Empirical comparison of time series models and tensor product penalised splines for modelling spatial dependence in plant breeding field trials.

Plant breeding field trials are typically arranged as a row by column rectangular lattice. They have been widely analysed using linear mixed models in which low order autoregressive integrated moving average (ARIMA) time series models, and the subclass of separable lattice processes, are used to account for two-dimensional spatial dependence between the plot errors. A separable first order autoregressive model has been shown to be particularly useful in the analysis of plant breeding trials. Recently, tensor product penalised splines (TPS) have been proposed to model two-dimensional smooth variation in field trial data. This represents a non-stochastic smoothing approach which is in contrast to the autoregressive (AR) approach which models a stochastic covariance structure between the lattice of errors. This paper compares the AR and TPS methods empirically for a large set of early generation plant breeding trials. Here, the fitted models include information on genetic relatedness among the entries being evaluated. This provides a more relevant framework for comparison than the assumption of independent genetic effects. Judged by Akaike Information Criteria (AIC), the AR models were a better fit than the TPS model for more than 80% of trials. In the cases where the TPS model provided a better fit it did so by only a small amount whereas the AR models made a substantial improvement across a range of trials. When the AR and TPS models differ, there can be marked differences in the ranking of genotypes between the two methods of analysis based on their predicted genetic effects. Using the best fitting model for a trial as the benchmark, the rate of mis-classification of entries for selection was greater for the TPS model than the AR models. This has important practical implications for breeder selection decisions.

Meteorological and landscape influences on pollen beetle immigration into oilseed rape crops.

Heavy reliance on pesticide inputs to maintain crop yields has been an important aspect of agricultural intensification. Insecticide use has had detrimental impacts on pollinators and natural pest control agents, contributing to a decline in associated ecosystem services, and has also led to resistance development in pest populations. Throughout Europe, in oilseed rape (Brassica napus L.) crops, prophylactic use of insecticides against pollen beetles (Meligethes aeneus F. also known as Brassicogethes aeneus) has led to such issues, and there is an urgent need to develop more sustainable pest management practices for the crop. Although advice is available to oilseed rape growers regarding control thresholds, it may not be adhered to due to the expense of pollen beetle monitoring relative to the inexpensive cost of pyrethroid insecticides. Thus, the key to reducing prophylactic insecticide applications may lie with improved, less labour intensive methods of pollen beetle monitoring. For these to be realized, a better understanding is needed of the effects of agri-landscape features and meteorological conditions on pollen beetle immigration into the crop. In this study, based on data from four years of pollen beetle monitoring on a total of 41 field sites, we model the effects of meteorological (wind speed and direction, rainfall and accumulated temperature) and landscape (areas of woodland, residential gardens, the current and previous seasons' oilseed rape crops, and lengths of hedgerows and treelines) variables on directional sticky trap catches, at both the single trap and field scales. Meteorological variables, particularly accumulated temperature and wind speed were more important than landscape variables in predicting the abundance of pollen beetles immigrating into OSR fields. Sticky traps that were facing downwind caught more beetles than those that were facing across-wind or upwind; this is the first study to show at a landscape-scale, direct evidence for use of upwind anemotaxis by pollen beetles at the point of entry during immigration into the crop. At the field scale, the area of oilseed rape grown in the previous season was found to be positively related to trap catch, but no relationships with other landscape variables were found. Optimally-placed monitoring traps could complement existing decision support systems to reduce pollen beetle monitoring effort and encourage use of insecticides only when control thresholds are breached, thus enhancing the sustainability of oilseed rape production. Knowledge of the area of oilseed rape crops grown during the previous season in the surrounding landscape could contribute to risk assessment of potential pest pressure for individual OSR crops.

A hypomethylated population of Brassica rapa for forward and reverse epi-genetics.

BACKGROUND: Epigenetic marks superimposed on the DNA sequence of eukaryote chromosomes provide agility and plasticity in terms of modulating gene expression, ontology, and response to the environment. Modulating the methylation status of cytosine can generate epialleles, which have been detected and characterised at specific loci in several plant systems, and have the potential to generate novel and relatively stable phenotypes. There have been no systematic attempts to explore and utilise epiallelic variation, and so extend the range of phenotypes available for selection in crop improvement. We developed an approach for generating novel epialleles by perturbation of the DNA methylation status. 5- Azacytidine (5-AzaC) provides selective targeting of 5 mCG, which in plants is associated with exonic DNA. Targeted chemical intervention using 5-AzaC has advantages over transgenic or mutant modulation of methyltransferases, allowing stochastic generation of epialleles across the genome. RESULTS: We demonstrate the potential of stochastic chemically-induced hypomethylation to generate novel and valuable variation for crop improvement. Systematic analysis of dose-response to 5-AzaC in B. rapa guided generation of a selfed stochastically hypomethylated population, used for forward screening of several agronomic traits. Dose-response was sigmoidal for several traits, similar to that observed for chemical mutagens such as EMS. We demonstrated transgenerational inheritance of some phenotypes. BraRoAZ is a unique hypomethylated population of 1000 E2 sib lines. When compared to untreated controls, 5-Aza C-treated lines exhibited reduced immuno-staining of 5mC on pachytene chromosomes, and Methylation Sensitive Amplified Polymorphism (MSAP) profiles that were both divergent and more variable. There was coincident phenotypic variation among these lines for a range of seed yield and composition traits, including increased seed protein content and decreased oil content, as well as decreased erucic acid and corresponding increases in linoleic and/or palmitic acid. Each 5-AzaC-treated line represents a unique combination of hypomethylated epialleles. CONCLUSIONS: The approach and populations developed are available for forward and reverse screening of epiallelic variation and subsequent functional and inheritance studies. The generation of stochastically hypomethylated populations has utility in epiallele discovery for a wide range of crop plants, and has considerable potential as an intervention strategy for crop improvement.

Regulatory hotspots are associated with plant gene expression under varying soil phosphorus supply in Brassica rapa.

Gene expression is a quantitative trait that can be mapped genetically in structured populations to identify expression quantitative trait loci (eQTL). Genes and regulatory networks underlying complex traits can subsequently be inferred. Using a recently released genome sequence, we have defined cis- and trans-eQTL and their environmental response to low phosphorus (P) availability within a complex plant genome and found hotspots of trans-eQTL within the genome. Interval mapping, using P supply as a covariate, revealed 18,876 eQTL. trans-eQTL hotspots occurred on chromosomes A06 and A01 within Brassica rapa; these were enriched with P metabolism-related Gene Ontology terms (A06) as well as chloroplast- and photosynthesis-related terms (A01). We have also attributed heritability components to measures of gene expression across environments, allowing the identification of novel gene expression markers and gene expression changes associated with low P availability. Informative gene expression markers were used to map eQTL and P use efficiency-related QTL. Genes responsive to P supply had large environmental and heritable variance components. Regulatory loci and genes associated with P use efficiency identified through eQTL analysis are potential targets for further characterization and may have potential for crop improvement.

To bite or not to bite! A questionnaire-based survey assessing why some people are bitten more than others by midges.

BACKGROUND: The Scottish biting midge, Culicoides impunctatus, responsible for more than 90% of biting attacks on human beings in Scotland, is known to demonstrate a preference for certain human hosts over others. METHODS: In this study we used a questionnaire-based survey to assess the association between people's perception of how badly they get bitten by midges and their demographic, lifestyle and health related characteristics. RESULTS: Most people (85.8%) reported being bitten sometimes, often or always with only 14.2% reporting never being bitten by midges when in Scotland. There was no association between level of bites received and age, smoking, diet, exercise, medication, eating strongly flavoured foods or alcohol consumption. However, there was a strong association between the probability of being bitten and increasing height (in men) and BMI (in women). A large proportion of participants (33.8%) reported experiencing a bad/severe reaction to midge bites while 53.1% reported a minor reaction and 13.1% no reaction at all. Also, women tend to react more than men to midge bites. Additionally, the results indicated that the susceptibility to being bitten by midges is hereditary. CONCLUSIONS: This study suggests that midges prefer to bite men that are tall and women that have a large BMI, and that the tendency for a child to be bitten or not could be inherited from their parent. The study is questionnaire-based; therefore, the interpretation of the results may be limited by the subjectivity of the answers given by the respondents. Although the results are relevant only to the Scottish biting midge, the approach used here could be useful for investigating human-insect interactions for other insects, particularly those which transmit pathogens that cause disease.

A novel transcriptomic approach to identify candidate genes for grain quality traits in wheat.

A novel methodology is described in which transcriptomics is combined with the measurement of bread-making quality and other agronomic traits for wheat genotypes grown in different environments (wet and cool or hot and dry conditions) to identify transcripts associated with these traits. Seven doubled haploid lines from the Spark x Rialto mapping population were selected to be matched for development and known alleles affecting quality. These were grown in polytunnels with different environments applied 14 days post-anthesis, and the whole experiment was repeated over 2 years. Transcriptomics using the wheat Affymetrix chip was carried out on whole caryopsis samples at two stages during grain filling. Transcript abundance was correlated with the traits for approximately 400 transcripts. About 30 of these were selected as being of most interest, and markers were derived from them and mapped using the population. Expression was identified as being under cis control for 11 of these and under trans control for 18. These transcripts are candidates for involvement in the biological processes which underlie genotypic variation in these traits.

Transcriptome analysis of grain development in hexaploid wheat.

BACKGROUND: Hexaploid wheat is one of the most important cereal crops for human nutrition. Molecular understanding of the biology of the developing grain will assist the improvement of yield and quality traits for different environments. High quality transcriptomics is a powerful method to increase this understanding. RESULTS: The transcriptome of developing caryopses from hexaploid wheat (Triticum aestivum, cv. Hereward) was determined using Affymetrix wheat GeneChip oligonucleotide arrays which have probes for 55,052 transcripts. Of these, 14,550 showed significant differential regulation in the period between 6 and 42 days after anthesis (daa). Large changes in transcript abundance were observed which were categorised into distinct phases of differentiation (6-10 daa), grain fill (12-21 daa) and desiccation/maturation (28-42 daa) and were associated with specific tissues and processes. A similar experiment on developing caryopses grown with dry and/or hot environmental treatments was also analysed, using the profiles established in the first experiment to show that most environmental treatment effects on transcription were due to acceleration of development, but that a few transcripts were specifically affected. Transcript abundance profiles in both experiments for nine selected known and putative wheat transcription factors were independently confirmed by real time RT-PCR. These expression profiles confirm or extend our knowledge of the roles of the known transcription factors and suggest roles for the unknown ones. CONCLUSION: This transcriptome data will provide a valuable resource for molecular studies on wheat grain. It has been demonstrated how it can be used to distinguish general developmental shifts from specific effects of treatments on gene expression and to diagnose the probable tissue specificity and role of transcription factors.

The analysis of longitudinal data using mixed model L-splines.

L-splines are a large family of smoothing splines defined in terms of a linear differential operator. This article develops L-splines within the context of linear mixed models and uses the resulting mixed model L-spline to analyze longitudinal data from a grassland experiment. In the spirit of time-series analysis, a periodic mixed model L-spline is developed, which partitions data into a smooth periodic component plus smooth long-term trend.