multiple-QTL Model Research Articles

Genetic linkage mapping and quantitative trait locus (QTL) analysis of sweet basil (Ocimum basilicum L.) to identify genomic regions associated with cold tolerance and major volatiles.

Chilling sensitivity is one of the greatest challenges affecting the marketability and profitability of sweet basil (Ocimum basilicum L.) in the US and worldwide. Currently, there are no sweet basils commercially available with significant chilling tolerance and traditional aroma profiles. This study was conducted to identify quantitative trait loci (QTLs) responsible for chilling tolerance and aroma compounds in a biparental mapping population, including the Rutgers advanced breeding line that served as a chilling tolerant parent, 'CB15', the chilling sensitive parent, 'Rutgers Obsession DMR' and 200 F2 individuals. Chilling tolerance was assessed by percent necrosis using machine learning and aroma profiling was evaluated using gas chromatography (GC) mass spectrometry (MS). Single nucleotide polymorphism (SNP) markers were generated from genomic sequences derived from double digestion restriction-site associated DNA sequencing (ddRADseq) and converted to genotype data using a reference genome alignment. A genetic linkage map was constructed and five statistically significant QTLs were identified in response to chilling temperatures with possible interactions between QTLs. The QTL on LG24 (qCH24) demonstrated the largest effect for chilling response and was significant in all three replicates. No QTLs were identified for linalool, as the population did not segregate sufficiently to detect this trait. Two significant QTLs were identified for estragole (also known as methyl chavicol) with only qEST1 on LG1 being significant in the multiple-QTL model (MQM). QEUC26 was identified as a significant QTL for eucalyptol (also known as 1,8-cineole) on LG26. These QTLs may represent key mechanisms for chilling tolerance and aroma in basil, providing critical knowledge for future investigation of these phenotypic traits and molecular breeding.

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.).

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

A simulation-based assessment of the efficiency of QTL mapping under environment and genotype x environment interaction effects.

The objective of this simulation-based study was to assess how genes, environments, and genotype x environment (GxE) interaction affect the quantitative trait loci (QTL) mapping efficiency. The simulation software performed 50 samplings of 300 recombinant inbred lines (RILs) from a F2, which were assessed in six environments. The RILs were genotyped for 977 single nucleotide polymorphisms (SNP) and phenotyped for grain yield. The average SNP density was 2 cM. We defined six QTLs and 190 minor genes. The trait heritability ranged from 30 to 80%. We fitted the single QTL model and the multiple QTL model on multiple phenotypes. The environment and complex GxE interaction effects led to a low correlation between the QTL heritability and power. The single- and across-environment analyses allowed all QTLs be declared, with an average power of 28 to 100%. In the across-environment analysis, five QTLs showed average power in the range 46 to 82%. Both models provided a good control of the false positive rate (6%, on average) and a precise localization of the QTLs (bias of 2 cM, on average). The QTL power in each environment has a high positive correlation with the range between QTL genotypes for the sum of the additive, environment, and GxE interaction effects (0.76 to 0.96). The uncertainty about the magnitude and sign of the environment and GxE interaction effects makes QTL mapping in multi-environment trials unpredictable. Unfortunately, this uncertainty has no solution because the geneticist has no control over the magnitude and sign of the environment and GxE interaction effects. However, the single- and across-environment analyses are efficient even under a low correlation between QTL heritability and power.

Mapping of QTLs for citrus quality traits throughout the fruit maturation process on clementine (Citrus reticulata × C. sinensis) and mandarin (C. reticulata Blanco) genetic maps

Citrus fruit quality is defined as the combination of physical and chemical traits; some of which may change during the ripening phase, e.g., acidity and sugar content. A clear understanding of their genetic control would be very helpful for marker-assisted breeding programs especially with regard to the juvenile phase and some reproductive features that hamper the selection of improved hybrids. A genetic study was thus performed on the heredity of quality traits and QTL detection based on segregation in a progeny generated from a cross between clementine cv “Commun” (Citrus × reticulata cv clementine) and mandarin cv “Willow leaf” (C. reticulata Blanco). Parental and consensus genetic linkage maps were constructed using 645 SNP and SSR markers. These maps were represented by 10 linkage groups in clementine and 12 linkage groups in mandarin, representing 75% and 58% respectively of the previously published clementine reference map. A total of 16 traits, including fruit mass, equatorial diameter, juice percentage, total soluble solids, acidity, pH, glucose, fructose, sucrose, and citric and malic acid concentrations were evaluated at three maturation dates. High variations indicating transgressive segregation were found for all traits, with normal or close to normal distributions. QTL analysis performed using the multiple QTL model allowed the detection of 34 QTLs on the three maps. QTLs were distributed in different linkage groups and generally detected at only one date of the ripening phase. The percentage of total variation explained ranged from 12 to 37% per QTL. Major QTLs (R2 ≥ 30%) were detected for equatorial diameter, glucose, and fructose (expressed in percentage dry matter) on linkage groups 8 and 9. Co-localization of QTLs controlling correlated and uncorrelated traits were mainly found on linkage groups 2, 4, 8, and 9, particularly between fruit mass and acidity.

High-Density Linkage Mapping and Identification of Quantitative Trait Loci Associated with Powdery Mildew Resistance in Flowering Dogwood (Cornus florida)

Flowering dogwood (Cornus florida L.) is a popular, spring-blooming ornamental tree native to the eastern United States. The species is in general very susceptible to powdery mildew caused by Erysiphe pulchra, which disfigures leaves, decreases growth, and negatively affects flowering. Breeding for resistance has been recognized as an ideal strategy for controlling the disease in C. florida, but efforts have been hindered by the rarity of PM resistance in available germplasm and knowledge of its genetic control. In this study, we mapped quantitative trait loci (QTL) associated with PM resistance/tolerance in two full sibling populations segregating for PM response: Rutgers H4AR15P25 (P25) × Rutgers H4AR15R28 (P28) (n = 195) and Rutgers H4AR15R25 × Rutgers H4AR15P35 (P35) (n = 83). High-density genetic linkage maps were constructed for the mapping populations using double digest restriction-site associated DNA sequencing-derived single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). The P25 × P28 map consisted of 2265 markers, spanning 1520 cM and 11 linkage groups (LGs) with an average marker spacing of 0.69 cM. The P25 × P35 map was constructed with 1788 markers, spanning 1256 cM and 11 LGs, with an average marker spacing of 0.72 cM. The maps had 604 markers in common and exhibited excellent collinearity. Through multiple QTL model mapping, one major QTL (LOD = 11.36 and R2 = 58.9%) was identified in P25 × P35. Furthermore, a minor QTL (LOD = 3.30 and R2 = 7.8%) was detected in P25 × P28. Due to their proximity onLG3, these QTL may be designating the same locus or tightly linked loci. The negative additive effects of both QTL signify that the PM susceptible male parents were contributing susceptibility alleles to the progeny. This is the first report of QTL associated with PM response on LG3 in C. florida and lays the groundwork for the development of marker-assisted selection for PM resistance in C. florida breeding programs.

Genomic Regions and Floral Traits Contributing to Low Temperature Tolerance at Young Microspore Stage in a Rice (Oryza sativa L.) Recombinant Inbred Line Population of Sherpa/IRAT109.

Aerobic rice production (AP) consumes less water compared to flooded systems. Developing genotypes and identifying genomic regions associated with low temperature (LT) tolerance at the young microspore stage (YMS) is imperative for AP, particularly for temperate regions. Using a recombinant inbred line population derived from the Australian LT tolerant variety Sherpa, experiments were conducted to map and dissect quantitative trait loci (QTL) associated with spikelet sterility (SS) after exposure to LT and to investigate floral traits contributing to the development of lower SS. Significant genotypic variation for SS was observed in the population after exposure to LT at YMS. Three genomic regions associated with SS, qYMCT3, qYMCT4, and qYMCT8.1 were identified in chromosomes 3, 4, and 8 respectively, using multiple QTL models explaining 22.4% of the genotypic variation. Introgression of the favorable allele from qYMCT3 was estimated to reduce SS by up to 15.4%. A co-locating genomic region with qYMCT3, qDTHW3.1 was identified as the major QTL affecting days to heading and explained as much as 44.7% of the genotypic variation. Whole-genome sequence and bioinformatic analyses demonstrated OsMADS50 as the candidate gene for qYMCT3/qDTHW3.1 and to our knowledge, this was the first attempt in connecting the role of OsMADS50 in both LT and flowering in rice. Differential sets selected for extreme SS showed LT tolerant genotype group produced higher total pollen per spikelet resulting in a higher number of dehisced anthers and pollen on stigma and eventually, lower SS than THE sensitive group. The relationship between these key floral traits with SS was induced only after exposure to LT and was not observed in warm ideal temperature conditions. Identification of elite germplasm with favorable QTL allele and combinations, gene cloning, and pyramiding with additional high-value QTL for key traits should empower breeders to develop AP adapted genotypes for temperate growing regions, and ultimately produce climate-resilient rice.

Genetic control of source-sink relationships in grain sorghum.

QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18Mb), 2 (2.52-11.43Mb) and 3 (1.32-3.95Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

Genome-wide association study of individual sugar content in fruit of Japanese pear (Pyrus spp.)

BackgroundUnderstanding mechanisms of sugar accumulation and composition is essential to determining fruit quality and maintaining a desirable balance of sugars in plant storage organs. The major sugars in mature Rosaceae fruits are sucrose, fructose, glucose, and sorbitol. Among these, sucrose and fructose have high sweetness, whereas glucose and sorbitol have low sweetness. Japanese pear has extensive variation in individual sugar contents in mature fruit. Increasing total sugar content and that of individual high-sweetness sugars is a major target of breeding programs. The objective of this study was to identify quantitative trait loci (QTLs) associated with fruit traits including individual sugar accumulation, to infer the candidate genes underlying the QTLs, and to assess the potential of genomic selection for breeding pear fruit traits.ResultsWe evaluated 10 fruit traits and conducted genome-wide association studies (GWAS) for 106 cultivars and 17 breeding populations (1112 F1 individuals) using 3484 tag single-nucleotide polymorphisms (SNPs). By implementing a mixed linear model and a Bayesian multiple-QTL model in GWAS, 56 SNPs associated with fruit traits were identified. In particular, a SNP located close to acid invertase gene PPAIV3 on chromosome 7 and a newly identified SNP on chromosome 11 had quite large effects on accumulation of sucrose and glucose, respectively. We used ‘Golden Delicious’ doubled haploid 13 (GDDH13), an apple reference genome, to infer the candidate genes for the identified SNPs. In the region flanking the SNP on chromosome 11, there is a tandem repeat of early responsive to dehydration (ERD6)-like sugar transporter genes that might play a role in the phenotypes observed.ConclusionsSNPs associated with individual sugar accumulation were newly identified at several loci, and candidate genes underlying QTLs were inferred using advanced apple genome information. The candidate genes for the QTLs are conserved across Pyrinae genomes, which will be useful for further fruit quality studies in Rosaceae. The accuracies of genomic selection for sucrose, fructose, and glucose with genomic best linear unbiased prediction (GBLUP) were relatively high (0.67–0.75), suggesting that it would be possible to select individuals having high-sweetness fruit with high sucrose and fructose contents and low glucose content.

Detection of Quantitative Trait Loci Controlling the Content of Phenolic Compounds in an Asian Plum (Prunus salicina L.) F1 Population.

Consumption of fresh fruit is known to protect against non-communicable diseases due to the fruit's content in compounds with an antioxidant capacity, among them is polyphenols. Asian plums (Prunus salicina L.) accumulate more than 40 phenolic compounds, with a remarkable diversity in their profiles, depending on the variety and environmental conditions. Although candidate genes have been indicated to control this trait, the loci controlling its phenotypic variation have not yet been defined in this species. The aim of this work was to identify the quantitative trait Loci (QTL) controlling the phenolic compounds content in the Asian plum skin and flesh. Using UHPLC-DAD-Orbitrap-MS, we determined that cyanidin-3-glucoside and cyanidin-3-rutinoside are the main anthocyanins in Asian plums. Other anthocyanins found to a lesser extent were tentatively identified as cyanidin bound to different sugar and procyanidin moieties. Then we phenotyped fruits of 92 and 80 F1 seedlings from the cross < “98.99” × “Angeleno”> (98 Ang) for two harvest seasons. We used HPLC-DAD to quantify single anthocyanin and spectrophotometric techniques to determine the total content of phenols, flavonoids, procyanidins, and antioxidant activity (DPPH and FRAP). To determine the phenotype-genotype association of phenolic compounds content, phenotypic values (adjusted by linear mixed-effects models), genotypic data and linkage maps were analyzed with the multiple QTL model (MQM) approach. We found a total of 21 significant trait-marker associations: 13 QTLs segregating from “98.99” and 8 QTLs from “Angeleno.” From these associations, 8 corresponded to phenolic compound content in the flesh and 13 in the skin. Phenotype variance was explained by the detected loci, ranging from 12.4 to 27.1%. The identified loci are related to the content of cyanidin-3-glucoside (LG4), cyanidin-3-rutinoside (LG4), total flavonoids and procyanidins (LG5 and LG8), and minor anthocyanin compounds (LG3 and LG4). These results will help improve the efficiency of breeding programs for the generation of Asian plum varieties with high phenolic compound content.

Transgressive resistance to Heterodera glycines in chromosome segment substitution lines derived from susceptible soybean parents.

Chromosome segment substitution lines (CSSLs) are valuable genetic resources for quantitative trait loci (QTL) mapping of complex agronomic traits especially suitable for minor effect QTL. Here, 162 BC3 F7 -BC7 F3 CSSLs derived from crossing two susceptible parent lines, soybean [Glycine max (L.) Merr.] 'Suinong14' (recurrent parent) × wild soybean (G. soja Siebold & Zucc.) ZYD00006, were used for QTL mapping of soybean cyst nematode (SCN, Heterodera glycine Ichinohe) resistance based on female index (FI) and cysts per gram root (CGR) through phenotypic screening and whole-genome resequencing of CSSLs. Phenotypic results displayed a wide range of distribution and transgressive lines in both HG Type 2.5.7 FI and CGR and demonstrated a higher correlation between CGR and root weight (R2 = .5424) compared with than between FI and CGR (R2 = .0018). Using the single-marker analysis nonparametric mapping test, 33 significant QTL were detected on 18 chromosomes contributing resistance to FI and CGR. Fourteen QTL contributing 5.6-15.5% phenotypic variance (PVE) to FI were revealed on 11 chromosomes, and 16 QTL accounting for 6.1-36.2% PVE in CGR were detected on 14 chromosomes with strong additive effect by multiple-QTL model (MQM) mapping. Twenty-five and 13 out of all 38 QTL identified for FI and CGR on 20 chromosomes were from ZYD00006 and Suinong14, respectively. The CSSLs with the combination of positive alleles for FI, CGR, and root weight exhibited low nematode reproduction. For the first time, QTL associated with CGR have been detected, and both FI and CGR should be considered for breeding purposes in the absence of strong resistance genes such as rhg1 and Rhg4.

The recombination landscape and multiple QTL mapping in a Solanum tuberosum cv. \u2018Atlantic\u2019-derived F1 population

There are many challenges involved with the genetic analyses of autopolyploid species, such as the tetraploid potato, Solanum tuberosum (2n = 4x = 48). The development of new analytical methods has made it valuable to re-analyze an F1 population (n = 156) derived from a cross involving ‘Atlantic’, a widely grown chipping variety in the USA. A fully integrated genetic map with 4285 single nucleotide polymorphisms, spanning 1630 cM, was constructed with MAPpoly software. We observed that bivalent configurations were the most abundant ones (51.0~72.4% depending on parent and linkage group), though multivalent configurations were also observed (2.2~39.2%). Seven traits were evaluated over four years (2006–8 and 2014) and quantitative trait loci (QTL) mapping was carried out using QTLpoly software. Based on a multiple-QTL model approach, we detected 21 QTL for 15 out of 27 trait-year combination phenotypes. A hotspot on linkage group 5 was identified with co-located QTL for maturity, plant yield, specific gravity, and internal heat necrosis resistance evaluated over different years. Additional QTL for specific gravity and dry matter were detected with maturity-corrected phenotypes. Among the genes around QTL peaks, we found those on chromosome 5 that have been previously implicated in maturity (StCDF1) and tuber formation (POTH1). These analyses have the potential to provide insights into the biology and breeding of tetraploid potato and other autopolyploid species.

Stable and Novel Quantitative Trait Loci (QTL) Confer Narrow Root Cone Angle in an Aerobic Rice (Oryza sativa L.) Production System

BackgroundAerobic rice production (AP) may be a solution to the looming water crisis by utilising less water compared to traditional flooded culture. As such, development of genotypes with narrow root cone angle (RCA) is considered a key AP adaptation trait as it could lead to deeper rooting and ensure water uptake at depth. Quantitative trait loci (QTL) and genes associated with rooting angle have been identified in rice, but usually in conventional transplanted systems or in upland and drought conditions. This study aimed to identify QTL associated with RCA in AP systems using a recombinant inbred line population derived from IRAT109.ResultsFour experiments conducted in glasshouse and aerobic field conditions revealed significant genotypic variation existed for RCA in the population. Single and multiple QTL models identified the presence of eight QTL distributed in chromosomes 1, 2, 3, 4, and 11. Combined, these QTL explained 36.7–51.2% of the genotypic variance in RCA present in the population. Two QTL, qRCA1.1 and qRCA1.3, were novel and may be new targets for improvement of RCA. Genotypes with higher number of favourable QTL alleles tended to have narrower RCA. qRCA4 was shown to be a major and stable QTL explaining up to 24.3% of the genotypic variation, and the presence of the target allele resulted in as much as 8.6° narrower RCA. Several genes related to abiotic stress stimulus response were found in the qRCA4 region.ConclusionStable and novel genomic regions associated with RCA have been identified. Genotypes which had combinations of these QTL, resulted in a narrower RCA phenotype. Allele mining, gene cloning, and physiological dissection should aid in understanding the molecular function and mechanisms underlying RCA and these QTL. Ultimately, our work provides an opportunity for breeding programs to develop genotypes with narrow RCA and deep roots for improved adaptation in an AP system for sustainable rice production.

Treatment of the X chromosome in mapping multiple quantitative trait loci

Statistical methods to map quantitative trait loci (QTL) often neglect the X chromosome and may focus exclusively on autosomal loci. But the X chromosome often requires special treatment: sex and cross-direction covariates may need to be included to avoid spurious evidence of linkage, and the X chromosome may require a separate significance threshold. In multiple-QTL analyses, including the consideration of epistatic interactions, the X chromosome also requires special care and consideration. We extend a penalized likelihood method for multiple-QTL model selection, to appropriately handle the X chromosome. We examine its performance in simulation and by application to a large eQTL data set. The method has been implemented in the package R/qtl.

Bayesian Modeling for Epistasis Analysis Using Data-Driven Reversible Jump.

We propose a procedure for modeling a phenotype using QTLs which estimate the additive and dominance effects of genotypes and epistasis. The estimation of the model is implemented through a Bayesian approach which uses the data-driven reversible jump (DDRJ) for multiple QTL mapping and model selection. We compare the DDRJ's performance with the usual reversible jump (RJ), QTLBim, multiple interval mapping (MIM) and LASSO using real and simulated data sets. The DDRJ outperforms the available methods to estimate the number of QTLs in epistatic models and it identifies their locations in the genome, without increasing the number of false-positive QTLs in the considered data. Since QTL mapping is a regression model involving complex non-observable variables and their interactions, the model selection procedure proposed here is also useful in other areas of research. The application for identifying main and epistatic relevant QTLs to systolic blood pressure after salt intervention is our main motivation.

Identification of loci controlling phenology, fruit quality and post-harvest quantitative parameters in Japanese plum (Prunus salicina Lindl.)

Abstract Japanese plums are popular fruits since they are exceptionally nutritious with high fiber and antioxidant content. This work has aimed to analyze the most critical phenology, fruit quality and postharvest parameters from a genomic point of view to identify molecular markers closely linked to the most significant Quantitative trait loci (QTLs). A genetic linkage map of an F1 population of 151 individuals from the cross '98–99’ × 'Angeleno' was constructed using previously reported Single Nucleotide polymorphism (SNP) data and 25 additional Simple Sequence Repeat (SSR) markers. Twenty-three phenotypic traits evaluated during three harvest seasons were assayed to estimate best linear unbiased predictors by using two genomic association QTL analysis approaches: General Linear Model-based single marker-trait associations (GLM) and Multiple QTL Model analyses (MQM). In addition, loss of weight and chlorophyll degradation between days 1 and 7 as well as fruit softening for days 1, 4, and 7 were monitored during two consecutive seasons. The most significant identified QTLs were linked to fruit development period and fruit weight in Linkage Groups (LG) 4 and 2, respectively. Regarding postharvest parameters, the identified QTLs related to chlorophyll degradation and loss of weight showed lower significance than phenology or fruit quality traits. In contrast, minor QTLs for fruit firmness evolution using destructive and non-destructive methods were confirmed in LG 4 and 5.

Three Quantitative Trait Loci Explain More than 60% of Variation for Chill Coma Recovery Time in a Natural Population of Drosophila ananassae.

Ectothermic species such as insects are particularly vulnerable to climatic fluctuations. Nevertheless, many insects that evolved and diversified in the tropics have successfully colonized temperate regions all over the globe. To shed light on the genetic basis of cold tolerance in such species, we conducted a quantitative trait locus (QTL) mapping experiment for chill coma recovery time (CCRT) in Drosophila ananassae, a cosmopolitan species that has expanded its range from tropical to temperate regions. We created a mapping population of recombinant inbred advanced intercross lines (RIAILs) from two founder strains with diverging CCRT phenotypes. The RIAILs were phenotyped for their CCRT and, together with the founder strains, genotyped for polymorphic markers with double-digest restriction site-associated DNA (ddRAD) sequencing. Using a hierarchical mapping approach that combined standard interval mapping and a multiple-QTL model, we mapped three QTL which altogether explained 64% of the phenotypic variance. For two of the identified QTL, we found evidence of epistasis. To narrow down the list of cold tolerance candidate genes, we cross-referenced the QTL intervals with genes that we previously identified as differentially expressed in response to cold in D. ananassae, and with thermotolerance candidate genes of D. melanogaster. Among the 58 differentially expressed genes that were contained within the QTL, GF15058 showed a significant interaction of the CCRT phenotype and gene expression. Further, we identified the orthologs of four D. melanogaster thermotolerance candidate genes, MtnA, klarsicht, CG5246 (D.ana/GF17132) and CG10383 (D.ana/GF14829) as candidates for cold tolerance in D. ananassae.

Enhancing Upland cotton for drought resilience, productivity, and fiber quality: comparative evaluation and genetic dissection.

To provision the world sustainably, modern society must increase overall crop production, while conserving and preserving natural resources. Producing more with diminishing water resources is an especially daunting endeavor. Toward the goal of genetically improving drought resilience of cultivated Upland cotton (Gossypium hirsutum L.), this study addresses the genetics of differential yield components referred to as productivity and fiber quality traits under regular-water versus low-water (LW) field conditions. We used ten traits to assess water stress deficit, which included six productivity and four fiber quality traits on two recombinant inbred line (RIL) populations from reciprocally crossed cultivars, Phytogen 72 and Stoneville 474. To facilitate genetic inferences, we genotyped RILs with the CottonSNP63K array, assembled high-density linkage maps of over 7000 SNPs and then analyzed quantitative trait variations. Analysis of variance revealed significant differences for all traits (p < 0.05) in these RIL populations. Although the LW irrigation regime significantly reduced all traits, except lint percent, the RILs exhibited a broad phenotypic spectrum of heritable differences across the water regimes. Transgressive segregation occurred among the RILs, suggesting the possibility of genetic gain through phenotypic selection for drought resilience and perhaps through marker-based selection. Analyses revealed more than 150 quantitative trait loci (QTLs) associated with productivity and fiber quality traits (p < 0.005) on different genomic regions of the cotton genome. The multiple-QTL models analysis with LOD > 3.0 detected 21 QTLs associated with productivity and 22 QTLs associated with fiber quality. For fiber traits, strong clustering and QTL associations occurred in c08 and its homolog c24 as well as c10, c14, and c21. Using contemporary genome sequence assemblies and bioinformatically related information, the identification of genomic regions associated with responses to plant stress/drought elevates the possibility of using marker-assisted and omics-based selection to enhance breeding for drought resilient cultivars and identifying candidate genes and networks. RILs with different responses to drought indicated that it is possible to maintain high fiber quality under LW conditions or reduce the of LW impact on quality. The heritable variation among elite bi-parental RILs for productivity and quality under field drought conditions, and their association of QTLs, and thus specific genomic regions, indicate opportunities for breeding-based gains in water resource conservation, i.e., enhancing cotton's agricultural sustainability.

Combined linkage and association mapping of putative QTLs controlling black tea quality and drought tolerance traits

The advancements in genotyping have opened new approaches for identification and precise mapping of quantitative trait loci (QTLs) in plants, particularly by combining linkage and association mapping (AM) analysis. In this study, a combination of linkage and the AM approach was used to identify and authenticate putative QTLs associated with black tea quality traits and percent relative water content (%RWC). The population structure analysis clustered two parents and their respective 261 F1 progenies from the two reciprocal crosses into two clusters with 141 tea accessions in cluster one and 122 tea accessions in cluster two. The two clusters were of mixed origin with tea accessions in population TRFK St. 504 clustering together with tea accessions in population TRFK St. 524. A total of 71 putative QTLs linked to black tea quality traits and %RWC were detected in interval mapping (IM) method and were used as cofactors in multiple QTL model (MQM) mapping where 46 putative QTLs were detected. The phenotypic variance for each QTL ranged from 2.8 to 23.3% in IM and 4.1 to 23% in MQM mapping. Using Q-model and Q + K-model in AM, a total of 49 DArTseq markers were associated with 16 phenotypic traits. Significant marker-trait association in AM were similar to those obtained in IM, and MQM mapping except for six more putative QTLs detected in AM which are involved in biosynthesis of secondary metabolites, carbon fixation and abiotic stress. The combined linkage and AM approach appears to have great potential to improve the selection of desirable traits in tea breeding.

Interspecific genetic maps in Miscanthus floridulus and M. sacchariflorus accelerate detection of QTLs associated with plant height and inflorescence

Miscanthus is recognized as a promising lignocellulosic crop for the production of bioethanol and bioproducts worldwide. To facilitate the identification of agronomical important traits and establish genetics knowledge, two genetic maps were developed from a controlled interspecific cross between M. floridulus and M. sacchariflorus. A total of 650 SSR markers were mapped in M. floridulus, spanning 19 linkage groups and 2053.31cM with an average interval of 3.25cM. The map of M. sacchariflorus comprised 495 SSR markers in 19 linkage groups covering 1684.86cM with an average interval of 3.54cM. The estimation on genome length indicated that the genome coverage of parental genetic maps were 93.87% and 89.91%, respectively. Eighty-eight bi-parental common markers were allowed to connect the two maps, and six pairs of syntenic linkage groups were recognized. Furthermore, quantitative trait loci (QTL) mapping of three agronomic traits, namely, plant height (PH), heading time (HT), and flowering time (FT), demonstrated that a total of 66 QTLs were identified in four consecutive years using interval mapping and multiple-QTL model. The LOD value of these QTLs ranged from 2.51 to 10.60, and the phenotypic variation explained varied from 9.50 to 37.10%. QTL cluster in syntenic groups MF19/MS7 contained six stable QTLs associated with PH, HT, and FT. In conclusion, we report for the first time the genetic mapping of biomass traits in M. floridulus and M. sacchariflorus. These results will be a valuable genetic resource, facilitating the discovery of essential genes and breeding of Miscanthus.

Comparative Aerial and Ground Based High Throughput Phenotyping for the Genetic Dissection of NDVI as a Proxy for Drought Adaptive Traits in Durum Wheat.

High-throughput phenotyping platforms (HTPPs) provide novel opportunities to more effectively dissect the genetic basis of drought-adaptive traits. This genome-wide association study (GWAS) compares the results obtained with two Unmanned Aerial Vehicles (UAVs) and a ground-based platform used to measure Normalized Difference Vegetation Index (NDVI) in a panel of 248 elite durum wheat (Triticum turgidum L. ssp. durum Desf.) accessions at different growth stages and water regimes. Our results suggest increased ability of aerial over ground-based platforms to detect quantitative trait loci (QTL) for NDVI, particularly under terminal drought stress, with 22 and 16 single QTLs detected, respectively, and accounting for 89.6 vs. 64.7% phenotypic variance based on multiple QTL models. Additionally, the durum panel was investigated for leaf chlorophyll content (SPAD), leaf rolling and dry biomass under terminal drought stress. In total, 46 significant QTLs affected NDVI across platforms, 22 of which showed concomitant effects on leaf greenness, 2 on leaf rolling and 10 on biomass. Among 9 QTL hotspots on chromosomes 1A, 1B, 2B, 4B, 5B, 6B, and 7B that influenced NDVI and other drought-adaptive traits, 8 showed per se effects unrelated to phenology.