Skip to main content
SpringerLink
Log in

Genomic Prediction of Columnaris Disease Resistance in Catfish

  • Original Article
  • Published:
Marine Biotechnology Aims and scope Submit manuscript

Abstract

Catfish is an important aquaculture species in the USA. Columnaris disease is distributed worldwide, affecting a wide variety of fish species including catfish . It leads to huge economic losses each year to the US catfish industry. Channel catfish in general is highly resistant to the disease, while blue catfish is highly susceptible. Genomic selection is an effective and accurate way to predict the breeding values and thus was expected to improve the prediction veracity of columnaris disease resistance in catfish effectively. In this study, two different methods, elastic net genomic best linear unbiased prediction (ENGBLUP) and genomic best linear unbiased prediction (GBLUP), were used to predict the columnaris disease resistance evaluated by binary survival status. Cross-validation showed that the prediction accuracy of ENGBLUP and GBLUP was 0.7347 and 0.4868, respectively, showing that ENGBLUP had a high prediction accuracy. It was shown that fitting QTL and polygenic effect with different distribution will improve genomic prediction accuracy for binary traits. In this study, an accurate and effective genomic selection method was proposed to predict the columnaris resistance in catfish, and its application should be beneficial to catfish breeding.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Arias CR, Cai W, Peatman E, Bullard SA (2012) Catfish hybrid Ictalurus punctatus× I. furcatus exhibits higher resistance to columnaris disease than the parental species. Dis Aquat Org 100:77–81

    Article  Google Scholar 

  • Bangera R, Correa K, Lhorente JP, Figueroa R, Yáñez JM (2017) Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar). BMC Genomics 18:121

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bebak J, Wagner B (2012) Use of vaccination against enteric septicemia of catfish and columnaris disease by the US catfish industry. J Aquat Anim Health 24:30–36

    Article  CAS  PubMed  Google Scholar 

  • Bernardet JF, Bowman JP (2006) In: Dworkin M, Falkow S, Rosenberg E, Schleifer KH, Stackebrandt E (eds) The genus Flavobacterium. New York, Springer

    Chapter  Google Scholar 

  • Bilodeau-Bourgeois AL, Bosworth BG, Wolters WR (2007) Reductions in susceptibility of channel catfish, Ictalurus punctatus, to enteric septicemia of catfish through two generations of selection. J World Aquacult Soc 38:450–453

    Article  Google Scholar 

  • Chamberlain AJ, Mcpartlan HC, Goddard ME (2007) The number of loci that affect milk production traits in dairy cattle. Genetics 177:1117–1123

    Article  PubMed  PubMed Central  Google Scholar 

  • Cros D, Denis M, Sánchez L, Cochard B, Flori A, Durand-Gasselin T, Nouy B, Omoré A, Pomiès V, Riou V, Suryana E, Bouvet JM (2015) Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.). Theor Appl Genet 128:397–410

    Article  PubMed  Google Scholar 

  • Darvasi A, Soller M (1992) Selective genotyping for determination of linkage between a marker locus and a quantitative trait locus. Theor Appl Genet 85:353–359

    Article  CAS  PubMed  Google Scholar 

  • de Campos CF, Lopes MS, E Silva FF, Veroneze R, Knol EF, Lopes PS, Guimaraes SE (2015) Genomic selection for boar taint compounds and carcass traits in a commercial pig population. Livest Sci 174:10–17

    Article  Google Scholar 

  • Declercq AM, Haesebrouck F, Den Broeck WV, Bossier P, Decostere A (2013) Columnaris disease in fish: a review with emphasis on bacterium-host interactions. Vet Res 44:27

    Article  PubMed  PubMed Central  Google Scholar 

  • Decostere A, Haesebrouck F, Devriese L (1998) Characterization of four Flavobacterium columnare (Flexibacter columnaris) strains isolated from tropical fish. Vet Microbiol 62:35–45

    Article  CAS  PubMed  Google Scholar 

  • Desta ZA, Ortiz R (2014) Genomic selection: genome-wide prediction in plant improvement. Trends Plant Sci 19:592–601

    Article  CAS  PubMed  Google Scholar 

  • Dong L, Xiao S, Chen J, Wan L, Wang Z (2016) Genomic selection using extreme phenotypes and pre-selection of SNPs in large yellow croaker (Larimichthys crocea). Mar Biotechnol 18:575–583

    Article  CAS  Google Scholar 

  • Dunham RA (2011) Aquaculture and fisheries biotechnology: genetic approaches. CABI, Wallingford

    Book  Google Scholar 

  • Dunham RA, Elaswad A (2018) Catfish biology and farming. Annu Rev Anim Biosci 6:305–325

    Article  PubMed  Google Scholar 

  • Dunham RA, Warr GW, Nichols A, Duncan PL, Argue BJ, Middleton DL, Kucuktas H (2002) Enhanced bacterial disease resistance of transgenic channel catfish Ictalurus punctatus possessing cecropin genes. Mar Biotechnol 4:338–344

    Article  CAS  Google Scholar 

  • Elaswad A, Dunham R (2018) Disease reduction in aquaculture with genetic and genomic technology: current and future approaches. Rev Aquacult 10:876–898

    Article  Google Scholar 

  • Fernando RL, Grossman M (1989) Marker assisted selection using best linear unbiased prediction. Genet Sel Evol 21:467

    Article  PubMed Central  Google Scholar 

  • Fuji K, Kobayashi K, Hasegawa O, Coimbra MRM, Sakamoto T, Okamoto N (2006) Identification of a single major genetic locus controlling the resistance to lymphocystis disease in Japanese flounder (Paralichthys olivaceus). Aquaculture 254:203–210

    Article  CAS  Google Scholar 

  • Geng X, Sha J, Liu S, Bao L, Zhang J, Wang R, Yao J, Li C, Feng J, Sun F, Sun L, Jiang C, Zhang Y, Chen A, Dunham RA, Zhi D, Liu Z (2015) A genome-wide association study in catfish reveals the presence of functional hubs of related genes within QTLs for columnaris disease resistance. BMC Genomics 16:196

    Article  PubMed  PubMed Central  Google Scholar 

  • Goddard ME, Hayes BJ (2007) Genomic selection. J Anim Breed Genet 124:323–330

    Article  CAS  PubMed  Google Scholar 

  • Houston RD, Haley CS, Hamilton A, Guy DR, Tinch AE, Taggart JB, Mcandrew BJ, Bishop S (2008) Major quantitative trait loci affect resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar). Genetics 178:1109–1115

    Article  PubMed  PubMed Central  Google Scholar 

  • Knol EF, Nielsen B, Knap P (2016) Genomic selection in commercial pig breeding. Anim Front 6:15–22

    Article  Google Scholar 

  • Legarra A, Calenge F, Mariani P, Velge P, Beaumont C (2011) Use of a reduced set of single nucleotide polymorphisms for genetic evaluation of resistance to Salmonella carrier state in laying hens. Poult Sci 90:731–736

    Article  CAS  PubMed  Google Scholar 

  • Li H, Wang J, Bao Z (2015) A novel genomic selection method combining GBLUP and LASSO. Genetica 143:299–304

    Article  CAS  PubMed  Google Scholar 

  • Li H, Su G, Jiang L, Bao Z (2017) An efficient unified model for genome-wide association studies and genomic selection. Genet Sel Evol 49:64

    Article  PubMed  PubMed Central  Google Scholar 

  • Liu Y, Lu S, Liu F, Shao C, Zhou Q, Wang N, Li Y, Yang Y, Zhang Y, Sun H, Zheng W, Chen S (2018) Genomic selection using BayesCπ and GBLUP for resistance against Edwardsiella tarda in Japanese flounder (Paralichthys olivaceus). Mar Biotechnol 20:559–565

    Article  CAS  Google Scholar 

  • Longin CF, Mi X, Würschum T (2015) Genomic selection in wheat: optimum allocation of test resources and comparison of breeding strategies for line and hybrid breeding. Theor Appl Genet 128:1297–1306

    Article  PubMed  Google Scholar 

  • Madsen P, Jensen J (2013) A User's guide to DMU. A package for analyzing multivariate mixed models. http://dmu.agrsci.dk/DMU/Doc/Current/dmuv6_guide.5.2.pdf. Accessed 7 July 2017

  • Meuwissen T, Hayes B, Goddard M (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Meuwissen T, Hayes B, Goddard M (2013) Accelerating improvement of livestock with genomic selection. Annu Rev Anim Biosci 1:221–237

    Article  PubMed  CAS  Google Scholar 

  • Moen T, Baranski M, Sonesson AK, Kjøglum S (2009) Confirmation and fine-mapping of a major QTL for resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar): population-level associations between markers and trait. BMC Genomics 10:368

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Mohammed H, Olivares-Fuster O, Lafrentz S, Arias CR (2013) New attenuated vaccine against columnaris disease in fish: choosing the right parental strain is critical for vaccine efficacy. Vaccine 31:5276–5280

    Article  CAS  PubMed  Google Scholar 

  • Morley N, Lewis J (2010) Consequences of an outbreak of columnaris disease (Flavobacterium columnare) to the helminth fauna of perch (Perca fluviatilis) in the queen Mary reservoir, south-east England. J Helminthol 84:186–192

    Article  CAS  PubMed  Google Scholar 

  • Nguyen TT, Bowman PJ, Haile-Mariam M, Pryce JE, Hayes BJ (2016) Genomic selection for tolerance to heat stress in Australian dairy cattle. J Dairy Sci 99:2849–2862

    Article  CAS  PubMed  Google Scholar 

  • Ozaki A, Araki K, Okamoto H, Okauchi M, Mushiake K, Yoshida K, Tsuzaki T, Fuji K, Sakamoto T, Okamoto N (2012) Progress of DNA marker-assisted breeding in maricultured finfish. Bull Fish Res Agen 35:31–37

    Google Scholar 

  • Shumbusho F, Raoul J, Astruc JM, Palhiere I, Lemarié S, Fugeray-Scarbel A, Elsen JM (2016) Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program. Animal 10:1033–1041

    Article  CAS  PubMed  Google Scholar 

  • Soto E, Mauel MJ, Karsi A, Lawrence M (2008) Genetic and virulence characterization of Flavobacterium columnare from channel catfish (Ictalurus punctatus). J Appl Microbiol 104:1302–1310

    Article  CAS  PubMed  Google Scholar 

  • Stranden I, Christensen OF (2011) Allele coding in genomic evaluation. Genet Sel Evol 43:25–25

    Article  PubMed  PubMed Central  Google Scholar 

  • Sun F, Peatman E, Li C, Liu S, Jiang Y, Zhou Z, Liu Z (2012) Transcriptomic signatures of attachment, NF-κB suppression and IFN stimulation in the catfish gill following columnaris bacterial infection. Dev Comp Immunol 38:169–180

    Article  CAS  PubMed  Google Scholar 

  • Usai MG, Goddard ME, Hayes BJ (2009) LASSO with cross-validation for genomic selection. Genet Res 91:427–436

    Article  CAS  Google Scholar 

  • VanRaden PM (2008) Efficient methods to compute genomic predictions. J Dairy Sci 91:4414–4423

    Article  CAS  PubMed  Google Scholar 

  • Wang Q, Yu Y, Zhang Q, Zhang X, Huang H, Xiang J, Li F (2019) Evaluation on the genomic selection in Litopenaeus vannamei for the resistance against Vibrio parahaemolyticus. Aquaculture 505:212–216

    Article  Google Scholar 

  • Wolc A, Stricker C, Arango J, Settar P, Fulton JE, Osullivan NP, Dekkers JC (2011) Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model. Genet Sel Evol 43:5

    Article  PubMed  PubMed Central  Google Scholar 

  • Wolters WR, Wise DJ, Klesius PH (1996) Survival and antibody response of channel catfish, blue catfish, and channel catfish female× blue catfish male hybrids after exposure to Edwardsiella ictaluri. J Aquat Anim Health 8:249–254

    Article  Google Scholar 

  • Xu S, Zhu D, Zhang Q (2014) Predicting hybrid performance in rice using genomic best linear unbiased prediction. Proc Natl Acad Sci U S A 111:12456–12461

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yang J, Benyamin B, Mcevoy BP, Gordon SD, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42:565–569

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This research was financially supported by Special Scientific Research Funds for Central Non-profit Institutes, Chinese Academy of Fishery Sciences (2016ZD0203).

Author information

Authors and Affiliations

  1. Key Laboratory of Aquatic Genomics, Ministry of Agriculture and Rural Affairs, CAFS Key Laboratory of Aquatic Genomics and Beijing Key Laboratory of Fishery Biotechnology, Chinese Academy of Fishery Sciences, Beijing, 100141, China

    Yaqun Zhang & Hengde Li

  2. Department of Biology, Syracuse University, Syracuse, NY, USA

    Zhanjiang Liu

Authors
  1. Yaqun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhanjiang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hengde Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Zhanjiang Liu or Hengde Li.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflicts of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Liu, Z. & Li, H. Genomic Prediction of Columnaris Disease Resistance in Catfish. Mar Biotechnol 22, 145–151 (2020). https://doi.org/10.1007/s10126-019-09941-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10126-019-09941-7

Keywords

Search

Navigation