Epistasis together with partial dominance, over-dominance and QTL by environment interactions contribute to yield heterosis in upland cotton

Yield-related quantitative trait loci identification and lint percentage hereditary dissection under salt stress in upland cotton

Salinity is frequently mentioned as a major constraint in worldwide agricultural production. Lint percentage (LP) is a crucial yield-component in cotton lint production. While the genetic factors affect cotton yield in saline soils are still unclear. Here, we employed a recombinant inbred line population in upland cotton (Gossypium hirsutum L.) and investigated the effects of salt stress on five yield and yield component traits, including seed cotton yield per plant, lint yield per plant, boll number per plant, boll weight, and LP. Between three datasets of salt stress (E1), normal growth (E2), and the difference values dataset of salt stress and normal conditions (D-value), 87, 82, and 55 quantitative trait loci (QTL) were detectable, respectively. In total, five QTL (qLY-Chr6-2, qBNP-Chr4-1, qBNP-Chr12-1, qBNP-Chr15-5, qLP-Chr19-2) detected in both in E1 and D-value were salt related QTL, and three stable QTL (qLP-Chr5-3, qLP-Chr13-1, qBW-Chr5-5) were detected both in E1 and E2 across 3 years. Silencing of nine genes within a stable QTL (qLP-Chr5-3) highly expressed in fiber developmental stages increased LP and decreased fiber length (FL), indicating that multiple minor-effect genes clustered on Chromosome 5 regulate LP and FL. Additionally, the difference in LP caused by Gh_A05G3226 is mainly in transcription level rather than in the sequence difference. Moreover, silencing of salt related gene (GhDAAT) within qBNP-Chr4-1 decreased salt tolerance in cotton. Our findings shed light on the regulatory mechanisms underlining cotton salt tolerance and fiber initiation.

Inheritance of Some Traits in Crosses between Hybrid Tea Roses and Old Garden Roses

The limited knowledge about the inheritance of traits in roses makes the efficient development of rose varieties challenging. In order to achieve breeding goals, the inheritance of traits needs to be explored. Additionally, for the inheritance of a trait like scent, which remains a mystery, it is crucial to know the success of parental traits in transmitting them to the next generation. Understanding this allows for accurate parental selection, ensuring sustainability in meeting market demand and providing convenience to breeders. The aim of this study was to assess the success of cross-combinations between scented old garden roses and hybrid tea roses used in cut roses in transferring their existing traits, with the objective of achieving scented cut roses. The evaluated traits included recurrent blooming, flower stem length, flower diameter, petal number, scent, and bud length of both parents and progenies. The inheritance of these traits was evaluated through theoretical evaluations, including calculating heterosis and heterobeltiosis and determining narrow-sense heritability. The combinations and examined traits were assessed using a hierarchical clustering heat map. The results of this study indicated that flower stem length, flower diameter, petal number, and bud length traits had a moderate degree of narrow-sense heritability, suggesting the influence of non-additive genes on these traits. This study observed a low success rate in obtaining progenies with scent in cross combinations between cut roses and old garden roses, indicating the challenges in obtaining scented genotypes. The discrepancy between the observed phenotypic rates and the expected phenotypic and genotypic rates, according to Punnett squares, suggests that the examined traits could be controlled by polygenic genes. The progenies were observed to exhibit a greater resemblance to old garden roses than hybrid tea roses and did not meet the commercial quality standards for cut flowers. The significant negative heterosis observed in 65.12% (petal number) and 99.61% (flower diameter) of the progenies provides strong evidence of resemblance to old garden roses. Considering these findings, it is recommended to consider old garden roses as parents, taking into account their suitability for other breeding objectives.

Genetic dissection of lint percentage in short-season cotton using combined QTL mapping and RNA-seq

KEY MESSAGE

In total, 17 QTLs for lint percentage in short-season cotton, including three stable QTLs, were detected. Twenty-eight differentially expressed genes located within the stable QTLs were identified, and two genes were validated by qRT-PCR. The breeding and use of short-season cotton have significant values in addressing the question of occupying farmlands with either cotton or cereals. However, the fiber yields of short-season cotton varieties are significantly lower than those of middle- and late-maturing varieties. How to effectively improve the fiber yield of short-season cotton has become a focus of cotton research. Here, a high-density genetic map was constructed using genome resequencing and an RIL population generated from the hybridization of two short-season cotton accessions, Dong3 and Dong4. The map contained 4960 bin markers across the 26 cotton chromosomes and spanned 3971.08 cM, with an average distance of 0.80 cM between adjacent markers. Based on the genetic map, quantitative trait locus (QTL) mapping for lint percentage (LP, %), an important yield component trait, was performed. In total, 17 QTLs for LP, including three stable QTLs, qLP-A02, qLP-D04, and qLP-D12, were detected. Three out of 11 non-redundant QTLs overlapped with previously reported QTLs, whereas the other eight were novel QTLs. A total of 28 differentially expressed genes associated with the three stable QTLs were identified using RNA-seq of ovules and fibers at different seed developmental stages from the parental materials. The two genes, Ghir_A02G017640 and Ghir_A02G018500, may be related to LP as determined by further qRT-PCR validation. This study provides useful information for the genetic dissection of LP and promotes the molecular breeding of short-season cotton.

Plant biochemical genetics in the multiomics era

Our understanding of plant biology has been revolutionized by modern genetics and biochemistry. However, biochemical genetics can be traced back to the foundation of Mendelian genetics; indeed, one of Mendel's milestone discoveries of seven characteristics of pea plants later came to be ascribed to a mutation in a starch branching enzyme. Here, we review both current and historical strategies for the elucidation of plant metabolic pathways and the genes that encode their component enzymes and regulators. We use this historical review to discuss a range of classical genetic phenomena including epistasis, canalization, and heterosis as viewed through the lens of contemporary high-throughput data obtained via the array of approaches currently adopted in multiomics studies.

Genome-wide association study reveals novel quantitative trait loci and candidate genes of lint percentage in upland cotton based on the CottonSNP80K array

Thirty-four SNPs corresponding with 22 QTLs for lint percentage, including 13 novel QTLs, was detected via GWAS. Two candidate genes underlying this trait were also identified. Cotton (Gossypium spp.) is an important natural textile fiber and oilseed crop cultivated worldwide. Lint percentage (LP, %) is one of the important yield components, and increasing LP is a core goal of cotton breeding improvement. However, the genetic and molecular mechanisms underlying LP in upland cotton remain unclear. Here, we performed a genome-wide association study (GWAS) for LP based on 254 upland cotton accessions in four environments as well as the best linear unbiased predictors using the high-density CottonSNP80K array. In total, 41,413 high-quality single-nucleotide polymorphisms (SNPs) were screened, and 34 SNPs within 22 quantitative trait loci (QTLs) were significantly associated with LP. In total, 175 candidate genes were identified from two major genomic loci (GR1 and GR2), and 50 hub genes were identified through GO enrichment and weighted gene co-expression network analysis. Two candidate genes (Gh_D01G0162 and Gh_D07G0463), which may participate in early fiber development to affect the number of fiber protrusions and LP, were also identified. Their genetic variation and expression were verified by linkage disequilibrium blocks, haplotypes, and quantitative real-time polymerase chain reaction, respectively. The weighted gene interaction network analysis showed that the expression of Gh_D07G0463 was significantly correlated with that of Gh_D01G0162. These identified SNPs, QTLs and candidate genes provide important insights into the genetic and molecular mechanisms underlying variations in LP and serve as a foundation for LP improvement via marker-assisted breeding.

Identification of a major QTL and genome-wide epistatic interactions for single vs. paired spikelets in a maize-teosinte F2 population

Maize ear carries paired spikelets, whereas the ear of its wild ancestor, teosinte, bears single spikelets. However, little is known about the genetic basis of the processes of transformation of single spikelets in teosinte ear to paired spikelets in maize ear. In this study, a two-ranked, paired-spikelets primitive maize and a two-ranked, single-spikelet teosinte were utilized to develop an F2 population, and quantitative trait locus (loci) (QTL) mapping for single vs. paired spikelets (PEDS) was performed. One major QTL (qPEDS3.1) for PEDS located on chromosome 3S was identified in the 162 F2 plants using the inclusive composite interval mapping of additive (ICIM-ADD) module, explaining 23.79% of the phenotypic variance. Out of the 409 F2 plants, 43 plants with PEDS = 0% and 43 plants with PEDS > 20% were selected for selective genotyping, and the QTL (qPEDS3.1) was detected again. Moreover, the QTL (qPEDS3.1) was validated in three environments, which explained 31.05%, 38.94%, and 23.16% of the phenotypic variance, respectively. In addition, 50 epistatic QTLs were detected in the 162 F2 plants using the two-locus epistatic QTL (ICIM-EPI) module; they were distributed on all 10 chromosomes and explained 94.40% of the total phenotypic variance. The results contribute to a better understanding of the genetic basis of domestication of paired spikelets and provide a genetic resource for future map-based cloning; in addition, the systematic dissection of epistatic interactions underlies a theoretical framework for overcoming epistatic effects on QTL fine mapping.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01276-x.

Marker effects and heritability estimates using additive-dominance genomic architectures via artificial neural networks in Coffea canephora

Many methodologies are used to predict the genetic merit in animals and plants, but some of them require priori assumptions that may increase the complexity of the model. Artificial neural network (ANN) has advantage to not require priori assumptions about the relationships between inputs and the output allowing great flexibility to handle different types of complex non-additive effects, such as dominance and epistasis. Despite this advantage, the biological interpretability of ANNs is still limited. The aim of this research was to estimate the heritability and markers effects for two traits in Coffea canephora using an additive-dominance architecture ANN and to compare it with genomic best linear unbiased prediction (GBLUP). The data used consists of 51 clones of C. canephora varietal Conilon, 32 of varietal group Robusta and 82 intervarietal hybrids. From this, 165 phenotyped individuals were genotyped for 14,387 SNPs. Due to the high computational cost of ANNs, we used Bagging decision tree to reduce the dimensionality of the data, selecting the markers that accumulated 70% of the total importance. An ANN with three hidden layers was run, each varying from 1 to 40 neurons summing 64,000 neural networks. The network architectures with the best predictive ability were selected. The best architectures were composed by 4, 15, and 33 neurons in the first, second and third hidden layers, respectively, for yield, and by 13, 20, and 24 neurons, respectively for rust resistance. The predictive ability was greater when using ANN with three hidden layers than using one hidden layer and GBLUP, with 0.72 and 0.88 for yield and coffee leaf rust resistance, respectively. The concordance rate (CR) of the 10% larger markers effects among the methods varied between 10% and 13.8%, for additive effects and between 5.4% and 11.9% for dominance effects. The narrow-sense ([Formula: see text]) and dominance-only ([Formula: see text]) heritability estimates were 0.25 and 0.06, respectively, for yield, and 0.67 and 0.03, respectively for rust resistance. The ANN was able to estimate the heritabilities from an additive-dominance genomic architectures and the ANN with three hidden layers obtained best predictive ability when compared with those obtained from GBLUP and ANN with one hidden layer.

Analyzing Quantitative Trait Loci for Fiber Quality and Yield-Related Traits From a Recombinant Inbred Line Population With Gossypium hirsutum Race palmeri as One Parent

Fiber quality and yield-related traits are important agronomic traits in cotton breeding. To detect the genetic basis of fiber quality and yield related traits, a recombinant inbred line (RIL) population consisting of 182 lines was established from a cross between Gossypium hirsutum cultivar CCRI35 and G. hirsutum race palmeri accession TX-832. The RIL population was deeply genotyped using SLAF-seq and was phenotyped in six environments. A high-density genetic linkage map with 15,765 SNP markers and 153 SSR markers was constructed, with an average distance of 0.30 cM between adjacent markers. A total of 210 fiber quality quantitative trait loci (QTLs) and 73 yield-related QTLs were identified. Of the detected QTLs, 62 fiber quality QTLs and 10 yield-related QTLs were stable across multiple environments. Twelve and twenty QTL clusters were detected on the At and Dt subgenome, respectively. Twenty-three major QTL clusters were further validated through associated analysis and five candidate genes of four stable fiber quality QTLs were identified. This study revealed elite loci influencing fiber quality and yield and significant phenotypic selection regions during G. hirsutum domestication, and set a stage for future utilization of molecular marker assisted breeding in cotton breeding programs.

QTL controlling fiber quality traits under salt stress in upland cotton (Gossypium hirsutum L.)

QTL for fiber quality traits under salt stress discerned candidate genes controlling fatty acid metabolism. Salinity stress seriously affects plant growth and limits agricultural productivity of crop plants. To dissect the genetic basis of response to salinity stress, a recombinant inbred line population was developed to compare fiber quality in upland cotton (Gossypium hirsutum L.) under salt stress and normal conditions. Based on three datasets of (1) salt stress, (2) normal growth, and (3) the difference value between salt stress and normal conditions, 51, 70, and 53 QTL were mapped, respectively. Three QTL for fiber length (FL) (qFL-Chr1-1, qFL-Chr5-5, and qFL-Chr24-4) were detected under both salt and normal conditions and explained 4.26%, 9.38%, and 3.87% of average phenotypic variation, respectively. Seven genes within intervals of two stable QTL (qFL-Chr1-1 and qFL-Chr5-5) were highly expressed in lines with extreme long fiber. A total of 35 QTL clusters comprised of 107 QTL were located on 18 chromosomes and exhibited pleiotropic effects. Thereinto, two clusters were responsible for improving five fiber quality traits, and 6 influenced FL and fiber strength (FS). The QTL with positive effect for fiber length exhibited active effects on fatty acid synthesis and elongation, but the ones with negative effect played passive roles on fatty acid degradation under salt stress.

Genome-wide dissection of hybridization for fiber quality- and yield-related traits in upland cotton

An evaluation of combining ability can facilitate the selection of suitable parents and superior F₁ hybrids for hybrid cotton breeding, although the molecular genetic basis of combining ability has not been fully characterized. In the present study, 282 female parents were crossed with four male parents in accordance with the North Carolina II mating scheme to generate 1128 hybrids. The parental lines were genotyped based on restriction site-associated DNA sequencing and 306 814 filtered single nucleotide polymorphisms were used for genome-wide association analysis involving the phenotypes, general combining ability (GCA) values, and specific combining ability values of eight fiber quality- and yield-related traits. The main results were: (i) all parents could be clustered into five subgroups based on population structure analyses and the GCA performance of the female parents had significant differences between subgroups; (ii) 20 accessions with a top 5% GCA value for more than one trait were identified as elite parents for hybrid cotton breeding; (iii) 120 significant single nucleotide polymorphisms, clustered into 66 quantitative trait loci, such as the previously reported Gh_A07G1769 and GhHOX3 genes, were found to be significantly associated with GCA; and (iv) identified quantitative trait loci for GCA had a cumulative effect on GCA of the accessions. Overall, our results suggest that pyramiding the favorable loci for GCA may improve the efficiency of hybrid cotton breeding.

Identification of candidate genes for key fibre-related QTLs and derivation of favourable alleles in Gossypium hirsutum recombinant inbred lines with G. barbadense introgressions

Fine mapping QTLs and identifying candidate genes for cotton fibre-quality and yield traits would be beneficial to cotton breeding. Here, we constructed a high-density genetic map by specific-locus amplified fragment sequencing (SLAF-seq) to identify QTLs associated with fibre-quality and yield traits using 239 recombinant inbred lines (RILs), which was developed from LMY22 (a high-yield Gossypium hirsutumL. cultivar) × LY343 (a superior fibre-quality germplasm with G. barbadenseL. introgressions). The genetic map spanned 3426.57 cM, including 3556 SLAF-based SNPs and 199 SSR marker loci. A total of 104 QTLs, including 67 QTLs for fibre quality and 37 QTLs for yield traits, were identified with phenotypic data collected from 7 environments. Among these, 66 QTLs were co-located in 19 QTL clusters on 12 chromosomes, and 24 QTLs were detected in three or more environments and determined to be stable. We also investigated the genomic components of LY343 and their contributions to fibre-related traits by deep sequencing the whole genome of LY343, and we found that genomic components from G. hirsutum races (which entered LY343 via its G. barbadense parent) contributed more favourable alleles than those from G. barbadense. We further identified six putative candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL6), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fibre-length QTLs and Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint-percentage QTLs. Our results provide comprehensive insight into the genetic basis of the formation of fibre-related traits and would be helpful for cloning fibre-development-related genes as well as for marker-assisted genetic improvement in cotton.

Overdominance is the major genetic basis of lint yield heterosis in interspecific hybrids between G. hirsutum and G. barbadense

The genetic basis of heterosis has not been resolved for approximately a century, although the role of loci with overdominant (ODO) effects has continued to be discussed by biologists. In the present investigation, a proposed model was studied in Gossypium hirsutum L. introgression lines (ILs) harbouring a segment of G. barbadense. These introgressions were confirmed by a single marker of G. barbadense. These ILs contained 396 quantitative trait loci (QTLs) for 11 yield and non-yield traits that were recorded in the field on homozygous and heterozygous plants for 5 years. After comparing the different types of QTLs between the yield group and the non-yield group, it was found that the yield group had significantly higher ODO QTL ratios. Moreover, 16 ODO QTLs identified for 5 yield-related traits were consistently detected during 5 cotton growing seasons (2010-2011 and 2013-2015): 6 of 7 for boll weight, 3 of 11 for seed-cotton yield per plant, 4 of 17 for boll number, 2 of 13 for lint yield per plant and 1 of 11 for lint percentage. Therefore, we propose that overdominance is the major genetic basis of lint yield heterosis in interspecific hybrids between G. barbadense and G. hirsutum. These findings have important implications in cotton breeding in that the boll weight can be improved by utilizing ODO QTLs via heterosis; thus, the stagnant yield barrier can be smashed to achieve sustainable increases in cotton production. Additionally, this concept can be translated to other field crops for improving their yield potential.

Comparative transcriptome analysis reveals important roles of nonadditive genes in maize hybrid An'nong 591 under heat stress

BACKGROUND

Heterosis is the superior performance of F₁ hybrids relative to their parental lines for a wide range of traits. In this study, expression profiling and heterosis associated genes were analyzed by RNA sequencing (RNA-Seq) in seedlings of the maize hybrid An'nong 591 and its parental lines under control and heat stress conditions.

RESULTS

Through performing nine pairwise comparisons, the maximum number of differentially expressed genes (DEGs) was detected between the two parental lines, and the minimum number was identified between the F₁ hybrid and the paternal lines under both conditions, which suggested greater genetic contribution of the paternal line to heat stress tolerance. Gene Ontology (GO) enrichment analysis of the 4518 common DEGs indicated that GO terms associated with diverse stress responses and photosynthesis were highly overrepresented in the 76 significant terms of the biological process category. A total of 3970 and 7653 genes exhibited nonadditive expression under control and heat stress, respectively. Among these genes, 2253 (56.8%) genes overlapped, suggesting that nonadditive genes tend to be conserved in expression. In addition, 5400 nonadditive genes were found to be specific for heat stress condition, and further GO analysis indicated that terms associated with stress responses were significantly overrepresented, and 60 genes were assigned to the GO term response to heat. Pathway enrichment analysis indicated that 113 genes were involved in spliceosome metabolic pathways. Nineteen of the 33 overlapping genes assigned to the GO term response to heat showed significantly higher number of alternative splicing (AS) events under heat stress than under control conditions, suggesting that AS of these genes play an important role in response to heat stress.

CONCLUSIONS

This study reveals the transcriptomic divergence of the maize F₁ hybrid and its parental lines under control and heat stress conditions, and provides insight into the underlying molecular mechanisms of heterosis and the response to heat stress in maize.

The evolution of hybrid fitness during speciation

The evolution of postzygotic reproductive isolation is an important component of speciation. But before isolation is complete there is sometimes a phase of heterosis in which hybrid fitness exceeds that of the two parental species. The genetics and evolution of heterosis and postzygotic isolation have typically been studied in isolation, precluding the development of a unified theory of speciation. Here, we develop a model that incorporates both positive and negative gene interactions, and accounts for the evolution of both heterosis and postzygotic isolation. We parameterize the model with recent data on the fitness effects of 10,000 mutations in yeast, singly and in pairwise epistatic combinations. The model makes novel predictions about the types of interactions that contribute to declining hybrid fitness. We reproduce patterns familiar from earlier models of speciation (e.g. Haldane's Rule and Darwin's Corollary) and identify new mechanisms that may underlie these patterns. Our approach provides a general framework for integrating experimental data from gene interaction networks into speciation theory and makes new predictions about the genetic mechanisms of speciation.

Cumulative and different genetic effects contributed to yield heterosis using maternal and paternal backcross populations in Upland cotton

Heterosis has been utilized in commercial production, but the heterosis mechanism has remained vague. Hybrid cotton is suitable to dissect the heterosis mechanism. In order to explore the genetic basis of heterosis in Upland cotton, we generated paternal and maternal backcross (BC/P and BC/M) populations. Data for yield and yield-component traits were collected over 2 years in three replicated BC/P field trials and four replicated BC/M field trials. At single-locus level, 26 and 27 QTLs were identified in BC/P and BC/M populations, respectively. Six QTLs shared in both BC populations. A total of 27 heterotic loci were detected. Partial dominant and over-dominant QTLs mainly determined yield heterosis in the BC/P and BC/M populations. QTLs for different traits displayed varied genetic effects in two BC populations. Eleven heterotic loci overlapped with QTLs but no common heterotic locus was detected in both BC populations. We resolved the 333 kb (48 genes) and 516 kb (25 genes) physical intervals based on 16 QTL clusters and 35 common QTLs, respectively, in more than one environment or population. We also identified 189 epistatic QTLs and a number of QTL × environment interactions in two BC populations and the corresponding MPH datasets. The results indicated that cumulative effects contributed to yield heterosis in Upland cotton, including epistasis, QTL × environment interaction, additive, partial dominance and over-dominance.

Genetic basis of heterosis for yield and yield components explored by QTL mapping across four genetic populations in upland cotton

Background

Quantitative 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.

Results

Significant 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.

Conclusions

At 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.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5289-2) contains supplementary material, which is available to authorized users.

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

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.

Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.)

Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.

Bypassing Negative Epistasis on Yield in Tomato Imposed by a Domestication Gene

Selection for inflorescence architecture with improved flower production and yield is common to many domesticated crops. However, tomato inflorescences resemble wild ancestors, and breeders avoided excessive branching because of low fertility. We found branched variants carry mutations in two related transcription factors that were selected independently. One founder mutation enlarged the leaf-like organs on fruits and was selected as fruit size increased during domestication. The other mutation eliminated the flower abscission zone, providing "jointless" fruit stems that reduced fruit dropping and facilitated mechanical harvesting. Stacking both beneficial traits caused undesirable branching and sterility due to epistasis, which breeders overcame with suppressors. However, this suppression restricted the opportunity for productivity gains from weak branching. Exploiting natural and engineered alleles for multiple family members, we achieved a continuum of inflorescence complexity that allowed breeding of higher-yielding hybrids. Characterizing and neutralizing similar cases of negative epistasis could improve productivity in many agricultural organisms. VIDEO ABSTRACT.

QTLs Analysis and Validation for Fiber Quality Traits Using Maternal Backcross Population in Upland Cotton

Cotton fiber is renewable natural fiber source for textile. Improving fiber quality is an essential goal for cotton breeding project. In present study, F₁₄ recombinant inbred line (RIL) population was backcrossed by the maternal parent to obtain a backcross (BC) population, derived from one Upland cotton hybrid. Three repetitive field trials were performed by randomized complete block design with two replicates in three locations in 2015, together with the BC population, common male parent and the RIL population. Totally, 26 QTLs in BC population explained 5.00-14.17% of phenotype variation (PV) and 37 quantitative trait loci (QTL) were detected in RIL population explaining 5.13-34.00% of PV. Seven common QTLs detected simultaneously in two populations explained PV from 7.69 to 23.05%. A total of 20 QTLs in present study verified the previous results across three environments in 2012. Particularly, qFL-Chr5-2 controlling fiber length on chromosome 5 explained 34.00% of PV, while qFL-Chr5-3 only within a 0.8 cM interval explained 13.93% of PV on average in multiple environments. These stable QTLs explaining great variation offered essential information for marker-assisted selection (MAS) to improve fiber quality traits. Lots of epistasis being detected in both populations acted as one of important genetic compositions of fiber quality traits.

Identification of QTL for Fiber Quality and Yield Traits Using Two Immortalized Backcross Populations in Upland Cotton

Two immortalized backcross populations (DHBCF₁s and JMBCF₁s) were developed using a recombinant inbred line (RIL) population crossed with the two parents DH962 and Jimian5 (as the males), respectively. The fiber quality and yield component traits of the two backcross populations were phenotyped at four environments (two locations, two years). One hundred seventy-eight quantitative trait loci (QTL) were detected including 76 for fiber qualities and 102 for yield components, explaining 4.08–17.79% of the phenotypic variation (PV). Among the 178 QTL, 22 stable QTL were detected in more than one environment or population. A stable QTL, qFL-c10-1, was detected in the previous F₂ population, a RIL population in 3 environments and the current two BCF₁ populations in this study, explaining 5.79–37.09% of the PV. Additionally, 117 and 110 main-effect QTL (M-QTL) and 47 and 191 digenic epistatic QTL (E-QTL) were detected in the DHBCF₁s and JMBCF₁s populations, respectively. The effect of digenic epistasis played a more important role on lint percentage, fiber length and fiber strength. These results obtained in the present study provided more resources to obtain stable QTL, confirming the authenticity and reliability of the QTL for molecular marker-assisted selection breeding and QTL cloning.

Genetic analysis of Upland cotton dynamic heterosis for boll number per plant at multiple developmental stages

Yield is an important breeding target. As important yield components, boll number per plant (BNP) shows dynamic character and strong heterosis in Upland cotton. However, the genetic basis underlying the dynamic heterosis is poorly understood. In this study, we conducted dynamic quantitative trait loci (QTL) analysis for BNP and heterosis at multiple developmental stages and environments using two recombinant inbred lines (RILs) and two corresponding backcross populations. By the single-locus analysis, 23 QTLs were identified at final maturity, while 99 QTLs were identified across other three developmental stages. A total of 48 conditional QTLs for BNP were identified for the adjacent stages. QTLs detected at later stage mainly existed in the partial dominance to dominance range and QTLs identified at early stage mostly showed effects with the dominance to overdominance range during plant development. By two-locus analysis, we observe that epistasis played an important role not only in the variation of the performance of the RIL population but also in the expression of heterosis in backcross population. Taken together, the present study reveals that the genetic basis of heterosis is dynamic and complicated, and it is involved in dynamic dominance effect, epistasis and QTL by environmental interactions.

Main Effect QTL with Dominance Determines Heterosis for Dynamic Plant Height in Upland Cotton

Plant height, which shows dynamic development and heterosis, is a major trait affecting plant architecture and has an indirect influence on economic yield related to biological yield in cotton. In the present study, we carried out dynamic analysis for plant height and its heterosis by quantitative trait loci (QTL) mapping at multiple developmental stages using two recombinant inbred lines (RILs) and their backcross progeny. At the single-locus level, 47 QTL were identified at five developmental stages in two hybrids. In backcross populations, QTL identified at an early stage mainly showed partial effects and QTL detected at a later stage mostly displayed overdominance effects. At the two-locus level, we found that main effect QTL played a more important role than epistatic QTL in the expression of heterosis in backcross populations. Therefore, this study implies that the genetic basis of plant height heterosis shows dynamic character and main effect QTL with dominance determines heterosis for plant height in Upland cotton.

Genetic Analysis and QTL Detection on Fiber Traits Using Two Recombinant Inbred Lines and Their Backcross Populations in Upland Cotton

Cotton fiber, a raw natural fiber material, is widely used in the textile industry. Understanding the genetic mechanism of fiber traits is helpful for fiber quality improvement. In the present study, the genetic basis of fiber quality traits was explored using two recombinant inbred lines (RILs) and corresponding backcross (BC) populations under multiple environments in Upland cotton based on marker analysis. In backcross populations, no significant correlation was observed between marker heterozygosity and fiber quality performance and it suggested that heterozygosity was not always necessarily advantageous for the high fiber quality. In two hybrids, 111 quantitative trait loci (QTL) for fiber quality were detected using composite interval mapping, in which 62 new stable QTL were simultaneously identified in more than one environment or population. QTL detected at the single-locus level mainly showed additive effect. In addition, a total of 286 digenic interactions (E-QTL) and their environmental interactions [QTL × environment interactions (QEs)] were detected for fiber quality traits by inclusive composite interval mapping. QE effects should be considered in molecular marker-assisted selection breeding. On average, the E-QTL explained a larger proportion of the phenotypic variation than the main-effect QTL did. It is concluded that the additive effect of single-locus and epistasis with few detectable main effects play an important role in controlling fiber quality traits in Upland cotton.