Genetic differentiation analysis for the identification of complementary parental pools for sorghum hybrid breeding in Ethiopia

Key message The potential for exploiting heterosis for sorghum hybrid production in Ethiopia with improved local adaptation and farmers preferences has been investigated and populations suitable for initial hybrid development have been identified. Abstract Hybrids in sorghum have demonstrated increased productivity and stability of performance in the developed world. In Ethiopia, the uptake of hybrid sorghum has been limited to date, primarily due to poor adaptation and absence of farmer’s preferred traits in existing hybrids. This study aimed to identify complementary parental pools to develop locally adapted hybrids, through an analysis of whole genome variability of 184 locally adapted genotypes and introduced hybrid parents (R and B). Genetic variability was assessed using genetic distance, model-based STRUCTURE analysis and pair-wise comparison of groups. We observed a high degree of genetic similarity between the Ethiopian improved inbred genotypes and a subset of landraces adapted to lowland agro-ecology with the introduced R lines. This coupled with the genetic differentiation from existing B lines, indicated that these locally adapted genotype groups are expected to have similar patterns of heterotic expression as observed between introduced R and B line pools. Additionally, the hybrids derived from these locally adapted genotypes will have the benefit of containing farmers preferred traits. The groups most divergent from introduced B lines were the Ethiopian landraces adapted to highland and intermediate agro-ecologies and a subset of lowland-adapted genotypes, indicating the potential for increased heterotic response of their hybrids. However, these groups were also differentiated from the R lines, and hence are different from the existing complementary heterotic pools. This suggests that although these groups could provide highly divergent parental pools, further research is required to investigate the extent of heterosis and their hybrid performance.

Production attributes of Merino sheep genetically divergent for wool growth are reflected in differing rumen microbiotas

Divergent genetic selection for wool growth as a single trait has led to major changes in sheep physiology and metabolism, including variations in rumen microbial protein production and uptake of α-amino nitrogen in portal blood. This study was conducted to determine if sheep with different genetic merit for wool growth exhibit distinct rumen bacterial diversity. Eighteen Merino wethers were separated into groups of contrasting genetic merit for clean fleece weight (CFW; low: WG− and high: WG+) and fed a blend of oaten and lucerne chaff diet at two levels of intake (LOI; 1 or 1.5 times maintenance energy requirements) for two seven-week periods in a crossover design. Bacterial diversity in rumen fluid collected by esophageal intubation was characterized using 454 amplicon pyrosequencing of the V3/V4 regions of the 16S rRNA gene. Bacterial diversity estimated by Phylogenetic distance, Chao1 and observed species did not differ significantly with CFW or LOI; however, the Shannon diversity index differed (P=0.04) between WG+ (7.67) and WG− sheep (8.02). WG+ animals had a higher (P=0.03) proportion of Bacteroidetes (71.9% vs 66.5%) and a lower (P=0.04) proportion of Firmicutes (26.6% vs 31.6%) than WG− animals. Twenty-four specific operational taxonomic units (OTUs), belonging to the Firmicutes and Bacteroidetes phyla, were shared among all the samples, whereas specific OTUs varied significantly in presence/abundance (P<0.05) between wool genotypes and 50 varied (P<0.05) with LOI. It appears that genetic selection for fleece weight is associated with differences in rumen bacterial diversity that persist across different feeding levels. Moderate correlations between seven continuous traits, such as methane production or microbial protein production, and the presence and abundance of 17 OTUs were found, indicating scope for targeted modification of the microbiome to improve the energetic efficiency of rumen microbial synthesis and reduce the greenhouse gas footprint of ruminants.

Non-cellulosic cell wall polysaccharides are subject to genotype × environment effects in sorghum (Sorghum bicolor) grain

Sorghum is a staple food for half a billion people and, through growth on marginal land with minimal inputs, is an important source of feed, forage and increasingly, biofuel feedstock. Here we present information about non-cellulosic cell wall polysaccharides in a diverse set of cultivated and wild Sorghum bicolor grains. Sorghum grain contains predominantly starch (64–76) but is relatively deficient in other polysaccharides present in wheat, oats and barley. Despite overall low quantities, sorghum germplasm exhibited a remarkable range in polysaccharide amount and structure. Total (1,3;1,4)-β-glucan ranged from 0.06 to 0.43 (w/w) whilst internal cellotriose:cellotetraose ratios ranged from 1.8 to 2.9:1. Arabinoxylan amounts fell between 1.5 and 3.6 (w/w) and the arabinose:xylose ratio, denoting arabinoxylan structure, ranged from 0.95 to 1.35. The distribution of these and other cell wall polysaccharides varied across grain tissues as assessed by electron microscopy. When ten genotypes were tested across five environmental sites, genotype (G) was the dominant source of variation for both (1,3;1,4)-β-glucan and arabinoxylan content (69–74), with environment (E) responsible for 5–14. There was a small G × E effect for both polysaccharides. This study defines the amount and spatial distribution of polysaccharides and reveals a significant genetic influence on cell wall composition in sorghum grain.

Risk assessment for Puccinia psidii becoming established in South Africa

Puccinia psidii, the causal agent of myrtle rust, was first recorded from Latin America more than 100 years ago. It occurs on many native species of Myrtaceae in Latin America and also infects non-native plantation-grown Eucalyptus species in the region. The pathogen has gradually spread to new areas including Australia and most recently South Africa. The aim of this study was to consider the susceptibility of selected Eucalyptus genotypes, particularly those of interest to South African forestry, to infection by P. psidii. In addition, risk maps were compiled based on suitable climatic conditions and the occurrence of potential susceptible tree species. This made it possible to identify the season when P. psidii would be most likely to infect and to define the geographic areas where the rust disease would be most likely to establish in South Africa. As expected, variation in susceptibility was observed between eucalypt genotypes tested. Importantly, species commonly planted in South Africa show good potential for yielding disease-tolerant material for future planting. Myrtle rust is predicted to be more common in spring and summer. Coastal areas, as well as areas in South Africa with subtropical climates, are more conducive to outbreaks of the pathogen.

Frost trends and their estimated impact on yield in the Australian wheatbelt

Radiant spring frosts occurring during reproductive developmental stages can result in catastrophic yield loss for wheat producers. To better understand the spatial and temporal variability of frost, the occurrence and impact of frost events on rain-fed wheat production was estimated across the Australian wheatbelt for 1957–2013 using a 0.05 ° gridded weather data set. Simulated yield outcomes at 60 key locations were compared with those for virtual genotypes with different levels of frost tolerance. Over the last six decades, more frost events, later last frost day, and a significant increase in frost impact on yield were found in certain regions of the Australian wheatbelt, in particular in the South-East and West. Increasing trends in frost-related yield losses were simulated in regions where no significant trend of frost occurrence was observed, due to higher mean temperatures accelerating crop development and causing sensitive post-heading stages to occur earlier, during the frost risk period. Simulations indicated that with frost-tolerant lines the mean national yield could be improved by up to 20 through (i) reduced frost damage (~10 improvement) and (ii) the ability to use earlier sowing dates (adding a further 10 improvement). In the simulations, genotypes with an improved frost tolerance to temperatures 1 °C lower than the current 0 °C reference provided substantial benefit in most cropping regions, while greater tolerance (to 3 °C lower temperatures) brought further benefits in the East. The results indicate that breeding for improved reproductive frost tolerance should remain a priority for the Australian wheat industry, despite warming climates.

Characterization of maize growing environments in eastern and southern Africa using the APSIM model

Maize grown in eastern and southern Africa experiences random occurrences of drought. This uncertainty creates difficulty in developing superior varieties and their agronomy. Characterisation of drought types and their frequencies could help in better defining selection environments for improving resistance to drought. We used the well tested APSIM maize model to characterise major drought stress patterns and their frequencies across six countries of the region including Ethiopia, Kenya, Tanzania, Malawi, Mozambique and Zimbabwe. The database thus generated covered 35 sites, 17 to 86 years of daily climate records, 3 varieties and 3 planting densities from a total of 11,174 simulations. The analysis identified four major drought environment types including those characterised by low-stress which occurred in 42% of the years, mid-season drought occurring in 15% of the years, late-terminal stress which occurred in 22% of the years and early-terminal drought occurring in 21% of the years. These frequencies varied in relation to sites, genotypes and management. The simulations showed that early terminal stress could result in a yield reduction of 70% compared with low-stress environmental types. The study presents the importance of environmental characterization in contributing to maize improvement in eastern and southern Africa.

Genome-wide association analysis and differential expression analysis of resistance to Sclerotinia stem rot in Brassica napus

Brassica napus is one of the most important oil crops in the world, and stem rot caused by the fungus Sclerotinia sclerotiorum results in major losses in yield and quality. To elucidate resistance genes and pathogenesis-related genes, genome-wide association analysis of 347 accessions was performed using the Illumina 60K Brassica SNP (single nucleotide polymorphism) array. In addition, the detached stem inoculation assay was used to select five highly resistant (R) and susceptible (S) B. napus lines, 48 h postinoculation with S. sclerotiorum for transcriptome sequencing. We identified 17 significant associations for stem resistance on chromosomes A8 and C6, five of which were on A8 and 12 on C6. The SNPs identified on A8 were located in a 409-kb haplotype block, and those on C6 were consistent with previous QTL mapping efforts. Transcriptome analysis suggested that S. sclerotiorum infection activates the immune system, sulphur metabolism, especially glutathione (GSH) and glucosinolates in both R and S genotypes. Genes found to be specific to the R genotype related to the jasmonic acid pathway, lignin biosynthesis, defence response, signal transduction and encoding transcription factors. Twenty-four genes were identified in both the SNP-trait association and transcriptome sequencing analyses, including a tau class glutathione S-transferase (GSTU) gene cluster. This study provides useful insight into the molecular mechanisms underlying the plant's response to S. sclerotiorum.

Heat stress effects on grain sorghum productivity-biology and modelling

Heat stress can cause sterility in sorghum and the anticipated increased frequency of high temperature events implies increasing risk to sorghum productivity in Australia. Here we summarise our research on specific varietal attributes associated with heat stress tolerance in sorghum and evaluate how they might affect yield outcomes in production environments by a crop simulation analysis. We have recently conducted a range of controlled environment and field experiments to study the physiology and genetics of high temperature effects on growth and development of sorghum. Sorghum seed set was reduced by high temperature effects (>36-38oC) on pollen germination around flowering, but genotypes differed in their tolerance to high temperature stress. Effects were quantified in a manner that enabled their incorporation into the APSIM sorghum crop model. Simulation analysis indicated that risk of high temperature damage and yield loss depended on sowing date, and variety. While climate trends will exacerbate high temperature effects, avoidance by crop management and genetic tolerance seems possible.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

An improved simulation model to predict pre-harvest aflatoxin risk in maize

Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

Integrating Rapid Phenotyping and Speed Breeding to Improve Stay-Green and Root Adaptation of Wheat in Changing, Water-Limited, Australian Environments

Temperatures have increased and in-crop rainfall decreased over recent decades in many parts of the Australian wheat cropping region. With these trends set to continue or intensify, improving crop adaptation in the face of climate change is particularly urgent in this, already drought-prone, cropping region. Importantly, improved performance under water-limitation must be achieved while retaining yield potential during more favourable seasons. A multi-trait-based approach to improve wheat yield and yield stability in the face of water-limitation and heat has been instigated in northern Australia using novel phenotyping techniques and a nested association mapping (NAM) approach. An innovative laboratory technique allows rapid root trait screening of hundreds of lines. Using soil grown seedlings, the method offers significant advantages over many other lab-based techniques. Another recently developed method allows novel stay-green traits to be quantified objectively for hundreds of genotypes in standard field trial plots. Field trials in multiple locations and seasons allow evaluation of targeted trait values and identification of superior germplasm. Traits, including yield and yield components are measured for hundreds of NAM lines in rain fed environments under various levels of water-limitation. To rapidly generate lines of interest, the University of Queensland “speed breeding” method is being employed, allowing up to 7 plant generations per annum. A NAM population of over 1000 wheat recombinant inbred lines has been progressed to the F5 generation within 18 months. Genotyping the NAM lines with the genome-wide DArTseq molecular marker system provides up to 40,000 markers. They are now being used for association mapping to validate QTL previously identified in bi-parental populations and to identify novel QTL for stay-green and root traits. We believe that combining the latest techniques in physiology, phenotyping, genetics and breeding will increase genetic progress toward improved adaptation to water-limited environments.

New yellow head virus genotype (YHV7) in giant tiger shrimp Penaeus monodon indigenous to northern Australia

ABSTRACT: In 2012, giant tiger shrimp Penaeus monodon originally sourced from Joseph Bonaparte Gulf in northern Australia were examined in an attempt to identify the cause of elevated mortalities among broodstock at a Queensland hatchery. Nucleic acid extracted from ethanol-fixed gills of 3 individual shrimp tested positive using the OIE YHV Protocol 2 RT-PCR designed to differentiate yellow head virus (YHV1) from gill-associated virus (GAV, synonymous with YHV2) and the OIE YHV Protocol 3 RT-nested PCR designed for consensus detection of YHV genotypes. Sequence analysis of the 794 bp (Protocol 2) and 359 bp (Protocol 3) amplicons from 2 distinct regions of ORF1b showed that the yellow-head-complex virus detected was novel when compared with Genotypes 1 to 6. Nucleotide identity on the Protocol 2 and Protocol 3 ORF1b sequences was highest with the highly pathogenic YHV1 genotype (81 and 87%, respectively) that emerged in P. monodon in Thailand and lower with GAV (78 and 82%, respectively) that is enzootic to P. monodon inhabiting eastern Australia. Comparison of a longer (725 bp) ORF1b sequence, spanning the Protocol 3 region and amplified using a modified YH30/31 RT-nPCR, provided further phylogenetic evidence for the virus being distinct from the 6 described YHV genotypes. The virus represents a unique seventh YHV genotype (YHV7). Despite the mortalities observed, the role of YHV7 remains unknown.

Genomic regions influencing seminal root traits in barley

Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley (Hordeum vulgare L.). Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH) population (ND24260 × 'Flagship') comprising 330 lines genotyped with diversity array technology (DArT) markers were evaluated for seminal root angle (deviation from vertical) and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL) for seminal root traits (root angle, two QTL; root number, five QTL) were detected in the DH population. A major QTL influencing both root angle and root number (RAQ2/RNQ4) was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat (Triticum aestivum L.), and sorghum [Sorghum bicolor (L.) Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.

Highly heritable resistance to root-lesion nematode (Pratylenchus thornei) in Australian chickpea germplasm observed using an optimised glasshouse method and multi-environment trial analysis

Pratylenchus thornei is a root-lesion nematode (RLN) of economic significance in the grain growing regions of Australia. Chickpea (Cicer arietinum) is a significant legume crop grown throughout these regions, but previous testing found most cultivars were susceptible to P. thornei. Therefore, improved resistance to P. thornei is an important objective of the Australian chickpea breeding program. A glasshouse method was developed to assess resistance of chickpea lines to P. thornei, which requires relatively low labour and resource input, and hence is suited to routine adoption within a breeding program. Using this method, good differentiation of chickpea cultivars for P. thornei resistance was measured after 12 weeks. Nematode multiplication was higher for all genotypes than the unplanted control, but of the 47 cultivars and breeding lines tested, 17 exhibited partial resistance, allowing less than two fold multiplication. The relative differences in resistance identified using this method were highly heritable (0.69) and were validated against P. thornei data from seven field trials using a multi-environment trial analysis. Genetic correlations for cultivar resistance between the glasshouse and six of the field trials were high (>0.73). These results demonstrate that resistance to P. thornei in chickpea is highly heritable and can be effectively selected in a limited set of environments. The improved resistance found in a number of the newer chickpea cultivars tested shows that some advances have been made in the P. thornei resistance of Australian chickpea cultivars, and that further targeted breeding and selection should provide incremental improvements.