Seed dormancy in barley: identifying superior genotypes through incorporating epistatic interactions

A genetic linkage map of barley with 128 molecular markers was constructed using a doubled haploid (DH) mapping population derived from a cross between barley (Hordeum vulgare) cvv. Stirling and Harrington. Quantitative trait loci controlling seed dormancy were characterised in the population. A major quantitative trait locus (QTL) controlling seed dormancy and accounting for over half the phenotypic variation (52.17%) was identified on the distal end of the long arm of chromosome 5H. Minor QTLs were also detected near the centromeric region of 5H and on chromosomes 1H and 3H. These minor QTLs with additive effects accounted for 7.52% of the phenotypic variance measured. Examination of epistatic interactions further detected additional minor QTLs near the centromere of 2H and on the long arm and short arms of 4H. Combinations of parental alleles at the QTL locations in predictive analyses indicated dramatic differences in germination. These results emphasise the potential differences in dormancy that can be achieved through the use of specific gene combinations and highlights the importance of minor genes and the epistatic interactions that occur between them. This study found that the combination of Stirling alleles at the two QTL locations on the 5H chromosome and Harrington alleles at the 1H and 3H QTL locations significantly produced the greatest dormancy. Uncovering gene complexes controlling the trait may enable breeders to produce superior genotypes with the desirable allele combinations necessary for manipulating seed dormancy in barley.

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Modelling of genetic interactions improves prediction of hybrid patterns – a case study in domestic fowl

Genetics Research ◽

10.1017/s001667231200047x ◽

2012 ◽

Vol 94 (5) ◽

pp. 255-266 ◽

Cited By ~ 9

Author(s):

JOSÉ M. ÁLVAREZ-CASTRO ◽

ARNAUD LE ROUZIC ◽

LEIF ANDERSSON ◽

PAUL B. SIEGEL ◽

ÖRJAN CARLBORG

Keyword(s):

Phenotypic Diversity ◽

Complex Trait ◽

Phenotypic Variance ◽

Small Contribution ◽

Epistatic Interactions ◽

Multiple Loci ◽

Body Weights ◽

Gene Complexes ◽

Trait Locus

SummaryA major challenge in complex trait genetics is to unravel how multiple loci and environmental factors together cause phenotypic diversity. Both first (F1) and second (F2) generation hybrids often display phenotypes that deviate from what is expected under intermediate inheritance. We have here studied two chicken F2 populations generated by crossing divergent chicken lines to assess how epistatic loci, identified in earlier quantitative trait locus (QTL) studies, contribute to hybrid deviations from the mid-parent phenotype. Empirical evidence suggests that the average phenotypes of the intercross birds tend to be lower than the midpoint between the parental means in both crosses. Our results confirm that epistatic interactions, despite a relatively small contribution to the phenotypic variance, play an important role in the deviation of hybrid phenotypes from the mid-parent values (i.e. multi-locus hybrid genotypes lead to lower rather than higher body weights). To a lesser extent, dominance also appears to contribute to the mid-parent deviation, at least in one of the crosses. This observation coincides with the hypothesis that hybridization tends to break up co-adapted gene complexes, i.e. generate Bateson–Dobzhansky–Muller incompatibilities.

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Identification of two major quantitative trait locus for fresh seed dormancy using the diversity arrays technology and diversity arrays technology-seq based genetic map in Spanish-type peanuts

Plant Breeding ◽

10.1111/pbr.12360 ◽

2016 ◽

Vol 135 (3) ◽

pp. 367-375 ◽

Cited By ~ 10

Author(s):

Manish K Vishwakarma ◽

Manish K Pandey ◽

Yaduru Shasidhar ◽

Surendra S Manohar ◽

Patne Nagesh ◽

...

Keyword(s):

Quantitative Trait Locus ◽

Genetic Map ◽

Seed Dormancy ◽

Quantitative Trait ◽

Major Quantitative Trait Locus ◽

Diversity Arrays Technology ◽

Fresh Seed ◽

Trait Locus

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Faculty Opinions recommendation of Cloning of DOG1, a quantitative trait locus controlling seed dormancy in Arabidopsis.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1048305.500216 ◽

2006 ◽

Author(s):

Julin Maloof

Keyword(s):

Quantitative Trait Locus ◽

Seed Dormancy ◽

Quantitative Trait ◽

Trait Locus

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

Genetics ◽

10.1093/genetics/161.2.673 ◽

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.

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Relationship between Yield Components and Partial Resistance to Lecanicillium fungicola in the Button Mushroom, Agaricus bisporus, Assessed by Quantitative Trait Locus Mapping

Applied and Environmental Microbiology ◽

10.1128/aem.07554-11 ◽

2012 ◽

Vol 78 (7) ◽

pp. 2435-2442 ◽

Cited By ~ 23

Author(s):

Marie Foulongne-Oriol ◽

Anne Rodier ◽

Jean-Michel Savoie

Keyword(s):

Quantitative Trait ◽

Wild Strain ◽

Genomic Region ◽

Yield Component ◽

Phenotypic Variance ◽

Button Mushroom ◽

Content Type ◽

Dry Bubble ◽

Trait Locus ◽

Genomic Regions

ABSTRACTDry bubble, caused byLecanicillium fungicola, is one of the most detrimental diseases affecting button mushroom cultivation. In a previous study, we demonstrated that breeding for resistance to this pathogen is quite challenging due to its quantitative inheritance. A second-generation hybrid progeny derived from an intervarietal cross between a wild strain and a commercial cultivar was characterized forL. fungicolaresistance under artificial inoculation in three independent experiments. Analysis of quantitative trait loci (QTL) was used to determine the locations, numbers, and effects of genomic regions associated with dry-bubble resistance. Four traits related to resistance were analyzed. Two to four QTL were detected per trait, depending on the experiment. Two genomic regions, on linkage group X (LGX) and LGVIII, were consistently detected in the three experiments. The genomic region on LGX was detected for three of the four variables studied. The total phenotypic variance accounted for by all QTL ranged from 19.3% to 42.1% over all traits in all experiments. For most of the QTL, the favorable allele for resistance came from the wild parent, but for some QTL, the allele that contributed to a higher level of resistance was carried by the cultivar. Comparative mapping with QTL for yield-related traits revealed five colocations between resistance and yield component loci, suggesting that the resistance results from both genetic factors and fitness expression. The consequences for mushroom breeding programs are discussed.

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

Genetics ◽

10.1093/genetics/153.3.1233 ◽

1999 ◽

Vol 153 (3) ◽

pp. 1233-1243 ◽

Cited By ~ 6

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.

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