Genomics, Proteomics & Bioinformatics

KaKs_Calculator is a software package that calculates nonsynonymous (Ka) and synonymous (Ks) substitution rates through model selection and model averaging. Since existing methods for this estimation adopt their specific mutation (substitution) models that consider different evolutionary features, leading to diverse estimates, KaKs_Calculator implements a set of candidate models in a maximum likelihood framework and adopts the Akaike information criterion to measure fitness between models and data, aiming to include as many features as needed for accurately capturing evolutionary information in protein-coding sequences. In addition, several existing methods for calculating Ka and Ks are also incorporated into this software. KaKs_Calculator, including source codes, compiled executables, and documentation, is freely available for academic use at http://evolution.genomics.org.cn/software.htm.

As a dioxygenase, Ten-Eleven Translocation 2 (TET2) catalyzes subsequent steps of 5-methylcytosine (5mC) oxidation. TET2 plays a critical role in the self-renewal, proliferation, and differentiation of hematopoietic stem cells, but its impact on mature hematopoietic cells is not well-characterized. Here we show that Tet2 plays an essential role in osteoclastogenesis. Deletion of Tet2 impairs the differentiation of osteoclast precursor cells (macrophages) and their maturation into bone-resorbing osteoclasts in vitro. Furthermore, Tet2−/− mice exhibit mild osteopetrosis, accompanied by decreased number of osteoclasts in vivo. Tet2 loss in macrophages results in the altered expression of a set of genes implicated in osteoclast differentiation, such as Cebpa, Mafb, and Nfkbiz. Tet2 deletion also leads to a genome-wide alteration in the level of 5-hydroxymethylcytosine (5hmC) and altered expression of a specific subset of macrophage genes associated with osteoclast differentiation. Furthermore, Tet2 interacts with Runx1 and negatively modulates its transcriptional activity. Our studies demonstrate a novel molecular mechanism controlling osteoclast differentiation and function by Tet2, that is, through interactions with Runx1 and the maintenance of genomic 5hmC. Targeting Tet2 and its pathway could be a potential therapeutic strategy for the prevention and treatment of abnormal bone mass caused by the deregulation of osteoclast activities.

MicroRNA (miRNA) plays vital roles in biological processes like RNA splicing and regulation of gene expression. Studies have revealed that there might be possible links between oncogenesis and expression profiles of some miRNAs, due to their differential expression between normal and tumor tissues. However, the automatic classification of miRNAs into different categories by considering the similarity of their expression values has rarely been addressed. This article proposes a solution framework for solving some real-life classification problems related to cancer, miRNA, and mRNA expression datasets. In the first stage, a multiobjective optimization based framework, non-dominated sorting genetic algorithm II, is proposed to automatically determine the appropriate classifier type, along with its suitable parameter and feature combinations, pertinent for classifying a given dataset. In the second page, a stack-based ensemble technique is employed to get a single combinatorial solution from the set of solutions obtained in the first stage. The performance of the proposed two-stage approach is evaluated on several cancer and RNA expression profile datasets. Compared to several state-of-the-art approaches for classifying different datasets, our method shows supremacy in the accuracy of classification.