Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize

The improvement of kernel morphology traits is an important goal in common wheat (Triticum aestivum L.) breeding programs because of their close relationship with grain yield and milling quality. The aim of this study was to map quantitative trait loci (QTL) for kernel morphology traits using 240 recombinant inbred lines derived from a cross between the non-1BL.1RS translocation cv. PH 82-2 and the 1BL.1RS translocation cv. Neixiang 188, grown in six environments in China. Inclusive composite interval mapping identified 71 main-effect QTL on 16 chromosomes for seven kernel morphology traits measured by digital imaging, viz. kernel length, width, perimeter, area, shape factor, factor form-density and width/length ratio. Each of these loci explained from 2.6 to 28.2% of the phenotypic variation. Eight QTL clusters conferring the largest effects on kernel weight and kernel morphology traits were detected on chromosomes 1BL.1RS (2), 2A, 4A, 4B, 6B, 6D and 7A. Fourteen epistatic QTL were identified for all kernel morphology traits except kernel width/length ratio, involving 24 main-effect QTL distributed on 13 chromosomes, and explaining 2.5–8.3% of the phenotypic variance. Five loci, viz. Sec-1 on 1BL.1RS, Glu-B1 on 1BL, Xcfe53 on 2A, Xwmc238 on 4B, and Xbarc174 on 7A, were detected consistently across environments, and their linked DNA markers may be used for marker-assisted selection in breeding for improved wheat kernel traits and grain yield.

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Identification of Quantitative Trait Loci Associated with Nutrient Use Efficiency Traits, Using SNP Markers in an Early Backcross Population of Rice (Oryza sativa L.)

International Journal of Molecular Sciences ◽

10.3390/ijms20040900 ◽

2019 ◽

Vol 20 (4) ◽

pp. 900 ◽

Cited By ~ 3

Author(s):

Zilhas Jewel ◽

Jauhar Ali ◽

Anumalla Mahender ◽

Jose Hernandez ◽

Yunlong Pang ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Grain Yield ◽

Quantitative Trait ◽

Nutrient Use Efficiency ◽

Snp Markers ◽

Rice Cultivars ◽

Backcross Population ◽

Nutrient Use ◽

Trait Loci ◽

Use Efficiency

The development of rice cultivars with nutrient use efficiency (NuUE) is highly crucial for sustaining global rice production in Asia and Africa. However, this requires a better understanding of the genetics of NuUE-related traits and their relationship to grain yield. In this study, simultaneous efforts were made to develop nutrient use efficient rice cultivars and to map quantitative trait loci (QTLs) governing NuUE-related traits in rice. A total of 230 BC1F5 introgression lines (ILs) were developed from a single early backcross population involving Weed Tolerant Rice 1, as the recipient parent, and Hao-an-nong, as the donor parent. The ILs were cultivated in field conditions with a different combination of fertilizer schedule under six nutrient conditions: minus nitrogen (–N), minus phosphorus (–P), (–NP), minus nitrogen phosphorus and potassium (–NPK), 75% of recommended nitrogen (75N), and NPK. Analysis of variance revealed that significant differences (p < 0.01) were noted among ILs and treatments for all traits. A high-density linkage map was constructed by using 704 high-quality single nucleotide polymorphism (SNP) markers. A total of 49 main-effect QTLs were identified on all chromosomes, except on chromosome 7, 11 and 12, which are showing 20.25% to 34.68% of phenotypic variation. With further analysis of these QTLs, we refined them to four top hotspot QTLs (QTL harbor-I to IV) located on chromosomes 3, 5, 9, and 11. However, we identified four novel putative QTLs for agronomic efficiency (AE) and 22 QTLs for partial factor productivity (PFP) under –P and 75N conditions. These interval regions of QTLs, several transporters and genes are located that were involved in nutrient uptake from soil to plant organs and tolerance to biotic and abiotic stresses. Further, the validation of these potential QTLs, genes may provide remarkable value for marker-aided selection and pyramiding of multiple QTLs, which would provide supporting evidence for the enhancement of grain yield and cloning of NuUE tolerance-responsive genes in rice.

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Genetic Mapping Identifies Consistent Quantitative Trait Loci for Yield Traits of Rice under Greenhouse Drought Conditions

Genes ◽

10.3390/genes11010062 ◽

2020 ◽

Vol 11 (1) ◽

pp. 62

Author(s):

Niranjan Baisakh ◽

Jonalyn Yabes ◽

Andres Gutierrez ◽

Venkata Mangu ◽

Peiyong Ma ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Grain Yield ◽

Drought Resistance ◽

Quantitative Trait ◽

Chromosome 1 ◽

Phenotypic Variance ◽

Yield Traits ◽

Rice Varieties ◽

Drought Tolerant ◽

Trait Loci

Improving drought resistance in crops is imperative under the prevailing erratic rainfall patterns. Drought affects the growth and yield of most modern rice varieties. Recent breeding efforts aim to incorporate drought resistance traits in rice varieties that can be suitable under alternative irrigation schemes, such as in a (semi)aerobic system, as row (furrow-irrigated) rice. The identification of quantitative trait loci (QTLs) controlling grain yield, the most important trait with high selection efficiency, can lead to the identification of markers to facilitate marker-assisted breeding of drought-resistant rice. Here, we report grain yield QTLs under greenhouse drought using an F2:3 population derived from Cocodrie (drought sensitive) × Nagina 22 (N22) (drought tolerant). Eight QTLs were identified for yield traits under drought. Grain yield QTL under drought on chromosome 1 (phenotypic variance explained (PVE) = 11.15%) co-localized with the only QTL for panicle number (PVE = 37.7%). The drought-tolerant parent N22 contributed the favorable alleles for all QTLs except qGN3.2 and qGN5.1 for grain number per panicle. Stress-responsive transcription factors, such as ethylene response factor, WD40 domain protein, zinc finger protein, and genes involved in lipid/sugar metabolism were linked to the QTLs, suggesting their possible role in drought tolerance mechanism of N22 in the background of Cocodrie, contributing to higher yield under drought.

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