scholarly journals RFLP mapping in soybean: association between marker loci and variation in quantitative traits.

Genetics ◽  
1990 ◽  
Vol 126 (3) ◽  
pp. 735-742 ◽  
Author(s):  
P Keim ◽  
B W Diers ◽  
T C Olson ◽  
R C Shoemaker
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Glycine Soja ◽  
Interspecific Cross ◽  
Field Trials ◽  
Rflp Markers ◽  
Progeny Testing ◽  
Trait Loci ◽  
Marker Loci

Abstract We have constructed a genetic map for soybean and identified associations between genetic markers and quantitative trait loci. One-hundred-fifty restriction fragment length polymorphisms (RFLPs) were used to identify genetic linkages in an F2 segregating population from an interspecific cross (Glycine max x Glycine soja). Twenty-six genetic linkage groups containing ca. 1200 recombination units are reported. Progeny-testing of F2-derived families allowed quantitative traits to be evaluated in replicated field trials. Genomic regions, which accounted for a portion of the genetic variation (R2 = 16 to 24%) in several reproductive and morphological traits, were linked to RFLP markers. Significant associations between RFLP markers and quantitative trait loci were detected for eight of nine traits evaluated. The ability to identify genes within a continuously varying trait has important consequences for plant breeding and for understanding evolutionary processes.

scholarly journals The contribution of quantitative trait loci and neutral marker loci to the genetic variances and covariances among quantitative traits in random mating populations.

Genetics ◽  
1995 ◽  
Vol 139 (1) ◽  
pp. 445-455 ◽  
Author(s):  
A Ruiz ◽  
A Barbadilla
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Random Mating ◽  
Unbiased Estimation ◽  
Limited Information ◽  
Trait Loci ◽  
Marker Loci ◽  
Neutral Marker ◽  
Variance Explained

Abstract Using Cockerham's approach of orthogonal scales, we develop genetic models for the effect of an arbitrary number of multiallelic quantitative trait loci (QTLs) or neutral marker loci (NMLs) upon any number of quantitative traits. These models allow the unbiased estimation of the contributions of a set of marker loci to the additive and dominance variances and covariances among traits in a random mating population. The method has been applied to an analysis of allozyme and quantitative data from the European oyster. The contribution of a set marker loci may either be real, when the markers are actually QTLs, or apparent, when they are NMLs that are in linkage disequilibrium with hidden QTLs. Our results show that the additive and dominance variances contributed by a set of NMLs are always minimum estimates of the corresponding variances contributed by the associated QTLs. In contrast, the apparent contribution of the NMLs to the additive and dominance covariances between two traits may be larger than, equal to or lower than the actual contributions of the QTLs. We also derive an expression for the expected variance explained by the correlation between a quantitative trait and multilocus heterozygosity. This correlation explains only a part of the genetic variance contributed by the markers, i.e., in general, a combination of additive and dominance variances and, thus, provides only very limited information relative to the method supplied here.

scholarly journals Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Genetics ◽  
1987 ◽  
Vol 116 (1) ◽  
pp. 113-125
Author(s):  
M D Edwards ◽  
C W Stuber ◽  
J F Wendel
Keyword(s):  
Quantitative Trait Loci ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Gene Action ◽  
Individual Plant ◽  
Gene Effects ◽  
Individual Gene ◽  
Trait Loci ◽  
Marker Loci

ABSTRACT Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17–20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800–1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.

Mapping quantitative trait loci controlling soybean seed starch content in an interspecific cross of ‘Williams 82’ (Glycine max ) and ‘PI 366121’ (Glycine soja )

2017 ◽  
Vol 136 (3) ◽  
pp. 379-385 ◽  
Author(s):  
Sanjeev K. Dhungana ◽  
Krishnanand P. Kulkarni ◽  
Cheol W. Park ◽  
Hyun Jo ◽  
Jong T. Song ◽  
...  
Keyword(s):  
Glycine Max ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Glycine Soja ◽  
Starch Content ◽  
Interspecific Cross ◽  
Soybean Seed ◽  
Trait Loci

scholarly journals Comparative Quantitative Trait Loci Mapping of Partial Resistance to Puccinia sorghi Across Four Populations of European Flint Maize

1998 ◽  
Vol 88 (12) ◽  
pp. 1324-1329 ◽  
Author(s):  
Thomas Lübberstedt ◽  
Dietrich Klein ◽  
Albrecht E. Melchinger
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Partial Resistance ◽  
Interval Mapping ◽  
Field Trials ◽  
Phenotypic Variance ◽  
Puccinia Sorghi ◽  
Maize Populations ◽  
Trait Loci ◽  
Marker Loci

We mapped and characterized quantitative trait loci (QTL) for partial resistance to Puccinia sorghi and investigated consistency across different European flint maize populations. Four independent populations, containing 280 F3 lines (A×BI), 120 F5 lines (A×BII), 131 F4 lines (A×C), and 133 F4 lines (C×D) were produced from four European elite flint inbreds (A, B, C, and D) and genotyped at 89, 151, 104, and 122 restriction fragment length polymorphism marker loci, respectively. All Fn lines were evaluated in field trials with two replications in three or five (A×BI) environments. Genotypic variance was highly significant for rust ratings in all populations, and heritabilities exceeded 0.64. Between 4 and 13 QTL were detected in individual populations using composite interval mapping, explaining between 33 and 71% of the phenotypic variance. Twenty QTL were distributed over all ten chromosomes, without preference to chromosomes 3, 4, 6, and 10, which harbor qualitatively acting Rp loci. In most cases, gene action was additive or partially dominant. Four pairs of QTL displayed significant digenic epistatic interactions, and QTL-environment interactions were observed frequently. Approximately half of the QTL were consistent between A×BI and A×BII or A×C and C×D; fewer were consistent between A×BI and A×C or C×D. In European flint maize germ plasm, conventional selection for partial rust resistance seems to be more promising than marker-assisted selection.

scholarly journals Novel Quantitative Trait Loci for Grain Cadmium Content Identified in Hard White Spring Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Ling Qiao ◽  
Justin Wheeler ◽  
Rui Wang ◽  
Kyle Isham ◽  
Natalie Klassen ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Gene ◽  
Spring Wheat ◽  
Quantitative Trait ◽  
Field Trials ◽  
Cadmium Content ◽  
Wheat Population ◽  
Trait Loci ◽  
Multiple Field ◽  
First Time

Cadmium (Cd) is a heavy metal that can cause a variety of adverse effects on human health, including cancer. Wheat comprises approximately 20% of the human diet worldwide; therefore, reducing the concentrations of Cd in wheat grain will have significant impacts on the intake of Cd in food products. The tests for measuring the Cd content in grain are costly, and the content is affected significantly by soil pH. To facilitate breeding for low Cd content, this study sought to identify quantitative trait loci (QTL) and associated molecular markers that can be used in molecular breeding. One spring wheat population of 181 doubled haploid lines (DHLs), which was derived from a cross between two hard white spring wheat cultivars “UI Platinum” (UIP) and “LCS Star” (LCS), was assessed for the Cd content in grain in multiple field trials in Southeast Idaho, United States. Three major QTL regions, namely, QCd.uia2-5B, QCd.uia2-7B, and QCd.uia2-7D, were identified on chromosomes 5B, 7B, and 7D, respectively. All genes in these three QTL regions were identified from the NCBI database. However, three genes related to the uptake and transport of Cd were used in the candidate gene analysis. The sequences of TraesCS5B02G388000 (TaHMA3) in the QCd.uia2-5B region and TraesCS7B02G320900 (TaHMA2) and TraesCS7B02G322900 (TaMSRMK3) in the QCd.uia2-7B region were compared between UIP and LCS. TaHMA2 on 7B is proposed for the first time as a candidate gene for grain Cd content in wheat. A KASP marker associated with this gene was developed and it will be further validated in near-isogenic lines via a gene-editing system in future studies.

Molecular mapping of quantitative trait loci in japonica rice

Genome ◽  
1996 ◽  
Vol 39 (2) ◽  
pp. 395-403 ◽  
Author(s):  
Edilberto D. Redoña ◽  
David J. Mackill
Keyword(s):  
Oryza Sativa ◽  
Quantitative Trait Loci ◽  
Qtl Mapping ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Rflp Markers ◽  
Seedling Vigor ◽  
Trait Loci ◽  
Rice Chromosomes ◽  
Molecular Maps

Rice (Oryza sativa L.) molecular maps have previously been constructed using interspecific crosses or crosses between the two major subspecies: indica and japonica. For japonica breeding programs, however, it would be more suitable to use intrasubspecific crosses. A linkage map of 129 random amplified polymorphic DNA (RAPD) and 18 restriction fragment length polymorphism (RFLP) markers was developed using 118 F2 plants derived from a cross between two japonica cultivars with high and low seedling vigor, Italica Livorno (IL) and Labelle (LBL), respectively. The map spanned 980.5 cM (Kosambi function) with markers on all 12 rice chromosomes and an average distance of 7.6 cM between markers. Codominant (RFLP) and coupling phase linkages (among RAPDs) accounted for 79% of total map length and 71% of all intervals. This map contained a greater percentage of markers on chromosome 10, the least marked of the 12 rice chromosomes, than other rice molecular maps, but had relatively fewer markers on chromosomes 1 and 2. We used this map to detect quantitative trait loci (QTL) for four seedling vigor related traits scored on 113 F3 families in a growth chamber slantboard test at 18 °C. Two coleoptile, five root, and five mesocotyl length QTLs, each accounting for 9–50% of the phenotypic variation, were identified by interval analysis. Single-point analysis confirmed interval mapping results and detected additional markers significantly influencing each trait. About two-thirds of alleles positive for the putative QTLs were from the high-vigor parent, IL. One RAPD marker (OPAD13720) was associated with a IL allele that accounted for 18.5% of the phenotypic variation for shoot length, the most important determinant of seedling vigor in water-seeded rice. Results indicate that RAPDs are useful for map development and QTL mapping in rice populations with narrow genetic base, such as those derived from crosses among japonica cultivars. Other potential uses of the map are discussed. Key words : QTL mapping, RAPD, RFLP, seedling vigor, japonica, Oryza sativa.

Impact of the D genome and quantitative trait loci on quantitative traits in a spring durum by spring bread wheat cross

2015 ◽  
Vol 128 (9) ◽  
pp. 1799-1811 ◽  
Author(s):  
J. R. Kalous ◽  
J. M. Martin ◽  
J. D. Sherman ◽  
H.-Y. Heo ◽  
N. K. Blake ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Bread Wheat ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Spring Bread Wheat ◽  
D Genome ◽  
Trait Loci ◽  
Wheat Cross

Mapping quantitative trait loci for pre-harvest sprouting resistance in white-grained winter wheat line CA 0431

2013 ◽  
Vol 64 (6) ◽  
pp. 573 ◽  
Author(s):  
X. L. Miao ◽  
Y. J. Zhang ◽  
X. C. Xia ◽  
Z. H. He ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Winter Wheat ◽  
Quantitative Trait ◽  
Interval Mapping ◽  
Field Trials ◽  
Economic Losses ◽  
Phenotypic Variance ◽  
Wheat Line ◽  
F2 Population ◽  
Trait Loci

Pre-harvest sprouting (PHS) in wheat severely reduces yield and end-use quality, resulting in substantial economic losses. The Chinese winter wheat line CA 0431, with white grain, showed high PHS resistance for many years. To identify quantitative trait loci (QTLs) of PHS resistance in this line, 220 F2 plants and the corresponding F2 : 3 lines derived from a cross between CA 0431 and the PHS-susceptible cultivar Zhongyou 206 were used for PHS testing and QTL analysis. Field trials were conducted in Beijing during the 2010–11 and 2011–12 cropping seasons, and in Anyang during 2011–12. PHS resistance was evaluated by assessing the sprouting responses of intact spikes. In total, 1444 molecular markers were used to screen the parents, and 31 markers with polymorphisms between the resistant and susceptible bulks were used to genotype the entire F2 population. Broad-sense heritability of sprouting rate was 0.71 across environments. Inclusive composite interval mapping identified four QTLs, QPhs.caas-2BL, QPhs.caas-3AS.1, QPhs.caas-3AS.2, and QPhs.caas-3AL, each explaining 2.8–27.7% of the phenotypic variance across environments. The QTLs QPhs.caas-3AS.1, QPhs.caas-3AS.2, and QPhs.caas-3AL were located at similar positions to QTLs reported previously, whereas QPhs.caas-2BL is likely a new QTL flanked by markers Xbarc1042 and Xmag3319. Line CA 0431 and the identified markers can be used in breeding programs targeting improvement of PHS resistance for white-kernel wheat.

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