Targeted 3' processing of antisense transcripts triggers Arabidopsis FLC chromatin silencing.

Noncoding RNA is emerging as an important regulator of gene expression in many organisms. We are characterizing RNA-mediated chromatin silencing of the Arabidopsis major floral repressor gene, FLC. Through suppressor mutagenesis, we identify a requirement for CstF64 and CstF77, two conserved RNA 3'-end-processing factors, in FLC silencing. However, FLC sense transcript 3' processing is not affected in the mutants. Instead, CstF64 and CstF77 are required for 3' processing of FLC antisense transcripts. A specific RNA-binding protein directs their activity to a proximal antisense polyadenylation site. This targeted processing triggers localized histone demethylase activity and results in reduced FLC sense transcription. Targeted 3' processing of antisense transcripts may be a common mechanism triggering transcriptional silencing of the corresponding sense gene.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.