1
|
Liu Z, Gao D. Hydin as the Candidate Master Sex Determination Gene in Channel Catfish (Ictalurus punctatus) and Its Epigenetic Regulation. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2024; 27:6. [PMID: 39579181 DOI: 10.1007/s10126-024-10387-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Accepted: 10/07/2024] [Indexed: 11/25/2024]
Abstract
Sex determination is a fascinating area of research. To date, more than 20 master sex determination (SD) genes have been reported from vertebrate animals. With channel catfish (Ictalurus punctatus), much work has been conducted to determine its master SD gene, ranging from genetic linkage mapping, genome-wide association (GWA) analysis, genome sequencing, comparative genome analysis, epigenomic analysis, transcriptome analysis, and functional studies. Here in this mini review, we provide positional, expression, regulatory, and functional evidence supporting hydin (hydrocephalus-inducing protein or HYDIN axonemal central pair apparatus protein-like) as a master SD gene in channel catfish. Hydin is located within the sex determination region (SDR) within a mapped 8.9-Mb non-recombinational segment on chromosome 4 of channel catfish. It is highly expressed in genetic males, but not in genetic females. The alleles of X and Y are highly differentially methylated with the X chromosome being hypermethylated and the Y chromosome hypomethylated. The hypomethylated Y allele of hydin is expressed while the hypermethylated X allele is not expressed. Such allelic expression fits well with the XY sex determination system of channel catfish. Functional analysis using a methylation blocker, 5-aza-dC, demonstrated that demethylation, especially within the SDR, is accompanied with increased expression of hydin, which led to sex reversal of genetic females into phenotypic males. These evidences support the candidacy of hydin as a master SD gene in channel catfish. Future knockout and analysis of affected genes after hydin knockout should provide insights into how hydin functions as a master SD gene.
Collapse
Affiliation(s)
- Zhanjiang Liu
- Department of Biology, College of Arts and Sciences, Tennessee Technological University, Cookeville, TN, 38505, USA.
| | - Dongya Gao
- Department of Biology, College of Arts and Sciences, Tennessee Technological University, Cookeville, TN, 38505, USA
| |
Collapse
|
2
|
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
|
3
|
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
|
4
|
Guo X, Puritz JB, Wang Z, Proestou D, Allen S, Small J, Verbyla K, Zhao H, Haggard J, Chriss N, Zeng D, Lundgren K, Allam B, Bushek D, Gomez-Chiarri M, Hare M, Hollenbeck C, La Peyre J, Liu M, Lotterhos KE, Plough L, Rawson P, Rikard S, Saillant E, Varney R, Wikfors G, Wilbur A. Development and Evaluation of High-Density SNP Arrays for the Eastern Oyster Crassostrea virginica. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2023; 25:174-191. [PMID: 36622459 DOI: 10.1007/s10126-022-10191-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
The eastern oyster Crassostrea virginica is a major aquaculture species for the USA. The sustainable development of eastern oyster aquaculture depends upon the continued improvement of cultured stocks through advanced breeding technologies. The Eastern Oyster Breeding Consortium (EOBC) was formed to advance the genetics and breeding of the eastern oyster. To facilitate efficient genotyping needed for genomic studies and selection, the consortium developed two single-nucleotide polymorphism (SNP) arrays for the eastern oyster: one screening array with 566K SNPs and one breeders' array with 66K SNPs. The 566K screening array was developed based on whole-genome resequencing data from 292 oysters from Atlantic and Gulf of Mexico populations; it contains 566,262 SNPs including 47K from protein-coding genes with a marker conversion rate of 48.34%. The 66K array was developed using best-performing SNPs from the screening array, which contained 65,893 oyster SNPs including 22,984 genic markers with a calling rate of 99.34%, a concordance rate of 99.81%, and a much-improved marker conversion rate of 92.04%. Null alleles attributable to large indels were found in 13.1% of the SNPs, suggesting that copy number variation is pervasive. Both arrays provided easy identification and separation of selected stocks from wild progenitor populations. The arrays contain 31 mitochondrial SNPs that allowed unambiguous identification of Gulf mitochondrial genotypes in some Atlantic populations. The arrays also contain 756 probes from 13 oyster and human pathogens for possible detection. Our results show that marker conversion rate is low in high polymorphism species and that the two-step process of array development can greatly improve array performance. The two arrays will advance genomic research and accelerate genetic improvement of the eastern oyster by delineating genetic architecture of production traits and enabling genomic selection. The arrays also may be used to monitor pedigree and inbreeding, identify selected stocks and their introgression into wild populations, and assess the success of oyster restoration.
Collapse
Affiliation(s)
- Ximing Guo
- Haskin Shellfish Research Laboratory, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA.
| | - Jonathan B Puritz
- Department of Biological Sciences, University of Rhode Island, 120 Flagg Road, Kingston, RI, 02881, USA
| | - Zhenwei Wang
- Haskin Shellfish Research Laboratory, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA
| | - Dina Proestou
- USDA ARS NCWMAC Shellfish Genetics Lab, 120 Flagg Rd., Kingston, RI, 02881, USA
| | - Standish Allen
- Virginia Institute of Marine Science, 1375 Greate Rd., Gloucester Pt., VA, 23062, USA
| | - Jessica Small
- Virginia Institute of Marine Science, 1375 Greate Rd., Gloucester Pt., VA, 23062, USA
| | | | - Honggang Zhao
- Department of Natural Resources and the Environment, Cornell University, Ithaca, NY, 14853, USA
| | - Jaime Haggard
- Haskin Shellfish Research Laboratory, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA
| | - Noah Chriss
- Haskin Shellfish Research Laboratory, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA
| | - Dan Zeng
- Haskin Shellfish Research Laboratory, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA
| | - Kathryn Lundgren
- USDA ARS NCWMAC Shellfish Genetics Lab, 120 Flagg Rd., Kingston, RI, 02881, USA
| | - Bassem Allam
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, 11794, USA
| | - David Bushek
- Haskin Shellfish Research Laboratory, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA
| | - Marta Gomez-Chiarri
- Department of Fisheries, Animal and Veterinary Science, University of Rhode Island, 120 Flagg Road, Kingston, RI, 02881, USA
| | - Matthew Hare
- Department of Natural Resources and the Environment, Cornell University, Ithaca, NY, 14853, USA
| | - Christopher Hollenbeck
- Texas A&M University - Corpus Christi, Texas A&M AgriLife Research, 6300 Ocean Drive Unit 5892, Corpus Christi, TX, 78412, USA
| | - Jerome La Peyre
- School of Animal Sciences, Louisiana State University Agricultural Center, 201 Animal and Food Sciences Laboratory Building, Forestry Lane, Baton Rouge, LA, 70803, USA
| | - Ming Liu
- Patuxent Environmental and Aquatic Research Laboratory, Morgan State University, 10545 Mackall Road, Saint Leonard, MD, 20685, USA
| | - Katie E Lotterhos
- Northeastern Marine Science Center, 430 Nahant Rd, Nahant, MA, 01908, USA
| | - Louis Plough
- Horn Point Lab, University of Maryland, 5745 Lovers Lane, Cambridge, MD, 21613, USA
| | - Paul Rawson
- School of Marine Sciences, University of Maine, 5751 Murray Hall, , Orono, ME, 04469, USA
| | - Scott Rikard
- School of Fisheries Aquaculture and Aquatic Sciences, Auburn University Shellfish Laboratory, Auburn University, 150 Agassiz St., Dauphin Island, AL, 36528, USA
| | - Eric Saillant
- School of Ocean Science and Engineering, The University of Southern Mississippi, 103 McIlwain Drive, Ocean Springs, MS, 39564, USA
| | - Robin Varney
- Shellfish Research Hatchery, University of North Carolina Wilmington, 5600 Marvin K. Moss Ln., Wilmington, NC, 28409, USA
| | - Gary Wikfors
- Milford CT Laboratory, NOAA Fisheries, 212 Rogers Avenue, Milford, CT, 06460, USA
| | - Ami Wilbur
- Shellfish Research Hatchery, University of North Carolina Wilmington, 5600 Marvin K. Moss Ln., Wilmington, NC, 28409, USA
| |
Collapse
|
5
|
Wang H, Su B, Butts IAE, Dunham RA, Wang X. Chromosome-level assembly and annotation of the blue catfish Ictalurus furcatus, an aquaculture species for hybrid catfish reproduction, epigenetics, and heterosis studies. Gigascience 2022; 11:6636942. [PMID: 35809049 PMCID: PMC9270728 DOI: 10.1093/gigascience/giac070] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 05/24/2022] [Accepted: 06/16/2022] [Indexed: 12/17/2022] Open
Abstract
Background The blue catfish is of great value in aquaculture and recreational fisheries. The F1 hybrids of female channel catfish (Ictalurus punctatus) × male blue catfish (Ictalurusfurcatus) have been the primary driver of US catfish production in recent years because of superior growth, survival, and carcass yield. The channel–blue hybrid also provides an excellent model to investigate molecular mechanisms of environment-dependent heterosis. However, transcriptome and methylome studies suffered from low alignment rates to the channel catfish genome due to divergence, and the genome resources for blue catfish are not publicly available. Results The blue catfish genome assembly is 841.86 Mbp in length with excellent continuity (8.6 Mbp contig N50, 28.2 Mbp scaffold N50) and completeness (98.6% Eukaryota and 97.0% Actinopterygii BUSCO). A total of 30,971 protein-coding genes were predicted, of which 21,781 were supported by RNA sequencing evidence. Phylogenomic analyses revealed that it diverged from channel catfish approximately 9 million years ago with 15.7 million fixed nucleotide differences. The within-species single-nucleotide polymorphism (SNP) density is 0.32% between the most aquaculturally important blue catfish strains (D&B and Rio Grande). Gene family analysis discovered significant expansion of immune-related families in the blue catfish lineage, which may contribute to disease resistance in blue catfish. Conclusions We reported the first high-quality, chromosome-level assembly of the blue catfish genome, which provides the necessary genomic tool kit for transcriptome and methylome analysis, SNP discovery and marker-assisted selection, gene editing and genome engineering, and reproductive enhancement of the blue catfish and hybrid catfish.
Collapse
Affiliation(s)
- Haolong Wang
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL 36849, USA.,Alabama Agricultural Experiment Station, Auburn, AL 36849, USA
| | - Baofeng Su
- Alabama Agricultural Experiment Station, Auburn, AL 36849, USA.,School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL 36849, USA
| | - Ian A E Butts
- Alabama Agricultural Experiment Station, Auburn, AL 36849, USA.,School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL 36849, USA
| | - Rex A Dunham
- Alabama Agricultural Experiment Station, Auburn, AL 36849, USA.,School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL 36849, USA
| | - Xu Wang
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL 36849, USA.,Alabama Agricultural Experiment Station, Auburn, AL 36849, USA.,HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| |
Collapse
|
6
|
Neumann GB, Korkuć P, Arends D, Wolf MJ, May K, Reißmann M, Elzaki S, König S, Brockmann GA. Design and performance of a bovine 200 k SNP chip developed for endangered German Black Pied cattle (DSN). BMC Genomics 2021; 22:905. [PMID: 34922441 PMCID: PMC8684242 DOI: 10.1186/s12864-021-08237-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 12/03/2021] [Indexed: 08/26/2023] Open
Abstract
BACKGROUND German Black Pied cattle (DSN) are an endangered dual-purpose breed which was largely replaced by Holstein cattle due to their lower milk yield. DSN cattle are kept as a genetic reserve with a current herd size of around 2500 animals. The ability to track sequence variants specific to DSN could help to support the conservation of DSN's genetic diversity and to provide avenues for genetic improvement. RESULTS Whole-genome sequencing data of 304 DSN cattle were used to design a customized DSN200k SNP chip harboring 182,154 variants (173,569 SNPs and 8585 indels) based on ten selection categories. We included variants of interest to DSN such as DSN unique variants and variants from previous association studies in DSN, but also variants of general interest such as variants with predicted consequences of high, moderate, or low impact on the transcripts and SNPs from the Illumina BovineSNP50 BeadChip. Further, the selection of variants based on haplotype blocks ensured that the whole-genome was uniformly covered with an average variant distance of 14.4 kb on autosomes. Using 300 DSN and 162 animals from other cattle breeds including Holstein, endangered local cattle populations, and also a Bos indicus breed, performance of the SNP chip was evaluated. Altogether, 171,978 (94.31%) of the variants were successfully called in at least one of the analyzed breeds. In DSN, the number of successfully called variants was 166,563 (91.44%) while 156,684 (86.02%) were segregating at a minor allele frequency > 1%. The concordance rate between technical replicates was 99.83 ± 0.19%. CONCLUSION The DSN200k SNP chip was proved useful for DSN and other Bos taurus as well as one Bos indicus breed. It is suitable for genetic diversity management and marker-assisted selection of DSN animals. Moreover, variants that were segregating in other breeds can be used for the design of breed-specific customized SNP chips. This will be of great value in the application of conservation programs for endangered local populations in the future.
Collapse
Affiliation(s)
- Guilherme B Neumann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany
| | - Paula Korkuć
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany
| | - Danny Arends
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany
| | - Manuel J Wolf
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Gießen, Germany
| | - Katharina May
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Gießen, Germany
| | - Monika Reißmann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany
| | - Salma Elzaki
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.,Department of Genetics and Animal Breeding, Faculty of Animal Production, University of Khartoum, Khartoum North, Sudan
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-Universität, Gießen, Germany
| | - Gudrun A Brockmann
- Animal Breeding Biology and Molecular Genetics, Albrecht Daniel Thaer-Institute for Agricultural and Horticultural Sciences, Humboldt Universität zu Berlin, Berlin, Germany.
| |
Collapse
|
7
|
Development of a multi-species SNP array for serrasalmid fish Colossoma macropomum and Piaractus mesopotamicus. Sci Rep 2021; 11:19289. [PMID: 34588599 PMCID: PMC8481427 DOI: 10.1038/s41598-021-98885-x] [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: 01/26/2021] [Accepted: 09/09/2021] [Indexed: 11/13/2022] Open
Abstract
Scarce genomic resources have limited the development of breeding programs for serrasalmid fish Colossoma macropomum (tambaqui) and Piaractus mesopotamicus (pacu), the key native freshwater fish species produced in South America. The main objectives of this study were to design a dense SNP array for this fish group and to validate its performance on farmed populations from several locations in South America. Using multiple approaches based on different populations of tambaqui and pacu, a final list of 29,575 and 29,612 putative SNPs was selected, respectively, to print an Axiom AFFYMETRIX (THERMOFISHER) SerraSNP array. After validation, 74.17% (n = 21,963) and 71.25% (n = 21,072) of SNPs were classified as polymorphic variants in pacu and tambaqui, respectively. Most of the SNPs segregated within each population ranging from 14,199 to 19,856 in pacu; and from 15,075 to 20,380 in tambaqui. Our results indicate high levels of genetic diversity and clustered samples according to their hatchery origin. The developed SerraSNP array represents a valuable genomic tool approaching in-depth genetic studies for these species.
Collapse
|
8
|
Zhou Z, Wang M, Yang J, Liu B, Li L, Shi Y, Pu F, Xu P. Genome-wide association analysis reveals genetic variations and candidate genes associated with growth-related traits and condition factor in Takifugu bimaculatus. REPRODUCTION AND BREEDING 2021. [DOI: 10.1016/j.repbre.2021.05.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
|
9
|
Peñaloza C, Manousaki T, Franch R, Tsakogiannis A, Sonesson AK, Aslam ML, Allal F, Bargelloni L, Houston RD, Tsigenopoulos CS. Development and testing of a combined species SNP array for the European seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata). Genomics 2021; 113:2096-2107. [PMID: 33933591 PMCID: PMC8276775 DOI: 10.1016/j.ygeno.2021.04.038] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 03/30/2021] [Accepted: 04/27/2021] [Indexed: 12/23/2022]
Abstract
SNP arrays are powerful tools for high-resolution studies of the genetic basis of complex traits, facilitating both selective breeding and population genomic research. The European seabass (Dicentrarchus labrax) and the gilthead seabream (Sparus aurata) are the two most important fish species for Mediterranean aquaculture. While selective breeding programmes increasingly underpin stock supply for this industry, genomic selection is not yet widespread. Genomic selection has major potential to expedite genetic gain, particularly for traits practically impossible to measure on selection candidates, such as disease resistance and fillet characteristics. The aim of our study was to design a combined-species 60 K SNP array for European seabass and gilthead seabream, and to test its performance on farmed and wild populations from numerous locations throughout the species range. To achieve this, high coverage Illumina whole-genome sequencing of pooled samples was performed for 24 populations of European seabass and 27 populations of gilthead seabream. This resulted in a database of ~20 million SNPs per species, which were then filtered to identify high-quality variants and create the final set for the development of the ‘MedFish’ SNP array. The array was then tested by genotyping a subset of the discovery populations, highlighting a high conversion rate to functioning polymorphic assays on the array (92% in seabass; 89% in seabream) and repeatability (99.4–99.7%). The platform interrogates ~30 K markers in each species, includes features such as SNPs previously shown to be associated with performance traits, and is enriched for SNPs predicted to have high functional effects on proteins. The array was demonstrated to be effective at detecting population structure across a wide range of fish populations from diverse geographical origins, and to examine the extent of haplotype sharing among Mediterranean farmed fish populations. In conclusion, the new MedFish array enables efficient and accurate high-throughput genotyping for genome-wide distributed SNPs for each fish species, and will facilitate stock management, population genomics approaches, and acceleration of selective breeding through genomic selection. Α 60 K SNP array (MedFish) was designed for European seabass and gilthead seabream from wild and domesticated populations. The array exhibited a high conversion rate (92% in seabass; 89% in seabream) and repeatability (99.4 and 99.7%). The MedFish array is expected to facilitate stock management and acceleration of selective breeding via genomic selection.
Collapse
Affiliation(s)
- C Peñaloza
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, UK
| | - T Manousaki
- Hellenic Centre for Marine Research, Thalassocosmos Gournes Pediados, 71500 Irakleio, Crete, Greece
| | - R Franch
- Padova University, Via Ugo Bassi, 58yB, I-35131 Padova, Italy
| | - A Tsakogiannis
- Hellenic Centre for Marine Research, Thalassocosmos Gournes Pediados, 71500 Irakleio, Crete, Greece
| | - A K Sonesson
- Nofima, Norwegian Institute of Food, Fisheries and Aquaculture Research, PO Box 210, N-1432 Ås, Norway
| | - M L Aslam
- Nofima, Norwegian Institute of Food, Fisheries and Aquaculture Research, PO Box 210, N-1432 Ås, Norway
| | - F Allal
- MARBEC, University of Montpellier, Ifremer, CNRS, IRD, 34250 Palavas-les-Flots, France
| | - L Bargelloni
- Padova University, Via Ugo Bassi, 58yB, I-35131 Padova, Italy
| | - R D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, UK.
| | - C S Tsigenopoulos
- Hellenic Centre for Marine Research, Thalassocosmos Gournes Pediados, 71500 Irakleio, Crete, Greece.
| |
Collapse
|
10
|
Lu S, Zhou Q, Chen Y, Liu Y, Li Y, Wang L, Yang Y, Chen S. Development of a 38 K single nucleotide polymorphism array and application in genomic selection for resistance against Vibrio harveyi in Chinese tongue sole, Cynoglossus semilaevis. Genomics 2021; 113:1838-1844. [PMID: 33819565 DOI: 10.1016/j.ygeno.2021.03.034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 02/20/2021] [Accepted: 03/31/2021] [Indexed: 11/17/2022]
Abstract
Based on 1572 re-sequenced Chinese tongue sole (Cynoglossus semilaevis), we investigated the accuracy of four genomic methods at predicting genomic estimated breeding values (GEBVs) of Vibrio harveyi resistance in C. semilaevis when SNPs varying from 500 to 500 k. All methods outperformed the pedigree-based best linear unbiased prediction when SNPs reached 50 k or more. Then, we developed an SNP array "Solechip No.1" for C. semilaevis breeding using the Affymetrix Axiom technology. This array contains 38,295 SNPs with an average of 10.5 kb inter-spacing between two adjacent SNPs. We selected 44 candidates as the parents of 23 families and genotyped them by the array. The challenge survival rates of offspring families had a correlation of 0.706 with the mid-parental GEBVs. This SNP array is a convenient and reliable tool in genotyping, which could be used for improving V. harveyi resistance in C. semilaevis coupled with the genomic selection methods.
Collapse
Affiliation(s)
- Sheng Lu
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Wuxi Fisheries College, Nanjing Agricultural University, 214081 Wuxi, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China
| | - Qian Zhou
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China
| | - Yadong Chen
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China
| | - Yang Liu
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China
| | - Yangzhen Li
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China
| | - Lei Wang
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China
| | - Yingming Yang
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China
| | - Songlin Chen
- Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Key Laboratory for Sustainable Development of Marine Fisheries, Ministry of Agriculture, 266071 Qingdao, China; Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266373, China; Shandong Key Laboratory of Marine Fisheries Biotechnology and Genetic Breeding, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, 266071 Qingdao, China.
| |
Collapse
|
11
|
Yoshikawa S, Hamasaki M, Kadomura K, Yamada T, Chuda H, Kikuchi K, Hosoya S. Genetic Dissection of a Precocious Phenotype in Male Tiger Pufferfish (Takifugu rubripes) using Genotyping by Random Amplicon Sequencing, Direct (GRAS-Di). MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2021; 23:177-188. [PMID: 33599909 PMCID: PMC8032607 DOI: 10.1007/s10126-020-10013-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 12/21/2020] [Indexed: 06/12/2023]
Abstract
The novel non-targeted PCR-based genotyping system, namely Genotyping by Random Amplicon Sequencing, Direct (GRAS-Di), is characterized by the simplicity in library construction and robustness against DNA degradation and is expected to facilitate advancements in genetics, in both basic and applied sciences. In this study, we tested the utility of GRAS-Di for genetic analysis in a cultured population of the tiger pufferfish Takifugu rubripes. The genetic analyses included family structure analysis, genetic map construction, and quantitative trait locus (QTL) analysis for the male precocious phenotype using a population consisting of four full-sib families derived from a genetically precocious line. An average of 4.7 million raw reads were obtained from 198 fish. Trimmed reads were mapped onto a Fugu reference genome for genotyping, and 21,938 putative single-nucleotide polymorphisms (SNPs) were obtained. These 22 K SNPs accurately resolved the sibship and parent-offspring pairs. A fine-scale linkage map (total size: 1,949 cM; average interval: 1.75 cM) was constructed from 1,423 effective SNPs, for which the allele inheritance patterns were known. QTL analysis detected a significant locus for testes weight on Chr_14 and three suggestive loci on Chr_1, Chr_8, and Chr_19. The significant QTL was shared by body length and body weight. The effect of each QTL was small (phenotypic variation explained, PVE: 3.1-5.9%), suggesting that the precociousness seen in the cultured pufferfish is polygenic. Taken together, these results indicate that GRAS-Di is a practical genotyping tool for aquaculture species and applicable for molecular breeding programs, such as marker-assisted selection and genomic selection.
Collapse
Affiliation(s)
- Sota Yoshikawa
- Nagasaki Prefectural Institute of Fisheries, Nagasaki, Japan
- Fisheries Laboratory, Graduate School of Agricultural and Life Sciences, University of Tokyo, Shizuoka, Japan
| | | | | | | | - Hisashi Chuda
- Aquaculture Research Institute, Kindai University, Wakayama, Japan
| | - Kiyoshi Kikuchi
- Fisheries Laboratory, Graduate School of Agricultural and Life Sciences, University of Tokyo, Shizuoka, Japan
| | - Sho Hosoya
- Fisheries Laboratory, Graduate School of Agricultural and Life Sciences, University of Tokyo, Shizuoka, Japan.
| |
Collapse
|
12
|
Dadshani S, Mathew B, Ballvora A, Mason AS, Léon J. Detection of breeding signatures in wheat using a linkage disequilibrium-corrected mapping approach. Sci Rep 2021; 11:5527. [PMID: 33750919 PMCID: PMC7970893 DOI: 10.1038/s41598-021-85226-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/25/2021] [Indexed: 01/31/2023] Open
Abstract
Marker assisted breeding, facilitated by reference genome assemblies, can help to produce cultivars adapted to changing environmental conditions. However, anomalous linkage disequilibrium (LD), where single markers show high LD with markers on other chromosomes but low LD with adjacent markers, is a serious impediment for genetic studies. We used a LD-correction approach to overcome these drawbacks, correcting the physical position of markers derived from 15 and 135 K arrays in a diversity panel of bread wheat representing 50 years of breeding history. We detected putative mismapping of 11.7% markers and improved the physical alignment of 5.4% markers. Population analysis indicated reduced genetic diversity over time as a result of breeding efforts. By analysis of outlier loci and allele frequency change over time we traced back the 2NS/2AS translocation of Aegilops ventricosa to one cultivar, "Cardos" (registered in 1998) which was the first among the panel to contain this translocation. A "selective sweep" for this important translocation region on chromosome 2AS was found, putatively linked to plant response to biotic stress factors. Our approach helps in overcoming the drawbacks of incorrectly anchored markers on the wheat reference assembly and facilitates detection of selective sweeps for important agronomic traits.
Collapse
Affiliation(s)
- Said Dadshani
- Institute of Crop Science and Resource Conservation (INRES), Plant Breeding, University of Bonn, Bonn, Germany.
| | - Boby Mathew
- Bayer CropScience, Monheim am Rhein, Germany
| | - Agim Ballvora
- Institute of Crop Science and Resource Conservation (INRES), Plant Breeding, University of Bonn, Bonn, Germany
| | - Annaliese S Mason
- Institute of Crop Science and Resource Conservation (INRES), Plant Breeding, University of Bonn, Bonn, Germany
| | - Jens Léon
- Institute of Crop Science and Resource Conservation (INRES), Plant Breeding, University of Bonn, Bonn, Germany.
| |
Collapse
|
13
|
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
|
14
|
Development and validation of a RAD-Seq target-capture based genotyping assay for routine application in advanced black tiger shrimp (Penaeus monodon) breeding programs. BMC Genomics 2020; 21:541. [PMID: 32758142 PMCID: PMC7430818 DOI: 10.1186/s12864-020-06960-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 07/29/2020] [Indexed: 11/26/2022] Open
Abstract
Background The development of genome-wide genotyping resources has provided terrestrial livestock and crop industries with the unique ability to accurately assess genomic relationships between individuals, uncover the genetic architecture of commercial traits, as well as identify superior individuals for selection based on their specific genetic profile. Utilising recent advancements in de-novo genome-wide genotyping technologies, it is now possible to provide aquaculture industries with these same important genotyping resources, even in the absence of existing genome assemblies. Here, we present the development of a genome-wide SNP assay for the Black Tiger shrimp (Penaeus monodon) through utilisation of a reduced-representation whole-genome genotyping approach (DArTseq). Results Based on a single reduced-representation library, 31,262 polymorphic SNPs were identified across 650 individuals obtained from Australian wild stocks and commercial aquaculture populations. After filtering to remove SNPs with low read depth, low MAF, low call rate, deviation from HWE, and non-Mendelian inheritance, 7542 high-quality SNPs were retained. From these, 4236 high-quality genome-wide loci were selected for baits-probe development and 4194 SNPs were included within a finalized target-capture genotype-by-sequence assay (DArTcap). This assay was designed for routine and cost effective commercial application in large scale breeding programs, and demonstrates higher confidence in genotype calls through increased call rate (from 80.2 ± 14.7 to 93.0% ± 3.5%), increased read depth (from 20.4 ± 15.6 to 80.0 ± 88.7), as well as a 3-fold reduction in cost over traditional genotype-by-sequencing approaches. Conclusion Importantly, this assay equips the P. monodon industry with the ability to simultaneously assign parentage of communally reared animals, undertake genomic relationship analysis, manage mate pairings between cryptic family lines, as well as undertake advance studies of genome and trait architecture. Critically this assay can be cost effectively applied as P. monodon breeding programs transition to undertaking genomic selection.
Collapse
|
15
|
Development and Validation of an Open Access SNP Array for Nile Tilapia ( Oreochromis niloticus). G3-GENES GENOMES GENETICS 2020; 10:2777-2785. [PMID: 32532799 PMCID: PMC7407453 DOI: 10.1534/g3.120.401343] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Tilapia are among the most important farmed fish species worldwide, and are fundamental for the food security of many developing countries. Several genetically improved Nile tilapia (Oreochromis niloticus) strains exist, such as the iconic Genetically Improved Farmed Tilapia (GIFT), and breeding programs typically follow classical pedigree-based selection. The use of genome-wide single-nucleotide polymorphism (SNP) data can enable an understanding of the genetic architecture of economically important traits and the acceleration of genetic gain via genomic selection. Due to the global importance and diversity of Nile tilapia, an open access SNP array would be beneficial for aquaculture research and production. In the current study, a ∼65K SNP array was designed based on SNPs discovered from whole-genome sequence data from a GIFT breeding nucleus population and the overlap with SNP datasets from wild fish populations and several other farmed Nile tilapia strains. The SNP array was applied to clearly distinguish between different tilapia populations across Asia and Africa, with at least ∼30,000 SNPs segregating in each of the diverse population samples tested. It is anticipated that this SNP array will be an enabling tool for population genetics and tilapia breeding research, facilitating consistency and comparison of results across studies.
Collapse
|
16
|
Jones JC, Du ZG, Bernstein R, Meyer M, Hoppe A, Schilling E, Ableitner M, Juling K, Dick R, Strauss AS, Bienefeld K. Tool for genomic selection and breeding to evolutionary adaptation: Development of a 100K single nucleotide polymorphism array for the honey bee. Ecol Evol 2020; 10:6246-6256. [PMID: 32724511 PMCID: PMC7381592 DOI: 10.1002/ece3.6357] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 04/19/2020] [Accepted: 04/20/2020] [Indexed: 01/03/2023] Open
Abstract
High-throughput high-density genotyping arrays continue to be a fast, accurate, and cost-effective method for genotyping thousands of polymorphisms in high numbers of individuals. Here, we have developed a new high-density SNP genotyping array (103,270 SNPs) for honey bees, one of the most ecologically and economically important pollinators worldwide. SNPs were detected by conducting whole-genome resequencing of 61 honey bee drones (haploid males) from throughout Europe. Selection of SNPs for the chip was done in multiple steps using several criteria. The majority of SNPs were selected based on their location within known candidate regions or genes underlying a range of honey bee traits, including hygienic behavior against pathogens, foraging, and subspecies. Additionally, markers from a GWAS of hygienic behavior against the major honey bee parasite Varroa destructor were brought over. The chip also includes SNPs associated with each of three major breeding objectives-honey yield, gentleness, and Varroa resistance. We validated the chip and make recommendations for its use by determining error rates in repeat genotypings, examining the genotyping performance of different tissues, and by testing how well different sample types represent the queen's genotype. The latter is a key test because it is highly beneficial to be able to determine the queen's genotype by nonlethal means. The array is now publicly available and we suggest it will be a useful tool in genomic selection and honey bee breeding, as well as for GWAS of different traits, and for population genomic, adaptation, and conservation questions.
Collapse
Affiliation(s)
- Julia C. Jones
- Institute for Bee ResearchHohen NeuendorfGermany
- School of Biology and Environmental ScienceUniversity College DublinDublinIreland
| | - Zhipei G. Du
- Institute for Bee ResearchHohen NeuendorfGermany
| | | | | | | | | | | | | | | | | | | |
Collapse
|
17
|
Gutierrez AP, Symonds J, King N, Steiner K, Bean TP, Houston RD. Potential of genomic selection for improvement of resistance to ostreid herpesvirus in Pacific oyster (Crassostrea gigas). Anim Genet 2020; 51:249-257. [PMID: 31999002 DOI: 10.1111/age.12909] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/20/2019] [Indexed: 01/15/2023]
Abstract
In genomic selection (GS), genome-wide SNP markers are used to generate genomic estimated breeding values for selection candidates. The application of GS in shellfish looks promising and has the potential to help in dealing with one of the main issues currently affecting Pacific oyster production worldwide, which is the 'summer mortality syndrome'. This causes periodic mass mortality in farms worldwide and has mainly been attributed to a specific variant of the ostreid herpesvirus (OsHV-1). In the current study, we evaluated the potential of genomic selection for host resistance to OsHV-1 in Pacific oysters, and compared it with pedigree-based approaches. An OsHV-1 disease challenge was performed using an immersion-based virus exposure treatment for oysters for 7 days. A total of 768 samples were genotyped using the medium-density SNP array for oysters. A GWAS was performed for the survival trait using a GBLUP approach in blupf90 software. Heritability ranged from 0.25 ± 0.05 to 0.37 ± 0.05 (mean ± SE) based on pedigree and genomic information respectively. Genomic prediction was more accurate than pedigree prediction, and SNP density reduction had little impact on prediction accuracy until marker densities dropped below approximately 500 SNPs. This demonstrates the potential for GS in Pacific oyster breeding programmes, and importantly, demonstrates that a low number of SNPs might suffice to obtain accurate genomic estimated breeding values, thus potentially making the implementation of GS more cost effective.
Collapse
Affiliation(s)
- A P Gutierrez
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
| | - J Symonds
- Cawthron Institute, 98 Halifax Street East, Nelson, 7010, New Zealand
| | - N King
- Cawthron Institute, 98 Halifax Street East, Nelson, 7010, New Zealand
| | - K Steiner
- Cawthron Institute, 98 Halifax Street East, Nelson, 7010, New Zealand
| | - T P Bean
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
| | - R D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK
| |
Collapse
|
18
|
Yáñez JM, Yoshida G, Barria A, Palma-Véjares R, Travisany D, Díaz D, Cáceres G, Cádiz MI, López ME, Lhorente JP, Jedlicki A, Soto J, Salas D, Maass A. High-Throughput Single Nucleotide Polymorphism (SNP) Discovery and Validation Through Whole-Genome Resequencing in Nile Tilapia (Oreochromis niloticus). MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2020; 22:109-117. [PMID: 31938972 DOI: 10.1007/s10126-019-09935-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Accepted: 11/19/2019] [Indexed: 06/10/2023]
Abstract
Nile tilapia (Oreochromis niloticus) is the second most important farmed fish in the world and a sustainable source of protein for human consumption. Several genetic improvement programs have been established for this species in the world. Currently, the estimation of genetic merit of breeders is typically based on genealogical and phenotypic information. Genome-wide information can be exploited to efficiently incorporate traits that are difficult to measure into the breeding goal. Thus, single nucleotide polymorphisms (SNPs) are required to investigate phenotype-genotype associations and determine the genomic basis of economically important traits. We performed de novo SNP discovery in three different populations of farmed Nile tilapia. A total of 29.9 million non-redundant SNPs were identified through Illumina (HiSeq 2500) whole-genome resequencing of 326 individual samples. After applying several filtering steps, including removing SNP based on genotype and site quality, presence of Mendelian errors, and non-unique position in the genome, a total of 50,000 high-quality SNPs were selected for the development of a custom Illumina BeadChip SNP panel. These SNPs were highly informative in the three populations analyzed showing between 43,869 (94%) and 46,139 (99%) SNPs in Hardy-Weinberg Equilibrium; 37,843 (76%) and 45,171(90%) SNPs with a minor allele frequency (MAF) higher than 0.05; and 43,450 (87%) and 46,570 (93%) SNPs with a MAF higher than 0.01. The 50K SNP panel developed in the current work will be useful for the dissection of economically relevant traits, enhancing breeding programs through genomic selection, as well as supporting genetic studies in farmed populations of Nile tilapia using dense genome-wide information.
Collapse
Affiliation(s)
- José M Yáñez
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile.
- Núcleo Milenio INVASAL, Concepción, Chile.
| | - Grazyella Yoshida
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
- Benchmark Genetics Chile, Puerto Montt, Chile
| | - Agustín Barria
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
| | - Ricardo Palma-Véjares
- Centro para la Regulación del Genoma, Universidad de Chile, Santiago, Chile
- Centro de Modelamiento Matemático UMI CNRS 2807, Universidad de Chile, Santiago, Chile
| | - Dante Travisany
- Centro para la Regulación del Genoma, Universidad de Chile, Santiago, Chile
- Centro de Modelamiento Matemático UMI CNRS 2807, Universidad de Chile, Santiago, Chile
| | - Diego Díaz
- Centro para la Regulación del Genoma, Universidad de Chile, Santiago, Chile
- Centro de Modelamiento Matemático UMI CNRS 2807, Universidad de Chile, Santiago, Chile
| | - Giovanna Cáceres
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - María I Cádiz
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - María E López
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | | | - Ana Jedlicki
- Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - José Soto
- Grupo Acuacorporacion, Internacional (GACI), Cañas, Costa Rica
| | - Diego Salas
- Grupo Acuacorporacion, Internacional (GACI), Cañas, Costa Rica
| | - Alejandro Maass
- Centro para la Regulación del Genoma, Universidad de Chile, Santiago, Chile
- Centro de Modelamiento Matemático UMI CNRS 2807, Universidad de Chile, Santiago, Chile
| |
Collapse
|
19
|
Howe GT, Jayawickrama K, Kolpak SE, Kling J, Trappe M, Hipkins V, Ye T, Guida S, Cronn R, Cushman SA, McEvoy S. An Axiom SNP genotyping array for Douglas-fir. BMC Genomics 2020; 21:9. [PMID: 31900111 PMCID: PMC6942338 DOI: 10.1186/s12864-019-6383-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 12/10/2019] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND In forest trees, genetic markers have been used to understand the genetic architecture of natural populations, identify quantitative trait loci, infer gene function, and enhance tree breeding. Recently, new, efficient technologies for genotyping thousands to millions of single nucleotide polymorphisms (SNPs) have finally made large-scale use of genetic markers widely available. These methods will be exceedingly valuable for improving tree breeding and understanding the ecological genetics of Douglas-fir, one of the most economically and ecologically important trees in the world. RESULTS We designed SNP assays for 55,766 potential SNPs that were discovered from previous transcriptome sequencing projects. We tested the array on ~ 2300 related and unrelated coastal Douglas-fir trees (Pseudotsuga menziesii var. menziesii) from Oregon and Washington, and 13 trees of interior Douglas-fir (P. menziesii var. glauca). As many as ~ 28 K SNPs were reliably genotyped and polymorphic, depending on the selected SNP call rate. To increase the number of SNPs and improve genome coverage, we developed protocols to 'rescue' SNPs that did not pass the default Affymetrix quality control criteria (e.g., 97% SNP call rate). Lowering the SNP call rate threshold from 97 to 60% increased the number of successful SNPs from 20,669 to 28,094. We used a subset of 395 unrelated trees to calculate SNP population genetic statistics for coastal Douglas-fir. Over a range of call rate thresholds (97 to 60%), the median call rate for SNPs in Hardy-Weinberg equilibrium ranged from 99.2 to 99.7%, and the median minor allele frequency ranged from 0.198 to 0.233. The successful SNPs also worked well on interior Douglas-fir. CONCLUSIONS Based on the original transcriptome assemblies and comparisons to version 1.0 of the Douglas-fir reference genome, we conclude that these SNPs can be used to genotype about 10 K to 15 K loci. The Axiom genotyping array will serve as an excellent foundation for studying the population genomics of Douglas-fir and for implementing genomic selection. We are currently using the array to construct a linkage map and test genomic selection in a three-generation breeding program for coastal Douglas-fir.
Collapse
Affiliation(s)
- Glenn T Howe
- Pacific Northwest Tree Improvement Research Cooperative, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA.
| | - Keith Jayawickrama
- Northwest Tree Improvement Cooperative, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA
| | - Scott E Kolpak
- Pacific Northwest Tree Improvement Research Cooperative, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA
| | - Jennifer Kling
- Pacific Northwest Tree Improvement Research Cooperative, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA
| | - Matt Trappe
- Northwest Tree Improvement Cooperative, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA
| | - Valerie Hipkins
- USDA Forest Service, National Forest Genetics Laboratory, Placerville, CA, USA
| | - Terrance Ye
- Northwest Tree Improvement Cooperative, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA
| | | | - Richard Cronn
- USDA Forest Service, Pacific Northwest Research Station, Corvallis, OR, USA
| | - Samuel A Cushman
- USDA Forest Service, Rocky Mountain Research Station, Flagstaff, AZ, USA
| | - Susan McEvoy
- Pacific Northwest Tree Improvement Research Cooperative, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA
| |
Collapse
|
20
|
Wang W, Tan S, Luo J, Shi H, Zhou T, Yang Y, Jin Y, Wang X, Niu D, Yuan Z, Gao D, Dunham R, Liu Z. GWAS Analysis Indicated Importance of NF-κB Signaling Pathway in Host Resistance Against Motile Aeromonas Septicemia Disease in Catfish. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2019; 21:335-347. [PMID: 30895402 DOI: 10.1007/s10126-019-09883-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 02/18/2019] [Indexed: 06/09/2023]
Abstract
Motile Aeromonas septicemia (MAS) disease caused by a bacterial pathogen, Aeromonas hydrophila, is an emerging but severe disease of catfish. Genetic enhancement of disease resistance is considered to be effective to control the disease. To provide an insight into the genomic basis of MAS disease resistance, in this study, we conducted a genome-wide association study (GWAS) to identify quantitative trait loci (QTL). A total of 1820 interspecific backcross catfish of 7 families were challenged with A. hydrophila, and 382 phenotypic extremes were selected for genotyping with the catfish 690 K SNP arrays. Three QTL on linkage group (LG) 2, 26 and 29 were identified to be significantly associated with MAS resistance. Within these regions, a total of 24 genes had known functions in immunity, 10 of which were involved in NF-κB signaling pathway, suggesting the importance of NF-κB signaling pathway in MAS resistance. In addition, three suggestively significant QTL were identified on LG 11, 17, and 20. The limited numbers of QTL involved in MAS resistance suggests that marker-assisted selection may be a viable approach for catfish breeding.
Collapse
Affiliation(s)
- Wenwen Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Suxu Tan
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Jian Luo
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Huitong Shi
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yujia Yang
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yulin Jin
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaozhu Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Donghong Niu
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zihao Yuan
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Dongya Gao
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Rex Dunham
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zhanjiang Liu
- Department of Biology, College of Art and Sciences, Syracuse University, Syracuse, NY, 13244, USA.
| |
Collapse
|
21
|
Nugent CM, Leong JS, Christensen KA, Rondeau EB, Brachmann MK, Easton AA, Ouellet-Fagg CL, Crown MTT, Davidson WS, Koop BF, Danzmann RG, Ferguson MM. Design and characterization of an 87k SNP genotyping array for Arctic charr (Salvelinus alpinus). PLoS One 2019; 14:e0215008. [PMID: 30951561 PMCID: PMC6450613 DOI: 10.1371/journal.pone.0215008] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 03/25/2019] [Indexed: 11/21/2022] Open
Abstract
We have generated a high-density, high-throughput genotyping array for characterizing genome-wide variation in Arctic charr (Salvelinus alpinus). Novel single nucleotide polymorphisms (SNPs) were identified in charr from the Fraser, Nauyuk and Tree River aquaculture strains, which originated from northern Canada and fish from Iceland using high coverage sequencing, reduced representation sequencing and RNA-seq datasets. The array was designed to capture genome-wide variation from a diverse suite of Arctic charr populations. Cross validation of SNPs from various sources and comparison with previously published Arctic charr SNP data provided a set of candidate SNPs that generalize across populations. Further candidate SNPs were identified based on minor allele frequency, association with RNA transcripts, even spacing across intergenic regions and association with the sex determining (sdY) gene. The performance of the 86,503 SNP array was assessed by genotyping Fraser, Nauyuk and Tree River strain individuals, as well as wild Icelandic Arctic charr. Overall, 63,060 of the SNPs were polymorphic within at least one group and 36.8% were unique to one of the four groups, suggesting that the array design allows for characterization of both within and across population genetic diversity. The concordance between sdY markers and known phenotypic sex indicated that the array can accurately determine the sex of individuals based on genotype alone. The Salp87k genotyping array provides researchers and breeders the opportunity to analyze genetic variation in Arctic charr at a more detailed level than previously possible.
Collapse
Affiliation(s)
- Cameron M. Nugent
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | - Jong S. Leong
- University of Victoria, Department of Biology, Victoria, British Columbia, Canada
| | - Kris A. Christensen
- Fisheries and Oceans Canada, Centre for Aquaculture and Environmental Research, West Vancouver, British Columbia, Canada
| | - Eric B. Rondeau
- Fisheries and Oceans Canada, Centre for Aquaculture and Environmental Research, West Vancouver, British Columbia, Canada
| | - Matthew K. Brachmann
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | - Anne A. Easton
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | | | - Michelle T. T. Crown
- Simon Fraser University, Molecular Biology and Biochemistry, Burnaby, British Columbia, Canada
| | - William S. Davidson
- Simon Fraser University, Molecular Biology and Biochemistry, Burnaby, British Columbia, Canada
| | - Ben F. Koop
- University of Victoria, Department of Biology, Victoria, British Columbia, Canada
| | - Roy G. Danzmann
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| | - Moira M. Ferguson
- University of Guelph, Department of Integrative Biology, Guelph, Ontario, Canada
| |
Collapse
|
22
|
Bao L, Tian C, Liu S, Zhang Y, Elaswad A, Yuan Z, Khalil K, Sun F, Yang Y, Zhou T, Li N, Tan S, Zeng Q, Liu Y, Li Y, Li Y, Gao D, Dunham R, Davis K, Waldbieser G, Liu Z. The Y chromosome sequence of the channel catfish suggests novel sex determination mechanisms in teleost fish. BMC Biol 2019; 17:6. [PMID: 30683095 PMCID: PMC6346536 DOI: 10.1186/s12915-019-0627-7] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 01/09/2019] [Indexed: 11/30/2022] Open
Abstract
Background Sex determination mechanisms in teleost fish broadly differ from mammals and birds, with sex chromosomes that are far less differentiated and recombination often occurring along the length of the X and Y chromosomes, posing major challenges for the identification of specific sex determination genes. Here, we take an innovative approach of comparative genome analysis of the genomic sequences of the X chromosome and newly sequenced Y chromosome in the channel catfish. Results Using a YY channel catfish as the sequencing template, we generated, assembled, and annotated the Y genome sequence of channel catfish. The genome sequence assembly had a contig N50 size of 2.7 Mb and a scaffold N50 size of 26.7 Mb. Genetic linkage and GWAS analyses placed the sex determination locus within a genetic distance less than 0.5 cM and physical distance of 8.9 Mb. However, comparison of the channel catfish X and Y chromosome sequences showed no sex-specific genes. Instead, comparative RNA-Seq analysis between females and males revealed exclusive sex-specific expression of an isoform of the breast cancer anti-resistance 1 (BCAR1) gene in the male during early sex differentiation. Experimental knockout of BCAR1 gene converted genetic males (XY) to phenotypic females, suggesting BCAR1 as a putative sex determination gene. Conclusions We present the first Y chromosome sequence among teleost fish, and one of the few whole Y chromosome sequences among vertebrate species. Comparative analyses suggest that sex-specific isoform expression through alternative splicing may underlie sex determination processes in the channel catfish, and we identify BCAR1 as a potential sex determination gene. Electronic supplementary material The online version of this article (10.1186/s12915-019-0627-7) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Lisui Bao
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Changxu Tian
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yu Zhang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ahmed Elaswad
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zihao Yuan
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Karim Khalil
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Fanyue Sun
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yujia Yang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ning Li
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Suxu Tan
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Qifan Zeng
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yang Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yueru Li
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yun Li
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Dongya Gao
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Rex Dunham
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Kenneth Davis
- USDA-ARS Warmwater Aquaculture Research Unit, P.O. Box 38, 141 Experiment Station Road, Stoneville, MS, 38776, USA
| | - Geoffrey Waldbieser
- USDA-ARS Warmwater Aquaculture Research Unit, P.O. Box 38, 141 Experiment Station Road, Stoneville, MS, 38776, USA
| | - Zhanjiang Liu
- Department of Biology, College of Art and Sciences, Syracuse University, Syracuse, NY, 13244, USA.
| |
Collapse
|
23
|
Zenger KR, Khatkar MS, Jones DB, Khalilisamani N, Jerry DR, Raadsma HW. Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters. Front Genet 2019; 9:693. [PMID: 30728827 PMCID: PMC6351666 DOI: 10.3389/fgene.2018.00693] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 12/11/2018] [Indexed: 11/20/2022] Open
Abstract
Within aquaculture industries, selection based on genomic information (genomic selection) has the profound potential to change genetic improvement programs and production systems. Genomic selection exploits the use of realized genomic relationships among individuals and information from genome-wide markers in close linkage disequilibrium with genes of biological and economic importance. We discuss the technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries, with a particular focus on molluscs (pearl oysters, Pinctada maxima) and marine shrimp (Litopenaeus vannamei and Penaeus monodon). The use of low-cost genome sequencing has enabled cost-effective genotyping on a large scale and is of particular value for species without a reference genome or access to commercial genotyping arrays. We highlight the pitfalls and offer the solutions to the genotyping by sequencing approach and the building of appropriate genetic resources to undertake genomic selection from first-hand experience. We describe the potential to capture large-scale commercial phenotypes based on image analysis and artificial intelligence through machine learning, as inputs for calculation of genomic breeding values. The application of genomic selection over traditional aquatic breeding programs offers significant advantages through being able to accurately predict complex polygenic traits including disease resistance; increasing rates of genetic gain; minimizing inbreeding; and negating potential limiting effects of genotype by environment interactions. Further practical advantages of genomic selection through the use of large-scale communal mating and rearing systems are highlighted, as well as presenting rate-limiting steps that impact on attaining maximum benefits from adopting genomic selection. Genomic selection is now at the tipping point where commercial applications can be readily adopted and offer significant short- and long-term solutions to sustainable and profitable aquaculture industries.
Collapse
Affiliation(s)
- Kyall R Zenger
- Centre for Sustainable Tropical Fisheries and Aquaculture, College of Science and Engineering, James Cook University, Townsville, QLD, Australia.,ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
| | - Mehar S Khatkar
- ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, Australia
| | - David B Jones
- Centre for Sustainable Tropical Fisheries and Aquaculture, College of Science and Engineering, James Cook University, Townsville, QLD, Australia
| | - Nima Khalilisamani
- ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, Australia
| | - Dean R Jerry
- Centre for Sustainable Tropical Fisheries and Aquaculture, College of Science and Engineering, James Cook University, Townsville, QLD, Australia.,ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Tropical Futures Institute, James Cook University Singapore, Singapore, Singapore
| | - Herman W Raadsma
- ARC Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia.,Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, NSW, Australia
| |
Collapse
|
24
|
Tan S, Wang W, Zhong X, Tian C, Niu D, Bao L, Zhou T, Jin Y, Yang Y, Yuan Z, Gao D, Dunham R, Liu Z. Increased Alternative Splicing as a Host Response to Edwardsiella ictaluri Infection in Catfish. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2018; 20:729-738. [PMID: 30014301 DOI: 10.1007/s10126-018-9844-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 07/04/2018] [Indexed: 05/26/2023]
Abstract
Alternative splicing is the process of generating multiple transcripts from a single pre-mRNA used by eukaryotes to regulate gene expression and increase proteomic complexity. Although alternative splicing profiles have been well studied in mammalian species, they have not been well studied in aquatic species, especially after biotic stresses. In the present study, genomic information and RNA-Seq datasets were utilized to characterize alternative splicing profiles and their induced changes after bacterial infection with Edwardsiella ictaluri in channel catfish (Ictalurus punctatus). A total of 27,476 alternative splicing events, derived from 9694 genes, were identified in channel catfish. Exon skipping was the most abundant while mutually exclusive exon was the least abundant type of alternative splicing. Alternative splicing was greatly induced by E. ictaluri infection with 21.9% increase in alternative splicing events. Interestingly, genes involved in RNA binding and RNA splicing themselves were significantly enriched in differentially alternatively spliced genes after infection. Sequence analyses of splice variants of a representative alternatively spliced gene, splicing factor srsf2, revealed that certain spliced transcripts may undergo nonsense-mediated decay (NMD), suggesting functional significance of the induced alternative splicing. Although statistical analysis was not possible with such large datasets, results from quantitative real-time PCR from representative differential alternative splicing events provided general validation of the bacterial infection-induced alternative splicing. This is the first comprehensive study of alternative splicing and its changes in response to bacterial infection in fish species, providing insights into the molecular mechanisms of host responses to biotic stresses.
Collapse
Affiliation(s)
- Suxu Tan
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Wenwen Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaoxiao Zhong
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Changxu Tian
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Donghong Niu
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
- College of Life Sciences, Shanghai Ocean University, Shanghai, China
| | - Lisui Bao
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yulin Jin
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yujia Yang
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zihao Yuan
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Dongya Gao
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Rex Dunham
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zhanjiang Liu
- Department of Biology, College of Art and Sciences, Syracuse University, Syracuse, NY, 13244, USA.
| |
Collapse
|
25
|
Guppy JL, Jones DB, Jerry DR, Wade NM, Raadsma HW, Huerlimann R, Zenger KR. The State of " Omics" Research for Farmed Penaeids: Advances in Research and Impediments to Industry Utilization. Front Genet 2018; 9:282. [PMID: 30123237 PMCID: PMC6085479 DOI: 10.3389/fgene.2018.00282] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 07/09/2018] [Indexed: 12/19/2022] Open
Abstract
Elucidating the underlying genetic drivers of production traits in agricultural and aquaculture species is critical to efforts to maximize farming efficiency. "Omics" based methods (i.e., transcriptomics, genomics, proteomics, and metabolomics) are increasingly being applied to gain unprecedented insight into the biology of many aquaculture species. While the culture of penaeid shrimp has increased markedly, the industry continues to be impeded in many regards by disease, reproductive dysfunction, and a poor understanding of production traits. Extensive effort has been, and continues to be, applied to develop critical genomic resources for many commercially important penaeids. However, the industry application of these genomic resources, and the translation of the knowledge derived from "omics" studies has not yet been completely realized. Integration between the multiple "omics" resources now available (i.e., genome assemblies, transcriptomes, linkage maps, optical maps, and proteomes) will prove critical to unlocking the full utility of these otherwise independently developed and isolated resources. Furthermore, emerging "omics" based techniques are now available to address longstanding issues with completing keystone genome assemblies (e.g., through long-read sequencing), and can provide cost-effective industrial scale genotyping tools (e.g., through low density SNP chips and genotype-by-sequencing) to undertake advanced selective breeding programs (i.e., genomic selection) and powerful genome-wide association studies. In particular, this review highlights the status, utility and suggested path forward for continued development, and improved use of "omics" resources in penaeid aquaculture.
Collapse
Affiliation(s)
- Jarrod L. Guppy
- Australian Research Council Industrial Transformation Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
- College of Science and Engineering and Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, QLD, Australia
| | - David B. Jones
- Australian Research Council Industrial Transformation Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
- College of Science and Engineering and Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, QLD, Australia
| | - Dean R. Jerry
- Australian Research Council Industrial Transformation Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
- College of Science and Engineering and Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, QLD, Australia
| | - Nicholas M. Wade
- Australian Research Council Industrial Transformation Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
- Aquaculture Program, CSIRO Agriculture & Food, Queensland Bioscience Precinct, St Lucia, QLD, Australia
| | - Herman W. Raadsma
- Australian Research Council Industrial Transformation Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
- Faculty of Science, Sydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia
| | - Roger Huerlimann
- Australian Research Council Industrial Transformation Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
- College of Science and Engineering and Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, QLD, Australia
| | - Kyall R. Zenger
- Australian Research Council Industrial Transformation Research Hub for Advanced Prawn Breeding, James Cook University, Townsville, QLD, Australia
- College of Science and Engineering and Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, QLD, Australia
| |
Collapse
|
26
|
Robledo D, Palaiokostas C, Bargelloni L, Martínez P, Houston R. Applications of genotyping by sequencing in aquaculture breeding and genetics. REVIEWS IN AQUACULTURE 2018; 10:670-682. [PMID: 30220910 PMCID: PMC6128402 DOI: 10.1111/raq.12193] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 12/27/2016] [Indexed: 05/18/2023]
Abstract
Selective breeding is increasingly recognized as a key component of sustainable production of aquaculture species. The uptake of genomic technology in aquaculture breeding has traditionally lagged behind terrestrial farmed animals. However, the rapid development and application of sequencing technologies has allowed aquaculture to narrow the gap, leading to substantial genomic resources for all major aquaculture species. While high-density single-nucleotide polymorphism (SNP) arrays for some species have been developed recently, direct genotyping by sequencing (GBS) techniques have underpinned many of the advances in aquaculture genetics and breeding to date. In particular, restriction-site associated DNA sequencing (RAD-Seq) and subsequent variations have been extensively applied to generate population-level SNP genotype data. These GBS techniques are not dependent on prior genomic information such as a reference genome assembly for the species of interest. As such, they have been widely utilized by researchers and companies focussing on nonmodel aquaculture species with relatively small research communities. Applications of RAD-Seq techniques have included generation of genetic linkage maps, performing genome-wide association studies, improvements of reference genome assemblies and, more recently, genomic selection for traits of interest to aquaculture like growth, sex determination or disease resistance. In this review, we briefly discuss the history of GBS, the nuances of the various GBS techniques, bioinformatics approaches and application of these techniques to various aquaculture species.
Collapse
Affiliation(s)
- Diego Robledo
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesUniversity of EdinburghMidlothianUK
| | - Christos Palaiokostas
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesUniversity of EdinburghMidlothianUK
| | - Luca Bargelloni
- Department of Comparative Biomedicine and Food ScienceUniversity of PadovaLegnaroPadovaItaly
| | - Paulino Martínez
- Department of ZoologyGenetics and Physical AnthropologyFaculty of VeterinaryUniversity of Santiago de CompostelaLugoSpain
| | - Ross Houston
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesUniversity of EdinburghMidlothianUK
| |
Collapse
|
27
|
Shi H, Zhou T, Wang X, Yang Y, Wu C, Liu S, Bao L, Li N, Yuan Z, Jin Y, Tan S, Wang W, Zhong X, Qin G, Geng X, Gao D, Dunham R, Liu Z. Genome-wide association analysis of intra-specific QTL associated with the resistance for enteric septicemia of catfish. Mol Genet Genomics 2018; 293:1365-1378. [PMID: 29967962 DOI: 10.1007/s00438-018-1463-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Accepted: 06/19/2018] [Indexed: 02/07/2023]
Abstract
Disease resistance is one of the most important traits for aquaculture industry. For catfish industry, enteric septicemia of catfish (ESC), caused by the bacterial pathogen Edwardsiella ictaluri, is the most severe disease, causing enormous economic losses every year. In this study, we used three channel catfish families with 900 individuals (300 fish per family) and the 690K catfish SNP array, and conducted a genome-wide association study to detect the quantitative trait loci (QTL) associated with ESC resistance. Three significant QTL, with two of located on LG1 and one on LG26, and three suggestive QTL located on LG1, LG3, and LG21, respectively, were identified to be associated with ESC resistance. With a well-assembled- and -annotated reference genome sequence, genes around the involved QTL regions were identified. Among these genes, 37 genes had known functions in immunity, which may be involved in ESC resistance. Notably, nlrc3 and nlrp12 identified here were also found in QTL regions of ESC resistance in the channel catfish × blue catfish interspecific hybrid system, suggesting this QTL was operating within both intra-specific channel catfish populations and interspecific hybrid backcross populations. Many of the genes of the Class I MHC pathway, for mediated antigen processing and presentation, were found in the QTL regions. The positional correlation found in this study and the expressional correlation found in previous studies indicated that Class I MHC pathway was significantly associated with ESC resistance. This study validated one QTL previously identified using the second and fourth generation of the interspecific hybrid backcross progenies, and identified five additional QTL among channel catfish families. Taken together, it appears that there are only a few major QTL for ESC disease resistance, making marker-assisted selection an effective approach for genetic improvements of ESC resistance.
Collapse
Affiliation(s)
- Huitong Shi
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaozhu Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yujia Yang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Chenglong Wu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Lisui Bao
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ning Li
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zihao Yuan
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yulin Jin
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Suxu Tan
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Wenwen Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaoxiao Zhong
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Guyu Qin
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xin Geng
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Dongya Gao
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Rex Dunham
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zhanjiang Liu
- Department of Biology, College of Art and Sciences, Syracuse University, Syracuse, NY, 13244, USA.
| |
Collapse
|
28
|
GWAS analysis using interspecific backcross progenies reveals superior blue catfish alleles responsible for strong resistance against enteric septicemia of catfish. Mol Genet Genomics 2018; 293:1107-1120. [PMID: 29737402 DOI: 10.1007/s00438-018-1443-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Accepted: 05/02/2018] [Indexed: 12/11/2022]
Abstract
Infectious diseases pose significant threats to the catfish industry. Enteric septicemia of catfish (ESC) caused by Edwardsiella ictaluri is the most devastating disease for catfish aquaculture, causing huge economic losses annually. Channel catfish and blue catfish exhibit great contrast in resistance against ESC, with channel catfish being highly susceptible and blue catfish being highly resistant. As such, the interspecific backcross progenies provide an ideal system for the identification of quantitative trait locus (QTL). We previously reported one significant QTL on linkage group (LG) 1 using the third-generation backcrosses, but the number of founders used to make the second- and third-generation backcross progenies was very small. Although the third-generation backcross progenies provided a greater power for fine mapping than the first-generation backcrosses, some major QTL for disease resistance may have been missing due to the small numbers of founders used to produce the higher generation backcrosses. In this study, we performed a genome-wide association study using first-generation backcrosses with the catfish 690 K SNP arrays to identify additional ESC disease resistance QTL, especially those at the species level. Two genomic regions on LG1 and LG23 were determined to be significantly associated with ESC resistance as revealed by a mixed linear model and family-based association test. Examination of the resistance alleles indicated their origin from blue catfish, indicating that at least two major disease resistance loci exist among blue catfish populations. Upon further validation, markers linked with major ESC disease resistance QTL should be useful for marker-assisted introgression, allowing development of highly ESC resistant breeds of catfish.
Collapse
|
29
|
Kim JM, Santure AW, Barton HJ, Quinn JL, Cole EF, Visser ME, Sheldon BC, Groenen MAM, van Oers K, Slate J. A high-density SNP chip for genotyping great tit (Parus major) populations and its application to studying the genetic architecture of exploration behaviour. Mol Ecol Resour 2018; 18:877-891. [PMID: 29573186 DOI: 10.1111/1755-0998.12778] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 03/05/2018] [Accepted: 03/05/2018] [Indexed: 12/25/2022]
Abstract
High-density SNP microarrays ("SNP chips") are a rapid, accurate and efficient method for genotyping several hundred thousand polymorphisms in large numbers of individuals. While SNP chips are routinely used in human genetics and in animal and plant breeding, they are less widely used in evolutionary and ecological research. In this article, we describe the development and application of a high-density Affymetrix Axiom chip with around 500,000 SNPs, designed to perform genomics studies of great tit (Parus major) populations. We demonstrate that the per-SNP genotype error rate is well below 1% and that the chip can also be used to identify structural or copy number variation. The chip is used to explore the genetic architecture of exploration behaviour (EB), a personality trait that has been widely studied in great tits and other species. No SNPs reached genomewide significance, including at DRD4, a candidate gene. However, EB is heritable and appears to have a polygenic architecture. Researchers developing similar SNP chips may note: (i) SNPs previously typed on alternative platforms are more likely to be converted to working assays; (ii) detecting SNPs by more than one pipeline, and in independent data sets, ensures a high proportion of working assays; (iii) allele frequency ascertainment bias is minimized by performing SNP discovery in individuals from multiple populations; and (iv) samples with the lowest call rates tend to also have the greatest genotyping error rates.
Collapse
Affiliation(s)
- J-M Kim
- Department of Animal & Plant Sciences, University of Sheffield, Sheffield, UK.,Department of Animal Science and Technology, Chung-Ang University, Anseong, Gyeonggi-do, Korea
| | - A W Santure
- Department of Animal & Plant Sciences, University of Sheffield, Sheffield, UK.,School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - H J Barton
- Department of Animal & Plant Sciences, University of Sheffield, Sheffield, UK
| | - J L Quinn
- School of Biological, Earth and Environmental Science (BEES), University College Cork, Cork, Ireland
| | - E F Cole
- Department of Zoology, Edward Grey Institute, University of Oxford, Oxford, UK
| | | | - M E Visser
- Department of Animal Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, Netherlands
| | - B C Sheldon
- Department of Zoology, Edward Grey Institute, University of Oxford, Oxford, UK
| | - M A M Groenen
- Wageningen University and Research - Animal Breeding and Genomics, Wageningen, Netherlands
| | - K van Oers
- Department of Animal Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, Netherlands
| | - J Slate
- Department of Animal & Plant Sciences, University of Sheffield, Sheffield, UK
| |
Collapse
|
30
|
You Q, Yang X, Peng Z, Xu L, Wang J. Development and Applications of a High Throughput Genotyping Tool for Polyploid Crops: Single Nucleotide Polymorphism (SNP) Array. FRONTIERS IN PLANT SCIENCE 2018; 9:104. [PMID: 29467780 PMCID: PMC5808122 DOI: 10.3389/fpls.2018.00104] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Accepted: 01/19/2018] [Indexed: 05/18/2023]
Abstract
Polypoid species play significant roles in agriculture and food production. Many crop species are polyploid, such as potato, wheat, strawberry, and sugarcane. Genotyping has been a daunting task for genetic studies of polyploid crops, which lags far behind the diploid crop species. Single nucleotide polymorphism (SNP) array is considered to be one of, high-throughput, relatively cost-efficient and automated genotyping approaches. However, there are significant challenges for SNP identification in complex, polyploid genomes, which has seriously slowed SNP discovery and array development in polyploid species. Ploidy is a significant factor impacting SNP qualities and validation rates of SNP markers in SNP arrays, which has been proven to be a very important tool for genetic studies and molecular breeding. In this review, we (1) discussed the pros and cons of SNP array in general for high throughput genotyping, (2) presented the challenges of and solutions to SNP calling in polyploid species, (3) summarized the SNP selection criteria and considerations of SNP array design for polyploid species, (4) illustrated SNP array applications in several different polyploid crop species, then (5) discussed challenges, available software, and their accuracy comparisons for genotype calling based on SNP array data in polyploids, and finally (6) provided a series of SNP array design and genotype calling recommendations. This review presents a complete overview of SNP array development and applications in polypoid crops, which will benefit the research in molecular breeding and genetics of crops with complex genomes.
Collapse
Affiliation(s)
- Qian You
- Key Laboratory of Sugarcane Biology and Genetic Breeding Ministry of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China
- Agronomy Department, University of Florida, Gainesville, FL, United States
| | - Xiping Yang
- Agronomy Department, University of Florida, Gainesville, FL, United States
| | - Ze Peng
- Agronomy Department, University of Florida, Gainesville, FL, United States
| | - Liping Xu
- Key Laboratory of Sugarcane Biology and Genetic Breeding Ministry of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China
- *Correspondence: Liping Xu
| | - Jianping Wang
- Agronomy Department, University of Florida, Gainesville, FL, United States
- Plant Molecular and Cellular Biology Program, Genetics Institute, University of Florida, Gainesville, FL, United States
- Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Center for Genomics and Biotechnology, Fujian Agriculture and Forestry University, Fuzhou, China
- Jianping Wang
| |
Collapse
|
31
|
Li N, Zhou T, Geng X, Jin Y, Wang X, Liu S, Xu X, Gao D, Li Q, Liu Z. Identification of novel genes significantly affecting growth in catfish through GWAS analysis. Mol Genet Genomics 2017; 293:587-599. [PMID: 29230585 DOI: 10.1007/s00438-017-1406-1] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Accepted: 12/07/2017] [Indexed: 12/01/2022]
Abstract
Growth is the most important economic trait in aquaculture. Improvements in growth-related traits can enhance production, reduce costs and time to produce market-size fish. Catfish is the major aquaculture species in the United States, accounting for 65% of the US finfish production. However, the genes underlying growth traits in catfish were not well studied. Currently, the majority of the US catfish industry uses hybrid catfish derived from channel catfish female mated with blue catfish male. Interestingly, channel catfish and blue catfish exhibit differences in growth-related traits, and therefore the backcross progenies provide an efficient system for QTL analysis. In this study, we conducted a genome-wide association study for catfish body weight using the 250 K SNP array with 556 backcross progenies generated from backcross of male F1 hybrid (female channel catfish × male blue catfish) with female channel catfish. A genomic region of approximately 1 Mb on linkage group 5 was found to be significantly associated with body weight. In addition, four suggestively associated QTL regions were identified on linkage groups 1, 2, 23 and 24. Most candidate genes in the associated regions are known to be involved in muscle growth and bone development, some of which were reported to be associated with obesity in humans and pigs, suggesting that the functions of these genes may be evolutionarily conserved in controlling growth. Additional fine mapping or functional studies should allow identification of the causal genes for fast growth in catfish, and elucidation of molecular mechanisms of regulation of growth in fish.
Collapse
Affiliation(s)
- Ning Li
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xin Geng
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yulin Jin
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaozhu Wang
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Xiaoyan Xu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.,Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Shanghai Ocean University, Shanghai, 201306, China
| | - Dongya Gao
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Qi Li
- The Shellfish Genetics and Breeding Laboratory, Fisheries College, Ocean University of China, Qingdao, 266003, Shandong, China
| | - Zhanjiang Liu
- Department of Biology, Syracuse University, Syracuse, NY, 13244, USA.
| |
Collapse
|
32
|
Geng X, Liu S, Yuan Z, Jiang Y, Zhi D, Liu Z. A Genome-Wide Association Study Reveals That Genes with Functions for Bone Development Are Associated with Body Conformation in Catfish. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2017; 19:570-578. [PMID: 28971324 DOI: 10.1007/s10126-017-9775-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2017] [Accepted: 08/08/2017] [Indexed: 06/07/2023]
Abstract
Body conformation is of great scientific and commercial interest for aquaculture fish species because it affects biological adaptation of the organism to environments, and is of economic importance to the aquaculture industry considering its direct effect on fillet yield. Catfish is the primary aquaculture species in the USA. Two major species used in the aquaculture industry, channel catfish and blue catfish, differ in body shape and therefore the backcross progenies serve as a good model for quantitative trait locus (QTL) analysis. Here, a genome-wide association study (GWAS) with hybrid catfish was conducted to identify the QTL for body conformation, including deheaded body length (DBL), body length (BL), body depth (BD), and body breadth (BB), which were all standardized by cubic root of body weight. Overall, the results indicate that the traits are polygenic. For DBL, linkage group (LG) 2 and LG 24 contain significant QTL, and LG 13 and LG 26 contain suggestively associated QTL (-log10(P value) > 4.5). Compared with DBL, additional SNPs were identified to be associated with body length on LG 2, LG 7, and LG 18. Although no significant QTL for body depth was found, three suggestively associated QTLs were identified on LG 5, LG 13, and LG 14. No SNP for body breadth reached the threshold for suggestive association. Genes close to the associated SNPs were determined, many of which are known to be involved in bone development. This work therefore provides the basis for future identification of causal genes for the control of body conformation.
Collapse
Affiliation(s)
- Xin Geng
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zihao Yuan
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yanliang Jiang
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Degui Zhi
- School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Zhanjiang Liu
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
| |
Collapse
|
33
|
A comparative integrated gene-based linkage and locus ordering by linkage disequilibrium map for the Pacific white shrimp, Litopenaeus vannamei. Sci Rep 2017; 7:10360. [PMID: 28871114 PMCID: PMC5583237 DOI: 10.1038/s41598-017-10515-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Accepted: 08/09/2017] [Indexed: 11/23/2022] Open
Abstract
The Pacific whiteleg shrimp, Litopenaeus vannamei, is the most farmed aquaculture species worldwide with global production exceeding 3 million tonnes annually. Litopenaeus vannamei has been the focus of many selective breeding programs aiming to improve growth and disease resistance. However, these have been based primarily on phenotypic measurements and omit potential gains by integrating genetic selection into existing breeding programs. Such integration of genetic information has been hindered by the limited available genomic resources, background genetic parameters and knowledge on the genetic architecture of commercial traits for L. vannamei. This study describes the development of a comprehensive set of genomic gene-based resources including the identification and validation of 234,452 putative single nucleotide polymorphisms in-silico, of which 8,967 high value SNPs were incorporated into a commercially available Illumina Infinium ShrimpLD-24 v1.0 genotyping array. A framework genetic linkage map was constructed and combined with locus ordering by disequilibrium methodology to generate an integrated genetic map containing 4,817 SNPs, which spanned a total of 4552.5 cM and covered an estimated 98.12% of the genome. These gene-based genomic resources will not only be valuable for identifying regions underlying important L. vannamei traits, but also as a foundational resource in comparative and genome assembly activities.
Collapse
|
34
|
Zhong X, Wang X, Zhou T, Jin Y, Tan S, Jiang C, Geng X, Li N, Shi H, Zeng Q, Yang Y, Yuan Z, Bao L, Liu S, Tian C, Peatman E, Li Q, Liu Z. Genome-Wide Association Study Reveals Multiple Novel QTL Associated with Low Oxygen Tolerance in Hybrid Catfish. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2017; 19:379-390. [PMID: 28601969 DOI: 10.1007/s10126-017-9757-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Accepted: 05/23/2017] [Indexed: 06/07/2023]
Abstract
Hypoxic condition is common in aquaculture, leading to major economic losses. Genetic analysis of hypoxia tolerance, therefore, is not only scientifically significant, but also economically important. Catfish is generally regarded as being highly tolerant to low dissolved oxygen, but variations exist among various populations, strains, and species. In this study, we conducted a genome-wide association study (GWAS) using the catfish 250 K SNP array to identify quantitative trait locus (QTL) associated with tolerance to low dissolved oxygen in the channel catfish × blue catfish interspecific system. Four linkage groups (LG2, LG4, LG23, and LG29) were found to be associated with low oxygen tolerance in hybrid catfish. Multiple significant SNPs were found to be physically linked in genomic regions containing significant QTL for low oxygen tolerance on LG2 and LG23, and in those regions containing suggestively significant QTL on LG2, LG4, LG23, and LG29, suggesting that the physically linked SNPs were genuinely segregating and related with low oxygen tolerance. Analysis of genes within the associated genomic regions suggested that many of these genes were involved in VEGF, MAPK, mTOR, PI3K-Akt, P53-mediated apoptosis, and DNA damage checkpoint pathways. Comparative analysis indicated that most of the QTL at the species level, as analyzed by using the interspecific system, did not overlap with those identified from six strains of channel catfish, confirming the complexity of the genetic architecture of hypoxia tolerance in catfish.
Collapse
Affiliation(s)
- Xiaoxiao Zhong
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
- Key Laboratory of Mariculture Ministry of Education, Ocean University of China, Qingdao, 266003, China
| | - Xiaozhu Wang
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Yulin Jin
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Suxu Tan
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Chen Jiang
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Xin Geng
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Ning Li
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Huitong Shi
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Qifan Zeng
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Yujia Yang
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Zihao Yuan
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Lisui Bao
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Changxu Tian
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Eric Peatman
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA
| | - Qi Li
- Key Laboratory of Mariculture Ministry of Education, Ocean University of China, Qingdao, 266003, China
| | - Zhanjiang Liu
- Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, USA.
| |
Collapse
|
35
|
Gutierrez AP, Turner F, Gharbi K, Talbot R, Lowe NR, Peñaloza C, McCullough M, Prodöhl PA, Bean TP, Houston RD. Development of a Medium Density Combined-Species SNP Array for Pacific and European Oysters ( Crassostrea gigas and Ostrea edulis). G3 (BETHESDA, MD.) 2017; 7:2209-2218. [PMID: 28533337 PMCID: PMC5499128 DOI: 10.1534/g3.117.041780] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 05/06/2017] [Indexed: 01/01/2023]
Abstract
SNP arrays are enabling tools for high-resolution studies of the genetic basis of complex traits in farmed and wild animals. Oysters are of critical importance in many regions from both an ecological and economic perspective, and oyster aquaculture forms a key component of global food security. The aim of our study was to design a combined-species, medium density SNP array for Pacific oyster (Crassostrea gigas) and European flat oyster (Ostrea edulis), and to test the performance of this array on farmed and wild populations from multiple locations, with a focus on European populations. SNP discovery was carried out by whole-genome sequencing (WGS) of pooled genomic DNA samples from eight C. gigas populations, and restriction site-associated DNA sequencing (RAD-Seq) of 11 geographically diverse O. edulis populations. Nearly 12 million candidate SNPs were discovered and filtered based on several criteria, including preference for SNPs segregating in multiple populations and SNPs with monomorphic flanking regions. An Affymetrix Axiom Custom Array was created and tested on a diverse set of samples (n = 219) showing ∼27 K high quality SNPs for C. gigas and ∼11 K high quality SNPs for O. edulis segregating in these populations. A high proportion of SNPs were segregating in each of the populations, and the array was used to detect population structure and levels of linkage disequilibrium (LD). Further testing of the array on three C. gigas nuclear families (n = 165) revealed that the array can be used to clearly distinguish between both families based on identity-by-state (IBS) clustering parental assignment software. This medium density, combined-species array will be publicly available through Affymetrix, and will be applied for genome-wide association and evolutionary genetic studies, and for genomic selection in oyster breeding programs.
Collapse
Affiliation(s)
- Alejandro P Gutierrez
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, United Kingdom
| | - Frances Turner
- Edinburgh Genomics, Ashworth Laboratories, University of Edinburgh, EH9 3FL, United Kingdom
| | - Karim Gharbi
- Edinburgh Genomics, Ashworth Laboratories, University of Edinburgh, EH9 3FL, United Kingdom
| | - Richard Talbot
- Edinburgh Genomics, Ashworth Laboratories, University of Edinburgh, EH9 3FL, United Kingdom
| | - Natalie R Lowe
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, United Kingdom
| | - Carolina Peñaloza
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, United Kingdom
| | - Mark McCullough
- Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, BT7 1NN, United Kingdom
| | - Paulo A Prodöhl
- Institute for Global Food Security, School of Biological Sciences, Queen's University Belfast, BT7 1NN, United Kingdom
| | - Tim P Bean
- Centre for Environment Fisheries and Aquaculture Science, Cefas Weymouth Laboratory, Dorset DT4 8UB, United Kingdom
| | - Ross D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, United Kingdom
| |
Collapse
|
36
|
Wang L, Liu P, Huang S, Ye B, Chua E, Wan ZY, Yue GH. Genome-Wide Association Study Identifies Loci Associated with Resistance to Viral Nervous Necrosis Disease in Asian Seabass. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2017; 19:255-265. [PMID: 28484864 DOI: 10.1007/s10126-017-9747-7] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 04/19/2017] [Indexed: 05/22/2023]
Abstract
Viral nervous necrosis disease (VNN), caused by nervous necrosis virus (NNV), is one major threat to mariculture. Identifying loci and understanding the mechanisms associated with resistance to VNN are important in selective breeding programs. We performed a genome-wide association study (GWAS) using genotyping-by-sequencing (GBS) to study the genomic architecture of resistance to NNV infection in Asian seabass. We genotyped 986 individuals from 43 families produced by 15 founders with 44498 bi-allelic genetic variants using GBS. The GWAS identified three genome-wide significant loci on chromosomes 16, 19, and 20, respectively, and six suggestive loci on chromosomes 1, 8, 14, 15, 21, and 24, respectively, associated with resistance to NNV infection measured as binary and quantitative traits. Using the 500 most significant markers in combination with a training population of 800 samples could reach a genomic prediction accuracy of 0.7. Candidate genes significantly associated with resistance to NNV, including lysine-specific demethylase 2A, beta-defensin 1, and cystatin-B, which play important roles in immune responses against virus infection, were identified. Almost all the candidate genes were differentially expressed in different tissues against NNV infection. The significant genetic variants can be used in genomic selection and help understand the mechanism of resistance to VNN. Future studies should use populations of large effective size and whole genome resequencing to identify more useful genetic variants.
Collapse
Affiliation(s)
- Le Wang
- Molecular Population Genetics and Breeding Group, Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, 117604, Singapore
| | - Peng Liu
- Molecular Population Genetics and Breeding Group, Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, 117604, Singapore
- Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore
| | - Shuqing Huang
- Molecular Population Genetics and Breeding Group, Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, 117604, Singapore
| | - Baoqing Ye
- Molecular Population Genetics and Breeding Group, Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, 117604, Singapore
| | - Elaine Chua
- Molecular Population Genetics and Breeding Group, Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, 117604, Singapore
| | - Zi Yi Wan
- Molecular Population Genetics and Breeding Group, Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, 117604, Singapore
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - Gen Hua Yue
- Molecular Population Genetics and Breeding Group, Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, 117604, Singapore.
- Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore.
| |
Collapse
|
37
|
Nunes JDRDS, Liu S, Pértille F, Perazza CA, Villela PMS, de Almeida-Val VMF, Hilsdorf AWS, Liu Z, Coutinho LL. Large-scale SNP discovery and construction of a high-density genetic map of Colossoma macropomum through genotyping-by-sequencing. Sci Rep 2017; 7:46112. [PMID: 28387238 PMCID: PMC5384230 DOI: 10.1038/srep46112] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 03/06/2017] [Indexed: 11/11/2022] Open
Abstract
Colossoma macropomum, or tambaqui, is the largest native Characiform species found in the Amazon and Orinoco river basins, yet few resources for genetic studies and the genetic improvement of tambaqui exist. In this study, we identified a large number of single-nucleotide polymorphisms (SNPs) for tambaqui and constructed a high-resolution genetic linkage map from a full-sib family of 124 individuals and their parents using the genotyping by sequencing method. In all, 68,584 SNPs were initially identified using minimum minor allele frequency (MAF) of 5%. Filtering parameters were used to select high-quality markers for linkage analysis. We selected 7,734 SNPs for linkage mapping, resulting in 27 linkage groups with a minimum logarithm of odds (LOD) of 8 and maximum recombination fraction of 0.35. The final genetic map contains 7,192 successfully mapped markers that span a total of 2,811 cM, with an average marker interval of 0.39 cM. Comparative genomic analysis between tambaqui and zebrafish revealed variable levels of genomic conservation across the 27 linkage groups which allowed for functional SNP annotations. The large-scale SNP discovery obtained here, allowed us to build a high-density linkage map in tambaqui, which will be useful to enhance genetic studies that can be applied in breeding programs.
Collapse
Affiliation(s)
- José de Ribamar da Silva Nunes
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil.,The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, United States of America.,Nature and Culture Institute, Federal University of Amazon (UFAM), Benjamin Constant, Amazonas, Brazil
| | - Shikai Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, United States of America
| | - Fábio Pértille
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Caio Augusto Perazza
- Unit of Biotechnology, University of Mogi das Cruzes, P.O. Box 411, 08701-970, Mogi das Cruzes, SP, Brazil
| | - Priscilla Marqui Schmidt Villela
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| | - Vera Maria Fonseca de Almeida-Val
- Brazilian National Institute for Research of the Amazon, Laboratory of Ecophysiology and Molecular Evolution, Manaus, Amazonas, Brazil.,University Nilton Lins, Aquaculture Graduate Program, Manaus, Amazonas, Brazil
| | | | - Zhanjiang Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, Aquatic Genomics Unit, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Auburn University, Auburn, AL, 36849, United States of America
| | - Luiz Lehmann Coutinho
- Animal Science department, University of São Paulo (USP)/Luiz de Queiroz College of Agriculture (ESALQ), Piracicaba, São Paulo, Brazil
| |
Collapse
|
38
|
Qi H, Song K, Li C, Wang W, Li B, Li L, Zhang G. Construction and evaluation of a high-density SNP array for the Pacific oyster (Crassostrea gigas). PLoS One 2017; 12:e0174007. [PMID: 28328985 PMCID: PMC5362100 DOI: 10.1371/journal.pone.0174007] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2016] [Accepted: 03/01/2017] [Indexed: 12/31/2022] Open
Abstract
Single nucleotide polymorphisms (SNPs) are widely used in genetics and genomics research. The Pacific oyster (Crassostrea gigas) is an economically and ecologically important marine bivalve, and it possesses one of the highest levels of genomic DNA variation among animal species. Pacific oyster SNPs have been extensively investigated; however, the mechanisms by which these SNPs may be used in a high-throughput, transferable, and economical manner remain to be elucidated. Here, we constructed an oyster 190K SNP array using Affymetrix Axiom genotyping technology. We designed 190,420 SNPs on the chip; these SNPs were selected from 54 million SNPs identified through re-sequencing of 472 Pacific oysters collected in China, Japan, Korea, and Canada. Our genotyping results indicated that 133,984 (70.4%) SNPs were polymorphic and successfully converted on the chip. The SNPs were distributed evenly throughout the oyster genome, located in 3,595 scaffolds with a length of ~509.4 million; the average interval spacing was 4,210 bp. In addition, 111,158 SNPs were distributed in 21,050 coding genes, with an average of 5.3 SNPs per gene. In comparison with genotypes obtained through re-sequencing, ~69% of the converted SNPs had a concordance rate of >0.971; the mean concordance rate was 0.966. Evaluation based on genotypes of full-sib family individuals revealed that the average genotyping accuracy rate was 0.975. Carrying 133 K polymorphic SNPs, our oyster 190K SNP array is the first commercially available high-density SNP chip for mollusks, with the highest throughput. It represents a valuable tool for oyster genome-wide association studies, fine linkage mapping, and population genetics.
Collapse
Affiliation(s)
- Haigang Qi
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
- National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
| | - Kai Song
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- Laboratory for Marine Fisheries and Aquaculture, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong, China
| | - Chunyan Li
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
- National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
| | - Wei Wang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
- National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
| | - Busu Li
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
- National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
| | - Li Li
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- Laboratory for Marine Fisheries and Aquaculture, Qingdao National Laboratory for Marine Science and Technology, Qingdao, Shandong, China
- * E-mail: (LL); (GZ)
| | - Guofan Zhang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
- National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China
- * E-mail: (LL); (GZ)
| |
Collapse
|
39
|
Li Y, Geng X, Bao L, Elaswad A, Huggins KW, Dunham R, Liu Z. A deletion in the Hermansky–Pudlak syndrome 4 (Hps4) gene appears to be responsible for albinism in channel catfish. Mol Genet Genomics 2017; 292:663-670. [DOI: 10.1007/s00438-017-1302-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 02/11/2017] [Indexed: 10/20/2022]
|
40
|
Status and future perspectives of single nucleotide polymorphisms (SNPs) markers in farmed fishes: Way ahead using next generation sequencing. GENE REPORTS 2017. [DOI: 10.1016/j.genrep.2016.12.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
|
41
|
Abdelrahman H, ElHady M, Alcivar-Warren A, Allen S, Al-Tobasei R, Bao L, Beck B, Blackburn H, Bosworth B, Buchanan J, Chappell J, Daniels W, Dong S, Dunham R, Durland E, Elaswad A, Gomez-Chiarri M, Gosh K, Guo X, Hackett P, Hanson T, Hedgecock D, Howard T, Holland L, Jackson M, Jin Y, Khalil K, Kocher T, Leeds T, Li N, Lindsey L, Liu S, Liu Z, Martin K, Novriadi R, Odin R, Palti Y, Peatman E, Proestou D, Qin G, Reading B, Rexroad C, Roberts S, Salem M, Severin A, Shi H, Shoemaker C, Stiles S, Tan S, Tang KFJ, Thongda W, Tiersch T, Tomasso J, Prabowo WT, Vallejo R, van der Steen H, Vo K, Waldbieser G, Wang H, Wang X, Xiang J, Yang Y, Yant R, Yuan Z, Zeng Q, Zhou T. Aquaculture genomics, genetics and breeding in the United States: current status, challenges, and priorities for future research. BMC Genomics 2017; 18:191. [PMID: 28219347 PMCID: PMC5319170 DOI: 10.1186/s12864-017-3557-1] [Citation(s) in RCA: 86] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 02/06/2017] [Indexed: 12/31/2022] Open
Abstract
Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product quality, and profitability in support of the commercial sector and for the benefit of consumers. In order to achieve these goals, it is important to understand the genomic structure and organization of aquaculture species, and their genomic and phenomic variations, as well as the genetic basis of traits and their interrelationships. In addition, it is also important to understand the mechanisms of regulation and evolutionary conservation at the levels of genome, transcriptome, proteome, epigenome, and systems biology. With genomic information and information between the genomes and phenomes, technologies for marker/causal mutation-assisted selection, genome selection, and genome editing can be developed for applications in aquaculture. A set of genomic tools and resources must be made available including reference genome sequences and their annotations (including coding and non-coding regulatory elements), genome-wide polymorphic markers, efficient genotyping platforms, high-density and high-resolution linkage maps, and transcriptome resources including non-coding transcripts. Genomic and genetic control of important performance and production traits, such as disease resistance, feed conversion efficiency, growth rate, processing yield, behaviour, reproductive characteristics, and tolerance to environmental stressors like low dissolved oxygen, high or low water temperature and salinity, must be understood. QTL need to be identified, validated across strains, lines and populations, and their mechanisms of control understood. Causal gene(s) need to be identified. Genetic and epigenetic regulation of important aquaculture traits need to be determined, and technologies for marker-assisted selection, causal gene/mutation-assisted selection, genome selection, and genome editing using CRISPR and other technologies must be developed, demonstrated with applicability, and application to aquaculture industries.Major progress has been made in aquaculture genomics for dozens of fish and shellfish species including the development of genetic linkage maps, physical maps, microarrays, single nucleotide polymorphism (SNP) arrays, transcriptome databases and various stages of genome reference sequences. This paper provides a general review of the current status, challenges and future research needs of aquaculture genomics, genetics, and breeding, with a focus on major aquaculture species in the United States: catfish, rainbow trout, Atlantic salmon, tilapia, striped bass, oysters, and shrimp. While the overall research priorities and the practical goals are similar across various aquaculture species, the current status in each species should dictate the next priority areas within the species. This paper is an output of the USDA Workshop for Aquaculture Genomics, Genetics, and Breeding held in late March 2016 in Auburn, Alabama, with participants from all parts of the United States.
Collapse
Affiliation(s)
- Hisham Abdelrahman
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Mohamed ElHady
- Department of Biological Sciences, Auburn University, Auburn, AL, 36849, USA
| | | | - Standish Allen
- Aquaculture Genetics & Breeding Technology Center, Virginia Institute of Marine Science, Gloucester Point, VA, 23062, USA
| | - Rafet Al-Tobasei
- Department of Biology, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Lisui Bao
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ben Beck
- Aquatic Animal Health Research Unit, USDA-ARS, 990 Wire Road, Auburn, AL, 36832, USA
| | - Harvey Blackburn
- USDA-ARS-NL Wheat & Corn Collections at a Glance GRP, National Animal Germplasm Program, 1111 S. Mason St., Fort Collins, CO, 80521-4500, USA
| | - Brian Bosworth
- USDA-ARS/CGRU, 141 Experimental Station Road, Stoneville, MS, 38701, USA
| | - John Buchanan
- Center for Aquaculture Technologies, 8395 Camino Santa Fe, Suite E, San Diego, CA, 92121, USA
| | - Jesse Chappell
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - William Daniels
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Sheng Dong
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Rex Dunham
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Evan Durland
- Department of Fisheries and Wildlife, Oregon State University, Corvallis, OR, 97331, USA
| | - Ahmed Elaswad
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Marta Gomez-Chiarri
- Department of Fisheries, Animal & Veterinary Science, 134 Woodward Hall, 9 East Alumni Avenue, Kingston, RI, 02881, USA
| | - Kamal Gosh
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ximing Guo
- Haskin Shellfish Research Laboratory, Department of Marine and Coastal Sciences, Rutgers University, 6959 Miller Avenue, Port Norris, NJ, 08349, USA
| | - Perry Hackett
- Department of Genetics, Cell Biology and Development, 5-108 MCB, 420 Washington Avenue SE, Minneapolis, MN, 55455, USA
| | - Terry Hanson
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Dennis Hedgecock
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089-0371, USA
| | - Tiffany Howard
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Leigh Holland
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Molly Jackson
- Taylor Shellfish Farms, 130 SE Lynch RD, Shelton, WA, 98584, USA
| | - Yulin Jin
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Karim Khalil
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Thomas Kocher
- Department of Biology, University of Maryland, 2132 Biosciences Research Building, College Park, MD, 20742, USA
| | - Tim Leeds
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, 25430, USA
| | - Ning Li
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Lauren Lindsey
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Shikai Liu
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Zhanjiang Liu
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA.
| | - Kyle Martin
- Troutlodge, 27090 Us Highway 12, Naches, WA, 98937, USA
| | - Romi Novriadi
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Ramjie Odin
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Yniv Palti
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, 25430, USA
| | - Eric Peatman
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Dina Proestou
- USDA ARS NEA NCWMAC Shellfish Genetics at the University Rhode Island, 469 CBLS, 120 Flagg Road, Kingston, RI, 02881, USA
| | - Guyu Qin
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Benjamin Reading
- Department of Applied Ecology, North Carolina State University, Raleigh, NC, 27695-7617, USA
| | - Caird Rexroad
- USDA ARS Office of National Programs, George Washington Carver Center Room 4-2106, 5601 Sunnyside Avenue, Beltsville, MD, 20705, USA
| | - Steven Roberts
- School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, 98105, USA
| | - Mohamed Salem
- Department of Biology, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
| | - Andrew Severin
- Genome Informatics Facility, Office of Biotechnology, Iowa State University, Ames, IA, 50011, USA
| | - Huitong Shi
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Craig Shoemaker
- Aquatic Animal Health Research Unit, USDA-ARS, 990 Wire Road, Auburn, AL, 36832, USA
| | - Sheila Stiles
- USDOC/NOAA, National Marine Fisheries Service, NEFSC, Milford Laboratory, Milford, Connectcut, 06460, USA
| | - Suxu Tan
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Kathy F J Tang
- School of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, 85721, USA
| | - Wilawan Thongda
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Terrence Tiersch
- Aquatic Germplasm and Genetic Resources Center, School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA, 70820, USA
| | - Joseph Tomasso
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Wendy Tri Prabowo
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Roger Vallejo
- National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, 25430, USA
| | | | - Khoi Vo
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Geoff Waldbieser
- USDA-ARS/CGRU, 141 Experimental Station Road, Stoneville, MS, 38701, USA
| | - Hanping Wang
- Aquaculture Genetics and Breeding Laboratory, The Ohio State University South Centers, Piketon, OH, 45661, USA
| | - Xiaozhu Wang
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Jianhai Xiang
- Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, 266071, China
| | - Yujia Yang
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Roger Yant
- Hybrid Catfish Company, 1233 Montgomery Drive, Inverness, MS, 38753, USA
| | - Zihao Yuan
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Qifan Zeng
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Tao Zhou
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| |
Collapse
|
42
|
Development of a 690 K SNP array in catfish and its application for genetic mapping and validation of the reference genome sequence. Sci Rep 2017; 7:40347. [PMID: 28079141 PMCID: PMC5228154 DOI: 10.1038/srep40347] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 12/05/2016] [Indexed: 02/02/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) are capable of providing the highest level of genome coverage for genomic and genetic analysis because of their abundance and relatively even distribution in the genome. Such a capacity, however, cannot be achieved without an efficient genotyping platform such as SNP arrays. In this work, we developed a high-density SNP array with 690,662 unique SNPs (herein 690 K array) that were relatively evenly distributed across the entire genome, and covered 98.6% of the reference genome sequence. Here we also report linkage mapping using the 690 K array, which allowed mapping of over 250,000 SNPs on the linkage map, the highest marker density among all the constructed linkage maps. These markers were mapped to 29 linkage groups (LGs) with 30,591 unique marker positions. This linkage map anchored 1,602 scaffolds of the reference genome sequence to LGs, accounting for over 97% of the total genome assembly. A total of 1,007 previously unmapped scaffolds were placed to LGs, allowing validation and in few instances correction of the reference genome sequence assembly. This linkage map should serve as a valuable resource for various genetic and genomic analyses, especially for GWAS and QTL mapping for genes associated with economically important traits.
Collapse
|
43
|
XU W, CHEN S. Genomics and genetic breeding in aquatic animals: progress and prospects. FRONTIERS OF AGRICULTURAL SCIENCE AND ENGINEERING 2017; 4:305. [DOI: 10.15302/j-fase-2017154] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
|
44
|
Berry DP, O'Brien A, Wall E, McDermott K, Randles S, Flynn P, Park S, Grose J, Weld R, McHugh N. Inter- and intra-reproducibility of genotypes from sheep technical replicates on Illumina and Affymetrix platforms. Genet Sel Evol 2016; 48:86. [PMID: 27832740 PMCID: PMC5105264 DOI: 10.1186/s12711-016-0267-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Accepted: 11/04/2016] [Indexed: 12/03/2022] Open
Abstract
Background Accurate genomic analyses are predicated upon access to accurate genotype input data. The objective of this study was to quantify the reproducibility of genotype data that are generated from the same genotype platform and from different genotyping platforms. Methods Genotypes based on 51,121 single nucleotide polymorphisms (SNPs) for 84 animals that were each genotyped on Illumina and Affymetrix platforms and for another 25 animals that were each genotyped twice on the same Illumina platform were compared. Genotypes based on 11,323 SNPs for an additional 21 animals that were genotyped on two different Illumina platforms by two different service providers were also compared. Reproducibility of the results was measured as the correlation between allele counts and as genotype and allele concordance rates. Results A mean within-animal correlation of 0.9996 was found between allele counts in the 25 duplicate samples that were genotyped on the same Illumina platform and varied from 0.9963 to 1.0000 per animal. The mean (minimum, maximum) genotype and allele concordance rates per animal between the 25 duplicate samples were equal to 0.9996 (0.9968, 1.0000) and 0.9993 (0.9937, 1.0000), respectively. The concordance rate between the two different Illumina platforms was also near 1. A mean within-animal correlation of 0.9738 was found between genotypes that were generated on the Illumina and Affymetrix platforms and varied from 0.9505 to 0.9812 per animal. The mean (minimum, maximum) within-animal genotype and allele concordance rates between the Illumina and Affymetrix platforms were equal to 0.9711 (0.9418, 0.9798) and 0.9845 (0.9695, 0.9889), respectively. The genotype concordance rate across all genotypes increased from 0.9711 to 0.9949 when the SNPs used were restricted to those with three high-resolution genotype clusters which represented 75.2% of the called genotypes. Conclusions and implications Our results suggest that, regardless of the genotype platform or service provider, high genotype concordance rates are achieved especially if they are restricted to high-quality extracted DNA and SNPs that result in high-quality genotypes.
Collapse
Affiliation(s)
- Donagh P Berry
- Animal and Grassland Research and Innovation Centre, Moorepark, Teagasc, Fermoy, Co. Cork, Ireland.
| | - Aine O'Brien
- Animal and Grassland Research and Innovation Centre, Moorepark, Teagasc, Fermoy, Co. Cork, Ireland
| | - Eamonn Wall
- Sheep Ireland, Highfield House, Shinagh, Bandon, Co. Cork, Ireland
| | - Kevin McDermott
- Sheep Ireland, Highfield House, Shinagh, Bandon, Co. Cork, Ireland
| | - Shane Randles
- Sheep Ireland, Highfield House, Shinagh, Bandon, Co. Cork, Ireland
| | | | | | - Jenny Grose
- GeneSeek, A Neogen Company, Lincoln, NE, USA
| | | | - Noirin McHugh
- Animal and Grassland Research and Innovation Centre, Moorepark, Teagasc, Fermoy, Co. Cork, Ireland
| |
Collapse
|
45
|
GWAS analysis of QTL for enteric septicemia of catfish and their involved genes suggest evolutionary conservation of a molecular mechanism of disease resistance. Mol Genet Genomics 2016; 292:231-242. [DOI: 10.1007/s00438-016-1269-x] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 11/01/2016] [Indexed: 10/20/2022]
|
46
|
A Genome-Wide Association Study Identifies Multiple Regions Associated with Head Size in Catfish. G3-GENES GENOMES GENETICS 2016; 6:3389-3398. [PMID: 27558670 PMCID: PMC5068958 DOI: 10.1534/g3.116.032201] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Skull morphology is fundamental to evolution and the biological adaptation of species to their environments. With aquaculture fish species, head size is also important for economic reasons because it has a direct impact on fillet yield. However, little is known about the underlying genetic basis of head size. Catfish is the primary aquaculture species in the United States. In this study, we performed a genome-wide association study using the catfish 250K SNP array with backcross hybrid catfish to map the QTL for head size (head length, head width, and head depth). One significantly associated region on linkage group (LG) 7 was identified for head length. In addition, LGs 7, 9, and 16 contain suggestively associated regions for head length. For head width, significantly associated regions were found on LG9, and additional suggestively associated regions were identified on LGs 5 and 7. No region was found associated with head depth. Head size genetic loci were mapped in catfish to genomic regions with candidate genes involved in bone development. Comparative analysis indicated that homologs of several candidate genes are also involved in skull morphology in various other species ranging from amphibian to mammalian species, suggesting possible evolutionary conservation of those genes in the control of skull morphologies.
Collapse
|
47
|
Multiple across-strain and within-strain QTLs suggest highly complex genetic architecture for hypoxia tolerance in channel catfish. Mol Genet Genomics 2016; 292:63-76. [PMID: 27734158 DOI: 10.1007/s00438-016-1256-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Accepted: 10/03/2016] [Indexed: 10/20/2022]
Abstract
The ability to survive hypoxic conditions is important for various organisms, especially for aquatic animals. Teleost fish, representing more than 50 % of vertebrate species, are extremely efficient in utilizing low levels of dissolved oxygen in water. However, huge variations exist among various taxa of fish in their ability to tolerate hypoxia. In aquaculture, hypoxia tolerance is among the most important traits because hypoxia can cause major economic losses. Genetic enhancement for hypoxia tolerance in catfish is of great interest, but little was done with analysis of the genetic architecture of hypoxia tolerance. The objective of this study was to conduct a genome-wide association study to identify QTLs for hypoxia tolerance using the catfish 250K SNP array with channel catfish families from six strains. Multiple significant and suggestive QTLs were identified across and within strains. One significant QTL and four suggestive QTLs were identified across strains. Six significant QTLs and many suggestive QTLs were identified within strains. There were rare overlaps among the QTLs identified within the six strains, suggesting a complex genetic architecture of hypoxia tolerance. Overall, within-strain QTLs explained larger proportion of phenotypic variation than across-strain QTLs. Many of genes within these identified QTLs have known functions for regulation of oxygen metabolism and involvement in hypoxia responses. Pathway analysis indicated that most of these genes were involved in MAPK or PI3K/AKT/mTOR signaling pathways that were known to be important for hypoxia-mediated angiogenesis, cell proliferation, apoptosis and survival.
Collapse
|
48
|
Bai ZY, Han XK, Liu XJ, Li QQ, Li JL. Construction of a high-density genetic map and QTL mapping for pearl quality-related traits in Hyriopsis cumingii. Sci Rep 2016; 6:32608. [PMID: 27587236 PMCID: PMC5009340 DOI: 10.1038/srep32608] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2016] [Accepted: 08/11/2016] [Indexed: 11/22/2022] Open
Abstract
A high-density genetic map is essential for quantitative trait locus (QTL) fine mapping. In this study, 4,508 effective single nucleotide polymorphism markers (detected using specific-locus amplified fragment sequencing) and 475 microsatellites were mapped to 19 linkage groups (LGs) using a family with 157 individuals. The map spanned 2,713 cM, with an average of 259 markers and 79 loci per LG and an average inter-marker distance of 1.81 cM. To identify QTLs for pearl quality traits, 26 putatively significant QTLs were detected for 10 traits, including, three for shell width, seven for body weight, two for shell weight, two for margin mantle weight, five for inner mantle weight, and seven for shell nacre colour. Among them, five QTLs associated with shell nacre colour were mapped to LG17 and explained 19.7% to 22.8% of the trait variation; this suggests that some important genes or loci determine shell nacre colour in LG17. The linkage map and mapped QTLs for shell nacre colour would be useful for improving the quality of Hyriopsis cumingii via marker-assisted selection.
Collapse
Affiliation(s)
- Zhi-Yi Bai
- Key Laboratory of Freshwater Aquatic Genetic Resources, Shanghai Ocean University, Ministry of Agriculture, Shanghai 201306, China
- Shanghai Engineering Research Centre of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
| | - Xue-Kai Han
- Key Laboratory of Freshwater Aquatic Genetic Resources, Shanghai Ocean University, Ministry of Agriculture, Shanghai 201306, China
| | - Xiao-Jun Liu
- Key Laboratory of Freshwater Aquatic Genetic Resources, Shanghai Ocean University, Ministry of Agriculture, Shanghai 201306, China
| | - Qing-Qing Li
- Key Laboratory of Freshwater Aquatic Genetic Resources, Shanghai Ocean University, Ministry of Agriculture, Shanghai 201306, China
| | - Jia-Le Li
- Key Laboratory of Freshwater Aquatic Genetic Resources, Shanghai Ocean University, Ministry of Agriculture, Shanghai 201306, China
- Shanghai Engineering Research Centre of Aquaculture, Shanghai Ocean University, Shanghai 201306, China
- Aquaculture Division, E-Institute of Shanghai Universities, Shanghai Ocean University, Shanghai 201306, China
| |
Collapse
|
49
|
Jin Y, Zhou T, Geng X, Liu S, Chen A, Yao J, Jiang C, Tan S, Su B, Liu Z. A genome-wide association study of heat stress-associated SNPs in catfish. Anim Genet 2016; 48:233-236. [PMID: 27476875 DOI: 10.1111/age.12482] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2016] [Indexed: 10/21/2022]
Abstract
Heat tolerance is a complex and economically important trait for catfish genetic breeding programs. With global climate change, it is becoming an increasingly important trait. To better understand the molecular basis of heat stress, a genome-wide association study (GWAS) was carried out using the 250 K catfish SNP array with interspecific backcross progenies, which derived from crossing female channel catfish with male F1 hybrid catfish (female channel catfish × male blue catfish). Three significant associated SNPs were detected by performing an EMMAX approach for GWAS. The SNP located on linkage group 14 explained 12.1% of phenotypical variation. The other two SNPs, located on linkage group 16, explained 11.3 and 11.5% of phenotypical variation respectively. A total of 14 genes with heat stress related functions were detected within the significant associated regions. Among them, five genes-TRAF2, FBXW5, ANAPC2, UBR1 and KLHL29- have known functions in the protein degradation process through the ubiquitination pathway. Other genes related to heat stress include genes involved in protein biosynthesis (PRPF4 and SYNCRIP), protein folding (DNAJC25), molecule and iron transport (SLC25A46 and CLIC5), cytoskeletal reorganization (COL12A1) and energy metabolism (COX7A2, PLCB1 and PLCB4) processes. The results provide fundamental information about genes and pathways that is useful for further investigation into the molecular mechanisms of heat stress. The associated SNPs could be promising candidates for selecting heat-tolerant catfish lines after validating their effects on larger and various catfish populations.
Collapse
Affiliation(s)
- Y Jin
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - T Zhou
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - X Geng
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - S Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - A Chen
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - J Yao
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - C Jiang
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - S Tan
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - B Su
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| | - Z Liu
- The Fish Molecular Genetics and Biotechnology Laboratory, School of Fisheries, Aquaculture and Aquatic Sciences and Program of Cell and Molecular Biosciences, Aquatic Genomics Unit, Auburn University, Auburn, AL, 36849, USA
| |
Collapse
|
50
|
Huang MC, Chuang TP, Chen CH, Wu JY, Chen YT, Li LH, Yang HC. An integrated analysis tool for analyzing hybridization intensities and genotypes using new-generation population-optimized human arrays. BMC Genomics 2016; 17:266. [PMID: 27029637 PMCID: PMC4815280 DOI: 10.1186/s12864-016-2478-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 02/16/2016] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Affymetrix Axiom single nucleotide polymorphism (SNP) arrays provide a cost-effective, high-density, and high-throughput genotyping solution for population-optimized analyses. However, no public software is available for the integrated genomic analysis of hybridization intensities and genotypes for this new-generation population-optimized genotyping platform. RESULTS A set of statistical methods was developed for an integrated analysis of allele frequency (AF), allelic imbalance (AI), loss of heterozygosity (LOH), long contiguous stretch of homozygosity (LCSH), and copy number variation or alteration (CNV/CNA) on the basis of SNP probe hybridization intensities and genotypes. This study analyzed 3,236 samples that were genotyped using different SNP platforms. The proposed AF adjustment method considerably increased the accuracy of AF estimation. The proposed quick circular binary segmentation algorithm for segmenting copy number reduced the computation time of the original segmentation method by 30-67 %. The proposed CNV/CNA detection, which integrates AI and LOH/LCSH detection, had a promising true positive rate and well-controlled false positive rate in simulation studies. Moreover, our real-time quantitative polymerase chain reaction experiments successfully validated the CNVs/CNAs that were identified in the Axiom data analyses using the proposed methods; some of the validated CNVs/CNAs were not detected in the Affymetrix Array 6.0 data analysis using the Affymetrix Genotyping Console. All the analysis functions are packaged into the ALICE (AF/LOH/LCSH/AI/CNV/CNA Enterprise) software. CONCLUSIONS ALICE and the used genomic reference databases, which can be downloaded from http://hcyang.stat.sinica.edu.tw/software/ALICE.html , are useful resources for analyzing genomic data from the Axiom and other SNP arrays.
Collapse
Affiliation(s)
- Mei-Chu Huang
- Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan.,Institute of Statistical Science, Academia Sinica, No 128, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan.,Institute of Biomedical Informatics, National Yang-Ming University, Taipei, 112, Taiwan
| | - Tzu-Po Chuang
- Taiwan International Graduate Program in Molecular Medicine, National Yang-Ming University and Academia Sinica, Taipei, 115, Taiwan.,Institute of Biochemistry and Molecular Biology, National Yang-Ming University, Taipei, 112, Taiwan
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan
| | - Ling-Hui Li
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan.
| | - Hsin-Chou Yang
- Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan. .,Institute of Statistical Science, Academia Sinica, No 128, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan. .,Institute of Public Health, National Yang Ming University, Taipei, 112, Taiwan. .,Department of Statistics, National Cheng Kung University, Tainan, 701, Taiwan. .,Institute of Statistics, National Tsing Hua University, Hsinchu, 300, Taiwan. .,School of Public Health, National Defense Medical Center, Taipei, 114, Taiwan.
| |
Collapse
|