bims-plasge Biomed News
on Plastid genes
Issue of 2020–04–05
two papers selected by
Vera S. Bogdanova, ИЦиГ СО РАН



  1. Plant Physiol. 2020 Apr 03. pii: pp.01564.2019. [Epub ahead of print]
      Plant fatty acid biosynthesis occurs in both plastids and mitochondria. Here, we report the identification and characterization of Arabidopsis (Arabidopsis thaliana) genes encoding three enzymes shared between the mitochondria- and plastid-localized Type II fatty acid synthase systems (mtFAS and ptFAS, respectively). Two of these enzymes, β-ketoacyl-acyl carrier protein (ACP) reductase (pt/mtKR) and enoyl-ACP reductase (pt/mtER) catalyze two of the reactions that constitute the core four-reaction cycle of the FAS system, which iteratively elongates the acyl-chain by two carbon atoms per cycle. The third enzyme, malonyl-CoA:ACP transacylase (pt/mtMCAT) catalyzes the reaction that loads the mtFAS system with substrate by malonylating the phosphopantetheinyl cofactor of ACP. Green fluorescent protein (GFP) fusion experiments revealed that the these enzymes localize to both chloroplasts and mitochondria. This localization was validated by characterization of mutant alleles, which were rescued by transgenes expressing enzyme variants that were retargeted only to plastids or only mitochondria. The singular retargeting of these proteins to plastids rescued the embryo-lethality associated with disruption of the essential ptFAS system, but these rescued plants displayed phenotypes typical of the lack of mtFAS function, including reduced lipoylation of the H subunit of the glycine decarboxylase complex, hyperaccumulation of glycine, and reduced growth. However, these latter traits were reversible in an elevated CO2 atmosphere, which suppresses mtFAS-associated photorespiration-dependent chemotypes. Sharing enzymatic components between mtFAS and ptFAS systems constrains the evolution of these non-redundant fatty acid biosynthetic machineries.
    DOI:  https://doi.org/10.1104/pp.19.01564
  2. PLoS Genet. 2020 Apr;16(4): e1008462
      In flowering plants, gene expression in the haploid male gametophyte (pollen) is essential for sperm delivery and double fertilization. Pollen also undergoes dynamic epigenetic regulation of expression from transposable elements (TEs), but how this process interacts with gene expression is not clearly understood. To explore relationships among these processes, we quantified transcript levels in four male reproductive stages of maize (tassel primordia, microspores, mature pollen, and sperm cells) via RNA-seq. We found that, in contrast with vegetative cell-limited TE expression in Arabidopsis pollen, TE transcripts in maize accumulate as early as the microspore stage and are also present in sperm cells. Intriguingly, coordinate expression was observed between highly expressed protein-coding genes and their neighboring TEs, specifically in mature pollen and sperm cells. To investigate a potential relationship between elevated gene transcript level and pollen function, we measured the fitness cost (male-specific transmission defect) of GFP-tagged coding sequence insertion mutations in over 50 genes identified as highly expressed in the pollen vegetative cell, sperm cell, or seedling (as a sporophytic control). Insertions in seedling genes or sperm cell genes (with one exception) exhibited no difference from the expected 1:1 transmission ratio. In contrast, insertions in over 20% of vegetative cell genes were associated with significant reductions in fitness, showing a positive correlation of transcript level with non-Mendelian segregation when mutant. Insertions in maize gamete expressed2 (Zm gex2), the sole sperm cell gene with measured contributions to fitness, also triggered seed defects when crossed as a male, indicating a conserved role in double fertilization, given the similar phenotype previously demonstrated for the Arabidopsis ortholog GEX2. Overall, our study demonstrates a developmentally programmed and coordinated transcriptional activation of TEs and genes in pollen, and further identifies maize pollen as a model in which transcriptomic data have predictive value for quantitative phenotypes.
    DOI:  https://doi.org/10.1371/journal.pgen.1008462