Decoding the sorghum methylome: understanding epigenetic contributions to agronomic traits

DNA methylation is a chromatin modification that plays an essential role in regulatinggene expression and genome stability and it is typically associated with gene silencingand heterochromatin. Owing to its heritability, alterations in the patterns of DNA methyla-tion have the potential to provide for epigenetic inheritance of traits. Contemporary epige-nomic technologies provide information beyond sequence variation and could supplyalternative sources of trait variation for improvement in crops such as sorghum. Yet, com-pared with other species such as maize and rice, the sorghum DNA methylome is farless well understood. The distribution of CG, CHG, and CHH methylation in the genomeis different compared with other species. CG and CHG methylation levels peak aroundcentromeric segments in the sorghum genome and are far more depleted in the genedense chromosome arms. The genes regulating DNA methylation in sorghum are also yetto be functionally characterised; better understanding of their identity and functional ana-lysis of DNA methylation machinery mutants in diverse genotypes will be important tobetter characterise the sorghum methylome. Here, we catalogue homologous genesencoding methylation regulatory enzymes in sorghum based on genes inArabidopsis,maize, and rice. Discovering variation in the methylome may uncover epialleles thatprovide extra information to explain trait variation and has the potential to be applied inepigenome-wide association studies or genomic prediction. DNA methylation can alsoimprove genome annotations and discover regulatory elements underlying traits. Thus,improving our knowledge of the sorghum methylome can enhance our understanding ofthe molecular basis of traits and may be useful to improve sorghum performance

Heterosis in locally adapted sorghum genotypes and potential of hybrids for increased productivity in contrasting environments in Ethiopia

Increased productivity in sorghum has been achieved in the developed world using hybrids. Despite their yield advantage, introduced hybrids have not been adopted in Ethiopia due to the lack of adaptive traits, their short plant stature and small grain size. This study was conducted to investigate hybrid performance and the magnitude of heterosis of locally adapted genotypes in addition to introduced hybrids in three contrasting environments in Ethiopia. In total, 139 hybrids, derived from introduced seed parents crossed with locally adapted genotypes and introduced R lines, were evaluated. Overall, the hybrids matured earlier than the adapted parents, but had higher grain yield, plant height, grain number and grain weight in all environments. The lowland adapted hybrids displayed a mean better parent heterosis (BPH) of 19%, equating to 1160 kg ha− 1 and a 29% mean increase in grain yield, in addition to increased plant height and grain weight, in comparison to the hybrids derived from the introduced R lines. The mean BPH for grain yield for the highland adapted hybrids was 16% in the highland and 52% in the intermediate environment equating to 698 kg ha− 1 and 2031 kg ha− 1, respectively, in addition to increased grain weight. The magnitude of heterosis observed for each hybrid group was related to the genetic distance between the parental lines. The majority of hybrids also showed superiority over the standard check varieties. In general, hybrids from locally adapted genotypes were superior in grain yield, plant height and grain weight compared to the high parents and introduced hybrids indicating the potential for hybrids to increase productivity while addressing farmers' required traits

A global resource for exploring and exploiting genetic variation in sorghum crop wild relatives

One response to mitigate the impact of climate change on agricultural systems is to develop new varieties that are tolerant to the new range of biotic and abiotic challenges this change causes. This requires access to novel variants of genes for complex adaptive traits. Crop wild relatives are a potentially valuable source of these genes however these materials are often difficult to work with and identifying valuable alleles is difficult without substantial investment in pre-breeding. In this study we describe the development of a nested association mapping population for sorghum using two cultivated grain sorghum reference parents and 9 wild and exotic sorghum accessions as donors. The donor parents come from the verticilliflorum, drummondii and margaritiferum taxa and were sampled from a range of environments across Africa. In total the resource of consists of 13 populations and a total of 1,224 lines. The population has been genotyped with DArT markers which produced 42,372 unique SNP markers covering the genome. We determine the utility of the resource for high resolution mapping of complex traits by demonstrating that the exotics contain unique alleles for some example adaptive trait loci and by using the population for GWAS. The resource should provide useful material for plant breeders attempting to deal with the challenges generated by climate change. This article is protected by copyright. All rights reserve

Maximizing value of genetic sequence data requires an enabling environment and urgency

Severe price spikes of the major grain commodities and rapid expansion of cultivated area in the past two decades are symptoms of a severely stressed global food supply. Scientific discovery and improved agricultural productivity are needed and are enabled by unencumbered access to, and use of, genetic sequence data. In the same way the world witnessed rapid development of vaccines for COVID-19, genetic sequence data afford enormous opportunities to improve crop production. In addition to an enabling regulatory environment that allowed for the sharing of genetic sequence data, robust funding fostered the rapid development of coronavirus diagnostics and COVID-19 vaccines. A similar level of commitment, collaboration, and cooperation is needed for agriculture

Genomic prediction of grain yield and drought-adaptation capacity in sorghum is enhanced by multi-trait analysis

Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorghum breeding for broad adaptation to a range of environments. Genomic prediction for these traits may be enhanced by joint multi-trait analysis. The objectives of this study were to assess the capacity of multi-trait models to improve genomic prediction of parental breeding values for grain yield and stay-green in sorghum by using information from correlated auxiliary traits, and to determine the combinations of traits that optimize predictive results in specific scenarios. The dataset included phenotypic performance of 2645 testcross hybrids across 26 environments as well as genomic and pedigree information on their female parental lines. The traits considered were grain yield (GY), stay-green (SG), plant height (PH), and flowering time (FT). We evaluated the improvement in predictive performance of multi-trait G-BLUP models relative to single-trait G-BLUP. The use of a blended kinship matrix exploiting pedigree and genomic information was also explored to optimize multi-trait predictions. Predictive ability for GY increased up to 16% when PH information on the training population was exploited through multi-trait genomic analysis. For SG prediction, full advantage from multi-trait G-BLUP was obtained only when GY information was also available on the predicted lines per se, with predictive ability improvements of up to 19%. Predictive ability, unbiasedness and accuracy of predictions from conventional multi-trait G-BLUP were further optimized by using a combined pedigree-genomic relationship matrix. Results of this study suggest that multi-trait genomic evaluation combining routinely measured traits may be used to improve prediction of crop productivity and drought adaptability in grain sorghum.EEA PergaminoFil: Velazco, Julio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Sección Forrajeras; Argentina. Wageningen University and Research . Biometris – Mathematical and Statistical Methods; HolandaFil: Jordan, David R. The University of Queensland. Hermitage Research Facility. Queensland Alliance for Agriculture and Food Innovation; AustraliaFil: Mace, Emma S. The University of Queensland. Hermitage Research Facility. Queensland Alliance for Agriculture and Food Innovation; Australia. Hermitage Research Facility. Department of Agriculture and Fisheries; AustraliaFil: Hunt, Colleen H. The University of Queensland. Hermitage Research Facility. Queensland Alliance for Agriculture and Food Innovation; Australia. Hermitage Research Facility. Department of Agriculture and Fisheries; AustraliaFil: Malosetti, Marcos. Wageningen University and Research . Biometris – Mathematical and Statistical Methods; HolandaFil: Eeuwijk, Fred A. van. Wageningen University and Research . Biometris – Mathematical and Statistical Methods; Holand

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 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

Isolation and characterization of novel microsatellite markers and their application for diversity assessment in cultivated groundnut (Arachis hypogaea)

<p>Abstract</p> <p>Background</p> <p>Cultivated peanut or groundnut (<it>Arachis hypogaea </it>L.) is the fourth most important oilseed crop in the world, grown mainly in tropical, subtropical and warm temperate climates. Due to its origin through a single and recent polyploidization event, followed by successive selection during breeding efforts, cultivated groundnut has a limited genetic background. In such species, microsatellite or simple sequence repeat (SSR) markers are very informative and useful for breeding applications. The low level of polymorphism in cultivated germplasm, however, warrants a need of larger number of polymorphic microsatellite markers for cultivated groundnut.</p> <p>Results</p> <p>A microsatellite-enriched library was constructed from the genotype TMV2. Sequencing of 720 putative SSR-positive clones from a total of 3,072 provided 490 SSRs. 71.2% of these SSRs were perfect type, 13.1% were imperfect and 15.7% were compound. Among these SSRs, the GT/CA repeat motifs were the most common (37.6%) followed by GA/CT repeat motifs (25.9%). The primer pairs could be designed for a total of 170 SSRs and were optimized initially on two genotypes. 104 (61.2%) primer pairs yielded scorable amplicon and 46 (44.2%) primers showed polymorphism among 32 cultivated groundnut genotypes. The polymorphic SSR markers detected 2 to 5 alleles with an average of 2.44 per locus. The polymorphic information content (PIC) value for these markers varied from 0.12 to 0.75 with an average of 0.46. Based on 112 alleles obtained by 46 markers, a phenogram was constructed to understand the relationships among the 32 genotypes. Majority of the genotypes representing subspecies <it>hypogaea </it>were grouped together in one cluster, while the genotypes belonging to subspecies <it>fastigiata </it>were grouped mainly under two clusters.</p> <p>Conclusion</p> <p>Newly developed set of 104 markers extends the repertoire of SSR markers for cultivated groundnut. These markers showed a good level of PIC value in cultivated germplasm and therefore would be very useful for germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships in cultivated groundnut as well as related <it>Arachis </it>species.</p

Spot form of net blotch resistance in barley is under complex genetic control

Key message: Evaluation of resistance toPyrenophora teresf.maculatain barley breeding populations via association mapping revealed a complex genetic architecture comprising a mixture of major and minor effect genes. Abstract: In the search for stable resistance to spot form of net blotch (Pyrenophora teres f. maculata, SFNB), association mapping was conducted on four independent barley (Hordeum vulgare L.) breeding populations comprising a total of 898 unique elite breeding lines from the Northern Region Barley Breeding Program in Australia for discovery of quantitative trait loci (QTL) influencing resistance at seedling and adult plant growth stages. A total of 29 significant QTL were validated across multiple breeding populations, with 22 conferring resistance at both seedling and adult plant growth stages. The remaining 7 QTL conferred resistance at either seedling (2 QTL) or adult plant (5 QTL) growth stages only. These 29 QTL represented 24 unique genomic regions, of which five were found to co-locate with previously identified QTL for SFNB. The results indicated that SFNB resistance is controlled by a large number of QTL varying in effect size with large effects QTL on chromosome 7H. A large proportion of the QTL acted in the same direction for both seedling and adult responses, suggesting that phenotypic selection for SFNB resistance performed at either growth stage could achieve adequate levels of resistance. However, the accumulation of specific resistance alleles on several chromosomes must be considered in molecular breeding selection strategies

The Sorghum QTL Atlas: a powerful tool for trait dissection, comparative genomics and crop improvement

Key message: We describe the development and application of the Sorghum QTL Atlas, a high-resolution, open-access research platform to facilitate candidate gene identification across three cereal species, sorghum, maize and rice. Abstract: The mechanisms governing the genetic control of many quantitative traits are only poorly understood and have yet to be fully exploited. Over the last two decades, over a thousand QTL and GWAS studies have been published in the major cereal crops including sorghum, maize and rice. A large body of information has been generated on the genetic basis of quantitative traits, their genomic location, allelic effects and epistatic interactions. However, such QTL information has not been widely applied by cereal improvement programs and genetic researchers worldwide. In part this is due to the heterogeneous nature of QTL studies which leads QTL reliability variation from study to study. Using approaches to adjust the QTL confidence interval, this platform provides access to the most updated sorghum QTL information than any database available, spanning 23 years of research since 1995. The QTL database provides information on the predicted gene models underlying the QTL CI, across all sorghum genome assembly gene sets and maize and rice genome assemblies and also provides information on the diversity of the underlying genes and information on signatures of selection in sorghum. The resulting high-resolution, open-access research platform facilitates candidate gene identification across 3 cereal species, sorghum, maize and rice. Using a number of trait examples, we demonstrate the power and resolution of the resource to facilitate comparative genomics approaches to provide a bridge between genomics and applied breeding. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature

QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum