Genotypic and phenotypic characterization of a large, diverse population of maize near‐isogenic lines

Morales, Laura; Repka, Ace; Swarts, Kelly; Stafstrom, William C.; He, Yuqing; Sermons, Shannon M.; Yang, Qin; Lopez‐Zuniga, Luis O.; Rucker, Elizabeth; Thomason, Wade E.; Nelson, Rebecca; Balint‐Kurti, Peter

doi:10.1111/tpj.14787

Cited by 13 publications

(24 citation statements)

References 37 publications

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“…NILs with introgressions across the centromeric region of chromosome 8 overlapped two QTL for resistance to NLB, including qNLB8.06, which overlaps the Ht2 and Htn resistance loci (Chung et al 2010;Hurni et al 2015). Co-localized QTL regions for resistance to NLB between this nNIL study and the larger nNIL library (Morales et al 2020) were identified near qNLB6.05 and in overlapping qNLB8.05 regions. Differences in the disease phenotyping environments, genotyping and analysis methodologies, as well as nNIL library composition maybe have contributed to the limited concordance between the results from the two nNIL libraries.…”

Section: Description and Utility Of The Nnil Library For Dissection Omentioning

confidence: 71%

“…The nNIL library described in this paper is part of a community resource developed by Syngenta as a tool for dissection of important traits (Gandhi et al 2001;Morales et al, 2020) and available upon request from the International Maize and Wheat Improvement Center (CIMMYT). We describe a subset of a larger population of NILs derived from 18 donor parents (consisting of founder lines in the NAM population) and backcrossed to B73, that were initially selected to harbor introgressions around known QTL for resistance to NLB.…”

Section: Description and Utility Of The Nnil Library For Dissection Omentioning

confidence: 99%

“…The potential for association mapping in a nNIL population is based on the diverse parentage of the nNILs and the high-density SNP coverage. The library can be used for QTL mapping or confirmation (Morales et al 2020) and individual NILs can be selected for use in fine-mapping of specific loci of interest, to allow testing of candidate genes. The heterozygous introgressions identified in these lines can be exploited for heterogeneous inbred family analysis (Tuinstra et al 1997).…”

Section: Description and Utility Of The Nnil Library For Dissection Omentioning

confidence: 99%

“…Utilizing RILs typically allows QTL mapping at low resolution, and fine mapping with NILs can also be limited in regions of low recombination (e.g., Jamann et al 2014). NILs have been used in genetic studies of quantitative disease resistance in maize for QTL discovery (Chung et al 2010;Liu et al 2015;Lopez-Zuniga et al 2019, Morales et al 2020, for phenotypic analysis (Chung et al 2011;Jamann et al 2014;Zhang et al 2017;Morales et al 2020) and for identifying the genes underlying QTL (Yang et al 2017).…”

Section: Introductionmentioning

confidence: 99%

“…, Jamann et al 2014 ). NILs have been used in genetic studies of quantitative disease resistance in maize for QTL discovery ( Chung et al 2010 ; Lopez-Zuniga et al 2019 , Morales et al 2020 ), for phenotypic analysis ( Chung et al 2011 ; Jamann et al 2014 ; Zhang et al 2017 ; Morales et al 2020 ) and for identifying the genes underlying QTL ( Yang et al 2017 ).…”

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confidence: 99%

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Maize Introgression Library Provides Evidence for the Involvement ofliguleless1in Resistance to Northern Leaf Blight

Kolkman

Strable

Harline

et al. 2020

G3 Genes|Genomes|Genetics

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Plant disease resistance is largely governed by complex genetic architecture. In maize, few disease resistance loci have been characterized. Near-isogenic lines are a powerful genetic tool to dissect quantitative trait loci. We analyzed an introgression library of maize (Zea mays) near-isogenic lines, termed a nested near-isogenic line library for resistance to northern leaf blight caused by the fungal pathogen Setosphaeria turcica. The population was comprised of 412 BC5F4 near-isogenic lines that originated from 18 diverse donor parents and a common recurrent parent, B73. Single nucleotide polymorphisms identified through genotyping by sequencing were used to define introgressions and for association analysis. Near isogenic lines that conferred resistance and susceptibility to northern leaf blight were comprised of introgressions that overlapped known northern leaf blight quantitative trait loci. Genome-wide association analysis and stepwise regression further resolved five quantitative trait loci regions, and implicated several candidate genes, including Liguleless1, a key determinant of leaf architecture in cereals. Two independently-derived mutant alleles of liguleless1 inoculated with S. turcica showed enhanced susceptibility to northern leaf blight. In the maize nested association mapping population, leaf angle was positively correlated with resistance to northern leaf blight in five recombinant inbred line populations, and negatively correlated with northern leaf blight in four recombinant inbred line populations. This study demonstrates the power of an introgression library combined with high density marker coverage to resolve quantitative trait loci. Furthermore, the role of liguleless1 in leaf architecture and in resistance to northern leaf blight has important applications in crop improvement.

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Section: Description and Utility Of The Nnil Library For Dissection Omentioning

confidence: 71%

Section: Description and Utility Of The Nnil Library For Dissection Omentioning

confidence: 99%

Section: Description and Utility Of The Nnil Library For Dissection Omentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Maize Introgression Library Provides Evidence for the Involvement ofliguleless1in Resistance to Northern Leaf Blight

Kolkman

Strable

Harline

et al. 2020

G3 Genes|Genomes|Genetics

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Genetic dissection of maize plant architecture using a novel nested association mapping population

Zhao

Song

et al. 2021

The Plant Genome

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The leaf angle (LA), plant height (PH), and ear height (EH) are key plant architectural traits influencing maize (Zea mays L.) yield. However, their genetic determinants have not yet been well‐characterized. Here, we developed a maize advanced backcross‐nested association mapping population in Henan Agricultural University (HNAU‐NAM1) comprised of 1,625 BC1F4/BC2F4 lines. These were obtained by crossing a diverse set of 12 representative inbred lines with the common GEMS41 line, which were then genotyped using the MaizeSNP9.4K array. Genetic diversity and phenotypic distribution analyses showed considerable levels of genetic variation. We obtained 18–88 quantitative trait loci (QTLs) associated with LA, PH, and EH by using three complementary mapping methods, named as separate linkage mapping, joint linkage mapping, and genome‐wide association studies. Our analyses enabled the identification of ten QTL hot‐spot regions associated with the three traits, which were distributed on nine different chromosomes. We further selected 13 major QTLs that were simultaneously detected by three methods and deduced the candidate genes, of which eight were not reported before. The newly constructed HNAU‐NAM1 population in this study will further broaden our insights into understanding of genetic regulation of plant architecture, thus will help to improve maize yield and provide an invaluable resource for maize functional genomics and breeding research.

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Brown midrib mutant and genome‐wide association analysis uncover lignin genes for disease resistance in maize

et al. 2022

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Brown midrib (BMR) maize (Zea mays L.) harbors mutations that result in lower lignin levels and higher feed digestibility, making it a desirable silage market class for ruminant nutrition. Northern leaf blight (NLB) epidemics in upstate New York highlighted the disease susceptibility of commercially grown BMR maize hybrids.We found the bm1, bm2, bm3, and bm4 mutants in a W64A genetic background to be more susceptible to foliar fungal (NLB, gray leaf spot [GLS], and anthracnose leaf blight [ALB]) and bacterial (Stewart's wilt) diseases. The bm1, bm2, and bm3 mutants showed enhanced susceptibility to anthracnose stalk rot (ASR), and the bm1 and bm3 mutants were more susceptible to Gibberella ear rot (GER). Colocalization of quantitative trait loci (QTL) and correlations between stalk strength and disease traits in recombinant inbred line families suggest possible pleiotropies. The role of lignin in plant defense was explored using high-resolution, genome-wide association analysis for resistance to NLB in the Goodman diversity panel. Association analysis identified 100 single and clustered single-nucleotide polymorphism (SNP) associations for resistance to NLB but did not implicate natural functional variation at bm1-bm5. Strong associations implicated a suite of diverse candidate genes including lignin-related genes such as a β-glucosidase gene cluster, hct11, knox1, knox2, zim36, lbd35, CASP-like protein 8, and xat3. The candidate genes are targets for breeding quantitative resistance to NLB in maize for use in silage and nonsilage purposes.

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Genotypic and phenotypic characterization of a large, diverse population of maize near‐isogenic lines

Abstract: This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Cited by 13 publications

References 37 publications

Maize Introgression Library Provides Evidence for the Involvement ofliguleless1in Resistance to Northern Leaf Blight

Maize Introgression Library Provides Evidence for the Involvement ofliguleless1in Resistance to Northern Leaf Blight

Genetic dissection of maize plant architecture using a novel nested association mapping population

Brown midrib mutant and genome‐wide association analysis uncover lignin genes for disease resistance in maize

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