Classifying genotype by environment interactions for targeted germplasm deployment with a focus on Eucalyptus

A novel methodology for describing genotype by environment interactions estimated from multi-environment field trials is described and an empirical example using an extensive trial network of eucalypts is presented. The network of experiments containing 65 eucalypts was established in 38 replicated field trials across the tropics and subtropics of eastern Australia, with a selection of well-tested species used to provide a more detailed examination of productivity differentials across environmental gradients. By focusing on changes in species’ productivity across environmental gradients, the results are applicable for all species established across the range of environments evaluated in the trial network and simultaneously classify species and environments so that results may be applied across the landscape. The methodology developed was able to explain most (93 %) of the variation in the selected species relative changes in productivity across the various environmental variables examined. Responses were primarily regulated by changes in variables related to water availability and secondarily by temperature related variables. Clustering and ordination can identify groups of species with similar physiological responses to environment and may also guide the parameterisation and calibration of process based models of plant growth. Ordination was particularly useful in the identification of species with distinct environmental response patterns that would be useful as probes for extracting more information from future trials.

Development of a Rapid Multiplex PCR Assay To Genotype Pasteurella multocida Strains by Use of the Lipopolysaccharide Outer Core Biosynthesis Locus

Pasteurella multocida is a Gram-negative bacterial pathogen that is the causative agent of a wide range of diseases in many animal species, including humans. A widely used method for differentiation of P. multocida strains involves the Heddleston serotyping scheme. This scheme was developed in the early 1970s and classifies P. multocida strains into 16 somatic or lipopolysaccharide (LPS) serovars using an agar gel diffusion precipitin test. However, this gel diffusion assay is problematic, with difficulties reported in accuracy, reproducibility, and the sourcing of quality serovar-specific antisera. Using our knowledge of the genetics of LPS biosynthesis in P. multocida, we have developed a multiplex PCR (mPCR) that is able to differentiate strains based on the genetic organization of the LPS outer core biosynthesis loci. The accuracy of the LPS-mPCR was compared with classical Heddleston serotyping using LPS compositional data as the "gold standard." The LPS-mPCR correctly typed 57 of 58 isolates; Heddleston serotyping was able to correctly and unambiguously type only 20 of the 58 isolates. We conclude that our LPS-mPCR is a highly accurate LPS genotyping method that should replace the Heddleston serotyping scheme for the classification of P. multocida strains.

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.

Homologues of the maize rust resistance gene Rp1-D are genetically associated with a major rust resistance QTL in sorghum

As part of a comparative mapping study between sugarcane and sorghum, a sugarcane cDNA clone with homology to the maize Rp1-D rust resistance gene was mapped in sorghum. The cDNA probe hybridised to multiple loci, including one on sorghum linkage group (LG) E in a region where a major rust resistance QTL had been previously mapped. Partial sorghum Rp1-D homologues were isolated from genomic DNA of rust-resistant and -susceptible progeny selected from a sorghum mapping population. Sequencing of the Rp1-D homologues revealed five discrete sequence classes: three from resistant progeny and two from susceptible progeny. PCR primers specific to each sequence class were used to amplify products from the progeny and confirmed that the five sequence classes mapped to the same locus on LG E. Cluster analysis of these sorghum sequences and available sugarcane, maize and sorghum Rp1-D homologue sequences showed that the maize Rp1-D sequence and the partial sugarcane Rp1-D homologue were clustered with one of the sorghum resistant progeny sequence classes, while previously published sorghum Rp1-D homologue sequences clustered with the susceptible progeny sequence classes. Full-length sequence information was obtained for one member of a resistant progeny sequence class ( Rp1-SO) and compared with the maize Rp1-D sequence and a previously identified sorghum Rp1 homologue ( Rph1-2). There was considerable similarity between the two sorghum sequences and less similarity between the sorghum and maize sequences. These results suggest a conservation of function and gene sequence homology at the Rp1 loci of maize and sorghum and provide a basis for convenient PCR-based screening tools for putative rust resistance alleles in sorghum.

Selecting for increased barley grain size

In this study, 120–144 commercial varieties and breeding lines were assessed for grain size attributes including plump grain (>2.8 mm) and retention (>2.5 mm+>2.8 mm). Grain samples were produced from replicated trials at 25 sites across four years. Climatic conditions varied between years as well as between sites. Several of the trial sites were irrigated while the remaining were produced under dryland conditions. A number of the dryland sites suffered severe drought stress. The grain size data was analysed for genetic (G), environmental (E) and genotype by environment (G×E) interactions. All analyses included maturity as a covariate. The genetic effect on grain size was greater than environmental or maturity effects despite some sites suffering terminal moisture stress. The model was used to calculate heritability values for each site used in the study. These values ranged from 89 to 98% for plump grain and 88 to 96% for retention. The results demonstrated that removing the sources of non-heritable variation, such as maturity and field effects, can improve genetic estimates of the retention and plump grain fractions. By partitioning all variance components, and thereby having more robust estimates of genetic differences, plant breeders can have greater confidence in selecting barley genotypes which maintain large, stable grain size across a range of environments.

Measurement of genetic and environmental variation in barley (Hordeum vulgare) grain hardness

In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding populations that have large variation in barley grain hardness.

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

Background: Cultivated peanut or groundnut (Arachis hypogaea 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. Results: 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 hypogaea were grouped together in one cluster, while the genotypes belonging to subspecies fastigiata were grouped mainly under two clusters. Conclusion. 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 Arachis species.

Genetic control of propagation traits in a single Corymbia torelliana x Corymbia variegata family

Genetic control of vegetative propagation traits was described for a second-generation, outbred, intersectional hybrid family (N = 208) derived from two species, Corymbia torelliana (F. Muell.) K.D. Hill & L.A.S. Johnson and Corymbia variegata (F. Muell.) K.D. Hill & L.A.S. Johnson, which contrast for propagation characteristics and in their capacity to develop lignotubers. Large phenotypic variances were evident for rooting and most other propagation traits, with significant proportions attributable to differences between clones (broad-sense heritabilities 0.2-0.5). Bare root assessment of rooting rate and root quality parameters tended to have the highest heritabilities, whereas rooting percentage based on root emergence from pots and shoot production were intermediate. Root biomass and root initiation had the lowest heritabilities. Strong favourable genetic correlations were found between rooting percentage and root quality traits such as root biomass, volume, and length. Lignotuber development on a seedling was associated with low rooting and a tendency to poor root quality in cuttings and was in accord with the persistence of species parent types due to gametic phase disequilibrium. On average, nodal cuttings rooted more frequently and with higher quality root systems, but significant cutting type x genotype interaction indicated that for some clones, higher rooting rates were obtained from tips. Low germination, survival of seedlings, and rooting rates suggested strong hybrid breakdown in this family.

Crop and environmental attributes underpinning genotype by environment interaction in synthetic-derived bread wheat evaluated in Mexico and Australia

Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the north-west of Mexico (CIANO) and sites across Australia during 3 seasons. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. Previously, we have evaluated both the performance of genotypes across environments and the genotype x environment interaction (G x E). The objective of this study was to interpret the G x E for yield in terms of crop attributes measured at individual sites and to identify the potential environmental drivers of this interaction. Groups of SBWs with consistent yield performance were identified, often comprising closely related lines. However, contrasting performance was also relatively common among sister lines or between a recurrent parent and its SBWs. Early flowering was a common feature among lines with broad adaptation and/or high yield in the northern Australian wheatbelt, while yields in the southern region did not show any association with the maturity type. Lines with high yields in the southern and northern regions had cooler canopies during flowering and early grain filling. Among the SBWs with Australian genetic backgrounds, lines best adapted to CIANO were tall (>100 cm), with a slightly higher ground cover. These lines also displayed a higher concentration of water-soluble carbohydrates in the stem at flowering, which was negatively correlated with stem number per unit area when evaluated in southern Australia (Horsham). Possible reasons for these patterns are discussed. Selection for yield at CIANO did not specifically identify the lines best adapted to northern Australia, although they were not the most poorly adapted either. In addition, groups of lines with specific adaptation to the south would not have been selected by choosing the highest yielding lines at CIANO. These findings suggest that selection at CIMMYT for Australian environments may be improved by either trait based selection or yield data combined with trait information. Flowering date, canopy temperature around flowering, tiller density, and water-soluble carbohydrate concentration in the stem at flowering seem likely candidates.

Architectural modelling of maize under water stress

Two field experiments using maize (Pioneer 31H50) and three watering regimes [(i) irrigated for the whole crop cycle, until anthesis, (ii) not at all (experiment 1) and (iii) fully irrigated and rain grown for the whole crop cycle (experiment 2)] were conducted at Gatton, Australia, during the 2003-04 season. Data on crop ontogeny, leaf, sheath and internode lengths and leaf width, and senescence were collected at 1- to 3-day intervals. A glasshouse experiment during 2003 quantified the responses of leaf shape and leaf presentation to various levels of water stress. Data from experiment 1 were used to modify and parameterise an architectural model of maize (ADEL-Maize) to incorporate the impact of water stress on maize canopy characteristics. The modified model produced accurate fitted values for experiment 1 for final leaf area and plant height, but values during development for leaf area were lower than observed data. Crop duration was reasonably well fitted and differences between the fully irrigated and rain-grown crops were accurately predicted. Final representations of maize crop canopies were realistic. Possible explanations for low values of leaf area are provided. The model requires further development using data from the glasshouse study and before being validated using data from experiment 2 and other independent data. It will then be used to extend functionality in architectural models of maize. With further research and development, the model should be particularly useful in examining the response of maize production to water stress including improved prediction of total biomass and grain yield. This will facilitate improved simulation of plant growth and development processes allowing investigation of genotype by environment interactions under conditions of suboptimal water supply.

Field evaluation of 64 rootstocks for growth and yield of 'Kensington Pride' mango

Despite an abundance of polyembryonic genotypes and the need for rootstocks that improve scion yield and productivity, simultaneous field testing of a wide range of mango (Mangifera indica L.) genotypes as rootstocks has not previously been reported. In this experiment, we examined the growth and yield of 'Kensington Pride' on 64 mango genotypes of diverse origin during the first four seasons of fruit production to identify those worth longer-term assessment. We also recorded morphological characteristics of seedlings of 46 of these genotypes in an attempt to relate these measures to subsequent field performance. Tree canopy development on the most vigorous rootstocks was almost double that on the least vigorous. Growth rates differed by more than 160%. Cumulative marketable yield ranged from 36 kg/tree for the lowest yielding rootstock to 181 kg/tree for the most productive. Yield efficiency also differed markedly among the 64 rootstocks with the best treatment being 3.5 times more efficient than the poorest treatment. No relationship was found between yield efficiency and tree size, suggesting it is possible to select highly efficient rootstocks of differing vigor. Two genotypes ('Brodie' and 'MYP') stood out as providing high yield efficiency with small tree size. A further two genotypes ('B' and 'Watertank') were identified as offering high yield efficiency and large tree size and should provide high early yields at traditional tree spacing. Efforts to relate the morphology of different genotype seedlings to subsequent performance as a rootstock showed that nursery performance of mango seedlings is no indication of their likely behavior as a rootstock. The economic cost of poor yields and low yield efficiencies during the early years of commercial orchard production provide a rationale for culling many of the rootstock treatments in this experiment and concentrating future assessment on the top ~20% of the 64 treatments. Of these, 'MYP', 'B', 'Watertank', 'Manzano', and 'Pancho' currently show the most promise.

Using a supply chain approach to guide R&D

Consumers today are presented with an increasing array of products. The growing competition for consumer expenditure requires a whole of supply chain approach to maintain market share for existing cultivars and to successfully commercialise new cultivars. The supply chain needs to deliver value and satisfaction to the end customer and profitability to their members. Critical to getting the product right is developing inherent robustness into the cultivar, and developing processes and systems through the whole supply chain that maintain product quality and add value. This paper describes the approach we have used in working with supply chains in Australia and Indonesia to identify priority areas for improvement. Our experience demonstrates the need for a champion in the supply chain with significant influence and a desire to improve. The paper also describes our approach towards improving a specific supply chain to achieve successful commercialisation of a new cultivar. The cultivar was primarily selected for good production characteristics and attractive visual appeal. The performance of the fruit is being monitored from farm to retail shelf to identify points where quality is lost and practices can be improved. A targeted R&D program is investigating ways of improving production efficiency (nutrition, flowering and canopy management), maturity standards to optimise flavour, harvesting and packing practices to reduce skin damage, and ripening and handling practices to optimise shelf life. This integrated approach is based on similar approaches used to improve the performance of existing mango and avocado cultivars.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

ShadowBoxer and LocusEater: programs to optimise experimental design and multiplexing strategies for genetic mark-recapture

Genetic mark–recapture requires efficient methods of uniquely identifying individuals. 'Shadows' (individuals with the same genotype at the selected loci) become more likely with increasing sample size, and bias harvest rate estimates. Finding loci is costly, but better loci reduce analysis costs and improve power. Optimal microsatellite panels minimize shadows, but panel design is a complex optimization process. locuseater and shadowboxer permit power and cost analysis of this process and automate some aspects, by simulating the entire experiment from panel design to harvest rate estimation.