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Macknight, R.

Publications and source records attributed to Macknight, R..

2 recordsLinked to original sources

Integrating molecular and physiological approaches to quantify genetic controls for wheat development and improve phenotyping

Disentangling genotype x environment (GxE) effects is critical to understand the performance of wheat across different environments. A framework for doing this was previously presented in a model that integrated knowledge of crop physiology and the Vrn gene feedback loop to explain and predict the time of anthesis. The aims of this study were: 1) provide an updated description of the Cereal Anthesis Molecular Phenology (CAMP) model; 2) to verify the models assumptions regarding the relationship between Vrn gene expression and the timing of phenological stages in a set of diverse genotypes and environments; 3) to use the CAMP model to establish a phenotyping strategy for use in genetic studies and model parameterisation. Six wheat genotypes with a range of cool temperature and photoperiod sensitivities were evaluated. Apical development, final leaf number (FLN) and temporal expression of Vrn1, Vrn2 and Vrn3 were compared with model predictions. There was a clear relationship between FLN responses to cool temperature and photoperiod, the timing of phenological events and the patterns of Vrn gene expression for all genotypes. There was general agreement between the temporal patterns of foliar gene expression observed with those assumed by CAMP, but some obvious discrepancies. These may be related to differences between gene expression in foliar (observed) and apical (assumed by the model) parts of the plant, or differences in the way observed and modelled gene expression are scaled. Overall, the model described all the observed development responses to environment and provides a basis for building quantitative predictions of field-based development from genotypic and environmental data. A protocol is presented for phenotyping wheat using FLN measured in specific combinations of temperature and photoperiod. It allows easy and unconfounded measure of key developmental phenotypes that clearly relate to the genetic make-up of the plants and underlying gene expression profiles.

plant biology↗

Identification of flowering-time genes in mast flowering plants using de novo transcriptomic analysis

Mast flowering is synchronised highly variable flowering by a population of perennial plants over a wide geographical area. High seeding years are seen as a threat to native and endangered species due to high predator density caused by the abundance of seed. An understanding of the molecular pathways that influence masting behaviour in plants could provide better prediction of a forthcoming masting season and enable conservation strategies to be deployed. In this study, a high-throughput large-scale RNA-sequencing was performed on two masting plant species, Celmisia lyallii (Asteraceae), and Chionochloa pallens (Poaceae) to develop a reference transcriptome for functional and molecular analysis. An average total of 33 million 150 base-paired reads, for both species, were assembled using the Trinity pipeline, resulting in 151,803 and 348,649 transcripts respectively for Celmisia and Chionochloa. The two datasets generated were blasted against the publicly available databases, TAIR, Swiss-Prot, non-redundant protein (nr), KEGG and COG for unigene annotations. On average, 56% of the unigenes were finally annotated with gene descriptions mapped to known protein sequences for both the species. Gene ontology analysis was then performed on the assembled reference transcriptomes, categorising the transcripts on the basis of putative biological processes, molecular function, and cellular localisation. A total of 543 transcripts from Celmisia and 470 transcripts from Chionochloa were also mapped to unique flowering-time proteins identified in Arabidopsis, suggesting the conservation of the flowering network in these wild alpine plants, growing in natural field conditions. These genes can further be analysed to understand the molecular regulation of the reproductive phase transition in the masting plants.

plant biology↗