Literature DB >> 35100395

Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing.

Stuart J Macdonald1,2, Kristen M Cloud-Richardson1, Dylan J Sims-West1, Anthony D Long3.   

Abstract

Despite the value of recombinant inbred lines for the dissection of complex traits, large panels can be difficult to maintain, distribute, and phenotype. An attractive alternative to recombinant inbred lines for many traits leverages selecting phenotypically extreme individuals from a segregating population, and subjecting pools of selected and control individuals to sequencing. Under a bulked or extreme segregant analysis paradigm, genomic regions contributing to trait variation are revealed as frequency differences between pools. Here, we describe such an extreme quantitative trait locus, or extreme quantitative trait loci, mapping strategy that builds on an existing multiparental population, the Drosophila Synthetic Population Resource, and involves phenotyping and genotyping a population derived by mixing hundreds of Drosophila Synthetic Population Resource recombinant inbred lines. Simulations demonstrate that challenging, yet experimentally tractable extreme quantitative trait loci designs (≥4 replicates, ≥5,000 individuals/replicate, and selecting the 5-10% most extreme animals) yield at least the same power as traditional recombinant inbred line-based quantitative trait loci mapping and can localize variants with sub-centimorgan resolution. We empirically demonstrate the effectiveness of the approach using a 4-fold replicated extreme quantitative trait loci experiment that identifies 7 quantitative trait loci for caffeine resistance. Two mapped extreme quantitative trait loci factors replicate loci previously identified in recombinant inbred lines, 6/7 are associated with excellent candidate genes, and RNAi knock-downs support the involvement of 4 genes in the genetic control of trait variation. For many traits of interest to drosophilists, a bulked phenotyping/genotyping extreme quantitative trait loci design has considerable advantages.
© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  DSPR; QTL mapping; caffeine resistance; complex traits; multiparental populations

Mesh:

Year:  2022        PMID: 35100395      PMCID: PMC8893256          DOI: 10.1093/genetics/iyab238

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.402


  87 in total

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Journal:  Genetics       Date:  1996-01       Impact factor: 4.562

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Journal:  Psychopharmacology (Berl)       Date:  2015-11-19       Impact factor: 4.530

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Authors:  Ian M Ehrenreich
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7.  Accurate Allele Frequencies from Ultra-low Coverage Pool-Seq Samples in Evolve-and-Resequence Experiments.

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8.  Large-Scale Analyses Provide No Evidence for Gene-Gene Interactions Influencing Type 2 Diabetes Risk.

Authors:  Abhishek Nag; Mark I McCarthy; Anubha Mahajan
Journal:  Diabetes       Date:  2020-08-21       Impact factor: 9.461

9.  Genome evolution across 1,011 Saccharomyces cerevisiae isolates.

Authors:  Jackson Peter; Matteo De Chiara; Anne Friedrich; Jia-Xing Yue; David Pflieger; Anders Bergström; Anastasie Sigwalt; Benjamin Barre; Kelle Freel; Agnès Llored; Corinne Cruaud; Karine Labadie; Jean-Marc Aury; Benjamin Istace; Kevin Lebrigand; Pascal Barbry; Stefan Engelen; Arnaud Lemainque; Patrick Wincker; Gianni Liti; Joseph Schacherer
Journal:  Nature       Date:  2018-04-11       Impact factor: 49.962

10.  Combined sequence-based and genetic mapping analysis of complex traits in outbred rats.

Authors:  Amelie Baud; Roel Hermsen; Victor Guryev; Pernilla Stridh; Delyth Graham; Martin W McBride; Tatiana Foroud; Sophie Calderari; Margarita Diez; Johan Ockinger; Amennai D Beyeen; Alan Gillett; Nada Abdelmagid; Andre Ortlieb Guerreiro-Cacais; Maja Jagodic; Jonatan Tuncel; Ulrika Norin; Elisabeth Beattie; Ngan Huynh; William H Miller; Daniel L Koller; Imranul Alam; Samreen Falak; Mary Osborne-Pellegrin; Esther Martinez-Membrives; Toni Canete; Gloria Blazquez; Elia Vicens-Costa; Carme Mont-Cardona; Sira Diaz-Moran; Adolf Tobena; Oliver Hummel; Diana Zelenika; Kathrin Saar; Giannino Patone; Anja Bauerfeind; Marie-Therese Bihoreau; Matthias Heinig; Young-Ae Lee; Carola Rintisch; Herbert Schulz; David A Wheeler; Kim C Worley; Donna M Muzny; Richard A Gibbs; Mark Lathrop; Nico Lansu; Pim Toonen; Frans Paul Ruzius; Ewart de Bruijn; Heidi Hauser; David J Adams; Thomas Keane; Santosh S Atanur; Tim J Aitman; Paul Flicek; Tomas Malinauskas; E Yvonne Jones; Diana Ekman; Regina Lopez-Aumatell; Anna F Dominiczak; Martina Johannesson; Rikard Holmdahl; Tomas Olsson; Dominique Gauguier; Norbert Hubner; Alberto Fernandez-Teruel; Edwin Cuppen; Richard Mott; Jonathan Flint
Journal:  Nat Genet       Date:  2013-05-26       Impact factor: 38.330

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