1
|
Junxiao S, Peng B, Yunfei T, Xufeng B. Identification of quantitative trait loci for abdominal muscle content in red swamp crayfish (Procambarus clarkii) and potential application in molecular breeding. Gene 2025; 959:149528. [PMID: 40273959 DOI: 10.1016/j.gene.2025.149528] [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: 01/16/2025] [Revised: 04/20/2025] [Accepted: 04/21/2025] [Indexed: 04/26/2025]
Abstract
Red swamp crayfish (Procambarus clarkii) is a prized aquatic product among consumers, abdominal muscle content being a crucial economic trait. Therefore, there is an urgent need to exploit the genetic basis of crayfish abdominal muscle content for breeding. In the present study, Quantitative Trait Locus (QTL) mapping was performed using 10 different populations (Pop1-Pop10), raised in water tanks, ponds, and rice-crayfish fields, using single- and multiple-culture models of full-sib families and natural populations, from 2020 to 2023. In total, 22 QTLs for abdominal muscle content were identified with population repetitions, explaining the phenotypic variation in the range of 2.7 %-21.3 %, six of which were heterosis sites. Additionally, nine of the 22 QTLs had the consistent genotype with phenotypic effect in eight natural populations (Pop3-Pop10), where the proportion of genotypes with phenotypic effect of the QTL for abdominal muscle weight / body weight (MW/BW) and chelae weight / body weight (CHW/BW) in the group including the top 10 % of the yield of abdominal muscle content individuals (High group) was significantly higher than that in the group including the bottom 10 % of the yield of abdominal muscle content individuals (Low group), respectively (P < 0.01). These results suggest that the QTLs identified repeatedly, especially the nine QTLs, are reliable candidate loci for abdominal muscle content, which is immensely important for the genetic analysis of abdominal muscle content in red swamp crayfish and molecular marker-assisted breeding.
Collapse
Affiliation(s)
- Sun Junxiao
- National Key Laboratory of Crop Genetic Improvement, Shuangshui Shuanglü Institute, Huazhong Agricultural University, Wuhan 430070, China; College of Fisheries, Huazhong Agricultural University, Wuhan 430070, China
| | - Bo Peng
- National Key Laboratory of Crop Genetic Improvement, Shuangshui Shuanglü Institute, Huazhong Agricultural University, Wuhan 430070, China; College of Fisheries, Huazhong Agricultural University, Wuhan 430070, China
| | - Tan Yunfei
- National Key Laboratory of Crop Genetic Improvement, Shuangshui Shuanglü Institute, Huazhong Agricultural University, Wuhan 430070, China; College of Fisheries, Huazhong Agricultural University, Wuhan 430070, China
| | - Bai Xufeng
- National Key Laboratory of Crop Genetic Improvement, Shuangshui Shuanglü Institute, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, Wuhan 430070, China; College of Fisheries, Huazhong Agricultural University, Wuhan 430070, China; Engineering Research Center of Green Development for Conventional Aquatic Biological Industry in the Yangtze River Economic Belt, Ministry of Education, Wuhan 430070, China.
| |
Collapse
|
2
|
Ali A, Gao G, Al-Tobasei R, Youngblood RC, Waldbieser GC, Scheffler BE, Palti Y, Salem M. Chromosome level genome assembly and annotation of the Swanson rainbow trout homozygous line. Sci Data 2025; 12:345. [PMID: 40011488 DOI: 10.1038/s41597-025-04693-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 02/21/2025] [Indexed: 02/28/2025] Open
Abstract
The genome of the Swanson doubled haploid (DH) YY male line of rainbow trout was de novo assembled using the Canu pipeline, high-coverage PacBio long-read sequence data, Bionano optical maps, and Hi-C proximity ligation sequence data, resulting in 29 major scaffolds aligning with the karyotype of the Swanson line (2 N = 58). This assembly, totaling 2.3 Gb with an N50 of 52.4 Mb, represents approximately 95% of the genome in 29 chromosome sequences with only 109 gaps between scaffolds. Notably, corrections to previous errors in the Swanson line genome assembly were made, including the identification of a double large inversion on the Omy05 chromosome (~57 Mb), the absence of the Omy20 inversion between the Arlee and Swanson assemblies, and the discovery of a ~6.7 Mb inversion on Omy26. This comprehensive assembly contributes to refining the rainbow trout reference genome and serves as a valuable resource for future genetic studies within this species.
Collapse
Affiliation(s)
- Ali Ali
- Department of Animal and Avian Sciences, University of Maryland, College Park, College Park, MD, USA
| | - Guangtu Gao
- USDA-ARS National Center for Cool and Cold Water Aquaculture, Kearneysville, WV, 25430, USA
| | - Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Ramey C Youngblood
- Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, MS, 39762, USA
| | - Geoffrey C Waldbieser
- USDA-ARS Warmwater Aquaculture Research Unit, 141 Experimental Station Road, Stoneville, MS, 38776, USA
| | - Brian E Scheffler
- USDA-ARS Genomics and Bioinformatics Research Unit, 141 Experimental Station Road, Stoneville, MS, 38776, USA
| | - Yniv Palti
- USDA-ARS National Center for Cool and Cold Water Aquaculture, Kearneysville, WV, 25430, USA
| | - Mohamed Salem
- Department of Animal and Avian Sciences, University of Maryland, College Park, College Park, MD, USA.
| |
Collapse
|
3
|
Ding M, Tao Y, Hua J, Dong Y, Lu S, Qiang J, He J. Genome-Wide Association Study Reveals Growth-Related SNPs and Candidate Genes in Largemouth Bass ( Micropterus salmoides) Adapted to Hypertonic Environments. Int J Mol Sci 2025; 26:1834. [PMID: 40076461 PMCID: PMC11899790 DOI: 10.3390/ijms26051834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2025] [Revised: 01/29/2025] [Accepted: 01/30/2025] [Indexed: 03/14/2025] Open
Abstract
Sustainable development of the largemouth bass industry is hindered by limited freshwater resources. Consequently, the expansion of farming space by brackish and saline water aquaculture has become imperative. Largemouth bass is an economically important freshwater fish species. However, there is presently a lack of germplasm resources with the capacity to adapt to hypertonic environments and maintain rapid growth. A genome-wide association study is a technique used for the detection of genetic variants associated with specific phenotypic traits. In this study, we firstly applied this technique to explore the potential single-nucleotide polymorphism (SNP) locus and candidate genes associated with rapid growth and adaptation to the hypertonic environment of largemouth bass. A total of 10 potential growth-related SNPs were obtained on chromosome 16, and SNP16:4120214 was a significant SNP peak. Based on these SNPs, 23 candidate genes were annotated in the genome, including Nkcc1, Mapkap1, Hmgcs1, Slc27a6, and Shroom3. Shroom3 expression was significantly higher in individuals enriched for the most growth-advantageous genotypes. Shroom3 upregulation is beneficial for fish growth in hyperosmotic environments. This study provides insight into the genetic basis of rapid growth in hypertonic environments and foundational information for the future breeding of salt-tolerant largemouth bass.
Collapse
Affiliation(s)
- Miaomiao Ding
- Wuxi Fisheries College, Nanjing Agricultural University, Wuxi 214081, China; (M.D.); (J.H.)
| | - Yifan Tao
- Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Ministry of Agriculture and Rural Affairs, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China; (Y.T.); (Y.D.); (S.L.)
| | - Jixiang Hua
- Wuxi Fisheries College, Nanjing Agricultural University, Wuxi 214081, China; (M.D.); (J.H.)
| | - Yalun Dong
- Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Ministry of Agriculture and Rural Affairs, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China; (Y.T.); (Y.D.); (S.L.)
| | - Siqi Lu
- Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Ministry of Agriculture and Rural Affairs, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China; (Y.T.); (Y.D.); (S.L.)
| | - Jun Qiang
- Wuxi Fisheries College, Nanjing Agricultural University, Wuxi 214081, China; (M.D.); (J.H.)
- Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Ministry of Agriculture and Rural Affairs, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China; (Y.T.); (Y.D.); (S.L.)
| | - Jixiang He
- Fisheries Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230041, China
| |
Collapse
|
4
|
Andersen LK, Thompson NF, Abernathy JW, Ahmed RO, Ali A, Al-Tobasei R, Beck BH, Calla B, Delomas TA, Dunham RA, Elsik CG, Fuller SA, García JC, Gavery MR, Hollenbeck CM, Johnson KM, Kunselman E, Legacki EL, Liu S, Liu Z, Martin B, Matt JL, May SA, Older CE, Overturf K, Palti Y, Peatman EJ, Peterson BC, Phelps MP, Plough LV, Polinski MP, Proestou DA, Purcell CM, Quiniou SMA, Raymo G, Rexroad CE, Riley KL, Roberts SB, Roy LA, Salem M, Simpson K, Waldbieser GC, Wang H, Waters CD, Reading BJ. Advancing genetic improvement in the omics era: status and priorities for United States aquaculture. BMC Genomics 2025; 26:155. [PMID: 39962419 PMCID: PMC11834649 DOI: 10.1186/s12864-025-11247-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Accepted: 01/15/2025] [Indexed: 02/20/2025] Open
Abstract
BACKGROUND The innovations of the "Omics Era" have ushered in significant advancements in genetic improvement of agriculturally important animal species through transforming genetics, genomics and breeding strategies. These advancements were often coordinated, in part, by support provided over 30 years through the 1993-2023 National Research Support Project 8 (NRSP8, National Animal Genome Research Program, NAGRP) and affiliate projects focused on enabling genomic discoveries in livestock, poultry, and aquaculture species. These significant and parallel advances demand strategic planning of future research priorities. This paper, as an output from the May 2023 Aquaculture Genomics, Genetics, and Breeding Workshop, provides an updated status of genomic resources for United States aquaculture species, highlighting major achievements and emerging priorities. MAIN TEXT Finfish and shellfish genome and omics resources enhance our understanding of genetic architecture and heritability of performance and production traits. The 2023 Workshop identified present aims for aquaculture genomics/omics research to build on this progress: (1) advancing reference genome assembly quality; (2) integrating multi-omics data to enhance analysis of production and performance traits; (3) developing resources for the collection and integration of phenomics data; (4) creating pathways for applying and integrating genomics information across animal industries; and (5) providing training, extension, and outreach to support the application of genome to phenome. Research focuses should emphasize phenomics data collection, artificial intelligence, identifying causative relationships between genotypes and phenotypes, establishing pathways to apply genomic information and tools across aquaculture industries, and an expansion of training programs for the next-generation workforce to facilitate integration of genomic sciences into aquaculture operations to enhance productivity, competitiveness, and sustainability. CONCLUSION This collective vision of applying genomics to aquaculture breeding with focus on the highlighted priorities is intended to facilitate the continued advancement of the United States aquaculture genomics, genetics and breeding research community and industries. Critical challenges ahead include the practical application of genomic tools and analytical frameworks beyond academic and research communities that require collaborative partnerships between academia, government, and industry. The scope of this review encompasses the use of omics tools and applications in the study of aquatic animals cultivated for human consumption in aquaculture settings throughout their life-cycle.
Collapse
Affiliation(s)
| | | | | | - Ridwan O Ahmed
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | - Ali Ali
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | | | - Benjamin H Beck
- USDA-ARS Aquatic Animal Health Research Unit, Auburn, AL, USA
| | - Bernarda Calla
- USDA-ARS Pacific Shellfish Research Unit, Newport, OR, USA
| | - Thomas A Delomas
- USDA-ARS National Cold Water Marine Aquaculture Center, Kingston, RI, USA
| | - Rex A Dunham
- School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, AL, USA
| | | | - S Adam Fuller
- USDA-ARS Harry K Dupree Stuttgart National Aquaculture Research Center, Stuttgart, AR, USA
| | - Julio C García
- USDA-ARS Aquatic Animal Health Research Unit, Auburn, AL, USA
| | - Mackenzie R Gavery
- Environmental and Fishery Sciences Division, NOAA Northwest Fisheries Science Center, Seattle, WA, USA
| | - Christopher M Hollenbeck
- Texas A&M AgriLife Research, College Station, TX, USA
- Texas A&M University - Corpus Christi, Corpus Christi, TX, USA
| | - Kevin M Johnson
- California Sea Grant, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
- Biological Sciences Department, Center for Coastal Marine Sciences, California Polytechnic State University, San Luis Obispo, CA, USA
| | | | - Erin L Legacki
- USDA-ARS National Cold Water Marine Aquaculture Center, Orono, ME, USA
| | - Sixin Liu
- USDA-ARS National Center for Cool and Cold Water Aquaculture, Kearneysville, WV, USA
| | - Zhanjiang Liu
- Department of Biology, Tennessee Technological University, Cookeville, TN, USA
| | - Brittany Martin
- USDA-ARS Aquatic Animal Health Research Unit, Auburn, AL, USA
| | - Joseph L Matt
- Texas A&M University - Corpus Christi, Corpus Christi, TX, USA
| | - Samuel A May
- USDA-ARS National Cold Water Marine Aquaculture Center, Orono, ME, USA
| | - Caitlin E Older
- USDA-ARS Warmwater Aquaculture Research Unit, Stoneville, MS, USA
| | - Ken Overturf
- USDA-ARS Small Grains and Potato Germplasm Research, Hagerman, ID, USA
| | - Yniv Palti
- USDA-ARS National Center for Cool and Cold Water Aquaculture, Kearneysville, WV, USA
| | | | - Brian C Peterson
- USDA-ARS National Cold Water Marine Aquaculture Center, Orono, ME, USA
| | | | - Louis V Plough
- USDA-ARS Pacific Shellfish Research Unit, Newport, OR, USA
- Horn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD, USA
| | - Mark P Polinski
- USDA-ARS National Cold Water Marine Aquaculture Center, Orono, ME, USA
| | - Dina A Proestou
- USDA-ARS National Cold Water Marine Aquaculture Center, Kingston, RI, USA
| | | | | | - Guglielmo Raymo
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | | | - Kenneth L Riley
- Office of Aquaculture, NOAA Fisheries, Silver Spring, MD, USA
| | | | - Luke A Roy
- School of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Alabama Fish Farming Center, Greensboro, AL, USA
| | - Mohamed Salem
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, USA
| | - Kelly Simpson
- USDA-ARS Aquatic Animal Health Research Unit, Auburn, AL, USA
| | | | | | - Charles D Waters
- NOAA Alaska Fisheries Science Center Auke Bay Laboratories, Juneau, AK, USA
| | - Benjamin J Reading
- Department of Applied Ecology, North Carolina State University, Raleigh, NC, USA
| |
Collapse
|
5
|
He X, Zhang J, Jiang W, Wu P, Liu Y, Ren H, Jin X, Shi H, Zhou X, Feng L. A new insight on alleviating the inhibitory effect of aflatoxin B1 on muscle development in grass carp ( Ctenopharyngodon idella): The effect of 4-Methylesculetin in vivo and in vitro. ANIMAL NUTRITION (ZHONGGUO XU MU SHOU YI XUE HUI) 2024; 19:339-354. [PMID: 39640553 PMCID: PMC11617288 DOI: 10.1016/j.aninu.2024.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 08/01/2024] [Accepted: 08/18/2024] [Indexed: 12/07/2024]
Abstract
Aflatoxin B1 (AFB1), an important fungal toxin, exists mainly in plant feed ingredients and animals consuming feed contaminated with AFB1 will have reduced growth and impaired health condition mainly due to oxidative stress and reduced immunity. Our previous study found that AFB1 caused oxidative damage and inhibited muscle development of zebrafish. 4-Methylesculetin (4-ME), a coumarin derivative, is now used in biochemistry and medicine widely because of its antioxidant function. Whether 4-ME could alleviate the inhibition of muscle development in grass carp induced by AFB1 has not been reported. In this experiment, 720 healthy grass carp (11.40 ± 0.01 g) were randomly divided into 4 groups with 3 replicates of 60 fish each, including control group, AFB1 group (60 μg/kg diet AFB1), 4-ME group (10 mg/kg diet 4-ME), and AFB1+4-ME group (60 μg/kg diet AFB1 + 10 mg/kg 4-ME diet), for a 60-d growth experiment. In vitro, we also set up 4 treatment groups for grass carp primary myoblast, including control group, AFB1 group (15 μmol/L AFB1), 4-ME group (0.5 μmol/L 4-ME) and AFB1+4-ME group (15 μmol/L AFB1+0.5 μmol/L 4-ME). The results showed that dietary AFB1 decreased growth performance of grass carp, damaged the ultrastructure and induced oxidative damage in grass carp muscle, and significantly decreased the mRNA and protein expression levels of myogenin (MyoG), myogenic differentiation (MyoD), myosin heavy chain (MYHC), as well as the protein expression levels of laminin β1, fibronectin and collagen Ⅰ (P < 0.05), significantly activated the protein expression levels of urokinase-type plasminogen activator (uPA), matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9) and phosphorylate-38 mitogen-activated protein kinase (p38 MAPK) both in grass carp muscle and grass carp primary myoblast (P < 0.05). Supplementation of AFB1 with 4-ME significantly improved the growth performance inhibition and alleviated the muscle fiber development inhibition and extracellular matrix (ECM) degradation in grass carp induced by AFB1 (P < 0.05). The present results revealed that supplementation of AFB1 contaminated feed with 4-ME reduced the inhibition of growth and muscle development by alleviating AFB1-induced ECM degradation in grass carp, which might be related to the p38 MAPK/uPA/MMP/ECM pathway. The results implied that 4-ME could be used as a valuable mycotoxin scavenger in animal feed.
Collapse
Affiliation(s)
- Xiangning He
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiajia Zhang
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Weidan Jiang
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
- Fish Nutrition and Safety Production, University Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
- Key Laboratory for Animal Disease-Resistance Nutrition, Ministry of Education, Ministry of Agriculture and Rural Affairs, Key Laboratory of Sichuan Provence, Chengdu 611130, China
| | - Pei Wu
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
- Fish Nutrition and Safety Production, University Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
- Key Laboratory for Animal Disease-Resistance Nutrition, Ministry of Education, Ministry of Agriculture and Rural Affairs, Key Laboratory of Sichuan Provence, Chengdu 611130, China
| | - Yang Liu
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
- Fish Nutrition and Safety Production, University Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
- Key Laboratory for Animal Disease-Resistance Nutrition, Ministry of Education, Ministry of Agriculture and Rural Affairs, Key Laboratory of Sichuan Provence, Chengdu 611130, China
| | - Hongmei Ren
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaowan Jin
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Hequn Shi
- Guangzh Cohoo Biotechnology Co., Ltd., Guangzhou 510663, China
| | - Xiaoqiu Zhou
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
- Fish Nutrition and Safety Production, University Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
- Key Laboratory for Animal Disease-Resistance Nutrition, Ministry of Education, Ministry of Agriculture and Rural Affairs, Key Laboratory of Sichuan Provence, Chengdu 611130, China
| | - Lin Feng
- Animal Nutrition Institute, Sichuan Agricultural University, Chengdu 611130, China
- Fish Nutrition and Safety Production, University Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
- Key Laboratory for Animal Disease-Resistance Nutrition, Ministry of Education, Ministry of Agriculture and Rural Affairs, Key Laboratory of Sichuan Provence, Chengdu 611130, China
| |
Collapse
|
6
|
Zhou Q, Wang J, Li J, Chen Z, Wang N, Li M, Wang L, Si Y, Lu S, Cui Z, Liu X, Chen S. Decoding the fish genome opens a new era in important trait research and molecular breeding in China. SCIENCE CHINA. LIFE SCIENCES 2024; 67:2064-2083. [PMID: 39145867 DOI: 10.1007/s11427-023-2670-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Accepted: 07/01/2024] [Indexed: 08/16/2024]
Abstract
Aquaculture represents the fastest-growing global food production sector, as it has become an essential component of the global food supply. China has the world's largest aquaculture industry in terms of production volume. However, the sustainable development of fish culture is hindered by several concerns, including germplasm degradation and disease outbreaks. The practice of genomic breeding, which relies heavily on genome information and genotypephenotype relationships, has significant potential for increasing the efficiency of aquaculture production. In 2014, the completion of the genome sequencing and annotation of the Chinese tongue sole signified the beginning of the fish genomics era in China. Since then, domestic researchers have made dramatic progress in functional genomic studies. To date, the genomes of more than 60 species of fish in China have been assembled and annotated. Based on these reference genomes, evolutionary, comparative, and functional genomic studies have revolutionized our understanding of a wide range of biologically and economically important traits of fishes, including growth and development, sex determination, disease resistance, metamorphosis, and pigmentation. Furthermore, genomic tools and breeding techniques such as SNP arrays, genomic selection, and genome editing have greatly accelerated genetic improvement through the incorporation of functional genomic information into breeding activities. This review aims to summarize the current status, advances, and perspectives of the genome resources, genomic study of important traits, and genomic breeding techniques of fish in China. The review will provide aquaculture researchers, fish breeders, and farmers with updated information concerning fish genomic research and breeding technology. The summary will help to promote the genetic improvement of production traits and thus will support the sustainable development of fish aquaculture.
Collapse
Affiliation(s)
- Qian Zhou
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Jialin Wang
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Jiongtang Li
- Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, 100041, China
| | - Zhangfan Chen
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Na Wang
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Ming Li
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Lei Wang
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Yufeng Si
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Sheng Lu
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Zhongkai Cui
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Xuhui Liu
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China
| | - Songlin Chen
- State Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, Shandong, 266071, China.
- Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao Marine Science and Technology Center, Qingdao, Shandong, 266237, China.
| |
Collapse
|
7
|
Salem M, Al-Tobasei R, Ali A, An L, Wang Y, Bai X, Bi Y, Zhou H. Functional annotation of regulatory elements in rainbow trout uncovers roles of the epigenome in genetic selection and genome evolution. Gigascience 2024; 13:giae092. [PMID: 39657104 DOI: 10.1093/gigascience/giae092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 07/16/2024] [Accepted: 10/24/2024] [Indexed: 12/17/2024] Open
Abstract
Rainbow trout (RBT) has gained widespread attention as a biological model across various fields and has been rapidly adopted for aquaculture and recreational purposes on 6 continents. Despite significant efforts to develop genome sequences for RBT, the functional genomic basis of RBT's environmental, phenotypic, and evolutionary variations still requires epigenome reference annotations. This study has produced a comprehensive catalog and epigenome annotation tracks of RBT, detecting gene regulatory elements, including chromatin histone modifications, chromatin accessibility, and DNA methylation. By integrating chromatin immunoprecipitation sequencing, ATAC sequencing, Methyl Mini-seq, and RNA sequencing data, this new regulatory element catalog has helped to characterize the epigenome dynamics and its correlation with gene expression. The study has also identified potential causal variants and transcription factors regulating complex domestication phenotypic traits. This research also provides valuable insights into the epigenome's role in gene evolution and the mechanism of duplicate gene retention 100 million years after RBT whole-genome duplication and during re-diploidization. The newly developed epigenome annotation maps are among the first in fish and are expected to enhance the accuracy and efficiency of genomic studies and applications, including genome-wide association studies, causative variation identification, and genomic selection in RBT and fish comparative genomics.
Collapse
Affiliation(s)
- Mohamed Salem
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742-231, USA
| | - Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN 37132, USA
| | - Ali Ali
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742-231, USA
| | - Liqi An
- Department of Animal Science, University of California, Davis, Davis, CA 95616, USA
| | - Ying Wang
- Department of Animal Science, University of California, Davis, Davis, CA 95616, USA
| | - Xuechen Bai
- Department of Animal Science, University of California, Davis, Davis, CA 95616, USA
| | - Ye Bi
- Department of Animal Science, University of California, Davis, Davis, CA 95616, USA
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, Davis, CA 95616, USA
| |
Collapse
|
8
|
Wang W, Zhang T, Du L, Li K, Zhang L, Li H, Gao X, Xu L, Li J, Gao H. Transcriptomic analysis reveals diverse expression patterns underlying the fiber diameter of oxidative and glycolytic skeletal muscles in steers. Meat Sci 2024; 207:109350. [PMID: 37844514 DOI: 10.1016/j.meatsci.2023.109350] [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: 12/21/2022] [Revised: 08/18/2023] [Accepted: 10/02/2023] [Indexed: 10/18/2023]
Abstract
Skeletal muscles consist of heterogeneous fibers with various contractile and metabolic properties that affect meat quality. The size of muscle fibers contributes to muscle mass and myopathy. Thus, improved understanding of the expression patterns underlying fiber size might open possibilities to change them using genetic methods. The aim of this study was to reveal transcriptomic landscapes of one oxidative (Psoas major) and three glycolytic (Longissimus lumborum, Triceps brachii, and Semimembranosus) muscles. Principal component analysis (PCA) showed significant differences in gene expression among the four muscles. Specifically, 2777 differentially expressed genes (DEGs) were detected between six pairwise comparisons of the four muscles. Weighted gene co-expression network analysis (WGCNA) identified six modules, which were significantly associated with muscle fiber diameter. We also identified 23 candidate genes, and enrichment analysis showed that biosynthesis of amino acids (bta01230), sarcomere (GO:0030017), and regulation of actin cytoskeleton (bta04810) overlapped in DEGs and WGCNA. Nineteen of these genes (e.g., EEF1A2, FARSB, and PINK1) have been reported to promote or inhibit muscle growth and development. Our findings contribute to the understanding of fiber size differences among oxidative and glycolytic muscles, which may provide a basis for breeding to improve meat yield.
Collapse
Affiliation(s)
- Wenxiang Wang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Tianliu Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Lili Du
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Keanning Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Lupei Zhang
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Haipeng Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Xue Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Lingyang Xu
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Junya Li
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Huijiang Gao
- Laboratory of Molecular Biology and Bovine Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| |
Collapse
|
9
|
Nandanpawar P, Sahoo L, Sahoo B, Murmu K, Chaudhari A, Pavan kumar A, Das P. Identification of differentially expressed genes and SNPs linked to harvest body weight of genetically improved rohu carp, Labeo rohita. Front Genet 2023; 14:1153911. [PMID: 37359361 PMCID: PMC10285081 DOI: 10.3389/fgene.2023.1153911] [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: 01/30/2023] [Accepted: 05/25/2023] [Indexed: 06/28/2023] Open
Abstract
In most of the aquaculture selection programs, harvest body weight has been a preferred performance trait for improvement. Molecular interplay of genes linked to higher body weight is not elucidated in major carp species. The genetically improved rohu carp with 18% average genetic gain per generation with respect to harvest body weight is a promising candidate for studying genes' underlying performance traits. In the present study, muscle transcriptome sequencing of two groups of individuals, with significant difference in breeding value, belonging to the tenth generation of rohu carp was performed using the Illumina HiSeq 2000 platform. A total of 178 million paired-end raw reads were generated to give rise to 173 million reads after quality control and trimming. The genome-guided transcriptome assembly and differential gene expression produced 11,86,119 transcripts and 451 upregulated and 181 downregulated differentially expressed genes (DEGs) between high-breeding value and low-breeding value (HB & LB) groups, respectively. Similarly, 39,158 high-quality coding SNPs were identified with the Ts/Tv ratio of 1.23. Out of a total of 17 qPCR-validated transcripts, eight were associated with cellular growth and proliferation and harbored 13 SNPs. The gene expression pattern was observed to be positively correlated with RNA-seq data for genes such as myogenic factor 6, titin isoform X11, IGF-1 like, acetyl-CoA, and thyroid receptor hormone beta. A total of 26 miRNA target interactions were also identified to be associated with significant DETs (p-value < 0.05). Genes such as Myo6, IGF-1-like, and acetyl-CoA linked to higher harvest body weight may serve as candidate genes in marker-assisted breeding and SNP array construction for genome-wide association studies and genomic selection.
Collapse
Affiliation(s)
- P. Nandanpawar
- ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - L. Sahoo
- ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - B. Sahoo
- ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - K. Murmu
- ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| | - A. Chaudhari
- ICAR-Central Institute of Fisheries Education, Mumbai, Maharashtra, India
| | - A. Pavan kumar
- ICAR-Central Institute of Fisheries Education, Mumbai, Maharashtra, India
| | - P. Das
- ICAR-Central Institute of Freshwater Aquaculture, Bhubaneswar, Odisha, India
| |
Collapse
|
10
|
Garcia A, Tsuruta S, Gao G, Palti Y, Lourenco D, Leeds T. Genomic selection models substantially improve the accuracy of genetic merit predictions for fillet yield and body weight in rainbow trout using a multi-trait model and multi-generation progeny testing. Genet Sel Evol 2023; 55:11. [PMID: 36759760 PMCID: PMC9912574 DOI: 10.1186/s12711-023-00782-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 01/16/2023] [Indexed: 02/11/2023] Open
Abstract
BACKGROUND In aquaculture, the proportion of edible meat (FY = fillet yield) is of major economic importance, and breeding animals of superior genetic merit for this trait can improve efficiency and profitability. Achieving genetic gains for fillet yield is possible using a pedigree-based best linear unbiased prediction (PBLUP) model with direct and indirect selection. To investigate the feasibility of using genomic selection (GS) to improve FY and body weight (BW) in rainbow trout, the prediction accuracy of GS models was compared to that of PBLUP. In addition, a genome-wide association study (GWAS) was conducted to identify quantitative trait loci (QTL) for the traits. All analyses were performed using a two-trait model with FY and BW, and variance components, heritability, and genetic correlations were estimated without genomic information. The data used included 14,165 fish in the pedigree, of which 2742 and 12,890 had FY and BW phenotypic records, respectively, and 2484 had genotypes from the 57K single nucleotide polymorphism (SNP) array. RESULTS The heritabilities were moderate, at 0.41 and 0.33 for FY and BW, respectively. Both traits were lowly but positively correlated (genetic correlation; r = 0.24), which suggests potential favourable correlated genetic gains. GS models increased prediction accuracy compared to PBLUP by up to 50% for FY and 44% for BW. Evaluations were found to be biased when validation was performed on future performances but not when it was performed on future genomic estimated breeding values. CONCLUSIONS The low but positive genetic correlation between fillet yield and body weight indicates that some improvement in fillet yield may be achieved through indirect selection for body weight. Genomic information increases the prediction accuracy of breeding values and is an important tool to accelerate genetic progress for fillet yield and growth in the current rainbow trout population. No significant QTL were found for either trait, indicating that both traits are polygenic, and that marker-assisted selection will not be helpful to improve these traits in this population.
Collapse
Affiliation(s)
- Andre Garcia
- grid.213876.90000 0004 1936 738XDepartment of Animal and Dairy Science, University of Georgia, Athens, GA 30602 USA
| | - Shogo Tsuruta
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA.
| | - Guangtu Gao
- grid.463419.d0000 0001 0946 3608National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV 25430 USA
| | - Yniv Palti
- grid.463419.d0000 0001 0946 3608National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV 25430 USA
| | - Daniela Lourenco
- grid.213876.90000 0004 1936 738XDepartment of Animal and Dairy Science, University of Georgia, Athens, GA 30602 USA
| | - Tim Leeds
- grid.463419.d0000 0001 0946 3608National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV 25430 USA
| |
Collapse
|
11
|
Ahmed RO, Ali A, Al-Tobasei R, Leeds T, Kenney B, Salem M. Weighted Single-Step GWAS Identifies Genes Influencing Fillet Color in Rainbow Trout. Genes (Basel) 2022; 13:genes13081331. [PMID: 35893068 PMCID: PMC9332390 DOI: 10.3390/genes13081331] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/22/2022] [Accepted: 07/23/2022] [Indexed: 02/04/2023] Open
Abstract
The visual appearance of the fish fillet is a significant determinant of consumers' purchase decisions. Depending on the rainbow trout diet, a uniform bright white or reddish/pink fillet color is desirable. Factors affecting fillet color are complex, ranging from the ability of live fish to accumulate carotenoids in the muscle to preharvest environmental conditions, early postmortem muscle metabolism, and storage conditions. Identifying genetic markers of fillet color is a desirable goal but a challenging task for the aquaculture industry. This study used weighted, single-step GWAS to explore the genetic basis of fillet color variation in rainbow trout. We identified several SNP windows explaining up to 3.5%, 2.5%, and 1.6% of the additive genetic variance for fillet redness, yellowness, and whiteness, respectively. SNPs are located within genes implicated in carotenoid metabolism (β,β-carotene 15,15'-dioxygenase, retinol dehydrogenase) and myoglobin homeostasis (ATP synthase subunit β, mitochondrial (ATP5F1B)). These genes are involved in processes that influence muscle pigmentation and postmortem flesh coloration. Other identified genes are involved in the maintenance of muscle structural integrity (kelch protein 41b (klh41b), collagen α-1(XXVIII) chain (COL28A1), and cathepsin K (CTSK)) and protection against lipid oxidation (peroxiredoxin, superoxide dismutase 2 (SOD2), sestrin-1, Ubiquitin carboxyl-terminal hydrolase-10 (USP10)). A-to-G single-nucleotide polymorphism in β,β-carotene 15,15'-dioxygenase, and USP10 result in isoleucine-to-valine and proline-to-leucine non-synonymous amino acid substitutions, respectively. Our observation confirms that fillet color is a complex trait regulated by many genes involved in carotenoid metabolism, myoglobin homeostasis, protection against lipid oxidation, and maintenance of muscle structural integrity. The significant SNPs identified in this study could be prioritized via genomic selection in breeding programs to improve fillet color in rainbow trout.
Collapse
Affiliation(s)
- Ridwan O. Ahmed
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA; (R.O.A.); (A.A.)
| | - Ali Ali
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA; (R.O.A.); (A.A.)
| | - Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN 37132, USA;
| | - Tim Leeds
- United States Department of Agriculture Kearneysville, National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, Kearneysville, WV 25430, USA;
| | - Brett Kenney
- Division of Animal and Nutritional Sciences, West Virginia University, Morgantown, WV 26506, USA;
| | - Mohamed Salem
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA; (R.O.A.); (A.A.)
- Correspondence:
| |
Collapse
|
12
|
Genome-wide association study reveals the genetic basis of growth trait in yellow catfish with sexual size dimorphism. Genomics 2022; 114:110380. [PMID: 35533968 DOI: 10.1016/j.ygeno.2022.110380] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 04/20/2022] [Accepted: 05/02/2022] [Indexed: 01/14/2023]
Abstract
Sexual size dimorphism has been widely observed in a large number of animals including fish species. Genome-wide association study (GWAS) is a powerful tool to dissect the genetic basis of complex traits, whereas the sex-differences in the genomics of animal complex traits have been ignored in the GWAS analysis. Yellow catfish (Pelteobagrus fulvidraco) is an important aquaculture fish in China with significant sexual size dimorphism. In this study, GWAS was conducted to identify candidate SNPs and genes related to body length (BL) and body weight (BW) in 125 female yellow catfish from a breeding population. In total, one BL-related SNP and three BW-related SNPs were identified to be significantly associated with the traits. Besides, one of these SNPs (Chr15:19195072) was shared in both the BW and BL traits in female yellow catfish, which was further validated in 185 male individuals and located on the exon of stat5b gene. Transgenic yellow catfish and zebrafish that expressed yellow catfish stat5b showed increased growth rate and reduction of sexual size dimorphism. These results not only reveal the genetic basis of growth trait and sexual size dimorphism in fish species, but also provide useful information for the marker-assisted breeding in yellow catfish.
Collapse
|
13
|
Palaiokostas C, Anjum A, Jeuthe H, Kurta K, Lopes Pinto F, Koning DJ. A genomic‐based vision on the genetic diversity and key performance traits in selectively bred Arctic charr (
Salvelinus alpinus
). Evol Appl 2021; 15:565-577. [PMID: 35505879 PMCID: PMC9046918 DOI: 10.1111/eva.13261] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 04/19/2021] [Accepted: 05/29/2021] [Indexed: 12/25/2022] Open
Abstract
Routine implementation of genomic information for guiding selection decisions is not yet common in the majority of aquaculture species. Reduced representation sequencing approaches offer a cost‐effective solution for obtaining genome‐wide information in species with a limited availability of genomic resources. In the current study, we implemented double‐digest restriction site‐associated DNA sequencing (ddRAD‐seq) on an Arctic charr strain with the longest known history of selection (approximately 40 years) aiming to improve selection decisions. In total, 1730 animals reared at four different farms in Sweden and spanning from year classes 2013–2017 were genotyped using ddRAD‐seq. Approximately 5000 single nucleotide polymorphisms (SNPs) were identified, genetic diversity‐related metrics were estimated, and genome‐wide association studies (GWAS) for body length at different time points and age of sexual maturation were conducted. Low genetic differentiation amongst animals from the different farms was observed based on both the results from pairwise Fst values and principal component analysis (PCA). The existence of associations was investigated between the mean genome‐wide heterozygosity of each full‐sib family (year class 2017) and the corresponding inbreeding coefficient or survival to the eyed stage. A moderate correlation (−0.33) was estimated between the mean observed heterozygosity of each full‐sib family and the corresponding inbreeding coefficient, while no linear association was obtained with the survival to the eyed stage. GWAS did not detect loci with major effect for any of the studied traits. However, genomic regions explaining more than 1% of the additive genetic variance for either studied traits were suggested across 14 different chromosomes. Overall, key insights valuable for future selection decisions of Arctic charr have been obtained, suggesting ddRAD as an attractive genotyping platform for obtaining genome‐wide information in a cost‐effective manner.
Collapse
Affiliation(s)
- Christos Palaiokostas
- Department of Animal Breeding and Genetics Swedish University of Agricultural Sciences Uppsala Sweden
| | - Anam Anjum
- Department of Animal Breeding and Genetics Swedish University of Agricultural Sciences Uppsala Sweden
| | - Henrik Jeuthe
- Department of Animal Breeding and Genetics Swedish University of Agricultural Sciences Uppsala Sweden
- Aquaculture Center North Kälarne Sweden
| | - Khrystyna Kurta
- Department of Animal Breeding and Genetics Swedish University of Agricultural Sciences Uppsala Sweden
| | - Fernando Lopes Pinto
- Department of Animal Breeding and Genetics Swedish University of Agricultural Sciences Uppsala Sweden
| | - Dirk Jan Koning
- Department of Animal Breeding and Genetics Swedish University of Agricultural Sciences Uppsala Sweden
| |
Collapse
|
14
|
Orbán L, Shen X, Phua N, Varga L. Toward Genome-Based Selection in Asian Seabass: What Can We Learn From Other Food Fishes and Farm Animals? Front Genet 2021; 12:506754. [PMID: 33968125 PMCID: PMC8097054 DOI: 10.3389/fgene.2021.506754] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 03/15/2021] [Indexed: 01/08/2023] Open
Abstract
Due to the steadily increasing need for seafood and the plateauing output of fisheries, more fish need to be produced by aquaculture production. In parallel with the improvement of farming methods, elite food fish lines with superior traits for production must be generated by selection programs that utilize cutting-edge tools of genomics. The purpose of this review is to provide a historical overview and status report of a selection program performed on a catadromous predator, the Asian seabass (Lates calcarifer, Bloch 1790) that can change its sex during its lifetime. We describe the practices of wet lab, farm and lab in detail by focusing onto the foundations and achievements of the program. In addition to the approaches used for selection, our review also provides an inventory of genetic/genomic platforms and technologies developed to (i) provide current and future support for the selection process; and (ii) improve our understanding of the biology of the species. Approaches used for the improvement of terrestrial farm animals are used as examples and references, as those processes are far ahead of the ones used in aquaculture and thus they might help those working on fish to select the best possible options and avoid potential pitfalls.
Collapse
Affiliation(s)
- László Orbán
- Reproductive Genomics Group, Temasek Life Sciences Laboratory, Singapore, Singapore.,Frontline Fish Genomics Research Group, Department of Applied Fish Biology, Institute of Aquaculture and Environmental Safety, Hungarian University of Agriculture and Life Sciences, Keszthely, Hungary
| | - Xueyan Shen
- Reproductive Genomics Group, Temasek Life Sciences Laboratory, Singapore, Singapore.,Tropical Futures Institute, James Cook University, Singapore, Singapore
| | - Norman Phua
- Reproductive Genomics Group, Temasek Life Sciences Laboratory, Singapore, Singapore
| | - László Varga
- Institute of Genetics and Biotechnology, Hungarian University of Agriculture and Life Sciences, Gödöllõ, Hungary.,Institute for Farm Animal Gene Conservation, National Centre for Biodiversity and Gene Conservation, Gödöllõ, Hungary
| |
Collapse
|
15
|
Blay C, Haffray P, Bugeon J, D’Ambrosio J, Dechamp N, Collewet G, Enez F, Petit V, Cousin X, Corraze G, Phocas F, Dupont-Nivet M. Genetic Parameters and Genome-Wide Association Studies of Quality Traits Characterised Using Imaging Technologies in Rainbow Trout, Oncorhynchus mykiss. Front Genet 2021; 12:639223. [PMID: 33692832 PMCID: PMC7937956 DOI: 10.3389/fgene.2021.639223] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 02/03/2021] [Indexed: 12/18/2022] Open
Abstract
One of the top priorities of the aquaculture industry is the genetic improvement of economically important traits in fish, such as those related to processing and quality. However, the accuracy of genetic evaluations has been hindered by a lack of data on such traits from a sufficiently large population of animals. The objectives of this study were thus threefold: (i) to estimate genetic parameters of growth-, yield-, and quality-related traits in rainbow trout (Oncorhynchus mykiss) using three different phenotyping technologies [invasive and non-invasive: microwave-based, digital image analysis, and magnetic resonance imaging (MRI)], (ii) to detect quantitative trait loci (QTLs) associated with these traits, and (iii) to identify candidate genes present within these QTL regions. Our study collected data from 1,379 fish on growth, yield-related traits (body weight, condition coefficient, head yield, carcass yield, headless gutted carcass yield), and quality-related traits (total fat, percentage of fat in subcutaneous adipose tissue, percentage of fat in flesh, flesh colour); genotypic data were then obtained for all fish using the 57K SNP Axiom® Trout Genotyping array. Heritability estimates for most of the 14 traits examined were moderate to strong, varying from 0.12 to 0.67. Most traits were clearly polygenic, but our genome-wide association studies (GWASs) identified two genomic regions on chromosome 8 that explained up to 10% of the genetic variance (cumulative effects of two QTLs) for several traits (weight, condition coefficient, subcutaneous and total fat content, carcass and headless gutted carcass yields). For flesh colour traits, six QTLs explained 1-4% of the genetic variance. Within these regions, we identified several genes (htr1, gnpat, ephx1, bcmo1, and cyp2x) that have been implicated in adipogenesis or carotenoid metabolism, and thus represent good candidates for further functional validation. Finally, of the three techniques used for phenotyping, MRI demonstrated particular promise for measurements of fat content and distribution, while the digital image analysis-based approach was very useful in quantifying colour-related traits. This work provides new insights that may aid the development of commercial breeding programmes in rainbow trout, specifically with regard to the genetic improvement of yield and flesh-quality traits as well as the use of invasive and/or non-invasive technologies to predict such traits.
Collapse
Affiliation(s)
- Carole Blay
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
| | | | | | - Jonathan D’Ambrosio
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
- SYSAAF, Station LPGP-INRAE, Rennes, France
| | - Nicolas Dechamp
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
| | | | | | | | - Xavier Cousin
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
- MARBEC, University of Montpellier, CNRS, Ifremer, IRD, Palavas-les-Flots, France
| | - Geneviève Corraze
- INRAE, University of Pau & Pays Adour, E2S UPPA, UMR 1419 NuMéA, Saint-Pée-sur-Nivelle, France
| | - Florence Phocas
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
| | | |
Collapse
|
16
|
Al-Tobasei R, Ali A, Garcia ALS, Lourenco D, Leeds T, Salem M. Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels. BMC Genomics 2021; 22:92. [PMID: 33516179 PMCID: PMC7847601 DOI: 10.1186/s12864-021-07404-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 01/22/2021] [Indexed: 12/20/2022] Open
Abstract
Background One of the most important goals for the rainbow trout aquaculture industry is to improve fillet yield and fillet quality. Previously, we showed that a 50 K transcribed-SNP chip can be used to detect quantitative trait loci (QTL) associated with fillet yield and fillet firmness. In this study, data from 1568 fish genotyped for the 50 K transcribed-SNP chip and ~ 774 fish phenotyped for fillet yield and fillet firmness were used in a single-step genomic BLUP (ssGBLUP) model to compute the genomic estimated breeding values (GEBV). In addition, pedigree-based best linear unbiased prediction (PBLUP) was used to calculate traditional, family-based estimated breeding values (EBV). Results The genomic predictions outperformed the traditional EBV by 35% for fillet yield and 42% for fillet firmness. The predictive ability for fillet yield and fillet firmness was 0.19–0.20 with PBLUP, and 0.27 with ssGBLUP. Additionally, reducing SNP panel densities indicated that using 500–800 SNPs in genomic predictions still provides predictive abilities higher than PBLUP. Conclusion These results suggest that genomic evaluation is a feasible strategy to identify and select fish with superior genetic merit within rainbow trout families, even with low-density SNP panels. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07404-9.
Collapse
Affiliation(s)
- Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Ali Ali
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Andre L S Garcia
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA
| | - Daniela Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA
| | - Tim Leeds
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA
| | - Mohamed Salem
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| |
Collapse
|
17
|
Zou K, Kim KS, Kim K, Kang D, Park YH, Sun H, Ha BK, Ha J, Jun TH. Genetic Diversity and Genome-Wide Association Study of Seed Aspect Ratio Using a High-Density SNP Array in Peanut ( Arachis hypogaea L.). Genes (Basel) 2020; 12:E2. [PMID: 33375051 PMCID: PMC7822046 DOI: 10.3390/genes12010002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 12/09/2020] [Accepted: 12/17/2020] [Indexed: 12/12/2022] Open
Abstract
Peanut (Arachis hypogaea L.) is one of the important oil crops of the world. In this study, we aimed to evaluate the genetic diversity of 384 peanut germplasms including 100 Korean germplasms and 284 core collections from the United States Department of Agriculture (USDA) using an Axiom_Arachis array with 58K single-nucleotide polymorphisms (SNPs). We evaluated the evolutionary relationships among 384 peanut germplasms using a genome-wide association study (GWAS) of seed aspect ratio data processed by ImageJ software. In total, 14,030 filtered polymorphic SNPs were identified from the peanut 58K SNP array. We identified five SNPs with significant associations to seed aspect ratio on chromosomes Aradu.A09, Aradu.A10, Araip.B08, and Araip.B09. AX-177640219 on chromosome Araip.B08 was the most significantly associated marker in GAPIT and Regularization method. Phosphoenolpyruvate carboxylase (PEPC) was found among the eleven genes within a linkage disequilibrium (LD) of the significant SNPs on Araip.B08 and could have a strong causal effect in determining seed aspect ratio. The results of the present study provide information and methods that are useful for further genetic and genomic studies as well as molecular breeding programs in peanuts.
Collapse
Affiliation(s)
- Kunyan Zou
- Department of Plant Bioscience, Pusan National University, Miryang 50463, Korea; (K.Z.); (D.K.); (Y.-H.P.)
| | | | - Kipoong Kim
- Department of Statistics, Pusan National University, Busan 46241, Korea; (K.K.); (H.S.)
| | - Dongwoo Kang
- Department of Plant Bioscience, Pusan National University, Miryang 50463, Korea; (K.Z.); (D.K.); (Y.-H.P.)
| | - Yu-Hyeon Park
- Department of Plant Bioscience, Pusan National University, Miryang 50463, Korea; (K.Z.); (D.K.); (Y.-H.P.)
| | - Hokeun Sun
- Department of Statistics, Pusan National University, Busan 46241, Korea; (K.K.); (H.S.)
| | - Bo-Keun Ha
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Korea;
| | - Jungmin Ha
- Department of Plant Science, Gangneung-Wonju National University, Gangneung 25457, Korea;
| | - Tae-Hwan Jun
- Department of Plant Bioscience, Pusan National University, Miryang 50463, Korea; (K.Z.); (D.K.); (Y.-H.P.)
- Life and Industry Convergence Research Institute, Pusan National University, Miryang 50463, Korea
| |
Collapse
|
18
|
Zhou T, Chen B, Ke Q, Zhao J, Pu F, Wu Y, Chen L, Zhou Z, Bai Y, Pan Y, Gong J, Zheng W, Xu P. Development and Evaluation of a High-Throughput Single-Nucleotide Polymorphism Array for Large Yellow Croaker ( Larimichthys crocea). Front Genet 2020; 11:571751. [PMID: 33193675 PMCID: PMC7645154 DOI: 10.3389/fgene.2020.571751] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 09/29/2020] [Indexed: 11/16/2022] Open
Abstract
High-density single-nucleotide polymorphism (SNP) genotyping array is an essential tool for genetic analyses of animals and plants. Large yellow croaker (Larimichthys crocea) is one of the most commercially important marine fish species in China. Although plenty of SNPs have been identified in large yellow croaker, no high-throughput genotyping array is available. In this study, a high-throughput SNP array named NingXin-I with 600K SNPs was developed and evaluated. A set of 82 large yellow croakers were collected from different locations of China and re-sequenced. A total of 9.34M SNPs were identified by mapping sequence reads to the large yellow croaker reference genome. About 1.98M candidate SNPs were selected for further analyses by using criteria such as SNP quality score and conversion performance in the final array. Finally, 579.5K SNPs evenly distributed across the large yellow croaker genome with an average spacing of 1.19 kb were proceeded to array production. The performance of NingXin-I array was evaluated in 96 large yellow croaker individuals from five populations, and 83.38% SNPs on the array were polymorphic sites. A further test of the NingXin-I array in five closely related species in Sciaenidae identified 26.68–56.23% polymorphic SNP rate across species. A phylogenetic tree inferred by using the genotype data generated by NingXin-I confirmed the phylogenetic distance of the species in Sciaenidae. The performance of NingXin-I in large yellow croaker and the other species in Sciaenidae suggested high accuracy and broad application. The NingXin-I array should be valuable for quantitative genetic studies, such as genome-wide association studies (GWASs), high-density linkage map construction, haplotype analysis, and genome-based selection.
Collapse
Affiliation(s)
- Tao Zhou
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Baohua Chen
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Qiaozhen Ke
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Large Yellow Croaker Breeding, Ningde Fufa Fisheries Company Limited, Ningde, China
| | - Ji Zhao
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Fei Pu
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Yidi Wu
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Lin Chen
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Zhixiong Zhou
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Yulin Bai
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Ying Pan
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Large Yellow Croaker Breeding, Ningde Fufa Fisheries Company Limited, Ningde, China
| | - Jie Gong
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
| | - Weiqiang Zheng
- State Key Laboratory of Large Yellow Croaker Breeding, Ningde Fufa Fisheries Company Limited, Ningde, China
| | - Peng Xu
- Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China.,State Key Laboratory of Large Yellow Croaker Breeding, Ningde Fufa Fisheries Company Limited, Ningde, China
| |
Collapse
|
19
|
Ali A, Al-Tobasei R, Lourenco D, Leeds T, Kenney B, Salem M. Genome-wide scan for common variants associated with intramuscular fat and moisture content in rainbow trout. BMC Genomics 2020; 21:529. [PMID: 32736521 PMCID: PMC7393730 DOI: 10.1186/s12864-020-06932-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 07/20/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Genetic improvement of fillet quality attributes is a priority of the aquaculture industry. Muscle composition impacts quality attributes such as flavor, appearance, texture, and juiciness. Fat and moisture make up about ~ 80% of the tissue weight. The genetic architecture underlying the fat and moisture content of the muscle is still to be fully explored in fish. A 50 K gene transcribed SNP chip was used for genotyping 789 fish with available phenotypic data for fat and moisture content. Genotyped fish were obtained from two consecutive generations produced in the National Center for Cool and Cold Water Aquaculture (NCCCWA) growth-selective breeding program. Estimates of SNP effects from weighted single-step GBLUP (WssGBLUP) were used to perform genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with the studied traits. RESULTS Using genomic sliding windows of 50 adjacent SNPs, 137 and 178 SNPs were identified as associated with fat and moisture content, respectively. Chromosomes 19 and 29 harbored the highest number of SNPs explaining at least 2% of the genetic variation in fat and moisture content. A total of 61 common SNPs on chromosomes 19 and 29 affected the aforementioned traits; this association suggests common mechanisms underlying intramuscular fat and moisture content. Additionally, based on single-marker GWA analyses, 8 and 24 SNPs were identified in association with fat and moisture content, respectively. CONCLUSION SNP-harboring genes were primarily involved in lipid metabolism, cytoskeleton remodeling, and protein turnover. This work provides putative SNP markers that could be prioritized and used for genomic selection in breeding programs.
Collapse
Affiliation(s)
- Ali Ali
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Daniela Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA
| | - Tim Leeds
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA
| | - Brett Kenney
- Division of Animal and Nutritional Sciences, West Virginia University, Morgantown, WV, 26506, USA
| | - Mohamed Salem
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| |
Collapse
|
20
|
Comparative Analysis of the Transcriptome and Distribution of Putative SNPs in Two Rainbow Trout ( Oncorhynchus mykiss) Breeding Strains by Using Next-Generation Sequencing. Genes (Basel) 2020; 11:genes11080841. [PMID: 32722051 PMCID: PMC7464081 DOI: 10.3390/genes11080841] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 07/22/2020] [Accepted: 07/23/2020] [Indexed: 11/24/2022] Open
Abstract
Selective breeding can significantly improve the establishment of sustainable and profitable aquaculture fish farming. For rainbow trout (Oncorhynchus mykiss), one of the main aquaculture coldwater species in Europe, a variety of selected hatchery strains are commercially available. In this study, we investigated the genetic variation between the local Born strain, selected for survival, and the commercially available Silver Steelhead strain, selected for growth. We sequenced the transcriptome of six tissues (gills, head kidney, heart, liver, spleen, and white muscle) from eight healthy individuals per strain, using RNA-seq technology to identify strain-specific gene-expression patterns and single nucleotide polymorphisms (SNPs). In total, 1760 annotated genes were differentially expressed across all tissues. Pathway analysis assigned them to different gene networks. We also identified a set of SNPs, which are heterozygous for one of the two breeding strains: 1229 of which represent polymorphisms over all tissues and individuals. Our data indicate a strong genetic differentiation between Born and Silver Steelhead trout, despite the relatively short time of evolutionary separation of the two breeding strains. The results most likely reflect their specifically adapted genotypes and might contribute to the understanding of differences regarding their robustness toward high stress and pathogenic challenge described in former studies.
Collapse
|
21
|
Yang Y, Wu L, Wu X, Li B, Huang W, Weng Z, Lin Z, Song L, Guo Y, Meng Z, Liu X, Xia J. Identification of Candidate Growth-Related SNPs and Genes Using GWAS in Brown-Marbled Grouper (Epinephelus fuscoguttatus). MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2020; 22:153-166. [PMID: 31927644 DOI: 10.1007/s10126-019-09940-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 12/22/2019] [Indexed: 06/10/2023]
Abstract
Brown-marbled grouper, Epinephelus fuscoguttatus, is not only an important commercial fish species, but also an important crossbreeding parent in grouper industry. Improvement of growth traits of this species contributes to the development of grouper breeding. Currently, the development of molecular marker associated with growth of brown-marbled grouper is rare. Thus, we performed the first genome-wide association study (GWAS) for five growth traits in 172 brown-marbled groupers with 43,688 SNPs detected by ddRAD-seq. We identified a total of 5 significant and 18 suggestive QTLs located in multiple chromosomes associated with growth traits. In the 20 kb window of the significant SNPs and suggestive SNPs, 5 and 14 potential candidate genes affecting growth were detected, respectively. Five potential candidate genes near the significantly associated SNPs were selected for expression analysis. Among of which, bmp2k, wasf1, and acyp2 involved in bone development, maintenance of mitochondrion structure, and metabolism were differentially expressed. Interestingly, the SNP 23:29601315 located in the intron of bmp2k was significantly associated with body weight, body length, body height, and body thickness and suggestively associated with total length. We verified the locus using another new group including 123 individuals. The results showed that individuals with CC genotype have better growth traits comparing other individuals. Our findings not only contribute to understanding the molecular mechanism of growth regulation, but also promote the advance of marker-assisted selection in brown-marbled grouper.
Collapse
Affiliation(s)
- Yang Yang
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Lina Wu
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Xi Wu
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Bijun Li
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Wenhua Huang
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Zhuoying Weng
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Zixuan Lin
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
| | - Leling Song
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Yin Guo
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| | - Zining Meng
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China.
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China.
- Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Guangzhou, 510275, People's Republic of China.
| | - Xiaochun Liu
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China.
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China.
- Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Guangzhou, 510275, People's Republic of China.
| | - Junhong Xia
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals and Guangdong Provincial Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yat-sen University, Guangzhou, 510275, People's Republic of China
- Southern Laboratory of Ocean Science and Engineering, Zhuhai, 519000, People's Republic of China
| |
Collapse
|
22
|
Ali A, Al-Tobasei R, Lourenco D, Leeds T, Kenney B, Salem M. Genome-wide identification of loci associated with growth in rainbow trout. BMC Genomics 2020; 21:209. [PMID: 32138655 PMCID: PMC7059289 DOI: 10.1186/s12864-020-6617-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 02/24/2020] [Indexed: 12/22/2022] Open
Abstract
Background Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. Results A previously developed 50 K gene-transcribed SNP chip, containing ~ 21 K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~ 6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R2 = 0.09). Conclusion The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.
Collapse
Affiliation(s)
- Ali Ali
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA
| | - Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Daniela Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, 30602, USA
| | - Tim Leeds
- United States Department of Agriculture Kearneysville, National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, Kearneysville, WV, USA
| | - Brett Kenney
- Division of Animal and Nutritional Sciences, West Virginia University, Morgantown, WV, 26506, USA
| | - Mohamed Salem
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
| |
Collapse
|
23
|
Dong C, Jiang P, Zhang J, Li X, Li S, Bai J, Fan J, Xu P. High-Density Linkage Map and Mapping for Sex and Growth-Related Traits of Largemouth Bass ( Micropterus salmoides). Front Genet 2019; 10:960. [PMID: 31649731 PMCID: PMC6796248 DOI: 10.3389/fgene.2019.00960] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 09/09/2019] [Indexed: 11/13/2022] Open
Abstract
The largemouth bass is an important species, and its culture has risen sharply with the surge in fish aquaculture in China. Due to the lack of selective breeding technology for the largemouth bass, the growth rate and disease resistance are low, its sexual maturation is slow, and other serious problems are contributing to a sharp decline in the safety and quality of largemouth bass products in recent decades. Therefore, comprehensive breeding programs to improve the economic performance and promote the modern industrial development of largemouth bass must be considered a priority. Here, a total of 152 adult largemouth bass, including two parents and 150 progenies, were selected to produce the genetic mapping family. Then, a high-density linkage map was constructed based on restriction site–associated DNA sequencing using 6,917 single-nucleotide polymorphisms (SNPs) located in 24 linkage groups (LGs). The total genetic length of the linkage map was 1,261.96 cM, and the length of each LG varied from 24.72 cM for LG02 to 117.53 cM for LG16, with an average length of 52.58 cM and an average SNP number of 286. Thirteen significant quantitative trait loci (QTLs) for sex determination were located on LG04, LG05, LG08, LG12, LG15, LG21, and LG23. An informative QTL cluster that included six QTLs was detected on LG12. However, one notable QTL, which accounted for 71.48% of the total phenotypic variation, was located in the region of 1.85 cM on LG05. In addition, 32 identified QTLs were related to growth, including body weight, body length, body height, and head length. The QTLs for these growth-related traits are located in 13 LG regions and have little effect on phenotypic variation. This high-density genetic linkage map will enable the fine-mapping of economic traits and support the future genome assembly of the largemouth bass. Additionally, our study will be useful for future selective culture of largemouth bass and could potentially be used in molecular-assisted breeding of largemouth bass for aquaculture.
Collapse
Affiliation(s)
- Chuanju Dong
- Pearl River Fisheries Research Institute, CAFS, Guangzhou, China.,College of Fisheries, Henan Normal University, Xinxiang, China.,Key Laboratory of Tropical and Subtropical Fishery Resource Application and Cultivation, Ministry of Agriculture, Pearl River Fisheries Research Institute, CAFS, Guangzhou, China
| | - Peng Jiang
- Pearl River Fisheries Research Institute, CAFS, Guangzhou, China
| | - Jiangfan Zhang
- College of Fisheries, Henan Normal University, Xinxiang, China
| | - Xuejun Li
- College of Fisheries, Henan Normal University, Xinxiang, China
| | - Shengjie Li
- Pearl River Fisheries Research Institute, CAFS, Guangzhou, China.,College of Fisheries, Henan Normal University, Xinxiang, China
| | - Junjie Bai
- Pearl River Fisheries Research Institute, CAFS, Guangzhou, China
| | - Jiajia Fan
- Pearl River Fisheries Research Institute, CAFS, Guangzhou, China
| | - Peng Xu
- College of Fisheries, Henan Normal University, Xinxiang, China.,State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
| |
Collapse
|
24
|
Wu L, Yang Y, Li B, Huang W, Wang X, Liu X, Meng Z, Xia J. First Genome-wide Association Analysis for Growth Traits in the Largest Coral Reef-Dwelling Bony Fishes, the Giant Grouper (Epinephelus lanceolatus). MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2019; 21:707-717. [PMID: 31392592 DOI: 10.1007/s10126-019-09916-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Accepted: 07/23/2019] [Indexed: 06/10/2023]
Abstract
The giant grouper, Epinephelus lanceolatus, is the largest coral reef-dwelling bony fish species. However, despite extremely fast growth performance and the considerable economic importance in this species, its genetic regulation of growth remains unknown. Here, we performed the first genome-wide association study (GWAS) for five growth traits in 289 giant groupers using 42,323 single nucleotide polymorphisms (SNPs) obtained by genotyping-by-sequencing (GBS). We identified a total of 36 growth-related SNPs, of which 11 SNPs reached a genome-wide significance level. The phenotypic variance explained by these SNPs varied from 7.09% for body height to 18.42% for body length. Moreover, 22 quantitative trait loci (QTLs) for growth traits, including nine significant QTLs and 13 suggestive QTLs, were found on multiple chromosomes. Interestingly, the QTL (LG17: 6934451) was shared between body weight and body height, while two significant QTLs (LG7: 22596399 and LG15: 11877836) for body length were consistent with the associated regions of total length at the genome-wide suggestive level. Eight potential candidate genes close to the associated SNPs were selected for expression analysis, of which four genes (phosphatidylinositol transfer protein cytoplasmic 1, protein tyrosine phosphatase receptor type E, alpha/beta hydrolase domain-containing protein 17C, and vascular endothelial growth factor A-A) were differentially expressed and involved in metabolism, development, response stress, etc. This study improves our understanding of the complex genetic architecture of growth in the giant grouper. The results contribute to the selective breeding of grouper species and the conservation of coral reef fishes.
Collapse
Affiliation(s)
- Lina Wu
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China
| | - Yang Yang
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China
| | - Bijun Li
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China
| | - Wenhua Huang
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China
| | - Xi Wang
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China
| | - Xiaochun Liu
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China
| | - Zining Meng
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China.
| | - Junhong Xia
- State Key Laboratory of Biocontrol, Institute of Aquatic Economic Animals, and the Guangdong Province Key Laboratory for Aquatic Economic Animals, Life Science School, Sun Yet-Sen University, Guangzhou, 510275, China
| |
Collapse
|
25
|
Ali A, Al-Tobasei R, Lourenco D, Leeds T, Kenney B, Salem M. Genome-Wide Association Study Identifies Genomic Loci Affecting Filet Firmness and Protein Content in Rainbow Trout. Front Genet 2019; 10:386. [PMID: 31130980 PMCID: PMC6509548 DOI: 10.3389/fgene.2019.00386] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 04/10/2019] [Indexed: 01/10/2023] Open
Abstract
Filet quality traits determine consumer satisfaction and affect profitability of the aquaculture industry. Soft flesh is a criterion for fish filet downgrades, resulting in loss of value. Filet firmness is influenced by many factors, including rate of protein turnover. A 50K transcribed gene SNP chip was used to genotype 789 rainbow trout, from two consecutive generations, produced in the USDA/NCCCWA selective breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform genome-wide association (GWA) analyses to identify quantitative trait loci affecting filet firmness and protein content. Applying genomic sliding windows of 50 adjacent SNPs, 212 and 225 SNPs were associated with genetic variation in filet shear force and protein content, respectively. Four common SNPs in the ryanodine receptor 3 gene (RYR3) affected the aforementioned filet traits; this association suggests common mechanisms underlying filet shear force and protein content. Genes harboring SNPs were mostly involved in calcium homeostasis, proteolytic activities, transcriptional regulation, chromatin remodeling, and apoptotic processes. RYR3 harbored the highest number of SNPs (n = 32) affecting genetic variation in shear force (2.29%) and protein content (4.97%). Additionally, based on single-marker analysis, a SNP in RYR3 ranked at the top of all SNPs associated with variation in shear force. Our data suggest a role for RYR3 in muscle firmness that may be considered for genomic- and marker-assisted selection in breeding programs of rainbow trout.
Collapse
Affiliation(s)
- Ali Ali
- Department of Biology and Molecular Biosciences Program, Middle Tennessee State University, Murfreesboro, TN, United States
| | - Rafet Al-Tobasei
- Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, United States.,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Daniela Lourenco
- Department of Animal and Dairy Science, University of Georgia, Athens, GA, United States
| | - Tim Leeds
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, United States
| | - Brett Kenney
- Division of Animal and Nutritional Sciences, West Virginia University, Morgantown, WV, United States
| | - Mohamed Salem
- Department of Biology and Molecular Biosciences Program, Middle Tennessee State University, Murfreesboro, TN, United States.,Computational Science Program, Middle Tennessee State University, Murfreesboro, TN, United States
| |
Collapse
|