Analysis of the genetic basis of plant height-related traits in response to ethylene by QTL mapping in maize (Zea mays L.)

Zhang, Weiqiang; Li, Zhi; Fang, Hui; Zhang, Mingcai; Liu, Duan

doi:10.1371/journal.pone.0193072

Cited by 10 publications

(5 citation statements)

References 70 publications

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“…Most of the hotspot regions were consistent with those found in previous studies, and bin 1.01 and bin 1.02 contained fifteen QTLs for seven traits (excluding ED), bin 4.08 contained fifteen QTLs for eight traits, and bin 6.05 contained at least five QTLs (Table S8). These hotspot regions were consistent with or similar to findings in previous studies [5,57,65,66].…”

Section: Hotspot Bin Regions On Chromosomes Associated With Ear-relat...supporting

confidence: 93%

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

Zhang,

Sun,

Zhang

et al. 2023

Genes

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In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.

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Section: Hotspot Bin Regions On Chromosomes Associated With Ear-relat...supporting

confidence: 93%

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

Zhang,

Sun,

Zhang

et al. 2023

Genes

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“…Two QTLs [ qFe(III)-R/S5-1 and qFe(III)-RDW5-1 ] controlling root dry weight under Fe deficiency in this work were co-localized with the loci controlling the same trait under Fe-deficient condition identified by linkage and association analysis ( Benke et al, 2014 , 2015 ). Besides, intervals of these two loci were also overlapped by the genomic regions of the QTLs controlling plant height under normal and external ethylene conditions, root diameter under low-P stress, and SPAD under low-Fe stress ( Benke et al, 2014 ; Azevedo et al, 2015 ; Luo et al, 2017 ; Zhang et al, 2018 ). This implicated that these gnomic regions may harbor several genes with pleiotropic effect not only on root biomass accumulation but also on plant height, root morphological traits, and leaf SPAD at the seedling stage.…”

Section: Discussionmentioning

confidence: 99%

Identification of Quantitative Trait Loci Associated With Iron Deficiency Tolerance in Maize

et al. 2022

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Iron (Fe) is a limiting factor in crop growth and nutritional quality because of its low solubility. However, the current understanding of how major crops respond to Fe deficiency and the genetic basis remains limited. In the present study, Fe-efficient inbred line Ye478 and Fe-inefficient inbred line Wu312 and their recombinant inbred line (RIL) population were utilized to reveal the physiological and genetic responses of maize to low Fe stress. Compared with the Fe-sufficient conditions (+Fe: 200 μM), Fe-deficient supply (−Fe: 30 μM) significantly reduced shoot and root dry weights, leaf SPAD of Fe-efficient inbred line Ye478 by 31.4, 31.8, and 46.0%, respectively; decreased Fe-inefficient inbred line Wu312 by 72.0, 45.1, and 84.1%, respectively. Under Fe deficiency, compared with the supply of calcium nitrate (N1), supplying ammonium nitrate (N2) significantly increased the shoot and root dry weights of Wu312 by 37.5 and 51.6%, respectively; and enhanced Ye478 by 23.9 and 45.1%, respectively. Compared with N1, N2 resulted in a 70.0% decrease of the root Fe concentration for Wu312 in the −Fe treatment, N2 treatment reduced the root Fe concentration of Ye478 by 55.8% in the −Fe treatment. These findings indicated that, compared with only supplying nitrate nitrogen, combined supply of ammonium nitrogen and nitrate nitrogen not only contributed to better growth in maize but also significantly reduced Fe concentration in roots. In linkage analysis, ten quantitative trait loci (QTLs) associated with Fe deficiency tolerance were detected, explaining 6.2–12.0% of phenotypic variation. Candidate genes considered to be associated with the mechanisms underlying Fe deficiency tolerance were identified within a single locus or QTL co-localization, including ZmYS3, ZmPYE, ZmEIL3, ZmMYB153, ZmILR3 and ZmNAS4, which may form a sophisticated network to regulate the uptake, transport and redistribution of Fe. Furthermore, ZmYS3 was highly induced by Fe deficiency in the roots; ZmPYE and ZmEIL3, which may be involved in Fe homeostasis in strategy I plants, were significantly upregulated in the shoots and roots under low Fe stress; ZmMYB153 was Fe-deficiency inducible in the shoots. Our findings will provide a comprehensive insight into the physiological and genetic basis of Fe deficiency tolerance.

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“…Moreover, 35 of 54 QTLs in the current study were identified in the QTLs associated with plant height, the shoot or root dry weight, the R/S ratio, and the seedling root traits in previous reports (Tables S1 and S2). Both qKB-PH6-1 and qKB-PH9-1, controlling plant height under Zn deficiency on chromosome 6 and 9, were overlapped with the loci related to plant height reported by Zhang et al [69] (2018) and Luo et al [68] (2017), respectively. This indicates that these regions may contain a single gene exerting a strong effect underlying the QTL colocalization for plant height under Zn-deficiency stress.…”

Section: Comparisons Of Qtls Identified In This Study With Previous R...mentioning

confidence: 54%

“…To our knowledge, very few Zn efficiency-associated loci have been identified in maize, but numerous QTLs were identified to be associated with Zn and other microelements concentrations in maize [22,24,[62][63][64][65]. In addition, there were lots of QTLs related to the traits we used in this study, such as plant height, shoot or root dry weight, and the R/S ratio under other conditions rather than Zn-deficient condition [66][67][68][69]. Thereby, these QTLs in previous studies were compared with current results based on their physical position.…”

Section: Comparisons Of Qtls Identified In This Study With Previous R...mentioning

confidence: 94%

Identification of Zinc Efficiency-Associated Loci (ZEALs) and Candidate Genes for Zn Deficiency Tolerance of Two Recombination Inbred Line Populations in Maize

Jian-qin

Qin

et al. 2022

IJMS

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Zinc (Zn) deficiency is one of the most common micronutrient disorders in cereal plants, greatly impairing crop productivity and nutritional quality. Identifying the genes associated with Zn deficiency tolerance is the basis for understanding the genetic mechanism conferring tolerance. In this study, the K22×BY815 and DAN340×K22 recombination inbred line (RIL) populations, which were derived from Zn-inefficient and Zn-efficient inbred lines, were utilized to detect the quantitative trait loci (QTLs) associated with Zn deficiency tolerance and to further identify candidate genes within these loci. The BLUP (Best Linear Unbiased Prediction) values under Zn-deficient condition (-Zn) and the ratios of the BLUP values under Zn deficient condition to the BLUP values under Zn-sufficient condition (-Zn/CK) were used to perform linkage mapping. In QTL analysis, 21 QTLs and 33 QTLs controlling the Zn score, plant height, shoot and root dry weight, and root-to-shoot ratio were detected in the K22×BY815 population and the DAN340×K22 population, explaining 5.5–16.6% and 4.2–23.3% of phenotypic variation, respectively. In addition, seventeen candidate genes associated with the mechanisms underlying Zn deficiency tolerance were identified in QTL colocalizations or the single loci, including the genes involved in the uptake, transport, and redistribution of Zn (ZmIRT1, ZmHMAs, ZmNRAMP6, ZmVIT, ZmNAS3, ZmDMAS1, ZmTOM3), and the genes participating in the auxin and ethylene signal pathways (ZmAFBs, ZmIAA17, ZmETR, ZmEIN2, ZmEIN3, ZmCTR3, ZmEBF1). Our findings will broaden the understanding of the genetic structure of the tolerance to Zn deficiency in maize.

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Analysis of the genetic basis of plant height-related traits in response to ethylene by QTL mapping in maize (Zea mays L.)

Cited by 10 publications

References 70 publications

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review

Identification of Quantitative Trait Loci Associated With Iron Deficiency Tolerance in Maize

Identification of Zinc Efficiency-Associated Loci (ZEALs) and Candidate Genes for Zn Deficiency Tolerance of Two Recombination Inbred Line Populations in Maize

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