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Cost-effectively dissecting the genetic architecture of complex wool traits in rabbits by low-coverage sequencing.
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- Additional Information
- Source:
Publisher: BioMed Central Country of Publication: France NLM ID: 9114088 Publication Model: Electronic Cited Medium: Internet ISSN: 1297-9686 (Electronic) Linking ISSN: 0999193X NLM ISO Abbreviation: Genet Sel Evol Subsets: MEDLINE
- Publication Information:
Publication: London : BioMed Central
Original Publication: Paris : Elsevier, c1989-
- Subject Terms:
- Abstract:
Background: Rabbit wool traits are important in fiber production and for model organism research on hair growth, but their genetic architecture remains obscure. In this study, we focused on wool characteristics in Angora rabbits, a breed well-known for the quality of its wool. Considering the cost to generate population-scale sequence data and the biased detection of variants using chip data, developing an effective genotyping strategy using low-coverage whole-genome sequencing (LCS) data is necessary to conduct genetic analyses.
Results: Different genotype imputation strategies (BaseVar + STITCH, Bcftools + Beagle4, and GATK + Beagle5), sequencing coverages (0.1X, 0.5X, 1.0X, 1.5X, and 2.0X), and sample sizes (100, 200, 300, 400, 500, and 600) were compared. Our results showed that using BaseVar + STITCH at a sequencing depth of 1.0X with a sample size larger than 300 resulted in the highest genotyping accuracy, with a genotype concordance higher than 98.8% and genotype accuracy higher than 0.97. We performed multivariate genome-wide association studies (GWAS), followed by conditional GWAS and estimation of the confidence intervals of quantitative trait loci (QTL) to investigate the genetic architecture of wool traits. Six QTL were detected, which explained 0.4 to 7.5% of the phenotypic variation. Gene-level mapping identified the fibroblast growth factor 10 (FGF10) gene as associated with fiber growth and diameter, which agrees with previous results from functional data analyses on the FGF gene family in other species, and is relevant for wool rabbit breeding.
Conclusions: We suggest that LCS followed by imputation can be a cost-effective alternative to array and high-depth sequencing for assessing common variants. GWAS combined with LCS can identify new QTL and candidate genes that are associated with quantitative traits. This study provides a cost-effective and powerful method for investigating the genetic architecture of complex traits, which will be useful for genomic breeding applications.
(© 2022. The Author(s).)
- References:
Bioinformatics. 2009 Jul 15;25(14):1754-60. (PMID: 19451168)
Science. 2019 Dec 6;366(6470):1218-1225. (PMID: 31672914)
J Proteomics. 2020 Aug 15;225:103853. (PMID: 32534213)
Nature. 2017 Jul 13;547(7662):173-178. (PMID: 28658209)
Nat Genet. 2016 Aug;48(8):912-8. (PMID: 27376238)
Inflamm Regen. 2020 Sep 21;40:35. (PMID: 32973962)
Am J Hum Genet. 2007 Nov;81(5):1084-97. (PMID: 17924348)
J Dairy Sci. 2022 Apr;105(4):3355-3366. (PMID: 35151474)
Sci Rep. 2016 Nov 28;6:38073. (PMID: 27892541)
Biomed Res Int. 2015;2015:730139. (PMID: 25685806)
Wiad Lek. 2001;54(1-2):11-8. (PMID: 11344694)
Nat Protoc. 2009;4(1):44-57. (PMID: 19131956)
Nat Genet. 2016 Aug;48(8):965-969. (PMID: 27376236)
Cell. 2021 Jun 24;184(13):3542-3558.e16. (PMID: 34051138)
Mol Biol Evol. 2013 Sep;30(9):2224-34. (PMID: 23777627)
Am J Hum Genet. 2018 Sep 6;103(3):338-348. (PMID: 30100085)
Front Genet. 2021 Nov 03;12:728764. (PMID: 34804115)
Genome Res. 2010 Sep;20(9):1297-303. (PMID: 20644199)
Bioinformatics. 2014 Aug 1;30(15):2114-20. (PMID: 24695404)
Genet Sel Evol. 2017 Oct 25;49(1):78. (PMID: 29070022)
Genet Sel Evol. 2018 Dec 13;50(1):64. (PMID: 30545283)
Cell Stem Cell. 2009 Feb 6;4(2):155-69. (PMID: 19200804)
Gigascience. 2015 Feb 25;4:7. (PMID: 25722852)
Nat Genet. 2021 Jul;53(7):1104-1111. (PMID: 34083788)
Cell Rep. 2019 Jun 18;27(12):3413-3421.e3. (PMID: 31216464)
Cell. 2018 Oct 4;175(2):347-359.e14. (PMID: 30290141)
Bioinformatics. 2019 Aug 1;35(15):2555-2561. (PMID: 30576415)
J Diabetes Res. 2013;2013:906590. (PMID: 23710470)
Cell. 2019 Mar 21;177(1):184-199. (PMID: 30901539)
BMC Genomics. 2021 Mar 20;22(1):197. (PMID: 33743587)
Nucleic Acids Res. 2010 Sep;38(16):e164. (PMID: 20601685)
Bioinformatics. 2019 May 15;35(10):1786-1788. (PMID: 30321304)
Am J Hum Genet. 2016 Jan 7;98(1):116-26. (PMID: 26748515)
BMC Complement Altern Med. 2016 Jul 07;16:187. (PMID: 27386946)
New Phytol. 2019 Aug;223(3):1489-1504. (PMID: 31066055)
BMC Biol. 2021 Sep 9;19(1):197. (PMID: 34503498)
Am J Hum Genet. 2011 Jan 7;88(1):76-82. (PMID: 21167468)
Genet Mol Res. 2017 Mar 22;16(1):. (PMID: 28340264)
Exp Mol Med. 2018 May 22;50(5):1-10. (PMID: 29789565)
Bioinformatics. 2011 Nov 1;27(21):2987-93. (PMID: 21903627)
BMC Genomics. 2020 Jan 13;21(1):41. (PMID: 31931710)
Bioinformatics. 2011 Aug 1;27(15):2156-8. (PMID: 21653522)
Development. 2005 Jul;132(13):2981-90. (PMID: 15930103)
Nat Commun. 2020 Nov 19;11(1):5900. (PMID: 33214558)
J Dermatol Sci. 2007 Jun;46(3):189-98. (PMID: 17374475)
Science. 2014 Aug 29;345(6200):1074-1079. (PMID: 25170157)
Nat Rev Genet. 2010 Jul;11(7):499-511. (PMID: 20517342)
Anim Sci J. 2016 Feb;87(2):159-67. (PMID: 26260584)
Philos Trans R Soc Lond B Biol Sci. 2020 Sep 28;375(1808):20190601. (PMID: 32772666)
Am J Hum Genet. 2007 Sep;81(3):559-75. (PMID: 17701901)
Am J Hum Genet. 2021 Apr 1;108(4):656-668. (PMID: 33770507)
Hum Genet. 2020 Jun;139(6-7):723-732. (PMID: 32285198)
Genetics. 2017 May;206(1):91-104. (PMID: 28348060)
Genome Res. 2009 Sep;19(9):1655-64. (PMID: 19648217)
Nat Genet. 2021 Jan;53(1):120-126. (PMID: 33414550)
Anim Reprod Sci. 2015 Dec;163:30-4. (PMID: 26498507)
PLoS One. 2015 Oct 12;10(10):e0137601. (PMID: 26458263)
Hum Mol Genet. 2016 Jun 1;25(11):2360-2365. (PMID: 27146844)
J Dairy Sci. 2008 Nov;91(11):4414-23. (PMID: 18946147)
Proc Natl Acad Sci U S A. 2021 Jun 22;118(25):. (PMID: 34155138)
Clin Cosmet Investig Dermatol. 2016 May 17;9:127-34. (PMID: 27274299)
Gigascience. 2021 Jul 20;10(7):. (PMID: 34282453)
FASEB J. 2010 Oct;24(10):3869-81. (PMID: 20522784)
- Grant Information:
SDAIT-21-02 Shandong Province Special Economic Animal Innovation Team; 2021LZGC002 Agricultural Improved Seed Project of Shandong Province; 2020M682217 China Postdoctoral Science Foundation; ZR2020QC175 Shandong Provincial Natural Science Foundation; ZR2020QC176 Shandong Provincial Natural Science Foundation; 32102526 National Natural Science Foundation of China; 32002172 National Natural Science Foundation of China
- Publication Date:
Date Created: 20221119 Date Completed: 20221123 Latest Revision: 20221123
- Publication Date:
20221213
- Accession Number:
PMC9673297
- Accession Number:
10.1186/s12711-022-00766-y
- Accession Number:
36401180
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