scholarly journals Quantitative trait loci mapping of phenotypic plasticity and genotype–environment interactions in plant and insect performance

2011 ◽  
Vol 366 (1569) ◽  
pp. 1368-1379 ◽  
Author(s):  
C. Tétard-Jones ◽  
M. A. Kertesz ◽  
R. F. Preziosi
Keyword(s):  
Phenotypic Plasticity ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Environment Interaction ◽  
Mapping Procedure ◽  
Barley Genome ◽  
Community Genetic ◽  
Main Effect ◽  
Trait Loci

Community genetic studies generally ignore the plasticity of the functional traits through which the effect is passed from individuals to the associated community. However, the ability of organisms to be phenotypically plastic allows them to rapidly adapt to changing environments and plasticity is commonly observed across all taxa. Owing to the fitness benefits of phenotypic plasticity, evolutionary biologists are interested in its genetic basis, which could explain how phenotypic plasticity is involved in the evolution of species interactions. Two current ideas exist: (i) phenotypic plasticity is caused by environmentally sensitive loci associated with a phenotype; (ii) phenotypic plasticity is caused by regulatory genes that simply influence the plasticity of a phenotype. Here, we designed a quantitative trait loci (QTL) mapping experiment to locate QTL on the barley genome associated with barley performance when the environment varies in the presence of aphids, and the composition of the rhizosphere. We simultaneously mapped aphid performance across variable rhizosphere environments. We mapped main effects, QTL × environment interaction (QTL×E), and phenotypic plasticity (measured as the difference in mean trait values) for barley and aphid performance onto the barley genome using an interval mapping procedure. We found that QTL associated with phenotypic plasticity were co-located with main effect QTL and QTL×E. We also located phenotypic plasticity QTL that were located separately from main effect QTL. These results support both of the current ideas of how phenotypic plasticity is genetically based and provide an initial insight into the functional genetic basis of how phenotypically plastic traits may still be important sources of community genetic effects.

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 Genotype-Environment Interaction for Quantitative Trait Loci Affecting Life Span in Drosophila melanogaster

Genetics ◽  
2000 ◽  
Vol 154 (1) ◽  
pp. 213-227 ◽  
Author(s):  
Cristina Vieira ◽  
Elena G Pasyukova ◽  
Zhao-Bang Zeng ◽  
J Brant Hackett ◽  
Richard F Lyman ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Life Span ◽  
Quantitative Trait ◽  
Recombinant Inbred Lines ◽  
Adult Life ◽  
Environment Interaction ◽  
Mapping Procedure ◽  
Genotype Environment Interaction ◽  
Trait Loci

Abstract The nature of genetic variation for Drosophila longevity in a population of recombinant inbred lines was investigated by estimating quantitative genetic parameters and mapping quantitative trait loci (QTL) for adult life span in five environments: standard culture conditions, high and low temperature, and heat-shock and starvation stress. There was highly significant genetic variation for life span within each sex and environment. In the analysis of variance of life span pooled over sexes and environments, however, the significant genetic variation appeared in the genotype × sex and genotype × environment interaction terms. The genetic correlation of longevity across the sexes and environments was not significantly different from zero in these lines. We estimated map positions and effects of QTL affecting life span by linkage to highly polymorphic roo transposable element markers, using a multiple-trait composite interval mapping procedure. A minimum of 17 QTL were detected; all were sex and/or environment-specific. Ten of the QTL had sexually antagonistic or antagonistic pleiotropic effects in different environments. These data provide support for the pleiotropy theory of senescence and the hypothesis that variation for longevity might be maintained by opposing selection pressures in males and females and variable environments. Further work is necessary to assess the generality of these results, using different strains, to determine heterozygous effects and to map the life span QTL to the level of genetic loci.

scholarly journals Quantitative Trait Loci Controlling Light and Hormone Response in Two Accessions ofArabidopsis thaliana

Genetics ◽  
2002 ◽  
Vol 160 (2) ◽  
pp. 683-696 ◽  
Author(s):  
Justin O Borevitz ◽  
Julin N Maloof ◽  
Jason Lutes ◽  
Tsegaye Dabi ◽  
Joanna L Redfern ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Natural Variation ◽  
Red Light ◽  
Light Response ◽  
Environment Interaction ◽  
Isogenic Line ◽  
Hormone Response ◽  
New Genes ◽  
Trait Loci

AbstractWe have mapped quantitative trait loci (QTL) responsible for natural variation in light and hormone response between the Cape Verde Islands (Cvi) and Landsberg erecta (Ler) accessions of Arabidopsis thaliana using recombinant inbred lines (RILs). Hypocotyl length was measured in four light environments: white, blue, red, and far-red light and in the dark. In addition, white light plus gibberellin (GA) and dark plus the brassinosteroid biosynthesis inhibitor brassinazole (BRZ) were used to detect hormone effects. Twelve QTL were identified that map to loci not previously known to affect light response, as well as loci where candidate genes have been identified from known mutations. Some QTL act in all environments while others show genotype-by-environment interaction. A global threshold was established to identify a significant epistatic interaction between two loci that have few main effects of their own. LIGHT1, a major QTL, has been confirmed in a near isogenic line (NIL) and maps to a new locus with effects in all light environments. The erecta mutation can explain the effect of the HYP2 QTL in the blue, BRZ, and dark environments, but not in far-red. LIGHT2, also confirmed in an NIL, has effects in white and red light and shows interaction with GA. The phenotype and map position of LIGHT2 suggest the photoreceptor PHYB as a candidate gene. Natural variation in light and hormone response thus defines both new genes and known genes that control light response in wild accessions.

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 Quantitative Trait Loci × Maternal Cytoplasmic Environment Interaction for Development Rate inOncorhynchus mykiss

Genetics ◽  
2006 ◽  
Vol 175 (1) ◽  
pp. 335-347 ◽  
Author(s):  
Krista M. Nichols ◽  
Karl W. Broman ◽  
Kyle Sundin ◽  
Jennifer M. Young ◽  
Paul A. Wheeler ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Development Rate ◽  
Environment Interaction ◽  
Trait Loci

scholarly journals Footprints in time: comparative quantitative trait loci mapping of the pitcher-plant mosquito, Wyeomyia smithii

2012 ◽  
Vol 279 (1747) ◽  
pp. 4551-4558 ◽  
Author(s):  
William E. Bradshaw ◽  
Kevin J. Emerson ◽  
Julian M. Catchen ◽  
William A. Cresko ◽  
Christina M. Holzapfel
Keyword(s):  
Quantitative Trait Loci ◽  
Adaptive Evolution ◽  
Quantitative Trait ◽  
Genetic Basis ◽  
Natural Populations ◽  
Cumulative Effect ◽  
Single Species ◽  
Interval Mapping ◽  
Photoperiodic Response ◽  
Trait Loci

Identifying regions of the genome contributing to phenotypic evolution often involves genetic mapping of quantitative traits. The focus then turns to identifying regions of ‘major’ effect, overlooking the observation that traits of ecological or evolutionary relevance usually involve many genes whose individual effects are small but whose cumulative effect is large. Herein, we use the power of fully interfertile natural populations of a single species of mosquito to develop three quantitative trait loci (QTL) maps: one between two post-glacially diverged populations and two between a more ancient and a post-glacial population. All demonstrate that photoperiodic response is genetically a highly complex trait. Furthermore, we show that marker regressions identify apparently ‘non-significant’ regions of the genome not identified by composite interval mapping, that the perception of the genetic basis of adaptive evolution is crucially dependent upon genetic background and that the genetic basis for adaptive evolution of photoperiodic response is highly variable within contemporary populations as well as between anciently diverged populations.

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 Identification of main-effect quantitative trait loci (QTLs) for low-temperature stress tolerance germination- and early seedling vigor-related traits in rice (Oryza sativa L.)

2020 ◽  
Vol 40 (1) ◽  
Author(s):  
S. Najeeb ◽  
J. Ali ◽  
A. Mahender ◽  
Y.L. Pang ◽  
J. Zilhas ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Low Temperature ◽  
Quantitative Trait ◽  
Root Length ◽  
Stress Index ◽  
Multiple Traits ◽  
Main Effect ◽  
Trait Loci ◽  
Early Seedling ◽  
Genomic Regions

AbstractAn attempt was made in the current study to identify the main-effect and co-localized quantitative trait loci (QTLs) for germination and early seedling growth traits under low-temperature stress (LTS) conditions in rice. The plant material used in this study was an early backcross population of 230 introgression lines (ILs) in BCIF7 generation derived from the Weed Tolerant Rice-1 (WTR-1) (as the recipient) and Haoannong (HNG) (as the donor). Genetic analyses of LTS tolerance revealed a total of 27 main-effect quantitative trait loci (M-QTLs) mapped on 12 chromosomes. These QTLs explained more than 10% of phenotypic variance (PV), and average PV of 12.71% while employing 704 high-quality SNP markers. Of these 27 QTLs distributed on 12 chromosomes, 11 were associated with low-temperature germination (LTG), nine with low-temperature germination stress index (LTGS), five with root length stress index (RLSI), and two with biomass stress index (BMSI) QTLs, shoot length stress index (SLSI) and root length stress index (RLSI), seven with seed vigor index (SVI), and single QTL with root length (RL). Among them, five significant major QTLs (qLTG(I)1, qLTGS(I)1–2, qLTG(I)5, qLTGS(I)5, and qLTG(I)7) mapped on chromosomes 1, 5, and 7 were associated with LTG and LTGS traits and the PV explained ranged from 16 to 23.3%. The genomic regions of these QTLs were co-localized with two to six QTLs. Most of the QTLs were growth stage-specific and found to harbor QTLs governing multiple traits. Eight chromosomes had more than four QTLs and were clustered together and designated as promising LTS tolerance QTLs (qLTTs), as qLTT1, qLTT2, qLTT3, qLTT5, qLTT6, qLTT8, qLTT9, and qLTT11. A total of 16 putative candidate genes were identified in the major M-QTLs and co-localized QTL regions distributed on different chromosomes. Overall, these significant genomic regions of M-QTLs are responsible for multiple traits and this suggested that these could serve as the best predictors of LTS tolerance at germination and early seedling growth stages. Furthermore, it is necessary to fine-map these regions and to find functional markers for marker-assisted selection in rice breeding programs for cold tolerance.

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