<scp>QTL</scp> for maize grain yield identified by <scp>QTL</scp> mapping in six environments and consensus loci for grain weight detected by meta‐analysis

Pan, Limei; Yin, Zengqi; Huang, Yaqun; Chen, Jingtang; Zhu, Linghua; Zhao, Yang; Guo, Jian-Wei

doi:10.1111/pbr.12524

Cited by 10 publications

(6 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Three of the regions where significant SNPs associated with grain yield under high pressure of corn borer were detected (~ 199–202 Mb in chromosome 1, ~ 128 Mb in chromosome 5, and ~ 6–12 Mb in chromosome 9) were close (~ 0.2 Mb) or within 3 meta-QTL for grain yield detected by Wang et al [78]. In chromosome 1, a meta-QTL containing a high number of individual QTLs and spanning between ~ 200 and ~ 208 Mb was also detected by Pan et al [79]. In addition, the analysis of Wang et al [78] identified a meta-QTL at ~ 197–198 Mb in chromosome 1, very close to the previously mentioned.…”

Section: Discussionmentioning

confidence: 56%

Mapping of resistance to corn borers in a MAGIC population of maize

et al. 2019

View full text Add to dashboard Cite

BackgroundCorn borers constitute an important pest of maize around the world; in particular Sesamia nonagrioides Lefèbvre, named Mediterranean corn borer (MCB), causes important losses in Southern Europe. Methods of selection can be combined with transgenic approaches to increase the efficiency and durability of the resistance to corn borers. Previous studies of the genetic factors involved in resistance to MCB have been carried out using bi-parental populations that have low resolution or using association inbred panels that have a low power to detect rare alleles. We developed a Multi-parent Advanced Generation InterCrosses (MAGIC) population to map with high resolution the genetic determinants of resistance to MCB.ResultsWe detected multiple single nucleotide polymorphisms (SNPs) of low effect associated with resistance to stalk tunneling by MCB. We dissected a wide region related to stalk tunneling in multiple studies into three smaller regions (at ~ 150, ~ 155, and ~ 165 Mb in chromosome 6) that closely overlap with regions associated with cell wall composition. We also detected regions associated with kernel resistance and agronomic traits, although the co-localization of significant regions between traits was very low. This indicates that it is possible the concurrent improvement of resistance and agronomic traits.ConclusionsWe developed a mapping population which allowed a finer dissection of the genetics of maize resistance to corn borers and a solid nomination of candidate genes based on functional information. The population, given its large variability, was also adequate to map multiple traits and study the relationship between them.

show abstract

Section: Discussionmentioning

confidence: 56%

Mapping of resistance to corn borers in a MAGIC population of maize

et al. 2019

View full text Add to dashboard Cite

show abstract

“…When the phenotypes of different traits of a maize population were assessed, it was found that the low-P tolerance in different genotypes was significantly correlated with the phenotype of plants under low P. Both can be used for screening and genetic analysis of low-P tolerant germplasm [41] . According to the definition of PUE, biomass and yield are still the main selection criteria when screening for P-efficient germplasm, but both traits are very complex quantitative traits controlled by many minor QTL [42][43][44] .…”

Section: Genotypic Differences In Response To Low-p Starvation In Maizementioning

confidence: 99%

Genetic study and molecular breeding for high phosphorus use efficiency in maize

Li¹,

Meng²,

Kuang³

et al. 2019

Front. Agr. Sci. Eng.

View full text Add to dashboard Cite

Phosphorus is the second most important macronutrient after nitrogen and it has many vital functions in the life of plants. Most soils have a low available P content, which has become a key limiting factor for increasing crop production. Also, low P use efficiency (PUE) of crops in conjunction with excessive application of P fertilizers has resulted in serious environmental problems. Thus, dissecting the genetic architecture of crop PUE, mining related quantitative trait loci (QTL) and using molecular breeding methods to improve high PUE germplasm are of great significance and serve as an efficient approach for the development of sustainable agriculture. In this review, molecular and phenotypic characteristics of maize inbred lines with high PUE, related QTL and genes as well as low-P responses are summarized. Based on this, a breeding strategy applying genomic selection as the core, and integrating the existing genetic information and molecular breeding techniques is proposed for breeding high PUE maize inbred lines and hybrids.

show abstract

“…Several researchers have reported that yield contributing traits usually exhibit stable QTLs across environments (MESSMER et al, 2009;LIU et al, 2014;ZHANG et al, 2017). Till today various researchers carried out QTL analysis for various yield traits, namely those related to ear morphology (EL, ED) (MENDES-MOREIRA et al, 2015;CHEN et al, 2016;SU et al, 2017), KR/E (VELDBOOM and LEE, 1994;AUSTIN and LEE, 1996), K/R (CHEN et al, 2016;SU et al, 2017), TW (CHEN et al, 2016;PAN et al, 2017;SU et al, 2017;ZHAO et al, 2018) and GY/P (VEIGA et al, 2012;CHEN et al, 2016;SU et al, 2017;NIKOLIC et al, 2018;RIBEIRO et al, 2018). To date, many QTLs for yield contributing traits were discovered of which 45 QTLs were associated with ED, 149 with TW, 46 with EL, and 23 with KR/E (https://archive.gramene.org/qtl/).…”

Section: Introductionmentioning

confidence: 99%

Identification of QTLS for yield and contributing traits in maize-teosinte derived bils under diseased-stressed and control conditions

et al. 2021

View full text Add to dashboard Cite

In maize, grain yield is the most important trait having a complex inheritance pattern. Yield contributing traits are more stable and have higher heritability than yield. Therefore, the present study was conducted to identify quantitative trait loci (QTLs) associated with grain yield and its components by using simple sequence repeat (SSR) markers. A population of 169 BC1F5 lines was derived from the crossing between maize inbred line DI-103 and teosinte-parviglumis was utilized for genotyping and phenotyping. In diseased stressed condition (E1), ear length (EL), ear diameter (ED), kernel rows per ear (KR/E), kernels per row (K/R), test weight (TW), and grain yield per plant (GY/P) had 7, 6, 7, 4, 6 and 5 QTLs whereas, in controlled condition (E2) 5, 2, 5, 4, 5 and 3 QTLs were detected for enlisted characters, respectively. Consistent QTLs across the environments were detected for 5 of the 6 investigated traits and number of QTLs were EL (2), ED (1), KR/E (3), TW (1), and GY/P (1) whereas, for K/R none of the QTLs were common between E1 and E2. By mapping analysis, we have identified genomic regions associated with two traits in a manner that was consistent with phenotypic correlations among traits, supporting either pleiotropy or tight linkage among QTLs. Three co-localized QTLs were identified between grain yield and contributing traits. Notably umc1720-linked QTL at bin 4.10 was simultaneously responsible for GY and EL, ED, KR/E, K/R; umc1215-linked QTL at bin 6.03 was simultaneously responsible for GY and ED, KR/E, K/R, TW; umc1279-linked QTL was responsible for GY and ED, TW. The findings suggest that the chromosomal region containing co-localized QTLs governing multiple yields associated traits are potential targets for selection. In addition for 6 studied traits, 44 superior lines were identified, and along with both the parents i.e. maize (DI-103) and teosinte they were clustered in 11 groups. Therefore, lines clustered independently can be utilized in a hybridization programme for the accumulation of yield contributing traits for yield maximization.

show abstract

QTL for maize grain yield identified by QTL mapping in six environments and consensus loci for grain weight detected by meta‐analysis

Cited by 10 publications

References 64 publications

Mapping of resistance to corn borers in a MAGIC population of maize

Mapping of resistance to corn borers in a MAGIC population of maize

Genetic study and molecular breeding for high phosphorus use efficiency in maize

Identification of QTLS for yield and contributing traits in maize-teosinte derived bils under diseased-stressed and control conditions

Contact Info

Product

Resources

About