Identification of quantitative trait loci underlying fatty acid content of soybean (Glycine max), including main, epistatic and QTL×environment effects across multiple environments

2017 ◽  
Vol 68 (9) ◽  
pp. 842 ◽  
Author(s):  
Ning Xia ◽  
Depeng Wu ◽  
Xia Li ◽  
Weili Teng ◽  
Xue Zhao ◽  
...  
Keyword(s):  
Glycine Max ◽  
Fatty Acid ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Acid Content ◽  
Recombinant Inbred Lines ◽  
Fatty Acid Content ◽  
Environment Interaction ◽  
Epistatic Qtls ◽  
Trait Loci

The uses and nutritional value of soybean (Glycine max (L.) Merrill) oil are largely influenced by the levels and relative proportions in the seed of the five major fatty acids: oleic (OA), palmitic (PA), stearic (SA), linoleic (LLA), linolenic (LNA). The present study was undertaken to identify quantitative trait loci (QTLs) that are associated with fatty acid content (particularly OA) and to determine the effects of epistasis and the environment. The mapping population included 134 recombinant inbred lines (RILs) derived from soybean varieties Suinong10 and L-9. Phenotypic data of the two parents and their RILs were obtained at Harbin in 2013, 2014 and 2015. Nineteen QTLs associated with individual fatty acid content (six for OA, four for LNA, three for PA, two for SA, four for LLA) were identified. Twelve of these QTLs (four for OA, three for LNA, two for PA, one for SA, two for LLA) were detected with an additive main effect and/or additive × environment interaction effect in certain environments. Epistatic QTLs were identified for contents of OA (two QTLs), LNA (one QTL) and LLA (one QTL) in different environments, and which exhibited significant epistatic effects. Our observation of these additive and epistatic QTLs suggested that soybean possesses a complex network for fatty acid accumulation, which is valuable for marker-assisted selection.

scholarly journals Genotype-Environment Interaction at Quantitative Trait Loci Affecting Sensory Bristle Number in Drosophila melanogaster

Genetics ◽  
1998 ◽  
Vol 149 (4) ◽  
pp. 1883-1898 ◽  
Author(s):  
Marjorie C Gurganus ◽  
James D Fry ◽  
Sergey V Nuzhdin ◽  
Elena G Pasyukova ◽  
Richard F Lyman ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Rank Order ◽  
Recombinant Inbred Lines ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Bristle Number ◽  
A Genome ◽  
Trait Loci

AbstractThe magnitude of segregating variation for bristle number in Drosophila melanogaster exceeds that predicted from models of mutation-selection balance. To evaluate the hypothesis that genotype-environment interaction (GEI) maintains variation for bristle number in nature, we quantified the extent of GEI for abdominal and sternopleural bristles among 98 recombinant inbred lines, derived from two homozygous laboratory strains, in three temperature environments. There was considerable GEI for both bristle traits, which was mainly attributable to changes in rank order of line means. We conducted a genome-wide screen for quantitative trait loci (QTLs) affecting bristle number in each sex and temperature environment, using a dense (3.2-cM) marker map of polymorphic insertion sites of roo transposable elements. Nine sternopleural and 11 abdominal bristle number QTLs were detected. Significant GEI was exhibited by 14 QTLs, but there was heterogeneity among QTLs in their sensitivity to thermal and sexual environments. To further evaluate the hypothesis that GEI maintains variation for bristle number, we require estimates of allelic effects across environments at genetic loci affecting the traits. This level of resolution may be achievable for Drosophila bristle number because candidate loci affecting bristle development often map to the same location as bristle number QTLs.

Inclusive composite-interval mapping reveals quantitative trait loci for plant architectural traits in sorghum (Sorghum bicolor)

2019 ◽  
Vol 70 (8) ◽  
pp. 659
Author(s):  
Huawen Zhang ◽  
Runfeng Wang ◽  
Bin Liu ◽  
Erying Chen ◽  
Yanbing Yang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Sorghum Bicolor ◽  
Quantitative Trait ◽  
Composite Interval Mapping ◽  
Recombinant Inbred Lines ◽  
Interval Mapping ◽  
Environment Interaction ◽  
Trait Loci ◽  
Inclusive Composite Interval Mapping ◽  
Architectural Traits

Architecture-efficient sorghum (Sorghum bicolor (L.) Moench) has erect leaves forming a compact canopy that enables highly effective utilisation of solar radiation; it is suitable for high-density planting, resulting in an elevated overall production. Development of sorghum ideotypes with optimal plant architecture requires knowledge of the genetic basis of plant architectural traits. The present study investigated seven production-related architectural traits by using 181 sorghum recombinant inbred lines (RILs) with contrasting architectural phenotypes developed from the cross Shihong 137 × L-Tian. Parents along with RILs were phenotyped for plant architectural traits for two consecutive years (2012, 2013) at two locations in the field. Analysis of variance revealed significant (P ≤ 0.05) differences among RILs for architectural traits. All traits showed medium to high broad-sense heritability estimates (0.43–0.94) and significant (P ≤ 0.05) genotype × environment effects. We employed 181 simple sequence repeat markers to identify quantitative trait loci (QTLs) and the effects of QTL × environment interaction based on the inclusive composite interval mapping algorithm. In total, 53 robust QTLs (log of odds ≥4.68) were detected for these seven traits and explained 2.11–12.11% of phenotypic variation. These QTLs had small effects of QTL × environment interaction and yet significant epistatic effects, indicating that they could stably express across environments but influence phenotypes through strong interaction with non-allelic loci. The QTLs and linked markers need to be verified through function and candidate-gene analyses. The new knowledge of the genetic regulation of architectural traits in the present study will provide a theoretical basis for the genetic improvement of architectural traits in sorghum.

Identification of quantitative trait loci underlying seed oil content of soybean including main, epistatic and QTL×environment effects in different regions of Northeast China

2017 ◽  
Vol 68 (7) ◽  
pp. 625 ◽  
Author(s):  
Weili Teng ◽  
Binbin Zhang ◽  
Qi Zhang ◽  
Wen Li ◽  
Depeng Wu ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Oil Content ◽  
Recombinant Inbred Lines ◽  
Soybean Seed ◽  
Environment Interaction ◽  
Additive Effects ◽  
Linkage Groups ◽  
Soybean Breeding ◽  
Trait Loci

Oil content is a primary trait in soybean and determines the quality of soy food, feed and oil product. Increasing oil content is a major objective of soybean breeding. The aims of the present study were to identify quantitative trait loci (QTLs) and epistatic QTLs associated with oil content in soybean seed by using 129 recombinant inbred lines derived from a cross between cultivar Dongnong 46 (oil content 22.53%) and the semi-wild line L-100 (oil content 17.33%). Phenotypic data were collected from 10 tested environments including Harbin in the years 2012–15, Hulan in 2013–15 and Acheng in 2013–15. A genetic linkage map including 213 simple sequence repeat markers in 18 chromosomes (or linkage groups) was constructed, covering ~3623.39 cM. Seven QTLs, located on five chromosomes (or linkage groups), were identified to be associated with oil content, explaining 2.24–17.54% of the phenotypic variation in multi-environments. Among these identified QTLs, five (qOIL-2, qOIL-4, qOIL-5, qOIL-6 and qOIL-7) were detected in more than five environments. Seven QTLs had additive and/or additive × environment interaction effects. QTLs with higher additive effects were more stable in multi-environments than those with lower additive effects. Moreover, five epistatic, pairwise QTLs were identified in different environments. The findings with respect to genetic architecture for oil content could be valuable for marker-assisted selection in soybean breeding programs for high oil content.

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.

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