gene clustering
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BMC Genomics ◽  
2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Quang-Huy Nguyen ◽  
Duc-Hau Le

Abstract Background When it comes to the co-expressed gene module detection, its typical challenges consist of overlap between identified modules and local co-expression in a subset of biological samples. The nature of module detection is the use of unsupervised clustering approaches and algorithms. Those methods are advanced undoubtedly, but the selection of a certain clustering method for sample- and gene-clustering tasks is separate, in which the latter task is often more complicated. Results This study presented an R-package, Overlapping CoExpressed gene Module (oCEM), armed with the decomposition methods to solve the challenges above. We also developed a novel auxiliary statistical approach to select the optimal number of principal components using a permutation procedure. We showed that oCEM outperformed state-of-the-art techniques in the ability to detect biologically relevant modules additionally. Conclusions oCEM helped non-technical users easily perform complicated statistical analyses and then gain robust results. oCEM and its applications, along with example data, were freely provided at https://github.com/huynguyen250896/oCEM.


Plants ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 163
Author(s):  
Natalia Petrova ◽  
Natalia Mokshina

Plant proteins with lectin domains play an essential role in plant immunity modulation, but among a plurality of lectins recruited by plants, only a few members have been functionally characterized. For the analysis of flax lectin gene expression, we used FIBexDB, which includes an efficient algorithm for flax gene expression analysis combining gene clustering and coexpression network analysis. We analyzed the lectin gene expression in various flax tissues, including root tips infected with Fusarium oxysporum. Two pools of lectin genes were revealed: downregulated and upregulated during the infection. Lectins with suppressed gene expression are associated with protein biosynthesis (Calreticulin family), cell wall biosynthesis (galactose-binding lectin family) and cytoskeleton functioning (Malectin family). Among the upregulated lectin genes were those encoding lectins from the Hevein, Nictaba, and GNA families. The main participants from each group are discussed. A list of lectin genes, the expression of which can determine the resistance of flax, is proposed, for example, the genes encoding amaranthins. We demonstrate that FIBexDB is an efficient tool both for the visualization of data, and for searching for the general patterns of lectin genes that may play an essential role in normal plant development and defense.


2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Fangzhou Guo ◽  
Jun Yan ◽  
Guoyuan Ling ◽  
Hainan Chen ◽  
Qianrong Huang ◽  
...  

Lower-grade glioma (LGG) is a common type of central nervous system tumor. Due to its complicated pathogenesis, the choice and timing of adjuvant therapy after tumor treatment are controversial. This study explored and identified potential therapeutic targets for lower-grade. The bioinformatics method was employed to identify potential biomarkers and LGG molecular mechanisms. Firstly, we selected and downloaded GSE15824, GSE50161, and GSE86574 from the GEO database, which included 40 LGG tissue and 28 normal brain tissue samples. GEO and VENN software identified of 206 codifference expressed genes (DEGs). Secondly, we applied the DAVID online software to investigate the DEG biological function and KEGG pathway enrichment, as well as to build the protein interaction visualization network through Cytoscape and STRING website. Then, the MCODE plug is used in the analysis of 22 core genes. Thirdly, the 22 core genes were analyzed with UNCLA software, of which 18 genes were associated with a worse prognosis. Fourthly, GEPIA was used to analyze the 18 selected genes, and 14 genes were found to be a significantly different expression between LGGs and normal brain tumor samples. Fifthly, hierarchical gene clustering was used to examine the 14 important gene expression differences in different histologies, as well as analysis of the KEGG pathway. Five of these genes were shown to be abundant in the natural killer cell-mediated cytokines (NKCC) and phagosome pathways. The five key genes that may be affected by the immune microenvironment play a crucial role in LGG development.


DNA ◽  
2022 ◽  
Vol 2 (1) ◽  
pp. 1-21
Author(s):  
Dimitrios S. Kanakoglou ◽  
Andromachi Pampalou ◽  
Lina S. Malakou ◽  
Eleftheria Lakiotaki ◽  
Theodoros Loupis ◽  
...  

Zinc fingers consist of one of the most abundant motifs in transcription factors and DNA-binding proteins. Recent studies provide evidence on the pathological implication of zinc finger proteins in various neurodevelopmental disorders and malignancies but their role in pediatric brain tumors is largely unexplored. To this end, we investigated the differential expression of zinc finger-containing genes along with relevant biological processes and pathways among four main brain tumor categories (pilocytic astrocytomas, ependymomas, medulloblastomas and glioblastomas). By employing an extended bioinformatic toolset, we performed a preliminary in silico study in order to identify the expression of zinc finger-containing genes and associated functions in pediatric brain tumors. Our data analysis reveals the prominent role of C2H2-type zinc finger-containing genes in the molecular mechanisms underlying pediatric brain tumors followed by the Ring and PHD finger types. Significant dysregulation of ABLIM2 and UHFR1 genes was detected in all tumor types drawing attention to the dysregulation of cell polarization process and Ubiquitin-Proteasome System (UPS) in the pathogenesis of pediatric brain tumors. Moreover, significant gene clustering was observed in multiple locations with two highly visible clusters revealing a contrast in gene regulation between medulloblastomas and the other three brain tumor types, indicating a promising area of future research.


2021 ◽  
Author(s):  
Irina Rodionova ◽  
Bernhard Palsson ◽  
Ye Gao ◽  
Nicholas Wong ◽  
Richard Szubin ◽  
...  

Abstract Although Escherichia coli K-12 strains represent perhaps the best known model bacteria, we do not know the identity or functions of all of their transcription factors (TFs). It is now possible to systematically discover the physiological function of TFs in E. coli BW25113 using a set of synergistic methods; including ChIP-exo, growth phenotyping, conserved gene clustering, and transcriptome analysis. Among 47 LysR-type TFs (LTFs) found on the E. coli K-12 genome, many regulate nitrogen source utilization or amino acid metabolism. However, 19 LTFs remain unknown. In this study, we elucidated the regulation of seven of these 19 LTFs: YbdO, YbeF, YgfI, YiaU, YneJ, YcaN, YbhD. We show that: 1) YbdO regulation has an effect on bacterial growth at low pH with citrate supplementation. YbdO is a repressor of the ybdNM operon and is implicated in the regulation of citrate lyase genes (citCDEFG); 2) YgfI activates the dhaKLM operon that encodes the phosphotransferase system involved in glycerol and dihydroxyacetone utilization; 3) YiaU regulates the yiaT gene encoding an outer membrane protein, and waaPSBOJYZU operon is also important in determining cell density at the stationary phase; 4) YneJ, re-named here as PtrR, directly regulates the expression of the succinate-semialdehyde dehydrogenase, Sad (also known as YneI), and is a predicted regulator of fnrS (a small RNA molecule). PtrR is important for bacterial growth in the presence of L-glutamate and putrescine as nitrogen sources; and 5) YbhD and YcaN regulate adjacent y-genes on the genome and YbeF is involved in flagella gene regulation. We have thus established the functions for four LTFs and identified the target genes for three LTFs.


2021 ◽  
Author(s):  
Irina A. Rodionova ◽  
Ye Gao ◽  
Hyun Gyu Lim ◽  
Milton H. Saier ◽  
Bernhard Palsson ◽  
...  

Although Escherichia coli K-12 strains represent perhaps the best known model bacteria, we do not know the identity or functions of all of their transcription factors (TFs). It is now possible to systematically discover the physiological function of TFs in E. coli BW25113 using a set of synergistic methods; including ChIP-exo, growth phenotyping, conserved gene clustering, and transcriptome analysis. Among 47 LysR-type TFs (LTFs) found on the E. coli K-12 genome, many regulate nitrogen source utilization or amino acid metabolism. However, 19 LTFs remain unknown. In this study, we elucidated the regulation of seven of these 19 LTFs: YbdO, YbeF, YgfI, YiaU, YneJ, YcaN, YbhD. We show that: 1) YbdO regulation has an effect on bacterial growth at low pH with citrate supplementation. YbdO is a repressor of the ybdNM operon and is implicated in the regulation of citrate lyase genes (citCDEFG); 2) YgfI activates the dhaKLM operon that encodes the phosphotransferase system involved in glycerol and dihydroxyacetone utilization; 3) YiaU regulates the yiaT gene encoding an outer membrane protein, and waaPSBOJYZU operon is also important in determining cell density at the stationary phase; 4) YneJ, re-named here as PtrR, directly regulates the expression of the succinate-semialdehyde dehydrogenase, Sad (also known as YneI), and is a predicted regulator of fnrS (a small RNA molecule). PtrR is important for bacterial growth in the presence of L-glutamate and putrescine as nitrogen sources; and 5) YbhD and YcaN regulate adjacent y-genes on the genome and YbeF is involved in flagella gene regulation. We have thus established the functions for four LTFs and identified the target genes for three LTFs.


2021 ◽  
Vol 13 (24) ◽  
pp. 13997
Author(s):  
Jayan Duminda Mahesh Senevirathna ◽  
Ryo Yonezawa ◽  
Taiki Saka ◽  
Yoji Igarashi ◽  
Noriko Funasaka ◽  
...  

Aquatic habitats are home to large animals such as marine mammals. Toothed whales have special fat deposits in the forehead region (called the melon) of their heads that are associated with echolocation underwater. This fat is also important industrially for human use. Due to the lack of gene expression information on the melon fat of toothed whales, we investigated the melon morphology via the transcriptomic approach. Four parts of the melons of three individual Risso’s dolphins were used for total RNA extraction, cDNA library preparation, and sequencing via next-generation sequencing (NGS) technologies. After the downstream analysis of raw sequence data, we determined that the outer layer of the melon’s ML4 region played multifunctional roles. The 36 differentially expressed genes of outer melon included ASB5, MYH13, MYOM2, and MYOM3. These genes are associated with muscle function and energy metabolism. Gene clustering and functional enrichment analyses also represented enrichments, such as the pentose phosphate pathway and morphogenesis related to lipid metabolism and muscle functions. This study will be crucial for muscle and fat functional-related molecular studies on aquatic mammals. Additionally, the study presents potential pathways, such as melon fat biosynthesis, for sustainable future developments.


2021 ◽  
Author(s):  
Yi Liao ◽  
Juntao Wang ◽  
Zhangsheng Zhu ◽  
Yuanlong Liu ◽  
Jinfeng Chen ◽  
...  

AbstractThe architecture of topologically associating domains (TADs) varies across plant genomes. Understanding the functional consequences of this diversity requires insights into the pattern, structure, and function of TADs. Here, we present a comprehensive investigation of the 3D genome organization of pepper (Capsicum annuum) and its association with gene expression and genomic variants. We report the first chromosome-scale long-read genome assembly of pepper and generate Hi-C contact maps for four tissues. The contact maps indicate that 3D structure varies somewhat across tissues, but generally the genome was segregated into subcompartments that were correlated with transcriptional state. In addition, chromosomes were almost continuously spanned by TADs, with the most prominent found in large genomic regions that were rich in retrotransposons. A substantial fraction of TAD boundaries were demarcated by chromatin loops, suggesting loop extrusion is a major mechanism for TAD formation; many of these loops were bordered by genes, especially in highly repetitive regions, resulting in gene clustering in three dimensional space. Integrated analysis of Hi-C profiles and transcriptomes showed that change in 3D chromatin structures (e.g. subcompartments, TADs, and loops) was not the primary mechanism contributing to differential gene expression between tissues, but chromatin structure does play a role in transcription stability. TAD boundaries were significantly enriched for breaks of synteny and depletion of sequence variation, suggesting that TADs constrain patterns of genome structural evolution in plants. Together, our work provides insights into principles of 3D genome folding in large plant genomes and its association with function and evolution.


2021 ◽  
Author(s):  
Dongya Wu ◽  
Bowen Jiang ◽  
Chu-Yu Ye ◽  
Michael P. Timko ◽  
Longjiang Fan

AbstractBenzoxazinoids are a class of protective and allelopathic plant secondary metabolites, first identified in maize (Zea mays) and subsequently shown to be encoded by a biosynthetic gene cluster (BGC), the Bx cluster. Data mining of mining 40 high-quality grass genomes identified complete Bx clusters (containing genes Bx1 to Bx5 and Bx8) in three genera (Zea, Echinochloa and Dichanthelium) in the Panicoideae and partial clusters in the Triticeae. The Bx cluster originated from gene duplication of native analogues of Bx genes and chromosomal translocation. An ancient Bx cluster including additional Bx genes (e.g., Bx6) is found in ancestral Panicoideae. The ancient Bx cluster was gained by the Triticeae ancestor via a horizontal transfer (HT) event from the ancestral Panicoideae and later separated into three parts on different chromosomes. Bx6 appears to have been under less constrained selection during evolution of the Panicoideae as evidenced by the fact that was translocated ∼1.31-Mb away from the Bx cluster in Z. mays, moved to other chromosomes in Echinochloa, and even lost in Dichanthelium. Further investigation indicated that intense selection and polyploidization shaped the evolutionary trajectory of the Bx cluster in the grass family. This study provides the first case of HT of BGCs among plants and sheds new insights on the evolution of BGCs.SignificanceBiosynthetic gene clustering and horizontal gene transfer are two evolutionary inventions for rapid adaption by organisms. Horizontal transfer of a gene cluster has been reported in fungi and bacteria, but not in plants up to now. By mining the genomes of 40 monocot species, we deciphered the organization of Bx gene cluster, a biosynthetic gene cluster for benzoxazinoids in grasses. We found that the Bx cluster was formed by gene duplication of native analogues of individual Bx genes and directional translocation. More importantly, the Bx cluster in Triticeae was inherited from the Panicoideae via horizontal transfer. Compared with the native analogues, Bx clusters in grasses show constrained purifying selection underscoring their significance in environmental adaption.


2021 ◽  
Author(s):  
Dan Li ◽  
Hong Gu ◽  
Qiaozhen Chang ◽  
Jia Wang ◽  
Pan Qin

Abstract Clustering algorithms have been successfully applied to identify co-expressed gene groups from gene expression data. Missing values often occur in gene expression data, which presents a challenge for gene clustering. When partitioning incomplete gene expression data into co-expressed gene groups, missing value imputation and clustering are generally performed as two separate processes. These two-stage methods are likely to result in unsuitable imputation values for clustering task and unsatisfying clustering performance. This paper proposes a multi-objective joint optimization framework for clustering incomplete gene expression data that addresses this problem. The proposed framework can impute the missing expression values under the guidance of clustering, and therefore realize the synergistic improvement of imputation and clustering. In addition, gene expression similarity and gene semantic similarity extracted from the Gene Ontology are combined, as the form of functional neighbor interval for each missing expression value, to provide reasonable constraints for the joint optimization framework. Experiments on several benchmark data sets confirm the effectiveness of the proposed framework.


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