scholarly journals Quantitative Trait Loci Analysis of Resistance to Sclerotinia sclerotiorum in Sunflower

2005 ◽  
Vol 95 (7) ◽  
pp. 834-839 ◽  
Author(s):  
S. Rönicke ◽  
V. Hahn ◽  
A. Vogler ◽  
W. Friedt
Keyword(s):  
Quantitative Trait Loci ◽  
Sclerotinia Sclerotiorum ◽  
Quantitative Trait ◽  
Interval Mapping ◽  
Lesion Length ◽  
Phenotypic Variance ◽  
Linkage Groups ◽  
Mapping Procedure ◽  
Trait Loci ◽  
Head Rot

A quantitative trait loci (QTL) analysis of resistance to Sclerotinia sclerotiorum was carried out with 283 sunflower (Helianthus annuus) F2:3 families derived from a cross between a resistant (SWS-B-04) and a highly susceptible sunflower inbred line. For that purpose, a genetic map based on 195 amplified fragment length polymorphism and 20 simple sequence repeat markers was constructed. The map has a size of 2,273.5 centimorgans and comprises 17 linkage groups, 12 of which could be associated to already defined linkage groups. The heads of sunflower F3 families were artificially inoculated by using sclerotinia mycelium in three field environments. The lesion length was measured in centimeters 1 week postinoculation and head rot was scored according to a 1-to-8 head rot scale 2 weeks postinoculation. Using the composite interval mapping procedure, three QTL for lesion length and two QTL for head rot could be identified. These QTL explain 10.6 to 17.1% of the total phenotypic variance.

scholarly journals Quantitative Trait Loci Affecting Survival and Fertility-Related Traits in Caenorhabditis elegans Show Genotype-Environment Interactions, Pleiotropy and Epistasis

Genetics ◽  
1999 ◽  
Vol 153 (3) ◽  
pp. 1233-1243 ◽  
Author(s):  
David R Shook ◽  
Thomas E Johnson
Keyword(s):  
Caenorhabditis Elegans ◽  
Quantitative Trait Loci ◽  
Population Growth ◽  
Quantitative Trait ◽  
Age Of Onset ◽  
Inbred Strains ◽  
Interval Mapping ◽  
Phenotypic Variance ◽  
Epistatic Interactions ◽  
Trait Loci

Abstract We have identified, using composite interval mapping, quantitative trait loci (QTL) affecting a variety of life history traits (LHTs) in the nematode Caenorhabditis elegans. Using recombinant inbred strains assayed on the surface of agar plates, we found QTL for survival, early fertility, age of onset of sexual maturity, and population growth rate. There was no overall correlation between survival on solid media and previous measures of survival in liquid media. Of the four survival QTL found in these two environments, two have genotype-environment interactions (GEIs). Epistatic interactions between markers were detected for four traits. A multiple regression approach was used to determine which single markers and epistatic interactions best explained the phenotypic variance for each trait. The amount of phenotypic variance accounted for by genetic effects ranged from 13% (for internal hatching) to 46% (for population growth). Epistatic effects accounted for 9–11% of the phenotypic variance for three traits. Two regions containing QTL that affected more than one fertility-related trait were found. This study serves as an example of the power of QTL mapping for dissecting the genetic architecture of a suite of LHTs and indicates the potential importance of environment and GEIs in the evolution of this architecture.

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.

A random model approach to interval mapping of quantitative trait loci.

Genetics ◽  
1995 ◽  
Vol 141 (3) ◽  
pp. 1189-1197 ◽  
Author(s):  
S Xu ◽  
W R Atchley
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Fixed Effects ◽  
Interval Mapping ◽  
Random Model ◽  
Likelihood Method ◽  
Mapping Procedure ◽  
Trait Loci ◽  
Outbred Populations ◽  
Model Approach

Abstract Mapping quantitative trait loci in outbred populations is important because many populations of organisms are noninbred. Unfortunately, information about the genetic architecture of the trait may not be available in outbred populations. Thus, the allelic effects of genes can not be estimated with ease. In addition, under linkage equilibrium, marker genotypes provide no information about the genotype of a QTL (our terminology for a single quantitative trait locus is QTL while multiple loci are referred to as QTLs). To circumvent this problem, an interval mapping procedure based on a random model approach is described. Under a random model, instead of estimating the effects, segregating variances of QTLs are estimated by a maximum likelihood method. Estimation of the variance component of a QTL depends on the proportion of genes identical-by-descent (IBD) shared by relatives at the locus, which is predicted by the IBD of two markers flanking the QTL. The marker IBD shared by two relatives are inferred from the observed marker genotypes. The procedure offers an advantage over the regression interval mapping in terms of high power and small estimation errors and provides flexibility for large sibships, irregular pedigree relationships and incorporation of common environmental and fixed effects.

scholarly journals Quantitative Trait Loci Mapping of Resistance to Sugarcane Mosaic Virus in Maize

1999 ◽  
Vol 89 (8) ◽  
pp. 660-667 ◽  
Author(s):  
Xianchun Xia ◽  
Albrecht E. Melchinger ◽  
Lissy Kuntze ◽  
Thomas Lübberstedt
Keyword(s):  
Quantitative Trait Loci ◽  
Mosaic Virus ◽  
Quantitative Trait ◽  
Virus Disease ◽  
Interval Mapping ◽  
Field Trials ◽  
Sugarcane Mosaic Virus ◽  
Phenotypic Variance ◽  
Environment Interaction ◽  
Trait Loci

Sugarcane mosaic virus (SCMV) is an important virus disease of maize (Zea mays) in Europe. In this study, we mapped and characterized quantitative trait loci (QTL) affecting resistance to SCMV in a maize population consisting of 219 F3 or immortalized F2 families from the cross of two European maize inbreds, D32 (resistant) × D145 (susceptible). Resistance was evaluated in replicated field trials across two environments under artificial inoculation. The method of composite interval mapping was employed for QTL detection with a linkage map based on 87 restriction fragment length polymorphism and 7 mapped microsatellite markers. Genotypic and genotype × environment interaction variances for SCMV resistance were highly significant in the population. Heritabilities ranged from 0.77 to 0.94 for disease scores recorded on seven consecutive dates. Five QTL for SCMV resistance were identified on chromosomes 1, 3, 5, 6, and 10 in the joint analyses. Two major QTL on chromosomes 3 and 6 were detected consistently in both environments. Significant epistatic effects were found among some of these QTL. A simultaneous fit with all QTL in the joint analyses explained between 70 and 77% of the phenotypic variance observed at various stages of plant development. Resistance to SCMV was correlated with plant height and days to anthesis.

Mapping of quantitative trait loci controlling broomrape (Orobanche crenata Forsk.) resistance in faba bean (Vicia faba L.)

Genome ◽  
2002 ◽  
Vol 45 (6) ◽  
pp. 1057-1063 ◽  
Author(s):  
Belén Román ◽  
Ana M Torres ◽  
Diego Rubiales ◽  
Jose Ignacio Cubero ◽  
Zlatko Satovic
Keyword(s):  
Quantitative Trait Loci ◽  
Vicia Faba ◽  
Faba Bean ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Interval Mapping ◽  
Phenotypic Variance ◽  
Orobanche Crenata ◽  
Resistant Parent ◽  
Trait Loci

Orobanche crenata Forsk. is a root parasite that produces devastating effects on many crop legumes and has become a limiting factor for faba bean production in the Mediterranean region. The efficacy of available control methods is minimal and breeding for broomrape resistance remains the most promising method of control. Resistance seems to be scarce and complex in nature, being a quantitative characteristic difficult to manage in breeding programmes. To identify and map the QTLs (quantitative trait loci) controlling the trait, 196 F2 plants derived from the cross between a susceptible and a resistant parent were analysed using isozymes, RAPD, seed protein genes, and microsatellites. F2- derived F3 lines were studied for broomrape resistance under field conditions. Of the 130 marker loci segregating in the F2 population, 121 could be mapped into 16 linkage groups. Simple interval mapping (SIM) and composite interval mapping (CIM) were performed using QTL Cartographer. Composite interval mapping using the maximum number of markers as cofactors was clearly the most efficient way to locate putative QTLs. Three QTLs for broomrape resistance were detected. One of the three QTLs explained more than 35% of the phenotypic variance, whereas the others accounted for 11.2 and 25.5%, respectively. This result suggests that broomrape resistance in faba bean can be considered a polygenic trait with major effects of a few single genes.Key words: Orobanche crenata, Vicia faba, QTL, broomrape resistance.

Mapping Quantitative Trait Loci for Complex Binary Diseases Using Line Crosses

Genetics ◽  
1996 ◽  
Vol 143 (3) ◽  
pp. 1417-1424 ◽  
Author(s):  
Shizhong Xu ◽  
William R Atchley
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Threshold Model ◽  
Interval Mapping ◽  
Quantitative Character ◽  
Mapping Procedure ◽  
Single Quantitative Trait Locus ◽  
Trait Loci ◽  
Trait Locus ◽  
Normally Distributed

Abstract A composite interval gene mapping procedure for complex binary disease traits is proposed in this paper. The binary trait of interest is assumed to be controlled by an underlying liability that is normally distributed. The liability is treated as a typical quantitative character and thus described by the usual quantitative genetics model. Translation from the liability into a binary (disease) phenotype is through the physiological threshold model. Logistic regression analysis is employed to estimate the effects and locations of putative quantitative trait loci (our terminology for a single quantitative trait locus is QTL while multiple loci are referred to as QTLs). Simulation studies show that properties of this mapping procedure mimic those of the composite interval mapping for normally distributed data. Potential utilization of the QTL mapping procedure for resolving alternative genetic models (e.g., single- or two-trait-locus model) is discussed.

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 Identifying Quantitative Trait Loci for Resistance to Sclerotinia Head Rot in Two USDA Sunflower Germplasms

2008 ◽  
Vol 98 (8) ◽  
pp. 926-931 ◽  
Author(s):  
B. Yue ◽  
S. A. Radi ◽  
B. A. Vick ◽  
X. Cai ◽  
S. Tang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Field Experiments ◽  
Disease Incidence ◽  
Block Design ◽  
Phenotypic Variance ◽  
Target Region ◽  
Trait Loci ◽  
Head Rot

Sclerotinia head rot is a major disease of sunflower in the world, and quantitative trait loci (QTL) mapping could facilitate understanding of the genetic basis of head rot resistance and breeding in sunflower. One hundred twenty-three F2:3 and F2:4 families from a cross between HA 441 and RHA 439 were studied. The mapping population was evaluated for disease resistance in three field experiments in a randomized complete block design with two replicates. Disease incidence (DI) and disease severity (DS) were assessed. A genetic map with 180 target region amplification polymorphism, 32 simple sequence repeats, 11 insertion-deletion, and 2 morphological markers was constructed. Nine DI and seven DS QTL were identified with each QTL explaining 8.4 to 34.5% of phenotypic variance, suggesting the polygenic basis of the resistance to head rot. Five of these QTL were identified in more than one experiment, and each QTL explained more than 12.9% of phenotypic variance. These QTL could be useful in sunflower breeding. Although a positive correlation existed between the two disease indices, most of the respective QTL were located in different chromosomal regions, suggesting a different genetic basis for the two indices.

Mapping of quantitative trait loci for fire blight resistance in the apple cultivars ‘Florina’ and ‘Nova Easygro’

Genome ◽  
2010 ◽  
Vol 53 (9) ◽  
pp. 710-722 ◽  
Author(s):  
P.-M. F. Le Roux ◽  
M. A. Khan ◽  
G. A.L. Broggini ◽  
B. Duffy ◽  
C. Gessler ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Linkage Group ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Fire Blight ◽  
Shoot Length ◽  
Blight Resistance ◽  
Lesion Length ◽  
Linkage Groups ◽  
Trait Loci

Fire blight is a devastating bacterial disease of rosaceous plants. Its damage to apple production is a major concern, since no existing control option has proven to be completely effective. Some commercial apple varieties, such as ‘Florina’ and ‘Nova Easygro’, exhibit a consistent level of resistance to fire blight. In this study, we used an F1 progeny of ‘Florina’ × ‘Nova Easygro’ to build parental genetic maps and identify quantitative trait loci (QTLs) related to fire blight resistance. Linkage maps were constructed using a set of microsatellites and enriched with amplified fragment length polymorphism (AFLP) markers. In parallel, progeny plants were artificially inoculated with Erwinia amylovora strain CFBP 1430 in a quarantine glasshouse. Shoot length measured 7 days after inoculation (DAI) and lesion length measured 7 and 14 DAI were used to calculate the lesion length as a percentage of the shoot length (PLL1 and PLL2, respectively). Percent lesion length data were log10-transformed (log10(PLL)) and used to perform the Kruskal–Wallis test, interval mapping (IM), and multiple QTL mapping (MQM). Two significant fire blight resistance QTLs were detected in ‘Florina’. One QTL was mapped on linkage group 10 by IM and MQM; it explained 17.9% and 15.3% of the phenotypic variation by MQM with log10(PLL1) and log10(PLL2) data, respectively. A second QTL was identified on linkage group 5 by MQM with log10(PLL2) data; it explained 10.1% of the phenotypic variation. Genotyping the plants of ‘Florina’ pedigree with the microsatellites flanking the QTLs showed that the QTLs on linkage groups 5 and 10 were inherited from ‘Jonathan’ and ‘Starking’ (a ‘Red Delicious’ sport mutation), respectively. Other putative QTLs (defined as QTLs with LOD scores above the chromosomal threshold and below the genome-wide threshold) were detected by IM on linkage groups 5 and 9 of ‘Nova Easygro’.

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