Comparative Analysis of Qtls Affecting Plant Height and Maturity across the Poaceae, in Reference to an Interspecific Sorghum Population

Correspondence among QTLs affecting height and/or flowering was investigated across the five races of sorghum, an interspecific sorghum F(2) population, and 32 previously published sorghum, maize, rice, wheat, and barley populations revealing 185 QTLs or discrete mutants. Among nine QTLs mapped in the interspecific sorghum population (six affecting height and three affecting flowering), at least seven (78%) are associated with ``conversion,'''' backcross-introgression of alleles imparting reduced height or earlier flowering from cultivated sorghums into one or more exotic Sorghum bicolor races. One chromosomal region was ``converted'''' in all S. bicolor races--in the interspecific F(2), this region explined 54.8% of height variation (putatively the Dw2 gene) and 85.7% of flowering time variation (putatively Ma1). Comparative data suggest that Ma1 and Dw2 orthologs influence height and flowering of other Poaceae taxa and support classical dogma that the sorghum phenotypes attributed to Ma1 and Dw2 (respectively) are due to different genetic loci. Other sorghum QTLs also showed correspondence with those in other Poaceae, more frequently than would be expected by chance. Possible homoeologous QTLs were found within both the maize and sorghum genomes. Comparative QTL mapping provides a means to unify, and thereby simplify, molecular analysis of complex phenotypes.     

Joint QTL linkage mapping for multiple-cross mating design sharing one common parent

Background

Nested association mapping (NAM) is a novel genetic mating design that combines the advantages of linkage analysis and association mapping. This design provides opportunities to study the inheritance of complex traits, but also requires more advanced statistical methods. In this paper, we present the detailed algorithm of a QTL linkage mapping method suitable for genetic populations derived from NAM designs. This method is called joint inclusive composite interval mapping (JICIM). Simulations were designed on the detected QTL in a maize NAM population and an Arabidopsis NAM population so as to evaluate the efficiency of the NAM design and the JICIM method.

Principal Findings

Fifty-two QTL were identified in the maize population, explaining 89% of the phenotypic variance of days to silking, and nine QTL were identified in the Arabidopsis population, explaining 83% of the phenotypic variance of flowering time. Simulations indicated that the detection power of these identified QTL was consistently high, especially for large-effect QTL. For rare QTL having significant effects in only one family, the power of correct detection within the 5 cM support interval was around 80% for 1-day effect QTL in the maize population, and for 3-day effect QTL in the Arabidopsis population. For smaller-effect QTL, the power diminished, e.g., it was around 50% for maize QTL with an effect of 0.5 day. When QTL were linked at a distance of 5 cM, the likelihood of mapping them as two distinct QTL was about 70% in the maize population. When the linkage distance was 1 cM, they were more likely mapped as one single QTL at an intermediary position.

Conclusions

Because it takes advantage of the large genetic variation among parental lines and the large population size, NAM is a powerful multiple-cross design for complex trait dissection. JICIM is an efficient and specialty method for the joint QTL linkage mapping of genetic populations derived from the NAM design.     

Genotypic and phenotypic characterization of a large,diverse population of maize near‐isogenic lines

Genome‐wide association (GWA) studies can identify quantitative trait loci (QTL) putatively underlying traits of interest, and nested association mapping (NAM) can further assess allelic series. Near‐isogenic lines (NILs) can be used to characterize, dissect and validate QTL, but the development of NILs is costly. Previous studies have utilized limited numbers of NILs and introgression donors. We characterized a panel of 1270 maize NILs derived from crosses between 18 diverse inbred lines and the recurrent inbred parent B73, referred to as the nested NILs (nNILs). The nNILs were phenotyped for flowering time, height and resistance to three foliar diseases, and genotyped with genotyping‐by‐sequencing. Across traits, broad‐sense heritability (0.4–0.8) was relatively high. The 896 genotyped nNILs contain 2638 introgressions, which span the entire genome with substantial overlap within and among allele donors. GWA with the whole panel identified 29 QTL for height and disease resistance with allelic variation across donors. To date, this is the largest and most diverse publicly available panel of maize NILs to be phenotypically and genotypically characterized. The nNILs are a valuable resource for the maize community, providing an extensive collection of introgressions from the founders of the maize NAM population in a B73 background combined with data on six agronomically important traits and from genotyping‐by‐sequencing. We demonstrate that the nNILs can be used for QTL mapping and allelic testing. The majority of nNILs had four or fewer introgressions, and could readily be used for future fine mapping studies.     

Large‐scale GWAS in sorghum reveals common genetic control of grain size among cereals

Grain size is a key yield component of cereal crops and a major quality attribute. It is determined by a genotype’s genetic potential and its capacity to fill the grains. This study aims to dissect the genetic architecture of grain size in sorghum. An integrated genome‐wide association study (GWAS) was conducted using a diversity panel (n = 837) and a BC‐NAM population (n = 1421). To isolate genetic effects associated with genetic potential of grain size, rather than the genotype’s capacity to fill the grains, a treatment of removing half of the panicle was imposed during flowering. Extensive and highly heritable variation in grain size was observed in both populations in 5 field trials, and 81 grain size QTL were identified in subsequent GWAS. These QTL were enriched for orthologues of known grain size genes in rice and maize, and had significant overlap with SNPs associated with grain size in rice and maize, supporting common genetic control of this trait among cereals. Grain size genes with opposite effect on grain number were less likely to overlap with the grain size QTL from this study, indicating the treatment facilitated identification of genetic regions related to the genetic potential of grain size. These results enhance understanding of the genetic architecture of grain size in cereal, and pave the way for exploration of underlying molecular mechanisms and manipulation of this trait in breeding practices.     

Identification of genetic variants associated with maize flowering time using an extremely large multi‐genetic background population

Flowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi‐ genetic background population that contained more than 8000 lines under multiple Sino‐United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single‐nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One‐third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome‐wide association study of the three panels identified nearly 1000 flowering time‐associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs – one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time.     

Identification and validation of genomic regions that affect shoot fly resistance in sorghum [<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench]

Shoot fly is one of the most important pests affecting the sorghum production. The identification of quantitative trait loci (QTL) affecting shoot fly resistance enables to understand the underlying genetic mechanisms and genetic basis of complex interactions among the component traits. The aim of the present study was to detect QTL for shoot fly resistance and the associated traits using a population of 210 RILs of the cross 27B (susceptible) × IS2122 (resistant). RIL population was phenotyped in eight environments for shoot fly resistance (deadheart percentage), and in three environments for the component traits, such as glossiness, seedling vigor and trichome density. Linkage map was constructed with 149 marker loci comprising 127 genomic-microsatellite, 21 genic-microsatellite and one morphological marker. QTL analysis was performed by using MQM approach. 25 QTL (five each for leaf glossiness and seedling vigor, 10 for deadhearts, two for adaxial trichome density and three for abaxial trichome density) were detected in individual and across environments. The LOD and R ² (%) values of QTL ranged from 2.44 to 24.1 and 4.3 to 44.1%, respectively. For most of the QTLs, the resistant parent, IS2122 contributed alleles for resistance; while at two QTL regions, the susceptible parent 27B also contributed for resistance traits. Three genomic regions affected multiple traits, suggesting the phenomenon of pleiotrophy or tight linkage. Stable QTL were identified for the traits across different environments, and genetic backgrounds by comparing the QTL in the study with previously reported QTL in sorghum. For majority of the QTLs, possible candidate genes were identified. The QTLs identified will enable marker assisted breeding for shoot fly resistance in sorghum.     

Comparative analysis of QTLs affecting plant height and flowering among closely-related diploid and polyploid genomes.

Quantitative trait loci (QTLs) affecting plant height and flowering were studied in the two Saccharum species from which modern sugarcane cultivars are derived. Two segregating populations derived from interspecific crosses between Saccharum officinarum and Saccharum spontaneum were genotyped with 735 DNA markers. Among the 65 significant associations found between these two traits and DNA markers, 35 of the loci were linked to sugarcane genetic maps and 30 were unlinked DNA markers. Twenty-one of the 35 mapped QTLs were clustered in eight genomic regions of six sugarcane homologous groups. Some of these could be divergent alleles at homologous loci, making the actual number of genes implicated in these traits much less than 35. Four QTL clusters controlling plant height in sugarcane corresponded closely to four of the six plant-height QTLs previously mapped in sorghum. One QTL controlling flowering in sugarcane corresponded to one of three flowering QTLs mapped in sorghum. The correspondence in locations of QTLs affecting plant height and flowering in sugarcane and sorghum reinforce the notion that the simple sorghum genome is a valuable "template" for molecular dissection of the much more complex sugarcane genome.     

Identification of quantitative trait loci for yield and yield components in an advanced backcross population derived from the<Emphasis Type="Italic"> Oryza sativa</Emphasis> variety IR64 and the wild relative<Emphasis Type="Italic"> O. rufipogon</Emphasis>

A BC₂F₂ population developed from an interspecific cross between Oryza sativa (cv IR64) and O. rufipogon (IRGC 105491) was used in an advanced backcross QTL analysis to identify and introduce agronomically useful genes from this wild relative into the cultivated gene pool. The objectives of this study were: (1) to identify putative yield and yield component QTLs that can be useful to improve the elite cultivar IR64; (2) to compare the QTLs within this study with previously reported QTLs in rice as the basis for identifying QTLs that are stable across different environments and genetic backgrounds; and (3) to compare the identified QTLs with previously reported QTLs from maize to examine the degree of QTL conservation across the grass family. Two hundred eighty-five families were evaluated in two field environments in Indonesia, with two replications each, for 12 agronomic traits. A total of 165 markers consisting of 131 SSRs and 34 RFLPs were used to construct the genetic linkage map. By employing interval mapping and composite interval mapping, 42 QTLs were identified. Despite its inferior performance, 33% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield and yield components in the IR64 background. Twenty-two QTLs (53.4%) were located in similar regions as previously reported rice QTLs, suggesting the existence of stable QTLs across genetic backgrounds and environments. Twenty QTLs (47.6%) were exclusively detected in this study, uncovering potentially novel alleles from the wild, some of which might improve the performance of the tropical indica variety IR64. Additionally, several QTLs for plant height, grain weight, and flowering time detected in this study corresponded to homeologous regions in maize containing previously detected maize QTLs for these traits.     

Joint-multiple family linkage analysis predicts within-family variation better than single-family analysis of the maize nested association mapping population

Quantitative trait locus (QTL) mapping has been used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assisted selection. Many QTL mapping studies in plants have been limited to one biparental family population. Joint analysis of multiple biparental families offers an alternative approach to QTL mapping with a wider scope of inference. Joint-multiple population analysis should have higher power to detect QTL shared among multiple families, but may have lower power to detect rare QTL. We compared prediction ability of single-family and joint-family QTL analysis methods with fivefold cross-validation for 6 diverse traits using the maize nested association mapping population, which comprises 25 biparental recombinant inbred families. Joint-family QTL analysis had higher mean prediction abilities than single-family QTL analysis for all traits at most significance thresholds, and was always better at more stringent significance thresholds. Most robust QTL (detected in >50% of data samples) were restricted to one family and were often not detected at high frequency by joint-family analysis, implying substantial genetic heterogeneity among families for complex traits in maize. The superior predictive ability of joint-family QTL models despite important genetic differences among families suggests that joint-family models capture sufficient smaller effect QTL that are shared across families to compensate for missing some rare large-effect QTL.     

QTL mapping reveals the genetic architecture of loci affecting pre- and post-zygotic isolating barriers in Louisiana Iris

ABSTRACT: BACKGROUND: Hybridization among Louisiana Irises has been well established and the genetic architecture of reproductive isolation is known to affect the potential for and the directionality of introgression between taxa. Here we use co-dominant markers to identify regions where QTL are located both within and between backcross maps to compare the genetic architecture of reproductive isolation and fitness traits across treatments and years. RESULTS: QTL mapping was used to elucidate the genetic architecture of reproductive isolation between Iris fulva and Iris brevicaulis. Homologous co-dominant EST-SSR markers scored in two backcross populations between I. fulva and I. brevicaulis were used to generate genetic linkage maps. These were used as the framework for mapping QTL associated with variation in 11 phenotypic traits likely responsible for reproductive isolation and fitness. QTL were dispersed throughout the genome, with the exception of one region of a single linkage group (LG) where QTL for flowering time, sterility, and fruit production clustered. In most cases, homologous QTL were not identified in both backcross populations, however, homologous QTL for flowering time, number of growth points per rhizome, number of nodes per inflorescence, and number of flowers per node were identified on several linkage groups. CONCLUSION: Two different traits affecting reproductive isolation, flowering time and sterility, exhibit different genetic architectures, with numerous QTL across the Iris genome controlling flowering time and fewer, less distributed QTL affecting sterility. QTL for traits affecting fitness are largely distributed across the genome with occasional overlap, especially on LG 4, where several QTL increasing fitness and decreasing sterility cluster. Given the distribution and effect direction of QTL affecting reproductive isolation and fitness, we have predicted genomic regions where introgression may be more likely to occur (those regions associated with an increase in fitness and unlinked to loci controlling reproductive isolation) and those that are less likely to exhibit introgression (those regions linked to traits decreasing fitness and reproductive isolation).     

QTL for nodal root angle in sorghum (<Emphasis Type="Italic">Sorghum bicolor</Emphasis> L. Moench) co-locate with QTL for traits associated with drought adaptation

Nodal root angle in sorghum influences vertical and horizontal root distribution in the soil profile and is thus relevant to drought adaptation. In this study, we report for the first time on the mapping of four QTL for nodal root angle (qRA) in sorghum, in addition to three QTL for root dry weight, two for shoot dry weight, and three for plant leaf area. Phenotyping was done at the six leaf stage for a mapping population (n = 141) developed by crossing two inbred sorghum lines with contrasting root angle. Nodal root angle QTL explained 58.2% of the phenotypic variance and were validated across a range of diverse inbred lines. Three of the four nodal root angle QTL showed homology to previously identified root angle QTL in rice and maize, whereas all four QTL co-located with previously identified QTL for stay-green in sorghum. A putative association between nodal root angle QTL and grain yield was identified through single marker analysis on field testing data from a subset of the mapping population grown in hybrid combination with three different tester lines. Furthermore, a putative association between nodal root angle QTL and stay-green was identified using data sets from selected sorghum nested association mapping populations segregating for root angle. The identification of nodal root angle QTL presents new opportunities for improving drought adaptation mechanisms via molecular breeding to manipulate a trait for which selection has previously been very difficult.     

Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences

Managed environments in the form of well watered and water stressed trials were performed to study the genetic basis of grain yield and stay green in sorghum with the objective of validating previously detected QTL. As variations in phenology and plant height may influence QTL detection for the target traits, QTL for flowering time and plant height were introduced as cofactors in QTL analyses for yield and stay green. All but one of the flowering time QTL were detected near yield and stay green QTL. Similar co-localization was observed for two plant height QTL. QTL analysis for yield, using flowering time/plant height cofactors, led to yield QTL on chromosomes 2, 3, 6, 8 and 10. For stay green, QTL on chromosomes 3, 4, 8 and 10 were not related to differences in flowering time/plant height. The physical positions for markers in QTL regions projected on the sorghum genome suggest that the previously detected plant height QTL, Sb-HT9-1, and Dw2, in addition to the maturity gene, Ma5, had a major confounding impact on the expression of yield and stay green QTL. Co-localization between an apparently novel stay green QTL and a yield QTL on chromosome 3 suggests there is potential for indirect selection based on stay green to improve drought tolerance in sorghum. Our QTL study was carried out with a moderately sized population and spanned a limited geographic range, but still the results strongly emphasize the necessity of corrections for phenology in QTL mapping for drought tolerance traits in sorghum.     

QTL for fibre-related traits in grain × sweet sorghum as a tool for the enhancement of sorghum as a biomass crop

Compared to maize and temperate grasses, sorghum has received less attention in terms of improving cell wall components. The objectives of this study were to identify quantitative trait loci (QTL) with main effects, epistatic and pleiotropic effects along with QTL × environment (QE) interactions controlling fibre-related traits in sorghum. Neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), cellulose, hemicellulose, fresh leaf mass, stripped stalk mass, dry stalk mass, fresh biomass and dry biomass were analysed from a population of 188 grain × sweet sorghum recombinant inbred lines. A genetic map consisting of 157 DNA markers was constructed, and QTL were detected using composite interval mapping (CIM). CIM detected more than 5 additive QTL per trait explaining 7.1–24.7% of the phenotypic variation. Abundant co-localization of these QTL was observed across all chromosomes, and the highest cluster was identified on chromosome 6. Searching for candidate genes using the confidence interval of our QTL clusters reveals that these clusters might comprise a set of genes that are tightly linked. Some QTL showed multiple effects; however, the allele for each trait was favouring the parent with the increasing effect. QE interactions were observed for QTL showing multiple effects. Additive × additive interaction was observed for 7 out of 10 traits, indicating the importance of epistatic analysis. However, the phenotypic variation explained by digenic interactions was lower compared to the individual QTL. Our results indicate that various genetic components contribute to fibre-related traits and should be considered during the enhancement of sorghum for lignocellulosic biomass.     

Genetic design and statistical power of nested association mapping in maize

We investigated the genetic and statistical properties of the nested association mapping (NAM) design currently being implemented in maize (26 diverse founders and 5000 distinct immortal genotypes) to dissect the genetic basis of complex quantitative traits. The NAM design simultaneously exploits the advantages of both linkage analysis and association mapping. We demonstrated the power of NAM for high-power cost-effective genome scans through computer simulations based on empirical marker data and simulated traits with different complexities. With common-parent-specific (CPS) markers genotyped for the founders and the progenies, the inheritance of chromosome segments nested within two adjacent CPS markers was inferred through linkage. Genotyping the founders with additional high-density markers enabled the projection of genetic information, capturing linkage disequilibrium information, from founders to progenies. With 5000 genotypes, 30-79% of the simulated quantitative trait loci (QTL) were precisely identified. By integrating genetic design, natural diversity, and genomics technologies, this new complex trait dissection strategy should greatly facilitate endeavors to link molecular variation with phenotypic variation for various complex traits.     

Flowering time QTL in natural populations of Arabidopsis thaliana and implications for their adaptive value

The genetic basis of phenotypic traits is of great interest to evolutionary biologists, but their contribution to adaptation in nature is often unknown. To determine the genetic architecture of flowering time in ecologically relevant conditions, we used a recombinant inbred line population created from two locally adapted populations of Arabidopsis thaliana from Sweden and Italy. Using these RILs, we identified flowering time QTL in growth chambers that mimicked the natural temperature and photoperiod variation across the growing season in each native environment. We also compared the genomic locations of flowering time QTL to those of fitness (total fruit number) QTL from a previous three‐year field study. Ten total flowering time QTL were found, and in all cases, the Italy genotype caused early flowering regardless of the conditions. Two QTL were consistent across chamber environments, and these had the largest effects on flowering time. Five of the fitness QTL colocalized with flowering time QTL found in the Italy conditions, and in each case, the local genotype was favoured. In contrast, just two flowering time QTL found in the Sweden conditions colocalized with fitness QTL and in only one case was the local genotype favoured. This implies that flowering time may be more important for adaptation in Italy than Sweden. Two candidate genes (FLC and VIN3) underlying the major flowering time QTL found in the current study are implicated in local adaptation.     

Identification of QTL for sugar-related traits in a sweet × grain sorghum (<Emphasis Type="Italic">Sorghum bicolor</Emphasis> L. Moench) recombinant inbred population

QTL for stem sugar-related and other agronomic traits were identified in a converted sweet (R9188) × grain (R9403463-2-1) sorghum population. QTL analyses were conducted using phenotypic data for 11 traits measured in two field experiments and a genetic map comprising 228 SSR and AFLP markers grouped into 16 linkage groups, of which 11 could be assigned to the 10 sorghum chromosomes (SBI-01 to SBI-10). QTL were identified for all traits and were generally co-located to five locations (SBI-01, SBI-03, SBI-05, SBI-06 and SBI-10). QTL alleles from R9188 were detected for increased sucrose content and sugar content on SBI-01, SBI-05 and SBI-06. R9188 also contributed QTL alleles for increased Brix on SBI-05 and SBI-06, and increased sugar content on SBI-03. QTL alleles from R9403463-2-1 were found for increased sucrose content and sucrose yield on SBI-10, and increased glucose content on SBI-07. QTL alleles for increased height, later flowering and greater total dry matter yield were located on SBI-01 of R9403463-2-1, and SBI-06 of R9188. QTL alleles for increased grain yield from both R9403463-2-1 and R9188 were found on SBI-03. As an increase in stem sugars is an important objective in sweet sorghum breeding, the QTL identified in this study could be further investigated for use in marker-assisted selection of sweet sorghum.     

Modelling the genetic architecture of flowering time control in barley through nested association mapping

Background

Barley, globally the fourth most important cereal, provides food and beverages for humans and feed for animal husbandry. Maximizing grain yield under varying climate conditions largely depends on the optimal timing of flowering. Therefore, regulation of flowering time is of extraordinary importance to meet future food and feed demands. We developed the first barley nested association mapping (NAM) population, HEB-25, by crossing 25 wild barleys with one elite barley cultivar, and used it to dissect the genetic architecture of flowering time.

Results

Upon cultivation of 1,420 lines in multi-field trials and applying a genome-wide association study, eight major quantitative trait loci (QTL) were identified as main determinants to control flowering time in barley. These QTL accounted for 64% of the cross-validated proportion of explained genotypic variance (p_G). The strongest single QTL effect corresponded to the known photoperiod response gene Ppd-H1. After sequencing the causative part of Ppd-H1, we differentiated twelve haplotypes in HEB-25, whereof the strongest exotic haplotype accelerated flowering time by 11 days compared to the elite barley haplotype. Applying a whole genome prediction model including main effects and epistatic interactions allowed predicting flowering time with an unmatched accuracy of 77% of cross-validated p_G.

Conclusions

The elaborated causal models represent a fundamental step to explain flowering time in barley. In addition, our study confirms that the exotic biodiversity present in HEB-25 is a valuable toolbox to dissect the genetic architecture of important agronomic traits and to replenish the elite barley breeding pool with favorable, trait-improving exotic alleles.

     

The Genetic Architecture of Flowering Time and Photoperiod Sensitivity in Maize as Revealed by QTL Review and Meta Analysis

The control of flowering is not only important for reproduction,but also plays a key role in the processes of domestication and adaptation.To reveal the genetic architecture for flowering time and photoperiod sensitivity,a comprehensive evaluation of the relevant literature was performed and followed by meta analysis.A total of 25 synthetic consensus quantitative trait loci(QTL)and four hot-spot genomic regions were identified for photoperiod sensitivity including 11 genes related to photoperiod response or flower morphogenesis and development.Besides,a comparative analysis of the QTL for flowering time and photoperiod sensitivity highlighted the regions containing shared and unique QTL for the two traits.Candidate genes associated with maize flowering were identified through integrated analysis of the homologous genes for flowering time in plants and the consensus QTL regions for photoperiod sensitivity in maize(Zea mays L.).Our results suggest that the combination of literature review,meta-analysis and homologous blast is an efficient approach to identify new candidate genes and create a global view of the genetic architecture for maize photoperiodic flowering.Sequences of candidate genes can be used to develop molecular markers for various models of marker-assisted selection,such as marker-assisted recurrent selection and genomic selection that can contribute significantly to crop environmental adaptation.     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

Identification of quantitative trait loci for resistance to shoot fly in sorghum [<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench]

The shoot fly is one of the most destructive insect pests of sorghum at the seedling stage. Deployment of cultivars with improved shoot fly resistance would be facilitated by the use of molecular markers linked to QTL. The objective of this study was to dissect the genetic basis of resistance into QTL, using replicated phenotypic data sets obtained from four test environments, and a 162 microsatellite marker-based linkage map constructed using 168 RILs of the cross 296B (susceptible) × IS18551 (resistant). Considering five component traits and four environments, a total of 29 QTL were detected by multiple QTL mapping (MQM) viz., four each for leaf glossiness and seedling vigor, seven for oviposition, six for deadhearts, two for adaxial trichome density and six for abaxial trichome density. The LOD and R ² (%) values of QTL ranged from 2.6 to 15.0 and 5.0 to 33%, respectively. For most of the QTL, IS18551 contributed resistance alleles; however, at six QTL, alleles from 296B also contributed to resistance. QTL of the related component traits were co-localized, suggesting pleiotropy or tight linkage of genes. The new morphological marker Trit for trichome type was associated with the major QTL for component traits of resistance. Interestingly, QTL identified in this study correspond to QTL/genes for insect resistance at the syntenic maize genomic regions, suggesting the conservation of insect resistance loci between these crops. For majority of the QTL, possible candidate genes lie within or very near the ascribed confidence intervals in sorghum. Finally, the QTL identified in the study should provide a foundation for marker-assisted selection (MAS) programs for improving shoot fly resistance in sorghum.