Optimizing genotype by environment by management to maximize opportunities for maize productivity in North Eastern Australia.

The major objective of this experiment was to identify optimum plant population densities for different maize maturity groups depending on the environments’ potential and identify situations that reduce risk of crop failures while maximizing opportunities for better yield when weather conditions are good.

Large-scale characterization of drought pattern: a continent-wide modelling approach applied to the Australian wheatbelt – spatial and temporal trends

* Plant response to drought is complex, so that traits adapted to a specific drought type can confer disadvantage in another drought type. Understanding which type(s) of drought to target is of prime importance for crop improvement. * Modelling was used to quantify seasonal drought patterns for a check variety across the Australian wheatbelt, using 123 yr of weather data for representative locations and managements. Two other genotypes were used to simulate the impact of maturity on drought pattern. * Four major environment types summarized the variability in drought pattern over time and space. Severe stress beginning before flowering was common (44% of occurrences), with (24%) or without (20%) relief during grain filling. High variability occurred from year to year, differing with geographical region. With few exceptions, all four environment types occurred in most seasons, for each location, management system and genotype. * Applications of such environment characterization are proposed to assist breeding and research to focus on germplasm, traits and genes of interest for target environments. The method was applied at a continental scale to highly variable environments and could be extended to other crops, to other drought-prone regions around the world, and to quantify potential changes in drought patterns under future climates.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment. This fraction is result of undesirable genotype-by-environment interactions (GxE) and measured by the genetic correlation (rg) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of GxE over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels.

Modelling the effect of plant water use traits on yield and stay-green expression in sorghum

Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a ‘stay-green’ phenotype. In conclusion, we showed that breeding success remained highly probabilistic; maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.

Smoking behaviour modifies IL23r-associated disease risk in patients with Crohn's disease

Background and Aim The etiology of Crohn's disease (CD) implicates both genetic and environmental factors. Smoking behavior is one environmental risk factor to play a role in the development of CD. The study aimed to assess the contribution of the interleukin 23 receptor (IL23R) in determining disease susceptibility in two independent cohorts of CD, and to investigate the interactions between IL23R variants, smoking behavior, and CD-associated genes, NOD2 and ATG16L1. Methods Ten IL23R single-nucleotide polymorphisms (SNPs) were genotyped in 675 CD cases, and 1255 controls from Brisbane, Australia (dataset 1). Six of these SNPs were genotyped in 318 CD cases and 533 controls from Canterbury, New Zealand (dataset 2). Case–control analysis of genotype and allele frequencies, and haplotype analysis for all SNPs was conducted. Results We demonstrate a strong increased CD risk for smokers in both datasets (odds ratio 3.77, 95% confidence interval 2.88–4.94), and an additive interaction between IL23R SNPs and cigarette smoking. Ileal involvement was a consistent marker of strong SNP–CD association (P ≤ 0.001), while the lowest minor allele frequencies for location were found in those with colonic CD (L2). Three haplotype blocks were identified across the 10 IL23R SNPs conferring different risk of CD. Haplotypes conferred no further risk of CD when compared with single SNP analyses. Conclusion IL23R gene variants determine CD susceptibility in the Australian and New Zealand population, particularly ileal CD. A strong additive interaction exists between IL23R SNPs and smoking behavior resulting in a dramatic increase in disease risk depending upon specific genetic background.

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.

First report of Cotton leafroll dwarf virus in Thailand using a species-specific PCR validated with isolates from Brazil

Partial virus genome sequence with high nucleotide identity to Cotton leafroll dwarf virus (CLRDV) was identified from two cotton (Gossypium hirsutum) samples from Thailand displaying typical cotton leaf roll disease symptoms. We developed and validated a PCR assay for the detection of CLRDV isolates from Thailand and Brazil.

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.

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.

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.