Literature DB >> 31352407

Genetic Screening for Mutants with Altered Seminal Root Numbers in Hexaploid Wheat Using a High-Throughput Root Phenotyping Platform.

Oluwaseyi Shorinola1,2, Ryan Kaye3, Guy Golan4, Zvi Peleg4, Stefan Kepinski3, Cristobal Uauy5.   

Abstract

Roots are the main channel for water and nutrient uptake in plants. Optimization of root architecture provides a viable strategy to improve nutrient and water uptake efficiency and maintain crop productivity under water-limiting and nutrient-poor conditions. We know little, however, about the genetic control of root development in wheat, a crop supplying 20% of global calorie and protein intake. To improve our understanding of the genetic control of seminal root development in wheat, we conducted a high-throughput screen for variation in seminal root number using an exome-sequenced mutant population derived from the hexaploid wheat cultivar Cadenza. The screen identified seven independent mutants with homozygous and stably altered seminal root number phenotypes. One mutant, Cadenza0900, displays a recessive extra seminal root number phenotype, while six mutants (Cadenza0062, Cadenza0369, Cadenza0393, Cadenza0465, Cadenza0818 and Cadenza1273) show lower seminal root number phenotypes most likely originating from defects in the formation and activation of seminal root primordia. Segregation analysis in F2 populations suggest that the phenotype of Cadenza0900 is controlled by multiple loci whereas the Cadenza0062 phenotype fits a 3:1 mutant:wild-type segregation ratio characteristic of dominant single gene action. This work highlights the potential to use the sequenced wheat mutant population as a forward genetic resource to uncover novel variation in agronomic traits, such as seminal root architecture.
Copyright © 2019 Shorinola et al.

Entities:  

Keywords:  Forward Genetics; Mutations; Root; TILLING; Wheat

Mesh:

Year:  2019        PMID: 31352407      PMCID: PMC6723138          DOI: 10.1534/g3.119.400537

Source DB:  PubMed          Journal:  G3 (Bethesda)        ISSN: 2160-1836            Impact factor:   3.154


  35 in total

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Journal:  J Exp Bot       Date:  2009-06-10       Impact factor: 6.992

Review 2.  Genetic Control of Root System Development in Maize.

Authors:  Frank Hochholdinger; Peng Yu; Caroline Marcon
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3.  VERNALIZATION1 Modulates Root System Architecture in Wheat and Barley.

Authors:  Kai P Voss-Fels; Hannah Robinson; Stephen R Mudge; Cecile Richard; Saul Newman; Benjamin Wittkop; Andreas Stahl; Wolfgang Friedt; Matthias Frisch; Iulian Gabur; Anika Miller-Cooper; Bradley C Campbell; Alison Kelly; Glen Fox; Jack Christopher; Mandy Christopher; Karine Chenu; Jerome Franckowiak; Emma S Mace; Andrew K Borrell; Howard Eagles; David R Jordan; José R Botella; Graeme Hammer; Ian D Godwin; Ben Trevaskis; Rod J Snowdon; Lee T Hickey
Journal:  Mol Plant       Date:  2017-10-19       Impact factor: 13.164

Review 4.  Combining Traditional Mutagenesis with New High-Throughput Sequencing and Genome Editing to Reveal Hidden Variation in Polyploid Wheat.

Authors:  Cristobal Uauy; Brande B H Wulff; Jorge Dubcovsky
Journal:  Annu Rev Genet       Date:  2017-09-20       Impact factor: 16.830

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Journal:  Plant Cell       Date:  2005-04-13       Impact factor: 11.277

6.  RootNav: navigating images of complex root architectures.

Authors:  Michael P Pound; Andrew P French; Jonathan A Atkinson; Darren M Wells; Malcolm J Bennett; Tony Pridmore
Journal:  Plant Physiol       Date:  2013-06-13       Impact factor: 8.340

Review 7.  Genomics as the key to unlocking the polyploid potential of wheat.

Authors:  Philippa Borrill; Nikolai Adamski; Cristobal Uauy
Journal:  New Phytol       Date:  2015-06-24       Impact factor: 10.151

8.  Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat.

Authors:  Jonathan A Atkinson; Luzie U Wingen; Marcus Griffiths; Michael P Pound; Oorbessy Gaju; M John Foulkes; Jacques Le Gouis; Simon Griffiths; Malcolm J Bennett; Julie King; Darren M Wells
Journal:  J Exp Bot       Date:  2015-03-04       Impact factor: 6.992

9.  Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

Authors:  Michael P Pound; Jonathan A Atkinson; Alexandra J Townsend; Michael H Wilson; Marcus Griffiths; Aaron S Jackson; Adrian Bulat; Georgios Tzimiropoulos; Darren M Wells; Erik H Murchie; Tony P Pridmore; Andrew P French
Journal:  Gigascience       Date:  2017-10-01       Impact factor: 6.524

Review 10.  Uncovering the hidden half of plants using new advances in root phenotyping.

Authors:  Jonathan A Atkinson; Michael P Pound; Malcolm J Bennett; Darren M Wells
Journal:  Curr Opin Biotechnol       Date:  2018-07-19       Impact factor: 9.740

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  2 in total

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Authors:  Eric S Ober; Samir Alahmad; James Cockram; Cristian Forestan; Lee T Hickey; Josefine Kant; Marco Maccaferri; Emily Marr; Matthew Milner; Francisco Pinto; Charlotte Rambla; Matthew Reynolds; Silvio Salvi; Giuseppe Sciara; Rod J Snowdon; Pauline Thomelin; Roberto Tuberosa; Cristobal Uauy; Kai P Voss-Fels; Emma Wallington; Michelle Watt
Journal:  Theor Appl Genet       Date:  2021-04-26       Impact factor: 5.699

2.  Regulation of Sixth Seminal Root Formation by Jasmonate in Triticum aestivum L.

Authors:  Alexey Pigolev; Dmitry Miroshnichenko; Sergey Dolgov; Tatyana Savchenko
Journal:  Plants (Basel)       Date:  2021-01-23
  2 in total

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