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Carbon assimilation by Rubisco is often a limitation to photosynthesis and therefore plant productivity. We have previously shown that transgenic co-expression of the Rubisco large (LS) and small (SS) subunits along with an essential Rubisco accumulation factor, Raf1, leads to faster growth, increased photosynthesis, and enhanced chilling tolerance in maize (Zea mays). Maize also requires Rubisco accumulation factor2 (Raf2) for full accumulation of Rubisco. Here we have analyzed transgenic maize lines with increased expression of Raf2 or Raf2 plus LS and SS. We show that increasing Raf2 expression alone had minor effects on photosynthesis, whereas expressing Raf2 with Rubisco subunits led to increased Rubisco content, more rapid carbon assimilation, and greater plant height, most notably in plants at least 6 weeks of age. The magnitude of the effects was similar to what was observed previously for expression of Raf1 together with Rubisco subunits. Taken together, this suggests that increasing the amount of either assembly factor with Rubisco subunits can independently enhance Rubisco abundance and some aspects of plant performance. These results could also imply either synergy or a degree of functional redundancy for Raf1 and Raf2, the latter of whose precise role in Rubisco assembly is currently unknown. [ABSTRACT FROM AUTHOR]

The Boyce Thompson Institute (BTI) executed a faculty cluster hiring initiative to find scientists driven by the possibilities of collaboration. Given that academic hiring rarely evaluates and rewards teamwork, BTI invented a process that would. In doing so, the Institute was able to reduce gender bias commonly found in a typical academic search. [ABSTRACT FROM AUTHOR]

Interspecies RNA-Seq datasets are increasingly common, and have the potential to answer new questions about the evolution of gene expression. Single-species differential expression analysis is now a well-studied problem that benefits from sound statistical methods. Extensive reviews on biological or synthetic datasets have provided the community with a clear picture on the relative performances of the available methods in various settings. However, synthetic dataset simulation tools are still missing in the interspecies gene expression context. In this work, we develop and implement a new simulation framework. This tool builds on both the RNA-Seq and the phylogenetic comparative methods literatures to generate realistic count datasets, while taking into account the phylogenetic relationships between the samples. We illustrate the usefulness of this new framework through a targeted simulation study, that reproduces the features of a recently published dataset, containing gene expression data in adult eye tissue across blind and sighted freshwater crayfish species. Using our simulated datasets, we perform a fair comparison of several approaches used for differential expression analysis. This benchmark reveals some of the strengths and weaknesses of both the classical and phylogenetic approaches for interspecies differential expression analysis, and allows for a reanalysis of the crayfish dataset. The tool has been integrated in the R package compcodeR, freely available on Bioconductor. [ABSTRACT FROM AUTHOR]