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Kovacik M, Nowicka A, Zwyrtková J, Strejčková B, Vardanega I, Esteban E, Pasha A, Kaduchová K, Krautsova M, Červenková M, Šafář J, Provart NJ, Simon R, Pecinka A. The transcriptome landscape of developing barley seeds. THE PLANT CELL 2024; 36:2512-2530. [PMID: 38635902 PMCID: PMC11218782 DOI: 10.1093/plcell/koae095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 03/05/2024] [Indexed: 04/20/2024]
Abstract
Cereal grains are an important source of food and feed. To provide comprehensive spatiotemporal information about biological processes in developing seeds of cultivated barley (Hordeum vulgare L. subsp. vulgare), we performed a transcriptomic study of the embryo, endosperm, and seed maternal tissues collected from grains 4-32 days after pollination. Weighted gene co-expression network and motif enrichment analyses identified specific groups of genes and transcription factors (TFs) potentially regulating barley seed tissue development. We defined a set of tissue-specific marker genes and families of TFs for functional studies of the pathways controlling barley grain development. Assessing selected groups of chromatin regulators revealed that epigenetic processes are highly dynamic and likely play a major role during barley endosperm development. The repressive H3K27me3 modification is globally reduced in endosperm tissues and at specific genes related to development and storage compounds. Altogether, this atlas uncovers the complexity of developmentally regulated gene expression in developing barley grains.
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Affiliation(s)
- Martin Kovacik
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
- Department of Cell Biology and Genetics, Faculty of Science, Palacký University, Šlechtitelů 27, 779 00 Olomouc, Czech Republic
| | - Anna Nowicka
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
- Franciszek Górski Institute of Plant Physiology Polish Academy of Sciences, Niezapominajek 21, 30 239 Kraków, Poland
| | - Jana Zwyrtková
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
| | - Beáta Strejčková
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
| | - Isaia Vardanega
- Institute for Developmental Genetics, Heinrich-Heine-University, Universitätsstraße 1, 40225 Düsseldorf, Germany
| | - Eddi Esteban
- Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, 25 Willcocks St., Toronto, ON M5S 3B2, Canada
| | - Asher Pasha
- Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, 25 Willcocks St., Toronto, ON M5S 3B2, Canada
| | - Kateřina Kaduchová
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
| | - Maryna Krautsova
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
| | - Marie Červenková
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
| | - Jan Šafář
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
| | - Nicholas J Provart
- Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, 25 Willcocks St., Toronto, ON M5S 3B2, Canada
| | - Rüdiger Simon
- Institute for Developmental Genetics, Heinrich-Heine-University, Universitätsstraße 1, 40225 Düsseldorf, Germany
| | - Ales Pecinka
- Institute of Experimental Botany, Czech Acad Sci, Centre of Plant Structural and Functional Genomics, Šlechtitelů 31, 779 00 Olomouc, Czech Republic
- Department of Cell Biology and Genetics, Faculty of Science, Palacký University, Šlechtitelů 27, 779 00 Olomouc, Czech Republic
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Park JE, Patnaik BB, Sang MK, Song DK, Jeong JY, Hong CE, Kim YT, Shin HJ, Ziwei L, Patnaik HH, Hwang HJ, Park SY, Kang SW, Ko JH, Lee JS, Park HS, Jo YH, Han YS, Lee YS. Transcriptome sequencing of the endangered land snail Karaftohelix adamsi from the Island Ulleung: De novo assembly, annotation, valuation of fitness genes and SSR markers. Genes Genomics 2024; 46:851-870. [PMID: 38809491 DOI: 10.1007/s13258-024-01511-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 03/08/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND The Bradybaenidae snail Karaftohelix adamsi is endemic to Korea, with the species tracked from Island Ulleung in North Gyeongsang Province of South Korea. K. adamsi has been classified under the Endangered Wildlife Class II species of Korea and poses a severe risk of extinction following habitat disturbances. With no available information at the DNA (genome) or mRNA (transcriptome) level for the species, conservation by utilizing informed molecular resources seems difficult. OBJECTIVE In this study, we used the Illumina short-read sequencing and Trinity de novo assembly to draft the reference transcriptome of K. adamsi. RESULTS After assembly, 13,753 unigenes were obtained of which 10,511 were annotated to public databases (a maximum of 10,165 unigenes found homologs in PANM DB). A total of 6,351, 3,535, 358, and 3,407 unigenes were ascribed to the functional categories under KOG, GO, KEGG, and IPS, respectively. The transcripts such as the HSP 70, aquaporin, TLR, and MAPK, among others, were screened as putative functional resources for adaptation. DNA transposons were found to be thickly populated in comparison to retrotransposons in the assembled unigenes. Further, 2,164 SSRs were screened with the promiscuous presence of dinucleotide repeats such as AC/GT and AG/CT. CONCLUSION The transcriptome-guided discovery of molecular resources in K. adamsi will not only serve as a basis for functional genomics studies but also provide sustainable tools to be utilized for the protection of the species in the wild. Moreover, the development of polymorphic SSRs is valuable for the identification of species from newer habitats and cross-species genotyping.
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Affiliation(s)
- Jie Eun Park
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources, Soonchunhyang University, Chungnam, 31, Asan, South Korea
| | - Bharat Bhusan Patnaik
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
- PG Department of Biosciences and Biotechnology, Fakir Mohan University, Nuapadhi, Balasore, Odisha, 756089, India
| | - Min Kyu Sang
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources, Soonchunhyang University, Chungnam, 31, Asan, South Korea
| | - Dae Kwon Song
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources, Soonchunhyang University, Chungnam, 31, Asan, South Korea
| | - Jun Yang Jeong
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
| | - Chan Eui Hong
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
| | - Yong Tae Kim
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
| | - Hyeon Jun Shin
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
| | - Liu Ziwei
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
| | - Hongray Howrelia Patnaik
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- PG Department of Zoology, BJB Autonomous College, Bhubaneswar, Odisha, 751014, India
| | - Hee Ju Hwang
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
| | - So Young Park
- Biodiversity Research Team, Animal & Plant Research Department, Nakdonggang National Institute of Biological Resources, Sangju, Gyeongbuk, South Korea
| | - Se Won Kang
- Biological Resource Center (BRC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Jeongeup, Jeonbuk, South Korea
| | - Jung Ho Ko
- Police Science Institute, Korean National Police University, Asan, 31539, Chungnam, Korea
| | - Jun Sang Lee
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
| | - Hong Seog Park
- Research Institute, GnC BIO Co., LTD, 621-6 Banseok-Dong, Yuseong-Gu, Daejeon, 34069, Korea
| | - Yong Hun Jo
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea
| | - Yeon Soo Han
- College of Agriculture and Life Science, Chonnam National University, 77 Yongbong-Ro, Buk-Gu, Gwangju, 61186, South Korea
| | - Yong Seok Lee
- Korea Native Animal Resources Utilization Convergence Research Institute (KNAR), Soonchunhyang University, Asan, Chungnam, 31538, South Korea.
- Research Support Center for Bio-Bigdata Analysis and Utilization of Biological Resources, Soonchunhyang University, Chungnam, 31, Asan, South Korea.
- Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, 31538, Chungnam, Korea.
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Jackson DJ, Cerveau N, Posnien N. De novo assembly of transcriptomes and differential gene expression analysis using short-read data from emerging model organisms - a brief guide. Front Zool 2024; 21:17. [PMID: 38902827 PMCID: PMC11188175 DOI: 10.1186/s12983-024-00538-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 06/12/2024] [Indexed: 06/22/2024] Open
Abstract
Many questions in biology benefit greatly from the use of a variety of model systems. High-throughput sequencing methods have been a triumph in the democratization of diverse model systems. They allow for the economical sequencing of an entire genome or transcriptome of interest, and with technical variations can even provide insight into genome organization and the expression and regulation of genes. The analysis and biological interpretation of such large datasets can present significant challenges that depend on the 'scientific status' of the model system. While high-quality genome and transcriptome references are readily available for well-established model systems, the establishment of such references for an emerging model system often requires extensive resources such as finances, expertise and computation capabilities. The de novo assembly of a transcriptome represents an excellent entry point for genetic and molecular studies in emerging model systems as it can efficiently assess gene content while also serving as a reference for differential gene expression studies. However, the process of de novo transcriptome assembly is non-trivial, and as a rule must be empirically optimized for every dataset. For the researcher working with an emerging model system, and with little to no experience with assembling and quantifying short-read data from the Illumina platform, these processes can be daunting. In this guide we outline the major challenges faced when establishing a reference transcriptome de novo and we provide advice on how to approach such an endeavor. We describe the major experimental and bioinformatic steps, provide some broad recommendations and cautions for the newcomer to de novo transcriptome assembly and differential gene expression analyses. Moreover, we provide an initial selection of tools that can assist in the journey from raw short-read data to assembled transcriptome and lists of differentially expressed genes.
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Affiliation(s)
- Daniel J Jackson
- University of Göttingen, Department of Geobiology, Goldschmidtstr.3, Göttingen, 37077, Germany.
| | - Nicolas Cerveau
- University of Göttingen, Department of Geobiology, Goldschmidtstr.3, Göttingen, 37077, Germany
| | - Nico Posnien
- University of Göttingen, Department of Developmental Biology, GZMB, Justus-Von-Liebig-Weg 11, Göttingen, 37077, Germany.
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Hall WA, Mathison AJ, DeVoe E, Tschannen M, Wendt-Andrae J, Straza M, Awan M, Puckett LL, Lawton CAF, Schultz C, Urrutia R, Kerns S, Torres-Roca JF, Li XA, Erickson B, Nevalainen MT, Zimmermann MT, Paulson E. Changes in Daily Apparent Diffusion Coefficient on Fully Quantitative Magnetic Resonance Imaging Correlate With Established Genomic Pathways of Radiation Sensitivity and Reveal Novel Biologic Associations. Int J Radiat Oncol Biol Phys 2024:S0360-3016(24)00468-1. [PMID: 38819340 DOI: 10.1016/j.ijrobp.2024.03.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 03/21/2024] [Accepted: 03/27/2024] [Indexed: 06/01/2024]
Abstract
PURPOSE Changes in quantitative magnetic resonance imaging (qMRI) are frequently observed during chemotherapy or radiation therapy (RT). It is hypothesized that qMRI features are reflective of underlying tissue responses. It's unknown what underlying genomic characteristics underly qMRI changes. We hypothesized that qMRI changes may correlate with DNA damage response (DDR) capacity within human tumors. Therefore, we designed the current study to correlate qMRI changes from daily RT treatment with underlying tumor transcriptomic profiles. METHODS AND MATERIALS Study participants were prospectively enrolled (National Clinical Trial 03500081). RNA expression levels for 757 genes from pretreatment biopsies were obtained using a custom panel that included signatures of radiation sensitivity and DDR. Daily qMRI data were obtained from a 1.5 Tesla MR linear accelerator. Using these images, d-slow, d-star, perfusion, and apparent diffusion coefficient-mean values in tumors were plotted per-fraction, over time, and associated with genomic pathways. RESULTS A total of 1022 qMRIs were obtained from 39 patients and both genomic data and qMRI data from 27 total patients. For 20 of those patients, we also generated normal tissue transcriptomic data. Radio sensitivity index values most closely associated with tissue of origin. Multiple genomic pathways including DNA repair, peroxisome, late estrogen receptor responses, KRAS signaling, and UV response were significantly associated with qMRI feature changes (P < .001). CONCLUSIONS Genomic pathway associations across metabolic, RT sensitivity, and DDR pathways indicate common tumor biology that may correlate with qMRI changes during a course of treatment. Such data provide hypothesis-generating novel mechanistic insight into the biologic meaning of qMRI changes during treatment and enable optimal selection of imaging biomarkers for biologically MR-guided RT.
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Affiliation(s)
- William A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin.
| | - Angela J Mathison
- Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin; Department of Surgery, Division of Research, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Elias DeVoe
- Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Michael Tschannen
- Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Jaime Wendt-Andrae
- Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Michael Straza
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Musaddiq Awan
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Lindsay L Puckett
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Colleen A F Lawton
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Christopher Schultz
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Raul Urrutia
- Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin; Department of Surgery, Division of Research, Medical College of Wisconsin, Milwaukee, Wisconsin; Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Sarah Kerns
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Javier F Torres-Roca
- Department of Radiation Oncology and Bioinformatics, Moffitt Cancer Center, Tampa, Florida
| | - X Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Beth Erickson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Marja T Nevalainen
- Department of Pathology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Michael T Zimmermann
- Linda T. and John A. Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin; Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin; Clinical and Translational Sciences Institute, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Eric Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
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Nebauer DJ, Pearson LA, Neilan BA. Critical steps in an environmental metaproteomics workflow. Environ Microbiol 2024; 26:e16637. [PMID: 38760994 DOI: 10.1111/1462-2920.16637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 04/30/2024] [Indexed: 05/20/2024]
Abstract
Environmental metaproteomics is a rapidly advancing field that provides insights into the structure, dynamics, and metabolic activity of microbial communities. As the field is still maturing, it lacks consistent workflows, making it challenging for non-expert researchers to navigate. This review aims to introduce the workflow of environmental metaproteomics. It outlines the standard practices for sample collection, processing, and analysis, and offers strategies to overcome the unique challenges presented by common environmental matrices such as soil, freshwater, marine environments, biofilms, sludge, and symbionts. The review also highlights the bottlenecks in data analysis that are specific to metaproteomics samples and provides suggestions for researchers to obtain high-quality datasets. It includes recent benchmarking studies and descriptions of software packages specifically built for metaproteomics analysis. The article is written without assuming the reader's familiarity with single-organism proteomic workflows, making it accessible to those new to proteomics or mass spectrometry in general. This primer for environmental metaproteomics aims to improve accessibility to this exciting technology and empower researchers to tackle challenging and ambitious research questions. While it is primarily a resource for those new to the field, it should also be useful for established researchers looking to streamline or troubleshoot their metaproteomics experiments.
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Affiliation(s)
- Daniel J Nebauer
- School of Environmental and Life Sciences, The University of Newcastle, Callaghan, New South Wales, Australia
- Centre of Excellence in Synthetic Biology, Australian Research Council, Sydney, New South Wales, Australia
| | - Leanne A Pearson
- School of Environmental and Life Sciences, The University of Newcastle, Callaghan, New South Wales, Australia
- Centre of Excellence in Synthetic Biology, Australian Research Council, Sydney, New South Wales, Australia
| | - Brett A Neilan
- School of Environmental and Life Sciences, The University of Newcastle, Callaghan, New South Wales, Australia
- Centre of Excellence in Synthetic Biology, Australian Research Council, Sydney, New South Wales, Australia
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Zhao Y, Yang Z, Wang L, Zhang Y, Lin H, Wang J. Predicting Protein Functions Based on Heterogeneous Graph Attention Technique. IEEE J Biomed Health Inform 2024; 28:2408-2415. [PMID: 38319781 DOI: 10.1109/jbhi.2024.3357834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
In bioinformatics, protein function prediction stands as a fundamental area of research and plays a crucial role in addressing various biological challenges, such as the identification of potential targets for drug discovery and the elucidation of disease mechanisms. However, known functional annotation databases usually provide positive experimental annotations that proteins carry out a given function, and rarely record negative experimental annotations that proteins do not carry out a given function. Therefore, existing computational methods based on deep learning models focus on these positive annotations for prediction and ignore these scarce but informative negative annotations, leading to an underestimation of precision. To address this issue, we introduce a deep learning method that utilizes a heterogeneous graph attention technique. The method first constructs a heterogeneous graph that covers the protein-protein interaction network, ontology structure, and positive and negative annotation information. Then, it learns embedding representations of proteins and ontology terms by using the heterogeneous graph attention technique. Finally, it leverages these learned representations to reconstruct the positive protein-term associations and score unobserved functional annotations. It can enhance the predictive performance by incorporating these known limited negative annotations into the constructed heterogeneous graph. Experimental results on three species (i.e., Human, Mouse, and Arabidopsis) demonstrate that our method can achieve better performance in predicting new protein annotations than state-of-the-art methods.
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7
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Liu Z, Deng C, Zhou Z, Xiao Y, Jiang S, Zhu B, Naler LB, Jia X, Yao DD, Lu C. Epigenomic tomography for probing spatially defined chromatin state in the brain. CELL REPORTS METHODS 2024; 4:100738. [PMID: 38508188 PMCID: PMC10985265 DOI: 10.1016/j.crmeth.2024.100738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 12/24/2023] [Accepted: 02/27/2024] [Indexed: 03/22/2024]
Abstract
Spatially resolved epigenomic profiling is critical for understanding biology in the mammalian brain. Single-cell spatial epigenomic assays were developed recently for this purpose, but they remain costly and labor intensive for examining brain tissues across substantial dimensions and surveying a collection of brain samples. Here, we demonstrate an approach, epigenomic tomography, that maps spatial epigenomes of mouse brain at the scale of centimeters. We individually profiled neuronal and glial fractions of mouse neocortex slices with 0.5 mm thickness. Tri-methylation of histone 3 at lysine 27 (H3K27me3) or acetylation of histone 3 at lysine 27 (H3K27ac) features across these slices were grouped into clusters based on their spatial variation patterns to form epigenomic brain maps. As a proof of principle, our approach reveals striking dynamics in the frontal cortex due to kainic-acid-induced seizure, linked with transmembrane ion transporters, exocytosis of synaptic vesicles, and secretion of neurotransmitters. Epigenomic tomography provides a powerful and cost-effective tool for characterizing brain disorders based on the spatial epigenome.
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Affiliation(s)
- Zhengzhi Liu
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, USA
| | - Chengyu Deng
- Department of Chemical Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Zirui Zhou
- Department of Chemical Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Ya Xiao
- Department of Computer Science, Virginia Tech, Blacksburg, VA, USA
| | - Shan Jiang
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Bohan Zhu
- Department of Chemical Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Lynette B Naler
- Department of Chemical Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Xiaoting Jia
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA
| | | | - Chang Lu
- Department of Chemical Engineering, Virginia Tech, Blacksburg, VA, USA.
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Bhuva DD, Tan CW, Liu N, Whitfield HJ, Papachristos N, Lee SC, Kharbanda M, Mohamed A, Davis MJ. vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis. BMC Bioinformatics 2024; 25:64. [PMID: 38331751 PMCID: PMC10854147 DOI: 10.1186/s12859-024-05676-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 01/26/2024] [Indexed: 02/10/2024] Open
Abstract
Functional analysis of high throughput experiments using pathway analysis is now ubiquitous. Though powerful, these methods often produce thousands of redundant results owing to knowledgebase redundancies upstream. This scale of results hinders extensive exploration by biologists and can lead to investigator biases due to previous knowledge and expectations. To address this issue, we present vissE, a flexible network-based analysis and visualisation tool that organises information into semantic categories and provides various visualisation modules to characterise them with respect to the underlying data, thus providing a comprehensive view of the biological system. We demonstrate vissE's versatility by applying it to three different technologies: bulk, single-cell and spatial transcriptomics. Applying vissE to a factor analysis of a breast cancer spatial transcriptomic data, we identified stromal phenotypes that support tumour dissemination. Its adaptability allows vissE to enhance all existing gene-set enrichment and pathway analysis workflows, empowering biologists during molecular discovery.
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Affiliation(s)
- Dharmesh D Bhuva
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia.
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia.
- South Australian immunoGENomics Cancer Institute (SAiGENCI), Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia.
| | - Chin Wee Tan
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
- Fraser Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD, 4102, Australia
| | - Ning Liu
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
- South Australian immunoGENomics Cancer Institute (SAiGENCI), Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia
| | - Holly J Whitfield
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
- Wellcome Sanger Institute, Hinxton, UK
| | - Nicholas Papachristos
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Samuel C Lee
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
| | - Malvika Kharbanda
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
- South Australian immunoGENomics Cancer Institute (SAiGENCI), Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia
| | - Ahmed Mohamed
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
- Colonial Foundation Healthy Ageing Centre, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
| | - Melissa J Davis
- Division of Bioinformatics, Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, 3052, Australia
- Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
- South Australian immunoGENomics Cancer Institute (SAiGENCI), Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia
- Fraser Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD, 4102, Australia
- Department of Clinical Pathology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, 3010, Australia
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9
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Pasqui A, Cicaloni V, Tinti L, Guiotto A, Tinti C, Mori A, Bruttini M, Hayek J, Pecorelli A, Salvini L, Valacchi G. A proteomic approach to investigate the role of the MECP2 gene mutation in Rett syndrome redox regulatory pathways. Arch Biochem Biophys 2024; 752:109860. [PMID: 38110111 DOI: 10.1016/j.abb.2023.109860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/11/2023] [Accepted: 12/11/2023] [Indexed: 12/20/2023]
Abstract
Mutations in the X-linked methyl-CpG-binding 2 (MECP2) gene lead to Rett Syndrome (RTT; OMIM 312750), a devasting neurodevelopmental disorder. RTT clinical manifestations are complex and with different degrees of severity, going from autistic-like behavior to loss of acquired speech, motor skills and cardiac problems. Furthermore, the correlation between the type of MECP2 mutation and the clinical phenotype is still not fully understood. Contextually, different genotypes can differently affect the patient's phenotype and omics methodologies such as proteomics could be an important tool for a molecular characterization of genotype/phenotype correlation. The aim of our study was focused on evaluating RTT oxidative stress (OS) responses related to specific MECP2 gene mutations by using proteomics and bioinformatics approaches. Primary fibroblasts isolated from patients affected by R133C and R255× mutations were compared to healthy controls (HC). After clustering primary dermal fibroblasts based on their specific MECP2 mutations, fibroblast-derived protein samples were qualitative and quantitative analyzed, using a label free quantification (LFQ) analysis by mass spectrometry (MS), achieving a preliminary correlation for RTT genotype/phenotype. Among the identified proteins involved in redox regulation pathways, NAD(P)H:quinone acceptor oxidoreductase 1 (NQO1) was found to be absent in R255× cells, while it was present in R133C and in HC fibroblasts. Moreover, NQO1 aberrant gene regulation was also confirmed when cells were challenged with 100 μM hydrogen peroxide (H2O2). In conclusion, by employing a multidisciplinary approach encompassing proteomics and bioinformatics analyses, as well as molecular biology assays, the study uncovered phenotypic responses linked to specific MECP2 gene mutations. These findings contribute to a better understanding of the complexity of RTT molecular pathways, confirming the high heterogeneity among the patients.
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Affiliation(s)
- Arianna Pasqui
- Toscana Life Science Foundation, Siena, Italy; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, 53100 Siena, Italy
| | | | - Laura Tinti
- Toscana Life Science Foundation, Siena, Italy
| | - Anna Guiotto
- Plants for Human Health Institute, Animal Science Department, North Carolina State University, North Carolina Research Campus, Kannapolis, NC 28081, USA; Department of Environmental and Prevention Sciences, University of Ferrara, 44121 Ferrara, Italy
| | | | - Alessia Mori
- Diabetes Unit, Department of Medicine, Surgery and Neurosciences, University of Siena Italy; Fondazione Umberto Di Mario ONLUS c/o Toscana Life Science, Siena, Italy; Tuscany Centre for Precision Medicine (CReMeP), Siena 53100, Italy
| | - Marco Bruttini
- Diabetes Unit, Department of Medicine, Surgery and Neurosciences, University of Siena Italy; Fondazione Umberto Di Mario ONLUS c/o Toscana Life Science, Siena, Italy; Tuscany Centre for Precision Medicine (CReMeP), Siena 53100, Italy
| | | | - Alessandra Pecorelli
- Plants for Human Health Institute, Animal Science Department, North Carolina State University, North Carolina Research Campus, Kannapolis, NC 28081, USA; Department of Environmental and Prevention Sciences, University of Ferrara, 44121 Ferrara, Italy.
| | | | - Giuseppe Valacchi
- Plants for Human Health Institute, Animal Science Department, North Carolina State University, North Carolina Research Campus, Kannapolis, NC 28081, USA; Department of Environmental and Prevention Sciences, University of Ferrara, 44121 Ferrara, Italy; Department of Food and Nutrition, Kyung Hee University, Seoul 02447, Republic of Korea.
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10
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Hamamsy T, Barot M, Morton JT, Steinegger M, Bonneau R, Cho K. Learning sequence, structure, and function representations of proteins with language models. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.26.568742. [PMID: 38045331 PMCID: PMC10690258 DOI: 10.1101/2023.11.26.568742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
The sequence-structure-function relationships that ultimately generate the diversity of extant observed proteins is complex, as proteins bridge the gap between multiple informational and physical scales involved in nearly all cellular processes. One limitation of existing protein annotation databases such as UniProt is that less than 1% of proteins have experimentally verified functions, and computational methods are needed to fill in the missing information. Here, we demonstrate that a multi-aspect framework based on protein language models can learn sequence-structure-function representations of amino acid sequences, and can provide the foundation for sensitive sequence-structure-function aware protein sequence search and annotation. Based on this model, we introduce a multi-aspect information retrieval system for proteins, Protein-Vec, covering sequence, structure, and function aspects, that enables computational protein annotation and function prediction at tree-of-life scales.
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11
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Xue Z, Wu D, Zhang J, Pan Y, Kan R, Gao J, Zhou B. Protective effect and mechanism of procyanidin B2 against hypoxic injury of cardiomyocytes. Heliyon 2023; 9:e21309. [PMID: 37885736 PMCID: PMC10598540 DOI: 10.1016/j.heliyon.2023.e21309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 10/18/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023] Open
Abstract
Background Cardiomyocyte ischemia and hypoxia are important causes of oxidative stress damage and cardiomyocyte apoptosis in coronary heart disease (CHD). Epidemiological investigation has shown that eating more plant-based foods, such as vegetables and fruits, may significantly decrease the risk of CHD. As natural antioxidants, botanicals have fewer toxic side effects than chemical drugs and have great potential for development. Procyanidin B2 (PB2) is composed of flavan-3-ol and epicatechin and has been reported to have antioxidant and anti-inflammatory effects. However, whether PB2 exerts protective effects on hypoxic cardiomyocytes has remained unclear. This study aimed to explore the protective effect of PB2 against cardiomyocyte hypoxia and to provide new treatment strategies and ideas for myocardial ischemia and hypoxia in CHD. Methods and results A hypoxic cardiomyocyte model was constructed, and a CCK-8 assay proved that PB2 had a protective effect on cardiomyocytes in a hypoxic environment. DCFH fluorescence staining, DHE staining, and BODIPY lipid oxidation assessment revealed that PB2 reduced the oxidative stress levels of cardiomyocytes under hypoxic conditions. TUNEL staining, Annexin V/PI fluorescence flow cytometry, and Western blot analysis of the expression of the apoptosis marker protein cleaved caspase-3 confirmed that PB2 reduced cardiomyocyte apoptosis under hypoxic conditions. JC-1 staining indicated that PB2 reduced the mitochondrial membrane potential of cardiomyocytes under hypoxia. In addition, transcriptomic analysis proved that the expression of 158 genes in cardiomyocytes was significantly changed after PB2 was added during hypoxia, of which 53 genes were upregulated and 105 genes were downregulated. GO enrichment analysis demonstrated that the activity of cytokines, extracellular matrix proteins and other molecules was changed significantly in the biological process category. KEGG enrichment analysis showed that the IL-17 signaling pathway and JAK-STAT signaling pathway underwent significant changes. We also performed metabolomic analysis and found that the levels of 51 metabolites were significantly changed after the addition of PB2 to cardiomyocytes during hypoxia. Among them, 39 metabolites exhibited increased levels, while 12 metabolites exhibited decreased levels. KEGG enrichment analysis showed that cysteine and methionine metabolism, arginine and proline metabolism and other metabolic pathways underwent remarkable changes. Conclusion This study proves that PB2 can reduce the oxidative stress and apoptosis of cardiomyocytes during hypoxia to play a protective role. Transcriptomic and metabolomic analyses preliminarily revealed signaling pathways and metabolic pathways that are related to its protective mechanism. These findings lay a foundation for further research on the role of PB2 in the treatment of CHD and provide new ideas and new perspectives for research on PB2 in the treatment of other diseases.
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Affiliation(s)
- Zhimin Xue
- Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Danyu Wu
- Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiefang Zhang
- Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yiwen Pan
- Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Rongsheng Kan
- Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Gao
- Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Binquan Zhou
- Department of Cardiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
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12
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Nguyen TM, Craig DB, Tran D, Nguyen T, Draghici S. A novel approach for predicting upstream regulators (PURE) that affect gene expression. Sci Rep 2023; 13:18571. [PMID: 37903768 PMCID: PMC10616115 DOI: 10.1038/s41598-023-41374-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 08/25/2023] [Indexed: 11/01/2023] Open
Abstract
External factors such as exposure to a chemical, drug, or toxicant (CDT), or conversely, the lack of certain chemicals can cause many diseases. The ability to identify such causal CDTs based on changes in the gene expression profile is extremely important in many studies. Furthermore, the ability to correctly infer CDTs that can revert the gene expression changes induced by a given disease phenotype is a crucial step in drug repurposing. We present an approach for Predicting Upstream REgulators (PURE) designed to tackle this challenge. PURE can correctly infer a CDT from the measured expression changes in a given phenotype, as well as correctly identify drugs that could revert disease-induced gene expression changes. We compared the proposed approach with four classical approaches as well as with the causal analysis used in Ingenuity Pathway Analysis (IPA) on 16 data sets (1 rat, 5 mouse, and 10 human data sets), involving 8 chemicals or drugs. We assessed the results based on the ability to correctly identify the CDT as indicated by its rank. We also considered the number of false positives, i.e. CDTs other than the correct CDT that were reported to be significant by each method. The proposed approach performed best in 11 out of the 16 experiments, reporting the correct CDT at the very top 7 times. IPA was the second best, reporting the correct CDT at the top 5 times, but was unable to identify the correct CDT at all in 5 out of the 16 experiments. The validation results showed that our approach, PURE, outperformed some of the most popular methods in the field. PURE could effectively infer the true CDTs responsible for the observed gene expression changes and could also be useful in drug repurposing applications.
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Affiliation(s)
- Tuan-Minh Nguyen
- Department of Computer Science, Wayne State University, Detroit, 48202, USA
| | - Douglas B Craig
- Department of Computer Science, Wayne State University, Detroit, 48202, USA
- Department of Oncology, School of Medicine, Wayne State University, Detroit, MI, 48201, USA
| | - Duc Tran
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Tin Nguyen
- Department of Computer Science and Software Engineering, Auburn University, Auburn, 36849, USA
| | - Sorin Draghici
- Department of Computer Science, Wayne State University, Detroit, 48202, USA.
- Advaita Bioinformatics, Ann Arbor, MI, 48105, USA.
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Myszka K, Tomaś N, Wolko Ł. Gallic and ferulic acids suppress proteolytic activities and volatile trimethylamine production in the food-borne spoiler Rahnella aquatilis KM05. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2023; 103:6584-6594. [PMID: 37245214 DOI: 10.1002/jsfa.12753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 04/20/2023] [Accepted: 05/28/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND Rahnella aquatilis is a recognised microbial threat that alters the sensory properties of seafood. The high frequency with which R. aquatilis is isolated from fish has prompted a search for alternative preservatives. In the present study, in vitro and fish-based ecosystem (raw salmon-based medium) approaches were used to validate the antimicrobial effects of gallic (GA) and ferulic (FA) acids against R. aquatilis KM05. The results were compared with data describing the response of KM05 to sodium benzoate. Bioinformatics data of the whole genome were used to analyse the potential for fish spoilage by KM05 in detail, and the results revealed the main physiological characteristics that underlie reduced seafood quality. RESULTS In the KM05 genome, the most abundantly enriched Gene Ontology terms were 'metabolic process', 'organic substance metabolic process' and 'cellular process'. Through an evaluation of the Pfam annotations, 15 annotations were found to be directly involved in the proteolytic activity of KM05. Peptidase_M20 was the most abundantly represented (abundance value of 14060). Proteins representing the CutC family (abundance value of 427) indicated the potential for KM05 degradation of trimethyl-amine-N-oxide. Subinhibitory concentrations of GA and FA suppressed the proteolytic activities of KM05 both in vitro and in RS medium by an average of 33-45%. These results were confirmed by quantitative real-time PCR experiments, which also showed that the expression levels of genes involved in proteolytic activities and volatile trimethylamine production were also decreased. CONCLUSION Phenolic compounds can be used as potential food additives for preventing quality deterioration of fish products. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Kamila Myszka
- Department of Biotechnology and Food Microbiology, Poznan University of Life Sciences, Poznan, Poland
| | - Natalia Tomaś
- Department of Biotechnology and Food Microbiology, Poznan University of Life Sciences, Poznan, Poland
| | - Łukasz Wolko
- Department of Biochemistry and Biotechnology, Poznan University of Life Sciences, Poznan, Poland
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14
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Flores-Díaz A, Escoto-Sandoval C, Cervantes-Hernández F, Ordaz-Ortiz JJ, Hayano-Kanashiro C, Reyes-Valdés H, Garcés-Claver A, Ochoa-Alejo N, Martínez O. Gene Functional Networks from Time Expression Profiles: A Constructive Approach Demonstrated in Chili Pepper ( Capsicum annuum L.). PLANTS (BASEL, SWITZERLAND) 2023; 12:1148. [PMID: 36904008 PMCID: PMC10005043 DOI: 10.3390/plants12051148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/20/2023] [Accepted: 02/27/2023] [Indexed: 06/18/2023]
Abstract
Gene co-expression networks are powerful tools to understand functional interactions between genes. However, large co-expression networks are difficult to interpret and do not guarantee that the relations found will be true for different genotypes. Statistically verified time expression profiles give information about significant changes in expressions through time, and genes with highly correlated time expression profiles, which are annotated in the same biological process, are likely to be functionally connected. A method to obtain robust networks of functionally related genes will be useful to understand the complexity of the transcriptome, leading to biologically relevant insights. We present an algorithm to construct gene functional networks for genes annotated in a given biological process or other aspects of interest. We assume that there are genome-wide time expression profiles for a set of representative genotypes of the species of interest. The method is based on the correlation of time expression profiles, bound by a set of thresholds that assure both, a given false discovery rate, and the discard of correlation outliers. The novelty of the method consists in that a gene expression relation must be repeatedly found in a given set of independent genotypes to be considered valid. This automatically discards relations particular to specific genotypes, assuring a network robustness, which can be set a priori. Additionally, we present an algorithm to find transcription factors candidates for regulating hub genes within a network. The algorithms are demonstrated with data from a large experiment studying gene expression during the development of the fruit in a diverse set of chili pepper genotypes. The algorithm is implemented and demonstrated in a new version of the publicly available R package "Salsa" (version 1.0).
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Affiliation(s)
- Alan Flores-Díaz
- Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
| | - Christian Escoto-Sandoval
- Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
| | - Felipe Cervantes-Hernández
- Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
| | - José J. Ordaz-Ortiz
- Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
| | - Corina Hayano-Kanashiro
- Departamento de Investigaciones Científicas y Tecnológicas de la Universidad de Sonora, Hermosillo 83000, Mexico
| | - Humberto Reyes-Valdés
- Department of Plant Breeding, Universidad Autónoma Agraria Antonio Narro, Saltillo 25315, Mexico
| | - Ana Garcés-Claver
- Unidad de Hortofruticultura, Centro de Investigación y Tecnología Agroalimentaria de Aragón, Instituto Agroalimentario de Aragón-IA2 (CITA-Universidad de Zaragoza), 50059 Zaragoza, Spain
| | - Neftalí Ochoa-Alejo
- Departamento de Ingeniería Genética, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
| | - Octavio Martínez
- Unidad de Genómica Avanzada (Langebio), Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Cinvestav), Irapuato 36824, Mexico
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15
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Automated SSHHPS Analysis Predicts a Potential Host Protein Target Common to Several Neuroinvasive (+)ssRNA Viruses. Viruses 2023; 15:v15020542. [PMID: 36851756 PMCID: PMC9961674 DOI: 10.3390/v15020542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/24/2023] [Accepted: 02/01/2023] [Indexed: 02/18/2023] Open
Abstract
Within the viral genome, short stretches of homologous host pathogen sequences (SSHHPS) span the protease cleavage sites. To identify host proteins that may be cleaved during infection, we searched the human proteome for viral protease cleavage sites (~20 amino acids). We developed a sequence-to-symptom tool, automating the search and pairing process. We used the viral protein sequence, PHI-BLAST, and UniProt database for gene ontologies and disease relationships. We applied the tool to nine neuroinvasive viruses: Venezuelan and Eastern Equine encephalitis virus (VEEV, EEEV); severe acute respiratory syndrome (SARS, SARS-CoV-2); Middle East respiratory syndrome (MERS); EV-71; Japanese encephalitis virus (JEV); West Nile (WNV); and Zika (ZIKV). A comparison of the hits identified a protein common to all nine viruses called ADGRA2 (GPR124). ADGRA2 was a predicted hit of the 3CL main protease and papain-like protease (PLpro) of SARS-CoV-2. ADGRA2 is an adhesion G protein-coupled receptor and a key endothelial regulator of brain-specific angiogenesis. It is a Wnt7A/Wnt7B specific coactivator of beta-catenin signaling and is essential for blood-brain barrier (BBB) integrity in central nervous system (CNS) diseases. We show the cleavage of the predicted sequences in MYOM1, VWF by the SARS-CoV-2 PLpro; DNAH8 (dynein) by the MERS PLpro; ADGRA2 by the alphaviral VEEV nsP2 protease; and POT1 by the SARS-CoV-2 and MERS PLpro.
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16
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Ai H, Meng F, Ai Y. PathwayKO: An integrated platform for deciphering the systems-level signaling pathways. Front Immunol 2023; 14:1103392. [PMID: 37033947 PMCID: PMC10080220 DOI: 10.3389/fimmu.2023.1103392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 03/01/2023] [Indexed: 04/11/2023] Open
Abstract
Systems characterization of immune landscapes in health, disease and clinical intervention cases is a priority in modern medicine. High-throughput transcriptomes accumulated from gene-knockout (KO) experiments are crucial for deciphering target KO signaling pathways that are impaired by KO genes at the systems-level. There is a demand for integrative platforms. This article describes the PathwayKO platform, which has integrated state-of-the-art methods of pathway enrichment analysis, statistics analysis, and visualizing analysis to conduct cutting-edge integrative pathway analysis in a pipeline fashion and decipher target KO signaling pathways at the systems-level. We focus on describing the methodology, principles and application features of PathwayKO. First, we demonstrate that the PathwayKO platform can be utilized to comprehensively analyze real-world mouse KO transcriptomes (GSE22873 and GSE24327), which reveal systemic mechanisms underlying the innate immune responses triggered by non-infectious extensive hepatectomy (2 hours after 85% liver resection surgery) and infectious CASP-model sepsis (12 hours after CASP-model surgery). Strikingly, our results indicate that both cases hit the same core set of 21 KO MyD88-associated signaling pathways, including the Toll-like receptor signaling pathway, the NFκB signaling pathway, the MAPK signaling pathway, and the PD-L1 expression and PD-1 checkpoint pathway in cancer, alongside the pathways of bacterial, viral and parasitic infections. These findings suggest common fundamental mechanisms between these immune responses and offer informative cues that warrant future experimental validation. Such mechanisms in mice may serve as models for humans and ultimately guide formulating the research paradigms and composite strategies to reduce the high mortality rates of patients in intensive care units who have undergone successful traumatic surgical treatments. Second, we demonstrate that the PathwayKO platform model-based assessments can effectively evaluate the performance difference of pathway analysis methods when benchmarked with a collection of proper transcriptomes. Together, such advances in methods for deciphering biological insights at the systems-level may benefit the fields of bioinformatics, systems immunology and beyond.
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Affiliation(s)
- Hannan Ai
- State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Department of Electrical and Computer Engineering, The Grainger College of Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States
- National Center for Quality Supervision and Inspection of Automatic Equipment, National Center for Testing and Evaluation of Robots (Guangzhou), CRAT, SINOMACH-IT, Guangzhou, China
- *Correspondence: Hannan Ai, ; Yuncan Ai, .cn
| | - Fanmei Meng
- State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Yuncan Ai
- State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- The Second Affiliated Hospital, Guangdong Provincial Key Laboratory of Allergy & Clinical Immunology, Center for Inflammation, Immunity & Immune-mediated Disease, Sino-French Hoffmann Institute, Guangzhou Medical University, Guangzhou, Guangdong, China
- *Correspondence: Hannan Ai, ; Yuncan Ai, .cn
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17
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Fedorova AD, Kiniry SJ, Andreev DE, Mudge JM, Baranov PV. Thousands of human non-AUG extended proteoforms lack evidence of evolutionary selection among mammals. Nat Commun 2022; 13:7910. [PMID: 36564405 PMCID: PMC9789052 DOI: 10.1038/s41467-022-35595-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
The synthesis of most proteins begins at AUG codons, yet a small number of non-AUG initiated proteoforms are also known. Here we analyse a large number of publicly available Ribo-seq datasets to identify novel, previously uncharacterised non-AUG proteoforms using Trips-Viz implementation of a novel algorithm for detecting translated ORFs. In parallel we analyse genomic alignment of 120 mammals to identify evidence of protein coding evolution in sequences encoding potential extensions. Unexpectedly we find that the number of non-AUG proteoforms identified with ribosome profiling data greatly exceeds those with strong phylogenetic support suggesting their recent evolution. Our study argues that the protein coding potential of human genome greatly exceeds that detectable through comparative genomics and exposes the existence of multiple proteins encoded by the same genomic loci.
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Affiliation(s)
- Alla D Fedorova
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland.
- SFI Centre for Research Training in Genomics Data Science, University College Cork, Cork, Ireland.
| | - Stephen J Kiniry
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland
| | - Dmitry E Andreev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, RAS, Moscow, Russia
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Pavel V Baranov
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland.
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18
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García S. A, Costa M, Leon A, Pastor O. The challenge of managing the evolution of genomics data over time: a conceptual model-based approach. BMC Bioinformatics 2022; 23:472. [PMID: 36352353 PMCID: PMC9648044 DOI: 10.1186/s12859-022-04944-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 09/16/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Precision medicine is a promising approach that has revolutionized disease prevention and individualized treatment. The DELFOS oracle is a model-driven genomics platform that aids clinicians in identifying relevant variations that are associated with diseases. In its previous version, the DELFOS oracle did not consider the high degree of variability of genomics data over time. However, changes in genomics data have had a profound impact on clinicians' work and pose the need for changing past, present, and future clinical actions. Therefore, our objective in this work is to consider changes in genomics data over time in the DELFOS oracle. METHODS Our objective has been achieved through three steps. First, we studied the characteristics of each database from which the DELFOS oracle extracts data. Second, we characterized which genomics concepts of the conceptual schema that supports the DELFOS oracle change over time. Third, we updated the DELFOS Oracle so that it can manage the temporal dimension. To validate our approach, we carried out a use case to illustrate how the new version of the DELFOS oracle handles the temporal dimension. RESULTS Three events can change genomics data, namely, the addition of a new variation, the addition of a new link between a variation and a phenotype, and the update of a link between a variation and a phenotype. These events have been linked to the entities of the conceptual model that are affected by them. Finally, a new version of the DELFOS oracle that can deal with the temporal dimension has been implemented. CONCLUSION Huge amounts of genomics data that is associated with diseases change over time, impacting patients' diagnosis and treatment. Including this information in the DELFOS oracle added an extra layer of complexity, but using a model-driven based approach mitigated the cost of implementing the needed changes. The new version handles the temporal dimension appropriately and eases clinicians' work.
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Affiliation(s)
- Alberto García S.
- PROS Research Center, VRAIN Research Institute, Universitat Politècnica de València, Camino de Vera, Valencia, Spain
| | - Mireia Costa
- PROS Research Center, VRAIN Research Institute, Universitat Politècnica de València, Camino de Vera, Valencia, Spain
| | - Ana Leon
- PROS Research Center, VRAIN Research Institute, Universitat Politècnica de València, Camino de Vera, Valencia, Spain
| | - Oscar Pastor
- PROS Research Center, VRAIN Research Institute, Universitat Politècnica de València, Camino de Vera, Valencia, Spain
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Laghezza Masci V, Bernini R, Villanova N, Clemente M, Cicaloni V, Tinti L, Salvini L, Taddei AR, Tiezzi A, Ovidi E. In Vitro Anti-Proliferative and Apoptotic Effects of Hydroxytyrosyl Oleate on SH-SY5Y Human Neuroblastoma Cells. Int J Mol Sci 2022; 23:ijms232012348. [PMID: 36293207 PMCID: PMC9604296 DOI: 10.3390/ijms232012348] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 10/11/2022] [Accepted: 10/12/2022] [Indexed: 11/24/2022] Open
Abstract
The antitumor activity of polyphenols derived from extra virgin olive oil and, in particular the biological activity of HTyr, has been studied extensively. However, the use of HTyr as a therapeutic agent for clinical applications is limited by its low bioavailability and rapid excretion in humans. To overcome these limitations, several synthetic strategies have been optimized to prepare lipophenols and new compounds derived from HTyr to increase lipophilicity and bioavailability. One very promising ester is hydroxytyrosyl oleate (HTyr-OL) because the chemical structure of HTyr, which is responsible for several biological activities, is linked to the monounsaturated chain of oleic acid (OA), giving the compound high lipophilicity and thus bioavailability in the cellular environment. In this study, the in vitro cytotoxic, anti-proliferative, and apoptotic induction activities of HTyr-OL were evaluated against SH-SY5Y human neuroblastoma cells, and the effects were compared with those of HTyr and OA. The results showed that the biological activity of HTyr was maintained in HTyr-OL treatments at lower dosages. In addition, the shotgun proteomic approach was used to study HTyr-OL-treated and untreated neuroblastoma cells, revealing that the antioxidant, anti-proliferative and anti-inflammatory activities of HTyr-OL were observed in the unique proteins of the two groups of samples.
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Affiliation(s)
- Valentina Laghezza Masci
- Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, Largo dell’Università, 01100 Viterbo, Italy
| | - Roberta Bernini
- Department of Agriculture and Forest Sciences (DAFNE), University of Tuscia, Via San Camillo de Lellis snc, 01100 Viterbo, Italy
- Correspondence:
| | - Noemi Villanova
- Department of Agriculture and Forest Sciences (DAFNE), University of Tuscia, Via San Camillo de Lellis snc, 01100 Viterbo, Italy
| | - Mariangela Clemente
- Department of Agriculture and Forest Sciences (DAFNE), University of Tuscia, Via San Camillo de Lellis snc, 01100 Viterbo, Italy
| | - Vittoria Cicaloni
- Toscana Life Science Foundation, Via Fiorentina 1, 53100 Siena, Italy
| | - Laura Tinti
- Toscana Life Science Foundation, Via Fiorentina 1, 53100 Siena, Italy
| | - Laura Salvini
- Toscana Life Science Foundation, Via Fiorentina 1, 53100 Siena, Italy
| | - Anna Rita Taddei
- High Equipment Centre, Tuscia University, Largo dell’Università snc, 01100 Viterbo, Italy
| | - Antonio Tiezzi
- Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, Largo dell’Università, 01100 Viterbo, Italy
| | - Elisa Ovidi
- Department for Innovation in Biological, Agro-Food and Forest Systems (DIBAF), University of Tuscia, Largo dell’Università, 01100 Viterbo, Italy
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20
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Chang EH, Pouladi N, Guerra S, Jandova J, Kim A, Li H, Li J, Morgan W, Stern DA, Willis AL, Lussier YA, Martinez FD. Epithelial cell responses to rhinovirus identify an early-life-onset asthma phenotype in adults. J Allergy Clin Immunol 2022; 150:604-611. [PMID: 35367470 PMCID: PMC9463086 DOI: 10.1016/j.jaci.2022.03.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 02/15/2022] [Accepted: 03/24/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND The study of pathogenic mechanisms in adult asthma is often marred by a lack of precise information about the natural history of the disease. Children who have persistent wheezing (PW) during the first 6 years of life and whose symptoms start before age 3 years (PW+) are much more likely to have wheezing illnesses due to rhinovirus (RV) in infancy and to have asthma into adult life than are those who do not have PW (PW-). OBJECTIVE Our aim was to determine whether nasal epithelial cells from PW+ asthmatic adults as compared with cells from PW- asthmatic adults show distinct biomechanistic processes activated by RV exposure. METHODS Air-liquid interface cultures derived from nasal epithelial cells of 36-year old participants with active asthma with and without a history of PW in childhood (10 PW+ participants and 20 PW- participants) from the Tucson Children's Respiratory Study were challenged with a human RV-A strain (RV-A16) or control, and their RNA was sequenced. RESULTS A total of 35 differentially expressed genes involved in extracellular remodeling and angiogenesis distinguished the PW+ group from the PW- group at baseline and after RV-A stimulation. Notably, 22 transcriptomic pathways showed PW-by-RV interactions; the pathways were invariably overactivated in PW+ patients, and were involved in Toll-like receptor- and cytokine-mediated responses, remodeling, and angiogenic processes. CONCLUSIONS Asthmatic adults with a history of persistent wheeze in the first 6 years of life have specific biomolecular alterations in response to RV-A that are not present in patients without such a history. Targeting these mechanisms may slow the progression of asthma in these patients.
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Affiliation(s)
- Eugene H Chang
- Department of Otolaryngology, University of Arizona, Tucson, Arizona
- College of Medicine, University of Arizona, Tucson, Arizona
- Asthma / Airway Disease Research Center, University of Arizona, Tucson, Arizona
- The University of Arizona BIO5 Institute, University of Arizona, Tucson, Arizona
| | - Nima Pouladi
- Department of Biomedical Informatics, The University of Utah School of Medicine, Salt Lake City, UT
| | - Stefano Guerra
- College of Medicine, University of Arizona, Tucson, Arizona
- Asthma / Airway Disease Research Center, University of Arizona, Tucson, Arizona
- The University of Arizona BIO5 Institute, University of Arizona, Tucson, Arizona
| | - Jana Jandova
- Department of Otolaryngology, University of Arizona, Tucson, Arizona
| | - Alexander Kim
- Department of Otolaryngology, University of Arizona, Tucson, Arizona
| | - Haiquan Li
- The University of Arizona BIO5 Institute, University of Arizona, Tucson, Arizona
| | - Jianrong Li
- Department of Biomedical Informatics, The University of Utah School of Medicine, Salt Lake City, UT
| | - Wayne Morgan
- College of Medicine, University of Arizona, Tucson, Arizona
- Asthma / Airway Disease Research Center, University of Arizona, Tucson, Arizona
- The University of Arizona BIO5 Institute, University of Arizona, Tucson, Arizona
| | - Debra A Stern
- College of Medicine, University of Arizona, Tucson, Arizona
- Asthma / Airway Disease Research Center, University of Arizona, Tucson, Arizona
- The University of Arizona BIO5 Institute, University of Arizona, Tucson, Arizona
| | - Amanda L Willis
- Department of Otolaryngology, University of Arizona, Tucson, Arizona
| | - Yves A. Lussier
- Department of Biomedical Informatics, The University of Utah School of Medicine, Salt Lake City, UT
| | - Fernando D Martinez
- College of Medicine, University of Arizona, Tucson, Arizona
- Asthma / Airway Disease Research Center, University of Arizona, Tucson, Arizona
- The University of Arizona BIO5 Institute, University of Arizona, Tucson, Arizona
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21
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Silk T, Dipnall L, Wong YT, Craig JM. Epigenetics and ADHD. Curr Top Behav Neurosci 2022; 57:269-289. [PMID: 35505060 DOI: 10.1007/7854_2022_339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
There is robust evidence of genetic susceptibility to Attention-Deficit Hyperactivity Disorder (ADHD); however, there still remains significant variability that is not attributable to genetic factors. The emerging field of epigenetics is beginning to reveal how genotypic expression can be mediated by an array of variables including external environmental exposure, inter-individual developmental variation, and by the genome itself. Epigenetic modification plays a central role in neurobiological and developmental processes, and disturbances to these processes can have implications for a range of mental health problems. Although the field is still in its early days, this chapter will discuss the current standing of epigenetic research into ADHD. Firstly, key relevant epigenetic processes will be discussed. This will be followed by an overview of the key findings to date investigating the role of epigenetics in ADHD. Human studies have included the theory-driven approach of candidate-gene studies (CGS), as well as the increasingly popular exploratory approach of epigenome-wide association studies (EWAS). Overall, the findings are heterogeneous. However, it is possible that with more longitudinal studies and better characterised cohorts, both predictive and protective links between epigenetic processes and ADHD will be revealed.
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Affiliation(s)
- Timothy Silk
- Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Geelong, VIC, Australia. .,Murdoch Children's Research Institute, Parkville, VIC, Australia.
| | - Lillian Dipnall
- Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Geelong, VIC, Australia
| | - Yen Ting Wong
- Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Jeffrey M Craig
- Murdoch Children's Research Institute, Parkville, VIC, Australia.,Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Geelong, VIC, Australia
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22
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Liu Z, Wang J, Chen H, Wu Z, Liao F, Wang S, Zhu T. Uncovering BTB and CNC Homology1 (BACH1) as a Novel Cancer Therapeutic Target. Front Genet 2022; 13:920911. [PMID: 35651942 PMCID: PMC9149251 DOI: 10.3389/fgene.2022.920911] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 05/02/2022] [Indexed: 12/01/2022] Open
Abstract
BTB and CNC homology1 (BACH1), working as a transcriptional factor, is demonstrated to function on the regulation of epigenetic modifications by complex regulatory networks. Although BACH1 is reported as an oncogene, the overall analysis of its role remains lacking. In this study, we uncovered the capacity of BACH1 as a new pan-cancer therapeutic target. We found that BACH1 is highly expressed in abundant cancers and correlated with the poor prognosis of most cancers. The mutation sites of BACH1 varied in different cancer types and correlated to patients’ prognoses. The tumor mutation burden (TMB) in four cancer species and up to six tumor infiltrated immune cells had a significant relevance with BACH1. The enrichment analysis showed that the BACH1-associated genes were significantly enriched in the pathways of PD-1/L1 expression, ubiquitin-mediated proteolysis, T cell receptor, Th17 cell differentiation. We then demonstrated that BACH1 is positively correlated with the expression of many candidate genes, incluing SRPK2, GCLM, SLC40A1, and HK2 but negatively correlated with the expression of KEAP1 and GAPDH. Overall, our data shed light on BACH1’s effect on latent utility in cancer targeting therapy.
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Affiliation(s)
- Zheming Liu
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jing Wang
- Reproductive Medicine Centre, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Huiyong Chen
- Department of Rheumatology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zankai Wu
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Fuben Liao
- Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Sheng Wang
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Ting Zhu
- Department of Otolaryngology-Head and Neck Surgery, Renmin Hospital of Wuhan University, Wuhan, China
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23
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Delayed processing of blood samples impairs the accuracy of mRNA-based biomarkers. Sci Rep 2022; 12:8196. [PMID: 35581252 PMCID: PMC9113984 DOI: 10.1038/s41598-022-12178-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 05/03/2022] [Indexed: 11/29/2022] Open
Abstract
The transcriptome of peripheral white blood cells (PWBCs) are indicators of an organism’s physiological state, thus making them a prime biological sample for mRNA-based biomarker discovery. Here, we designed an experiment to evaluate the impact of delayed processing of whole blood samples on gene transcript abundance in PWBCs. We hypothesized that storing blood samples for 24 h at 4 °C would cause RNA degradation resulting in altered transcriptome profiles. There were no statistical differences in RNA quality parameters among samples processed after one, three, six, or eight hours post collection. Additionally, no significant differences were noted in RNA quality parameters or gene transcript abundance between samples collected from the jugular and coccygeal veins. However, samples processed after 24 h of storage had a lower RNA integrity number value (P = 0.03) in comparison to those processed after one hour of storage. Using RNA-sequencing, we identified four and 515 genes with differential transcript abundance in samples processed after storage for eight and 24 h, respectively, relative to samples processed after one hour. Sequencing coverage of transcripts was similar between samples from the 24-h and one-hour groups, thus showing no indication of RNA degradation. This alteration in transcriptome profiles can impair the accuracy of mRNA-based biomarkers, therefore, blood samples collected for mRNA-based biomarker discovery should be refrigerated immediately and processed within six hours post-sampling.
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24
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Tomaś N, Myszka K, Wolko Ł. Black pepper and tarragon essential oils suppress the lipolytic potential and the type II secretion system of P. psychrophila KM02. Sci Rep 2022; 12:5487. [PMID: 35361821 PMCID: PMC8971419 DOI: 10.1038/s41598-022-09311-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/21/2022] [Indexed: 12/01/2022] Open
Abstract
Given the increasing consumer demand for raw, nonprocessed, safe, and long shelf-life fish and seafood products, research concerning the application of natural antimicrobials as alternatives to preservatives is of great interest. The aim of the following paper was to evaluate the effect of essential oils (EOs) from black pepper (BPEO) and tarragon (TEO), and their bioactive compounds: limonene (LIM), β-caryophyllene (CAR), methyl eugenol (ME), and β-phellandrene (PHE) on the lipolytic activity and type II secretion system (T2SS) of Pseudomonas psychrophila KM02 (KM02) fish isolates grown in vitro and in fish model conditions. Spectrophotometric analysis with the p-NPP reagent showed inhibition of lipolysis from 11 to 46%. These results were confirmed by RT-qPCR, as the expression levels of lipA, lipB, and genes encoding T2SS were also considerably decreased. The supplementation of marinade with BPEO and TEO contributed to KM02 growth inhibition during vacuum packaging of salmon fillets relative to control samples. Whole-genome sequencing (WGS) provided insight into the spoilage potential of KM02, proving its importance as a spoilage microorganism whose metabolic activity should be inhibited to maintain the quality and safety of fresh fish in the food market.
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Affiliation(s)
- Natalia Tomaś
- Department of Biotechnology and Food Microbiology, Poznan University of Life Sciences, Wojska Polskiego 48, 60-637, Poznań, Poland.
| | - Kamila Myszka
- Department of Biotechnology and Food Microbiology, Poznan University of Life Sciences, Wojska Polskiego 48, 60-637, Poznań, Poland
| | - Łukasz Wolko
- Department of Biochemistry and Biotechnology, Poznan University of Life Sciences, Dojazd 11, 60-632, Poznań, Poland
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25
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Wijesooriya K, Jadaan SA, Perera KL, Kaur T, Ziemann M. Urgent need for consistent standards in functional enrichment analysis. PLoS Comput Biol 2022; 18:e1009935. [PMID: 35263338 PMCID: PMC8936487 DOI: 10.1371/journal.pcbi.1009935] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/21/2022] [Accepted: 02/18/2022] [Indexed: 11/25/2022] Open
Abstract
Gene set enrichment tests (a.k.a. functional enrichment analysis) are among the most frequently used methods in computational biology. Despite this popularity, there are concerns that these methods are being applied incorrectly and the results of some peer-reviewed publications are unreliable. These problems include the use of inappropriate background gene lists, lack of false discovery rate correction and lack of methodological detail. To ascertain the frequency of these issues in the literature, we performed a screen of 186 open-access research articles describing functional enrichment results. We find that 95% of analyses using over-representation tests did not implement an appropriate background gene list or did not describe this in the methods. Failure to perform p-value correction for multiple tests was identified in 43% of analyses. Many studies lacked detail in the methods section about the tools and gene sets used. An extension of this survey showed that these problems are not associated with journal or article level bibliometrics. Using seven independent RNA-seq datasets, we show misuse of enrichment tools alters results substantially. In conclusion, most published functional enrichment studies suffered from one or more major flaws, highlighting the need for stronger standards for enrichment analysis. Functional enrichment analysis is a commonly used technique to identify trends in large scale biological datasets. In biomedicine, functional enrichment analysis of gene expression data is frequently applied to identify disease and drug mechanisms. While enrichment tests were once primarily conducted with complicated computer scripts, web-based tools are becoming more widely used. Users can paste a list of genes into a website and receive enrichment results in a matter of seconds. Despite the popularity of these tools, there are concerns that statistical problems and incomplete reporting are compromising research quality. In this article, we conducted a systematic examination of published enrichment analyses and assessed whether (i) any statistical flaws were present and (ii) sufficient methodological detail is provided such that the study could be replicated. We found that lack of methodological detail and errors in statistical analysis were widespread, which undermines the reliability and reproducibility of these research articles. A set of best practices is urgently needed to raise the quality of published work.
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Affiliation(s)
- Kaumadi Wijesooriya
- Deakin University, School of Life and Environmental Sciences, Geelong, Australia
| | - Sameer A. Jadaan
- College of Health and Medical Technology, Middle Technical University, Baghdad, Iraq
| | - Kaushalya L. Perera
- Deakin University, School of Life and Environmental Sciences, Geelong, Australia
| | - Tanuveer Kaur
- Deakin University, School of Life and Environmental Sciences, Geelong, Australia
| | - Mark Ziemann
- Deakin University, School of Life and Environmental Sciences, Geelong, Australia
- * E-mail:
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26
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Genetic reprogramming of remnant duodenum may contribute to type 2 diabetes improvement after Roux en-Y gastric bypass. Nutrition 2022; 99-100:111631. [DOI: 10.1016/j.nut.2022.111631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 12/31/2021] [Accepted: 02/07/2022] [Indexed: 11/22/2022]
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27
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Homogentisic acid induces autophagy alterations leading to chondroptosis in human chondrocytes: Implications in Alkaptonuria. Arch Biochem Biophys 2022; 717:109137. [DOI: 10.1016/j.abb.2022.109137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 01/20/2022] [Accepted: 01/22/2022] [Indexed: 11/17/2022]
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28
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The Cancer Surfaceome Atlas integrates genomic, functional and drug response data to identify actionable targets. NATURE CANCER 2021; 2:1406-1422. [PMID: 35121907 PMCID: PMC9940627 DOI: 10.1038/s43018-021-00282-w] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 10/01/2021] [Indexed: 01/01/2023]
Abstract
Cell-surface proteins (SPs) are a rich source of immune and targeted therapies. By systematically integrating single-cell and bulk genomics, functional studies and target actionability, in the present study we comprehensively identify and annotate genes encoding SPs (GESPs) pan-cancer. We characterize GESP expression patterns, recurrent genomic alterations, essentiality, receptor-ligand interactions and therapeutic potential. We also find that mRNA expression of GESPs is cancer-type specific and positively correlates with protein expression, and that certain GESP subgroups function as common or specific essential genes for tumor cell growth. We also predict receptor-ligand interactions substantially deregulated in cancer and, using systems biology approaches, we identify cancer-specific GESPs with therapeutic potential. We have made this resource available through the Cancer Surfaceome Atlas ( http://fcgportal.org/TCSA ) within the Functional Cancer Genome data portal.
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29
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Zhang J, Liu X, Zhou W, Lu S, Wu C, Wu Z, Liu R, Li X, Wu J, Liu Y, Guo S, Jia S, Zhang X, Wang M. Identification of Key Genes Associated With the Process of Hepatitis B Inflammation and Cancer Transformation by Integrated Bioinformatics Analysis. Front Genet 2021; 12:654517. [PMID: 34539726 PMCID: PMC8440810 DOI: 10.3389/fgene.2021.654517] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 06/21/2021] [Indexed: 12/13/2022] Open
Abstract
Background Hepatocellular carcinoma (HCC) has become the main cause of cancer death worldwide. More than half of hepatocellular carcinoma developed from hepatitis B virus infection (HBV). The purpose of this study is to find the key genes in the transformation process of liver inflammation and cancer and to inhibit the development of chronic inflammation and the transformation from disease to cancer. Methods Two groups of GEO data (including normal/HBV and HBV/HBV-HCC) were selected for differential expression analysis. The differential expression genes of HBV-HCC in TCGA were verified to coincide with the above genes to obtain overlapping genes. Then, functional enrichment analysis, modular analysis, and survival analysis were carried out on the key genes. Results We identified nine central genes (CDK1, MAD2L1, CCNA2, PTTG1, NEK2) that may be closely related to the transformation of hepatitis B. The survival and prognosis gene markers composed of PTTG1, MAD2L1, RRM2, TPX2, CDK1, NEK2, DEPDC1, and ZWINT were constructed, which performed well in predicting the overall survival rate. Conclusion The findings of this study have certain guiding significance for further research on the transformation of hepatitis B inflammatory cancer, inhibition of chronic inflammation, and molecular targeted therapy of cancer.
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Affiliation(s)
- Jingyuan Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xinkui Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Wei Zhou
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Shan Lu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Chao Wu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Zhishan Wu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Runping Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xiaojiaoyang Li
- School of Life Sciences, Beijing University of Chinese Medicine, Beijing, China
| | - Jiarui Wu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Yingying Liu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Siyu Guo
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Shanshan Jia
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xiaomeng Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Miaomiao Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
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30
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Gutiérrez Y, Fresch M, Hellmann SL, Hankeln T, Scherber C, Brockmeyer J. A multifactorial proteomics approach to sex‐specific effects of diet composition and social environment in an omnivorous insect. Ecol Evol 2021. [DOI: 10.1002/ece3.7676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Yeisson Gutiérrez
- Centro de Bioinformática y Biología Computacional de Colombia – BIOS Manizales Colombia
| | - Marion Fresch
- Department Food Chemistry Institute for Biochemistry and Technical Biochemistry University of Stuttgart Stuttgart Germany
| | - Sören L. Hellmann
- Institute of Organismic and Molecular Evolutionary Biology University of Mainz Mainz Germany
| | - Thomas Hankeln
- Institute of Organismic and Molecular Evolutionary Biology University of Mainz Mainz Germany
| | - Christoph Scherber
- Institute of Landscape Ecology University of Münster Münster Germany
- Centre for Biodiversity Monitoring Zoological Research Museum Alexander Koenig Bonn Germany
| | - Jens Brockmeyer
- Department Food Chemistry Institute for Biochemistry and Technical Biochemistry University of Stuttgart Stuttgart Germany
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31
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Samsulrizal NH, Khadzran KS, Meenakshi Sundram TC, Zainuddin Z, Shaarani SHN, Azmi NSA, Harun S. Transcriptome profiling of Stevia rebaudiana MS007 revealed genes involved in flower development. ACTA ACUST UNITED AC 2021; 45:314-322. [PMID: 34377055 PMCID: PMC8313940 DOI: 10.3906/biy-2103-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 04/28/2021] [Indexed: 11/16/2022]
Abstract
Stevia rebaudiana
is a medicinal plant recommended to diabetic or obese patients as an alternative sweetener owing to its low-calorie property. Previous studies have found that the stevioside level is highest at the time of flower bud formation and lowest at the time of preceding and following flower bud formation. Hence, this study aims to identify the genes involved in the flowering of local
S. rebaudiana
accession MS007 by investigating the transcriptomic data of two stages of growth, before flowering (BF) and after flowering (AF) that were deposited under accession number SRX6362785 and SRX6362784 at the NCBI SRA database. The transcriptomic study managed to annotate 108299 unigenes of
S. rebaudiana
with 8871 and 9832 genes that were differentially expressed in BF and AF samples, respectively. These genes involved in various metabolic pathways related to flower development, response to stimulus as well as photosynthesis. Pheophorbide A oxygenase (
PAO
), eukaryotic translation initiation factor 3 subunit E (
TIF3E1
), and jasmonate ZIM domain-containing protein 1 (
JAZ1
) were found to be involved in the flower development. The outcome of this study will help further research in the manipulation of the flowering process, especially in the breeding programme to develop photo-insensitive
Stevia
plant.
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Affiliation(s)
- Nurul Hidayah Samsulrizal
- Department of Plant Science, Kulliyyah of Science, International Islamic University Malaysia, Kuantan, Pahang Malaysia
| | - Khairul Shahyidi Khadzran
- Department of Plant Science, Kulliyyah of Science, International Islamic University Malaysia, Kuantan, Pahang Malaysia.,Centre for Bioinformatics Research, Institute of Systems Biology, National University of Malaysia , Bangi, Selangor Malaysia
| | | | - Zarina Zainuddin
- Department of Plant Science, Kulliyyah of Science, International Islamic University Malaysia, Kuantan, Pahang Malaysia
| | | | - Nur Sabrina Ahmad Azmi
- Department of Plant Science, Kulliyyah of Science, International Islamic University Malaysia, Kuantan, Pahang Malaysia
| | - Sarahani Harun
- Centre for Bioinformatics Research, Institute of Systems Biology, National University of Malaysia , Bangi, Selangor Malaysia
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32
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Marzorati F, Wang C, Pavesi G, Mizzi L, Morandini P. Cleaning the Medicago Microarray Database to Improve Gene Function Analysis. PLANTS (BASEL, SWITZERLAND) 2021; 10:plants10061240. [PMID: 34207216 PMCID: PMC8234645 DOI: 10.3390/plants10061240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/30/2021] [Accepted: 05/11/2021] [Indexed: 06/13/2023]
Abstract
Transcriptomics studies have been facilitated by the development of microarray and RNA-Seq technologies, with thousands of expression datasets available for many species. However, the quality of data can be highly variable, making the combined analysis of different datasets difficult and unreliable. Most of the microarray data for Medicago truncatula, the barrel medic, have been stored and made publicly accessible on the web database Medicago truncatula Gene Expression atlas (MtGEA). The aim of this work is to ameliorate the quality of the MtGEA database through a general method based on logical and statistical relationships among parameters and conditions. The initial 716 columns available in the dataset were reduced to 607 by evaluating the quality of data through the sum of the expression levels over the entire transcriptome probes and Pearson correlation among hybridizations. The reduced dataset shows great improvements in the consistency of the data, with a reduction in both false positives and false negatives resulting from Pearson correlation and GO enrichment analysis among genes. The approach we used is of general validity and our intent is to extend the analysis to other plant microarray databases.
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Affiliation(s)
- Francesca Marzorati
- Department of Environmental Science and Policy, University of Milan, Via Celoria 10, 20133 Milano, Italy;
| | - Chu Wang
- Department of Biosciences, University of Milan, Via Celoria 26, 20133 Milano, Italy; (C.W.); (G.P.); (L.M.)
| | - Giulio Pavesi
- Department of Biosciences, University of Milan, Via Celoria 26, 20133 Milano, Italy; (C.W.); (G.P.); (L.M.)
| | - Luca Mizzi
- Department of Biosciences, University of Milan, Via Celoria 26, 20133 Milano, Italy; (C.W.); (G.P.); (L.M.)
| | - Piero Morandini
- Department of Environmental Science and Policy, University of Milan, Via Celoria 10, 20133 Milano, Italy;
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Sun C, Shah AM, Yang J, Wang Z, Zhu L, Song Y. Transcriptome Analysis of Oleaginous Fungus Mucor circinelloides WJ11 in Response to Exogenous Soybean Oil as Carbon Source. Nat Prod Commun 2021. [DOI: 10.1177/1934578x211023366] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Mucor circinelloides is an oleaginous fungus that utilizes a wide variety of carbon substrates for its growth. The different sources of carbon strongly influence the total lipid content of the fungus. These different carbon substrates are assimilated and dissimilated through different metabolic pathways before entering into the TAG synthesis pathway. In the present study, we attempted to explore the mechanism of ex-novo lipid biosynthesis in M. circinelloides WJ11 in response to exogenous plant oil as a carbon source through transcriptomic analysis. The lipid content of WJ11 grown in a media containing mixed soybean oil with glucose as a carbon source was up to 43.8%, an increase of 13.9% as compared to glucose alone as the carbon source. RNA-Seq analysis was performed to investigate global gene expression patterns in the oil-treated WJ11. Based on RNA-seq analysis, among the 4646 differentially expressed genes (DEGs), 2379 were up-regulated and 2267 down-regulated. The expression of acetyl-CoA synthetase, 6-phosphofructokinase, alcohol dehydrogenase (NADP+), fructose-bisphosphate aldolase, and pyruvate kinase was down-regulated while genes related to triglyceride synthesis were up-regulated. The majority of genes and pathways related to lipid biosynthesis were up-regulated indicating a diversion of metabolic pathways towards lipid biosynthesis. The data generated advance the genomic resources and provide insights into the mechanisms of ex-novo lipid accumulation in fungi that use exogenous oil as a carbon source.
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Affiliation(s)
- Caili Sun
- Colin Ratledge Center of Microbial Lipids, Shandong University of Technology, School of Agriculture Engineering and Food Sciences, Zibo, China
| | - Aabid Manzoor Shah
- Colin Ratledge Center of Microbial Lipids, Shandong University of Technology, School of Agriculture Engineering and Food Sciences, Zibo, China
| | - Junhuan Yang
- Colin Ratledge Center of Microbial Lipids, Shandong University of Technology, School of Agriculture Engineering and Food Sciences, Zibo, China
| | - Zongmin Wang
- Colin Ratledge Center of Microbial Lipids, Shandong University of Technology, School of Agriculture Engineering and Food Sciences, Zibo, China
| | | | - Yuanda Song
- Colin Ratledge Center of Microbial Lipids, Shandong University of Technology, School of Agriculture Engineering and Food Sciences, Zibo, China
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Fulcher BD, Arnatkeviciute A, Fornito A. Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data. Nat Commun 2021; 12:2669. [PMID: 33976144 PMCID: PMC8113439 DOI: 10.1038/s41467-021-22862-1] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/31/2021] [Indexed: 02/03/2023] Open
Abstract
Transcriptomic atlases have improved our understanding of the correlations between gene-expression patterns and spatially varying properties of brain structure and function. Gene-category enrichment analysis (GCEA) is a common method to identify functional gene categories that drive these associations, using gene-to-category annotation systems like the Gene Ontology (GO). Here, we show that applying standard GCEA methodology to spatial transcriptomic data is affected by substantial false-positive bias, with GO categories displaying an over 500-fold average inflation of false-positive associations with random neural phenotypes in mouse and human. The estimated false-positive rate of a GO category is associated with its rate of being reported as significantly enriched in the literature, suggesting that published reports are affected by this false-positive bias. We show that within-category gene-gene coexpression and spatial autocorrelation are key drivers of the false-positive bias and introduce flexible ensemble-based null models that can account for these effects, made available as a software toolbox.
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Affiliation(s)
- Ben D Fulcher
- School of Physics, The University of Sydney, Camperdown, NSW, Australia.
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.
| | - Aurina Arnatkeviciute
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
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35
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Silberstein M, Nesbit N, Cai J, Lee PH. Pathway analysis for genome-wide genetic variation data: Analytic principles, latest developments, and new opportunities. J Genet Genomics 2021; 48:173-183. [PMID: 33896739 PMCID: PMC8286309 DOI: 10.1016/j.jgg.2021.01.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 01/24/2021] [Accepted: 01/25/2021] [Indexed: 12/23/2022]
Abstract
Pathway analysis, also known as gene-set enrichment analysis, is a multilocus analytic strategy that integrates a priori, biological knowledge into the statistical analysis of high-throughput genetics data. Originally developed for the studies of gene expression data, it has become a powerful analytic procedure for in-depth mining of genome-wide genetic variation data. Astonishing discoveries were made in the past years, uncovering genes and biological mechanisms underlying common and complex disorders. However, as massive amounts of diverse functional genomics data accrue, there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data. In this review, we provide an intellectual foundation of this powerful analytic strategy, as well as an update of the state-of-the-art in recent method developments. The goal of this review is threefold: (1) introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data; (2) review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools; and (3) discuss remaining challenges and future directions for further method developments.
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Affiliation(s)
- Micah Silberstein
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Nicholas Nesbit
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jacquelyn Cai
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Phil H Lee
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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36
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Bastian FB, Roux J, Niknejad A, Comte A, Fonseca Costa SS, de Farias TM, Moretti S, Parmentier G, de Laval VR, Rosikiewicz M, Wollbrett J, Echchiki A, Escoriza A, Gharib WH, Gonzales-Porta M, Jarosz Y, Laurenczy B, Moret P, Person E, Roelli P, Sanjeev K, Seppey M, Robinson-Rechavi M. The Bgee suite: integrated curated expression atlas and comparative transcriptomics in animals. Nucleic Acids Res 2021; 49:D831-D847. [PMID: 33037820 PMCID: PMC7778977 DOI: 10.1093/nar/gkaa793] [Citation(s) in RCA: 93] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 08/24/2020] [Accepted: 09/15/2020] [Indexed: 01/24/2023] Open
Abstract
Bgee is a database to retrieve and compare gene expression patterns in multiple animal species, produced by integrating multiple data types (RNA-Seq, Affymetrix, in situ hybridization, and EST data). It is based exclusively on curated healthy wild-type expression data (e.g., no gene knock-out, no treatment, no disease), to provide a comparable reference of normal gene expression. Curation includes very large datasets such as GTEx (re-annotation of samples as ‘healthy’ or not) as well as many small ones. Data are integrated and made comparable between species thanks to consistent data annotation and processing, and to calls of presence/absence of expression, along with expression scores. As a result, Bgee is capable of detecting the conditions of expression of any single gene, accommodating any data type and species. Bgee provides several tools for analyses, allowing, e.g., automated comparisons of gene expression patterns within and between species, retrieval of the prefered conditions of expression of any gene, or enrichment analyses of conditions with expression of sets of genes. Bgee release 14.1 includes 29 animal species, and is available at https://bgee.org/ and through its Bioconductor R package BgeeDB.
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Affiliation(s)
- Frederic B Bastian
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Julien Roux
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Anne Niknejad
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Aurélie Comte
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Sara S Fonseca Costa
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Tarcisio Mendes de Farias
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Sébastien Moretti
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Gilles Parmentier
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Valentine Rech de Laval
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Marta Rosikiewicz
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Julien Wollbrett
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Amina Echchiki
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Angélique Escoriza
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Walid H Gharib
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Mar Gonzales-Porta
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Yohan Jarosz
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Balazs Laurenczy
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Philippe Moret
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Emilie Person
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Patrick Roelli
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Komal Sanjeev
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Mathieu Seppey
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Marc Robinson-Rechavi
- Department of Ecology and Evolution, University of Lausanne, 1015 Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
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37
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Galderisi S, Cicaloni V, Milella MS, Millucci L, Geminiani M, Salvini L, Tinti L, Tinti C, Vieira OV, Alves LS, Crevenna AH, Spiga O, Santucci A. Homogentisic acid induces cytoskeleton and extracellular matrix alteration in alkaptonuric cartilage. J Cell Physiol 2021; 236:6011-6024. [PMID: 33469937 DOI: 10.1002/jcp.30284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 12/29/2020] [Accepted: 01/05/2021] [Indexed: 11/08/2022]
Abstract
Alkaptonuria (AKU) is an ultra-rare disease caused by the deficient activity of homogentisate 1,2-dioxygenase enzyme, leading the accumulation of homogentisic acid (HGA) in connective tissues implicating the formation of a black pigmentation called "ochronosis." Although AKU is a multisystemic disease, the most affected tissue is the articular cartilage, which during the pathology appears to be highly damaged. In this study, a model of alkaptonuric chondrocytes and cartilage was realized to investigate the role of HGA in the alteration of the extracellular matrix (ECM). The AKU tissues lost its architecture composed of collagen, proteoglycans, and all the proteins that characterize the ECM. The cause of this alteration in AKU cartilage is attributed to a degeneration of the cytoskeletal network in chondrocytes caused by the accumulation of HGA. The three cytoskeletal proteins, actin, vimentin, and tubulin, were analyzed and a modification in their amount and disposition in AKU chondrocytes model was identified. Cytoskeleton is involved in many fundamental cellular processes; therefore, the aberration in this complex network is involved in the manifestation of AKU disease.
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Affiliation(s)
- Silvia Galderisi
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Vittoria Cicaloni
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy.,Toscana Life Sciences Foundation, Siena, Italy
| | - Maria S Milella
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Lia Millucci
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Michela Geminiani
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | | | - Laura Tinti
- Toscana Life Sciences Foundation, Siena, Italy
| | | | - Otilia V Vieira
- NOVA Medical School, 3CEDOC, Faculdade de Ciências Médicas, Lisboa, Portugal
| | - Liliana S Alves
- NOVA Medical School, 3CEDOC, Faculdade de Ciências Médicas, Lisboa, Portugal
| | | | - Ottavia Spiga
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
| | - Annalisa Santucci
- Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy
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38
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Combes F, Loux V, Vandenbrouck Y. GO Enrichment Analysis for Differential Proteomics Using ProteoRE. Methods Mol Biol 2021; 2361:179-196. [PMID: 34236662 DOI: 10.1007/978-1-0716-1641-3_11] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
With the increased simplicity of producing proteomics data, the bottleneck has now shifted to the functional analysis of large lists of proteins to translate this primary level of information into meaningful biological knowledge. Tools implementing such approach are a powerful way to gain biological insights related to their samples, provided that biologists/clinicians have access to computational solutions even when they have little programming experience or bioinformatics support. To achieve this goal, we designed ProteoRE (Proteomics Research Environment), a unified online research service that provides end-users with a set of tools to interpret their proteomics data in a collaborative and reproducible manner. ProteoRE is built upon the Galaxy framework, a workflow system allowing for data and analysis persistence, and providing user interfaces to facilitate the interaction with tools dedicated to the functional and the visual analysis of proteomics datasets. A set of tools relying on computational methods selected for their complementarity in terms of functional analysis was developed and made accessible via the ProteoRE web portal. In this chapter, a step-by-step protocol linking these tools is designed to perform a functional annotation and GO-based enrichment analyses applied to a set of differentially expressed proteins as a use case. Analytical practices, guidelines as well as tips related to this strategy are also provided. Tools, datasets, and results are freely available at http://www.proteore.org , allowing researchers to reuse them.
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Affiliation(s)
- Florence Combes
- Université Grenoble Alpes, INSERM, CEA, UMR BioSanté U1292, Grenoble, France
| | - Valentin Loux
- Université Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France
- Université Paris-Saclay, INRAE, BioinfOmics, MIGALE bioinformatics facility, Jouy-en-Josas, France
| | - Yves Vandenbrouck
- Université Grenoble Alpes, INSERM, CEA, UMR BioSanté U1292, Grenoble, France.
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39
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Cicaloni V, Pecorelli A, Cordone V, Tinti L, Rossi M, Hayek J, Salvini L, Tinti C, Valacchi G. A proteomics approach to further highlight the altered inflammatory condition in Rett syndrome. Arch Biochem Biophys 2020; 696:108660. [PMID: 33159892 DOI: 10.1016/j.abb.2020.108660] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 10/24/2020] [Accepted: 10/28/2020] [Indexed: 12/12/2022]
Abstract
Rett syndrome (RTT) is a progressive neurodevelopmental disorder caused by mutations in the X-linked MECP2 gene. RTT patients show multisystem disturbances associated with perturbed redox homeostasis and inflammation, which appear as possible key factors in RTT pathogenesis. In this study, using primary dermal fibroblasts from control and RTT subjects, we performed a proteomic analysis that, together with data mining approaches, allowed us to carry out a comprehensive characterization of RTT cellular proteome. Functional and pathway enrichment analyses showed that differentially expressed proteins in RTT were mainly enriched in biological processes related to immune/inflammatory responses. Overall, by using proteomic data mining as supportive approach, our results provide a detailed insight into the molecular pathways involved in RTT immune dysfunction that, causing tissue and organ damage, can increase the vulnerability of affected patients to unknown endogenous factors or infections.
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Affiliation(s)
- Vittoria Cicaloni
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Alessandra Pecorelli
- Plants for Human Health Institute, Animal Science Dept., NC Research Campus, NC State University, 600 Laureate Way, Kannapolis, NC, 28081, USA
| | - Valeria Cordone
- Department of Biomedical and Specialist Surgical Sciences, University of Ferrara, Ferrara, Italy
| | - Laura Tinti
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Marco Rossi
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Joussef Hayek
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Laura Salvini
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Cristina Tinti
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Giuseppe Valacchi
- Plants for Human Health Institute, Animal Science Dept., NC Research Campus, NC State University, 600 Laureate Way, Kannapolis, NC, 28081, USA; Department of Biomedical and Specialist Surgical Sciences, University of Ferrara, Ferrara, Italy; Kyung Hee University, Department of Food and Nutrition, Seoul, South Korea.
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40
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Zhao Y, Tang X, Lv M, Liu Q, Li J, Zhang B, Li L, Zhang X, Zhao Y. The molecular response mechanisms of a diatom Thalassiosira pseudonana to the toxicity of BDE-47 based on whole transcriptome analysis. AQUATIC TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2020; 229:105669. [PMID: 33142158 DOI: 10.1016/j.aquatox.2020.105669] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 10/16/2020] [Accepted: 10/21/2020] [Indexed: 06/11/2023]
Abstract
Polybrominated diphenyl ethers (PBDEs) are ubiquitously distributed persistent organic pollutants (POPs) in marine environments. Phytoplankton are the entrance of PBDEs entering to biotic environments from abiotic environments, while the responding mechanisms of phytoplankton to PBDEs have not been full established. Therefore, we chose the model diatom Thalassiosira pseudonana in this study, by integrating whole transcriptome analysis with physiological-biochemical data, to reveal the molecular responding mechanisms of T. pseudonana to the toxicity of BDE-47. Our results indicated the changes of genes expressions correlated to the physiological-biochemical changes, and there were multiple molecular mechanisms of T. pseudonana responding to the toxicity of BDE-47: Gene expressions evidence explained the suppression of light reaction and proved the occurrence of cellular oxidative stress; In the meanwhile, up-regulations of genes in pathways involving carbon metabolisms happened, including the Calvin cycle, glycolysis, TCA cycle, fatty acid synthesis, and triacylglycerol synthesis; Lastly, DNA damage was found and three outcome including DNA repair, cell cycle arrest and programmed cell death (PCD) happened, which could finally inhibit the cell division and population growth of T. pseudonana. This study presented the most complete molecular responding mechanisms of phytoplankton cells to PBDEs, and provided valuable information of various PBDEs-sensitive genes with multiple functions for further research involving organic pollutants and phytoplankton.
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Affiliation(s)
- Yirong Zhao
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China
| | - Xuexi Tang
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266071, China.
| | - Mengchen Lv
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China
| | - Qian Liu
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China
| | - Jun Li
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China
| | - Bihan Zhang
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China
| | - Luying Li
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China
| | - Xinxin Zhang
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266071, China
| | - Yan Zhao
- College of Marine Life Sciences, Department of Marine Ecology, Ocean University of China, Qingdao, 266003, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266071, China.
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41
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Kwok ML, Meng Q, Hu XL, Chung CT, Chan KM. Whole-transcriptome sequencing (RNA-seq) study of the ZFL zebrafish liver cell line after acute exposure to Cd 2+ ions. AQUATIC TOXICOLOGY (AMSTERDAM, NETHERLANDS) 2020; 228:105628. [PMID: 32971353 DOI: 10.1016/j.aquatox.2020.105628] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 09/03/2020] [Accepted: 09/06/2020] [Indexed: 06/11/2023]
Abstract
Cadmium (Cd) is a non-essential metal with no known biological function and a broad range of toxic effects in biological systems. We used whole-transcriptome sequencing (RNA-seq) to study the effects of Cd2+ toxicity in zebrafish liver cells, ZFL. The results of an RNA-Seq analysis of ZFL cells exposed to 5, 10 or 20 μM Cd2+ for 4- or 24-h. The differentially expressed genes affected by Cd2+ were analyzed by using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to study the regulated pathways. Cd2+ regulated the expression of genes associated with cellular Cu, Zn, and Fe homeostasis, DNA replication leading to cell cycle arrest and apoptosis, and glutathione metabolism. Cd2+ boosted up the amino acid synthesis, possibly to support the glutathione metabolism for tackling the oxidative stress generated from Cd2+. Cd2+ stimulation was similar to heat or xenobiotics, based on the responses from ZFL such as endoplasmic reticulum stress and protein folding. We linked also those finding of gene activations relating to carcinogenesis of Cd. This paper provides a comprehensive analysis of the expression profiles induced by Cd2+ exposure in ZFL cells, as well as useful insights into the specific toxic effects.
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Affiliation(s)
- Man Long Kwok
- School of Life Sciences, The Chinese University of Hong Kong, Sha Tin., N.T., Hong Kong
| | - Qi Meng
- School of Life Sciences, The Chinese University of Hong Kong, Sha Tin., N.T., Hong Kong
| | - Xue Lei Hu
- School of Life Sciences, The Chinese University of Hong Kong, Sha Tin., N.T., Hong Kong
| | - Chun Ting Chung
- School of Life Sciences, The Chinese University of Hong Kong, Sha Tin., N.T., Hong Kong
| | - King Ming Chan
- School of Life Sciences, The Chinese University of Hong Kong, Sha Tin., N.T., Hong Kong.
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Byadgi O, Marroni F, Dirks R, Massimo M, Volpatti D, Galeotti M, Beraldo P. Transcriptome Analysis of Amyloodinium ocellatum Tomonts Revealed Basic Information on the Major Potential Virulence Factors. Genes (Basel) 2020; 11:genes11111252. [PMID: 33114415 PMCID: PMC7692099 DOI: 10.3390/genes11111252] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/21/2020] [Accepted: 10/22/2020] [Indexed: 11/16/2022] Open
Abstract
The ectoparasite protozoan Amyloodinium ocellatum (AO) is the etiological agent of amyloodiniosis in European seabass (Dicentrarchus labrax) (ESB). There is a lack of information about basic molecular data on AO biology and its interaction with the host. Therefore, de novo transcriptome sequencing of AO tomonts was performed. AO trophonts were detached from infested ESB gills, and quickly becoming early tomonts were purified by Percoll® density gradient. Tomont total RNA was processed and quality was assessed immediately. cDNA libraries were constructed using TruSeq® Stranded mRNA kit and sequenced using Illumina sequencer. CLC assembly was used to generate the Transcriptome assembly of AO tomonts. Out of 48,188 contigs, 56.12% belong to dinophyceae wherein Symbiodinium microadriaticum had 94.61% similarity among dinophyceae. Functional annotations of contigs indicated that 12,677 had associated GO term, 9005 with KEGG term. The contigs belonging to dinophyceae resulted in the detection of several peptidases. A BLAST search for known virulent factors from the virulence database resulted in hits to Rab proteins, AP120, Ribosomal phosphoprotein, Heat-shock protein70, Casein kinases, Plasmepsin IV, and Brucipain. Hsp70 and casein kinase II alpha were characterized in-silico. Altogether, these results provide a reference database in understanding AO molecular biology, aiding to the development of novel diagnostics and future vaccines.
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Affiliation(s)
- Omkar Byadgi
- Section of Animal and Veterinary Sciences, Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, 33100 Udine, Italy; (M.M.); (D.V.); (M.G.); (P.B.)
- Correspondence: ; Tel.: +39-0432-558197
| | - Fabio Marroni
- Department of Agricultural, Food, Environmental and Animal Sciences, University of Udine, Via delle Scienze 206, 33100 Udine, Italy;
- IGA Technology Services, Via Jacopo Linussio, 51, 33100 Udine, Italy
| | - Ron Dirks
- Future Genomics Technologies B.V, 2333 Leiden, The Netherlands;
| | - Michela Massimo
- Section of Animal and Veterinary Sciences, Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, 33100 Udine, Italy; (M.M.); (D.V.); (M.G.); (P.B.)
| | - Donatella Volpatti
- Section of Animal and Veterinary Sciences, Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, 33100 Udine, Italy; (M.M.); (D.V.); (M.G.); (P.B.)
| | - Marco Galeotti
- Section of Animal and Veterinary Sciences, Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, 33100 Udine, Italy; (M.M.); (D.V.); (M.G.); (P.B.)
| | - Paola Beraldo
- Section of Animal and Veterinary Sciences, Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, 33100 Udine, Italy; (M.M.); (D.V.); (M.G.); (P.B.)
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Guerreiro EM, Øvstebø R, Thiede B, Costea DE, Søland TM, Kanli Galtung H. Cancer cell line-specific protein profiles in extracellular vesicles identified by proteomics. PLoS One 2020; 15:e0238591. [PMID: 32886718 PMCID: PMC7473518 DOI: 10.1371/journal.pone.0238591] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 08/19/2020] [Indexed: 12/15/2022] Open
Abstract
Extracellular vesicles (EVs), are important for intercellular communication in both physiological and pathological processes. To explore the potential of cancer derived EVs as disease biomarkers for diagnosis, monitoring, and treatment decision, it is necessary to thoroughly characterize their biomolecular content. The aim of the study was to characterize and compare the protein content of EVs derived from three different cancer cell lines in search of a specific molecular signature, with emphasis on proteins related to the carcinogenic process. Oral squamous cell carcinoma (OSCC), pancreatic ductal adenocarcinoma (PDAC) and melanoma brain metastasis cell lines were cultured in CELLine AD1000 flasks. EVs were isolated by ultrafiltration and size-exclusion chromatography and characterized. Next, the isolated EVs underwent liquid chromatography-mass spectrometry (LC-MS) analysis for protein identification. Functional enrichment analysis was performed for a more general overview of the biological processes involved. More than 600 different proteins were identified in EVs from each particular cell line. Here, 14%, 10%, and 24% of the identified proteins were unique in OSCC, PDAC, and melanoma vesicles, respectively. A specific protein profile was discovered for each cell line, e.g., EGFR in OSCC, Muc5AC in PDAC, and FN1 in melanoma vesicles. Nevertheless, 25% of all the identified proteins were common to all cell lines. Functional enrichment analysis linked the proteins in each data set to biological processes such as "biological adhesion", "cell motility", and "cellular component biogenesis". EV proteomics discovered cancer-specific protein profiles, with proteins involved in processes promoting tumor progression. In addition, the biological processes associated to the melanoma-derived EVs were distinct from the ones linked to the EVs isolated from OSCC and PDAC. The malignancy specific biomolecular cues in EVs may have potential applications as diagnostic biomarkers and in therapy.
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Affiliation(s)
- Eduarda M. Guerreiro
- Institute of Oral Biology, Faculty of Dentistry, University of Oslo, Oslo, Norway
| | - Reidun Øvstebø
- Department of Medical Biochemistry, Blood Cell Research Group, Oslo University Hospital, Ullevål, Oslo, Norway
| | - Bernd Thiede
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Daniela Elena Costea
- Centre for Cancer Biomarkers CCBio and Gade Laboratory for Pathology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Department of Pathology, Haukeland University Hospital, Bergen, Norway
| | - Tine M. Søland
- Institute of Oral Biology, Faculty of Dentistry, University of Oslo, Oslo, Norway
- Department of Pathology, Oslo University Hospital, Oslo, Norway
| | - Hilde Kanli Galtung
- Institute of Oral Biology, Faculty of Dentistry, University of Oslo, Oslo, Norway
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Parejo M, Wragg D, Henriques D, Charrière JD, Estonba A. Digging into the Genomic Past of Swiss Honey Bees by Whole-Genome Sequencing Museum Specimens. Genome Biol Evol 2020; 12:2535-2551. [PMID: 32877519 PMCID: PMC7720081 DOI: 10.1093/gbe/evaa188] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/24/2020] [Indexed: 11/20/2022] Open
Abstract
Historical specimens in museum collections provide opportunities to gain insights into the genomic past. For the Western honey bee, Apis mellifera L., this is particularly important because its populations are currently under threat worldwide and have experienced many changes in management and environment over the last century. Using Swiss Apis mellifera mellifera as a case study, our research provides important insights into the genetic diversity of native honey bees prior to the industrial-scale introductions and trade of non-native stocks during the 20th century—the onset of intensive commercial breeding and the decline of wild honey bees following the arrival of Varroa destructor. We sequenced whole-genomes of 22 honey bees from the Natural History Museum in Bern collected in Switzerland, including the oldest A. mellifera sample ever sequenced. We identify both, a historic and a recent migrant, natural or human-mediated, which corroborates with the population history of honey bees in Switzerland. Contrary to what we expected, we find no evidence for a significant genetic bottleneck in Swiss honey bees, and find that genetic diversity is not only maintained, but even slightly increased, most probably due to modern apicultural practices. Finally, we identify signals of selection between historic and modern honey bee populations associated with genes enriched in functions linked to xenobiotics, suggesting a possible selective pressure from the increasing use and diversity of chemicals used in agriculture and apiculture over the last century.
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Affiliation(s)
- Melanie Parejo
- Agroscope, Swiss Bee Research Center, Bern, Switzerland.,Lab. Genetics, Department of Genetics, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
| | - David Wragg
- The Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Dora Henriques
- Instituto Politécnico de Bragança, Centro de Investigação de Montanha (CIMO), Bragança, Portugal
| | | | - Andone Estonba
- Lab. Genetics, Department of Genetics, Faculty of Science and Technology, University of the Basque Country (UPV/EHU), Leioa, Spain
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Cicaloni V, Pecorelli A, Tinti L, Rossi M, Benedusi M, Cervellati C, Spiga O, Santucci A, Hayek J, Salvini L, Tinti C, Valacchi G. Proteomic profiling reveals mitochondrial alterations in Rett syndrome. Free Radic Biol Med 2020; 155:37-48. [PMID: 32445864 DOI: 10.1016/j.freeradbiomed.2020.05.014] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 05/14/2020] [Accepted: 05/16/2020] [Indexed: 12/11/2022]
Abstract
Rett syndrome (RTT) is a pervasive neurodevelopmental disorder associated with mutation in MECP2 gene. Despite a well-defined genetic cause, there is a growing consensus that a metabolic component could play a pivotal role in RTT pathophysiology. Indeed, perturbed redox homeostasis and inflammation, i.e. oxinflammation, with mitochondria dysfunction as the central hub between the two phenomena, appear as possible key contributing factors to RTT pathogenesis and its clinical features. While these RTT-related changes have been widely documented by transcriptomic profiling, proteomics studies supporting these evidences are still limited. Here, using primary dermal fibroblasts from control and patients, we perform a large-scale proteomic analysis that, together with data mining approaches, allow us to carry out the first comprehensive characterization of RTT cellular proteome, showing mainly changes in expression of proteins involved in the mitochondrial network. These findings parallel with an altered expression of key mediators of mitochondrial dynamics and mitophagy associated with abnormal mitochondrial morphology. In conclusion, our proteomic analysis confirms the pathological relevance of mitochondrial dysfunction in RTT pathogenesis and progression.
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Affiliation(s)
- Vittoria Cicaloni
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Alessandra Pecorelli
- Plants for Human Health Institute, Animal Science Dept., NC Research Campus, NC State University, 600 Laureate Way, Kannapolis, NC, 28081, USA
| | - Laura Tinti
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Marco Rossi
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Mascia Benedusi
- Department of Biomedical and Specialist Surgical Sciences, Section of Medical Biochemistry, Molecular Biology and Genetics, University of Ferrara, Ferrara, Italy
| | - Carlo Cervellati
- Department of Morphology and Experimental Medicine University of Ferrara, via Borsari 46, 44121, Ferrara, Italy
| | - Ottavia Spiga
- Department of Biotechnology, Chemistry and Pharmacy, Via Aldo Moro 2, University of Siena, Siena, Italy
| | - Annalisa Santucci
- Department of Biotechnology, Chemistry and Pharmacy, Via Aldo Moro 2, University of Siena, Siena, Italy
| | - Joussef Hayek
- Child Neuropsychiatry Unit, University General Hospital, Azienda Ospedaliera Universitaria Senese, Viale M. Bracci 16, 53100, Siena, Italy
| | - Laura Salvini
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Cristina Tinti
- Toscana Life Science Foundation, Via Fiorentina 1, 53100, Siena, Italy
| | - Giuseppe Valacchi
- Plants for Human Health Institute, Animal Science Dept., NC Research Campus, NC State University, 600 Laureate Way, Kannapolis, NC, 28081, USA; Department of Biomedical and Specialist Surgical Sciences, Section of Medical Biochemistry, Molecular Biology and Genetics, University of Ferrara, Ferrara, Italy; Kyung Hee University, Department of Food and Nutrition, Seoul, South Korea.
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Katz DC, Aponte JD, Liu W, Green RM, Mayeux JM, Pollard KM, Pomp D, Munger SC, Murray SA, Roseman CC, Percival CJ, Cheverud J, Marcucio RS, Hallgrímsson B. Facial shape and allometry quantitative trait locus intervals in the Diversity Outbred mouse are enriched for known skeletal and facial development genes. PLoS One 2020; 15:e0233377. [PMID: 32502155 PMCID: PMC7274373 DOI: 10.1371/journal.pone.0233377] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 05/04/2020] [Indexed: 02/06/2023] Open
Abstract
The biology of how faces are built and come to differ from one another is complex. Discovering normal variants that contribute to differences in facial morphology is one key to untangling this complexity, with important implications for medicine and evolutionary biology. This study maps quantitative trait loci (QTL) for skeletal facial shape using Diversity Outbred (DO) mice. The DO is a randomly outcrossed population with high heterozygosity that captures the allelic diversity of eight inbred mouse lines from three subspecies. The study uses a sample of 1147 DO animals (the largest sample yet employed for a shape QTL study in mouse), each characterized by 22 three-dimensional landmarks, 56,885 autosomal and X-chromosome markers, and sex and age classifiers. We identified 37 facial shape QTL across 20 shape principal components (PCs) using a mixed effects regression that accounts for kinship among observations. The QTL include some previously identified intervals as well as new regions that expand the list of potential targets for future experimental study. Three QTL characterized shape associations with size (allometry). Median support interval size was 3.5 Mb. Narrowing additional analysis to QTL for the five largest magnitude shape PCs, we found significant overrepresentation of genes with known roles in growth, skeletal and facial development, and sensory organ development. For most intervals, one or more of these genes lies within 0.25 Mb of the QTL's peak. QTL effect sizes were small, with none explaining more than 0.5% of facial shape variation. Thus, our results are consistent with a model of facial diversity that is influenced by key genes in skeletal and facial development and, simultaneously, is highly polygenic.
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Affiliation(s)
- David C. Katz
- Department of Cell Biology & Anatomy, Alberta Children’s Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, AB, Canada
| | - J. David Aponte
- Department of Cell Biology & Anatomy, Alberta Children’s Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, AB, Canada
| | - Wei Liu
- Department of Cell Biology & Anatomy, Alberta Children’s Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, AB, Canada
| | - Rebecca M. Green
- Department of Cell Biology & Anatomy, Alberta Children’s Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, AB, Canada
| | - Jessica M. Mayeux
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, United States of America
| | - K. Michael Pollard
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, United States of America
| | - Daniel Pomp
- Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC, United States of America
| | - Steven C. Munger
- The Jackson Laboratory, Bar Harbor, ME, United States of America
| | | | - Charles C. Roseman
- Department of Evolution, Ecology, and Behavior, University of Illinois Urbana Champaign, Urbana, IL, United States of America
| | - Christopher J. Percival
- Department of Anthropology, Stony Brook University, Stony Brook, NY, United States of America
| | - James Cheverud
- Department of Biology, Loyola University Chicago, Chicago, IL, United States of America
| | - Ralph S. Marcucio
- Department of Orthopaedic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, United States of America
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, Alberta Children’s Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, AB, Canada
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Yan G, Zhang J, Jiang M, Gao X, Yang H, Li L. Identification of Known and Novel MicroRNAs in Raspberry Organs Through High-Throughput Sequencing. FRONTIERS IN PLANT SCIENCE 2020; 11:728. [PMID: 32582255 PMCID: PMC7284492 DOI: 10.3389/fpls.2020.00728] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Accepted: 05/06/2020] [Indexed: 05/23/2023]
Abstract
MicroRNAs (miRNAs) are a class of small endogenous RNAs that play important regulatory roles in plants by negatively affecting gene expression. Studies on the identification of miRNAs and their functions in various plant species and organs have significantly contributed to plant development research. In the current study, we utilized high-throughput sequencing to detect the miRNAs in the root, stem, and leaf tissues of raspberry (Rubus idaeus). A total of more than 35 million small RNA reads ranging in size from 18 to 35 nucleotides were obtained, with 147 known miRNAs and 542 novel miRNAs identified among the three organs. Sequence verification and the relative expression profiles of the six known miRNAs were investigated by stem-loop quantitative real-time PCR. Furthermore, the potential target genes of the known and novel miRNAs were predicted and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway annotation. Enrichment analysis of the GO-associated biological processes and molecular functions revealed that these target genes were potentially involved in a wide range of metabolic pathways and developmental processes. Moreover, the miRNA target prediction revealed that most of the targets predicted as transcription factor-coding genes are involved in cellular and metabolic processes. This report is the first to identify miRNAs in raspberry. The detected miRNAs were analyzed by cluster analysis according to their expression, which revealed that these conservative miRNAs are necessary for plant functioning. The results add novel miRNAs to the raspberry transcriptome, providing a useful resource for the further elucidation of the functional roles of miRNAs in raspberry growth and development.
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Affiliation(s)
- Gengxuan Yan
- Key Laboratory of Saline-alkali Vegetation Ecology Restoration (Northeast Forestry University), Ministry of Education, Harbin, China
- College of Life Science, Northeast Forestry University, Harbin, China
| | - Jie Zhang
- Key Laboratory of Saline-alkali Vegetation Ecology Restoration (Northeast Forestry University), Ministry of Education, Harbin, China
- College of Life Science, Northeast Forestry University, Harbin, China
| | - Meng Jiang
- Key Laboratory of Saline-alkali Vegetation Ecology Restoration (Northeast Forestry University), Ministry of Education, Harbin, China
- College of Life Science, Northeast Forestry University, Harbin, China
| | - Xince Gao
- Key Laboratory of Saline-alkali Vegetation Ecology Restoration (Northeast Forestry University), Ministry of Education, Harbin, China
- College of Life Science, Northeast Forestry University, Harbin, China
| | - Hongyi Yang
- Key Laboratory of Saline-alkali Vegetation Ecology Restoration (Northeast Forestry University), Ministry of Education, Harbin, China
- College of Life Science, Northeast Forestry University, Harbin, China
| | - Lili Li
- Institute of Forestry Science of Heilongjiang Province, Harbin, China
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Yates-Stewart AD, Daron J, Wijeratne S, Shahid S, Edgington HA, Slotkin RK, Michel A. Soybean aphids adapted to host-plant resistance by down regulating putative effectors and up regulating transposable elements. INSECT BIOCHEMISTRY AND MOLECULAR BIOLOGY 2020; 121:103363. [PMID: 32201218 DOI: 10.1016/j.ibmb.2020.103363] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 03/06/2020] [Accepted: 03/15/2020] [Indexed: 06/10/2023]
Abstract
In agricultural systems, crops equipped with host-plant resistance (HPR) have enhanced protection against pests, and are used as a safe and sustainable tool in pest management. In soybean, HPR can control the soybean aphid (Aphis glycines), but certain aphid populations have overcome this resistance (i.e., virulence). The molecular mechanisms underlying aphid virulence to HPR are unknown, but likely involve effector proteins that are secreted by aphids to modulate plant defenses. Another mechanism to facilitate adaptation is through the activity of transposable elements, which can become activated by stress. In this study, we performed RNA sequencing of virulent and avirulent soybean aphids fed susceptible or resistant (Rag1 + Rag2) soybean. Our goal was to better understand the molecular mechanisms underlying soybean aphid virulence. Our data showed that virulent aphids mostly down regulate putative effector genes relative to avirulent aphids, especially when aphids were fed susceptible soybean. Decreased expression of effectors may help evade HPR plant defenses. Virulent aphids also transcriptionally up regulate a diverse set of transposable elements and nearby genes, which is consistent with stress adaptation. Our work demonstrates two mechanisms of pest adaptation to resistance, and identifies effector gene targets for future functional testing.
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Affiliation(s)
| | - Josquin Daron
- CNRS, Centre National de la Recherche Scientifique, Montpellier, France
| | - Saranga Wijeratne
- The Ohio State University, Molecular and Cellular Imaging Center, OARDC, Wooster, OH, USA
| | - Saima Shahid
- Donald Danforth Plant Science Center, St, Louis, MO, USA
| | - Hilary A Edgington
- The Ohio State University, Department of Entomology, CFAES Wooster Campus, Wooster, OH, USA
| | - R Keith Slotkin
- Donald Danforth Plant Science Center, St, Louis, MO, USA; Division of Biological Sciences, University of Missouri, Columbia, MO, USA
| | - Andy Michel
- The Ohio State University, Center for Applied Plant Sciences, Wooster, OH, USA; The Ohio State University, Department of Entomology, CFAES Wooster Campus, Wooster, OH, USA.
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Zhao Y, Wang J, Chen J, Zhang X, Guo M, Yu G. A Literature Review of Gene Function Prediction by Modeling Gene Ontology. Front Genet 2020; 11:400. [PMID: 32391061 PMCID: PMC7193026 DOI: 10.3389/fgene.2020.00400] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/30/2020] [Indexed: 12/14/2022] Open
Abstract
Annotating the functional properties of gene products, i.e., RNAs and proteins, is a fundamental task in biology. The Gene Ontology database (GO) was developed to systematically describe the functional properties of gene products across species, and to facilitate the computational prediction of gene function. As GO is routinely updated, it serves as the gold standard and main knowledge source in functional genomics. Many gene function prediction methods making use of GO have been proposed. But no literature review has summarized these methods and the possibilities for future efforts from the perspective of GO. To bridge this gap, we review the existing methods with an emphasis on recent solutions. First, we introduce the conventions of GO and the widely adopted evaluation metrics for gene function prediction. Next, we summarize current methods of gene function prediction that apply GO in different ways, such as using hierarchical or flat inter-relationships between GO terms, compressing massive GO terms and quantifying semantic similarities. Although many efforts have improved performance by harnessing GO, we conclude that there remain many largely overlooked but important topics for future research.
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Affiliation(s)
- Yingwen Zhao
- College of Computer and Information Science, Southwest University, Chongqing, China
| | - Jun Wang
- College of Computer and Information Science, Southwest University, Chongqing, China
| | - Jian Chen
- State Key Laboratory of Agrobiotechnology and National Maize Improvement Center, China Agricultural University, Beijing, China
| | - Xiangliang Zhang
- CBRC, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Maozu Guo
- School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China
| | - Guoxian Yu
- College of Computer and Information Science, Southwest University, Chongqing, China
- CBRC, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
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50
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Sah PP, Bhattacharya S, Banerjee A, Ray S. Identification of novel therapeutic target and epitopes through proteome mining from essential hypothetical proteins in Salmonella strains: An In silico approach towards antivirulence therapy and vaccine development. INFECTION GENETICS AND EVOLUTION 2020; 83:104315. [PMID: 32276082 DOI: 10.1016/j.meegid.2020.104315] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 03/29/2020] [Accepted: 04/02/2020] [Indexed: 10/24/2022]
Abstract
Salmonella strains are responsible for a huge mortality rate through foodborne ailment in the world that necessitated the discovery of novel drugs and vaccines. Essential hypothetical proteins (EHPs), whose structures and functions were previously unknown, could serve as potential therapeutic and vaccine targets. Antivirulence therapy shall emerge as a superior therapeutic approach that uses virulence factors as drug targets. This study annotated the biological functions of 96 out of total 106 essential hypothetical proteins in five strains of Salmonella and classified into nine important protein categories. 34 virulence factors were predicted among the EHPs, out of which, 11 were identified to be pathogen specific potential drug targets for antivirulence therapy. These targets were non-homologous to both human and gut microbiota proteome to avoid cross-reactivity with them. Seven identified targets had druggable property, while the rest four targets were novel targets. Four identified targets (DEG10320148, DEG10110027, DEG10110040 and DEG10110142) had antigenic properties and were further classified as: two membrane-bound Lipid-binding transmembrane proteins, a Zinc-binding membrane protein and an extracellular glycosylase. These targets could be potentially used for the development of subunit vaccines. The study further identified 11 highly conserved and exposed epitope sequences from these 4 vaccine targets. The three-dimensional structures of the vaccine targets were also elucidated along with highlighting the conformation of the epitopes. This study identified potential therapeutic targets for antivirulence therapy against Salmonella. It would therefore instigate in novel drug designing as well as provide important leads to new Salmonella vaccine development.
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Affiliation(s)
| | | | - Arundhati Banerjee
- Department of Biochemistry and Biophysics, University of Kalyani, Kalyani, Nadia, India
| | - Sujay Ray
- Amity Institute of Biotechnology, Amity University, Kolkata, India.
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