Literature DB >> 34841470

Discovery of genomic regions associated with resistance to late wilt disease caused by Harpophora maydis (Samra, Sabet and Hing) in maize (Zea mays L.).

N C Sunitha1, E Gangappa1, R P Veeresh Gowda2, S Ramesh3, Sunil Biradar2, Dharanendra Swamy2, H B Hemareddy2.   

Abstract

Late wilt disease (LWD) caused by Harpophora maydis (Samra, Sabet and Hing) is emerging as major production constraint in maize across the world. As a prelude to develop maize hybrid resistance to LWD, genetic basis of resistance was investigated. Two F2:3 mapping populations (derived from CV156670 × 414-33 (P-1) and CV156670 × CV143587 (P-2)) were challenged with LWD at two locations (Kallinayakanahalli and Muppadighatta) during 2017 post-rainy season. A wider range of LWD scores was observed at both locations in both the populations. LWD response was influenced by significant genotype × location interaction. Six and 56 F2:3 progeny families showed resistance level better than resistant parent. A total of 150 and 199 polymorphic single nucleotide polymorphism markers were used to genotype P-1 and P-2, respectively. Inclusive composite interval mapping was performed to detect significant Quantitative Trait Loci (QTL), QTL × QTL, QTL × location interaction effects. Three major and four minor QTL controlling LWD resistance were detected on chromosome-1. The position and effect of the QTL varied with the location. Significant di-QTL interactions involving QTL (with significant and/or non-significant effects) located within and between all the ten chromosomes were detected. Five of the seven detected QTL showed significant QTL × location interaction. Though two major QTL (q-lw-1.5 and q-lw-1.6) with lower Q×L interaction effects could be considered as stable, their phenotypic variance is not large enough to deploy them in Marker Assisted Selection (MAS). However, these QTL are of paramount importance in accumulating positive alleles for LWD resistance breeding.
© 2021. The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.

Entities:  

Keywords:  Late wilt disease; Mapping; QTL × Location interaction; QTL × QTL interaction

Mesh:

Year:  2021        PMID: 34841470     DOI: 10.1007/s13353-021-00672-x

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   3.240


  6 in total

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Journal:  Nat Genet       Date:  2007-10       Impact factor: 38.330

2.  Empirical threshold values for quantitative trait mapping.

Authors:  G A Churchill; R W Doerge
Journal:  Genetics       Date:  1994-11       Impact factor: 4.562

3.  Cephalosporium maydis, the Cause of Late Wilt in Maize, a Pathogen New to Portugal and Spain.

Authors:  M L Molinero-Ruiz; J M Melero-Vara; A Mateos
Journal:  Plant Dis       Date:  2010-03       Impact factor: 4.438

4.  Inclusive Composite Interval Mapping of QTL by Environment Interactions in Biparental Populations.

Authors:  Shanshan Li; Jiankang Wang; Luyan Zhang
Journal:  PLoS One       Date:  2015-07-10       Impact factor: 3.240

5.  Identification of QTLs for resistance to maize rough dwarf disease using two connected RIL populations in maize.

Authors:  Xintao Wang; Qing Yang; Ziju Dai; Yan Wang; Yingying Zhang; Baoquan Li; Wenming Zhao; Junjie Hao
Journal:  PLoS One       Date:  2019-12-17       Impact factor: 3.240

6.  Linkage mapping and genome-wide association study reveals conservative QTL and candidate genes for Fusarium rot resistance in maize.

Authors:  Yabin Wu; Zijian Zhou; Chaopei Dong; Jiafa Chen; Junqiang Ding; Xuecai Zhang; Cong Mu; Yuna Chen; Xiaopeng Li; Huimin Li; Yanan Han; Ruixia Wang; Xiaodong Sun; Jingjing Li; Xiaodong Dai; Weibin Song; Wei Chen; Jianyu Wu
Journal:  BMC Genomics       Date:  2020-05-12       Impact factor: 3.969

  6 in total
  1 in total

Review 1.  Control Strategies to Cope with Late Wilt of Maize.

Authors:  Ofir Degani
Journal:  Pathogens       Date:  2021-12-23
  1 in total

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