Identification of a candidate gene underlying qKRN5b for kernel row number in Zea mays L.

Shen, Xiaomeng; Zhao, Rongjun; Liu, Lei; Zhu, Can; Li, Manfei; Du, Hao; Zhang, Zuxin

doi:10.1007/s00122-019-03436-8

Cited by 12 publications

(8 citation statements)

References 53 publications

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“…Similarly, one consensus QTL in this study, qKRN4.1 , was located on chromosome 4, which included the KRN4 and qKRNW4 intervals. However, some clustered QTLs were not identified in this study, such as qKRN5a and qKRN5b [ 43 ]. In addition, several QTLs containing a single KRN gene with large effects also overlapped in our results.…”

Section: Discussionmentioning

confidence: 99%

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

et al. 2022

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Background Maize kernel row number (KRN) is one of the most important yield traits and has changed greatly during maize domestication and selection. Elucidating the genetic basis of KRN will be helpful to improve grain yield in maize. Results Here, we measured KRN in four environments using a nested association mapping (NAM) population named HNAU-NAM1 with 1,617 recombinant inbred lines (RILs) that were derived from 12 maize inbred lines with a common parent, GEMS41. Then, five consensus quantitative trait loci (QTLs) distributing on four chromosomes were identified in at least three environments along with the best linear unbiased prediction (BLUP) values by the joint linkage mapping (JLM) method. These QTLs were further validated by the separate linkage mapping (SLM) and genome-wide association study (GWAS) methods. Three KRN genes cloned through the QTL assay were found in three of the five consensus QTLs, including qKRN1.1, qKRN2.1 and qKRN4.1. Two new QTLs of KRN, qKRN4.2 and qKRN9.1, were also identified. On the basis of public RNA-seq and genome annotation data, five genes highly expressed in ear tissue were considered candidate genes contributing to KRN. Conclusions This study carried out a comprehensive analysis of the genetic architecture of KRN by using a new NAM population under multiple environments. The present results provide solid information for understanding the genetic components underlying KRN and candidate genes in qKRN4.2 and qKRN9.1. Single-nucleotide polymorphisms (SNPs) closely linked to qKRN4.2 and qKRN9.1 could be used to improve inbred yield during molecular breeding in maize.

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Section: Discussionmentioning

confidence: 99%

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

et al. 2022

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“…qKRN5b was a major QTL with a higher additive effect than qKRN5a and subsequently fine mapped into a 147.2 kb target region flanked by markers SC3603d1 and SC14631 , which harbored three putative candidate genes. Among them, Zm00001d013603 encodes an endonuclease/exonuclease/phosphatase family protein that can hydrolyze phosphatidylinositol diphosphates and was identified as the causal gene of qKRN5b based on expression analysis and sequence variation between the two parental lines [ 78 ]. The other major QTL of krn1 has been delimited into a 6.6 kb genomic region on chromosome 1 flanked by SNP1 and SNP2 markers.…”

Section: Genetic Dissection Of Grain Yield-related Traits In Sorghum ...mentioning

confidence: 99%

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Baye

Xie

2022

IJMS

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Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.

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“…The variation in KRN of inbred lines plays a major role in determining the perse plant yield of that hybrid for which they are contributing as parental lines. Over recent decades, the scientific community has been working to uncover the genetic architecture of grain yield and yield-related traits in maize (Zea mays L.) (Shen et. al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Characterization of sub-tropical maize (Zea Mays L.) inbred lines for the variation in kernel row numbers (KRN)

Mukri¹,

Gadag²,

Bhat³

et al. 2022

Preprint

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Genetic dissection of high KRN trait and cob length has been undertaken by several researchers resulting in identification of loci controlling the traits. Further fine mapping of QTLs controlling KRN and cob length and TILLING strategies identified the underlying genes. All these studies are used temperate maize genotypes which are of limited use to researcher in sub-tropical region, and the sub-tropical maize production systems. Present investigation explores the availability of genetic regions responsible for KRN in sub-tropical maize germplasm. A total of 280 sub-tropical maize germplasm was analyzed for their KRN variation and selected 45 stable lines were subjected to molecular characterization using genes linked to KRN in maize. Diversity analysis was also performed to understand the possible association of character with the KRN gene in deciding its variation in the given population. It was revealed that four genes showed highest probability of influencing KRN traits in these tropical maize inbred lines. The remaining genes not establishing specific pattern of association with high and low KRN genotypes may need further study on its allelic variation.

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Identification of a candidate gene underlying qKRN5b for kernel row number in Zea mays L.

Cited by 12 publications

References 53 publications

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Characterization of sub-tropical maize (Zea Mays L.) inbred lines for the variation in kernel row numbers (KRN)

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