Frontiers in Genetics

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ISSN / EISSN : 1664-8021 / 1664-8021
Published by: Frontiers Media SA (10.3389)
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Tingting Yuan, Chenglei Zhu, Guangzhu Li, Yan Liu, Kebin Yang, Zhen Li, ,
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.854346

Abstract:
Nitrogen is a key macronutrient essential for plant growth and development, and its availability has a strong influence on biological processes. Nitrogen fertilizer has been widely applied in bamboo forests in recent decades; however, the mechanism of nitrogen metabolism in bamboo is not fully elucidated. Here, we characterized the morphological, physiological, and transcriptome changes of moso bamboo in response to different schemes for nitrogen addition to illuminate the regulation mechanism of nitrogen metabolism. The appropriate addition of nitrogen improved the chlorophyll content and Pn (net photosynthetic rate) of leaves, the nitrogen and ammonium contents of the seedling roots, the biomass of the whole seedling, the number of lateral roots, and the activity of enzymes involved in nitrogen metabolism in the roots. Based on the whole transcriptome data of the roots, a total of 8,632 differentially expressed mRNAs (DEGs) were identified under different nitrogen additions, such as 52 nitrate transporter genes, 6 nitrate reductase genes, 2 nitrite reductase genes, 2 glutamine synthase genes, 2 glutamate synthase genes (GOGAT), 3 glutamate dehydrogenase genes, and 431 TFs belonging to 23 families. Meanwhile, 123 differentially expressed miRNAs (DEMs) and 396 differentially expressed lncRNAs (DELs) were characterized as nitrogen responsive, respectively. Furthermore, 94 DEM-DEG pairs and 23 DEL-DEG pairs involved in nitrogen metabolism were identified. Finally, a predicted regulatory network of nitrogen metabolism was initially constructed, which included 17 nitrogen metabolic pathway genes, 15 TFs, 4 miRNAs, and 10 lncRNAs by conjoint analysis of DEGs, DEMs, and DELs and their regulatory relationships, which was supported by RNA-seq data and qPCR results. The lncRNA-miRNA-mRNA network provides new insights into the regulation mechanism of nitrogen metabolism in bamboo, which facilitates further genetic improvement for bamboo to adapt to the fluctuating nitrogen environment.
Huiling Zhang, Ying Huang, Zhendong Bei, Zhen Ju, Jintao Meng, Min Hao, Jingjing Zhang, Haiping Zhang, Wenhui Xi
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.887491

Abstract:
Residue distance prediction from the sequence is critical for many biological applications such as protein structure reconstruction, protein–protein interaction prediction, and protein design. However, prediction of fine-grained distances between residues with long sequence separations still remains challenging. In this study, we propose DuetDis, a method based on duet feature sets and deep residual network with squeeze-and-excitation (SE), for protein inter-residue distance prediction. DuetDis embraces the ability to learn and fuse features directly or indirectly extracted from the whole-genome/metagenomic databases and, therefore, minimize the information loss through ensembling models trained on different feature sets. We evaluate DuetDis and 11 widely used peer methods on a large-scale test set (610 proteins chains). The experimental results suggest that 1) prediction results from different feature sets show obvious differences; 2) ensembling different feature sets can improve the prediction performance; 3) high-quality multiple sequence alignment (MSA) used for both training and testing can greatly improve the prediction performance; and 4) DuetDis is more accurate than peer methods for the overall prediction, more reliable in terms of model prediction score, and more robust against shallow multiple sequence alignment (MSA).
, , João Silva, Gabriele Procaccini, Emanuela Dattolo
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.866758

Abstract:
Plant populations distributed along broad latitudinal gradients often show patterns of clinal variation in genotype and phenotype. Differences in photoperiod and temperature cues across latitudes influence major phenological events, such as timing of flowering or seed dormancy. Here, we used an array of 4,941 SNPs derived from 2b-RAD genotyping to characterize population differentiation and levels of genetic and genotypic diversity of three populations of the seagrass Cymodocea nodosa along a latitudinal gradient extending across the Atlantic-Mediterranean boundary (i.e., Gran Canaria—Canary Islands, Faro—Portugal, and Ebro Delta—Spain). Our main goal was to search for potential outlier loci that could underlie adaptive differentiation of populations across the latitudinal distribution of the species. We hypothesized that such polymorphisms could be related to variation in photoperiod-temperature regime occurring across latitudes. The three populations were clearly differentiated and exhibited diverse levels of clonality and genetic diversity. Cymodocea nodosa from the Mediterranean displayed the highest genotypic richness, while the Portuguese population had the highest clonality values. Gran Canaria exhibited the lowest genetic diversity (as observed heterozygosity). Nine SNPs were reliably identified as outliers across the three sites by two different methods (i.e., BayeScan and pcadapt), and three SNPs could be associated to specific protein-coding genes by screening available C. nodosa transcriptomes. Two SNPs-carrying contigs encoded for transcription factors, while the other one encoded for an enzyme specifically involved in the regulation of flowering time, namely Lysine-specific histone demethylase 1 homolog 2. When analyzing biological processes enriched within the whole dataset of outlier SNPs identified by at least one method, “regulation of transcription” and “signalling” were among the most represented. Our results highlight the fundamental importance signal integration and gene-regulatory networks, as well as epigenetic regulation via DNA (de)methylation, could have for enabling adaptation of seagrass populations along environmental gradients.
Lifeng Ma, Hui Chen, Zhiying Zhang, Lijun Liu, Yiduo Zhao, Yansong Li, Zhipeng Zhao, Haitao Chen,
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.902553

Abstract:
Background: The incidence of gallstones in the Tibetan population is increasing rapidly. Previous studies indicated that genetic variation located in the cholesterol metabolism pathway may be associated with the incidence of gallstones.Methods: By recruiting 132 Tibetan gallstone patients and 52 normal Tibetan controls, we performed next-generation sequencing for 508 genes in the cholesterol metabolism pathway. Additionally, by integrating the sequence data of 41 normal Tibetan subjects in the public database, we finally obtained 93 normal Tibetan controls. Single nucleotide polymorphisms (SNPs) calling were performed by using the GATK pipeline. The quality control criteria for SNPs were: missing rate 0.01; and p value >0.001 in the Hardy-Weinberg Equilibrium (HWE) test. To eliminate the influence of population heterogeneity, Principal Component Analysis (PCA) was carried out by using the smartpca software. Association analyses were performed by Plink software. Multiple tests were adjusted by the false discovery rate (FDR) method.Results: A total of 2,401 SNPs were obtained by analyzing 508 genes, and 2,011 SNPs left after quality control. After adjusting the eigen vectors, we found that 10 SNPs (SNV05997, rs80145081, rs80005560, rs79074685, rs748546375, rs201880593, rs142559357, rs750769471, rs869789 and rs4072341) were significantly associated with gallstone. Subsequently, by comparing the case group with our control group and the public database control group separately, we further found that the SNP rs869789 was consistently significantly associated with gallstone (p = 9.04 × 10–3 in cases vs. our controls and 5.73 × 10–3 in cases vs. public controls, respectively).Conclusion: By systematically analyzed SNPs in the cholesterol metabolism pathway, we identified one polymorphic locus rs869789 significantly associated with the pathogenesis of gallstone in the Tibetan population. This study will provide clue for further mechanism study of gallstone in the Tibetan population.
Yang Yang, Yajuan Qu, Zhaopeng Li, Zhiyong Tan, Youming Lei,
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.874805

Abstract:
Background: TP53 mutations are the most frequent mutations in hepatocellular carcinoma (HCC) and affect the occurrence and development of this cancer type. Therefore, it is essential to clarify the function and mechanism of TP53 mutations in HCC.Methods: We performed a sequence of bioinformatic analyses to elucidate the characteristics of TP53 mutations in HCC. We downloaded the data of hepatocellular carcinoma from The Cancer Genome Atlas database and used different R packages for serial analyses, including gene mutation analysis, copy number variation analysis, analysis of the tumor mutational burden and microsatellite instability, differential gene expression analysis, and functional enrichment analysis of TP53 mutations, and performed gene set enrichment analysis. We established a protein-protein interaction network using the STRING online database and used the Cytoscape software for network visualization, and hub gene screening. In addition, we performed anticancer drug sensitivity analysis using data from the Genomics of Drug Sensitivity in Cancer. Immune infiltration and prognosis analyses were also performed.Results: Missense mutations accounted for a great proportion of HCC mutations, the frequency of single nucleotide polymorphisms was high, and C > T was the most common form of single nucleotide variations. TP53 had a mutation rate of 30% and was the most commonly mutated gene in HCC. In the TP53 mutant group, the tumor mutational burden (p < 0.001), drug sensitivity (p < 0.05), ESTIMATE score (p = 0.038), and stromal score (p < 0.001) dramatically decreased. The Cytoscape software screened ten hub genes, including CT45A1, XAGE1B, CT55, GAGE2A, PASD1, MAGEA4, CTAG2, MAGEA10, MAGEC1, and SAGE1. The prognostic model showed a poor prognosis in the TP53 mutation group compared with that in the wild-type group (overall survival, p = 0.023). Univariate and multivariate cox regression analyses revealed that TP53 mutation was an independent risk factor for the prognosis of HCC patients (p <0.05). The constructed prognostic model had a favorable forecast value for the prognosis of HCC patients at 1 and 3 years (1-year AUC = 0.752, 3-years AUC = 0.702).Conclusion: This study further deepened our understanding of TP53-mutated HCC, provided new insights into a precise individualized therapy for HCC, and has particular significance for prognosis prediction.
M. Kathleen Pitirri, Emily L. Durham, Natalie A. Romano, Jacob I. Santos, Abigail P. Coupe, Hao Zheng, Danny Z. Chen, Kazuhiko Kawasaki, Ethylin Wang Jabs, Joan T. Richtsmeier, et al.
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.871927

Abstract:
The Fgfr2cC342Y/+ Crouzon syndrome mouse model carries a cysteine to tyrosine substitution at amino acid position 342 (Cys342Tyr; C342Y) in the fibroblast growth factor receptor 2 (Fgfr2) gene equivalent to a FGFR2 mutation commonly associated with Crouzon and Pfeiffer syndromes in humans. The Fgfr2c C342Y mutation results in constitutive activation of the receptor and is associated with upregulation of osteogenic differentiation. Fgfr2cC342Y/+ Crouzon syndrome mice show premature closure of the coronal suture and other craniofacial anomalies including malocclusion of teeth, most likely due to abnormal craniofacial form. Malformation of the mandible can precipitate a plethora of complications including disrupting development of the upper jaw and palate, impediment of the airway, and alteration of occlusion necessary for proper mastication. The current paradigm of mandibular development assumes that Meckel’s cartilage (MC) serves as a support or model for mandibular bone formation and as a template for the later forming mandible. If valid, this implies a functional relationship between MC and the forming mandible, so mandibular dysmorphogenesis might be discerned in MC affecting the relationship between MC and mandibular bone. Here we investigate the relationship of MC to mandible development from the early mineralization of the mandible (E13.5) through the initiation of MC degradation at E17.7 using Fgfr2cC342Y/+ Crouzon syndrome embryos and their unaffected littermates (Fgfr2c+/+). Differences between genotypes in both MC and mandibular bone are subtle, however MC of Fgfr2cC342Y/+ embryos is generally longer relative to unaffected littermates at E15.5 with specific aspects remaining relatively large at E17.5. In contrast, mandibular bone is smaller overall in Fgfr2cC342Y/+ embryos relative to their unaffected littermates at E15.5 with the posterior aspect remaining relatively small at E17.5. At a cellular level, differences are identified between genotypes early (E13.5) followed by reduced proliferation in MC (E15.5) and in the forming mandible (E17.5) in Fgfr2cC342Y/+ embryos. Activation of the ERK pathways is reduced in the perichondrium of MC in Fgfr2cC342Y/+ embryos and increased in bone related cells at E15.5. These data reveal that the Fgfr2c C342Y mutation differentially affects cells by type, location, and developmental age indicating a complex set of changes in the cells that make up the lower jaw.
Zhixin Liu, Heng Liu, Deqiang Li, Liang Ma, Tongxin Lu, Hao Sun, , Hui Yang
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.905027

Abstract:
Objectives: This study aimed to identify novel biomarkers for osteoarthritis (OA) and explore potential pathological immune cell infiltration.Methods: We identified differentially expressed genes (DEGs) between OA and normal synovial tissues using the limma package in R, and performed enrichment analyses to understand the functions and enriched pathways of DEGs. Weighted gene co-expression network analysis (WGCNA) and distinct machine-learning algorithms were then used to identify hub modules and candidate biomarkers. We assessed the diagnostic value of the candidate biomarkers using receiver operating characteristic (ROC) analysis. We then used the CIBERSORT algorithm to analyze immune cell infiltration patterns, and the Wilcoxon test to screen out hub immune cells that might affect OA occurrence. Finally, the expression levels of hub biomarkers were confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR).Results: We identified 102 up-regulated genes and 110 down-regulated genes. The functional enrichment analysis results showed that DEGs are enriched mainly in immune response pathways. Combining the results of the algorithms and ROC analysis, we identified GUCA1A and NELL1 as potential diagnostic biomarkers for OA, and validated their diagnosibility using an external dataset. Construction of a TF-mRNA-miRNA network enabled prediction of potential candidate compounds targeting hub biomarkers. Immune cell infiltration analyses revealed the expression of hub biomarkers to be correlated with CD8 T cells, memory B cells, M0/M2 macrophages, resting mast cells and resting dendritic cells. qRT-PCR results showed both GUCA1A and NELL1 were significantly increased in OA samples (p < 0.01). All validations are consistent with the microarray hybridization, indicating that GUCA1A and NELL1 may be involved in the pathogenesis of OA.Conclusion: The findings suggest that GUCA1A and NELL1, closely related to OA occurrence and progression, represent new OA candidate markers, and that immune cell infiltration plays a significant role in the progression of OA.
Ingvild Buran Kroglund, Sara Kristiane Kjærgård Eide, Jan Eivind Østnes, Rolf Terje Kroglund, Jan-Erik Frisli, Courtney Alice Waugh
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.856766

Abstract:
The validation of the use of primary cell lines from non-lethal matrixes of feathers and blood of nestlings of a wild bird species, the tawny owl (Strix aluco) is described. Tawny Owl Feather Fibroblast (TOFF) cells and peripheral blood mononuclear cells (PBMCs) were isolated and cultured from the pulp of the secondary wing feathers and whole blood respectively from free-living tawny owl nestlings. Cell growth was registered up until 48 h for both the PBMC cells and the TOFFs. The validation of these primary cell lines in free-living birds has the potential to advance the assessment of immunotoxicological effects in wildlife via non-lethal manner. They provide a key tool with which to study cell toxicity and responses to environmental stressors on a cellular level in wild bird species of interest.
Corrigendum
Dimitri Guala,
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.921286

Abstract:
A Corrigendum on Network Crosstalk as a Basis for Drug Repurposing by Guala, D., and Sonnhammer, E. L. L. (2022). Frontiers in Genetics, 13, 259. doi: 10.3389/fgene.2022.792090 In the original article, there were error. The Data Availability Statement omitted the location of the code and its implementation. A correction has been made to Data Availability Statement We used R (r-project.org) version 3.6.3 for statistical tests and data visualization as well as Python (python.org). The datasets generated for this study together with corresponding code can be found in the Sonnhammer group repository https://bitbucket.org/sonnhammergroup/drugrepurposingbench/. A correction has also been made to the conflict of interest statement to declare a commercial affiliation: Author DG was employed by company Merck AB, Sweden. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated. All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Keywords: drug repurposing, drug repositioning, network-based, benchmark, functional association network, network crosstalk, shortest path Citation: Guala D and Sonnhammer ELL (2022) Corrigendum: Network Crosstalk as a Basis for Drug Repurposing. Front. Genet. 13:921286. doi: 10.3389/fgene.2022.921286 Received: 15 April 2022; Accepted: 19 April 2022; Published: 16 May 2022. Approved by: Copyright © 2022 Guala and Sonnhammer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Erik L. L. Sonnhammer, [email protected]
Simone Caligola, Francesco De Sanctis, Stefania Canè,
Published: 16 May 2022
Frontiers in Genetics, Volume 13; https://doi.org/10.3389/fgene.2022.867880

Abstract:
Tumors are not a simple aggregate of transformed cells but rather a complicated ecosystem containing various components, including infiltrating immune cells, tumor-related stromal cells, endothelial cells, soluble factors, and extracellular matrix proteins. Profiling the immune contexture of this intricate framework is now mandatory to develop more effective cancer therapies and precise immunotherapeutic approaches by identifying exact targets or predictive biomarkers, respectively. Conventional technologies are limited in reaching this goal because they lack high resolution. Recent developments in single-cell technologies, such as single-cell RNA transcriptomics, mass cytometry, and multiparameter immunofluorescence, have revolutionized the cancer immunology field, capturing the heterogeneity of tumor-infiltrating immune cells and the dynamic complexity of tenets that regulate cell networks in the tumor microenvironment. In this review, we describe some of the current single-cell technologies and computational techniques applied for immune-profiling the cancer landscape and discuss future directions of how integrating multi-omics data can guide a new “precision oncology” advancement.
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