Genomic prediction applied to high-biomass sorghum for bioenergy production

The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesCπ, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs.     

An Induced Sorghum Mutant Population Suitable for Bioenergy Research

The sorghum [Sorghum bicolor (L.) Moench] inbred line BTx623 has served as a parent for development of several mapping populations, also providing a source for the generation of DNA libraries for physical mapping, and as the inbred line selected for sorghum genome sequencing. Since genetic mapping, physical mapping and genome sequencing are all based on the same inbred line, these genetic resources have made the genome study of sorghum very efficient. However, in comparison with other model species, there is one important genetic resource still missing in the sorghum research community, a mutant population. A systematically annotated mutant population will facilitate many avenues of research, especially those focusing on functional genomics and bioenergy research. Here we report the generation of a sorghum mutant population derived from the inbred line BTx623 by treatment with the chemical agent ethyl methanesulfonate (EMS). The mutant population consists of 1,600 pedigreed M₃ families; each of them was derived from an independent M₁ seed. Many lines displayed traits such as brown midrib (bmr), erect leaves (erl), multiple tillers (mtl), and late flowering (lfl), characteristics useful for bioenergy research. Results from our phenotyping and genotyping studies indicate that this mutant population will be a valuable and useful genetic resource for both sorghum functional genomics and bioenergy research.     

Classical phenotyping and deep learning concur on genetic control of stomatal density and area in sorghum

Stomatal density (SD) and stomatal complex area (SCA) are important traits that regulate gas exchange and abiotic stress response in plants. Despite sorghum (Sorghum bicolor) adaptation to arid conditions, the genetic potential of stomata-related traits remains unexplored due to challenges in available phenotyping methods. Hence, identifying loci that control stomatal traits is fundamental to designing strategies to breed sorghum with optimized stomatal regulation. We implemented both classical and deep learning methods to characterize genetic diversity in 311 grain sorghum accessions for stomatal traits at two different field environments. Nearly 12,000 images collected from abaxial (Ab) and adaxial (Ad) leaf surfaces revealed substantial variation in stomatal traits. Our study demonstrated significant accuracy between manual and deep learning methods in predicting SD and SCA. In sorghum, SD was 32%–39% greater on the Ab versus the Ad surface, while SCA on the Ab surface was 2%–5% smaller than on the Ad surface. Genome-Wide Association Study identified 71 genetic loci (38 were environment-specific) with significant genotype to phenotype associations for stomatal traits. Putative causal genes underlying the phenotypic variation were identified. Accessions with similar SCA but carrying contrasting haplotypes for SD were tested for stomatal conductance and carbon assimilation under field conditions. Our findings provide a foundation for further studies on the genetic and molecular mechanisms controlling stomata patterning and regulation in sorghum. An integrated physiological, deep learning, and genomic approach allowed us to unravel the genetic control of natural variation in stomata traits in sorghum, which can be applied to other plants.

High-throughput phenotyping using deep learning tools integrated with genome-wide association studies revealed genes that control SD and area in grain sorghum.     

Harnessing Genetic Variation in Leaf Angle to Increase Productivity of Sorghum bicolor

The efficiency with which a plant intercepts solar radiation is determined primarily by its architecture. Understanding the genetic regulation of plant architecture and how changes in architecture affect performance can be used to improve plant productivity. Leaf inclination angle, the angle at which a leaf emerges with respect to the stem, is a feature of plant architecture that influences how a plant canopy intercepts solar radiation. Here we identify extensive genetic variation for leaf inclination angle in the crop plant Sorghum bicolor, a C4 grass species used for the production of grain, forage, and bioenergy. Multiple genetic loci that regulate leaf inclination angle were identified in recombinant inbred line populations of grain and bioenergy sorghum. Alleles of sorghum dwarf-3, a gene encoding a P-glycoprotein involved in polar auxin transport, are shown to change leaf inclination angle by up to 34° (0.59 rad). The impact of heritable variation in leaf inclination angle on light interception in sorghum canopies was assessed using functional-structural plant models and field experiments. Smaller leaf inclination angles caused solar radiation to penetrate deeper into the canopy, and the resulting redistribution of light is predicted to increase the biomass yield potential of bioenergy sorghum by at least 3%. These results show that sorghum leaf angle is a heritable trait regulated by multiple loci and that genetic variation in leaf angle can be used to modify plant architecture to improve sorghum crop performance.     

Bioenergy grass feedstock: current options and prospects for trait improvement using emerging genetic, genomic, and systems biology toolkits

For lignocellulosic bioenergy to become a viable alternative to traditional energy production methods, rapid increases in conversion efficiency and biomass yield must be achieved. Increased productivity in bioenergy production can be achieved through concomitant gains in processing efficiency as well as genetic improvement of feedstock that have the potential for bioenergy production at an industrial scale. The purpose of this review is to explore the genetic and genomic resource landscape for the improvement of a specific bioenergy feedstock group, the C4 bioenergy grasses. First, bioenergy grass feedstock traits relevant to biochemical conversion are examined. Then we outline genetic resources available bioenergy grasses for mapping bioenergy traits to DNA markers and genes. This is followed by a discussion of genomic tools and how they can be applied to understanding bioenergy grass feedstock trait genetic mechanisms leading to further improvement opportunities.     

Setaria viridis: A Model for C4 Photosynthesis

C₄ photosynthesis drives productivity in several major food crops and bioenergy grasses, including maize (Zea mays), sugarcane (Saccharum officinarum), sorghum (Sorghum bicolor), Miscanthus x giganteus, and switchgrass (Panicum virgatum). Gains in productivity associated with C₄ photosynthesis include improved water and nitrogen use efficiencies. Thus, engineering C₄ traits into C₃ crops is an attractive target for crop improvement. However, the lack of a small, rapid cycling genetic model system to study C₄ photosynthesis has limited progress in dissecting the regulatory networks underlying the C₄ syndrome. Setaria viridis is a member of the Panicoideae clade and is a close relative of several major feed, fuel, and bioenergy grasses. It is a true diploid with a relatively small genome of ~510 Mb. Its short stature, simple growth requirements, and rapid life cycle will greatly facilitate genetic studies of the C₄ grasses. Importantly, S. viridis uses an NADP-malic enzyme subtype C₄ photosynthetic system to fix carbon and therefore is a potentially powerful model system for dissecting C₄ photosynthesis. Here, we summarize some of the recent advances that promise greatly to accelerate the use of S. viridis as a genetic system. These include our recent successful efforts at regenerating plants from seed callus, establishing a transient transformation system, and developing stable transformation.     

Applying genotyping (TILLING) and phenotyping analyses to elucidate gene function in a chemically induced sorghum mutant population

Background  

Sorghum [Sorghum bicolor (L.) Moench] is ranked as the fifth most important grain crop and serves as a major food staple and fodder resource for much of the world, especially in arid and semi-arid regions. The recent surge in sorghum research is driven by its tolerance to drought/heat stresses and its strong potential as a bioenergy feedstock. Completion of the sorghum genome sequence has opened new avenues for sorghum functional genomics. However, the availability of genetic resources, specifically mutant lines, is limited. Chemical mutagenesis of sorghum germplasm, followed by screening for mutants altered in important agronomic traits, represents a rapid and effective means of addressing this limitation. Induced mutations in novel genes of interest can be efficiently assessed using the technique known as Targeting Induced Local Lesion IN Genomes (TILLING).     

Detection and validation of stay-green QTL in post-rainy sorghum involving widely adapted cultivar,M35-1 and a popular stay-green genotype B35

Background

Sorghum [Sorghum bicolor (L.) Moench] is an important dry-land cereal of the world providing food, fodder, feed and fuel. Stay-green (delayed-leaf senescence) is a key attribute in sorghum determining its adaptation to terminal drought stress. The objective of this study was to validate sorghum stay-green quantitative trait loci (QTL) identified in the past, and to identify new QTL in the genetic background of a post-rainy adapted genotype M35-1.

Results

A genetic linkage map based on 245 F₉ Recombinant Inbred Lines (RILs) derived from a cross between M35-1 (more senescent) and B35 (less senescent) with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers was used. The phenotypic data collected for three consecutive post-rainy crop seasons on the RIL population (M35-1 × B35) was used for QTL analysis. Sixty-one QTL were identified for various measures of stay-green trait and each trait was controlled by one to ten QTL. The phenotypic variation explained by each QTL ranged from 3.8 to 18.7%. Co-localization of QTL for more than five traits was observed on two linkage groups i.e. on SBI-09-3 flanked by S18 and Xgap206 markers and, on SBI-03 flanked by XnhsbSFCILP67 and Xtxp31. QTL identified in this study were stable across environments and corresponded to sorghum stay-green and grain yield QTL reported previously. Of the 60 genic SSRs mapped, 14 were closely linked with QTL for ten traits. A genic marker, XnhsbSFCILP67 (Sb03g028240) encoding Indole-3-acetic acid-amido synthetase GH3.5, was co-located with QTL for GLB, GLM, PGLM and GLAM on SBI-03. Genes underlying key enzymes of chlorophyll metabolism were also found in the stay-green QTL regions.

Conclusions

We validated important stay-green QTL reported in the past in sorghum and detected new QTL influencing the stay-green related traits consistently. Stg2, Stg3 and StgB were prominent in their expression. Collectively, the QTL/markers identified are likely candidates for subsequent verification for their involvement in stay-green phenotype using NILs and to develop drought tolerant sorghum varieties through marker-assisted breeding for terminal drought tolerance in sorghum.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-909) contains supplementary material, which is available to authorized users.     

Yield Results and Stability Analysis from the Sorghum Regional Biomass Feedstock Trial

Sorghum [Sorghum bicolor (L.) Moench] is one of four herbaceous dedicated bioenergy crops the U.S. Department of Energy identified as critical to annually produce one billion tons of dry biomass. Of these four crops, sorghum is unique as it is a drought-tolerant, annual crop established from seed that is readily tractable to genetic improvement. The purpose of this study was to assess the yield potential and stability of sorghums grown across diverse production environments in the USA. For this study, six sorghum genotypes (one cultivar, five hybrids) were grown in yield trials in seven locations in six states for 5 years (2008–2012). Variation in dry and fresh yield was attributable to not only genotypes, but also to the effects of year, location, and year × location. Even with the highest yielding genotype, environmental conditions were a major factor in determining the yield in a given year. This variability affects the consistency of the biomass supply for ethanol production. In general, the southeastern USA had the highest mean yields for fresh weight and dry weight, indicating that this area may be the most reliable for biomass production. A significant variation was detected among genotypes for fresh weight, dry weight, moisture content, and brix, revealing that sufficient variation within sorghum exists for continued improvement and that certain hybrids are more tractable for biomass/bioenergy production. With dedicated bioenergy sorghum germplasm and proper production environments, sorghum will be a valuable tool in the goal of the sustainable production of one billion tons of dry biomass each year in the USA.     

Identification of bioconversion quantitative trait loci in the interspecific cross Sorghum bicolor × Sorghum propinquum

For lignocellulosic bioenergy to be economically viable, genetic improvements must be made in feedstock quality including both biomass total yield and conversion efficiency. Toward this goal, multiple studies have considered candidate genes and discovered quantitative trait loci (QTL) associated with total biomass accumulation and/or grain production in bioenergy grass species including maize and sorghum. However, very little research has been focused on genes associated with increased biomass conversion efficiency. In this study, Trichoderma viride fungal cellulase hydrolysis activity was measured for lignocellulosic biomass (leaf and stem tissue) obtained from individuals in a F₅ recombinant inbred Sorghum bicolor × Sorghum propinquum mapping population. A total of 49 QTLs (20 leaf, 29 stem) were associated with enzymatic conversion efficiency. Interestingly, six high-density QTL regions were identified in which four or more QTLs overlapped. In addition to enzymatic conversion efficiency QTLs, two QTLs were identified for biomass crystallinity index, a trait which has been shown to be inversely correlated with conversion efficiency in bioenergy grasses. The identification of these QTLs provides an important step toward identifying specific genes relevant to increasing conversion efficiency of bioenergy feedstocks. DNA markers linked to these QTLs could be useful in marker-assisted breeding programs aimed at increasing overall bioenergy yields concomitant with selection of high total biomass genotypes.     

Genetic and genomic resources of sorghum to connect genotype with phenotype in contrasting environments

With the recent development of genomic resources and high‐throughput phenotyping platforms, the 21st century is primed for major breakthroughs in the discovery, understanding and utilization of plant genetic variation. Significant advances in agriculture remain at the forefront to increase crop production and quality to satisfy the global food demand in a changing climate all while reducing the environmental impacts of the world's food production. Sorghum, a resilient C₄ grain and grass important for food and energy production, is being extensively dissected genetically and phenomically to help connect the relationship between genetic and phenotypic variation. Unlike genetically modified crops such as corn or soybean, sorghum improvement has relied heavily on public research; thus, many of the genetic resources serve a dual purpose for both academic and commercial pursuits. Genetic and genomic resources not only provide the foundation to identify and understand the genes underlying variation, but also serve as novel sources of genetic and phenotypic diversity in plant breeding programs. To better disseminate the collective information of this community, we discuss: (i) the genomic resources of sorghum that are at the disposal of the research community; (ii) the suite of sorghum traits as potential targets for increasing productivity in contrasting environments; and (iii) the prospective approaches and technologies that will help to dissect the genotype–phenotype relationship as well as those that will apply foundational knowledge for sorghum improvement.     

Identification of SSR markers associated with height using pool-based genome-wide association mapping in sorghum

Sorghum has been proposed as a potential energy crop. However, it has been traditionally bred for grain yield and forage quality, not traits related to bioenergy production. To develop tools for genetic improvement of bioenergy-related traits such as height, genetic markers associated with these traits have first to be identified. Association mapping has been extensively used in humans and in some crop plants for this purpose. However, genome-wide association mapping using the whole association panel is costly and time-consuming. A variation of this method called pool-based genome-wide association mapping has been extensively used in humans. In this variation, pools of individuals with contrasting phenotypes, instead of the whole panel, are screened with genetic markers and polymorphic markers are confirmed by screening the individuals in the pools. Here, we identified several new simple sequence repeats (SSR) markers associated with height using this pool-based genome-wide association mapping in sorghum. After screening the tall and short pools of sorghum accessions from the sorghum Mini Core collection developed at the International Crops Research Institute for the Semi-Arid Tropics with 703 SSR markers, we have identified four markers that are closely associated with sorghum height on chromosomes 2, 6, and 9. Comparison with published maps indicates that all four markers are clustered with markers previously mapped to height or height-related traits and with candidate genes involved in regulating plant height such as FtsZ, Ugt, and GA 2-oxidase. The mapping method can be applied to other crop plants for which a high-throughput genome-wide association mapping platform is not yet available.     

Soil and root populations of fluorescent Pseudomonas spp. associated with seedlings and field-grown plants are affected by sorghum genotype

Sorghum [Sorghum bicolor (L.) Moench] is valued for bioenergy, feed and food. Potential of sorghum genotypes to support differing populations of root- and soil-associated fluorescent Pseudomonas spp. or Fusarium spp., in two soils, was assessed. Culturable pseudomonads were enumerated from roots and soil of sorghum (Redlan and RTx433) and wheat (Lewjain) seedlings repeatedly grown in cycled soils in the growth chamber. Pseudomonads and Fusarium spp. were assessed from roots and soil of field-grown sorghum along with biological control traits hydrogen cyanide (HCN) and 2,4-diacetylphlorogluconol (phl) production. After four 4-week cycles, soil associated with Redlan seedlings had greater numbers of fluorescent pseudomonads than Lewjain. In dryland field conditions, RTx433 roots had greater numbers of pseudomonads than Redlan before anthesis but similar numbers after. There were no differences in numbers of pseudomonads from dryland soil or roots or soil of irrigated plants. Percentages of HCN-producing root isolates and phl soil isolates declined on irrigated Redlan plants, but percentages of HCN-producers increased in dryland conditions. Redlan roots had greater percentages of Fusarium isolates in the Gibberella fujikuroi complex. Results indicated that sorghum genotype affected root-associated populations of fluorescent Pseudomonas spp. and Fusarium spp. across soil environments.     

Evaluation of Public Sweet Sorghum A-Lines for Use in Hybrid Production

A fundamental need for commercialization of sweet sorghum [Sorghum bicolor (L.) Moench] as a bioenergy crop is an adequate seed supply, which will require development of hybrid varieties using dwarf seed-parent lines. A set of six public sweet sorghum A-lines (Dwarf Kansas Sourless, KS9, N36, N38, N39, and N4692) were crossed with a set of six public sweet sorghum cultivars (Brawley, Kansas Collier, Dale, Sugar Drip, Waconia, and Wray). Grain, fiber, and sugar yields were determined, and conversion formulas were applied to estimate ethanol yields. Hybrids were grown in fields at Ithaca, NE, USA, in 1983–1984 fertilized with 112 kg ha^?1 N. In terms of yield components and overall ethanol yields, one A-line, N38, was inferior. Average total ethanol yields from hybrids made on the other A-lines were not significantly different, suggesting that any of those five A-lines could be useful seed-parents. With the exception of grain yield, cultivars used as pollen parents were among the highest-performing entries for all traits. For all traits directly contributing to total ethanol yield (grain yield, juice yield, % soluble solids, sugar yield, fiber yield), hybrids were also among the highest-performing entries. Results of this study demonstrate that hybrid sweet sorghum with performance criteria equivalent to existing sweet sorghum cultivars can be produced on the sweet sorghum seed-parent lines A-Dwarf Kansas Sourless, A-KS9, A-N36, A-N39, and A-N4692. Identification of specific seed-parent × pollen parent lines with characteristics best suited for particular growing regions and end-user needs will be critical for commercial hybrid development.     

Maize and sorghum: genetic resources for bioenergy grasses

The highly photosynthetic-efficient C4 grasses, such as switchgrass (Panicum virgatum), Miscanthus (Miscanthusxgiganteus), sorghum (Sorghum bicolor) and maize (Zea mays), are expected to provide abundant and sustainable resources of lignocellulosic biomass for the production of biofuels. A deeper understanding of the synthesis, deposition and hydrolysis of the distinctive cell walls of grasses is crucial to gain genetic control of traits that contribute to biomass yield and quality. With a century of genetic investigations and breeding success, recently completed genome sequences, well-characterized cell wall compositions, and a close evolutionary relationship with future bioenergy perennial grasses, we propose that maize and sorghum are key model systems for gene discovery relating to biomass yield and quality in the bioenergy grasses.     

A Diploid,Interspecific, Fertile Hybrid from Cultivated Sorghum, <Emphasis Type="Italic">Sorghum Bicolor</Emphasis>, and the Common Johnsongrass Weed <Emphasis Type="Italic">Sorghum Halepense</Emphasis>

Valuable agronomic traits are often present but inaccessible in the wild relatives of cultivated crop species. Utilization of wild germplasm depends on the production of fertile interspecific hybrids. Several unsuccessful attempts have been made to hybridize cultivated sorghum with its wild relatives to broaden its genetic base and enhance agronomic value. The successful approach used in this study employed the nuclear male sterility gene ms3 to generate a diploid fertile hybrid between the diploid cultivated sorghum (Sorghum bicolor (L) Pers.) and its weedy tetraploid wild relative Johnsongrass (Sorghum halepense (L.) Pers.). Eight sorghum plants were selected from a Nebraska stiff stalk collection that contains the male sterility gene ms3 and were used as the female parent. About 36,000 florets of male sterile sorghum were pollinated with Johnsongrass pollen to produce an average of one well-developed and 180 severely shriveled seed/18,000 crosses. The well-developed seed gave rise to a self-fertile diploid, while none of the shriveled seed were able to germinate. The F₁ hybrid was confirmed by using cultivated sorghum SSR markers and was selfed to produce an F₂ population. A sub-sample of 96 segregating F₂ plants was examined with 36 sorghum polymorphic SSR markers. Thirty-four markers showed a normal 1:2:1 segregation ratio, evidence of normal recombination across the genome. Preliminary results showed that several desirable traits from Johnsongrass, including resistance to greenbug and chinch bug and adaptability to cold temperatures, were expressed in the resulting progenies. These observations suggest that speciation within the genus Sorghum, giving rise to widely divergent phenotypes, is effected largely by ploidy-maintained crossing barriers but apparently not by extensive genomic divergence.     

Retrospective genomic analysis of sorghum adaptation to temperate-zone grain production

Background

Sorghum is a tropical C₄ cereal that recently adapted to temperate latitudes and mechanized grain harvest through selection for dwarfism and photoperiod-insensitivity. Quantitative trait loci for these traits have been introgressed from a dwarf temperate donor into hundreds of diverse sorghum landraces to yield the Sorghum Conversion lines. Here, we report the first comprehensive genomic analysis of the molecular changes underlying this adaptation.

Results

We apply genotyping-by-sequencing to 1,160 Sorghum Conversion lines and their exotic progenitors, and map donor introgressions in each Sorghum Conversion line. Many Sorghum Conversion lines carry unexpected haplotypes not found in either presumed parent. Genome-wide mapping of introgression frequencies reveals three genomic regions necessary for temperate adaptation across all Sorghum Conversion lines, containing the Dw1, Dw2, and Dw3 loci on chromosomes 9, 6, and 7 respectively. Association mapping of plant height and flowering time in Sorghum Conversion lines detects significant associations in the Dw1 but not the Dw2 or Dw3 regions. Subpopulation-specific introgression mapping suggests that chromosome 6 contains at least four loci required for temperate adaptation in different sorghum genetic backgrounds. The Dw1 region fractionates into separate quantitative trait loci for plant height and flowering time.

Conclusions

Generating Sorghum Conversion lines has been accompanied by substantial unintended gene flow. Sorghum adaptation to temperate-zone grain production involves a small number of genomic regions, each containing multiple linked loci for plant height and flowering time. Further characterization of these loci will accelerate the adaptation of sorghum and related grasses to new production systems for food and fuel.     

Mapping QTL for grain yield and other agronomic traits in post-rainy sorghum [Sorghum bicolor (L.) Moench]

Sorghum, a cereal of economic importance ensures food and fodder security for millions of rural families in the semi-arid tropics. The objective of the present study was to identify and validate quantitative trait loci (QTL) for grain yield and other agronomic traits using replicated phenotypic data sets from three post-rainy dry sorghum crop seasons involving a mapping population with 245 F₉ recombinant inbred lines derived from a cross of M35-1 × B35. A genetic linkage map was constructed with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers. The QTL analysis for 11 traits following composite interval mapping identified 91 QTL with 5–12 QTL for each trait. QTL detected in the population individually explained phenotypic variation between 2.5 and 30.3 % for a given trait and six major genomic regions with QTL effect on multiple traits were identified. Stable QTL across seasons were identified. Of the 60 genic markers mapped, 21 were found at QTL peak or tightly linked with QTL. A gene-based marker XnhsbSFCILP67 (Sb03g028240) on SBI-03, encoding indole-3-acetic acid-amido synthetase GH3.5, was found to be involved in QTL for seven traits. The QTL-linked markers identified for 11 agronomic traits may assist in fine mapping, map-based gene isolation and also for improving post-rainy sorghum through marker-assisted breeding.     

Location of major effect genes in sorghum (Sorghum bicolor (L.) Moench)

Major effect genes are often used for germplasm identification, for diversity analyses and as selection targets in breeding. To date, only a few morphological characters have been mapped as major effect genes across a range of genetic linkage maps based on different types of molecular markers in sorghum (Sorghum bicolor (L.) Moench). This study aims to integrate all available previously mapped major effect genes onto a complete genome map, linked to the whole genome sequence, allowing sorghum breeders and researchers to link this information to QTL studies and to be aware of the consequences of selection for major genes. This provides new opportunities for breeders to take advantage of readily scorable morphological traits and to develop more effective breeding strategies. We also provide examples of the impact of selection for major effect genes on quantitative traits in sorghum. The concepts described in this paper have particular application to breeding programmes in developing countries where molecular markers are expensive or impossible to access.