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Evaluation of nine statistics to identify QTLs in bulk segregant analysis using next generation sequencing approaches.

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  • Additional Information
    • Source:
      Publisher: BioMed Central Country of Publication: England NLM ID: 100965258 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2164 (Electronic) Linking ISSN: 14712164 NLM ISO Abbreviation: BMC Genomics Subsets: MEDLINE
    • Publication Information:
      Original Publication: London : BioMed Central, [2000-
    • Subject Terms:
    • Abstract:
      Background: Bulk segregant analysis (BSA) combined with next generation sequencing is a powerful tool to identify quantitative trait loci (QTL). The impact of the size of the study population and the percentage of extreme genotypes analysed have already been assessed. But a good comparison of statistical approaches designed to identify QTL regions using next generation sequencing (NGS) technologies for BSA is still lacking.
      Results: We developed an R code to simulate QTLs in bulks of F2 contrasted lines. We simulated a range of recombination rates based on estimations using different crop species. The simulations were used to benchmark the ability of statistical methods identify the exact location of true QTLs. A single QTL led to a shift in allele frequency across a large fraction of the chromosome for plant species with low recombination rate. The smoothed version of all statistics performed best notably the smoothed Euclidean distance-based statistics was always found to be more accurate in identifying the location of QTLs. We propose a simulation approach to build confidence interval statistics for the detection of QTLs.
      Conclusion: We highlight the statistical methods best suited for BSA studies using NGS technologies in crops even when recombination rate is low. We also provide simulation codes to build confidence intervals and to assess the impact of recombination for application to other studies. This computational study will help select NGS-based BSA statistics that are useful to the broad scientific community.
      (© 2022. The Author(s).)
    • References:
      Theor Appl Genet. 2021 Apr;134(4):1015-1031. (PMID: 33388885)
      Theor Appl Genet. 2021 Feb;134(2):743-754. (PMID: 33270143)
      BMC Plant Biol. 2012 Jan 26;12:14. (PMID: 22280551)
      PLoS Comput Biol. 2011 Nov;7(11):e1002255. (PMID: 22072954)
      Genetics. 2016 Nov;204(3):1295-1306. (PMID: 27655945)
      Genome Res. 2013 Apr;23(4):687-97. (PMID: 23299975)
      Methods Mol Biol. 2014;1127:291-303. (PMID: 24643569)
      BMC Plant Biol. 2019 Sep 11;19(1):398. (PMID: 31510927)
      Trends Plant Sci. 2019 Mar;24(3):263-274. (PMID: 30573308)
      Plant Sci. 2020 Dec;301:110669. (PMID: 33218635)
      Mol Genet Genomics. 2018 Apr;293(2):463-477. (PMID: 29188438)
      Theor Appl Genet. 2020 May;133(5):1791-1810. (PMID: 32040676)
      Nature. 2010 Apr 15;464(7291):1039-42. (PMID: 20393561)
      Bioinformatics. 2020 Apr 1;36(7):2150-2156. (PMID: 31742317)
      Sci Rep. 2020 Oct 29;10(1):18643. (PMID: 33122674)
      Front Plant Sci. 2020 Apr 03;11:303. (PMID: 32308659)
      Theor Appl Genet. 2014 Jul;127(7):1491-9. (PMID: 24845123)
      Curr Biol. 2018 Jul 23;28(14):2274-2282.e6. (PMID: 29983312)
      Nat Rev Genet. 2014 Nov;15(11):749-63. (PMID: 25246196)
      Mol Plant. 2019 Mar 4;12(3):426-437. (PMID: 30597214)
      PLoS One. 2013 Jul 30;8(7):e68433. (PMID: 23935868)
      PLoS One. 2015 Mar 18;10(3):e0119873. (PMID: 25785447)
      BMC Genomics. 2016 Mar 15;17:236. (PMID: 26980001)
      Plant J. 2013 Apr;74(1):174-83. (PMID: 23289725)
      DNA Res. 2015 Jun;22(3):193-203. (PMID: 25922536)
      PLoS One. 2018 Sep 28;13(9):e0200617. (PMID: 30265662)
      Nat Rev Genet. 2009 Aug;10(8):565-77. (PMID: 19584810)
      Theor Appl Genet. 2017 Jan;130(1):199-211. (PMID: 27714417)
      BMC Bioinformatics. 2020 Mar 6;21(1):99. (PMID: 32143574)
      Gigascience. 2017 Feb 1;6(2):1-8. (PMID: 28369461)
      G3 (Bethesda). 2016 Oct 13;6(10):3129-3138. (PMID: 27543295)
      Rice (N Y). 2017 Dec;10(1):8. (PMID: 28321828)
      Genetics. 2007 Jun;176(2):1187-96. (PMID: 17435243)
      Plant Genome. 2018 Jul;11(2):. (PMID: 30025013)
      Front Plant Sci. 2021 Feb 05;11:593207. (PMID: 33613580)
      Front Plant Sci. 2014 Sep 30;5:484. (PMID: 25324846)
      Nucleic Acids Res. 1991 Dec 11;19(23):6553-8. (PMID: 1684420)
      Mol Ecol. 2016 Sep;25(17):4177-96. (PMID: 27454560)
      Plant Biotechnol J. 2019 Jan;17(1):275-288. (PMID: 29890030)
      Hortic Res. 2017 Oct 04;4:17053. (PMID: 29118994)
      G3 (Bethesda). 2015 Nov 03;6(1):67-77. (PMID: 26530422)
      Plant Genome. 2016 Mar;9(1):. (PMID: 27898754)
      Heredity (Edinb). 2010 Sep;105(3):257-67. (PMID: 20461101)
      Trends Plant Sci. 2011 May;16(5):282-8. (PMID: 21439889)
      Plant J. 2015 Nov;84(3):587-96. (PMID: 26386250)
      Front Plant Sci. 2021 Feb 16;12:604709. (PMID: 33664756)
      Nat Rev Genet. 2014 Feb;15(2):121-32. (PMID: 24434847)
      Plant Biotechnol J. 2018 Feb 6;:. (PMID: 29406565)
      Plant Biotechnol J. 2016 Nov;14(11):2110-2119. (PMID: 27107184)
      Plant Biotechnol J. 2015 Jun;13(5):613-24. (PMID: 25382230)
      Proc Natl Acad Sci U S A. 1991 Nov 1;88(21):9828-32. (PMID: 1682921)
      BMC Plant Biol. 2019 Oct 8;19(1):412. (PMID: 31590656)
      BMC Bioinformatics. 2016 Mar 11;17:125. (PMID: 26968756)
      Plant Biotechnol J. 2016 Oct;14(10):1941-55. (PMID: 26990124)
      Genet Epidemiol. 2010 Jul;34(5):479-91. (PMID: 20552648)
      Nat Methods. 2008 Mar;5(3):247-52. (PMID: 18297082)
      Int J Mol Sci. 2020 Mar 21;21(6):. (PMID: 32245192)
      Nat Genet. 2006 Feb;38(2):203-8. (PMID: 16380716)
      Sci Rep. 2020 Jan 8;10(1):25. (PMID: 31913328)
      Nature. 2005 Aug 11;436(7052):793-800. (PMID: 16100779)
    • Contributed Indexing:
      Keywords: BSA; BSA-Seq; Confidence interval; NGS; QTL; Simulation; Statistics
    • Publication Date:
      Date Created: 20220706 Date Completed: 20220708 Latest Revision: 20220716
    • Publication Date:
      20220908
    • Accession Number:
      PMC9258084
    • Accession Number:
      10.1186/s12864-022-08718-y
    • Accession Number:
      35794552