Parentage Analysis in Giant Grouper () Using Microsatellite and SNP Markers from Genotyping-by-Sequencing Data.

Zhuoying Weng, Yang Yang, Xi Wang, Lina Wu, Sijie Hua, Hanfei Zhang, Zining Meng
Author Information
  1. Zhuoying Weng: State Key Laboratory of Biocontrol, Guangdong Province Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China.
  2. Yang Yang: State Key Laboratory of Biocontrol, Guangdong Province Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China.
  3. Xi Wang: State Key Laboratory of Biocontrol, Guangdong Province Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China.
  4. Lina Wu: State Key Laboratory of Biocontrol, Guangdong Province Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China.
  5. Sijie Hua: State Key Laboratory of Biocontrol, Guangdong Province Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China.
  6. Hanfei Zhang: State Key Laboratory of Biocontrol, Guangdong Province Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China.
  7. Zining Meng: State Key Laboratory of Biocontrol, Guangdong Province Key Laboratory for Aquatic Economic Animals, School of Life Sciences, Sun Yat-Sen University, Guangzhou 510275, China.

Abstract

Pedigree information is necessary for the maintenance of diversity for wild and captive populations. Accurate pedigree is determined by molecular marker-based parentage analysis, which may be influenced by the polymorphism and number of markers, integrity of samples, relatedness of parents, or different analysis programs. Here, we described the first development of 208 single nucleotide polymorphisms (SNPs) and 11 microsatellites for giant grouper () taking advantage of Genotyping-by-sequencing (GBS), and compared the power of SNPs and microsatellites for parentage and relatedness analysis, based on a mixed family composed of 4 candidate females, 4 candidate males and 289 offspring. CERVUS, PAPA and COLONY were used for mutually verification. We found that SNPs had a better potential for relatedness estimation, exclusion of non-parentage and individual identification than microsatellites, and > 98% accuracy of parentage assignment could be achieved by 100 polymorphic SNPs (MAF cut-off < 0.4) or 10 polymorphic microsatellites (mean H = 0.821, mean PIC = 0.651). This study provides a reference for the development of molecular markers for parentage analysis taking advantage of next-generation sequencing, and contributes to the molecular breeding, fishery management and population conservation.

Keywords

References

  1. Mol Ecol. 2003 Oct;12(10):2511-23 [PMID: 12969458]
  2. Theor Appl Genet. 2018 Mar;131(3):703-720 [PMID: 29264625]
  3. Evol Appl. 2014 Apr;7(4):480-92 [PMID: 24822082]
  4. Mol Ecol Resour. 2011 Mar;11 Suppl 1:150-61 [PMID: 21429171]
  5. Mol Ecol Resour. 2008 Jul;8(4):805-7 [PMID: 21585897]
  6. Nat Rev Genet. 2011 Jun 17;12(7):499-510 [PMID: 21681211]
  7. Ecol Evol. 2020 Apr 03;10(10):4483-4494 [PMID: 32489612]
  8. Bioinformatics. 2012 Jan 15;28(2):298-9 [PMID: 22110245]
  9. BMC Genomics. 2019 Dec 27;20(1):1026 [PMID: 31881838]
  10. Ecol Evol. 2020 Aug 10;10(17):9522-9531 [PMID: 32953080]
  11. Front Genet. 2019 Jun 19;10:597 [PMID: 31275363]
  12. Genetics. 2006 Apr;172(4):2567-82 [PMID: 16387880]
  13. Genet Mol Res. 2011 Dec 12;10(4):4006-11 [PMID: 22194200]
  14. Mol Biol Rep. 2016 Jun;43(6):541-8 [PMID: 27059503]
  15. Mar Biotechnol (NY). 2019 Oct;21(5):707-717 [PMID: 31392592]
  16. G3 (Bethesda). 2020 Jun 1;10(6):2069-2078 [PMID: 32312839]
  17. Genetics. 2002 Mar;160(3):1203-15 [PMID: 11901134]
  18. Mol Ecol. 2004 Nov;13(11):3261-73 [PMID: 15487987]
  19. PLoS One. 2011 May 04;6(5):e19379 [PMID: 21573248]
  20. Mol Ecol Resour. 2015 May;15(3):557-61 [PMID: 25186958]
  21. PLoS One. 2012;7(2):e32253 [PMID: 22389690]
  22. Heredity (Edinb). 2007 Aug;99(2):205-17 [PMID: 17487215]
  23. Mol Ecol Resour. 2017 Mar;17(2):183-193 [PMID: 27488248]
  24. Mol Ecol Resour. 2018 Feb 17;: [PMID: 29455472]
  25. Genet Mol Biol. 2013 Jul;36(2):185-91 [PMID: 23885200]
  26. PLoS One. 2014 Apr 16;9(4):e93392 [PMID: 24740141]
  27. Biology (Basel). 2021 Jan 07;10(1): [PMID: 33430356]
  28. Rev Aquac. 2018 Aug;10(3):670-682 [PMID: 30220910]
  29. Bioinformatics. 2019 May 15;35(10):1786-1788 [PMID: 30321304]
  30. Mol Ecol. 2019 Feb;28(3):544-567 [PMID: 30575167]
  31. Genes (Basel). 2019 Aug 31;10(9): [PMID: 31480436]
  32. Mol Ecol Resour. 2018 Nov;18(6):1263-1281 [PMID: 29870119]
  33. Bioinformatics. 2011 Nov 1;27(21):2987-93 [PMID: 21903627]
  34. Anim Genet. 2008 Oct;39(5):474-9 [PMID: 18573124]
  35. Bioinformatics. 2011 Aug 1;27(15):2156-8 [PMID: 21653522]
  36. Mar Drugs. 2014 Apr 30;12(5):2397-407 [PMID: 24796300]
  37. Nat Methods. 2012 Mar 04;9(4):357-9 [PMID: 22388286]
  38. Front Genet. 2019 Nov 12;10:1127 [PMID: 31781174]
  39. Bioinformatics. 2005 Jan 15;21(2):263-5 [PMID: 15297300]
  40. Heredity (Edinb). 2020 May;124(5):633-646 [PMID: 32123330]
  41. Mol Ecol. 2005 Feb;14(2):599-612 [PMID: 15660949]
  42. Int J Legal Med. 2001;114(4-5):204-10 [PMID: 11355396]
  43. Mol Ecol. 2007 Mar;16(5):1099-106 [PMID: 17305863]
  44. Mol Ecol Resour. 2010 May;10(3):551-5 [PMID: 21565056]
  45. Theor Popul Biol. 2012 Mar;81(2):131-43 [PMID: 22200649]
  46. Am J Hum Genet. 2007 Sep;81(3):559-75 [PMID: 17701901]
  47. Theor Popul Biol. 2006 Nov;70(3):300-21 [PMID: 16388833]
  48. Ecol Evol. 2019 Jun 11;9(12):7017-7029 [PMID: 31380030]
  49. Genet Mol Res. 2015 Feb 13;14(1):1362-70 [PMID: 25730075]
  50. Mol Ecol Resour. 2010 Jan;10(1):6-30 [PMID: 21564987]
  51. Theor Appl Genet. 2003 Feb;106(3):411-22 [PMID: 12589540]
  52. Bioinformatics. 2009 Aug 15;25(16):2078-9 [PMID: 19505943]
  53. Anim Genet. 2014 Feb;45(1):142-3 [PMID: 24033517]
  54. Mol Ecol. 2003 Apr;12(4):1039-47 [PMID: 12753222]
  55. Nucleic Acids Res. 1989 Aug 25;17(16):6463-71 [PMID: 2780284]

MeSH Term

Animals
Aquaculture
Bass
Female
Genotype
Genotyping Techniques
High-Throughput Nucleotide Sequencing
Male
Microsatellite Repeats
Pedigree
Polymorphism, Single Nucleotide

Word Cloud

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