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Biology subjects

Calderwood, A.

Publications and source records attributed to Calderwood, A..

3 recordsLinked to original sources

A Bayesian approach for identifying similar transcript dynamics using curve registration

Changes in gene expression over time can provide valuable insights into developmental processes and responses to the environment. Differences in expression may be indicative of potential differences in regulation. Comparing transcript dynamics may help identify correspondences between developmental stages within and between species, differences in the timing of key events during development, and transcriptional response to treatments or perturbations. A straightforward comparison between the dynamics is, however, hindered by measurements that were taken at different time points and over different timescales. To address this, we developed a statistical approach that seeks the optimal alignment between two time series as a function of a temporal shift and stretch. We validated our approach using simulated data and applied it to several transcriptome datasets, including comparisons between different plant species. Our development facilitates knowledge transfer from model systems to less studied species, the identification of modules of co-regulated genes, and the discovery of condition-specific, temporally differentially-expressed genes. The method is provided freely available as an R package.

bioinformatics↗

Bayesian optimisation for yield in high-dimensional trait-space identifies crop ideotypes in Oil Seed Rape

The improvement of crop yield has long been a major breeding target and is increasingly becoming a goal in many areas of plant research. Yield has been shown to be a complex trait, depending on multiple genes, plant architecture and plant-environment interactions. This complexity is frequently reduced by focussing on contributing factors to yield (yield traits). However, a quantitative understanding of the interplay between yield traits, and the effect of these relationships on yield is largely unexplored. Consequently, the extent to which crop varieties achieve their optimal morphology in a given environment and how this impacts on seed yield is unknown. Here we use causal inference to model the hierarchically structured effects of 27 macro and micro yield traits on each other over the course of plant development, and on seed yield in Spring and Winter oilseed rape plants. We perform Bayesian optimisation on the modelled yield potential, identifying the morphology of ideotype plants which are expected to be higher yielding than the existing varieties in the studied panels. We find that existing Spring varieties occupy the optimal regions of trait-space, but that potentially high yielding strategies are unexplored in extant Winter varieties. In addition to concrete recommendations for varietal improvement in oilseed rape, this work provides a novel, general methodological framework for the study of crop breeding as an optimisation problem.

plant biology↗

Comparative transcriptomics identifies differences in the regulation of the floral transition between Arabidopsis and Brassica rapa cultivars

The timing of the floral transition affects reproduction and yield, however its regulation in crops remains poorly understood. Here, we use RNA-Seq to determine and compare gene expression dynamics through the floral transition in the model species Arabidopsis thaliana and the closely related crop Brassica rapa. A direct comparison of gene expression over time between species shows little similarity, which could lead to the inference that different gene regulatory networks are at play. However, these differences can be largely resolved by synchronisation, through curve registration, of gene expression profiles. We find that different registration functions are required for different genes, indicating that there is no common developmental time to which Arabidopsis and B. rapa can be mapped through gene expression. Instead, the expression patterns of different genes progress at different rates. We find that co-regulated genes show similar changes in synchronisation between species, suggesting that similar gene regulatory sub-network structures may be active with different wiring between them. A detailed comparison of the regulation of the floral transition between Arabidopsis and B. rapa, and between two B. rapa accessions reveals different modes of regulation of the key floral integrator SOC1, and that the floral transition in the B. rapa accessions is triggered by different pathways, even when grown under the same environmental conditions. Our study adds to the mechanistic understanding of the regulatory network of flowering time in rapid cycling B. rapa under long days and highlights the importance of registration methods for the comparison of developmental gene expression data.

plant biology↗