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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - PHOTONET-C4 (Characterising the Gene Regulatory Networks Governing Photosynthesis: From Basic Understanding to Targeted Engineering)

Teaser

Summary

Photosynthesis is the primary energy source for life on earth. While the biochemistry and cell biology of photosynthesis are well understood, little is known of how the genes that mediate photosynthesis are regulated. Our research aims to address this knowledge gap by identifying the molecular regulators and mechanisms that control the expression of photosynthesis genes in the worldâ€™s most important food crops, the grasses. This work combines comparative genomics, evolutionary biology, high-throughput assays and genetic engineering.

Understanding and manipulating the gene regulatory network governing photosynthesis is one way in which engineer food and fuel crops for increased productivity. This may help contribute to future food security through enhanced sustainable agricultural production.

Work performed

The following is a list of the major results that have been achieved so far. The publications describing the result are listed after the result.

We discovered that photosynthetic nitrogen use efficiency directly influences the rate of gene and genome evolution
Kelly S: (2018) The amount of nitrogen used for photosynthesis modulates molecular evolution in plants. Molecular Biology and Evolution 35(7):1616-1625

We have developed a novel method for identifying lethal mutants through somatic hybridization
Moody LA, Kelly S, Coudert Y, Nimchuk ZL, Harrison CJ, Langdale JA (2018): Somatic hybridization provides segregating populations for the identification of causative mutations in sterile mutants of the moss Physcomitrella patens. New Phytologist 18(3):1270-1277

We have developed a novel computational method for analysing the trade-off between codon translational efficiency and codon biosynthetic cost and the impact this has on gene evolution
Seward EA, Kelly S (2018): Selection-driven cost-efficiency optimisation of transcripts modulates gene evolutionary rate in bacteria. Genome Biology 2018, 19:102.

We have developed a novel method for identifying optimal clusters of co-expressed genes
Abu-Jamous B, Kelly S: Clust (2018): automatic extraction of optimal co-expressed gene clusters from gene expression data. Genome Biology 2018, (in press).

We have discovered how plasmodesmata patterning varies between species that conduct C4 photosynthesis.
Danila FR, Quick WP, White RG, Kelly S, von Caemmerer S, Furbank RT (2018): Multiple mechanisms for enhanced plasmodesmata density in disparate subtypes of C4 grasses. Journal of experimental botany 2018. 69(5):1135-1145.

We have developed a novel computational method for analysing codon bias and optimising gene sequences for maximal protein expression.
Nascimento J, Kelly S, Sunter J, Carrington M (2018): Codon choice directs constitutive mRNA levels in trypanosomes. eLife e32467

We have developed a novel computational method for correcting gene model annotation errors
Dunne M, Kelly S: OMGene (2018): Mutual improvement of gene models through optimisation of evolutionary conservation. BMC Genomics 2018, 19(1):307

We have developed a novel computational method to identify missing genes in genome assemblies. This has allowed us to identify several transcription factor genes that were previously un-annotated in multiple grass genomes. (This is the completion of WP 1.1)
Dunne, M.P., Kelly, S. (2017) OrthoFiller: utilising data from multiple species to improve the completeness of genome annotations. BMC genomics 18:390.

We have mapped the evolution of all plant transcription factor gene families to enable cross-species identification of orthologous transcription factor genes.
Catarino, B., Hetherington, A.J., Emms, D.M., Kelly, S. Dolan, L. (2016) The stepwise increase in the number of transcription factor families in the Precambrian predated the diversification of plants on land. Molecular Biology and Evolution 33 (11): 2815-2819.

We have identified key transcription factor and transporter gene families that have been recruited to facilitate the partitioning of photosynthesis between two cell types in C4 species
Emms, D.M., Covshoff, S., Hibberd, J.M., and Kelly, S. (2016) Independent and parallel evolution of new genes by gene duplication in two origins of C4 photosynthesis provides new insight into the mechanism of phloem loading in C4 species. Molecular Biology and Evolution 33 (7): 1796-1806.

We have developed a novel computational method that allows us to improve our transcriptome assemblies and thus improve our analysis of transcription factor gene families in grass species lacking reference genomes
Smith Unna, R., Boursnell, C.R., Patro, R., Hibberd, J.M., and Kelly, S. (2016) TransRate: reference free quality assessment of de novo transcriptome assemblies. Genome Research 26: 1134-1144.

We have identified the key developmental stage in the rice leaf development where

Final results

We have delivered beyond the state of the art in multiple ways. For example our work on identifying missing genes in gene families has been generalized and released as a generic method for improving the genome annotation of any species.
Dunne, M.P., Kelly, S. (2017) OrthoFiller: utilising data from multiple species to improve the completeness of genome annotations. BMC genomics 18:390.

We have also generalised our method for improving gene model annotations
Dunne M, Kelly S: OMGene (2018): Mutual improvement of gene models through optimisation of evolutionary conservation. BMC Genomics 2018, 19(1):307

We have adapted our transcriptome analysis method to provide a general method that can be usses to assess any transcriptome.
Smith Unna, R., Boursnell, C.R., Patro, R., Hibberd, J.M., and Kelly, S. (2016) TransRate: reference free quality assessment of de novo transcriptome assemblies. Genome Research 26: 1134-1144.

Our search for transcription factors has lead to the unanticipated discovery of families of transporters that are potentially important for C4 photosynthetic function
Emms, D.M., Covshoff, S., Hibberd, J.M., and Kelly, S. (2016) Independent and parallel evolution of new genes by gene duplication in two origins of C4 photosynthesis provides new insight into the mechanism of phloem loading in C4 species. Molecular Biology and Evolution 33 (7): 1796-1806.

To further help go beyond the state of the art, we have authored two reviews that place our research program in the broader context of transcriptional control of photosynthesis and plant metabolic engineering. The first review provides a global overview of the successes and challenges in metabolic engineering in plants. This review pays particular attention to the successes that have been obtained from engineering expression of transcription factors to modulate biological production.
Oâ€™Neill, E., and Kelly, S. (2016) Engineering biosynthesis of high value compounds in photosynthetic organisms. Critical Reviews in Biotechnology 4: 1-24.
The second review places our understanding of the transcriptional regulation of photosynthesis in Arabidopsis thaliana in an evolutionary context, to provide new insight into transcriptional regulatory networks that control photosynthesis gene expression in grasses. This review reveals the striking differences between the grass and Arabidopsis networks and identifies avenues that may be exploited for engineering photosynthesis in the future.
Wang, P., Hendron, R.W., Kelly, S. (2017) Transcriptional control of photosynthetic capacity: Conservation and divergence from Arabidopsis to rice. New Phytologist 216 (1): 32-45.

We have used our genomic approaches to provide new insight into the origin and dispersal of the sweet potato
MuÃ±oz-RodrÃguez P, Carruthers T, Wood JRI, Williams BRM, Weitemier K, Kronmiller B, Ellis D, Anglin NL, Longway L, Harris SA, Rausher MD, Kelly S, Liston A, Scotland RW: (2018) Reconciling Conflicting Phylogenies in the Origin of Sweet Potato and Dispersal to Polynesia. Current Biology 28: 1246-1256.

We have discovered a novel gene that regulates the transition from 2D to 3D growth in plants.
Moody LA, Kelly S, Rabbinowitsch E, Langdale JA (2018): Genetic Regulation of the 2D to 3D Growth Transition in the Moss Physcomitrella patens. Current biology 2018, 28:473-478.