Molecular biology support for barley improvement - North

The principal aim of this project was to improve the rate of genetic gain and selection efficiency in developing barley varieties for Queensland (QLD) and New South Wales (NSW). The use of molecular markers in the Barley Breeding Australia – Northern Node (BBA-North), which has expanded significantly over the course of the project, has successfully contributed to improvements in the adaptive breeding of elite malting and feed barley germplasm; the deployment of genetic resistance to diseases including leaf rust, net and spot form of net blotch (NFNB, SFNB), stem rust and Russian wheat aphid (RWA); the rate of development of varieties with multiple disease resistance; the rate of genetic gain for grain yield by fixing other important traits; and in selection for animal feed quality traits

Promoting Sensory Environments and Strategies for Tennessee Baptist Children\u27s Homes

This project served to promote sensory strategies among youth residents and their caregivers of a children\u27s home in Brentwood, Tennessee as well as use the lens of occupational therapy to design an on-campus multi-sensory room

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

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

Estimation of Seismic Loss Functions for Typical Steel Office Buildings

Drought is one of the most important abiotic stresses and severely affects global agricultural production. Root system architecture (RSA) is the key determinant of water acquisition under moisture stress, and therefore has utility in breeding for drought tolerance in sorghum. Various components of RSA are known to influence drought tolerance in sorghum without any negative impact on yield. The growth angle of nodal roots is an important target trait for improving drought tolerance. Genetic variation for nodal root angle has been reported in sorghum, and this has been associated with grain yield under drought stress. Rapid advances in sorghum genomics have led to the identification of various quantitative trait loci (QTL) governing RSA, but the accuracy and preciseness in identification of QTL is the major hindrance in development of drought-tolerant cultivars through genetic manipulation of root traits. Hence, the complex genetic control of RSA and the lack of a high-throughput phenotyping platform have hampered integration of selection for RSA in breeding programs. These limitations can be overcome by designing a robust phenotyping platform that can maximize heritability and repeatability of RSA. Inclusion of the extensive phenotyping information with the recently developed genomic resources of sorghum will lead to mining of alleles that govern RSA and tailor a cultivar harboring genes for RSA that improve sorghum production under drought stress. This chapter provides an overview of the latest developments in RSA research in sorghum and gives direction to future breeding strategies to enhance the genetic gain for root 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

Recent emergence of the wheat Lr34 multi-pathogen resistance: insights from haplotype analysis in wheat, rice, sorghum and Aegilops tauschii

Spontaneous sequence changes and the selection of beneficial mutations are driving forces of gene diversification and key factors of evolution. In highly dynamic co-evolutionary processes such as plant-pathogen interactions, the plant's ability to rapidly adapt to newly emerging pathogens is paramount. The hexaploid wheat gene Lr34, which encodes an ATP-binding cassette (ABC) transporter, confers durable field resistance against four fungal diseases. Despite its extensive use in breeding and agriculture, no increase in virulence towards Lr34 has been described over the last century. The wheat genepool contains two predominant Lr34 alleles of which only one confers disease resistance. The two alleles, located on chromosome 7DS, differ by only two exon-polymorphisms. Putatively functional homoeologs and orthologs of Lr34 are found on the B-genome of wheat and in rice and sorghum, but not in maize, barley and Brachypodium. In this study we present a detailed haplotype analysis of homoeologous and orthologous Lr34 genes in genetically and geographically diverse selections of wheat, rice and sorghum accessions. We found that the resistant Lr34 haplotype is unique to the wheat D-genome and is not found in the B-genome of wheat or in rice and sorghum. Furthermore, we only found the susceptible Lr34 allele in a set of 252 Ae. tauschii genotypes, the progenitor of the wheat D-genome. These data provide compelling evidence that the Lr34 multi-pathogen resistance is the result of recent gene diversification occurring after the formation of hexaploid wheat about 8,000years ag

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