Development of genic-microsatellite markers for sorghum staygreen QTL using a comparative genomic approach with rice

De novo identification and targeted sequencing of SSRs efficiently fingerprints Sorghum bicolor sub-population identity

Recent plant breeding studies of several species have demonstrated the utility of combining molecular assessments of genetic distance into trait-linked SNP genotyping during the development of parent lines to maximize yield gains due to heterosis. SSRs (Short Sequence Repeats) are the molecular marker of choice to determine genetic diversity, but the methods historically used to sequence them have been burdensome. The ability to analyze SSRs in a higher-throughput manner independent of laboratory conditions would increase their utility in molecular ecology, germplasm curation, and plant breeding programs worldwide. This project reports simple bioinformatics methods that can be used to generate genome-wide de novo SSRs in silico followed by targeted Next Generation Sequencing (NGS) validation of those that provide the most information about sub-population identity of a breeding line, which influences heterotic group selection. While these methods were optimized in sorghum [Sorghum bicolor (L.) Moench], they were developed to be applied to any species with a reference genome and high-coverage whole-genome sequencing data of individuals from the sub-populations to be characterized. An analysis of published sorghum genomes selected to represent its five main races (bicolor, caudatum, durra, kafir, and guinea; 75 accessions total) identified 130,120 SSR motifs. Average lengths were 23.8 bp and 95% were between 10 and 92 bp, making them suitable for NGS. Validation through targeted sequencing amplified 188 of 192 assayed SSR loci. Results highlighted the distinctness of accessions from the guinea sub-group margaritiferum from all other sorghum accessions, consistent with previous studies of nuclear and mitochondrial DNA. SSRs that efficiently fingerprinted margaritiferum individuals (Xgma1 -Xgma6) are presented. Developing similar fingerprints of other sub-populations (Xunr1 -Xunr182) was not possible due to the extensive admixture between them in the data set analyzed. In summary, these methods were able to fingerprint specific sub-populations when rates of admixture between them are low.

An integrated and comparative approach towards identification, characterization and functional annotation of candidate genes for drought tolerance in sorghum (Sorghum bicolor (L.) Moench)

BACKGROUND

Drought is the most disastrous abiotic stress that severely affects agricultural productivity worldwide. Understanding the biological basis of drought-regulated traits, requires identification and an in-depth characterization of genetic determinants using model organisms and high-throughput technologies. However, studies on drought tolerance have generally been limited to traditional candidate gene approach that targets only a single gene in a pathway that is related to a trait. In this study, we used sorghum, one of the model crops that is well adapted to arid regions, to mine genes and define determinants for drought tolerance using drought expression libraries and RNA-seq data.

RESULTS

We provide an integrated and comparative in silico candidate gene identification, characterization and annotation approach, with an emphasis on genes playing a prominent role in conferring drought tolerance in sorghum. A total of 470 non-redundant functionally annotated drought responsive genes (DRGs) were identified using experimental data from drought responses by employing pairwise sequence similarity searches, pathway and interpro-domain analysis, expression profiling and orthology relation. Comparison of the genomic locations between these genes and sorghum quantitative trait loci (QTLs) showed that 40% of these genes were co-localized with QTLs known for drought tolerance. The genome reannotation conducted using the Program to Assemble Spliced Alignment (PASA), resulted in 9.6% of existing single gene models being updated. In addition, 210 putative novel genes were identified using AUGUSTUS and PASA based analysis on expression dataset. Among these, 50% were single exonic, 69.5% represented drought responsive and 5.7% were complete gene structure models. Analysis of biochemical metabolism revealed 14 metabolic pathways that are related to drought tolerance and also had a strong biological network, among categories of genes involved. Identification of these pathways, signifies the interplay of biochemical reactions that make up the metabolic network, constituting fundamental interface for sorghum defence mechanism against drought stress.

CONCLUSIONS

This study suggests untapped natural variability in sorghum that could be used for developing drought tolerance. The data presented here, may be regarded as an initial reference point in functional and comparative genomics in the Gramineae family.

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.

The stay-green trait

Stay-green (sometimes staygreen) refers to the heritable delayed foliar senescence character in model and crop plant species. In a cosmetic stay-green, a lesion interferes with an early step in chlorophyll catabolism. The possible contribution of synthesis to chlorophyll turnover in cosmetic stay-greens is considered. In functional stay-greens, the transition from the carbon capture period to the nitrogen mobilization (senescence) phase of canopy development is delayed, and/or the senescence syndrome proceeds slowly. Yield and composition in high-carbon (C) crops such as cereals, and in high-nitrogen (N) species such as legumes, reflect the source-sink relationship with canopy C capture and N remobilization. Quantitative trait loci studies show that functional stay-green is a valuable trait for improving crop stress tolerance, and is associated with the domestication syndrome in cereals. Stay-green variants reveal how autumnal senescence and dormancy are coordinated in trees. The stay-green phenotype can be the result of alterations in hormone metabolism and signalling, particularly affecting networks involving cytokinins and ethylene. Members of the WRKY and NAC families, and an ever-expanding cast of additional senescence-associated transcription factors, are identifiable by mutations that result in stay-green. Empirical selection for functional stay-green has contributed to increasing crop yields, particularly where it is part of a strategy that also targets other traits such as sink capacity and environmental sensitivity and is associated with appropriate crop management methodology. The onset and progress of senescence are phenological metrics that show climate change sensitivity, indicating that understanding stay-green can contribute to the design of appropriate crop types for future environments.

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.

Assessment of genetic diversity in the sorghum reference set using EST-SSR markers

Selection and use of genetically diverse genotypes are key factors in any crop breeding program to develop cultivars with a broad genetic base. Molecular markers play a major role in selecting diverse genotypes. In the present study, a reference set representing a wide range of sorghum genetic diversity was screened with 40 EST-SSR markers to validate both the use of these markers for genetic structure analyses and the population structure of this set. Grouping of accessions is identical in distance-based and model-based clustering methods. Genotypes were grouped primarily based on race within the geographic origins. Accessions derived from the African continent contributed 88.6 % of alleles confirming the African origin of sorghum. In total, 360 alleles were detected in the reference set with an average of 9 alleles per marker. The average PIC value was 0.5230 with a range of 0.1379-0.9483. Sub-race, guinea margaritiferum (Gma) from West Africa formed a separate cluster in close proximity to wild accessions suggesting that the Gma group represents an independent domestication event. Guineas from India and Western Africa formed two distinct clusters. Accessions belongs to the kafir race formed the most homogeneous group as observed in earlier studies. This analysis suggests that the EST-SSR markers used in the present study have greater discriminating power than the genomic SSRs. Genetic variance within the subpopulations was very high (71.7 %) suggesting that the germplasm lines included in the set are more diverse. Thus, this reference set representing the global germplasm is an ideal material for the breeding community, serving as a community resource for trait-specific allele mining as well as genome-wide association mapping.

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

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

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

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

EST-SSR markers derived from an elite barley cultivar (Hordeum vulgare L. 'Morex'): polymorphism and genetic marker potential

Microsatellites or simple sequence repeats have become the markers of choice for marker-assisted selection because of their low template DNA requirement, high reproducibility, and high level of polymorphism. This study investigated a new set of barley (Hordeum vulgare L.) EST-derived SSR markers designed to target gene sequences expressed during grain development, as they are more likely to be important in determining grain quality. The EST sequences (HVSMEh and HVSMEi) were derived from cDNA libraries of the elite six-rowed cultivar Morex, made from spikes harvested at 5 to 45 days after pollination. Approximately half of the 110 SSR markers derived from the ESTs were polymorphic in a panel of 8 diverse barley genotypes, with PIC values between 0.19 and 0.79. Twenty of the new markers were mapped to chromosomal locations using 2 doubled haploid populations. To demonstrate marker potential, quantitative trait locus (QTL) analyses were carried out with phenotypic data on wort beta-glucan content and beta-glucanase activity, two traits with a long history of genetic studies. Most of the EST-SSR markers mapped to within 10 cM of the cellulose synthase (HvCesA) and cellulose synthase-like (HvCslF) genes, which provides highly informative functional markers for tracking these genes in breeding programs. It was also observed that on any given chromosome, the QTL for beta-glucan content and beta-glucanase activity were rarely coincident but tended to occur in adjacent intervals along chromosomal regions, which agreed with their independent genetic basis; the adjacent localization may be important for coordination of cell wall degradation during germination and malting.

Identification of quantitative trait loci for resistance to shoot fly in sorghum [Sorghum bicolor (L.) Moench]

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

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F(7) RILs of the cross 296B x IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1-9 QTLs for each trait. Individual QTL accounted for 5.2-50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.