Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time

Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.

Breeding crops for drought-affected environments and improved climate resilience

Breeding climate-resilient crops with improved levels of abiotic and biotic stress resistance as a response to climate change presents both opportunities and challenges. Applying the framework of the "breeder's equation," which is used to predict the response to selection for a breeding program cycle, we review methodologies and strategies that have been used to successfully breed crops with improved levels of drought resistance, where the target population of environments (TPEs) is a spatially and temporally heterogeneous mixture of drought-affected and favorable (water-sufficient) environments. Long-term improvement of temperate maize for the US corn belt is used as a case study and compared with progress for other crops and geographies. Integration of trait information across scales, from genomes to ecosystems, is needed to accurately predict yield outcomes for genotypes within the current and future TPEs. This will require transdisciplinary teams to explore, identify, and exploit novel opportunities to accelerate breeding program outcomes; both improved germplasm resources and improved products (cultivars, hybrids, clones, and populations) that outperform and replace the products in use by farmers, in combination with modified agronomic management strategies suited to their local environments.

WGNAM: whole-genome nested association mapping

A powerful QTL analysis method for nested association mapping populations is presented. Based on a one-stage multi-locus model, it provides accurate predictions of founder specific QTL effects. Nested association mapping (NAM) populations have been created to enable the identification of quantitative trait loci (QTL) in different genetic backgrounds. A whole-genome nested association mapping (WGNAM) method is presented to perform QTL analysis in NAM populations. The WGNAM method is an adaptation of the multi-parent whole genome average interval mapping approach where the crossing design is incorporated through the probability of inheriting founder alleles for every marker across the genome. Based on a linear mixed model, this method provides a one-stage analysis of raw phenotypic data, molecular markers, and crossing design. It simultaneously scans the whole-genome through an iterative process leading to a model with all the identified QTL while keeping the false positive rate low. The WGNAM approach was assessed through a simulation study, confirming to be a powerful and accurate method for QTL analysis for a NAM population. This novel method can also accommodate a multi-reference NAM (MR-NAM) population where donor parents are crossed with multiple reference parents to increase genetic diversity. Therefore, a demonstration is presented using a MR-NAM population for wheat (Triticum aestivum L.) to perform a QTL analysis for plant height. The strength and size of the putative QTL were summarized enhancing the understanding of the QTL effects depending on the parental origin. Compared to other methods, the proposed methodology based on a one-stage analysis provides greater power to detect QTL and increased accuracy in the estimation of their effects. The WGNAM method establishes the basis for accurate QTL mapping studies for NAM and MR-NAM populations.

Genome-wide association studies identify putative pleiotropic locus mediating drought tolerance in sorghum

Drought is a key constraint on plant productivity and threat to food security. Sorghum (Sorghum bicolor L. Moench), a global staple food and forage crop, is among the most drought-adapted cereal crops, but its adaptation is not yet well understood. This study aims to better understand the genetic basis of preflowering drought in sorghum and identify loci underlying variation in water use and yield components under drought. A panel of 219 diverse sorghum from West Africa was phenotyped for yield components and water use in an outdoor large-tube lysimeter system under well-watered (WW) versus a preflowering drought water-stressed (WS) treatment. The experimental system was validated based on characteristic drought response in international drought tolerant check genotypes and genome-wide association studies (GWAS) that mapped the major height locus at QHT7.1 and Dw3. GWAS further identified marker trait associations (MTAs) for drought-related traits (plant height, flowering time, forage biomass, grain weight, water use) that each explained 7-70% of phenotypic variance. Most MTAs for drought-related traits correspond to loci not previously reported, but some MTA for forage biomass and grain weight under WS co-localized with staygreen post-flowering drought tolerance loci (Stg3a and Stg4). A globally common allele at S7_50055849 is associated with several yield components under drought, suggesting that it tags a major pleiotropic variant controlling assimilate partitioning to grain versus vegetative biomass. The GWAS revealed oligogenic variants for drought tolerance in sorghum landraces, which could be used as trait predictive markers for improved drought adaptation.

Genetic dissection of maize plant architecture using a novel nested association mapping population

The leaf angle (LA), plant height (PH), and ear height (EH) are key plant architectural traits influencing maize (Zea mays L.) yield. However, their genetic determinants have not yet been well-characterized. Here, we developed a maize advanced backcross-nested association mapping population in Henan Agricultural University (HNAU-NAM1) comprised of 1,625 BC₁ F₄ /BC₂ F₄ lines. These were obtained by crossing a diverse set of 12 representative inbred lines with the common GEMS41 line, which were then genotyped using the MaizeSNP9.4K array. Genetic diversity and phenotypic distribution analyses showed considerable levels of genetic variation. We obtained 18-88 quantitative trait loci (QTLs) associated with LA, PH, and EH by using three complementary mapping methods, named as separate linkage mapping, joint linkage mapping, and genome-wide association studies. Our analyses enabled the identification of ten QTL hot-spot regions associated with the three traits, which were distributed on nine different chromosomes. We further selected 13 major QTLs that were simultaneously detected by three methods and deduced the candidate genes, of which eight were not reported before. The newly constructed HNAU-NAM1 population in this study will further broaden our insights into understanding of genetic regulation of plant architecture, thus will help to improve maize yield and provide an invaluable resource for maize functional genomics and breeding research.

Genetic control of leaf angle in sorghum and its effect on light interception

Developing sorghum genotypes adapted to different light environments requires understanding of a plant's ability to capture light, determined through leaf angle specifically. This study dissected the genetic basis of leaf angle in 3 year field trials at two sites, using a sorghum diversity panel (729 accessions). A wide range of variation in leaf angle with medium heritability was observed. Leaf angle explained 36% variation in canopy light extinction coefficient, highlighting the extent to which variation in leaf angle influences light interception at the whole-canopy level. This study also found that the sorghum races of Guinea and Durra consistently having the largest and smallest leaf angle, respectively, highlighting the potential role of leaf angle in adaptation to distinct environments. The genome-wide association study detected 33 quantitative trait loci (QTLs) associated with leaf angle. Strong synteny was observed with previously detected leaf angle QTLs in maize (70%) and rice (40%) within 10 cM, among which the overlap was significantly enriched according to χ2 tests, suggesting a highly consistent genetic control in grasses. A priori leaf angle candidate genes identified in maize and rice were found to be enriched within a 1-cM window around the sorghum leaf angle QTLs. Additionally, protein domain analysis identified the WD40 protein domain as being enriched within a 1-cM window around the QTLs. These outcomes show that there is sufficient heritability and natural variation in the angle of upper leaves in sorghum which may be exploited to change light interception and optimize crop canopies for different contexts.

Sorghum genetic, genomic, and breeding resources

Sorghum research has entered an exciting and fruitful era due to the genetic, genomic, and breeding resources that are now available to researchers and plant breeders. As the world faces the challenges of a rising population and a changing global climate, new agricultural solutions will need to be developed to address the food and fiber needs of the future. To that end, sorghum will be an invaluable crop species as it is a stress-resistant C₄ plant that is well adapted for semi-arid and arid regions. Sorghum has already remained as a staple food crop in many parts of Africa and Asia and is critically important for animal feed and niche culinary applications in other regions, such as the United States. In addition, sorghum has begun to be developed into a promising feedstock for forage and bioenergy production. Due to this increasing demand for sorghum and its potential to address these needs, the continuous development of powerful community resources is required. These resources include vast collections of sorghum germplasm, high-quality reference genome sequences, sorghum association panels for genome-wide association studies of traits involved in food and bioenergy production, mutant populations for rapid discovery of causative genes for phenotypes relevant to sorghum improvement, gene expression atlas, and online databases that integrate all resources and provide the sorghum community with tools that can be used in breeding and genomic studies. Used in tandem, these valuable resources will ensure that the rate, quality, and collaborative potential of ongoing sorghum improvement efforts is able to rival that of other major crops.

QTL mapping for bioenergy traits in sweet sorghum recombinant inbred lines

During the past decade, sweet sorghum (Sorghum bicolor Moench L.) has shown great potential for bioenergy production, especially biofuels. In this study, 223 recombinant inbred lines (RILs) derived from a cross between two sweet sorghum lines (Brandes × Wray) were evaluated in three trials. Single-nucleotide polymorphisms (SNPs) derived from genotyping by sequencing of 272 RILs were used to build a high-density genetic map comprising 3,767 SNPs spanning 1,368.83 cM. Multitrait multiple interval mapping (MT-MIM) was carried out to map quantitative trait loci (QTL) for eight bioenergy traits. A total of 33 QTLs were identified for flowering time, plant height, total soluble solids and sucrose (five QTLs each), fibers (four QTLs), and fresh biomass yield, juice extraction yield, and reducing sugars (three QTLs each). QTL hotspots were found on chromosomes 1, 3, 6, 9, and 10, in addition to other QTLs detected on chromosomes 4 and 8. We observed that 14 out of the 33 mapped QTLs were found in all three trials. Upon further development and validation in other crosses, the results provided by the present study have a great potential to be used in marker-assisted selection in sorghum breeding programs for biofuel production.

Joint analysis of days to flowering reveals independent temperate adaptations in maize

Domesticates are an excellent model for understanding biological consequences of rapid climate change. Maize (Zea mays ssp. mays) was domesticated from a tropical grass yet is widespread across temperate regions today. We investigate the biological basis of temperate adaptation in diverse structured nested association mapping (NAM) populations from China, Europe (Dent and Flint) and the United States as well as in the Ames inbred diversity panel, using days to flowering as a proxy. Using cross-population prediction, where high prediction accuracy derives from overall genomic relatedness, shared genetic architecture, and sufficient diversity in the training population, we identify patterns in predictive ability across the five populations. To identify the source of temperate adapted alleles in these populations, we predict top associated genome-wide association study (GWAS) identified loci in a Random Forest Classifier using independent temperate-tropical North American populations based on lines selected from Hapmap3 as predictors. We find that North American populations are well predicted (AUC equals 0.89 and 0.85 for Ames and USNAM, respectively), European populations somewhat well predicted (AUC equals 0.59 and 0.67 for the Dent and Flint panels, respectively) and that the Chinese population is not predicted well at all (AUC is 0.47), suggesting an independent adaptation process for early flowering in China. Multiple adaptations for the complex trait days to flowering in maize provide hope for similar natural systems under climate change.

Development of an Australian Bread Wheat Nested Association Mapping Population, a New Genetic Diversity Resource for Breeding under Dry and Hot Climates

Genetic diversity, knowledge of the genetic architecture of the traits of interest and efficient means of transferring the desired genetic diversity into the relevant genetic background are prerequisites for plant breeding. Exotic germplasm is a rich source of genetic diversity; however, they harbor undesirable traits that limit their suitability for modern agriculture. Nested association mapping (NAM) populations are valuable genetic resources that enable incorporation of genetic diversity, dissection of complex traits and providing germplasm to breeding programs. We developed the OzNAM by crossing and backcrossing 73 diverse exotic parents to two Australian elite varieties Gladius and Scout. The NAM parents were genotyped using the iSelect wheat 90K Infinium SNP array, and the progeny were genotyped using a custom targeted genotyping-by-sequencing assay based on molecular inversion probes designed to target 12,179 SNPs chosen from the iSelect wheat 90K Infinium SNP array of the parents. In total, 3535 BC1F4:6 RILs from 125 families with 21 to 76 lines per family were genotyped and we found 4964 polymorphic and multi-allelic haplotype markers that spanned the whole genome. A subset of 530 lines from 28 families were evaluated in multi-environment trials over three years. To demonstrate the utility of the population in QTL mapping, we chose to map QTL for maturity and plant height using the RTM-GWAS approach and we identified novel and known QTL for maturity and plant height.

Association mapping and genomic selection for sorghum adaptation to tropical soils of Brazil in a sorghum multiparental random mating population

A multiparental random mating population used in sorghum breeding is amenable for the detection of QTLs related to tropical soil adaptation, fine mapping of underlying genes and genomic selection approaches. Tropical soils where low phosphorus (P) and aluminum (Al) toxicity limit sorghum [Sorghum bicolor (L.) Moench] production are widespread in the developing world. We report on BRP13R, a multiparental random mating population (MP-RMP), which is commonly used in sorghum recurrent selection targeting tropical soil adaptation. Recombination dissipated much of BRP13R's likely original population structure and average linkage disequilibrium (LD) persisted up to 2.5 Mb, establishing BRP13R as a middle ground between biparental populations and sorghum association panels. Genome-wide association mapping (GWAS) identified conserved QTL from previous studies, such as for root morphology and grain yield under low-P, and indicated the importance of dominance in the genetic architecture of grain yield. By overlapping consensus QTL regions, we mapped two candidate P efficiency genes to a ~ 5 Mb region on chromosomes 6 (ALMT) and 9 (PHO2). Remarkably, we find that only 200 progeny genotyped with ~ 45,000 markers in BRP13R can lead to GWAS-based positional cloning of naturally rare, subpopulation-specific alleles, such as for SbMATE-conditioned Al tolerance. Genomic selection was found to be useful in such MP-RMP, particularly if markers in LD with major genes are fitted as fixed effects into GBLUP models accommodating dominance. Shifts in allele frequencies in progeny contrasting for grain yield indicated that intermediate to minor-effect genes on P efficiency, such as SbPSTOL1 genes, can be employed in pre-breeding via allele mining in the base population. Therefore, MP-RMPs such as BRP13R emerge as multipurpose resources for efficient gene discovery and deployment for breeding sorghum cultivars adapted to tropical soils.

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

Large-scale genome-wide association study reveals that drought-induced lodging in grain sorghum is associated with plant height and traits linked to carbon remobilisation

KEY MESSAGE

We detected 213 lodging QTLs and demonstrated that drought-induced stem lodging in grain sorghum is substantially associated with stay-green and plant height suggesting a critical role of carbon remobilisation. Sorghum is generally grown in water limited conditions and often lodges under post-anthesis drought, which reduces yield and quality. Due to its complexity, our understanding on the genetic control of lodging is very limited. We dissected the genetic architecture of lodging in grain sorghum through genome-wide association study (GWAS) on 2308 unique hybrids grown in 17 Australian sorghum trials over 3 years. The GWAS detected 213 QTLs, the majority of which showed a significant association with leaf senescence and plant height (72% and 71%, respectively). Only 16 lodging QTLs were not associated with either leaf senescence or plant height. The high incidence of multi-trait association for the lodging QTLs indicates that lodging in grain sorghum is mainly associated with plant height and traits linked to carbohydrate remobilisation. This result supported the selection for stay-green (delayed leaf senescence) to reduce lodging susceptibility, rather than selection for short stature and lodging resistance per se, which likely reduces yield. Additionally, our data suggested a protective effect of stay-green on weakening the association between lodging susceptibility and plant height. Our study also showed that lodging resistance might be improved by selection for stem composition but was unlikely to be improved by selection for classical resistance to stalk rots.

Genome-wide mapping and prediction of plant architecture in a sorghum nested association mapping population

Modifying plant architecture is often necessary for yield improvement and climate adaptation, but we lack understanding of the genotype-phenotype map for plant morphology in sorghum. Here, we use a nested association mapping (NAM) population that captures global allelic diversity of sorghum to characterize the genetics of leaf erectness, leaf width (at two stages), and stem diameter. Recombinant inbred lines (n = 2200) were phenotyped in multiple environments (35,200 observations) and joint linkage mapping was performed with ∼93,000 markers. Fifty-four QTL of small to large effect were identified for trait BLUPs (9-16 per trait) each explaining 0.4-4% of variation across the NAM population. While some of these QTL colocalize with sorghum homologs of grass genes (e.g., those involved in transcriptional regulation of hormone synthesis [rice SPINDLY] and transcriptional regulation of development [rice Ideal plant architecture1]), most QTL did not colocalize with an a priori candidate gene (92%). Genomic prediction accuracy was generally high in five-fold cross-validation (0.65-0.83), and varied from low to high in leave-one-family-out cross-validation (0.04-0.61). The findings provide a foundation to identify the molecular basis of architecture variation in sorghum and establish genomic-enabled breeding for improved plant architecture.

Species-Specific Duplication Event Associated with Elevated Levels of Nonstructural Carbohydrates in Sorghum bicolor

Simple sugars are the essential foundation to plant life, and thus, their production, utilization, and storage are highly regulated processes with many complex genetic controls. Despite their importance, many of the genetic and biochemical mechanisms remain unknown or uncharacterized. Sorghum, a highly productive, diverse C₄ grass important for both industrial and subsistence agricultural systems, has considerable phenotypic diversity in the accumulation of nonstructural sugars in the stem. We use this crop species to examine the genetic controls of high levels of sugar accumulation, identify genetic mechanisms for the accumulation of nonstructural sugars, and link carbon allocation with iron transport. We identify a species-specific tandem duplication event controlling sugar accumulation using genome-wide association analysis, characterize multiple allelic variants causing increased sugar content, and provide further evidence of a putative neofunctionalization event conferring adaptability in Sorghum bicolor. Comparative genomics indicate that this event is unique to sorghum which may further elucidate evolutionary mechanisms for adaptation and divergence within the Poaceae. Furthermore, the identification and characterization of this event was only possible with the continued advancement and improvement of the reference genome. The characterization of this region and the process in which it was discovered serve as a reminder that any reference genome is imperfect and is in need of continual improvement.

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.

Sorghum as a Novel Crop for Central Europe: Using a Broad Diversity Set to Dissect Temperate-Adaptation

Sorghum (Sorghum bicolor L. Moench) is a promising novel crop for Central Europe. However, enhancements in cold tolerance and early maturity are essential for a successful adaptation to cooler climates. We scored a broad sorghum diversity set (n = 338) for early chilling tolerance, high-latitude adaptation, and bioenergy related agronomical traits in multi-environment trials. Our results show a high phenotypic variation and medium to high heritabilities for most traits, indicating that a robust breeding progress is feasible. Several public accessions with a good adaptation to cooler climates were identified, which can serve as valuable base material for sorghum breeding in temperate areas. Genome-wide association studies reveal a polygenic (quantitative) character for most of the traits, confirming previous studies. Hence, for practical breeding, it will be difficult to conduct efficient marker-assisted selection for temperate-adaptation traits in genetically diverse material.

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

The Ethiopian plateau hosts thousands of durum wheat (Triticum turgidum subsp. durum) farmer varieties (FV) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping (NAM) population intercrossing fifty Ethiopian FVs with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (EtNAM) is composed of fifty interconnected bi-parental families, totalling 6280 recombinant inbred lines (RILs) that represent both a powerful quantitative trait loci (QTL) mapping tool, and a large pre-breeding panel. Here, we discuss the molecular and phenotypic diversity of the EtNAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms (SNPs) to characterize a subset of 1200 EtNAM RILs from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association (GWA) approach. EtNAM RILs showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FVs with the international durum wheat allele pool. EtNAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium (LD) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across EtNAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the EtNAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

Genome-wide association of barley plant growth under drought stress using a nested association mapping population

BACKGROUND

Barley (Hordeum vulgare L.) is the fourth most important cereal crop worldwide. Barley production is compromised by many abiotic stresses including drought. Wild barley is a valuable source of alleles that can improve adaptation of cultivated barley to drought stress.

RESULTS

In the present study, a nested association mapping population named HEB-25, consisting of 1420 BC₁S₃ lines that were developed by crossing 25 different wild barley accessions to the elite barley cultivar 'Barke', was evaluated under both control and drought-stressed conditions in the Australian Plant Phenomics Facility, University of Adelaide. Overall, 14 traits reflecting the performance of individual plants in each treatment were calculated from non-destructive imaging over time and destructive end-of-experiment measurements. For each trait, best linear unbiased estimators (BLUEs) were calculated and used for genome-wide association study (GWAS) analysis. Among the quantitative trait loci (QTL) identified for the 14 traits, many co-localise with known inflorescence and developmental genes. We identified a QTL on chromosome 4H where, under drought and control conditions, wild barley alleles increased biomass by 10 and 17% respectively compared to the Barke allele.

CONCLUSIONS

Across all traits, QTL which increased phenotypic values were identified, providing a wider range of genetic diversity for the improvement of drought tolerance in barley.

Breaking the curse of dimensionality to identify causal variants in Breeding 4

In the past, plant breeding has undergone three major transformations and is currently transitioning to a new technological phase, Breeding 4. This phase is characterized by the development of methods for biological design of plant varieties, including transformation and gene editing techniques directed toward causal loci. The application of such technologies will require to reliably estimate the effect of loci in plant genomes by avoiding the situation where the number of loci assayed (p) surpasses the number of plant genotypes (n). Here, we discuss approaches to avoid this curse of dimensionality (n ≪ p), which will involve analyzing intermediate phenotypes such as molecular traits and component traits related to plant morphology or physiology. Because these approaches will rely on novel data types such as DNA sequences and high-throughput phenotyping images, Breeding 4 will call for analyses that are complementary to traditional quantitative genetic studies, being based on machine learning techniques which make efficient use of sequence and image data. In this article, we will present some of these techniques and their application for prioritizing causal loci and developing improved varieties in Breeding 4.

Development of a Pedigreed Sorghum Mutant Library

Induced mutagenesis is a powerful approach to generate variations for elucidation of gene function and to create new traits for breeding. Here, we described a procedure to develop a pedigreed mutant library through chemical mutagenesis with ethylmethane sulfonate (EMS) treated seeds in sorghum and discussed its potential to generate new traits for sorghum improvement. Unlike random mutagenesis, a pedigreed mutant library, once properly established, can serve as a powerful resource to isolate and recover mutations of both agronomical and biological importance. With the development of affordable and high-throughput next-generation sequencing technologies, identification of causal mutations from a mutant library with a uniform genetic background becomes increasingly efficient and cost-effective. Fast causal gene discovery from mutant libraries combined with precise genome editing techniques will accelerate incorporation of new traits and revolutionize crop breeding.

On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics

Understanding the quantitative genetics of crops has been and will continue to be central to maintaining and improving global food security. We outline four stages that plant breeding either has already achieved or will probably soon achieve. Top-of-the-line breeding programs are currently in Breeding 3.0, where inexpensive, genome-wide data coupled with powerful algorithms allow us to start breeding on predicted instead of measured phenotypes. We focus on three major questions that must be answered to move from current Breeding 3.0 practices to Breeding 4.0: ( a) How do we adapt crops to better fit agricultural environments? ( b) What is the nature of the diversity upon which breeding can act? ( c) How do we deal with deleterious variants? Answering these questions and then translating them to actual gains for farmers will be a significant part of achieving global food security in the twenty-first century.

Genome-Wide Association Study Using Historical Breeding Populations Discovers Genomic Regions Involved in High-Quality Rice

Rice ( L.) is one of the most important staple food crops in the world; however, there has recently been a shift in consumer demand for higher grain quality. Therefore, understanding the genetic architecture of grain quality has become a key objective of rice breeding programs. Genome-wide association studies (GWAS) using large diversity panels have successfully identified genomic regions associated with complex traits in diverse crop species. Our main objective was to identify genomic regions associated with grain quality and to identify and characterize favorable haplotypes for selection. We used two locally adapted rice breeding populations and historical phenotypic data for three rice quality traits: yield after milling, percentage of head rice recovery, and percentage of chalky grain. We detected 22 putative quantitative trait loci (QTL) in the same genomic regions as starch synthesis, starch metabolism, and cell wall synthesis-related genes are found. Additionally, we found a genomic region on chromosome 6 in the population that was associated with all quality traits and we identified favorable haplotypes. Furthermore, this region is linked to the gene that codes for a starch branching enzyme I, which is implicated in starch granule formation. In , we also found two putative QTL linked to , , and . Our study provides an insight into the genetic basis of rice grain chalkiness, yield after milling, and head rice, identifying favorable haplotypes and molecular markers for selection in breeding programs.

Integrating modelling and phenotyping approaches to identify and screen complex traits: transpiration efficiency in cereals

Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plant and with the environment, and to identify traits of most relevance to the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to characterize traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their value in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding programme. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programmes for improving yield gains in target populations of environments.

High-biomass C4 grasses-Filling the yield gap

A significant increase in agricultural productivity will be required by 2050 to meet the needs of an expanding and rapidly developing world population, without allocating more land and water resources to agriculture, and despite slowing rates of grain yield improvement. This review examines the proposition that high-biomass C₄ grasses could help fill the yield gap. High-biomass C₄ grasses exhibit high yield due to C₄ photosynthesis, long growth duration, and efficient capture and utilization of light, water, and nutrients. These C₄ grasses exhibit high levels of drought tolerance during their long vegetative growth phase ideal for crops grown in water-limited regions of agricultural production. The stems of some high-biomass C₄ grasses can accumulate high levels of non-structural carbohydrates that could be engineered to enhance biomass yield and utility as feedstocks for animals and biofuels production. The regulatory pathway that delays flowering of high-biomass C₄ grasses in long days has been elucidated enabling production and deployment of hybrids. Crop and landscape-scale modeling predict that utilization of high-biomass C₄ grass crops on land and in regions where water resources limit grain crop yield could increase agricultural productivity.

Modelling spatial trends in sorghum breeding field trials using a two-dimensional P-spline mixed model

A flexible and user-friendly spatial method called SpATS performed comparably to more elaborate and trial-specific spatial models in a series of sorghum breeding trials. Adjustment for spatial trends in plant breeding field trials is essential for efficient evaluation and selection of genotypes. Current mixed model methods of spatial analysis are based on a multi-step modelling process where global and local trends are fitted after trying several candidate spatial models. This paper reports the application of a novel spatial method that accounts for all types of continuous field variation in a single modelling step by fitting a smooth surface. The method uses two-dimensional P-splines with anisotropic smoothing formulated in the mixed model framework, referred to as SpATS model. We applied this methodology to a series of large and partially replicated sorghum breeding trials. The new model was assessed in comparison with the more elaborate standard spatial models that use autoregressive correlation of residuals. The improvements in precision and the predictions of genotypic values produced by the SpATS model were equivalent to those obtained using the best fitting standard spatial models for each trial. One advantage of the approach with SpATS is that all patterns of spatial trend and genetic effects were modelled simultaneously by fitting a single model. Furthermore, we used a flexible model to adequately adjust for field trends. This strategy reduces potential parameter identification problems and simplifies the model selection process. Therefore, the new method should be considered as an efficient and easy-to-use alternative for routine analyses of plant breeding trials.

Genome-wide associations with flowering time in switchgrass using exome-capture sequencing data

Flowering time is a major determinant of biomass yield in switchgrass (Panicum virgatum), a perennial bioenergy crop, because later flowering allows for an extended period of vegetative growth and increased biomass production. A better understanding of the genetic regulation of flowering time in switchgrass will aid the development of switchgrass varieties with increased biomass yields, particularly at northern latitudes, where late-flowering but southern-adapted varieties have high winter mortality. We use genotypes derived from recently published exome-capture sequencing, which mitigates challenges related to the large, highly repetitive and polyploid switchgrass genome, to perform genome-wide association studies (GWAS) using flowering time data from a switchgrass association panel in an effort to characterize the genetic architecture and genes underlying flowering time regulation in switchgrass. We identify associations with flowering time at multiple loci, including in a homolog of FLOWERING LOCUS T and in a locus containing TIMELESS, a homolog of a key circadian regulator in animals. Our results suggest that flowering time variation in switchgrass is due to variation at many positions across the genome. The relationship of flowering time and geographic origin indicates likely roles for genes in the photoperiod and autonomous pathways in generating switchgrass flowering time variation.

A Genomic Resource for the Development, Improvement, and Exploitation of Sorghum for Bioenergy

With high productivity and stress tolerance, numerous grass genera of the Andropogoneae have emerged as candidates for bioenergy production. To optimize these candidates, research examining the genetic architecture of yield, carbon partitioning, and composition is required to advance breeding objectives. Significant progress has been made developing genetic and genomic resources for Andropogoneae, and advances in comparative and computational genomics have enabled research examining the genetic basis of photosynthesis, carbon partitioning, composition, and sink strength. To provide a pivotal resource aimed at developing a comparative understanding of key bioenergy traits in the Andropogoneae, we have established and characterized an association panel of 390 racially, geographically, and phenotypically diverse Sorghum bicolor accessions with 232,303 genetic markers. Sorghum bicolor was selected because of its genomic simplicity, phenotypic diversity, significant genomic tools, and its agricultural productivity and resilience. We have demonstrated the value of sorghum as a functional model for candidate gene discovery for bioenergy Andropogoneae by performing genome-wide association analysis for two contrasting phenotypes representing key components of structural and non-structural carbohydrates. We identified potential genes, including a cellulase enzyme and a vacuolar transporter, associated with increased non-structural carbohydrates that could lead to bioenergy sorghum improvement. Although our analysis identified genes with potentially clear functions, other candidates did not have assigned functions, suggesting novel molecular mechanisms for carbon partitioning traits. These results, combined with our characterization of phenotypic and genetic diversity and the public accessibility of each accession and genomic data, demonstrate the value of this resource and provide a foundation for future improvement of sorghum and related grasses for bioenergy production.

A Belated Green Revolution for Cannabis: Virtual Genetic Resources to Fast-Track Cultivar Development

Cannabis is a predominantly diecious phenotypically diverse domesticated genus with few if any extant natural populations. International narcotics conventions and associated legislation have constrained the establishment, characterization, and use of Cannabis genetic resource collections. This has resulted in the underutilization of genepool variability in cultivar development and has limited the inclusion of secondary genepools associated with genetic improvement strategies of the Green Revolution. The structured screening of ex situ germplasm and the exploitation of locally-adapted intraspecific traits is expected to facilitate the genetic improvement of Cannabis. However, limited attempts have been made to establish the full extent of genetic resources available for pre-breeding. We present a thorough critical review of Cannabis ex situ genetic resources, and discuss recommendations for conservation, pre-breeding characterization, and genetic analysis that will underpin future cultivar development. We consider East Asian germplasm to be a priority for conservation based on the prolonged historical cultivation of Cannabis in this region over a range of latitudes, along with the apparent high levels of genetic diversity and relatively low representation in published genetic resource collections. Seed cryopreservation could improve conservation by reducing hybridization and genetic drift that may occur during Cannabis germplasm regeneration. Given the unique legal status of Cannabis, we propose the establishment of a global virtual core collection based on the collation of consistent and comprehensive provenance meta-data and the adoption of high-throughput DNA sequencing technologies. This would enable representative core collections to be used for systematic phenotyping, and so underpin breeding strategies for the genetic improvement of Cannabis.

MAGIC populations in crops: current status and future prospects

MAGIC populations present novel challenges and opportunities in crops due to their complex pedigree structure. They offer great potential both for dissecting genomic structure and for improving breeding populations. The past decade has seen the rise of multiparental populations as a study design offering great advantages for genetic studies in plants. The genetic diversity of multiple parents, recombined over several generations, generates a genetic resource population with large phenotypic diversity suitable for high-resolution trait mapping. While there are many variations on the general design, this review focuses on populations where the parents have all been inter-mated, typically termed Multi-parent Advanced Generation Intercrosses (MAGIC). Such populations have already been created in model animals and plants, and are emerging in many crop species. However, there has been little consideration of the full range of factors which create novel challenges for design and analysis in these populations. We will present brief descriptions of large MAGIC crop studies currently in progress to motivate discussion of population construction, efficient experimental design, and genetic analysis in these populations. In addition, we will highlight some recent achievements and discuss the opportunities and advantages to exploit the unique structure of these resources post-QTL analysis for gene discovery.

Genetic architecture of variation in heading date among Asian rice accessions

BACKGROUND

Heading date, a crucial factor determining regional and seasonal adaptation in rice (Oryza sativa L.), has been a major selection target in breeding programs. Although considerable progress has been made in our understanding of the molecular regulation of heading date in rice during last two decades, the previously isolated genes and identified quantitative trait loci (QTLs) cannot fully explain the natural variation for heading date in diverse rice accessions.

RESULTS

To genetically dissect naturally occurring variation in rice heading date, we collected QTLs in advanced-backcross populations derived from multiple crosses of the japonica rice accession Koshihikari (as a common parental line) with 11 diverse rice accessions (5 indica, 3 aus, and 3 japonica) that originate from various regions of Asia. QTL analyses of over 14,000 backcrossed individuals revealed 255 QTLs distributed widely across the rice genome. Among the detected QTLs, 128 QTLs corresponded to genomic positions of heading date genes identified by previous studies, such as Hd1, Hd6, Hd3a, Ghd7, DTH8, and RFT1. The other 127 QTLs were detected in different chromosomal regions than heading date genes.

CONCLUSIONS

Our results indicate that advanced-backcross progeny allowed us to detect and confirm QTLs with relatively small additive effects, and the natural variation in rice heading date could result from combinations of large- and small-effect QTLs. We also found differences in the genetic architecture of heading date (flowering time) among maize, Arabidopsis, and rice.

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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1459-7) contains supplementary material, which is available to authorized users.

Two distinct classes of QTL determine rust resistance in sorghum

BACKGROUND

Agriculture is facing enormous challenges to feed a growing population in the face of rapidly evolving pests and pathogens. The rusts, in particular, are a major pathogen of cereal crops with the potential to cause large reductions in yield. Improving stable disease resistance is an on-going major and challenging focus for many plant breeding programs, due to the rapidly evolving nature of the pathogen. Sorghum is a major summer cereal crop that is also a host for a rust pathogen Puccinia purpurea, which occurs in almost all sorghum growing areas of the world, causing direct and indirect yield losses in sorghum worldwide, however knowledge about its genetic control is still limited. In order to further investigate this issue, QTL and association mapping methods were implemented to study rust resistance in three bi-parental populations and an association mapping set of elite breeding lines in different environments.

RESULTS

In total, 64 significant or highly significant QTL and 21 suggestive rust resistance QTL were identified representing 55 unique genomic regions. Comparisons across populations within the current study and with rust QTL identified previously in both sorghum and maize revealed a high degree of correspondence in QTL location. Negative phenotypic correlations were observed between rust, maturity and height, indicating a trend for both early maturing and shorter genotypes to be more susceptible to rust.

CONCLUSIONS

The significant amount of QTL co-location across traits, in addition to the consistency in the direction of QTL allele effects, has provided evidence to support pleiotropic QTL action across rust, height, maturity and stay-green, supporting the role of carbon stress in susceptibility to rust. Classical rust resistance QTL regions that did not co-locate with height, maturity or stay-green QTL were found to be significantly enriched for the defence-related NBS-encoding gene family, in contrast to the lack of defence-related gene enrichment in multi-trait effect rust resistance QTL. The distinction of disease resistance QTL hot-spots, enriched with defence-related gene families from QTL which impact on development and partitioning, provides plant breeders with knowledge which will allow for fast-tracking varieties with both durable pathogen resistance and appropriate adaptive traits.

Flowering time regulation in crops—what did we learn from Arabidopsis?

The change from vegetative to reproductive growth is a key developmental switch in flowering plants. In agriculture, flowering is a prerequisite for crop production whenever seeds or fruits are harvested. An intricate network with various (epi-) genetic regulators responding to environmental and endogenous triggers controls the timely onset of flowering. Changes in the expression of a single flowering time (FTi) regulator can suffice to drastically alter FTi. FTi regulation is of utmost importance for genetic improvement of crops. We summarize recent discoveries on FTi regulators in crop species emphasizing crop-specific genes lacking homologs in Arabidopsis thaliana. We highlight pleiotropic effects on agronomically important characters, impact on adaptation to new geographical/climate conditions and future perspectives for crop improvement.

Multiparental mapping of plant height and flowering time QTL in partially isogenic sorghum families

Sorghum varieties suitable for grain production at temperate latitudes show dwarfism and photoperiod insensitivity, both of which are controlled by a small number of loci with large effects. We studied the genetic control of plant height and flowering time in five sorghum families (A-E), each derived from a cross between a tropical line and a partially isogenic line carrying introgressions derived from a common, temperate-adapted donor. A total of 724 F2:3 lines were phenotyped in temperate and tropical environments for plant height and flowering time and scored at 9139 SNPs using genotyping-by-sequencing. Biparental mapping was compared with multiparental mapping in different subsets of families (AB, ABC, ABCD, and ABCDE) using both a GWAS approach, which fit each QTL as a single effect across all families, and using a joint linkage approach, which fit QTL effects as nested within families. GWAS using all families (ABCDE) performed best at the cloned Dw3 locus, whereas joint linkage using all families performed best at the cloned Ma1 locus. Both multiparental approaches yielded apparently synthetic associations due to genetic heterogeneity and were highly dependent on the subset of families used. Comparison of all mapping approaches suggests that a GA2-oxidase underlies Dw1, and that a mir172a gene underlies a Dw1-linked flowering time QTL.

Sorghum phytochrome B inhibits flowering in long days by activating expression of SbPRR37 and SbGHD7, repressors of SbEHD1, SbCN8 and SbCN12

Light signaling by phytochrome B in long days inhibits flowering in sorghum by increasing expression of the long day floral repressors PSEUDORESPONSE REGULATOR PROTEIN (SbPRR37, Ma1) and GRAIN NUMBER, PLANT HEIGHT AND HEADING DATE 7 (SbGHD7, Ma6). SbPRR37 and SbGHD7 RNA abundance peaks in the morning and in the evening of long days through coordinate regulation by light and output from the circadian clock. 58 M, a phytochrome B deficient (phyB-1, ma3^R) genotype, flowered ∼60 days earlier than 100 M (PHYB, Ma3) in long days and ∼11 days earlier in short days. Populations derived from 58 M (Ma1, ma3^R, Ma5, ma6) and R.07007 (Ma1, Ma3, ma5, Ma6) varied in flowering time due to QTL aligned to PHYB/phyB-1 (Ma3), Ma5, and GHD7/ghd7-1 (Ma6). PHYC was proposed as a candidate gene for Ma5 based on alignment and allelic variation. PHYB and Ma5 (PHYC) were epistatic to Ma1 and Ma6 and progeny recessive for either gene flowered early in long days. Light signaling mediated by PhyB was required for high expression of the floral repressors SbPRR37 and SbGHD7 during the evening of long days. In 100 M (PHYB) the floral activators SbEHD1, SbCN8 and SbCN12 were repressed in long days and de-repressed in short days. In 58 M (phyB-1) these genes were highly expressed in long and short days. Furthermore, SbCN15, the ortholog of rice Hd3a (FT), is expressed at low levels in 100 M but at high levels in 58 M (phyB-1) regardless of day length, indicating that PhyB regulation of SbCN15 expression may modify flowering time in a photoperiod-insensitive manner.

Quantitative trait loci for thermal time to flowering and photoperiod responsiveness discovered in summer annual-type Brassica napus L

Time of flowering is a key adaptive trait in plants and is conditioned by the interaction of genes and environmental cues including length of photoperiod, ambient temperature and vernalisation. Here we investigated the photoperiod responsiveness of summer annual-types of Brassica napus (rapeseed, canola). A population of 131 doubled haploid lines derived from a cross between European and Australian parents was evaluated for days to flowering, thermal time to flowering (measured in degree-days) and the number of leaf nodes at flowering in a compact and efficient glasshouse-based experiment with replicated short and long day treatments. All three traits were under strong genetic control with heritability estimates ranging from 0.85–0.93. There was a very strong photoperiod effect with flowering in the population accelerated by 765 degree-days in the long day versus short day treatments. However, there was a strong genetic correlation of line effects (0.91) between the long and short day treatments and relatively low genotype x treatment interaction indicating that photoperiod had a similar effect across the population. Bivariate analysis of thermal time to flowering in short and long days revealed three main effect quantitative trait loci (QTLs) that accounted for 57.7% of the variation in the population and no significant interaction QTLs. These results provided insight into the contrasting adaptations of Australian and European varieties. Both parents responded to photoperiod and their alleles shifted the population to earlier flowering under long days. In addition, segregation of QTLs in the population caused wide transgressive segregation in thermal time to flowering. Potential candidate flowering time homologues located near QTLs were identified with the aid of the Brassica rapa reference genome sequence. We discuss how these results will help to guide the breeding of summer annual types of B. napus adapted to new and changing environments.

A first step toward the development of a barley NAM population and its utilization to detect QTLs conferring leaf rust seedling resistance

We suggest multi-parental nested association mapping as a valuable innovation in barley genetics, which increases the power to map quantitative trait loci and assists in extending genetic diversity of the elite barley gene pool. Plant genetic resources are a key asset to further improve crop species. The nested association mapping (NAM) approach was introduced to identify favorable genes in multi-parental populations. Here, we report toward the development of the first explorative barley NAM population and demonstrate its usefulness in a study on mapping quantitative trait loci (QTLs) for leaf rust resistance. The NAM population HEB-5 was developed from crossing and backcrossing five exotic barley donors with the elite barley cultivar 'Barke,' resulting in 295 NAM lines in generation BC1S1. HEB-5 was genetically characterized with 1,536 barley SNPs. Across HEB-5 and within the NAM families, no deviation from the expected genotype and allele frequencies was detected. Genetic similarity between 'Barke' and the NAM families ranged from 78.6 to 83.1 %, confirming the backcrossing step during population development. To explore its usefulness, a screen for leaf rust (Puccinia hordei) seedling resistance was conducted. Resistance QTLs were mapped to six barley chromosomes, applying a mixed model genome-wide association study. In total, four leaf rust QTLs were detected across HEB-5 and four QTLs within family HEB-F23. Favorable exotic QTL alleles reduced leaf rust symptoms on two chromosomes by 33.3 and 36.2 %, respectively. The located QTLs may represent new resistance loci or correspond to new alleles of known resistance genes. We conclude that the exploratory population HEB-5 can be applied to mapping and utilizing exotic QTL alleles of agronomic importance. The NAM concept will foster the evaluation of the genetic diversity, which is present in our primary barley gene pool.

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits.

CONSTANS is a photoperiod regulated activator of flowering in sorghum

BACKGROUND

Sorghum genotypes used for grain production in temperate regions are photoperiod insensitive and flower early avoiding adverse environments during the reproductive phase. In contrast, energy sorghum hybrids are highly photoperiod sensitive with extended vegetative phases in long days, resulting in enhanced biomass accumulation. SbPRR37 and SbGHD7 contribute to photoperiod sensitivity in sorghum by repressing expression of SbEHD1 and FT-like genes, thereby delaying flowering in long days with minimal influence in short days (PNAS_108:16469-16474, 2011; Plant Genome_in press, 2014). The GIGANTEA (GI)-CONSTANS (CO)-FLOWERING LOCUS T (FT) pathway regulates flowering time in Arabidopsis and the grasses (J Exp Bot_62:2453-2463, 2011). In long day flowering plants, such as Arabidopsis and barley, CONSTANS activates FT expression and flowering in long days. In rice, a short day flowering plant, Hd1, the ortholog of CONSTANS, activates flowering in short days and represses flowering in long days.

RESULTS

Quantitative trait loci (QTL) that modify flowering time in sorghum were identified by screening Recombinant Inbred Lines (RILs) derived from BTx642 and Tx7000 in long days, short days, and under field conditions. Analysis of the flowering time QTL on SBI-10 revealed that BTx642 encodes a recessive CONSTANS allele containing a His106Tyr substitution in B-box 2 known to inactivate CONSTANS in Arabidopsis thaliana. Genetic analysis characterized sorghum CONSTANS as a floral activator that promotes flowering by inducing the expression of EARLY HEADING DATE 1 (SbEHD1) and sorghum orthologs of the maize FT genes ZCN8 (SbCN8) and ZCN12 (SbCN12). The floral repressor PSEUDORESPONSE REGULATOR PROTEIN 37 (PRR37) inhibits sorghum CONSTANS activity and flowering in long days.

CONCLUSION

Sorghum CONSTANS is an activator of flowering that is repressed post-transcriptionally in long days by the floral inhibitor PRR37, contributing to photoperiod sensitive flowering in Sorghum bicolor, a short day plant.

A MITE transposon insertion is associated with differential methylation at the maize flowering time QTL Vgt1

One of the major quantitative trait loci for flowering time in maize, the Vegetative to generative transition 1 (Vgt1) locus, corresponds to an upstream (70 kb) noncoding regulatory element of ZmRap2.7, a repressor of flowering. At Vgt1, a miniature transposon (MITE) insertion into a conserved noncoding sequence was previously found to be highly associated with early flowering in independent studies. Because cytosine methylation is known to be associated with transposons and to influence gene expression, we aimed to investigate how DNA methylation patterns in wild-type and mutant Vgt1 correlate with ZmRap2.7 expression. The methylation state at Vgt1 was assayed in leaf samples of maize inbred and F1 hybrid samples, and at the syntenic region in sorghum. The Vgt1-linked conserved noncoding sequence was very scarcely methylated both in maize and sorghum. However, in the early maize Vgt1 allele, the region immediately flanking the highly methylated MITE insertion was significantly more methylated and showed features of methylation spreading. Allele-specific expression assays revealed that the presence of the MITE and its heavy methylation appear to be linked to altered ZmRap2.7 transcription. Although not providing proof of causative connection, our results associate transposon-linked differential methylation with allelic state and gene expression at a major flowering time quantitative trait locus in maize.

Genetic mapping of quantitative trait loci underlying flowering time in chrysanthemum (Chrysanthemum morifolium)

Flowering time is an important trait in chrysanthemum, but its genetic basis remains poorly understood. An intra-specific mapping population bred from the cross between the autumn-flowering cultivar ‘Yuhualuoying’ and the summer-flowering ‘Aoyunhanxiao’ was used to determine the number and relative effect of QTL segregating for five measures of flowering time. From flowering time data recorded over two consecutive seasons, 35 additive QTL were detected, each explaining between 5.8% and 22.7% of the overall phenotypic variance. Of these, 13 were detected in both years. Nine genomic regions harboring QTL for at least two of the five traits were identified. Ten pairs of loci epistatically determined the flowering time, but their contribution to the overall phenotypic variance was less than for the additive QTL. The results suggest that flowering time in chrysanthemum is principally governed by main effect QTL but that epistasis also contributes to the genetic architecture of the trait, and the major QTL identified herein are useful in our ongoing efforts to streamline the improvement of chrysanthemum via the use of molecular methodology.

High-throughput genomics in sorghum: from whole-genome resequencing to a SNP screening array

With its small, diploid and completely sequenced genome, sorghum (Sorghum bicolor L. Moench) is highly amenable to genomics-based breeding approaches. Here, we describe the development and testing of a robust single-nucleotide polymorphism (SNP) array platform that enables polymorphism screening for genome-wide and trait-linked polymorphisms in genetically diverse S. bicolor populations. Whole-genome sequences with 6× to 12× coverage from five genetically diverse S. bicolor genotypes, including three sweet sorghums and two grain sorghums, were aligned to the sorghum reference genome. From over 1 million high-quality SNPs, we selected 2124 Infinium Type II SNPs that were informative in all six source genomes, gave an optimal Assay Design Tool (ADT) score, had allele frequencies of 50% in the six genotypes and were evenly spaced throughout the S. bicolor genome. Furthermore, by phenotype-based pool sequencing, we selected an additional 876 SNPs with a phenotypic association to early-stage chilling tolerance, a key trait for European sorghum breeding. The 3000 attempted bead types were used to populate half of a dual-species Illumina iSelect SNP array. The array was tested using 564 Sorghum spp. genotypes, including offspring from four unrelated recombinant inbred line (RIL) and F2 populations and a genetic diversity collection. A high call rate of over 80% enabled validation of 2620 robust and polymorphic sorghum SNPs, underlining the efficiency of the array development scheme for whole-genome SNP selection and screening, with diverse applications including genetic mapping, genome-wide association studies and genomic selection.