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Zhao X, Qiu Y, Meng F, Zhuang Z, Ruan D, Wu J, Ma F, Zheng E, Cai G, Yang J, Yang M, Wu Z. Genome-wide association studies for loin muscle area, loin muscle depth and backfat thickness in DLY pigs. Anim Genet 2024; 55:134-139. [PMID: 38098441 DOI: 10.1111/age.13386] [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: 09/24/2022] [Revised: 10/17/2023] [Accepted: 11/28/2023] [Indexed: 01/04/2024]
Abstract
This study aimed at identifying genes associated with loin muscle area (LMA), loin muscle depth (LMD) and backfat thickness (BFT). We performed single-trait and multi-trait genome-wide association studies (GWASs) after genotyping 685 Duroc × (Landrace × Yorkshire) (DLY) pigs using the Geneseek Porcine 50K SNP chip. In the single-trait GWASs, we identified two, eight and two significant SNPs associated with LMA, LMD and BFT, respectively, and searched genes within the 1 Mb region near the significant SNPs with relevant functions as candidate genes. Consequently, we identified one (DOCK5), three (PID1, PITX2, ELOVL6) and three (CCR1, PARP14, CASR) promising candidate genes for LMA, LMD and BFT, respectively. Moreover, the multi-trait GWAS identified four significant SNPs associated with the three traits. In conclusion, the GWAS analysis of LMA, LMD and BFT in a DLY pig population identified several associated SNPs and candidate genes, further deepening our understanding of the genetic basis of these traits, and they may be useful for marker-assisted selection to improve the three traits in DLY pigs.
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Affiliation(s)
- Xiang Zhao
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fanming Meng
- State Key Laboratory of Livestock and Poultry Breeding/Guangdong Key Laboratory of Animal Breeding and Nutrition, Institute of Animal Science, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Fucai Ma
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
| | - Ming Yang
- Guangdong Zhongxin Breeding Technology Co., Ltd, Guangzhou, Guangdong, China
- College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, Guangdong, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Agro-animal Genomics and Molecular Breeding, South China Agricultural University, Guangzhou, Guangdong, China
- Yunfu Subcenter of Guangdong Laboratory for Lingnan Modern Agriculture, Yunfu, Guangdong, China
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Ogawa S, Takahashi H, Satoh M. Genetic parameter estimation for pork production and litter performance traits of Landrace, Large White, and Duroc pigs in Japan. J Anim Breed Genet 2023; 140:607-623. [PMID: 37340733 DOI: 10.1111/jbg.12814] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/14/2023] [Accepted: 06/09/2023] [Indexed: 06/22/2023]
Abstract
We estimated genetic parameters for two pork production and six litter performance traits of Landrace, Large White, and Duroc pigs reared in Japan. Pork production traits were average daily gain from birth to end of performance testing and backfat thickness at end of testing (46,042 records for Landrace, 40,467 records for Large White, and 42,920 records for Duroc). Litter performance traits were number born alive, litter size at weaning (LSW), number of piglets dead during suckling (ND), survival rate of piglets during suckling (SV), total piglet weight at weaning (TWW), and average piglet weight at weaning (AWW) (27,410, 26,716, and 12,430 records for Landrace, Large White, and Duroc, respectively). ND was calculated as the difference between LSW and litter size at start of suckling (LSS). SV was calculated as LSW/LSS. AWW was calculated as TWW/LSW. Pedigree data for Landrace, Large White, and Duroc breeds contained 50,193, 44,077, and 45,336 pigs, respectively. Trait heritability was estimated via single-trait analysis and genetic correlation between two traits was estimated via two-trait analysis. When considering the linear covariate of LSS in the statistical model for LSW and TWW, for all breeds, the heritability was estimated to be 0.4-0.5 for pork production traits and below 0.2 for litter performance traits. Estimated genetic correlation between average daily gain and backfat thickness was small, ranging from 0.057 to 0.112, and those between pork production traits and litter performance traits were negligible to moderate, ranging from -0.493 to 0.487. A wide range of genetic correlation values among the litter performance traits was estimated, while that between LSW and ND could not be obtained. The results of genetic parameter estimation were affected by whether the linear covariate of LSS was included in the statistical model for LSW and TWW or not. This finding implies the necessity of carefully interpreting the results according to the choice of statistical model. Our results could give fundamental information on simultaneously improving productivity and female reproductivity for pigs.
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Affiliation(s)
- Shinichiro Ogawa
- Institute of Livestock and Grassland Science, NARO, Tsukuba, Ibaraki, Japan
| | | | - Masahiro Satoh
- Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, Japan
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Wang Y, Zhou P, Zhou X, Fu M, Wang T, Liu Z, Liu X, Wang Z, Liu B. Effect of host genetics and gut microbiome on fat deposition traits in pigs. Front Microbiol 2022; 13:925200. [PMID: 36204621 PMCID: PMC9530793 DOI: 10.3389/fmicb.2022.925200] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/24/2022] [Indexed: 11/13/2022] Open
Abstract
Fat deposition affects meat quality, flavor, and production in pigs. Fat deposition is influenced by both genetics and environment. Symbiotic microbe with the host is an important environmental factor to influence fat deposition. In this study, the fat deposition traits were measured in 239 individuals obtained from Tongcheng pigs × Large White pigs resource population. The interactions between genetics and gut microbiome in fat deposition traits were investigated through whole-genome sequencing and cecum microbial 16S ribosomal RNA sequencing. The results showed that the percentage of leaf fat (PL) and intramuscular fat content (IMF) were significantly influenced by host genetics–gut microbiome interaction. The effects of interactions between host genetics and gut microbiome on PL and IMF were 0.13 and 0.29, respectively. The heritability of PL and IMF was estimated as 0.71 and 0.89, respectively. The microbiability of PL and IMF was 0.20 and 0.26, respectively. Microbiome-wide association analysis (MWAS) revealed Anaeroplasma, Paraprevotella, Pasteurella, and Streptococcus were significantly associated with PL, and Sharpea and Helicobacter exhibited significant association with IMF (p < 0.05). Furthermore, Paraprevotella was also identified as a critical microbe affecting PL based on the divergent Wilcoxon rank-sum test. Overall, this study reveals the effect of host genetics and gut microbiome on pig fat deposition traits and provides a new perspective on the genetic improvement of pig fat deposition traits.
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Affiliation(s)
- Yuan Wang
- 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, Huazhong Agricultural University, Wuhan, China
| | - Ping Zhou
- 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, Huazhong Agricultural University, Wuhan, China
| | - Xiang Zhou
- 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, Huazhong Agricultural University, Wuhan, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
- The Engineering Technology Research Center of Hubei Province Local Pig Breed Improvement, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Ming 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, Huazhong Agricultural University, Wuhan, China
| | - Tengfei Wang
- 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, Huazhong Agricultural University, Wuhan, China
| | - Zuhong Liu
- 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, Huazhong Agricultural University, Wuhan, China
| | - Xiaolei Liu
- 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, Huazhong Agricultural University, Wuhan, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
- The Engineering Technology Research Center of Hubei Province Local Pig Breed Improvement, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Zhiquan Wang
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Bang Liu
- 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, Huazhong Agricultural University, Wuhan, China
- The Cooperative Innovation Center for Sustainable Pig Production, Wuhan, China
- The Engineering Technology Research Center of Hubei Province Local Pig Breed Improvement, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
- *Correspondence: Bang Liu,
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Aikins-Wilson S, Bohlouli M, Engel P, König S. Effects of an herbal diet, diet x boar line and diet x genotype interactions on skin lesions and on growth performance in post-weaning pigs using a cross-classified experiment. Livest Sci 2022. [DOI: 10.1016/j.livsci.2022.105010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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5
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Chernenko OM, Chernenko OI, Mylostyvyi RV, Khmeleva OV, Garashchenko VY, Bordunova OG, Dutka VR. The results of fattening hybrid pigs of Danish selection. UKRAINIAN JOURNAL OF VETERINARY AND AGRICULTURAL SCIENCES 2022. [DOI: 10.32718/ujvas5-1.01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The results of a study of the breed combinations that influence pigs of Danish selection on fattening, meat, and economic indicators are presented. The experimental animals were divided into two groups according to their genotype. The method of groups-analogs was applied. The pigs were similar in terms of conditional heredity, sex, age, and body weight within each group. Five animals from each group were slaughtered at the meat processing plant to study the meat qualities. These studies arose due to the constant search for the most successful and cost-effective options for breed combinations that guarantee the effect of heterosis in hybrid offspring, which determined the scientific novelty and relevance. The dependence on breed combinations of fattening and meat qualities of young pigs obtained by simple two-breed and complex three-breed industrial crossbreeding of breeds of Danish selection has been established. At the final stage of fattening, a significant intergroup difference was established in terms of the average daily increase in body weight in favor of pigs of the breed combination F2 ¼Y ¼L ½D at 5.4% at P > 0.999 compared with analogs of the breed combination F1 ½Y ½L. Crossbreeds of the F2 generation turned out to be more early maturing and reached a body weight of 100 kg in 168.1 days, compared to 173.2 days in crossbreeds of the F1 generation with a difference of 5.1 days (P > 0.95) and a slaughter weight of 110 kg with a difference of 5.5 days (P > 0.95). They also spent less feed by 0.18 feed units per 1 kg of body weight gain, but the intergroup difference was insignificant. At slaughter, the weight of the steamed carcass in the crossbreeds of generation F2 ¼Y ¼L ½D was higher by 6.7 kg (P<0.95), and the slaughter yield was higher by 5.9 % (P > 0.999). It is concluded that the combination of Yorkshire breeds with Landraces and Durocs achieves a high economic effect on pork production since the level of profitability of pork production in three-breed hybrids is higher by 6.6%, respectively than in two-breed ones.
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Alam M, Chang HK, Lee SS, Choi TJ. Genetic Analysis of Major Production and Reproduction Traits of Korean Duroc, Landrace and Yorkshire Pigs. Animals (Basel) 2021; 11:1321. [PMID: 34063090 PMCID: PMC8147943 DOI: 10.3390/ani11051321] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 04/28/2021] [Accepted: 04/30/2021] [Indexed: 12/04/2022] Open
Abstract
The study aimed to investigate the genetic parameters of the production and reproduction traits of Korean Duroc, Landrace, and Yorkshire pigs. Three production traits, namely average daily gain (ADG), age at 105 kg body weight (DAYS105) and backfat thickness (BFT), and three reproduction traits, namely age at first farrowing (AFF), total number of piglets born (TNB) and number of piglets born alive (NBA), were analyzed. The reproduction dataset was based on first-parity gilts only. However, the production dataset comprised pigs of both sexes. Genetic parameters were estimated from individual datasets using a multiple-trait animal model in AIREMLF90 software. The heritability values of ADG, DAYS105 and BFT were 0.34-0.36, 0.41-0.44 and 0.38-0.48, respectively, across breeds. Heritability values for AFF, TNB and NBA were 0.07-0.14, 0.09-0.11 and 0.09-0.10, respectively. Strong genetic correlations existed between ADG and DAYS105 (-0.97) and between TNB and NBA (0.90 to 0.96). In line with breeding goals, all productive traits in Duroc pigs, and all reproduction traits except AFF in Landrace and Yorkshire pigs, also showed noticeable improvements in recent years. In conclusion, we believe that our findings on economic traits would greatly assist future pig breeding decisions in Korea.
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Affiliation(s)
| | - Hyuk-Kee Chang
- Correspondence: (H.-K.C.); (T.-J.C.); Tel.: +82-580-3353 (H.-K.C.); +82-580-3362 (T.-J.C.)
| | | | - Tae-Jeong Choi
- Animal Breeding and Genetics Division, National Institute of Animal Science, Cheonan-si 31000, Korea; (M.A.); (S.-S.L.)
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7
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Ogawa S, Ohnishi C, Ishii K, Uemoto Y, Satoh M. Genetic relationship between litter size traits at birth and body measurement and production traits in purebred Duroc pigs. Anim Sci J 2021; 91:e13497. [PMID: 33368835 DOI: 10.1111/asj.13497] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 11/14/2020] [Accepted: 12/03/2020] [Indexed: 11/28/2022]
Abstract
Heritabilities of litter size traits at birth (total number born (TNB), number born alive (NBA), and number still born (NSB)) and their genetic correlations with body measurement (body height, body length, front width (FW), chest width (CW), hind width, chest depth, chest girth, front cannon circumference, and rear cannon circumference) and production traits (ages at the start and end of performance testing (D30 and D105), average daily gain (ADG), backfat thickness, and loin muscle area) in purebred Duroc pigs were estimated. Records of performance testing for 2,835 animals and farrowing records of 1,168 litters from 437 dams were used. Genetic parameters were estimated using single-trait and two-trait animal models. Permanent environment effect was considered for litter size traits and common litter environmental effect was considered for body measurement and production traits. The estimated heritability was 0.10 ± 0.06 for TNB, 0.16 ± 0.06 for NBA, and 0.08 ± 0.05 for NSB. Positive genetic correlation of NBA was estimated with D30, D105, and ADG (0.51, 0.11, and 0.39). The estimated genetic correlation of NBA was 0.47 ± 0.17 with FW and 0.55 ± 0.18 with CW, implying that FW and CW could be promising indicator traits for efficiently improving NBA.
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Affiliation(s)
- Shinichiro Ogawa
- Graduate School of Agricultural Science, Tohoku University, Sendai, Japan
| | - Chika Ohnishi
- National Livestock Breeding Center, Miyazaki Station, Kobayashi, Japan
| | - Kazuo Ishii
- Division of Animal Breeding and Reproduction, Institute of Livestock and Grassland Science, NARO, Tsukuba, Japan
| | - Yoshinobu Uemoto
- Graduate School of Agricultural Science, Tohoku University, Sendai, Japan
| | - Masahiro Satoh
- Graduate School of Agricultural Science, Tohoku University, Sendai, Japan
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Aikins-Wilson S, Bohlouli M, König S. Maternal and direct genetic parameters for tail length, tail lesions, and growth traits in pigs. J Anim Sci 2021; 99:skaa398. [PMID: 33320242 PMCID: PMC7819635 DOI: 10.1093/jas/skaa398] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 12/11/2020] [Indexed: 11/13/2022] Open
Abstract
Tail length and tail lesions are the major triggers for tail biting in pigs. Against this background, 2 datasets were analyzed to estimate genetic parameters for tail characteristics and growth traits. Dataset 1 considered measurements for trait tail length (T-LEN) and for the growth traits birth weight (BW), weaning weight (WW), postweaning weight (PWW), and average daily gain (ADG) from 9,348 piglets. Piglets were born in the period from 2015 to 2018 and kept on the university Gießen research station. Dataset 2 included 4,943 binary observations from 1,648 pigs from the birth years 2016 to 2019 for tail lesions (T-LES) as indicators for nail necrosis, tail abnormalities, or tail biting. T-LES were recorded at 30 ± 7 d after entry for rearing (T-Les-1), at 50 ± 7 d after entry for rearing (end of the rearing period, T-LES-2), and 130 ± 20 d after entry for rearing (end of fattening period, T-LES-3). Genetic statistical model evaluation for dataset 1 based on Akaike's information criterion and likelihood ration tests suggested multiple-trait animal models considering covariances between direct and maternal genetic effects. The direct heritability for T-LEN was 0.42 (±0.03), indicating the potential for genetic selection on short tails. The maternal genetic heritability for T-LEN was 0.05 (±0.04), indicating the influence of uterine characteristics on morphological traits. The negative correlation between direct and maternal effects for T-LEN of -0.35 (±0.13), as well as the antagonistic relationships (i.e., positive direct genetic correlations in the range from 0.03 to 0.40) between T-LEN with the growth traits BW, WW, PWW, and ADG, complicate selection strategies and breeding goal definitions. The correlations between direct effects for T-LEN and maternal effects for breeding goal traits, and vice versa, were positive but associated with a quite large SE. The heritability for T-LES when considering the 3 repeated measurements was 0.23 (±0.04) from the linear (repeatability of 0.30) and 0.21 (±0.06; repeatability of 0.29) from the threshold model. The breeding value correlations between T-LES-3 with breeding values from the repeatability models were quite large (0.74 to 0.90), suggesting trait lesion recording at the end of the rearing period. To understand all genetic mechanisms in detail, ongoing studies are focusing on association analyses between T-LEN and T-LES, and the identification of tail biting from an actor's perspective.
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Affiliation(s)
- Sheila Aikins-Wilson
- Institute of Animal Breeding and Genetics, University of Giessen, Giessen, Germany
| | - Mehdi Bohlouli
- Institute of Animal Breeding and Genetics, University of Giessen, Giessen, Germany
| | - Sven König
- Institute of Animal Breeding and Genetics, University of Giessen, Giessen, Germany
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9
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Abstract
The use of diets with increased fibre content from alternative feedstuffs less digestible for pigs is a solution considered to limit the impact of increased feed costs on pig production. This study aimed at determining the impact of an alternative diet on genetic parameters for growth, feed efficiency, carcass composition and meat quality traits. A total of 783 Large White pigs were fed a high-fibre (HF) diet and 880 of their sibs were fed a conventional (CO) cereal-based diet. Individual daily feed intake, average daily gain, feed conversion ratio and residual feed intake were recorded as well as lean meat percentage (LMP), carcass yield (CY) and meat quality traits. Pigs fed the CO diet had better performances for growth and feed efficiency than pigs fed the HF diet. They also had lower LMP and higher CY. In addition, pigs fed the CO diet had lower loin percentage and ham percentage and higher backfat percentage. No differences were observed in meat quality traits between diets, except for a* and b* values. For all traits, the genetic variances and heritability were not different between diets. Genetic correlations for traits between diets ranged between 0.80 ± 0.13 and 0.99 ± not estimable, and none were significantly different from 0.99, except for LMP. Thus, traits in both diets were considered as mainly affected by similar sets of genes in the two diets. A genetic correlation lower than 0.80 would justify redesigning the breeding scheme; however, some genetic correlations did not differ significantly from 0.80 either. Therefore, larger populations are needed for a more definitive answer regarding the design of the breeding scheme. To further evaluate selection strategies, a production index was computed within diets for the 29 sires with estimated breeding value reliability higher than 0.35. The rank correlation between indices estimated in the CO and in the HF diet was 0.72. Altogether, we concluded that limited interaction between feed and genetics could be evidenced, and based on these results there is no need to change pig selection schemes to adapt to the future increased use of alternative feedstuffs in production farms.
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Lopez BIM, Seo K. Genetic parameters for litter traits at different parities in purebred Landrace and Yorkshire pigs. Anim Sci J 2019; 90:1497-1502. [PMID: 31603600 DOI: 10.1111/asj.13298] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 08/19/2019] [Accepted: 08/28/2019] [Indexed: 11/30/2022]
Abstract
Comparison of the multi-trait animal model and the traditional repeatability model was carried out using data obtained from 6,424 Landrace and 20,835 Yorkshire sows farrowed from January 2000 to April 2018 in order to estimate genetic parameters for litter traits at different parities. Specifically, records of the total number born (TNB), number born alive (NBA), total number of mortality (MORT), number of stillborn (NSB) and number of mummified pigs (MUM) were used. Although results showed the heterogeneity of heritability for litter traits at different parities, the mean heritability estimates from the multi-trait model were found to be higher than those of the repeatability model for all traits in both pig breeds. In terms of genetic correlation between parities, a slight difference in genetic control in the first parity was noted for TNB and NBA in Landrace and Yorkshire pigs. The correlation between the first parity and later parities ranged from 0.48 to 0.74 for TNB and NBA in both breeds. Moreover, genetic correlation between parities for MORT and NSB was observed to be high for parities higher than 2 in Yorkshire pigs. For MUM, genetic correlation between the first and other parities was generally low in both breeds, indicating that culling pigs on the basis of MUM at the first parity could probably be unreasonable. Overall, the results of this study suggest that the multi-trait approach for litter size traits is useful for the accurate estimation of genetic parameters.
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Affiliation(s)
- Bryan I M Lopez
- Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Wanju, South Korea
| | - Kangseok Seo
- Department of Animal Science and Technology, Sunchon National University, Suncheon, South Korea
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11
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E GX, Zhao YJ, Huang YF. Selection signatures of litter size in Dazu black goats based on a whole genome sequencing mixed pools strategy. Mol Biol Rep 2019; 46:5517-5523. [DOI: 10.1007/s11033-019-04904-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 06/01/2019] [Indexed: 12/19/2022]
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12
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Song B, Di S, Cui S, Chen N, Wang H, Wang X, Gao Q, Tong G, Wang H, Huang X, Ding L, Gao Y, Liu J, Wang X. Distinct Patterns of PPARγ Promoter Usage, Lipid Degradation Activity, and Gene Expression in Subcutaneous Adipose Tissue of Lean and Obese Swine. Int J Mol Sci 2018; 19:ijms19123892. [PMID: 30563100 PMCID: PMC6321263 DOI: 10.3390/ijms19123892] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 12/03/2018] [Accepted: 12/03/2018] [Indexed: 12/11/2022] Open
Abstract
Subcutaneous adipose tissue is a loose connective tissue specializing in the regulation of energy storage and metabolization. In domesticated pigs (Sus scrofa), the temporal development of subcutaneous adipose tissue is critical for meat production. However, the regulation of adipose tissue development remains unclear. Here, the subcutaneous adipose tissue development was characterized and compared in lean (Danish-Landrace) and obese (Min) pigs at juvenile and the juvenile-to-adult growth stages. Using RNA sequencing, we profiled the transcriptome of subcutaneous adipose tissue isolated from 4- and 16-week-old pigs and identified 24,718 expressed transcription units. Of them, 6327 genes were differentially expressed between the breeds and/or developmental stages. Compared with obese pigs, upregulated genes in lean pigs showed significant function and pathway enrichment in fatty acid degradation and mitochondrial functions. Further analysis uncovered the distinct usage preferences of the three alternative peroxisomeproliferator-activatedreceptorγ (PPARγ) promoters associated with the development of subcutaneous adipose tissue in both breeds. Transcriptome analysis of subcutaneous adipose tissue in lean and obese pigs suggested that marker-assisted selection of fatty acid degradation and PPARγ signaling pathways could be important directions for future pork quality improvement and modern breeding.
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Affiliation(s)
- Bin Song
- The Northeast Agricultural University, 59 Mucai St, Xiangfang District, Harbin 150030, China.
- Animal Science Institute of Heilongjiang Province, 2 Heyi St, Longsha District, Qiqihaer 161005, China.
| | - Shengwei Di
- The Northeast Agricultural University, 59 Mucai St, Xiangfang District, Harbin 150030, China.
| | - Shiquan Cui
- The Northeast Agricultural University, 59 Mucai St, Xiangfang District, Harbin 150030, China.
| | - Na Chen
- National Key Facility for Crop Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Huan Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Xuan Wang
- National Key Facility for Crop Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
- Department of Biological Sciences, Xian Jiaotong-Liverpool University, Suzhou 215123, China.
| | - Qian Gao
- National Key Facility for Crop Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Guizhi Tong
- Animal Science Institute of Heilongjiang Province, 2 Heyi St, Longsha District, Qiqihaer 161005, China.
| | - Hongbao Wang
- Animal Science Institute of Heilongjiang Province, 2 Heyi St, Longsha District, Qiqihaer 161005, China.
| | - Xuankai Huang
- The Northeast Agricultural University, 59 Mucai St, Xiangfang District, Harbin 150030, China.
- Animal Science Institute of Heilongjiang Province, 2 Heyi St, Longsha District, Qiqihaer 161005, China.
| | - Liyan Ding
- Animal Science Institute of Heilongjiang Province, 2 Heyi St, Longsha District, Qiqihaer 161005, China.
| | - Ying Gao
- National Key Facility for Crop Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Jun Liu
- The Northeast Agricultural University, 59 Mucai St, Xiangfang District, Harbin 150030, China.
- National Key Facility for Crop Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Xibiao Wang
- The Northeast Agricultural University, 59 Mucai St, Xiangfang District, Harbin 150030, China.
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