Dr Steve Kelly

<jats:title>Abstract</jats:title><jats:p>Orthobench is the standard benchmark to assess the accuracy of orthogroup inference methods. It contains 70 expert curated reference orthogroups (RefOGs) that span the Bilateria and cover a range of different challenges for orthogroup inference. Here we leveraged improvements in tree inference algorithms and computational resources to re-interrogate these RefOGs and carry out an extensive phylogenetic delineation of their composition. This phylogenetic revision altered the membership of 31 of the 70 RefOGs, with 24 subject to extensive revision and a further 7 that required minor changes. We further used these revised and updated RefOGs to provide an assessment of the orthogroup inference accuracy of widely used orthogroup inference methods. Finally, we provide an open-source benchmarking suite to support the future development and use of the Orthobench benchmark.</jats:p><jats:sec><jats:title>Significance statement</jats:title><jats:p>Orthogroup inference forms the foundation of comparative genomic analysis. Benchmarks to evaluate performance are essential to enable these methods to be compared and stimulate further method development. Here we present an update to the orthobench benchmark database and provide a comparative performance evaluation of commonly used orthogroup inference methods.</jats:p></jats:sec>

Investigating the evolution of plant biochemistry is challenging because few metabolites are preserved in fossils and because metabolic networks are difficult to experimentally characterize in diverse extant organisms. We report a comparative computational approach based on whole-genome metabolic pathway databases of eight species representative of major plant lineages, combined with homologous relationships among genes of 72 species from streptophyte algae to angiosperms. We use this genomic approach to identify metabolic gains and losses during land plant evolution. We extended our findings with additional analysis of 305 non-angiosperm plant transcriptomes. Our results revealed that genes encoding the complete biosynthetic pathway for brassinosteroid phytohormones and enzymes for brassinosteroid inactivation are present only in spermatophytes. Genes encoding only part of the biosynthesis pathway are present in ferns and lycophytes, indicating a stepwise evolutionary acquisition of this pathway. Nevertheless, brassinosteroids are ubiquitous in land plants, suggesting that brassinosteroid biosynthetic pathways differ between earlier- and later-diverging lineages. Conversely, genes for gibberellin biosynthesis and inactivation using methyltransferases are found in all land plant lineages. This suggests that bioactive gibberellins might be present in bryophytes, although they have yet to be detected experimentally. We also found that cytochrome P450 oxidases involved in cutin and suberin production are absent in genomes of non-angiosperm plants that nevertheless do contain these biopolymers. Overall, we identified significant differences in crucial metabolic processes between angiosperms and earlier-diverging land plants and resolve details of the evolutionary history of several phytohormone and structural polymer biosynthetic pathways in land plants.

Plants coordinate the expression of photosynthesis-related genes in response to growth and environmental changes. In species that conduct two-cell C4 photosynthesis, expression of photosynthesis genes is partitioned such that leaf mesophyll and bundle sheath cells accumulate different components of the photosynthetic pathway. The identities of the regulatory networks that facilitate this partitioning are unknown. Here, we show that differences in light perception between mesophyll and bundle sheath cells facilitate differential regulation and accumulation of photosynthesis gene transcripts in the C4 crop maize (Zea mays). Key components of the photosynthesis gene regulatory network differentially accumulated between mesophyll and bundle sheath cells, indicative of differential network activity across cell types. We further show that blue (but not red) light is necessary and sufficient to activate photosystem II assembly in mesophyll cells in etiolated maize. Finally, we demonstrate that 61% of all light-induced mesophyll and bundle sheath genes were induced only by blue light or only by red light, but not both. These findings provide evidence that subdivision of light signaling networks is a component of cellular partitioning of C4 photosynthesis in maize.