SUMO protease FUG1, histone reader AL3 and chromodomain protein LHP1 are integral to repeat expansion-induced gene silencing in Arabidopsis thaliana.

Epigenetic gene silencing induced by expanded repeats can cause diverse phenotypes ranging from severe growth defects in plants to genetic diseases such as Friedreich's ataxia in humans. The molecular mechanisms underlying repeat expansion-induced epigenetic silencing remain largely unknown. Using a plant model with a temperature-sensitive phenotype, we have previously shown that expanded repeats can induce small RNAs, which in turn can lead to epigenetic silencing through the RNA-dependent DNA methylation pathway. Here, using a genetic suppressor screen and yeast two-hybrid assays, we identified novel components required for epigenetic silencing caused by expanded repeats. We show that FOURTH ULP GENE CLASS 1 (FUG1)-an uncharacterized SUMO protease with no known role in gene silencing-is required for epigenetic silencing caused by expanded repeats. In addition, we demonstrate that FUG1 physically interacts with ALFIN-LIKE 3 (AL3)-a histone reader that is known to bind to active histone mark H3K4me2/3. Loss of function of AL3 abolishes epigenetic silencing caused by expanded repeats. AL3 physically interacts with the chromodomain protein LIKE HETEROCHROMATIN 1 (LHP1)-known to be associated with the spread of the repressive histone mark H3K27me3 to cause repeat expansion-induced epigenetic silencing. Loss of any of these components suppresses repeat expansion-associated phenotypes coupled with an increase in IIL1 expression with the reversal of gene silencing and associated change in epigenetic marks. Our findings suggest that the FUG1-AL3-LHP1 module is essential to confer repeat expansion-associated epigenetic silencing and highlight the importance of post-translational modifiers and histone readers in epigenetic silencing.

An optimized live imaging and growth analysis approach for Arabidopsis Sepals.

Background: Arabidopsis thaliana sepals are excellent models for analyzing growth of entire organs due to their relatively small size, which can be captured at a cellular resolution under a confocal microscope [1]. To investigate how growth of different tissue layers generates unique organ morphologies, it is necessary to live-image deep into the tissue. However, imaging deep cell layers of the sepal is practically challenging, as it is hindered by the presence of extracellular air spaces between mesophyll cells, among other factors which causes optical aberrations. Image processing is also difficult due to the low signal-to-noise ratio of the deeper tissue layers, an issue mainly associated with live imaging datasets. Addressing some of these challenges, we provide an optimized methodology for live imaging sepals and subsequent image processing. This helps us track the growth of individual cells on the outer and inner epidermal layers, which are the key drivers of sepal morphogenesis. Results: For live imaging sepals across all tissue layers at early stages of development, we found that the use of a bright fluorescent membrane marker, coupled with increased laser intensity and an enhanced Z- resolution produces high-quality images suitable for downstream image processing. Our optimized parameters allowed us to image the bottommost cell layer of the sepal (inner epidermal layer) without compromising viability. We used a 'voxel removal' technique to visualize the inner epidermal layer in MorphoGraphX [2, 3] image processing software. Finally, we describe the process of optimizing the parameters for creating a 2.5D mesh surface for the inner epidermis. This allowed segmentation and parent tracking of individual cells through multiple time points, despite the weak signal of the inner epidermal cells. Conclusion: We provide a robust pipeline for imaging and analyzing growth across inner and outer epidermal layers during early sepal development. Our approach can potentially be employed for analyzing growth of other internal cell layers of the sepals as well. For each of the steps, approaches, and parameters we used, we have provided in-depth explanations to help researchers understand the rationale and replicate our pipeline.

GWAS hints at pleiotropic roles for FLOWERING LOCUS T in flowering time and yield-related traits in canola.

BACKGROUND: Transition to flowering at the right time is critical for local adaptation and to maximize grain yield in crops. Canola is an important oilseed crop with extensive variation in flowering time among varieties. However, our understanding of underlying genes and their role in canola productivity is limited. RESULTS: We report our analyses of a diverse GWAS panel (300-368 accessions) of canola and identify SNPs that are significantly associated with variation in flowering time and response to photoperiod across multiple locations. We show that several of these associations map in the vicinity of FLOWERING LOCUS T (FT) paralogs and its known transcriptional regulators. Complementary QTL and eQTL mapping studies, conducted in an Australian doubled haploid population, also detected consistent genomic regions close to the FT paralogs associated with flowering time and yield-related traits. FT sequences vary between accessions. Expression levels of FT in plants grown in field (or under controlled environment cabinets) correlated with flowering time. We show that markers linked to the FT paralogs display association with variation in multiple traits including flowering time, plant emergence, shoot biomass and grain yield. CONCLUSIONS: Our findings suggest that FT paralogs not only control flowering time but also modulate yield-related productivity traits in canola.