Histone 3 lysine 36 to methionine mutations stably interact with and sequester SDG8 in Arabidopsis thaliana

Post-transcriptional modifications of histones play important roles in various biological processes. Here, we report that Arabidopsis plants overexpressing histone H3 lysine to methionine mutations at histone H3.1K36 (H3.1K36M) and H3.3K36 (H3.3K36M) have serious developmental defects with early-flowering and change in the modifications of endogenous histone H3, including acetylation at lysine 9 (H3K9ac), trimethylation at lysine 27 (H3K27me3), di- and tri-methylation at lysine 36 (H3K36me2 and H3K36me3). In addition, H3K36M mutation alters its subcellular localization and interacts with H3K36 methyltransferase SDG8. Our results support a model in which H3K36M stably interacts with SDG8, and inhibits the activity of SDG8 by sequestering SDG8, resulting in a dominant negative effect to affect the proper expression levels of a variety of genes and plant development.

American oyster, Crassostrea virginica, expresses a potent antibacterial histone H2B protein

An antibacterial protein was purified from acidified gill extract of a bivalve mollusk, the American oyster (Crassostrea virginica). Protein isolation was best accomplished by briefly boiling the tissues in a weak acetic acid solution. Adding protease inhibitors while boiling did not have a major effect on activity recovery. In contrast, use of only protease inhibitors (without boiling) resulted in virtually no recovery of this activity. The amino acid sequence of this antibacterial protein was identified as a histone H2B and was designated cvH2B. cvH2B had potent activity against gram-negative bacteria, including the human pathogens Vibrio parahaemolyticus and Vibrio vulnificus, which commonly reside in oyster tissues. We estimated that the concentration of this protein was well within the concentration that was inhibitory to these bacterial pathogens in vitro. This is the first report of the antimicrobial function of histone H2B from any mollusk.

Missing value imputation for microarray gene expression data using histone acetylation information

Background

It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages.

Results

The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method) is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor) and LLS(local least square) imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE). Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information.

Conclusion

We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified.