wageningen University & Research, Wageningen, The Netherlands.,Faculty of Animal Science, Vietnam National University of Agriculture, Hanoi, Vietnam
| | - Per Madsen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Elise Norberg
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark.,Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway
| | - Lei Wang
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Danye Marois
- Cobb-Vantress Inc., Siloam Springs, Arkansas, USA
| | | | - Just Jensen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
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15
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Mebratie W, Madsen P, Hawken R, Romé H, Marois D, Henshall J, Bovenhuis H, Jensen J. Genetic parameters for body weight and different definitions of residual feed intake in broiler chickens. Genet Sel Evol 2019; 51:53. [PMID: 31547801 PMCID: PMC6757393 DOI: 10.1186/s12711-019-0494-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 09/06/2019] [Indexed: 11/30/2022] Open
Abstract
Background The objectives of this study were to (1) simultaneously estimate genetic parameters for BW, feed intake (FI), and body weight gain (Gain) during a FI test in broiler chickens using multi-trait Bayesian analysis; (2) derive phenotypic and genetic residual feed intake (RFI) and estimate genetic parameters of the resulting traits; and (3) compute a Bayesian measure of direct and correlated superiority of a group selected on phenotypic or genetic residual feed intake. A total of 56,649 male and female broiler chickens were measured at one of two ages (\documentclass[12pt]{minimal}
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\begin{document}$${\text{t}}$$\end{document}t or \documentclass[12pt]{minimal}
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\begin{document}$${\text{t}} - 6$$\end{document}t-6 days). BW, FI, and Gain of males and females at the two ages were considered as separate traits, resulting in a 12-trait model. Phenotypic RFI (\documentclass[12pt]{minimal}
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\begin{document}$${\text{RFI}}_{\text{P}}$$\end{document}RFIP) and genetic RFI (\documentclass[12pt]{minimal}
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\begin{document}$${\text{RFI}}_{\text{G}}$$\end{document}RFIG) were estimated from a conditional distribution of FI given BW and Gain using partial phenotypic and partial genetic regression coefficients, respectively. Results Posterior means of heritability for BW, FI and Gain were moderately high and estimates were significantly different between males and females at the same age for all traits. In addition, the genetic correlations between male and female traits at the same age were significantly different from 1, which suggests a sex-by-genotype interaction. Genetic correlations between \documentclass[12pt]{minimal}
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\begin{document}$${\text{RFI}}_{\text{P}}$$\end{document}RFIP and \documentclass[12pt]{minimal}
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\begin{document}$${\text{RFI}}_{\text{G }}$$\end{document}RFIG were significantly different from 1 at an older age but not at a younger age. Conclusions The results of the multivariate Bayesian analyses in this study showed that genetic evaluation for production and feed efficiency traits should take sex and age differences into account to increase accuracy of selection and genetic gain. Moreover, for communicating with stakeholders, it is easier to explain results from selection on \documentclass[12pt]{minimal}
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\begin{document}$${\text{RFI}}_{\text{G}}$$\end{document}RFIG than selection on \documentclass[12pt]{minimal}
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\begin{document}$${\text{RFI}}_{\text{P}}$$\end{document}RFIP, since \documentclass[12pt]{minimal}
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\begin{document}$${\text{RFI}}_{\text{G}}$$\end{document}RFIG is genetically independent of production traits and it explains the efficiency of birds in nutrient utilization independently of energy requirements for production and maintenance.
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Affiliation(s)
- Wossenie Mebratie
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark. .,Animal Breeding and Genomics Centre, Wageningen University, P.O. Box 338, 6700 AH, Wageningen, The Netherlands. .,College of Agriculture and environmental sciences, Bahir Dar University, P.O. Box 5501, Bahir Dar, Ethiopia.
| | - Per Madsen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark
| | - Rachel Hawken
- Cobb-Vantress Inc., Siloam Springs, AR, 72761-1030, USA
| | - Hélène Romé
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark
| | - Danye Marois
- Cobb-Vantress Inc., Siloam Springs, AR, 72761-1030, USA
| | - John Henshall
- Cobb-Vantress Inc., Siloam Springs, AR, 72761-1030, USA
| | - Henk Bovenhuis
- Animal Breeding and Genomics Centre, Wageningen University, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| | - Just Jensen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830, Tjele, Denmark
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16
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Chu TT, Bastiaansen JWM, Berg P, Romé H, Marois D, Henshall J, Jensen J. Use of genomic information to exploit genotype-by-environment interactions for body weight of broiler chicken in bio-secure and production environments. Genet Sel Evol 2019; 51:50. [PMID: 31533614 PMCID: PMC6751605 DOI: 10.1186/s12711-019-0493-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 09/05/2019] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND The increase in accuracy of prediction by using genomic information has been well-documented. However, benefits of the use of genomic information and methodology for genetic evaluations are missing when genotype-by-environment interactions (G × E) exist between bio-secure breeding (B) environments and commercial production (C) environments. In this study, we explored (1) G × E interactions for broiler body weight (BW) at weeks 5 and 6, and (2) the benefits of using genomic information for prediction of BW traits when selection candidates were raised and tested in a B environment and close relatives were tested in a C environment. METHODS A pedigree-based best linear unbiased prediction (BLUP) multivariate model was used to estimate variance components and predict breeding values (EBV) of BW traits at weeks 5 and 6 measured in B and C environments. A single-step genomic BLUP (ssGBLUP) model that combined pedigree and genomic information was used to predict EBV. Cross-validations were based on correlation, mean difference and regression slope statistics for EBV that were estimated from full and reduced datasets. These statistics are indicators of population accuracy, bias and dispersion of prediction for EBV of traits measured in B and C environments. Validation animals were genotyped and non-genotyped birds in the B environment only. RESULTS Several indications of G × E interactions due to environmental differences were found for BW traits including significant re-ranking, heterogeneous variances and different heritabilities for BW measured in environments B and C. The genetic correlations between BW traits measured in environments B and C ranged from 0.48 to 0.54. The use of combined pedigree and genomic information increased population accuracy of EBV, and reduced bias of EBV prediction for genotyped birds compared to the use of pedigree information only. A slight increase in accuracy of EBV was also observed for non-genotyped birds, but the bias of EBV prediction increased for non-genotyped birds. CONCLUSIONS The G × E interaction was strong for BW traits of broilers measured in environments B and C. The use of combined pedigree and genomic information increased population accuracy of EBV substantially for genotyped birds in the B environment compared to the use of pedigree information only.
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Affiliation(s)
- Thinh T. Chu
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
- Wageningen University & Research, Animal Breeding and Genomics, 6709 PG Wageningen, The Netherlands
- Faculty of Animal Science, Vietnam National University of Agriculture, Gia Lam, Hanoi, Vietnam
| | - John W. M. Bastiaansen
- Wageningen University & Research, Animal Breeding and Genomics, 6709 PG Wageningen, The Netherlands
| | - Peer Berg
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, 1432 Ås, Norway
| | - Hélène Romé
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
| | - Danye Marois
- Cobb-Vantress Inc, Siloam Springs, AR 72761-1030 USA
| | - John Henshall
- Cobb-Vantress Inc, Siloam Springs, AR 72761-1030 USA
| | - Just Jensen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, 8830 Tjele, Denmark
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17
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Abstract
Improving feed efficiency is important for decreasing feed cost in poultry production, because feed account for approximately 70% of the total production costs. The selection of feed efficiency may affect other important economic traits. Therefore, the objectives of this present study was to evaluate the relationships of the residual feed intake (RFI) with live body weight, carcass weight, carcass composition, and size of small intestines in a population of F2 Pekin ducks. Nine-hundred and eighty F2 ducks were derived from a cross between 40 Pekin ducks and 10 Mallard ducks. The results showed no significant correlation of RFI with live body weight and eviscerated carcass weight. RFI had negative effects on breast meat weight and gizzard weight. A positive correlation of RFI with abdominal fat weight, skin weight, and jejunum length was detected. Our results indicated that the selection of RFI could improve the feed efficiency of ducks without affecting their carcass compositions.
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18
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Chu TT, Bastiaansen JW, Norberg E, Berg P. On farm observations to increase genetic gain in breeding schemes for village poultry production – A simulation study. ACTA AGR SCAND A-AN 2018. [DOI: 10.1080/09064702.2018.1543444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Affiliation(s)
- Thinh Tuan Chu
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University Tjele, Denmark
- Wageningen University & Research, Animal Breeding and Genomics, Wageningen, The Netherlands
| | - John W.M. Bastiaansen
- Wageningen University & Research, Animal Breeding and Genomics, Wageningen, The Netherlands
| | - Elise Norberg
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University Tjele, Denmark
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway
| | - Peer Berg
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University Tjele, Denmark
- Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, Ås, Norway
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19
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Wen C, Yan W, Zheng J, Ji C, Zhang D, Sun C, Yang N. Feed efficiency measures and their relationships with production and meat quality traits in slower growing broilers. Poult Sci 2018; 97:2356-2364. [PMID: 29669019 DOI: 10.3382/ps/pey062] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Indexed: 11/20/2022] Open
Abstract
Feed consumption accounts for the major cost of broiler production. Improving the efficiency of feed utilization is a primary goal in breeding strategies, although few studies have focused on slower growing broilers. Here, we recorded the feed intake (FI) during the fast-growing period (d 56 to 76) and measured the live weight, body measurements, carcass characteristics, and intramuscular fat (IMF) content of Chinese yellow broilers. Then, the residual feed intake (RFI) and feed conversion ratio (FCR) were calculated for each individual. Pair-wise phenotypic correlations were subsequently calculated between feed efficiency traits and others. Finally, we separately selected the more efficient individuals based on RFI and FCR values to evaluate the impacts on the traits of FI, growth, carcass characteristics, and meat quality. The results showed higher correlations between FCR and production traits than with RFI, while RFI showed a moderate and positive phenotypic correlation with abdominal fat. FCR was weakly correlated with FI and slightly positively correlated with IMF content. The correlation coefficient between RFI and FI was 0.62, and that between RFI and IMF content was close to zero. Without increasing FI, decreasing FCR could effectively enhance the growth rate and market weight with no adverse effect on meat quality. In contrast, by improving RFI, FI and abdominal fat mass were significantly reduced and thus increased the yield with no unfavorable effects on meat quality. In consideration of consumer preference and overall economical benefits, RFI is a more suitable index to improve feed efficiency in slower growing broilers.
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Affiliation(s)
- Chaoliang Wen
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Wei Yan
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Jiangxia Zheng
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Congliang Ji
- Guangdong Wen's Nanfang Poultry Breeding Co. Ltd, Yunfu 527400, Guangdong Province, China
| | - Dexiang Zhang
- Guangdong Wen's Nanfang Poultry Breeding Co. Ltd, Yunfu 527400, Guangdong Province, China
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and MOA Key Laboratory of Animal Genetics and Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
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20
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Huynh-Tran VH, Gilbert H, David I. Genetic structured antedependence and random regression models applied to the longitudinal feed conversion ratio in growing Large White pigs. J Anim Sci 2018; 95:4752-4763. [PMID: 29293706 DOI: 10.2527/jas2017.1864] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The objective of the present study was to compare a random regression model, usually used in genetic analyses of longitudinal data, with the structured antedependence (SAD) model to study the longitudinal feed conversion ratio (FCR) in growing Large White pigs and to propose criteria for animal selection when used for genetic evaluation. The study was based on data from 11,790 weekly FCR measures collected on 1,186 Large White male growing pigs. Random regression (RR) using orthogonal polynomial Legendre and SAD models was used to estimate genetic parameters and predict FCR-based EBV for each of the 10 wk of the test. The results demonstrated that the best SAD model (1 order of antedependence of degree 2 and a polynomial of degree 2 for the innovation variance for the genetic and permanent environmental effects, i.e., 12 parameters) provided a better fit for the data than RR with a quadratic function for the genetic and permanent environmental effects (13 parameters), with Bayesian information criteria values of -10,060 and -9,838, respectively. Heritabilities with the SAD model were higher than those of RR over the first 7 wk of the test. Genetic correlations between weeks were higher than 0.68 for short intervals between weeks and decreased to 0.08 for the SAD model and -0.39 for RR for the longest intervals. These differences in genetic parameters showed that, contrary to the RR approach, the SAD model does not suffer from border effect problems and can handle genetic correlations that tend to 0. Summarized breeding values were proposed for each approach as linear combinations of the individual weekly EBV weighted by the coefficients of the first or second eigenvector computed from the genetic covariance matrix of the additive genetic effects. These summarized breeding values isolated EBV trajectories over time, capturing either the average general value or the slope of the trajectory. Finally, applying the SAD model over a reduced period of time suggested that similar selection choices would result from the use of the records from the first 8 wk of the test. To conclude, the SAD model performed well for the genetic evaluation of longitudinal phenotypes.
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Miyumo S, Wasike CB, Kahi AK. Genetic and phenotypic parameters for feed efficiency in indigenous chicken in Kenya. Livest Sci 2018. [DOI: 10.1016/j.livsci.2017.11.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Genomic dissection and prediction of feed intake and residual feed intake traits using a longitudinal model in F2 chickens. Animal 2017; 12:1792-1798. [PMID: 29268803 DOI: 10.1017/s1751731117003354] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Feed efficiency traits (FETs) are important economic indicators in poultry production. Because feed intake (FI) is a time-dependent variable, longitudinal models can provide insights into the genetic basis of FET variation over time. It is expected that the application of longitudinal models as part of genome-wide association (GWA) and genomic selection (i.e. genome-wide selection (GS)) studies will lead to an increase in accuracy of selection. Thus, the objectives of this study were to evaluate the accuracy of estimated breeding values (EBVs) based on pedigree as well as high-density single nucleotide polymorphism (SNP) genotypes, and to conduct a GWA study on longitudinal FI and residual feed intake (RFI) in a total of 312 chickens with phenotype and genotype in the F2 population. The GWA and GS studies reported in this paper were conducted using β-spline random regression models for FI and RFI traits in a chicken F2 population, with FI and BW recorded for each bird weekly between 2 and 10 weeks of age. A single SNP regression approach was used on spline coefficients for weekly FI and RFI traits, with results showing that two significant SNPs for FI occur in the synuclein (SNCAIP) gene. Results also show that these regions are significantly associated with the spline coefficients (q 2) for 5- and 6-week-old birds, while GWA study results showed no SNP association with RFI in F2 chickens. Estimated breeding value predictions obtained using a pedigree-based best linear unbiased prediction (ABLUP) model were then compared with predictions based on genomic best linear unbiased prediction (GBLUP). The accuracy was measured as correlation between genomic EBV and EBV with the phenotypic value corrected for fixed effects divided by the square root of heritability. The regression of observed on predicted values was used to estimate bias of methods. Results show that prediction accuracies using GBLUP and ABLUP for the FI measured from 2nd to 10th week were between 0.06 and 0.46 and 0.03 and 0.37, respectively. These results demonstrate that genomic methods are able to increase the accuracy of predicted breeding values at later ages on the basis of both traits, and indicate that use of a longitudinal model can improve selection accuracy for the trajectory of traits in F2 chickens when compared with conventional methods.
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Pang M, Fu B, Yu X, Liu H, Wang X, Yin Z, Xie S, Tong J. Quantitative trait loci mapping for feed conversion efficiency in crucian carp (Carassius auratus). Sci Rep 2017; 7:16971. [PMID: 29209087 PMCID: PMC5717303 DOI: 10.1038/s41598-017-17269-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 11/21/2017] [Indexed: 11/29/2022] Open
Abstract
QTL is a chromosomal region including single gene or gene clusters that determine a quantitative trait. While feed efficiency is highly important in aquaculture fish, little genetic and genomic progresses have been made for this trait. In this study, we constructed a high-resolution genetic linkage map in a full-sib F1 family of crucian carp (Carassius auratus) consisting of 113 progenies with 8,460 SNP markers assigning onto 50 linkage groups (LGs). This genetic map spanned 4,047.824 cM (0.478 cM/marker) and covered 98.76% of the crucian carp genome. 35 chromosome-wide QTL affecting feed conversion efficiency (FCE, 8 QTL), relative growth rate (RGR, 9 QTL), average daily gain (ADG, 13 QTL) and average daily feed intake (ADFI, 5 QTL) were detected on 14 LGs, explaining 14.0–20.9% of the phenotypic variations. In LGs of LG16, LG25, LG36 and LG49, several QTL affecting different traits clustered together at the identical or close regions of the same linkage group. Seven candidate genes, whose biological functions may involve in the energy metabolism, digestion, biosynthesis and signal transduction, were identified from these QTL intervals by comparative genomics analysis. These results provide a basis for elucidating genetic mechanism of feed efficiency and potential marker-assisted selection in crucian carp.
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Affiliation(s)
- Meixia Pang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.,University of Chinese Academy of Sciences, Beijing, 100039, China
| | - Beide Fu
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Xiaomu Yu
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Haiyang Liu
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.,University of Chinese Academy of Sciences, Beijing, 100039, China
| | - Xinhua Wang
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.,University of Chinese Academy of Sciences, Beijing, 100039, China
| | - Zhan Yin
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Shouqi Xie
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
| | - Jingou Tong
- State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China.
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Emrani H, Vaez Torshizi R, Akbar Masoudi A, Ehsani A. Identification of new loci for body weight traits in F2 chicken population using genome-wide association study. Livest Sci 2017. [DOI: 10.1016/j.livsci.2017.10.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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Emamgholi Begli H, Vaez Torshizi R, Akbar Masoudi A, Ehsani A, Jensen J. Relationship between residual feed intake and carcass composition, meat quality and size of small intestine in a population of F 2 chickens. Livest Sci 2017. [DOI: 10.1016/j.livsci.2017.09.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Sell-Kubiak E, Wimmers K, Reyer H, Szwaczkowski T. Genetic aspects of feed efficiency and reduction of environmental footprint in broilers: a review. J Appl Genet 2017; 58:487-498. [PMID: 28342159 PMCID: PMC5655602 DOI: 10.1007/s13353-017-0392-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Revised: 01/18/2017] [Accepted: 03/08/2017] [Indexed: 11/28/2022]
Abstract
Currently, optimization of feed efficiency is one of the main challenges in improvement programs of livestock and poultry genetics. The objective of this review is to present the genetic aspects of feed efficiency related traits in meat-type chicken and possible ways to reduce the environmental impact of poultry meat production with effective breeding. Basic measures of feed efficiency are defined and the genetic background of these traits, including a review of heritabilities is described. Moreover, a number of genomic regions and candidate genes determining feed efficiency traits of broilers that were detected over the past decades are described. Classical and genomic selection strategies for feed efficiency in the context of its relationships with other performance traits are discussed as well. Finally, future strategies to improve feed digestibility are described as it is expected that they will decrease wastes and greenhouse gas emission. Further genetic improvement of feed efficiency, should be examined jointly with appropriate feeding strategies in broilers.
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Affiliation(s)
- Ewa Sell-Kubiak
- Departament of Genetics and Animal Breeding, Poznan University of Life Sciences, Wolynska st. 33, 60-637, Poznan, Poland
| | - Klaus Wimmers
- Institute of Genome Biology, Leibniz Institute of Farm Animal Biology, Wilhelm-Stahl-Allee 2, 18196, Dummerstorf, Germany
| | - Henry Reyer
- Institute of Genome Biology, Leibniz Institute of Farm Animal Biology, Wilhelm-Stahl-Allee 2, 18196, Dummerstorf, Germany
| | - Tomasz Szwaczkowski
- Departament of Genetics and Animal Breeding, Poznan University of Life Sciences, Wolynska st. 33, 60-637, Poznan, Poland.
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Mebratie W, Shirali M, Madsen P, Sapp R, Hawken R, Jensen J. The effect of selection and sex on genetic parameters of body weight at different ages in a commercial broiler chicken population. Livest Sci 2017. [DOI: 10.1016/j.livsci.2017.08.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Coyne JM, Berry DP, Matilainen K, Sevon-Aimonen ML, Mantysaari EA, Juga J, Serenius T, McHugh N. Genetic co-variance functions for live weight, feed intake, and efficiency measures in growing pigs1. J Anim Sci 2017. [DOI: 10.2527/jas.2017.1408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Non-genetic sources of variation and temporal variability in growth and feed efficiency traits among phylogenetically distinct clusters of indigenous chicken in Kenya. Trop Anim Health Prod 2016; 48:1569-1575. [PMID: 27562304 DOI: 10.1007/s11250-016-1129-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Accepted: 08/16/2016] [Indexed: 10/21/2022]
Abstract
This study aims to investigate the influence of non-genetic factors on feed efficiency in indigenous chicken. Residual feed intake (RFI), residual gain (RG) and residual intake and gain (RIG) were used as measures of feed efficiency. Feed intake and body weight data were collected on 107 experimental birds on a daily and weekly basis, respectively, from ages 11 to 20 weeks. A general linear model was fitted to determine the effect of sex, cluster, genotype and hatch group on mean performance and to assess temporal variation across clusters. The overall mean performance for daily gain (ADG), daily feed intake (ADFI), weekly metabolic body weight (MBW), RFI, RG and RIG was 10.38 g/day, 133.01 g/day, 164.12 g/day, 0.00 (±14.23), 0.00 (±1.83) and 0.00 (±14.64), respectively. Sex significantly influenced variation in ADG and RG while hatch group influenced all traits except ADFI. Cluster and genotype had no effect on the traits. Interaction between sex and cluster significantly influenced ADFI, RFI and RIG. There was a significant temporal variation within and among clusters resulting in re-ranking of the phylogenetic groups in efficiency across the test period. Results indicate that growth and feed efficiency traits are influenced by non-genetic factors which should be accounted for, to reduce bias and improve accuracy of performance evaluations in the indigenous chicken.
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