Dataset Information

QTL Mapping and Heterosis Analysis for Fiber Quality Traits Across Multiple Genetic Populations and Environments in Upland Cotton.

ABSTRACT: An "immortalized F₂" (IF₂) population and two reciprocal backcross (HSBCF₁ and MARBCF₁) populations were constructed to investigate the genetic bases of fiber quality traits in upland cotton across four different environments. A relatively high level of heterosis for micronaire (MIC) in IF₂ population as well as fiber length (FL) and MIC in MARBCF₁ population was observed. A total of 167 quantitative trait loci (QTLs) were detected in the three related experimental populations and their corresponding midparental heterosis (MPH) datasets using the composite interval mapping (CIM) approach. An analysis of genetic effects of QTLs detected in different populations and their MPH datasets showed 16 (24.24%) QTLs of partial dominance, and 46 (69.70%) QTLs of overdominance were identified in an IF₂ population; 89 (62.68%) additive QTLs, three (2.11%) partial dominant QTLs, and 49 (34.51%) over-dominant QTLs were detected in two BCF₁ populations. Multi-environment analysis showed 48 and 56 main-QTLs (m-QTLs) and 132 and 182 epistasis-QTLs (e-QTLs), by inclusive composite interval mapping (ICIM) in IF₂ and two BCF₁ populations, respectively. Phenotypic variance explained by e-QTLs, except for MARBCF₁ population, was higher than that by m-QTLs. Thus, the overdominant, partial dominant, and epistasis effects were the main causes of heterosis in the IF₂ population, whereas the additive, overdominant, and epistasis effects were the primary genetic basis of heterosis in the two BCF₁ populations. Altogether, additive effect, partial dominance, overdominance, and epistasis contributed to fiber quality heterosis in upland cotton, but overdominance and epistasis were the most important factors.

SUBMITTER: Li C

PROVIDER: S-EPMC6196769 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

QTL Mapping and Heterosis Analysis for Fiber Quality Traits Across Multiple Genetic Populations and Environments in Upland Cotton.

Li Cong C Yu Hurong H Li Cheng C Zhao Tianlun T Dong Yating Y Deng Xiaolei X Hu Jiahui J Zhang Yi Y Zhang Fan F Daud M K MK Chen Jinhong J Zhu Shuijin S

Frontiers in plant science 20181015

An "immortalized F2" (IF2) population and two reciprocal backcross (HSBCF1 and MARBCF1) populations were constructed to investigate the genetic bases of fiber quality traits in upland cotton across four different environments. A relatively high level of heterosis for micronaire (MIC) in IF2 population as well as fiber length (FL) and MIC in MARBCF1 population was observed. A total of 167 quantitative trait loci (QTLs) were detecte ...[more]

PMID: 30374360

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Project description:BackgroundQuantitative trait loci (QTL) mapping provides a powerful tool to unravel the genetic bases of cotton yield and its components, as well as their heterosis. In the present study, the genetic basis underlying inbreeding depression and heterosis for yield and yield components of upland cotton was investigated in recombinant inbred line (RIL), immortalized F2 (IF2), and two backcross (BCF1) populations based on a high-density SNP linkage map across four environments.ResultsSignificant inbreeding depression of fruit branches per plant (FB), boll numbers per plant (BN), seed cotton yield (SY), and lint yield (LY) in RIL population and high levels of heterosis for SY, LY, and boll weight (BW) in IF2 and two BCF1 populations were observed. A total of 285 QTLs were identified in the four related populations using a composite interval mapping approach. In the IF2 population, 26.60% partially dominant (PD) QTLs and 71.28% over-dominant (OD) QTLs were identified. In two BCF1 populations, 42.41% additive QTLs, 4.19% PD QTLs, and 53.40% OD QTLs were detected. For multi-environment analysis, phenotypic variances (PV) explained by e-QTLs were higher than those by m-QTLs in each of the populations, and the average PV of m-QTLs and e-QTLs explained by QTL?×?environment interactions occupied a considerable proportion of total PV in all seven datasets.ConclusionsAt the single-locus level, the genetic bases of heterosis varied in different populations. Partial dominance and over-dominance were the main cause of heterosis in the IF2 population, while additive effects and over-dominance were the main genetic bases of heterosis in two BCF1 populations. In addition, the various genetic components to heterosis presented trait specificity. In the multi-environment model analysis, epistasis was a common feature of most loci associated with inbreeding depression and heterosis. Furthermore, the environment was a critical factor in the expression of these m-QTLs and e-QTLs. Altogether, additive effects, over-dominance, epistasis and environmental interactions all contributed to the heterosis of yield and its components in upland cotton, with over-dominance and epistasis more important than the others.

Dataset Information

QTL Mapping and Heterosis Analysis for Fiber Quality Traits Across Multiple Genetic Populations and Environments in Upland Cotton.

Publications

QTL Mapping and Heterosis Analysis for Fiber Quality Traits Across Multiple Genetic Populations and Environments in Upland Cotton.

Similar Datasets

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