Identification of Quantitative Trait Loci Hotspots Affecting Agronomic Traits and High-Throughput Vegetation Indices in Rainfed Wheat

Understanding the genetic basis of agronomic traits is essential for wheat breeding programs to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can be a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin. The collection was phenotyped for agronomic and VI traits derived from multispectral images over 3 and 2 years, respectively. The GWAS identified 2,579 marker-trait associations (MTAs). The quantitative trait loci (QTL) overview index statistic detected 11 QTL hotspots involving more than one trait in at least 2 years. A CG analysis detected 12 CGs upregulated under abiotic stress in six QTL hotspots and 46 downregulated CGs in 10 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.

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Identification of QTL hotspots affecting agronomic traits and high-throughput vegetation indices in rainfed wheat

10.1101/2021.06.25.449881 ◽

2021 ◽

Author(s):

Ruben Rufo ◽

Andrea Lopez ◽

Marta S. Lopes ◽

Joaquim Bellvert ◽

Jose Miguel Soriano

Keyword(s):

Abiotic Stress ◽

Grain Yield ◽

Candidate Gene ◽

High Throughput ◽

Complex Traits ◽

Vegetation Index ◽

Genome Wide Association Study ◽

Agronomic Traits ◽

Wheat Breeding ◽

A Genome

Understanding the genetic basis of agronomic traits is essential for wheat breeding programmes to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can become a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin that were phenotyped for agronomic and VI traits derived from multispectral images over three and two years, respectively. GWAS identified 2579 marker-trait associations (MTAs). The QTL overview index statistic detected 11 QTL hotspots involving more than one trait in at least two years. A candidate gene analysis detected 12 CGs upregulated under abiotic stress in 6 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.

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Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 × 'AC Domain'

Genome ◽

10.1139/g05-055 ◽

2005 ◽

Vol 48 (5) ◽

pp. 870-883 ◽

Cited By ~ 165

Author(s):

C A McCartney ◽

D J Somers ◽

D G Humphreys ◽

O Lukow ◽

N Ames ◽

...

Keyword(s):

Triticum Aestivum ◽

Quantitative Trait Loci ◽

Grain Yield ◽

Plant Height ◽

Quantitative Trait ◽

Agronomic Traits ◽

Grain Weight ◽

Test Weight ◽

Trait Loci ◽

1000 Grain Weight

Relatively little is known about the genetic control of agronomic traits in common wheat (Triticum aestivum L.) compared with traits that follow Mendelian segregation patterns. A doubled-haploid population was generated from the cross RL4452 × 'AC Domain' to study the inheritance of the agronomic traits: plant height, time to maturity, lodging, grain yield, test weight, and 1000-grain weight. This cross includes the genetics of 2 western Canadian wheat marketing classes. Composite interval mapping was conducted with a microsatellite linkage map, incorporating 369 loci, and phenotypic data from multiple Manitoba environments. The plant height quantitative trait loci (QTLs), QHt.crc-4B and QHt.crc-4D, mapped to the expected locations of Rht-B1 and Rht-D1. These QTLs were responsible for most of the variation in plant height and were associated with other agronomic traits. An additional 25 agronomic QTLs were detected in the RL4452 × 'AC Domain' population beyond those associated with QHt.crc-4B and QHt.crc-4D. 'AC Domain' contributed 4 alleles for early maturity, including a major time to maturity QTL on 7D. RL4452 contributed 2 major alleles for increased grain yield at QYld.crc-2B and QYld.crc-4A, which are potential targets for marker-assisted selection. A key test weight QTL was detected on 3B and prominent 1000-grain weight QTLs were identified on 3D and 4A.Key words: height, lodging, mapping, maturity, microsatellite markers, test weight, 1000-grain weight, Triticum aestivum, wheat, yield.

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Identification of quantitative trait loci for agronomic traits contributed by a barley (Hordeum vulgare) Mediterranean landrace

Crop and Pasture Science ◽

10.1071/cp15149 ◽

2016 ◽

Vol 67 (1) ◽

pp. 37 ◽

Cited By ~ 6

Author(s):

Ridha Boudiar ◽

Ana M. Casas ◽

Carlos P. Cantalapiedra ◽

M. Pilar Gracia ◽

Ernesto Igartua

Keyword(s):

Quantitative Trait Loci ◽

Hordeum Vulgare ◽

Grain Yield ◽

Quantitative Trait ◽

Agronomic Traits ◽

Genotyping By Sequencing ◽

Kernel Weight ◽

Nucleotide Polymorphisms ◽

Hordeum Vulgare L ◽

Trait Loci

Some Spanish barley (Hordeum vulgare L.) landraces perform better than modern cultivars at low-production sites. The objective of this study was to identify favourable quantitative trait loci (QTLs) for interesting agronomic traits contributed by the landrace SBCC073. To achieve this objective, a population of 100 BC1F5 lines was derived from the cross between the elite cultivar Orria, with high productivity, and the Spanish landrace SBCC073, which was the best performer in low-production trials. The population was evaluated in field trials for 3 years (2011, 2013, and 2014) in Zaragoza, Spain. The population was genotyped with a DArTseq genotyping-by-sequencing assay. A genetic linkage map was developed by using markers of four flowering-time genes and 1227 single-nucleotide polymorphisms of good quality. The genetic map resulted in 11 linkage groups, covering a total distance of 871.1 cM. Five QTLs for grain yield were detected on 2H.1, 4H, 5H and 6H.2. Alleles from SBCC073 contributed to increased yield in three of them. A region at the end of chromosome 5H contains favourable alleles for early vigour, higher grain yield and earlier flowering, all derived from SBCC073. Alleles from Orria contributed to increasing grain yield and simultaneously to reducing plant height on the same region of 6H.2, and to increasing 1000-kernel weight on chromosomes 3H and 5H.

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A genome scan for quantitative trait loci affecting grain yield and its components of maize both in single-and two-locus levels

Science Bulletin ◽

10.1007/s11434-006-1452-2 ◽

2006 ◽

Vol 51 (12) ◽

pp. 1452-1461 ◽

Cited By ~ 3

Author(s):

Jianbing Yan ◽

Hua Tang ◽

Yiqin Huang ◽

Yonglian Zheng ◽

Chander Subhash ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Grain Yield ◽

Quantitative Trait ◽

Genome Scan ◽

A Genome ◽

Trait Loci

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Quantitative trait loci for agronomic traits in tetraploid wheat for enhancing grain yield in Kazakhstan environments

PLoS ONE ◽

10.1371/journal.pone.0234863 ◽

2020 ◽

Vol 15 (6) ◽

pp. e0234863 ◽

Cited By ~ 1

Author(s):

Shynar Anuarbek ◽

Saule Abugalieva ◽

Nicola Pecchioni ◽

Giovanni Laidò ◽

Marco Maccaferri ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Grain Yield ◽

Quantitative Trait ◽

Agronomic Traits ◽

Tetraploid Wheat ◽

Trait Loci

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Analysis of Quantitative Trait Loci (QTL) for Grain Yield and Agronomic Traits in Wheat (Triticum aestivum L.) Under Normal and Salt-Stress Conditions

Plant Molecular Biology Reporter ◽

10.1007/s11105-015-0876-8 ◽

2015 ◽

Vol 33 (6) ◽

pp. 2030-2040 ◽

Cited By ~ 9

Author(s):

Vahideh Narjesi ◽

Mohsen Mardi ◽

Eslam Majidi Hervan ◽

Amin Azadi ◽

Mohammad Reza Naghavi ◽

...

Keyword(s):

Triticum Aestivum ◽

Salt Stress ◽

Quantitative Trait Loci ◽

Grain Yield ◽

Quantitative Trait ◽

Agronomic Traits ◽

Triticum Aestivum L ◽

Stress Conditions ◽

Trait Loci

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A Genome Scan for Quantitative Trait Loci in a Wild Population of Red Deer (Cervus elaphus)

Genetics ◽

10.1093/genetics/162.4.1863 ◽

2002 ◽

Vol 162 (4) ◽

pp. 1863-1873 ◽

Cited By ~ 3

Author(s):

J Slate ◽

P M Visscher ◽

S MacGregor ◽

D Stevens ◽

M L Tate ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Cervus Elaphus ◽

Quantitative Trait ◽

Red Deer ◽

Wild Population ◽

Additive Genetic Variance ◽

Model Organisms ◽

A Genome ◽

Trait Loci ◽

In The Wild

Abstract Recent empirical evidence indicates that although fitness and fitness components tend to have low heritability in natural populations, they may nonetheless have relatively large components of additive genetic variance. The molecular basis of additive genetic variation has been investigated in model organisms but never in the wild. In this article we describe an attempt to map quantitative trait loci (QTL) for birth weight (a trait positively associated with overall fitness) in an unmanipulated, wild population of red deer (Cervus elaphus). Two approaches were used: interval mapping by linear regression within half-sib families and a variance components analysis of a six-generation pedigree of >350 animals. Evidence for segregating QTL was found on three linkage groups, one of which was significant at the genome-wide suggestive linkage threshold. To our knowledge this is the first time that a QTL for any trait has been mapped in a wild mammal population. It is hoped that this study will stimulate further investigations of the genetic architecture of fitness traits in the wild.

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Mapping of Quantitative Trait Loci Controlling Adaptive Traits in Coastal Douglas Fir. III. Quantitative Trait Loci-by-Environment Interactions

Genetics ◽

10.1093/genetics/165.3.1489 ◽

2003 ◽

Vol 165 (3) ◽

pp. 1489-1506

Author(s):

Kathleen D Jermstad ◽

Daniel L Bassoni ◽

Keith S Jech ◽

Gary A Ritchie ◽

Nicholas C Wheeler ◽

...

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Complex Traits ◽

Moisture Stress ◽

Interval Mapping ◽

Douglas Fir ◽

Adaptive Traits ◽

Growth Cessation ◽

Trait Loci ◽

Growth Initiation

Abstract Quantitative trait loci (QTL) were mapped in the woody perennial Douglas fir (Pseudotsuga menziesii var. menziesii [Mirb.] Franco) for complex traits controlling the timing of growth initiation and growth cessation. QTL were estimated under controlled environmental conditions to identify QTL interactions with photoperiod, moisture stress, winter chilling, and spring temperatures. A three-generation mapping population of 460 cloned progeny was used for genetic mapping and phenotypic evaluations. An all-marker interval mapping method was used for scanning the genome for the presence of QTL and single-factor ANOVA was used for estimating QTL-by-environment interactions. A modest number of QTL were detected per trait, with individual QTL explaining up to 9.5% of the phenotypic variation. Two QTL-by-treatment interactions were found for growth initiation, whereas several QTL-by-treatment interactions were detected among growth cessation traits. This is the first report of QTL interactions with specific environmental signals in forest trees and will assist in the identification of candidate genes controlling these important adaptive traits in perennial plants.

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