Abstract
An important challenge of crop improvement strategies is assigning function to paralogs in polyploid crops. Here we describe the circadian transcriptome in the polyploid crop Brassica rapa. Strikingly, almost three-quarters of the expressed genes exhibited circadian rhythmicity. Genetic redundancy resulting from whole genome duplication is thought to facilitate evolutionary change through sub- and neo-functionalization among paralogous gene pairs. We observed genome-wide expansion of the circadian expression phase among retained paralogous pairs. Using gene regulatory network models, we compared transcription factor targets between B. rapa and Arabidopsis circadian networks to reveal evidence for divergence between B. rapa paralogs that may be driven in part by variation in conserved non-coding sequences (CNS). Additionally, differential drought response among retained paralogous pairs suggests further functional diversification. These findings support the rapid expansion and divergence of the transcriptional network in a polyploid crop and offer a new approach for assessing paralog activity at the transcript level.
Highlights
The transition from basic research in Arabidopsis to new model systems for monocot and dicot crops has focused attention on the implications of polyploidy on our current models of genetic processes developed in Arabidopsis
Have these retained paralogs diversified in function and contributed to robustness and flexibility in the circadian clock? If the clock were essential for plant growth and coordinating responses with the environment, we would expect that the circadian regulation of the transcriptome would be impacted
We conducted a similar analysis to the BLAST comparison where we looked at the expression correlation of B. rapa Transcription Factors (TFs) vs. the orthologous Arabidopsis TF
Summary
Improving crop yield in rapidly changing climates depends on our ability to integrate these gene content expansions into functional classifications of physiological importance. This will rely on the growing collection of sequenced genomes, not just across crop species but of ecotypes within species, including complementary genomic datasets such as transcriptomes, methylomes, chromatin accessibility and metabolomic profiling. One difficulty in assigning new or overlapping functions among paralogs arises from heterogeneity in transcript abundance datasets generated under various environmental conditions, from various tissue types, and at distinct times of day. Many studies have explored the potential for functional divergence of duplicated genes by comparing expression levels normalized across a collection of expression studies [2,3,4,5] which limits the search to genes showing very dramatic differences in transcript abundance at a single time point
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