Arabidopsis thaliana is a reference plant that has been studied intensively for several decades. Recent advances in high-throughput experimental technology have enabled the generation of an unprecedented amount of data from A. thaliana, which has facilitated data-driven approaches to unravel the genetic organization of plant phenotypes. We previously published a description of a genome-scale functional gene network for A. thaliana, AraNet, which was constructed by integrating multiple co-functional gene networks inferred from diverse data types, and we demonstrated the predictive power of this network for complex phenotypes. More recently, we have observed significant growth in the availability of omics data for A. thaliana as well as improvements in data analysis methods that we anticipate will further enhance the integrated database of co-functional networks. Here, we present an updated co-functional gene network for A. thaliana, AraNet v2 (available at http://www.inetbio.org/aranet), which covers approximately 84% of the coding genome. We demonstrate significant improvements in both genome coverage and accuracy. To enhance the usability of the network, we implemented an AraNet v2 web server, which generates functional predictions for A. thaliana and 27 nonmodel plant species using an orthology-based projection of nonmodel plant genes on the A. thaliana gene network.
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http://dx.doi.org/10.1093/nar/gku1053 | DOI Listing |
Plants (Basel)
September 2024
Department of Smart Farm Science, Kyung Hee University, Yongin 17104, Republic of Korea.
Methods Mol Biol
June 2024
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China.
Dynamic and reversible N-methyladenosine (mA) modifications are associated with many essential cellular functions as well as physiological and pathological phenomena. In-depth study of mA co-functional patterns in epi-transcriptomic data may help to understand its complex regulatory mechanisms. In this chapter, we describe several biclustering mining algorithms for epi-transcriptomic data to discover potential co-functional patterns.
View Article and Find Full Text PDFElife
February 2024
Department of Human Genetics, University of Utah, Salt Lake City, United States.
Co-functional proteins tend to have rates of evolution that covary over time. This correlation between evolutionary rates can be measured over the branches of a phylogenetic tree through methods such as evolutionary rate covariation (ERC), and then used to construct gene networks by the identification of proteins with functional interactions. The cause of this correlation has been hypothesized to result from both compensatory coevolution at physical interfaces and nonphysical forces such as shared changes in selective pressure.
View Article and Find Full Text PDFWe developed an R codebase that uses a publicly-available compendium of transcriptomes from yeast single-gene deletion strains - the Deleteome - to predict gene function. Primarily, the codebase provides functions for identifying similarities between the transcriptomic signatures of deletion strains, thereby associating genes of interest with others that may be functionally related. We describe how our tool predicted a novel relationship between the yeast nucleoporin Nup170 and the Ctf18-RFC complex, which was confirmed experimentally, revealing a previously unknown link between nuclear pore complexes and the DNA replication machinery.
View Article and Find Full Text PDFImmunogenetics
December 2023
College of Animal Science and Technology, College of Veterinary Medicine, Zhejiang Agriculture and Forestry University, Key Laboratory of Applied Technology On Green-Eco-Healthy Animal Husbandry of Zhejiang Province, Hangzhou, China.
All jawed vertebrates have four T cell receptor (TCR) chains expressed by thymus-derived lymphocytes that play a significant role in animal immune defense. However, avian TCR studies have been limited to a few species, although their co-functional major histocompatibility complexes (MHCs) have been studied for decades, showing various copy numbers and polymorphisms. Here, using public genome data, we characterized the copy numbers, the phylogenic relationship and selection of T cell receptor complex (TCR-C) segments, and the genomic organization of TCR loci across birds.
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