Molecular mapping of quantitative trait loci for kernel morphology traits in a non-1BL.1RS×1BL.1RS wheat cross

2011 ◽  
Vol 62 (8) ◽  
pp. 625 ◽  
Author(s):  
Yonggui Xiao ◽  
Shengmei He ◽  
Jun Yan ◽  
Yong Zhang ◽  
Yelun Zhang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Quantitative Trait ◽  
Molecular Mapping ◽  
Length Ratio ◽  
Phenotypic Variance ◽  
Kernel Length ◽  
Main Effect ◽  
Trait Loci ◽  
Kernel Morphology

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.

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

Genes ◽  
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.

scholarly journals Overdominance and Epistasis Are Important for the Genetic Basis of Heterosis in Brassica rapa

HortScience ◽  
2007 ◽  
Vol 42 (5) ◽  
pp. 1207-1211 ◽  
Author(s):  
De-Kun Dong ◽  
Jia-Shu Cao ◽  
Kai Shi ◽  
Le-Cheng Liu
Keyword(s):  
Quantitative Trait Loci ◽  
Brassica Rapa ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Phenotypic Variance ◽  
Epistasis Analysis ◽  
Main Effect ◽  
Trait Loci ◽  
Component Traits ◽  
The Cross

To investigate the genetic basis of heterosis in Brassica rapa, an F2 population was produced from the cross of B. rapa L. subsp. chinensis (L.) Hanelt and B. rapa L. subsp. rapifera Metzg. Trait performances of the F1 hybrid showed evident mid parent heterosis, which varied from 18.55% to 101.62% for the 11 traits investigated. A total of 23 main effect quantitative trait loci (QTLs) were detected for biomass and its component traits, which could explain 4.38% to 47.80% of the phenotypic variance, respectively. Sixty-five percent of these QTLs showed obvious overdominance. Epistasis analysis detected 444 two-locus interactions for the 11 traits at the threshold of P < 0.005. Some of them remained significant when more stringent threshold were set. These results suggested that overdominance and epistasis might play an important role as the genetic basis of heterosis in B. rapa.

scholarly journals Identification and mapping of quantitative trait loci for resistance to Liriomyza trifolii in romaine lettuce cultivar ‘Valmaine’

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ramkrishna Kandel ◽  
Huangjun Lu ◽  
Germán V. Sandoya
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Molecular Mapping ◽  
Leafy Vegetables ◽  
Controlled Environment ◽  
Phenotypic Variance ◽  
Liriomyza Trifolii ◽  
Romaine Lettuce ◽  
Trait Loci ◽  
Lettuce Cultivar

AbstractLiriomyza trifolii (Diptera: Agromyzidae) is a leafminer that causes ruinous damage to many leafy vegetables including lettuce (Lactuca sativa L.) by stippling and tunneling the leaves. In this study, a population of 125 F3 families was developed from the intraspecific cross of ‘Valmaine’ (resistant) and ‘Okeechobee’ (susceptible) romaine cultivars for inheritance analysis and molecular mapping of the resistance loci controlling stippling damage. The experiments were conducted in an insectarium (controlled environment). Stippling damage proved to be heritable because the broad-sense heritability (H2) was 0.58. A segregation analysis suggested that a single dominant allele, Sd1 locus, controls resistance against L. trifolii. Furthermore, a quantitative trait loci (QTL) analysis identified one novel QTL, named Stippling on LG5 (qSTP5), flanked by two SNPs that were mapped to a 5.2 cM (8.5 Mb region) interval, explaining over 13% of the total phenotypic variance. Desirable allele for resistance to L. trifolii was derived from resistant cultivar Valmaine. Identification of SNPs closely linked to the QTL responsible for L. trifolii resistance should facilitate plant breeders to develop resistant romaine lettuce cultivars.

scholarly journals Conditional Mapping Identified Quantitative Trait Loci for Grain Protein Concentration Expressing Independently of Grain Yield in Canadian Durum Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuefeng Ruan ◽  
Bianyun Yu ◽  
Ron E. Knox ◽  
Wentao Zhang ◽  
Asheesh K. Singh ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Durum Wheat ◽  
Quantitative Trait ◽  
Protein Concentration ◽  
Grain Protein ◽  
Phenotypic Variance ◽  
Grain Protein Concentration ◽  
Trait Loci ◽  
Major Qtl

Grain protein concentration (GPC) is an important trait in durum cultivar development as a major determinant of the nutritional value of grain and end-use product quality. However, it is challenging to simultaneously select both GPC and grain yield (GY) due to the negative correlation between them. To characterize quantitative trait loci (QTL) for GPC and understand the genetic relationship between GPC and GY in Canadian durum wheat, we performed both traditional and conditional QTL mapping using a doubled haploid (DH) population of 162 lines derived from Pelissier × Strongfield. The population was grown in the field over 5 years and GPC was measured. QTL contributing to GPC were detected on chromosome 1B, 2B, 3A, 5B, 7A, and 7B using traditional mapping. One major QTL on 3A (QGpc.spa-3A.3) was consistently detected over 3 years accounting for 9.4–18.1% of the phenotypic variance, with the favorable allele derived from Pelissier. Another major QTL on 7A (QGpc.spa-7A) detected in 3 years explained 6.9–14.8% of the phenotypic variance, with the beneficial allele derived from Strongfield. Comparison of the QTL described here with the results previously reported led to the identification of one novel major QTL on 3A (QGpc.spa-3A.3) and five novel minor QTL on 1B, 2B and 3A. Four QTL were common between traditional and conditional mapping, with QGpc.spa-3A.3 and QGpc.spa-7A detected in multiple environments. The QTL identified by conditional mapping were independent or partially independent of GY, making them of great importance for development of high GPC and high yielding durum.

Quantitative Trait Loci for Susceptibility to Tapeworm Infection in the Red Flour Beetle

Genetics ◽  
2003 ◽  
Vol 165 (3) ◽  
pp. 1307-1315
Author(s):  
Daibin Zhong ◽  
Aditi Pai ◽  
Guiyun Yan
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Life Cycles ◽  
Red Flour Beetle ◽  
Phenotypic Variance ◽  
Flour Beetle ◽  
Trait Loci ◽  
Host Ecology ◽  
Tapeworm Infection

Abstract Parasites have profound effects on host ecology and evolution, and the effects of parasites on host ecology are often influenced by the magnitude of host susceptibility to parasites. Many parasites have complex life cycles that require intermediate hosts for their transmission, but little is known about the genetic basis of the intermediate host's susceptibility to these parasites. This study examined the genetic basis of susceptibility to a tapeworm (Hymenolepis diminuta) in the red flour beetle (Tribolium castaneum) that serves as an intermediate host in its transmission. Quantitative trait loci (QTL) mapping experiments were conducted with two independent segregating populations using amplified fragment length polymorphism (AFLP) markers and randomly amplified polymorphic DNA (RAPD) markers. A total of five QTL that significantly affected beetle susceptibility were identified in the two reciprocal crosses. Two common QTL on linkage groups 3 and 6 were identified in both crosses with similar effects on the phenotype, and three QTL were unique to each cross. In one cross, the three main QTL accounted for 29% of the total phenotypic variance and digenic epistasis explained 39% of the variance. In the second cross, the four main QTL explained 62% of the variance and digenic epistasis accounted for only 5% of the variance. The actions of these QTL were either overdominance or underdominance. Our results suggest that the polygenic nature of beetle susceptibility to the parasites and epistasis are important genetic mechanisms for the maintenance of variation within or among beetle strains in susceptibility to tapeworm infection.

scholarly journals The Genetic Basis of the Interspecific Differences in Wing Size in Nasonia (Hymenoptera; Pteromalidae): Major Quantitative Trait Loci and Epistasis

Genetics ◽  
2002 ◽  
Vol 161 (2) ◽  
pp. 673-684
Author(s):  
J Gadau ◽  
R E Page ◽  
J H Werren
Keyword(s):  
Quantitative Trait Loci ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Wing Length ◽  
Size Difference ◽  
Phenotypic Variance ◽  
Wing Size ◽  
Epistatic Interactions ◽  
Trait Loci ◽  
Wing Width

Abstract There is a 2.5-fold difference in male wing size between two haplodiploid insect species, Nasonia vitripennis and N. giraulti. The haploidy of males facilitated a full genomic screen for quantitative trait loci (QTL) affecting wing size and the detection of epistatic interactions. A QTL analysis of the interspecific wing-size difference revealed QTL with major effects and epistatic interactions among loci affecting the trait. We analyzed 178 hybrid males and initially found two major QTL for wing length, one for wing width, three for a normalized wing-size variable, and five for wing seta density. One QTL for wing width explains 38.1% of the phenotypic variance, and the same QTL explains 22% of the phenotypic variance in normalized wing size. This corresponds to a region previously introgressed from N. giraulti into N. vitripennis that accounts for 44% of the normalized wing-size difference between the species. Significant epistatic interactions were also found that affect wing size and density of setae on the wing. Screening for pairwise epistatic interactions between loci on different linkage groups revealed four additional loci for wing length and four loci for normalized wing size that were not detected in the original QTL analysis. We propose that the evolution of smaller wings in N. vitripennis males is primarily the result of major mutations at few genomic regions and involves epistatic interactions among some loci.

Quantitative Trait Loci Affecting Differences in Floral Morphology Between Two Species of Monkeyflower (Mimulus)

Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 367-382 ◽  
Author(s):  
H D Bradshaw ◽  
Kevin G Otto ◽  
Barbara E Frewen ◽  
John K McKay ◽  
Douglas W Schemske
Keyword(s):  
Quantitative Trait Loci ◽  
Reproductive Isolation ◽  
Quantitative Trait ◽  
Floral Morphology ◽  
Cumulative Effect ◽  
Sympatric Species ◽  
Accurate Estimate ◽  
Phenotypic Variance ◽  
Trait Loci ◽  
Morphological Differences

Abstract Conspicuous differences in floral morphology are partly responsible for reproductive isolation between two sympatric species of monkeyflower because of their effect on visitation of the flowers by different pollinators. Mimulus lewisii flowers are visited primarily by bumblebees, whereas M. cardinalis flowers are visited mostly by hummingbirds. The genetic control of 12 morphological differences between the flowers of M. lewisii and M. cardinalis was explored in a large linkage mapping population of F2 plants (n = 465) to provide an accurate estimate of the number and magnitude of effect of quantitative trait loci (QTLs) governing each character. Between one and six QTLs were identified for each trait. Most (9/12) traits appear to be controlled in part by at least one major QTL explaining ≥25% of the total phenotypic variance. This implies that either single genes of individually large effect or linked clusters of genes with a large cumulative effect can play a role in the evolution of reproductive isolation and speciation.

scholarly journals Quantitative Trait Loci for Grain Yield and Adaptation of Durum Wheat (Triticum durumDesf.) Across a Wide Range of Water Availability

Genetics ◽  
2008 ◽  
Vol 178 (1) ◽  
pp. 489-511 ◽  
Author(s):  
Marco Maccaferri ◽  
Maria Corinna Sanguineti ◽  
Simona Corneti ◽  
José Luis Araus Ortega ◽  
Moncef Ben Salem ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Grain Yield ◽  
Durum Wheat ◽  
Water Availability ◽  
Quantitative Trait ◽  
Wide Range ◽  
Trait Loci

scholarly journals Wheat genetic resources – how to exploit?

2011 ◽  
Vol 47 (Special Issue) ◽  
pp. S43-S48 ◽  
Author(s):  
A. Börner ◽  
K. Neumann ◽  
B. Kobiljski
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Resources ◽  
Quantitative Trait ◽  
Molecular Mapping ◽  
Agronomic Traits ◽  
Wide Spectrum ◽  
Plant Genetic Resources ◽  
Germplasm Collections ◽  
Food And Agriculture ◽  
Trait Loci

It is estimated that world-wide existing germplasm collections contain about 7.5 million accessions of plant genetic resources for food and agriculture. Wheat (Triticum and Aegilops) represents the biggest group comprising 900 000 accessions. However, such a huge number of accessions is hindering a successful exploitation of the germplasm. The creation of core collections representing a wide spectrum of the genetic variation of the whole assembly may help to overcome the problem. Here we demonstrate the successful utilisation of such a core collection for the identification and molecular mapping of genes (Quantitative Trait Loci) determining the agronomic traits flowering time and grain yield, exploiting a marker-trait-association based technique. Significant marker-trait associations were obtained and are presented. The intrachromosomal location of many of these associations coincided with those of already identified major genes or quantitative trait loci, but others were detected in regions where no known genes have been located to date.

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