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Liu J, Qiu S, Xue T, Yuan Y. Physiology and transcriptome of Eucommia ulmoides seeds at different germination stages. Plant Signal Behav 2024; 19:2329487. [PMID: 38493506 PMCID: PMC10950268 DOI: 10.1080/15592324.2024.2329487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 01/03/2024] [Indexed: 03/19/2024]
Abstract
E. ulmoides (Eucommia ulmoides) has significant industrial and medicinal value and high market demand. E. ulmoides grows seedlings through sowing. According to previous studies, plant hormones have been shown to regulate seed germination. To understand the relationship between hormones and E. ulmoides seed germination, we focused on examining the changes in various indicators during the germination stage of E. ulmoides seeds. We measured the levels of physiological and hormone indicators in E. ulmoides seeds at different germination stages and found that the levels of abscisic acid (ABA), gibberellin (GA), and indole acetic acid (IAA) significantly varied as the seeds germinated. Furthermore, we confirmed that ABA, GA, and IAA are essential hormones in the germination of E. ulmoides seeds using Gene Ontology and Kyoto Encyclopedia of Genes and Genomics enrichment analyses of the transcriptome. The discovery of hormone-related synthesis pathways in the control group of Eucommia seeds at different germination stages further confirmed this conclusion. This study provides a basis for further research into the regulatory mechanisms of E. ulmoides seeds at different germination stages and the relationship between other seed germination and plant hormones.
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Affiliation(s)
- Jia Liu
- Department of Civil and Architecture and Engineering, Chuzhou University, Chuzhou, Anhui, China
- Anhui Low Carbon Highway Engineering Research Center, Chuzhou University, Anhui, China
| | - Sumei Qiu
- College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou, China
| | - Tingting Xue
- Department of Civil and Architecture and Engineering, Chuzhou University, Chuzhou, Anhui, China
| | - Yingdan Yuan
- College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou, China
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Meng J, Zhao Y, Song X, An Q, Wu Z. Deciphering the miRNA transcriptome of granulosa cells from dominant and subordinate follicles at first follicular wave in goat. Anim Biotechnol 2024; 35:2259967. [PMID: 37750325 DOI: 10.1080/10495398.2023.2259967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Abstract
In goats, most follicles in the ovaries will be atresia and only a few dominant follicles (DFs) may eventually mature and ovulate at a follicular wave. To investigate the potential microRNAs (miRNAs) that regulate the expression of genes associated with follicular dominance or atresia, small RNA sequencing was performed on granulosa cells of DF and subordinate follicle at the first follicular wave in goats. A total of 108 differentially expressed miRNAs were detected in the two types of follicle granulosa cells: 16 upregulated miRNAs and 92 downregulated miRNAs. Kyoto Encyclopedia of Genes and Genomes analysis of the target genes showed that TKTL1, LOC102187810, LOC102184409 and ALDOA are closely associated with follicle dominance and are involved in the pentose phosphate pathway. Furthermore, a coexpression network of miRNAs and follicular dominance-related genes was constructed. The qPCR results well correlated with the small RNA sequencing data. Our findings provide new insight for exploring the molecular mechanism of miRNAs in regulating follicular development in goats.
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Affiliation(s)
- Jinzhu Meng
- Key Laboratory for Biodiversity Conservation and Utilization in the Fanjing Mountain Region, Tongren University, Tongren, P.R. China
- College of Veterinary Medicine, Hunan Agricultural University, Changsha, P.R. China
| | - Yuanyuan Zhao
- Key Laboratory for Biodiversity Conservation and Utilization in the Fanjing Mountain Region, Tongren University, Tongren, P.R. China
| | - Xingchao Song
- Key Laboratory for Biodiversity Conservation and Utilization in the Fanjing Mountain Region, Tongren University, Tongren, P.R. China
| | - Qingming An
- Key Laboratory for Biodiversity Conservation and Utilization in the Fanjing Mountain Region, Tongren University, Tongren, P.R. China
| | - Zhenyang Wu
- Key Laboratory for Biodiversity Conservation and Utilization in the Fanjing Mountain Region, Tongren University, Tongren, P.R. China
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3
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Li C, Cai R, Shi W, Zhang H, Liu Z, Xie F, Chen Y, Hong Q. Comparative transcriptome analysis of ovaries and testes reveals sex-biased genes and pathways in zebrafish. Gene 2024; 901:148176. [PMID: 38242380 DOI: 10.1016/j.gene.2024.148176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/07/2024] [Accepted: 01/16/2024] [Indexed: 01/21/2024]
Abstract
Zebrafish (Danio rerio) is a widely recognized and extensively studied model organism in scientific research. The regulatory mechanism of gonadal development and differentiation of this species has aroused considerable attention. Nonetheless, the major sex-biased genes and pathways associated with gonadal development remain elusive. Therefore, to comprehend this intricate process, gonadal transcriptome sequencing was carried out to identify differentially expressed genes (DEGs) between the testes and ovaries of adult zebrafish. The preliminary assessment yielded a total of 23,529,272 and 23,521,368 clean reads from the cDNA libraries of ovaries and testes. Afterward, a comparative analysis of the transcriptome revealed 3,604 upregulated and 11,371 downregulated DEGs in the ovaries compared to the testes. Of these genes, 428 were exclusively expressed in females, while 3,516 were exclusively expressed in males. Additionally, further assessments were conducted to explore the functions associated with these DEGs in various biological processes. The data revealed their involvement in sex-biased pathways, such as progesterone-mediated oocyte maturation, oocyte meiosis, cytokine-cytokine receptor interaction, and cardiac muscle contraction. Finally, the expression levels of 14 sex-biased DEGs (cdc20, ccnb1, ypel3, chn1, bmp15, rspo1, tnfsf10, egfra, acta2, cox8a, gsdf, dmrt1, star, and cyp17a1) associated with the enriched pathways were subjected to further validation through qRT-PCR. The data acquired from these investigations offer valuable resources to support further exploration of the mechanisms governing sexual dimorphism and gonadal development in zebrafish.
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Affiliation(s)
- Cong Li
- Department of Hematology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230032, China
| | - Rui Cai
- School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China
| | - Wenhui Shi
- School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China
| | - Hao Zhang
- School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China
| | - Zhuang Liu
- School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China
| | - Fenfen Xie
- School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China.
| | - Yuanhua Chen
- School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China.
| | - Qiang Hong
- School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China.
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Zhou Z, Li C, Yuan Q, Chi Y, Li Y, Yan Y, Al-Farraj SA, Stover NA, Chen Z, Chen X. Single-cell transcriptomic analysis reveals genome evolution in predatory litostomatean ciliates. Eur J Protistol 2024; 93:126062. [PMID: 38368736 DOI: 10.1016/j.ejop.2024.126062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/20/2024]
Abstract
Many ciliated protists prey on other large microbial organisms, including other protists and microscopic metazoans. The ciliate class Litostomatea unites both predatory and endosymbiotic species. The evolution of predation ability in ciliates remains poorly understood, in part, due to a lack of genomic data. To fill this gap, we acquired the transcriptome profiles of six predatory litostomateans using single-cell sequencing technology and investigated their transcriptomic features. Our results show that: (1) in contrast to non-predatory ciliates, the predatory litostomateans have expanded gene families associated with transmembrane activity and reactive oxidative stress response pathways, potentially as a result of cellular behaviors such as fast contraction and extension; (2) the expansion of the calcium-activated BK potassium channel gene family, which hypothetically regulates cell contractility, is an ancient evolutionary event for the class Litostomatea, suggesting a rewired metabolism associated with the hunting behavior of predatory ciliates; and (3) three whole genome duplication (WGD) events have been detected in litostomateans, with genes associated with biosynthetic processes, transmembrane activity, and calcium-activated potassium channel activity being retained during the WGD events. In addition, we explored the evolutionary relationships among 17 ciliate species, including eight litostomateans, and provided a rich foundational dataset for future in-depth phylogenomic studies of Litostomatea. Our comprehensive analyses suggest that the rewired cellular metabolism via expanded gene families and WGD events might be the potential genetic basis for the predation ability of raptorial ciliates.
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Affiliation(s)
- Zhaorui Zhou
- Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao 266003, China
| | - Chao Li
- Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao 266003, China
| | - Qingxiang Yuan
- Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao 266003, China
| | - Yong Chi
- Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao 266003, China
| | - Yuqing Li
- Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao 266003, China
| | - Ying Yan
- Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao 266003, China
| | - Saleh A Al-Farraj
- Zoology Department, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
| | - Naomi A Stover
- Department of Biology, Bradley University, Peoria 61625, USA.
| | - Zigui Chen
- Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
| | - Xiao Chen
- Laboratory of Marine Protozoan Biodiversity and Evolution, Marine College, Shandong University, Weihai 264209, China; Suzhou Research Institute, Shandong University, Suzhou 215123, China.
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Wang MZ, Wu J, Zhang SL, Mao LM, Ohi-Toma T, Takano A, Zhang YH, Cameron KM, Li P. Species delimitation in Amana (Liliaceae): transcriptomes battle with evolutionary complexity. Cladistics 2024; 40:135-156. [PMID: 37983640 DOI: 10.1111/cla.12565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 10/10/2023] [Accepted: 10/18/2023] [Indexed: 11/22/2023] Open
Abstract
Species delimitation has long been a subject of controversy, and there are many alternative concepts and approaches used to define species in plants. The genus Amana (Liliaceae), known as "East Asian tulips" has a number of cryptic species and a huge genome size (1C = 21.48-57.35 pg). It also is intriguing how such a spring ephemeral genus thrives in subtropical areas. However, phylogenetic relationships and species delimitation within Amana are challenging. Here we included all species and 84 populations of Amana, which are collected throughout its distribution range. A variety of methods were used to clarify its species relationships based on a combination of morphological, ecological, genetic, evolutionary and phylogenetic species concepts. This evidence supports the recognition of at least 12 species in Amana. Moreover, we explored the complex evolutionary history within the genus and detected several historical hybridization and introgression events based on phylogenetic trees (transcriptomic and plastid), phylonetworks, admixture and ABBA-BABA analyses. Morphological traits have undergone parallel evolution in the genus. This spring ephemeral genus might have originated from a temperate region, yet finally thrives in subtropical areas, and three hypotheses about its adaptive evolution are proposed for future testing. In addition, we propose a new species, Amana polymorpha, from eastern Zhejiang Province, China. This research also demonstrates that molecular evidence at the genome level (such as transcriptomes) has greatly improved the accuracy and reasonability of species delimitation and taxon classification.
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Affiliation(s)
- Mei-Zhen Wang
- Laboratory of Systematic & Evolutionary Botany and Biodiversity, College of Life Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Jing Wu
- Laboratory of Systematic & Evolutionary Botany and Biodiversity, College of Life Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
| | - Sheng-Lu Zhang
- Plant Quarantine Station of Lin'an District, Hangzhou, 311300, Zhejiang, China
| | - Li-Mi Mao
- Nanjing Institute of Geology and Palaeontology, Chinese Academy of Sciences, Nanjing, 210008, Jiangsu, China
| | - Tetsuo Ohi-Toma
- Nature Fieldwork Center, Okayama University of Science, Okayama, 700-0005, Japan
| | - Atsuko Takano
- Museum of Nature and Human Activities, Hyogo 6 chome, Yayoigaoka, Sanda, Hyogo, 669-1546, Japan
| | - Yong-Hua Zhang
- College of Life and Environmental Science, Wenzhou University, Wenzhou, 325035, China
| | - Kenneth M Cameron
- Department of Botany, University of Wisconsin, Madison, WI, 53706, USA
| | - Pan Li
- Laboratory of Systematic & Evolutionary Botany and Biodiversity, College of Life Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China
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Machireddy M, Oberman AG, DeBiase L, Stephens M, Li J, Littlepage LE, Niebur GL. Controlled mechanical loading affects the osteocyte transcriptome in porcine trabecular bone in situ. Bone 2024; 181:117028. [PMID: 38309412 PMCID: PMC10923013 DOI: 10.1016/j.bone.2024.117028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 01/09/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
INTRODUCTION Osteocytes modulate bone adaptation in response to mechanical stimuli imparted by the deforming bone tissue in which they are encased by communicating with osteoclasts and osteoblasts as well as other osteocytes in the lacuna-canalicular network through secreted cytokines and chemokines. Understanding the transcriptional response of osteocytes to mechanical stimulation in situ could identify new targets to inhibit bone loss or enhance bone formation in the presence of diseases like osteoporosis or metastatic cancer. We compared the mechanically regulated transcriptional response of osteocytes in trabecular bone following one or three days of controlled mechanical loading. METHODS Porcine trabecular bone explants were cultured in a bioreactor for 48 h and subsequently loaded twice a day for one day or 3 days. RNA was isolated and sequenced, and the Tuxedo suite was used to identify differentially expressed genes and pathway analysis was conducted using Ingenuity Pathway Analysis (IPA). RESULTS There were about 4000 differentially expressed genes following in situ culture relative to fresh bone. One hundred six genes were differentially expressed between the loaded and non-loaded groups following one day of loading compared to 913 genes after 3 d of loading. Only 45 of these were coincident between the two time points, indicating an evolving transcriptome. Clustering and principal component analysis indicated differences between the loaded and non-loaded groups after 3 d of loading. DISCUSSION With sustained loading, there was a nine-fold increase in the number of differentially expressed genes, suggesting that osteocytes respond to loading through sequential activation of downstream genes in the same pathways. The differentially expressed genes were related to osteoarthritis, osteocyte, and chondrocyte signaling pathways. We noted that NFkB and TNF signaling are affected by early loading and this may drive downstream effects on the mechanobiological response. Moreover, these genes may regulate catabolic effects of mechanical disuse through their actions on pre-osteoclasts in the bone marrow niche.
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Affiliation(s)
- Meghana Machireddy
- Tissue Mechanics Laboratory, Bioengineering Graduate Program, University of Notre Dame, IN 46556, USA
| | - Alyssa G Oberman
- Tissue Mechanics Laboratory, Bioengineering Graduate Program, University of Notre Dame, IN 46556, USA
| | - Lucas DeBiase
- Dept. of Aerospace and Mechanical Engineering, University of Notre Dame, IN 46556, USA
| | - Melissa Stephens
- Genomics and Bioinformatics Core Facility, University of Notre Dame, IN 46556, USA
| | - Jun Li
- Dept. of Applied Mathematics, Computations, and Statistics, University of Notre Dame, IN 46556, USA
| | - Laurie E Littlepage
- Dept. of Chemistry and Biochemistry, University of Notre Dame, IN 46556, USA; Harper Cancer Research Institute, University of Notre Dame, IN 46556, USA
| | - Glen L Niebur
- Tissue Mechanics Laboratory, Bioengineering Graduate Program, University of Notre Dame, IN 46556, USA; Harper Cancer Research Institute, University of Notre Dame, IN 46556, USA; Dept. of Aerospace and Mechanical Engineering, University of Notre Dame, IN 46556, USA.
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Zhang L, Lou H, Huang Y, Dong L, Gong X, Zhang X, Bao W, Xiao R. Identification of Synonymous Pathogenic Variants in Monogenic Disorders by Integrating Exome with Transcriptome Sequencing. J Mol Diagn 2024; 26:267-277. [PMID: 38280421 DOI: 10.1016/j.jmoldx.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/23/2023] [Accepted: 12/20/2023] [Indexed: 01/29/2024] Open
Abstract
Exome sequencing is becoming a first-tier clinical diagnostic test for Mendelian diseases, drastically reducing the time and cost of diagnostic odyssey and improving the diagnosis rate. Despite its success, exome sequencing faces practical challenges in assessing the pathogenicity of numerous intronic and synonymous variants, leaving a significant proportion of patients undiagnosed. In this study, a whole-blood transcriptome database was constructed that showed the expression profile of 2981 Online Mendelian Inheritance in Man disease genes in blood samples. Meanwhile, a workflow integrating exome sequencing, blood transcriptome sequencing, and in silico prediction tools to identify and validate splicing-altering intronic or synonymous variants was proposed. Following this pipeline, seven synonymous variants in eight patients were discovered. Of these, the functional evidence of c.981G>A (PIGN), c.1161A>G (ALPL), c.858G>A (ATP6AP2), and c.1011G>T (MTHFR) have not been reported previously. RNA sequencing validation confirmed that these variants induced aberrant splicing, expanding the disease-causing variant spectrum of these genes. Overall, this study shows the feasibility of combining multi-omics data to identify splicing-altering variants, especially the power of RNA sequencing. It also reveals that synonymous variants, which often are overlooked in standard diagnostic approaches, comprise an important portion of unresolved genetic diseases.
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Affiliation(s)
- Lin Zhang
- Prenatal Diagnosis Center, Peking University People's Hospital, Beijing, China.
| | | | - Yanhong Huang
- Prenatal Diagnosis Center, Liaocheng Maternal and Child Health Care Hospital, Liaocheng, China
| | - Liping Dong
- Newborn Screening Center, Zibo Maternal and Child Health Care Hospital, Zibo, China
| | - Xueye Gong
- Department of Medical Genetics and Prenatal Diagnosis, Binzhou Maternal and Child Health Care Hospital, Binzhou, China
| | - Xiaoning Zhang
- Department of the Clinical Laboratory, Binzhou Maternal and Child Health Care Hospital, Binzhou, China
| | - Wenqi Bao
- Becreative Lab Co., Ltd., Beijing, China
| | - Rui Xiao
- National Engineering Laboratory for Key Technology of Birth Defect Control and Prevention, Screening and Diagnostic R&D Center, Hangzhou, China
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Yuan CU, Quah FX, Hemberg M. Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing. Mol Aspects Med 2024; 96:101255. [PMID: 38368637 DOI: 10.1016/j.mam.2024.101255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/30/2024] [Accepted: 02/07/2024] [Indexed: 02/20/2024]
Abstract
Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.
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Affiliation(s)
- Chengwei Ulrika Yuan
- Department of Biochemistry, University of Cambridge, Cambridge, UK; Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Fu Xiang Quah
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Martin Hemberg
- Gene Lay Institute, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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Shen N, Xie H, Liu K, Li X, Wang L, Deng Y, Chen L, Bian Y, Xiao Y. Near-gapless genome and transcriptome analyses provide insights into fruiting body development in Lentinula edodes. Int J Biol Macromol 2024; 263:130610. [PMID: 38447851 DOI: 10.1016/j.ijbiomac.2024.130610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/01/2024] [Accepted: 03/02/2024] [Indexed: 03/08/2024]
Abstract
Fruiting body development in macrofungi is an intensive research subject. In this study, high-quality genomes were assembled for two sexually compatible monokaryons from a heterokaryotic Lentinula edodes strain WX1, and variations in L. edodes genomes were analyzed. Specifically, differential gene expression and allele-specific expression (ASE) were analyzed using the two monokaryotic genomes and transcriptome data from four different stages of fruiting body development in WX1. Results revealed that after aeration, mycelia sensed cell wall stress, pheromones, and a decrease in CO2 concentration, leading to up-regulated expression in genes related to cell adhesion, cell wall remodeling, proteolysis, and lipid metabolism, which may promote primordium differentiation. Aquaporin genes and those related to proteolysis, mitosis, lipid, and carbohydrate metabolism may play important roles in primordium development, while genes related to tissue differentiation and sexual reproduction were active in fruiting body. Several essential genes for fruiting body development were allele-specifically expressed and the two nuclear types could synergistically regulate fruiting body development by dominantly expressing genes with different functions. ASE was probably induced by long terminal repeat-retrotransposons. Findings here contribute to the further understanding of the mechanism of fruiting body development in macrofungi.
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Affiliation(s)
- Nan Shen
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Haoyu Xie
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Kefang Liu
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Xinru Li
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Lu Wang
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Youjin Deng
- College of Life Science, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China
| | - Lianfu Chen
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Yinbing Bian
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
| | - Yang Xiao
- State Key Laboratory of Agricultural Microbiology, Hubei Hongshan Laboratory, Institute of Applied Mycology, Huazhong Agricultural University, Wuhan, Hubei 430070, China.
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Groiss S, Viertler C, Kap M, Bernhardt G, Mischinger HJ, Sieuwerts A, Verhoef C, Riegman P, Kruhøffer M, Svec D, Sjöback SR, Becker KF, Zatloukal K. Inter-patient heterogeneity in the hepatic ischemia-reperfusion injury transcriptome: Implications for research and diagnostics. N Biotechnol 2024; 79:20-29. [PMID: 38072306 DOI: 10.1016/j.nbt.2023.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 12/07/2023] [Indexed: 01/16/2024]
Abstract
Cellular responses induced by surgical procedure or ischemia-reperfusion injury (IRI) may severely alter transcriptome profiles and complicate molecular diagnostics. To investigate this effect, we characterized such pre-analytical effects in 143 non-malignant liver samples obtained from 30 patients at different time points of ischemia during surgery from two individual cohorts treated either with the Pringle manoeuvre or total vascular exclusion. Transcriptomics profiles were analyzed by Affymetrix microarrays and expression of selected mRNAs was validated by RT-PCR. We found 179 mutually deregulated genes which point to elevated cytokine signaling with NFκB as a dominant pathway in ischemia responses. In contrast to ischemia, reperfusion induced pro-apoptotic and pro-inflammatory cascades involving TNF, NFκB and MAPK pathways. FOS and JUN were down-regulated in steatosis compared to their up-regulation in normal livers. Surprisingly, molecular signatures of underlying primary and secondary cancers were present in non-tumor tissue. The reported inter-patient variability might reflect differences in individual stress responses and impact of underlying disease conditions. Furthermore, we provide a set of 230 pre-analytically highly robust genes identified from histologically normal livers (<2% covariation across both cohorts) that might serve as reference genes and could be particularly suited for future diagnostic applications.
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Affiliation(s)
- Silvia Groiss
- Diagnostic & Research Institute of Pathology, Medical University of Graz, 8010 Graz, Austria
| | - Christian Viertler
- Diagnostic & Research Institute of Pathology, Medical University of Graz, 8010 Graz, Austria
| | - Marcel Kap
- Pathology Department, Erasmus University Medical Center, 3015CN Rotterdam, the Netherlands
| | - Gerwin Bernhardt
- Division of General Surgery, Department of Surgery, Medical University of Graz, 8010 Graz, Austria; Department of Orthopedics and Trauma Surgery, Medical University of Graz, 8010 Graz, Austria
| | - Hans-Jörg Mischinger
- Division of General Surgery, Department of Surgery, Medical University of Graz, 8010 Graz, Austria
| | - Anieta Sieuwerts
- Department of Medical Oncology, Erasmus MC Cancer Institute and Cancer Genomics Netherlands, Erasmus University Medical Center, 3015CN Rotterdam, the Netherlands
| | - Cees Verhoef
- Department of Surgical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center, 3015CN Rotterdam, the Netherlands
| | - Peter Riegman
- Pathology Department, Erasmus University Medical Center, 3015CN Rotterdam, the Netherlands
| | | | - David Svec
- Laboratory of Gene Expression, Institute of Biotechnology CAS, 252 50 Vestec, Czech Republic
| | | | | | - Kurt Zatloukal
- Diagnostic & Research Institute of Pathology, Medical University of Graz, 8010 Graz, Austria.
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Nanni A, Titus-McQuillan J, Bankole KS, Pardo-Palacios F, Signor S, Vlaho S, Moskalenko O, Morse A, Rogers RL, Conesa A, McIntyre LM. Nucleotide-level distance metrics to quantify alternative splicing implemented in TranD. Nucleic Acids Res 2024; 52:e28. [PMID: 38340337 PMCID: PMC10954468 DOI: 10.1093/nar/gkae056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 11/29/2023] [Accepted: 01/18/2024] [Indexed: 02/12/2024] Open
Abstract
Advances in affordable transcriptome sequencing combined with better exon and gene prediction has motivated many to compare transcription across the tree of life. We develop a mathematical framework to calculate complexity and compare transcript models. Structural features, i.e. intron retention (IR), donor/acceptor site variation, alternative exon cassettes, alternative 5'/3' UTRs, are compared and the distance between transcript models is calculated with nucleotide level precision. All metrics are implemented in a PyPi package, TranD and output can be used to summarize splicing patterns for a transcriptome (1GTF) and between transcriptomes (2GTF). TranD output enables quantitative comparisons between: annotations augmented by empirical RNA-seq data and the original transcript models; transcript model prediction tools for longread RNA-seq (e.g. FLAIR versus Isoseq3); alternate annotations for a species (e.g. RefSeq vs Ensembl); and between closely related species. In C. elegans, Z. mays, D. melanogaster, D. simulans and H. sapiens, alternative exons were observed more frequently in combination with an alternative donor/acceptor than alone. Transcript models in RefSeq and Ensembl are linked and both have unique transcript models with empirical support. D. melanogaster and D. simulans, share many transcript models and long-read RNAseq data suggests that both species are under-annotated. We recommend combined references.
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Affiliation(s)
- Adalena Nanni
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- University of Florida Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - James Titus-McQuillan
- University of North Carolina at Charlotte Department of Bioinformatics and Genomics Charlotte, NC, USA
| | - Kinfeosioluwa S Bankole
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- University of Florida Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | | | - Sarah Signor
- Department of Biological Sciences, North Dakota State University, Fargo, ND, USA
| | - Srna Vlaho
- Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Oleksandr Moskalenko
- University of Florida Research Computing, University of Florida, Gainesville, FL 32611, USA
| | - Alison M Morse
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- University of Florida Genetics Institute, University of Florida, Gainesville, FL 32611, USA
| | - Rebekah L Rogers
- University of North Carolina at Charlotte Department of Bioinformatics and Genomics Charlotte, NC, USA
| | - Ana Conesa
- Institute for Integrative Systems Biology. Spanish National Research Council, Paterna, Spain
| | - Lauren M McIntyre
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32611, USA
- University of Florida Genetics Institute, University of Florida, Gainesville, FL 32611, USA
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12
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Guo X, Ning J, Chen Y, Liu G, Zhao L, Fan Y, Sun S. Recent advances in differential expression analysis for single-cell RNA-seq and spatially resolved transcriptomic studies. Brief Funct Genomics 2024; 23:95-109. [PMID: 37022699 DOI: 10.1093/bfgp/elad011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 12/09/2022] [Accepted: 03/10/2023] [Indexed: 04/07/2023] Open
Abstract
Differential expression (DE) analysis is a necessary step in the analysis of single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) data. Unlike traditional bulk RNA-seq, DE analysis for scRNA-seq or SRT data has unique characteristics that may contribute to the difficulty of detecting DE genes. However, the plethora of DE tools that work with various assumptions makes it difficult to choose an appropriate one. Furthermore, a comprehensive review on detecting DE genes for scRNA-seq data or SRT data from multi-condition, multi-sample experimental designs is lacking. To bridge such a gap, here, we first focus on the challenges of DE detection, then highlight potential opportunities that facilitate further progress in scRNA-seq or SRT analysis, and finally provide insights and guidance in selecting appropriate DE tools or developing new computational DE methods.
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Affiliation(s)
- Xiya Guo
- School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory of Trace Elements and Endemic Diseases, Center for Single Cell Omics and Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| | - Jin Ning
- School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory of Trace Elements and Endemic Diseases, Center for Single Cell Omics and Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| | - Yuanze Chen
- School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory of Trace Elements and Endemic Diseases, Center for Single Cell Omics and Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| | - Guoliang Liu
- School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory of Trace Elements and Endemic Diseases, Center for Single Cell Omics and Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| | - Liyan Zhao
- School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory of Trace Elements and Endemic Diseases, Center for Single Cell Omics and Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| | - Yue Fan
- School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory of Trace Elements and Endemic Diseases, Center for Single Cell Omics and Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
| | - Shiquan Sun
- School of Public Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
- Key Laboratory of Trace Elements and Endemic Diseases, Center for Single Cell Omics and Health, Xi'an Jiaotong University, Xi'an, Shaanxi 710061, P.R. China
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13
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Jones EF, Haldar A, Oza VH, Lasseigne BN. Quantifying transcriptome diversity: a review. Brief Funct Genomics 2024; 23:83-94. [PMID: 37225889 DOI: 10.1093/bfgp/elad019] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 04/14/2023] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
Following the central dogma of molecular biology, gene expression heterogeneity can aid in predicting and explaining the wide variety of protein products, functions and, ultimately, heterogeneity in phenotypes. There is currently overlapping terminology used to describe the types of diversity in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptome diversity as a measure of the heterogeneity in (1) the expression of all genes within a sample or a single gene across samples in a population (gene-level diversity) or (2) the isoform-specific expression of a given gene (isoform-level diversity). We first overview modulators and quantification of transcriptome diversity at the gene level. Then, we discuss the role alternative splicing plays in driving transcript isoform-level diversity and how it can be quantified. Additionally, we overview computational resources for calculating gene-level and isoform-level diversity for high-throughput sequencing data. Finally, we discuss future applications of transcriptome diversity. This review provides a comprehensive overview of how gene expression diversity arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms and species.
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Affiliation(s)
- Emma F Jones
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anisha Haldar
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Vishal H Oza
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Brittany N Lasseigne
- The Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, AL, USA
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14
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Melton HJ, Zhang Z, Wu C. SUMMIT-FA: a new resource for improved transcriptome imputation using functional annotations. Hum Mol Genet 2024; 33:624-635. [PMID: 38129112 PMCID: PMC10954367 DOI: 10.1093/hmg/ddad205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/24/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
Transcriptome-wide association studies (TWAS) integrate gene expression prediction models and genome-wide association studies (GWAS) to identify gene-trait associations. The power of TWAS is determined by the sample size of GWAS and the accuracy of the expression prediction model. Here, we present a new method, the Summary-level Unified Method for Modeling Integrated Transcriptome using Functional Annotations (SUMMIT-FA), which improves gene expression prediction accuracy by leveraging functional annotation resources and a large expression quantitative trait loci (eQTL) summary-level dataset. We build gene expression prediction models in whole blood using SUMMIT-FA with the comprehensive functional database MACIE and eQTL summary-level data from the eQTLGen consortium. We apply these models to GWAS for 24 complex traits and show that SUMMIT-FA identifies significantly more gene-trait associations and improves predictive power for identifying "silver standard" genes compared to several benchmark methods. We further conduct a simulation study to demonstrate the effectiveness of SUMMIT-FA.
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Affiliation(s)
- Hunter J Melton
- Department of Statistics, Florida State University, 214 Rogers Building, 117 N. Woodward Avenue, Tallahassee, FL 32306, United States
| | - Zichen Zhang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 7007 Bertner Avenue, Unit 1689, Houston, TX 77030, United States
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 7007 Bertner Avenue, Unit 1689, Houston, TX 77030, United States
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15
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Josephs-Spaulding J, Rajput A, Hefner Y, Szubin R, Balasubramanian A, Li G, Zielinski DC, Jahn L, Sommer M, Phaneuf P, Palsson BO. Reconstructing the transcriptional regulatory network of probiotic L. reuteri is enabled by transcriptomics and machine learning. mSystems 2024; 9:e0125723. [PMID: 38349131 PMCID: PMC10949432 DOI: 10.1128/msystems.01257-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 01/09/2024] [Indexed: 03/20/2024] Open
Abstract
Limosilactobacillus reuteri, a probiotic microbe instrumental to human health and sustainable food production, adapts to diverse environmental shifts via dynamic gene expression. We applied the independent component analysis (ICA) to 117 RNA-seq data sets to decode its transcriptional regulatory network (TRN), identifying 35 distinct signals that modulate specific gene sets. Our findings indicate that the ICA provides a qualitative advancement and captures nuanced relationships within gene clusters that other methods may miss. This study uncovers the fundamental properties of L. reuteri's TRN and deepens our understanding of its arginine metabolism and the co-regulation of riboflavin metabolism and fatty acid conversion. It also sheds light on conditions that regulate genes within a specific biosynthetic gene cluster and allows for the speculation of the potential role of isoprenoid biosynthesis in L. reuteri's adaptive response to environmental changes. By integrating transcriptomics and machine learning, we provide a system-level understanding of L. reuteri's response mechanism to environmental fluctuations, thus setting the stage for modeling the probiotic transcriptome for applications in microbial food production. IMPORTANCE We have studied Limosilactobacillus reuteri, a beneficial probiotic microbe that plays a significant role in our health and production of sustainable foods, a type of foods that are nutritionally dense and healthier and have low-carbon emissions compared to traditional foods. Similar to how humans adapt their lifestyles to different environments, this microbe adjusts its behavior by modulating the expression of genes. We applied machine learning to analyze large-scale data sets on how these genes behave across diverse conditions. From this, we identified 35 unique patterns demonstrating how L. reuteri adjusts its genes based on 50 unique environmental conditions (such as various sugars, salts, microbial cocultures, human milk, and fruit juice). This research helps us understand better how L. reuteri functions, especially in processes like breaking down certain nutrients and adapting to stressful changes. More importantly, with our findings, we become closer to using this knowledge to improve how we produce more sustainable and healthier foods with the help of microbes.
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Affiliation(s)
- Jonathan Josephs-Spaulding
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
| | - Akanksha Rajput
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Ying Hefner
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Richard Szubin
- Department of Bioengineering, University of California, San Diego, California, USA
| | | | - Gaoyuan Li
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Daniel C. Zielinski
- Department of Bioengineering, University of California, San Diego, California, USA
| | - Leonie Jahn
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
| | - Morten Sommer
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
| | - Patrick Phaneuf
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
| | - Bernhard O. Palsson
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Copenhagen, Denmark
- Department of Bioengineering, University of California, San Diego, California, USA
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16
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Xu X, Khunsriraksakul C, Eales JM, Rubin S, Scannali D, Saluja S, Talavera D, Markus H, Wang L, Drzal M, Maan A, Lay AC, Prestes PR, Regan J, Diwadkar AR, Denniff M, Rempega G, Ryszawy J, Król R, Dormer JP, Szulinska M, Walczak M, Antczak A, Matías-García PR, Waldenberger M, Woolf AS, Keavney B, Zukowska-Szczechowska E, Wystrychowski W, Zywiec J, Bogdanski P, Danser AHJ, Samani NJ, Guzik TJ, Morris AP, Liu DJ, Charchar FJ, Tomaszewski M. Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets. Nat Commun 2024; 15:2359. [PMID: 38504097 PMCID: PMC10950894 DOI: 10.1038/s41467-024-46132-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 02/14/2024] [Indexed: 03/21/2024] Open
Abstract
Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.
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Affiliation(s)
- Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | | | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sebastien Rubin
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Scannali
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sushant Saluja
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Talavera
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Havell Markus
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Lida Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Maciej Drzal
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Akhlaq Maan
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Abigail C Lay
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Priscilla R Prestes
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
| | - Jeniece Regan
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Avantika R Diwadkar
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Grzegorz Rempega
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Jakub Ryszawy
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Robert Król
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - John P Dormer
- Department of Cellular Pathology, University Hospitals of Leicester, Leicester, UK
| | - Monika Szulinska
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Marta Walczak
- Department of Internal Diseases, Metabolic Disorders and Arterial Hypertension, Poznan University of Medical Sciences, Poznan, Poland
| | - Andrzej Antczak
- Department of Urology and Uro-oncology, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Pamela R Matías-García
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Adrian S Woolf
- Division of Cell Matrix Biology and Regenerative Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Royal Manchester Children's Hospital and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Bernard Keavney
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK
| | | | - Wojciech Wystrychowski
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - Joanna Zywiec
- Department of Internal Medicine, Diabetology and Nephrology, Zabrze, Medical University of Silesia, Katowice, Poland
| | - Pawel Bogdanski
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - A H Jan Danser
- Department of Internal Medicine, Division of Pharmacology and Vascular Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Tomasz J Guzik
- Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kraków, Poland
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal & Dermatological Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Fadi J Charchar
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Department of Physiology, University of Melbourne, Melbourne, Australia
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK.
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK.
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17
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Chen F, Zhang Y, Sedlazeck FJ, Creighton CJ. Germline structural variation globally impacts the cancer transcriptome including disease-relevant genes. Cell Rep Med 2024; 5:101446. [PMID: 38442712 DOI: 10.1016/j.xcrm.2024.101446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 01/01/2024] [Accepted: 02/06/2024] [Indexed: 03/07/2024]
Abstract
Germline variation and somatic alterations contribute to the molecular profile of cancers. We combine RNA with whole genome sequencing across 1,218 cancer patients to determine the extent germline structural variants (SVs) impact expression of nearby genes. For hundreds of genes, recurrent and common germline SV breakpoints within 100 kb associate with increased or decreased expression in tumors spanning various tissues of origin. A significant fraction of germline SV expression associations involves duplication of intergenic enhancers or 3' UTR disruption. Genes altered by both somatic and germline SVs include ATRX and CEBPA. Genes essential in cancer cell lines include BARD1 and IRS2. Genes with both expression and germline SV breakpoint patterns associated with patient survival include GCLM. Our results capture a class of phenotypic variation at work in the disease setting, including genes with cancer roles. Specific germline SVs represent potential cancer risk variants for genetic testing, including those involving genes with targeting implications.
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Affiliation(s)
- Fengju Chen
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yiqun Zhang
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Computer Science, Rice University, Houston, TX 77005, USA
| | - Chad J Creighton
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA.
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18
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Wu QZ, Lin WQ, Wu JY, Cao LW, Li HH, Gao R, Du WZ, Sheng GP, Chen YG, Li WW. Transcriptomic Insights into Metabolism-Dependent Biosynthesis of Bacterial Nanocellulose. ACS Appl Bio Mater 2024; 7:1801-1809. [PMID: 38416780 DOI: 10.1021/acsabm.3c01222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2024]
Abstract
Bacterial nanocellulose (BNC) is an attractive green-synthesized biomaterial for biomedical applications and various other applications. However, effective engineering of BNC production has been limited by our poor knowledge of the related metabolic processes. In contrast to the traditional perception that genome critically determines biosynthesis behaviors, here we discover that the glucose metabolism could also drastically affect the BNC synthesis in Gluconacetobacter hansenii. The transcriptomic profiles of two model BNC-producing strains, G. hansenii ATCC 53582 and ATCC 23769, which have highly similar genomes but drastically different BNC yields, were compared. The results show that their BNC synthesis capacities were highly related to metabolic activities such as ATP synthesis, ion transport protein assembly, and carbohydrate metabolic processes, confirming an important role of metabolism-related transcriptomes in governing the BNC yield. Our findings provide insights into the microbial biosynthesis behaviors from a transcriptome perspective, potentially guiding cellular engineering for biomaterial synthesis.
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Affiliation(s)
- Qi-Zhong Wu
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
- Sustainable Energy and Environmental Materials Innovation Center, Suzhou Institute for Advanced Research of USTC, Suzhou 215123, China
| | - Wei-Qiang Lin
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Jian-Yu Wu
- Sustainable Energy and Environmental Materials Innovation Center, Suzhou Institute for Advanced Research of USTC, Suzhou 215123, China
- CAS Key Laboratory of Urban Pollutant Conversion, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Li-Wen Cao
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Hui-Hui Li
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
- Sustainable Energy and Environmental Materials Innovation Center, Suzhou Institute for Advanced Research of USTC, Suzhou 215123, China
| | - Rui Gao
- Sustainable Energy and Environmental Materials Innovation Center, Suzhou Institute for Advanced Research of USTC, Suzhou 215123, China
| | - Wen-Zheng Du
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China
| | - Guo-Ping Sheng
- CAS Key Laboratory of Urban Pollutant Conversion, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
| | - Yin-Guang Chen
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Wen-Wei Li
- Sustainable Energy and Environmental Materials Innovation Center, Suzhou Institute for Advanced Research of USTC, Suzhou 215123, China
- CAS Key Laboratory of Urban Pollutant Conversion, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China
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19
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Holsten L, Dahm K, Oestreich M, Becker M, Ulas T. hCoCena: A toolbox for network-based co-expression analysis and horizontal integration of transcriptomic datasets. STAR Protoc 2024; 5:102922. [PMID: 38427570 PMCID: PMC10918327 DOI: 10.1016/j.xpro.2024.102922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/09/2024] [Accepted: 02/13/2024] [Indexed: 03/03/2024] Open
Abstract
As the number and complexity of transcriptomic datasets increase, there is a rising demand for accessible and user-friendly analysis tools. Here, we present hCoCena (horizontal construction of co-expression networks and analysis), a toolbox facilitating the analysis of a single dataset, as well as the joint analysis of multiple datasets. We describe steps for workspace setup, formatting tables, data processing, and network integration. We then detail procedures for gene clustering, gene set enrichment analysis, and transcription factor enrichment analysis. For complete details on the use and execution of this protocol, please refer to Oestreich et al.1.
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Affiliation(s)
- Lisa Holsten
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany; PRECISE Platform for Single Cell Genomics and Epigenomics, DZNE, and University of Bonn, 53127 Bonn, Germany; Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; Department of Pediatrics, University Hospital Würzburg, 97080 Würzburg, Germany.
| | - Kilian Dahm
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany; PRECISE Platform for Single Cell Genomics and Epigenomics, DZNE, and University of Bonn, 53127 Bonn, Germany; Department of Pediatrics, University Hospital Würzburg, 97080 Würzburg, Germany
| | - Marie Oestreich
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany; Modular High-Performance Computing and Artificial Intelligence, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Matthias Becker
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany; Modular High-Performance Computing and Artificial Intelligence, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Thomas Ulas
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany; PRECISE Platform for Single Cell Genomics and Epigenomics, DZNE, and University of Bonn, 53127 Bonn, Germany; Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany.
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20
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Zhou X, Seow WY, Ha N, Cheng TH, Jiang L, Boonruangkan J, Goh JJL, Prabhakar S, Chou N, Chen KH. Highly sensitive spatial transcriptomics using FISHnCHIPs of multiple co-expressed genes. Nat Commun 2024; 15:2342. [PMID: 38491027 PMCID: PMC10943009 DOI: 10.1038/s41467-024-46669-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 03/04/2024] [Indexed: 03/18/2024] Open
Abstract
High-dimensional, spatially resolved analysis of intact tissue samples promises to transform biomedical research and diagnostics, but existing spatial omics technologies are costly and labor-intensive. We present Fluorescence In Situ Hybridization of Cellular HeterogeneIty and gene expression Programs (FISHnCHIPs) for highly sensitive in situ profiling of cell types and gene expression programs. FISHnCHIPs achieves this by simultaneously imaging ~2-35 co-expressed genes (clustered into modules) that are spatially co-localized in tissues, resulting in similar spatial information as single-gene Fluorescence In Situ Hybridization (FISH), but with ~2-20-fold higher sensitivity. Using FISHnCHIPs, we image up to 53 modules from the mouse kidney and mouse brain, and demonstrate high-speed, large field-of-view profiling of a whole tissue section. FISHnCHIPs also reveals spatially restricted localizations of cancer-associated fibroblasts in a human colorectal cancer biopsy. Overall, FISHnCHIPs enables fast, robust, and scalable cell typing of tissues with normal physiology or undergoing pathogenesis.
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Affiliation(s)
- Xinrui Zhou
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Wan Yi Seow
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Norbert Ha
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Teh How Cheng
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Lingfan Jiang
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Jeeranan Boonruangkan
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Jolene Jie Lin Goh
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Shyam Prabhakar
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore
| | - Nigel Chou
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore.
| | - Kok Hao Chen
- Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Singapore.
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21
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Liao Y, Rao Z, Huang S, Zhao D. Protocol to analyze immune cells in the tumor microenvironment by transcriptome using machine learning. STAR Protoc 2024; 5:102684. [PMID: 38219153 PMCID: PMC10826422 DOI: 10.1016/j.xpro.2023.102684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/15/2023] [Accepted: 10/10/2023] [Indexed: 01/16/2024] Open
Abstract
Immunotherapy is a promising strategy to treat cancer. Here, we present a protocol for analyzing the transcriptome-based phenotypic alterations and immune cell infiltration in the tumor microenvironment. We describe steps for integrating single-cell RNA sequencing (scRNA-seq) data, comparing phenotypes and origins of mononuclear phagocytes, inferring the differentiation trajectory and infiltration process, and identifying infiltration-associated genes using machine learning. We then detail procedures for exploring the impact of these genes in prognosis through the integrated microarray and bulk RNA-seq data to obtain potential drug targets. For complete details on the use and execution of this protocol, please refer to Liao et al.1.
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Affiliation(s)
- Yunxi Liao
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China
| | - Ziyan Rao
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China
| | - Shaodong Huang
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China
| | - Dongyu Zhao
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China.
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22
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Lin W, Yang H, Lin J, Yang X, Liao Z, Zheng Y, Luo P, Liu C. OralExplorer: a web server for exploring the mechanisms of oral inflammatory diseases. J Transl Med 2024; 22:282. [PMID: 38491529 PMCID: PMC10943789 DOI: 10.1186/s12967-024-05019-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/22/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Oral inflammatory diseases are localized infectious diseases primarily caused by oral pathogens with the potential for serious systemic complications. However, publicly available datasets for these diseases are underutilized. To address this issue, a web tool called OralExplorer was developed. This tool integrates the available data and provides comprehensive online bioinformatic analysis. METHODS Human oral inflammatory disease-related datasets were obtained from the GEO database and normalized using a standardized process. Transcriptome data were then subjected to differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis, and visualization. The single-cell sequencing data was visualized as cluster plot, feature plot, and heatmaps. The web platform was primarily built using Shiny. The biomarkers identified in OralExplorer were validated using local clinical samples through qPCR and IHC. RESULTS A total of 35 human oral inflammatory disease-related datasets, covering 6 main disease types and 901 samples, were included in the study to identify potential molecular signatures of the mechanisms of oral diseases. OralExplorer consists of 5 main analysis modules (differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis and single-cell analysis), with multiple visualization options. The platform offers a simple and intuitive interface, high-quality images for visualization, and detailed analysis results tables for easy access by users. Six markers (IL1β, SRGN, CXCR1, FGR, ARHGEF2, and PTAFR) were identified by OralExplorer. qPCR- and IHC-based experimental validation showed significantly higher levels of these genes in the periodontitis group. CONCLUSIONS OralExplorer is a comprehensive analytical platform for oral inflammatory diseases. It allows users to interactively explore the molecular mechanisms underlying the action and regression of these diseases. It also aids dental researchers in unlocking the potential value of transcriptomics data related to oral diseases. OralExplorer can be accessed at https://smuonco.shinyapps.io/OralExplorer/ (Alternate URL: http://robinl-lab.com/OralExplorer ).
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Affiliation(s)
- Weiyin Lin
- Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Hong Yang
- The Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jiayu Lin
- Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Xia Yang
- Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Zhihao Liao
- Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Yifan Zheng
- Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China
| | - Peng Luo
- The Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
| | - Chufeng Liu
- Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, China.
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23
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Bai R, Luo Y. Exploring the role of mitochondrial-associated and peripheral neuropathy genes in the pathogenesis of diabetic peripheral neuropathy. BMC Neurol 2024; 24:95. [PMID: 38481183 PMCID: PMC10936109 DOI: 10.1186/s12883-024-03589-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 02/27/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Diabetic peripheral neuropathy (DPN) is a prevalent and serious complication of diabetes mellitus, impacting the nerves in the limbs and leading to symptoms like pain, numbness, and diminished function. While the exact molecular and immune mechanisms underlying DPN remain incompletely understood, recent findings indicate that mitochondrial dysfunction may play a role in the advancement of this diabetic condition. METHODS Two RNA transcriptome datasets (codes: GSE185011 and GSE95849), comprising samples from diabetic peripheral neuropathy (DPN) patients and healthy controls (HC), were retrieved from the Gene Expression Omnibus (GEO) database hosted by the National Center for Biotechnology Information (NCBI). Subsequently, differential expression analysis and gene set enrichment analysis were performed. Protein-protein interaction (PPI) networks were constructed to pinpoint key hub genes associated with DPN, with a specific emphasis on genes related to mitochondria and peripheral neuropathy disease (PND) that displayed differential expression. Additionally, the study estimated the levels of immune cell infiltration in both the HC and DPN samples. To validate the findings, quantitative polymerase chain reaction (qPCR) was employed to confirm the differential expression of selected genes in the DPN samples. RESULTS This research identifies four hub genes associated mitochondria or PN. Furthermore, the analysis revealed increased immune cell infiltration in DPN tissues, particularly notable for macrophages and T cells. Additionally, our investigation identified potential drug candidates capable of regulating the expression of the four hub genes. These findings were corroborated by qPCR results, reinforcing the credibility of our bioinformatics analysis. CONCLUSIONS This study provides a comprehensive overview of the molecular and immunological characteristics of DPN, based on both bioinformatics and experimental methods.
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Affiliation(s)
- Ruojing Bai
- Department of Geriatric Medicine, School of Clinical Medicine, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China
| | - Yuanyuan Luo
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China.
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24
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Liu S, Ezran C, Wang MFZ, Li Z, Awayan K, Long JZ, De Vlaminck I, Wang S, Epelbaum J, Kuo CS, Terrien J, Krasnow MA, Ferrell JE. An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome. Nat Commun 2024; 15:2188. [PMID: 38467625 PMCID: PMC10928088 DOI: 10.1038/s41467-024-46070-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 02/07/2024] [Indexed: 03/13/2024] Open
Abstract
Hormones mediate long-range cell communication and play vital roles in physiology, metabolism, and health. Traditionally, endocrinologists have focused on one hormone or organ system at a time. Yet, hormone signaling by its very nature connects cells of different organs and involves crosstalk of different hormones. Here, we leverage the organism-wide single cell transcriptional atlas of a non-human primate, the mouse lemur (Microcebus murinus), to systematically map source and target cells for 84 classes of hormones. This work uncovers previously-uncharacterized sites of hormone regulation, and shows that the hormonal signaling network is densely connected, decentralized, and rich in feedback loops. Evolutionary comparisons of hormonal genes and their expression patterns show that mouse lemur better models human hormonal signaling than mouse, at both the genomic and transcriptomic levels, and reveal primate-specific rewiring of hormone-producing/target cells. This work complements the scale and resolution of classical endocrine studies and sheds light on primate hormone regulation.
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Affiliation(s)
- Shixuan Liu
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Camille Ezran
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Michael F Z Wang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Zhengda Li
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyle Awayan
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Jonathan Z Long
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Sarafan ChEM-H, Stanford, CA, USA
| | - Iwijn De Vlaminck
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Sheng Wang
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Jacques Epelbaum
- Adaptive Mechanisms and Evolution (MECADEV), UMR 7179, National Center for Scientific Research, National Museum of Natural History, Brunoy, France
| | - Christin S Kuo
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jérémy Terrien
- Adaptive Mechanisms and Evolution (MECADEV), UMR 7179, National Center for Scientific Research, National Museum of Natural History, Brunoy, France
| | - Mark A Krasnow
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford, CA, USA.
| | - James E Ferrell
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.
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25
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Nemes K, Benő A, Topolcsányi P, Magó É, Fűr GM, Pongor LŐS. Predicting drug response of small cell lung cancer cell lines based on enrichment analysis of complex gene signatures. J Biotechnol 2024; 383:86-93. [PMID: 38280466 DOI: 10.1016/j.jbiotec.2024.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 01/23/2024] [Indexed: 01/29/2024]
Abstract
Advances in the field of genomics and transcriptomics have enabled researchers to identify gene signatures related to development and treatment of Small Cell Lung Cancer. In most cases, complex gene expression patterns are identified, comprising of genes with differential behavior. Most tools use single-genes as predictors of drug response, with only limited options for multi-gene use. Here we examine the potential of predicting drug response using these complex gene expression signatures by employing clustering and signal enrichment in Small Cell Lung Cancer. Our results demonstrate clustering genes from complex expression patterns helps identify differential activity of gene groups with alternate function which can then be used to predict drug response.
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Affiliation(s)
- Kolos Nemes
- Cancer Genomics and Epigenetics Core Group, Hungarian Center of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Alexandra Benő
- Cancer Genomics and Epigenetics Core Group, Hungarian Center of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Petronella Topolcsányi
- Cancer Genomics and Epigenetics Core Group, Hungarian Center of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Éva Magó
- Cancer Genomics and Epigenetics Core Group, Hungarian Center of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - Gabriella Mihalekné Fűr
- Cancer Genomics and Epigenetics Core Group, Hungarian Center of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary
| | - L Őrinc S Pongor
- Cancer Genomics and Epigenetics Core Group, Hungarian Center of Excellence for Molecular Medicine (HCEMM), Szeged, Hungary.
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26
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Sun Y, Lan Y, Rädecker N, Sheng H, Diaz-Pulido G, Qian PY, Huang H. Gene expression of Pocillopora damicornis coral larvae in response to acidification and ocean warming. BMC Genom Data 2024; 25:28. [PMID: 38459437 PMCID: PMC10924396 DOI: 10.1186/s12863-024-01211-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 02/19/2024] [Indexed: 03/10/2024] Open
Abstract
OBJECTIVES The endosymbiosis with Symbiodiniaceae is key to the ecological success of reef-building corals. However, climate change is threatening to destabilize this symbiosis on a global scale. Most studies looking into the response of corals to heat stress and ocean acidification focus on coral colonies. As such, our knowledge of symbiotic interactions and stress response in other stages of the coral lifecycle remains limited. Establishing transcriptomic resources for coral larvae under stress can thus provide a foundation for understanding the genomic basis of symbiosis, and its susceptibility to climate change. Here, we present a gene expression dataset generated from larvae of the coral Pocillopora damicornis in response to exposure to acidification and elevated temperature conditions below the bleaching threshold of the symbiosis. DATA DESCRIPTION This dataset is comprised of 16 samples (30 larvae per sample) collected from four treatments (Control, High pCO2, High Temperature, and Combined pCO2 and Temperature treatments). Freshly collected larvae were exposed to treatment conditions for five days, providing valuable insights into gene expression in this vulnerable stage of the lifecycle. In combination with previously published datasets, this transcriptomic resource will facilitate the in-depth investigation of the effects of ocean acidification and elevated temperature on coral larvae and its implication for symbiosis.
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Affiliation(s)
- Youfang Sun
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, 510301, Guangzhou, China
- Department of Ocean Science, The Hong Kong University of Science and Technology, Hong Kong, China
- CAS-HKUST Sanya Joint Laboratory of Marine Science Research and Key Laboratory of Tropical Marine Biotechnology of Hainan Province, Tropical Marine Biological Research Station in Hainan, Chinese Academy of Sciences, 572000, Sanya, China
| | - Yi Lan
- Department of Ocean Science, The Hong Kong University of Science and Technology, Hong Kong, China
- Southern Marine Science and Engineering Guangdong Laboratory, 511458, Guangzhou, China
| | - Nils Rädecker
- Laboratory for Biological Geochemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015, Lausanne, Switzerland
| | - Huaxia Sheng
- State Key Laboratory of Marine Environmental Sciences, Xiamen University, 361101, Xiamen, China
| | - Guillermo Diaz-Pulido
- School of Environment and Science, Coastal and Marine Research Centre, and Australian Rivers Institute, Griffith University, Nathan Campus, 4111, Brisbane, Queensland, Australia
| | - Pei-Yuan Qian
- Department of Ocean Science, The Hong Kong University of Science and Technology, Hong Kong, China.
- CAS-HKUST Sanya Joint Laboratory of Marine Science Research and Key Laboratory of Tropical Marine Biotechnology of Hainan Province, Tropical Marine Biological Research Station in Hainan, Chinese Academy of Sciences, 572000, Sanya, China.
- Southern Marine Science and Engineering Guangdong Laboratory, 511458, Guangzhou, China.
| | - Hui Huang
- Key Laboratory of Tropical Marine Bio-resources and Ecology, Guangdong Provincial Key Laboratory of Applied Marine Biology, South China Sea Institute of Oceanology, Chinese Academy of Sciences, 510301, Guangzhou, China.
- CAS-HKUST Sanya Joint Laboratory of Marine Science Research and Key Laboratory of Tropical Marine Biotechnology of Hainan Province, Tropical Marine Biological Research Station in Hainan, Chinese Academy of Sciences, 572000, Sanya, China.
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27
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Wittich H, Ardlie K, Taylor KD, Durda P, Liu Y, Mikhaylova A, Gignoux CR, Cho MH, Rich SS, Rotter JI, Manichaikul A, Im HK, Wheeler HE. Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits. Am J Hum Genet 2024; 111:445-455. [PMID: 38320554 PMCID: PMC10940016 DOI: 10.1016/j.ajhg.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/12/2024] [Accepted: 01/12/2024] [Indexed: 02/08/2024] Open
Abstract
Regulation of transcription and translation are mechanisms through which genetic variants affect complex traits. Expression quantitative trait locus (eQTL) studies have been more successful at identifying cis-eQTL (within 1 Mb of the transcription start site) than trans-eQTL. Here, we tested the cis component of gene expression for association with observed plasma protein levels to identify cis- and trans-acting genes that regulate protein levels. We used transcriptome prediction models from 49 Genotype-Tissue Expression (GTEx) Project tissues to predict the cis component of gene expression and tested the predicted expression of every gene in every tissue for association with the observed abundance of 3,622 plasma proteins measured in 3,301 individuals from the INTERVAL study. We tested significant results for replication in 971 individuals from the Trans-omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA). We found 1,168 and 1,210 cis- and trans-acting associations that replicated in TOPMed (FDR < 0.05) with a median expected true positive rate (π1) across tissues of 0.806 and 0.390, respectively. The target proteins of trans-acting genes were enriched for transcription factor binding sites and autoimmune diseases in the GWAS catalog. Furthermore, we found a higher correlation between predicted expression and protein levels of the same underlying gene (R = 0.17) than observed expression (R = 0.10, p = 7.50 × 10-11). This indicates the cis-acting genetically regulated (heritable) component of gene expression is more consistent across tissues than total observed expression (genetics + environment) and is useful in uncovering the function of SNPs associated with complex traits.
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Affiliation(s)
- Henry Wittich
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL 60660, USA
| | - Kristin Ardlie
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Peter Durda
- Laboratory for Clinical Biochemistry Research, University of Vermont, Colchester, VT 05446, USA
| | - Yongmei Liu
- Department of Medicine, Duke University School of Medicine, Durham, NC 27710, USA
| | - Anna Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Chris R Gignoux
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Denver Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Michael H Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Stephen S Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Ani Manichaikul
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Hae Kyung Im
- Section of Genetic Medicine, The University of Chicago, Chicago, IL 60637, USA
| | - Heather E Wheeler
- Program in Bioinformatics, Loyola University Chicago, Chicago, IL 60660, USA; Department of Biology, Loyola University Chicago, Chicago, IL 60660, USA.
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28
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Song Q, Wang P, Wang H, Pan M, Li X, Yao Z, Wang W, Tang G, Zhou S. Integrative analysis of chromatin accessibility and transcriptome landscapes in the induction of peritoneal fibrosis by high glucose. J Transl Med 2024; 22:243. [PMID: 38443979 PMCID: PMC10916192 DOI: 10.1186/s12967-024-05037-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 02/24/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Peritoneal fibrosis is the prevailing complication induced by prolonged exposure to high glucose in patients undergoing peritoneal dialysis. METHODS To elucidate the molecular mechanisms underlying this process, we conducted an integrated analysis of the transcriptome and chromatin accessibility profiles of human peritoneal mesothelial cells (HMrSV5) during high-glucose treatment. RESULTS Our study identified 2775 differentially expressed genes (DEGs) related to high glucose-triggered pathological changes, including 1164 upregulated and 1611 downregulated genes. Genome-wide DEGs and network analysis revealed enrichment in the epithelial-mesenchymal transition (EMT), inflammatory response, hypoxia, and TGF-beta pathways. The enriched genes included VEGFA, HIF-1α, TGF-β1, EGF, TWIST2, and SNAI2. Using ATAC-seq, we identified 942 hyper (higher ATAC-seq signal in high glucose-treated HMrSV5 cells than in control cells) and 714 hypo (lower ATAC-seq signal in high glucose-treated HMrSV5 cells versus control cells) peaks with differential accessibility in high glucose-treated HMrSV5 cells versus controls. These differentially accessible regions were positively correlated (R = 0.934) with the nearest DEGs. These genes were associated with 566 up- and 398 downregulated genes, including SNAI2, TGF-β1, HIF-1α, FGF2, VEGFA, and VEGFC, which are involved in critical pathways identified by transcriptome analysis. Integrated ATAC-seq and RNA-seq analysis also revealed key transcription factors (TFs), such as HIF-1α, ARNTL, ELF1, SMAD3 and XBP1. Importantly, we demonstrated that HIF-1α is involved in the regulation of several key genes associated with EMT and the TGF-beta pathway. Notably, we predicted and experimentally validated that HIF-1α can exacerbate the expression of TGF-β1 in a high glucose-dependent manner, revealing a novel role of HIF-1α in high glucose-induced pathological changes in human peritoneal mesothelial cells (HPMCs). CONCLUSIONS In summary, our study provides a comprehensive view of the role of transcriptome deregulation and chromosome accessibility alterations in high glucose-induced pathological fibrotic changes in HPMCs. This analysis identified hub genes, signaling pathways, and key transcription factors involved in peritoneal fibrosis and highlighted the novel glucose-dependent regulation of TGF-β1 by HIF-1α. This integrated approach has offered a deeper understanding of the pathogenesis of peritoneal fibrosis and has indicated potential therapeutic targets for intervention.
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Affiliation(s)
- Qiong Song
- Department of Nephrology, Shaanxi Second People's Hospital, Xi'an, Shaanxi, People's Republic of China
| | - Pengbo Wang
- Department of Nephrology, Shaanxi Second People's Hospital, Xi'an, Shaanxi, People's Republic of China
| | - Huan Wang
- Department of Emergency, Xijing Hospital, The Fourth Military Medical University of People's Liberation Army, Xi'an, Shaanxi, People's Republic of China
| | - Meijing Pan
- Department of Clinical Medicine, Xi'an Medical University, Xi'an, Shaanxi, People's Republic of China
| | - Xiujuan Li
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China
| | - Zhuan'e Yao
- Department of Nephrology, Shaanxi Second People's Hospital, Xi'an, Shaanxi, People's Republic of China
| | - Wei Wang
- Department of Nephrology, Shaanxi Second People's Hospital, Xi'an, Shaanxi, People's Republic of China
| | - Guangbo Tang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
| | - Sen Zhou
- Department of Nephrology, The First Hospital of Lanzhou University, Lanzhou, Gansu, People's Republic of China.
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Zhong Z, Hou J, Yao Z, Dong L, Liu F, Yue J, Wu T, Zheng J, Ouyang G, Yang C, Song J. Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics. Nat Commun 2024; 15:1929. [PMID: 38431724 PMCID: PMC10908802 DOI: 10.1038/s41467-024-46413-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 02/09/2024] [Indexed: 03/05/2024] Open
Abstract
Single-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.
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Affiliation(s)
- Zhixing Zhong
- Institute of Artificial Intelligence, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361102, China
- Institute of Molecular Medicine, Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Junchen Hou
- School of Pharmaceutical Sciences, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Zhixian Yao
- Institute of Molecular Medicine, Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Lei Dong
- Department of Pathology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Feng Liu
- School of Computing and Information Systems, The University of Melbourne, Carlton, Melbourne, VIC, 3053, Australia
| | - Junqiu Yue
- Department of Pathology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Tiantian Wu
- School of Pharmaceutical Sciences, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Junhua Zheng
- Institute of Molecular Medicine, Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
| | - Gaoliang Ouyang
- School of Pharmaceutical Sciences, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Chaoyong Yang
- Institute of Artificial Intelligence, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361102, China
- Institute of Molecular Medicine, Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM), Xiamen, 361005, China
| | - Jia Song
- Institute of Molecular Medicine, Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
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30
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Yao Y, Miethe S, Kattler K, Colakoglu B, Walter J, Schneider-Daum N, Herr C, Garn H, Ritzmann F, Bals R, Beisswenger C. Mutual Regulation of Transcriptomes between Murine Pneumocytes and Fibroblasts Mediates Alveolar Regeneration in Air-Liquid Interface Cultures. Am J Respir Cell Mol Biol 2024; 70:203-214. [PMID: 38051640 DOI: 10.1165/rcmb.2023-0078oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 12/05/2023] [Indexed: 12/07/2023] Open
Abstract
Alveolar type 2 and club cells are part of the stem cell niche of the lung and their differentiation is required for pulmonary homeostasis and tissue regeneration. A disturbed crosstalk between fibroblasts and epithelial cells contributes to the loss of lung structure in chronic lung diseases. Therefore, it is important to understand how fibroblasts and lung epithelial cells interact during regeneration. Here, we analyzed the interaction of fibroblasts and the alveolar epithelium modeled in air-liquid interface cultures. Single-cell transcriptomics showed that cocultivation with fibroblasts leads to increased expression of type 2 markers in pneumocytes, activation of regulons associated with the maintenance of alveolar type 2 cells (e.g., Etv5), and transdifferentiation of club cells toward pneumocytes. This was accompanied by an intensified transepithelial barrier. Vice versa, the activation of NF-κB pathways and the CEBPB regulon and the expression of IL-6 and other differentiation factors (e.g., fibroblast growth factors) were increased in fibroblasts cocultured with epithelial cells. Recombinant IL-6 enhanced epithelial barrier formation. Therefore, in our coculture model, regulatory loops were identified by which lung epithelial cells mediate regeneration and differentiation of the alveolar epithelium in a cooperative manner with the mesenchymal compartment.
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Affiliation(s)
- Yiwen Yao
- Department of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine and
- Department of Clinical Medicine, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Sarah Miethe
- Translational Inflammation Research Division and Core Facility for Single Cell Multiomics and
- German Center for Lung Research (DZL), Philipps University of Marburg, Marburg, Germany
- The Universities of Giessen and Marburg Lung Center (UGMLC), Giessen, Germany
| | - Kathrin Kattler
- Department of Genetics and Epigenetics, Saarland University, Homburg, Germany
| | - Betül Colakoglu
- Department of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine and
| | - Jörn Walter
- Department of Genetics and Epigenetics, Saarland University, Homburg, Germany
| | - Nicole Schneider-Daum
- Department of Drug Delivery, Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, Germany
| | - Christian Herr
- Department of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine and
| | - Holger Garn
- Translational Inflammation Research Division and Core Facility for Single Cell Multiomics and
- German Center for Lung Research (DZL), Philipps University of Marburg, Marburg, Germany
- The Universities of Giessen and Marburg Lung Center (UGMLC), Giessen, Germany
| | - Felix Ritzmann
- Department of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine and
- Department of Drug Delivery, Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, Germany
| | - Robert Bals
- Department of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine and
- Department of Drug Delivery, Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, Germany
| | - Christoph Beisswenger
- Department of Internal Medicine V - Pulmonology, Allergology and Critical Care Medicine and
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Zhang D, Yang Z, Jiang X, Liu Y, Chen X, Wu X. The comparison of morphology and transcriptome in the inner membrane reveals the potential mechanism of the heritable carapace color of the Chinese mitten crab Eriocheir sinensis. Gene 2024; 897:148058. [PMID: 38043835 DOI: 10.1016/j.gene.2023.148058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 11/25/2023] [Accepted: 11/30/2023] [Indexed: 12/05/2023]
Abstract
Carapace color plays an important role in the communication, reproduction, and self-defense of crustaceans, which is also related to their economic value. Chinese mitten crab (Eriocheir sinensis) is an important aquaculture species in China, and there are different strains with heritable carapace colors, i.e. Green, White, and Red. However, there is a lack of research on the formation mechanism of carapace color of this species. This study was conducted to compare the histology and transcriptome in the inner membrane of three carapace color strains of E. sinensis. Histological comparisons revealed that the inner membrane of green and red carapace crabs contained more melanin, appearing in clusters, and had a higher presence of yellow or orange pigments. In contrast, the inner membrane of white carapace crabs had smaller and fewer melanin particles, as well as a lower presence of yellow or orange pigments. Observation under an electron microscope showed that the inner membrane of E. sinensis contained a large number of collagen fibers and various types of cells, including fibroblasts, melanocytes, and other tissue cells, which exhibited different levels of activity. Transcriptome analysis showed that the Green, Red, and White strains of E. sinensis had approximately 80.3 K, 81.6 K and 80.3 K expressed unigenes in their inner membranes, respectively. When comparing Green and Red crabs, there were 2, 850 upregulated genes and 2, 240 downregulated genes. In the comparison between Red and White crabs, there were 2, 853 upregulated genes and 2, 583 downregulated genes. Furthermore, there were 2, 336 upregulated genes and 2, 738 downregulated genes in the inner membranes between White and Green crabs. Among these genes, some members of the solute carriers family, which are involved in carotenoid transportation, showed differential expression among the three carapace color strains. Additionally, significant differences were observed in the expression of genes related to melanin synthesis, including wingless/integrate, tyrosinase, guanine nucleotide-binding protein inhibitory subunit, cell adhesion molecule, adenylyl cyclase, and creb-binding protein. there were no differences in the gene expression levels of the crustacyanin family. In conclusion, this study identified several candidate genes associated with carapace color in the inner membrane of E. sinensis, suggesting a close relationship between the heritable carapace colors and the transport of the carotenoids as well as the synthesis of melanin.
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Affiliation(s)
- Dongdong Zhang
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China
| | - Zonglin Yang
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China
| | - Xiaodong Jiang
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China
| | - Yufei Liu
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China
| | - Xiaowu Chen
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China; Shanghai Collaborative Innovation for Aquatic Animal Genetics and Breeding, Shanghai Ocean University, Shanghai 201306, China; Centre for Research on Environmental Ecology and Fish Nutrition of the Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China.
| | - Xugan Wu
- Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China; Shanghai Collaborative Innovation for Aquatic Animal Genetics and Breeding, Shanghai Ocean University, Shanghai 201306, China; Centre for Research on Environmental Ecology and Fish Nutrition of the Ministry of Agriculture, Shanghai Ocean University, Shanghai 201306, China.
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32
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Levanon EY, Cohen-Fultheim R, Eisenberg E. In search of critical dsRNA targets of ADAR1. Trends Genet 2024; 40:250-259. [PMID: 38160061 DOI: 10.1016/j.tig.2023.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/04/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024]
Abstract
Recent studies have underscored the pivotal role of adenosine-to-inosine RNA editing, catalyzed by ADAR1, in suppressing innate immune interferon responses triggered by cellular double-stranded RNA (dsRNA). However, the specific ADAR1 editing targets crucial for this regulatory function remain elusive. We review analyses of transcriptome-wide ADAR1 editing patterns and their evolutionary dynamics, which offer valuable insights into this unresolved query. The growing appreciation of the significance of immunogenic dsRNAs and their editing in inflammatory and autoimmune diseases and cancer calls for a more comprehensive understanding of dsRNA immunogenicity, which may promote our understanding of these diseases and open doors to therapeutic avenues.
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Affiliation(s)
- Erez Y Levanon
- Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan 5290002, Israel.
| | - Roni Cohen-Fultheim
- Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan 5290002, Israel
| | - Eli Eisenberg
- Raymond and Beverly Sackler School of Physics and Astronomy, Tel Aviv, University, Tel Aviv 6997801, Israel.
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33
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Maas AE, Timmins-Schiffman E, Tarrant AM, Nunn BL, Park J, Blanco-Bercial L. Diel metabolic patterns revealed by in situ transcriptome and proteome in a vertically migratory copepod. Mol Ecol 2024; 33:e17284. [PMID: 38258354 DOI: 10.1111/mec.17284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 12/06/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024]
Abstract
Zooplankton undergo a diel vertical migration (DVM) which exposes them to gradients of light, temperature, oxygen, and food availability on a predictable daily schedule. Disentangling the co-varying and potentially synergistic interactions on metabolic rates has proven difficult, despite the importance of this migration for the delivery of metabolic waste products to the distinctly different daytime (deep) and nighttime (surface) habitats. This study examines the transcriptomic and proteomic profiles of the circumglobal migratory copepod, Pleuromamma xiphias, over the diel cycle. The transcriptome showed that 96% of differentially expressed genes were upregulated during the middle of the day - the period often considered to be of lowest zooplankton activity. The changes in protein abundance were more spread out over time, peaking (42% of comparisons) in the early evening. Between 9:00 and 15:00, both the transcriptome and proteome datasets showed increased expression related to chitin synthesis and degradation. Additionally, at 09:00 and 22:00, there were increases in myosin and vitellogenin proteins, potentially linked to the stress of migration and/or reproductive investment. Based on protein abundances detected, there is an inferred switch in broad metabolic processes, shifting from electron transport system in the day to glycolysis and glycogen mobilization in the afternoon/evening. These observations provide evidence of the diel impact of DVM on transcriptomic and proteomic pathways that likely influence metabolic processes and subsequent excretion products, and clarify how this behaviour results in the direct rapid transport of waste metabolites from the surface to the deep ocean.
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Affiliation(s)
- Amy E Maas
- Bermuda Institute of Ocean Sciences, School of Ocean Futures, Arizona State University, St. George's, Bermuda
| | | | - Ann M Tarrant
- Biology Department, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA
| | - Brook L Nunn
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Jea Park
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Leocadio Blanco-Bercial
- Bermuda Institute of Ocean Sciences, School of Ocean Futures, Arizona State University, St. George's, Bermuda
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Das SS, Das SK. Common and ethnic-specific derangements in skeletal muscle transcriptome associated with obesity. Int J Obes (Lond) 2024; 48:330-338. [PMID: 37993634 DOI: 10.1038/s41366-023-01417-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 10/25/2023] [Accepted: 11/07/2023] [Indexed: 11/24/2023]
Abstract
BACKGROUND Obesity is a common disease with a higher prevalence among African Americans. Obesity alters cellular function in many tissues, including skeletal muscle, and is a risk factor for many life-threatening diseases, including cardiovascular disease and diabetes. The similarities and differences in molecular mechanisms that may explain ethnic disparities in obesity between African and European ancestry individuals have not been studied. METHODS In this study, data from transcriptome-wide analyses on skeletal muscle tissues from well-powered human cohorts were used to compare genes and biological pathways affected by obesity in European and African ancestry populations. Data on obesity-induced differentially expressed transcripts and GWAS-identified SNPs were integrated to prioritize target genes for obesity-associated genetic variants. RESULTS Linear regression analysis in the FUSION (European, N = 301) and AAGMEx (African American, N = 256) cohorts identified a total of 2569 body mass index (BMI)-associated transcripts (q < 0.05), of which 970 genes (at p < 0.05) are associated in both cohorts, and the majority showed the same direction of effect on BMI. Biological pathway analyses, including over-representation and gene-set enrichment analyses, identified enrichment of protein synthesis pathways (e.g., ribosomal function) and the ceramide signaling pathway in both cohorts among BMI-associated down- and up-regulated transcripts, respectively. A comparison using the IPA-tool suggested the activation of inflammation pathways only in Europeans with obesity. Interestingly, these analyses suggested repression of the mitochondrial oxidative phosphorylation pathway in Europeans but showed its activation in African Americans. Integration of SNP-to-Gene analyses-predicted target genes for obesity-associated genetic variants (GWAS-identified SNPs) and BMI-associated transcripts suggested that these SNPs might cause obesity by altering the expression of 316 critical target genes (e.g., GRB14) in the muscle. CONCLUSIONS This study provides a replication of obesity-associated transcripts and biological pathways in skeletal muscle across ethnicities, but also identifies obesity-associated processes unique in either African or European ancestry populations.
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Affiliation(s)
- Sreejon S Das
- The School of Biotechnology at Atkins, Atkins Academic and Technology High, Winston-Salem, NC, 27101, USA
| | - Swapan K Das
- Department of Internal Medicine, Section of Endocrinology and Metabolism, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA.
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Lu J, Ren J, Liu J, Lu M, Cui Y, Liao Y, Zhou Y, Gao Y, Tang F, Wang J, Wang S, Wen L, Song L. High-resolution single-cell transcriptomic survey of cardiomyocytes from patients with hypertrophic cardiomyopathy. Cell Prolif 2024; 57:e13557. [PMID: 37766635 PMCID: PMC10905351 DOI: 10.1111/cpr.13557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/28/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
Hypertrophic cardiomyopathy (HCM) is a common inherited cardiovascular disease, which can cause heart failure and lead to death. In this study, we performed high-resolution single-cell RNA-sequencing of 2115 individual cardiomyocytes obtained from HCM patients and normal controls. Signature up- and down-regulated genes in HCM were identified by integrative analysis across 37 patients and 41 controls from our data and published human single-cell and single-nucleus RNA-seq datasets, which were further classified into gene modules by single-cell co-expression analysis. Using our high-resolution dataset, we also investigated the heterogeneity among individual cardiomyocytes and revealed five distinct clusters within HCM cardiomyocytes. Interestingly, we showed that some extracellular matrix (ECM) genes were up-regulated in the HCM cardiomyocytes, suggesting that they play a role in cardiac remodelling. Taken together, our study comprehensively profiled the transcriptomic programs of HCM cardiomyocytes and provided insights into molecular mechanisms underlying the pathogenesis of HCM.
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Affiliation(s)
- Jiansen Lu
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
| | - Jie Ren
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
- Peking‐Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina
| | - Jie Liu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Minjie Lu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yueli Cui
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
| | - Yuhan Liao
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
| | - Yuan Zhou
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
| | - Yun Gao
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
| | - Fuchou Tang
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
- Peking‐Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina
| | - Jizheng Wang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Shuiyun Wang
- Department of Cardiovascular Surgery, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Lu Wen
- College of Life Sciences, Biomedical Pioneering Innovation CenterMinistry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina
- Beijing Advanced Innovation Center for Genomics, College of Life SciencesPeking UniversityBeijingChina
| | - Lei Song
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Cardiomyopathy ward, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular DiseasesChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
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Li X, Yu X, Bi J, Jiang X, Zhang L, Li Z, Shao M. Integrating single-cell and spatial transcriptomes reveals COL4A1/2 facilitates the spatial organisation of stromal cells differentiation in breast phyllodes tumours. Clin Transl Med 2024; 14:e1611. [PMID: 38481388 PMCID: PMC10938066 DOI: 10.1002/ctm2.1611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 02/08/2024] [Accepted: 02/18/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Breast phyllodes tumours (PTs) are a unique type of fibroepithelial neoplasms with metastatic potential and recurrence tendency. However, the precise nature of heterogeneity in breast PTs remains poorly understood. This study aimed to elucidate the cell subpopulations composition and spatial structure and investigate diagnostic markers in the pathogenesis of PTs. METHODS We applied single-cell RNA sequencing and spatial transcriptomes on tumours and adjacent normal tissues for integration analysis. Immunofluorescence experiments were conducted to verify the tissue distribution of cells. Tumour cells from patients with PTs were cultured to validate the function of genes. To validate the heterogeneity, the epithelial and stromal components of tumour tissues were separated using laser capture microdissection, and microproteomics data were obtained using data-independent acquisition mass spectrometry. The diagnostic value of genes was assessed using immunohistochemistry staining. RESULTS Tumour stromal cells harboured seven subpopulations. Among them, a population of widely distributed cancer-associated fibroblast-like stroma cells exhibited strong communications with epithelial progenitors which underwent a mesenchymal transition. We identified two stromal subpopulations sharing epithelial progenitors and mesenchymal markers. They were inferred to further differentiate into transcriptionally active stromal subpopulations continuously expressing COL4A1/2. The binding of COL4A1/2 with ITGA1/B1 facilitated a growth pattern from the stroma towards the surrounding glands. Furthermore, we found consistent transcriptional changes between intratumoural heterogeneity and inter-patient heterogeneity by performing microproteomics studies on 30 samples from 11 PTs. The immunohistochemical assessment of 97 independent cohorts identified that COL4A1/2 and CSRP1 could aid in accurate diagnosis and grading. CONCLUSIONS Our study demonstrates that COL4A1/2 shapes the spatial structure of stromal cell differentiation and has important clinical implications for accurate diagnosis of breast PTs.
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Affiliation(s)
- Xia Li
- Department of PathologyShenzhen Traditional Chinese Medicine HospitalShenzhenP.R. China
- Department of PathologyThe Fourth Clinical Medical College of Guangzhou University of Chinese MedicineShenzhenP.R. China
| | - Xuewen Yu
- Department of PathologyShenzhen Traditional Chinese Medicine HospitalShenzhenP.R. China
- Department of PathologyThe Fourth Clinical Medical College of Guangzhou University of Chinese MedicineShenzhenP.R. China
| | - Jiaxin Bi
- Department of PathologyShenzhen Traditional Chinese Medicine HospitalShenzhenP.R. China
- Department of PathologyThe Fourth Clinical Medical College of Guangzhou University of Chinese MedicineShenzhenP.R. China
| | - Xu Jiang
- Department of PathologyShenzhen Traditional Chinese Medicine HospitalShenzhenP.R. China
- Department of PathologyThe Fourth Clinical Medical College of Guangzhou University of Chinese MedicineShenzhenP.R. China
| | - Lu Zhang
- Department of PathologyShenzhen Traditional Chinese Medicine HospitalShenzhenP.R. China
- Department of PathologyThe Fourth Clinical Medical College of Guangzhou University of Chinese MedicineShenzhenP.R. China
| | - Zhixin Li
- Department of SurgeryShenzhen Traditional Chinese Medicine HospitalShenzhenP.R. China
- Department of SurgeryThe Fourth Clinical Medical College of Guangzhou University of Chinese MedicineShenzhenP.R. China
| | - Mumin Shao
- Department of PathologyShenzhen Traditional Chinese Medicine HospitalShenzhenP.R. China
- Department of PathologyThe Fourth Clinical Medical College of Guangzhou University of Chinese MedicineShenzhenP.R. China
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Xu F, Liu S, Zhao A, Shang M, Wang Q, Jiang S, Cheng Q, Chen X, Zhai X, Zhang J, Wang X, Yan J. iFLAS: positive-unlabeled learning facilitates full-length transcriptome-based identification and functional exploration of alternatively spliced isoforms in maize. New Phytol 2024; 241:2606-2620. [PMID: 38291701 DOI: 10.1111/nph.19554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 01/06/2024] [Indexed: 02/01/2024]
Abstract
The advent of full-length transcriptome sequencing technologies has accelerated the discovery of novel splicing isoforms. However, existing alternative splicing (AS) tools are either tailored for short-read RNA-Seq data or designed for human and animal studies. The disparities in AS patterns between plants and animals still pose a challenge to the reliable identification and functional exploration of novel isoforms in plants. Here, we developed integrated full-length alternative splicing analysis (iFLAS), a plant-optimized AS toolkit that introduced a semi-supervised machine learning method known as positive-unlabeled (PU) learning to accurately identify novel isoforms. iFLAS also enables the investigation of AS functions from various perspectives, such as differential AS, poly(A) tail length, and allele-specific AS (ASAS) analyses. By applying iFLAS to three full-length transcriptome sequencing datasets, we systematically identified and functionally characterized maize (Zea mays) AS patterns. We found intron retention not only introduces premature termination codons, resulting in lower expression levels of isoforms, but may also regulate the length of 3'UTR and poly(A) tail, thereby affecting the functional differentiation of isoforms. Moreover, we observed distinct ASAS patterns in two genes within heterosis offspring, highlighting their potential value in breeding. These results underscore the broad applicability of iFLAS in plant full-length transcriptome-based AS research.
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Affiliation(s)
- Feng Xu
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Songyu Liu
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Anwen Zhao
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Meiqi Shang
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Qian Wang
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Shuqin Jiang
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Qian Cheng
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Xingming Chen
- Molbreeding Biotechnology Co., Ltd, Shijiazhuang, Hebei Province, 051430, China
| | - Xiaoguang Zhai
- Molbreeding Biotechnology Co., Ltd, Shijiazhuang, Hebei Province, 051430, China
| | - Jianan Zhang
- Molbreeding Biotechnology Co., Ltd, Shijiazhuang, Hebei Province, 051430, China
| | - Xiangfeng Wang
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
| | - Jun Yan
- State Key Laboratory of Maize Bio-Breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100094, China
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38
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Hayashida N, Urano-Tashiro Y, Horie T, Saiki K, Yamanaka Y, Takahashi Y. Transcriptome and metabolome analyses of Streptococcus gordonii DL1 under acidic conditions. J Oral Biosci 2024; 66:112-118. [PMID: 38135272 DOI: 10.1016/j.job.2023.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 12/24/2023]
Abstract
OBJECTIVES Streptococcus gordonii is associated with the formation of biofilms, especially those that comprise dental plaque. Notably, S. gordonii DL1 causes infective endocarditis (IE). Colonization of this bacterium requires a mechanism that can tolerate a drop in environmental pH by producing acid via its own sugar metabolism. The ability to survive acidic environmental conditions might allow the bacterium to establish vegetative colonization even in the endocardium due to inflammation-induced lowering of pH, increasing the risk of IE. At present, the mechanism by which S. gordonii DL1 survives under acidic conditions is not thoroughly elucidated. The present study was thus conducted to elucidate the mechanism(s) by which S. gordonii DL1 survives under acidic conditions. METHODS We analyzed dynamic changes in gene transcription and intracellular metabolites in S. gordonii DL1 exposed to acidic conditions, using transcriptome and metabolome analyses. RESULTS Transcriptome analysis revealed upregulation of genes involved in heat shock response and glycolysis, and down regulation of genes involved in phosphotransferase systems and biosynthesis of amino acids. The most upregulated genes were a beta-strand repeat protein of unknown function (SGO_RS06325), followed by copper-translocating P-type ATPase (SGO_RS09470) and malic enzyme (SGO_RS01850). The latter two of these contribute to cytoplasmic alkalinization. S. gordonii mutant strains lacking each of these genes showed significantly reduced survival under acidic conditions. Metabolome analysis revealed that cytoplasmic levels of several amino acids were reduced. CONCLUSIONS S. gordonii survives the acidic conditions by recovering the acidic cytoplasm using the various activities, which are regulated at the transcriptional level.
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Affiliation(s)
- Naoto Hayashida
- Department of Microbiology, The Nippon Dental University School of Life Dentistry at Tokyo, Japan.
| | - Yumiko Urano-Tashiro
- Department of Microbiology, The Nippon Dental University School of Life Dentistry at Tokyo, Japan.
| | - Tetsuro Horie
- Research Center for Odontology, The Nippon Dental University School of Life Dentistry at Tokyo, Japan.
| | - Keitarou Saiki
- Department of Microbiology, The Nippon Dental University School of Life Dentistry at Tokyo, Japan.
| | - Yuki Yamanaka
- Department of Microbiology, The Nippon Dental University School of Life Dentistry at Tokyo, Japan.
| | - Yukihiro Takahashi
- Department of Microbiology, The Nippon Dental University School of Life Dentistry at Tokyo, Japan.
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Ju X, Li S, Froom R, Wang L, Lilic M, Delbeau M, Campbell EA, Rock JM, Liu S. Incomplete transcripts dominate the Mycobacterium tuberculosis transcriptome. Nature 2024; 627:424-430. [PMID: 38418874 PMCID: PMC10937400 DOI: 10.1038/s41586-024-07105-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 01/23/2024] [Indexed: 03/02/2024]
Abstract
Mycobacterium tuberculosis (Mtb) is a bacterial pathogen that causes tuberculosis (TB), an infectious disease that is responsible for major health and economic costs worldwide1. Mtb encounters diverse environments during its life cycle and responds to these changes largely by reprogramming its transcriptional output2. However, the mechanisms of Mtb transcription and how they are regulated remain poorly understood. Here we use a sequencing method that simultaneously determines both termini of individual RNA molecules in bacterial cells3 to profile the Mtb transcriptome at high resolution. Unexpectedly, we find that most Mtb transcripts are incomplete, with their 5' ends aligned at transcription start sites and 3' ends located 200-500 nucleotides downstream. We show that these short RNAs are mainly associated with paused RNA polymerases (RNAPs) rather than being products of premature termination. We further show that the high propensity of Mtb RNAP to pause early in transcription relies on the binding of the σ-factor. Finally, we show that a translating ribosome promotes transcription elongation, revealing a potential role for transcription-translation coupling in controlling Mtb gene expression. In sum, our findings depict a mycobacterial transcriptome that prominently features incomplete transcripts resulting from RNAP pausing. We propose that the pausing phase constitutes an important transcriptional checkpoint in Mtb that allows the bacterium to adapt to environmental changes and could be exploited for TB therapeutics.
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Affiliation(s)
- Xiangwu Ju
- Laboratory of Nanoscale Biophysics and Biochemistry, The Rockefeller University, New York, NY, USA
| | - Shuqi Li
- Laboratory of Host-Pathogen Biology, The Rockefeller University, New York, NY, USA
| | - Ruby Froom
- Laboratory of Host-Pathogen Biology, The Rockefeller University, New York, NY, USA
- Laboratory of Molecular Biophysics, The Rockefeller University, New York, NY, USA
| | - Ling Wang
- Laboratory of Nanoscale Biophysics and Biochemistry, The Rockefeller University, New York, NY, USA
| | - Mirjana Lilic
- Laboratory of Molecular Biophysics, The Rockefeller University, New York, NY, USA
| | - Madeleine Delbeau
- Laboratory of Molecular Biophysics, The Rockefeller University, New York, NY, USA
| | - Elizabeth A Campbell
- Laboratory of Molecular Biophysics, The Rockefeller University, New York, NY, USA
| | - Jeremy M Rock
- Laboratory of Host-Pathogen Biology, The Rockefeller University, New York, NY, USA.
| | - Shixin Liu
- Laboratory of Nanoscale Biophysics and Biochemistry, The Rockefeller University, New York, NY, USA.
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40
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Koh E, Goh W, Julca I, Villanueva E, Mutwil M. PEO: Plant Expression Omnibus - a comparative transcriptomic database for 103 Archaeplastida. Plant J 2024; 117:1592-1603. [PMID: 38050352 DOI: 10.1111/tpj.16566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 11/16/2023] [Indexed: 12/06/2023]
Abstract
The Plant Expression Omnibus (PEO) is a web application that provides biologists with access to gene expression insights across over 100 plant species, ~60 000 manually annotated RNA-seq samples, and more than 4 million genes. The tool allows users to explore the expression patterns of genes across different organs, identify organ-specific genes, and discover top co-expressed genes for any gene of interest. PEO also provides functional annotations for each gene, allowing for the identification of genetic modules and pathways. PEO is designed to facilitate comparative kingdom-wide gene expression analysis and provide a valuable resource for plant biology research. We provide two case studies to demonstrate the utility of PEO in identifying candidate genes in pollen coat biosynthesis in Arabidopsis and investigating the biosynthetic pathway components of capsaicin in Capsicum annuum. The database is freely available at https://expression.plant.tools/.
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Affiliation(s)
- Eugene Koh
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - William Goh
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - Irene Julca
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - Erielle Villanueva
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - Marek Mutwil
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
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41
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Chen X, Qi Y, Huang Q, Sun C, Zheng Y, Ji L, Shi Y, Cheng X, Li Z, Zheng S, Cao Y, Gu Z, Yu J. Single-cell transcriptome characteristics of testicular terminal epithelium lineages during aging in the Drosophila. Aging Cell 2024; 23:e14057. [PMID: 38044573 DOI: 10.1111/acel.14057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 11/14/2023] [Accepted: 11/17/2023] [Indexed: 12/05/2023] Open
Abstract
Aging is a complex biological process leading to impaired functions, with a variety of hallmarks. In the testis of Drosophila, the terminal epithelium region is involved in spermatid release and maturation, while its functional diversity and regulatory mechanism remain poorly understood. In this study, we performed single-cell RNA-sequencing analysis (scRNA-seq) to characterize the transcriptomes of terminal epithelium in Drosophila testes at 2-, 10 and 40-Days. Terminal epithelium populations were defined with Metallothionein A (MtnA) and subdivided into six novel sub-cell clusters (EP0-EP5), and a series of marker genes were identified based on their expressions. The data revealed the functional characteristics of terminal epithelium populations, such as tight junction, focal adhesion, bacterial invasion, oxidative stress, mitochondrial function, proteasome, apoptosis and metabolism. Interestingly, we also found that disrupting genes for several relevant pathways in terminal epithelium led to male fertility disorders. Moreover, we also discovered a series of age-biased genes and pseudotime trajectory mediated state-biased genes during terminal epithelium aging. Differentially expressed genes during terminal epithelium aging were mainly participated in the regulation of several common signatures, e.g. mitochondria-related events, protein synthesis and degradation, and metabolic processes. We further explored the Drosophila divergence and selection in the functional constraints of age-biased genes during aging, revealing that age-biased genes in epithelial cells of 2 Days group evolved rapidly and were endowed with greater evolutionary advantages. scRNA-seq analysis revealed the diversity of testicular terminal epithelium populations, providing a gene target resource for further systematic research of their functions during aging.
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Affiliation(s)
- Xia Chen
- Department of Obstetrics and Gynecology, Nantong First People's Hospital, Affiliated Hospital 2 of Nantong University; Medical School of Nantong University, Nantong University, Nantong, Jiangsu, China
| | - Yujuan Qi
- Clinical Center of Reproductive Medicine, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
| | - Qiuru Huang
- Institute of Reproductive Medicine, Medical School of Nantong University, Nantong University, Nantong, China
| | - Chi Sun
- Department of Geriatrics, Affiliated Hospital of Nantong University, Nantong University, Nantong, China
| | - Yanli Zheng
- Department of Obstetrics and Gynecology, Nantong First People's Hospital, Affiliated Hospital 2 of Nantong University; Medical School of Nantong University, Nantong University, Nantong, Jiangsu, China
| | - Li Ji
- Institute of Reproductive Medicine, Medical School of Nantong University, Nantong University, Nantong, China
| | - Yi Shi
- Institute of Reproductive Medicine, Medical School of Nantong University, Nantong University, Nantong, China
| | - Xinmeng Cheng
- Institute of Reproductive Medicine, Medical School of Nantong University, Nantong University, Nantong, China
| | - Zhenbei Li
- Clinical Center of Reproductive Medicine, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
| | - Sen Zheng
- Clinical Center of Reproductive Medicine, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
| | - Yijuan Cao
- Clinical Center of Reproductive Medicine, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
| | - Zhifeng Gu
- Department of Rheumatology, Affiliated Hospital of Nantong University, Nantong University, Nantong, China
| | - Jun Yu
- Institute of Reproductive Medicine, Medical School of Nantong University, Nantong University, Nantong, China
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42
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Zhang J, Yue Y, Hu M, Yi F, Chen J, Lai J, Xin B. Dynamic transcriptome landscape of maize pericarp development. Plant J 2024; 117:1574-1591. [PMID: 37970738 DOI: 10.1111/tpj.16548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 10/09/2023] [Accepted: 11/05/2023] [Indexed: 11/17/2023]
Abstract
As a maternal tissue, the pericarp supports and protects for other components of seed, such as embryo and endosperm. Despite the importance of maize pericarp in seed, the genome-wide transcriptome pattern throughout maize pericarp development has not been well characterized. Here, we developed RNA-seq transcriptome atlas of B73 maize pericarp development based on 21 samples from 5 days before fertilization (DBP5) to 32 days after fertilization (DAP32). A total of 25 346 genes were detected in programming pericarp development, including 1887 transcription factors (TFs). Together with pericarp morphological changes, the global clustering of gene expression revealed four developmental stages: undeveloped, thickening, expansion and strengthening. Coexpression analysis provided further insights on key regulators in functional transition of four developmental stages. Combined with non-seed, embryo, endosperm, and nucellus transcriptome data, we identified 598 pericarp-specific genes, including 75 TFs, which could elucidate key mechanisms and regulatory networks of pericarp development. Cell wall related genes were identified that reflected their crucial role in the maize pericarp structure building. In addition, key maternal proteases or TFs related with programmed cell death (PCD) were proposed, suggesting PCD in the maize pericarp was mediated by vacuolar processing enzymes (VPE), and jasmonic acid (JA) and ethylene-related pathways. The dynamic transcriptome atlas provides a valuable resource for unraveling the genetic control of maize pericarp development.
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Affiliation(s)
- Jihong Zhang
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, 100193, P. R. China
| | - Yang Yue
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, 100193, P. R. China
| | - Mingjian Hu
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, 100193, P. R. China
| | - Fei Yi
- Engineering Research Center of Plant Growth Regulator, Ministry of Education & College of Agronomy and Biotechnology, China Agricultural University, Beijing, P. R. China
| | - Jian Chen
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, 100193, P. R. China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100193, P. R. China
| | - Jinsheng Lai
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, 100193, P. R. China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100193, P. R. China
| | - Beibei Xin
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, 100193, P. R. China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100193, P. R. China
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43
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Weerakoon H, Mohamed A, Wong Y, Chen J, Senadheera B, Haigh O, Watkins TS, Kazakoff S, Mukhopadhyay P, Mulvenna J, Miles JJ, Hill MM, Lepletier A. Integrative temporal multi-omics reveals uncoupling of transcriptome and proteome during human T cell activation. NPJ Syst Biol Appl 2024; 10:21. [PMID: 38418561 PMCID: PMC10901835 DOI: 10.1038/s41540-024-00346-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/25/2024] [Indexed: 03/01/2024] Open
Abstract
Engagement of the T cell receptor (TCR) triggers molecular reprogramming leading to the acquisition of specialized effector functions by CD4 helper and CD8 cytotoxic T cells. While transcription factors, chemokines, and cytokines are known drivers in this process, the temporal proteomic and transcriptomic changes that regulate different stages of human primary T cell activation remain to be elucidated. Here, we report an integrative temporal proteomic and transcriptomic analysis of primary human CD4 and CD8 T cells following ex vivo stimulation with anti-CD3/CD28 beads, which revealed major transcriptome-proteome uncoupling. The early activation phase in both CD4 and CD8 T cells was associated with transient downregulation of the mRNA transcripts and protein of the central glucose transport GLUT1. In the proliferation phase, CD4 and CD8 T cells became transcriptionally more divergent while their proteome became more similar. In addition to the kinetics of proteome-transcriptome correlation, this study unveils selective transcriptional and translational metabolic reprogramming governing CD4 and CD8 T cell responses to TCR stimulation. This temporal transcriptome/proteome map of human T cell activation provides a reference map exploitable for future discovery of biomarkers and candidates targeting T cell responses.
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Affiliation(s)
- Harshi Weerakoon
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, Australia
- Faculty of Medicine and Allied Sciences, Rajarata University of Sri Lanka, Saliyapura, Sri Lanka
| | - Ahmed Mohamed
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Yide Wong
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, QLD, Australia
| | - Jinjin Chen
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
| | | | - Oscar Haigh
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Thomas S Watkins
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Stephen Kazakoff
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | | | - Jason Mulvenna
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - John J Miles
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Michelle M Hill
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
- Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Ailin Lepletier
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia.
- Institute for Glycomics, Griffith Univeristy, Gold Coast, QLD, Australia.
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44
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Pereira WJ, Boyd J, Conde D, Triozzi PM, Balmant KM, Dervinis C, Schmidt HW, Boaventura-Novaes C, Chakraborty S, Knaack SA, Gao Y, Feltus FA, Roy S, Ané JM, Frugoli J, Kirst M. The single-cell transcriptome program of nodule development cellular lineages in Medicago truncatula. Cell Rep 2024; 43:113747. [PMID: 38329875 DOI: 10.1016/j.celrep.2024.113747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 10/31/2023] [Accepted: 01/22/2024] [Indexed: 02/10/2024] Open
Abstract
Legumes establish a symbiotic relationship with nitrogen-fixing rhizobia by developing nodules. Nodules are modified lateral roots that undergo changes in their cellular development in response to bacteria, but the transcriptional reprogramming that occurs in these root cells remains largely uncharacterized. Here, we describe the cell-type-specific transcriptome response of Medicago truncatula roots to rhizobia during early nodule development in the wild-type genotype Jemalong A17, complemented with a hypernodulating mutant (sunn-4) to expand the cell population responding to infection and subsequent biological inferences. The analysis identifies epidermal root hair and stele sub-cell types associated with a symbiotic response to infection and regulation of nodule proliferation. Trajectory inference shows cortex-derived cell lineages differentiating to form the nodule primordia and, posteriorly, its meristem, while modulating the regulation of phytohormone-related genes. Gene regulatory analysis of the cell transcriptomes identifies new regulators of nodulation, including STYLISH 4, for which the function is validated.
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Affiliation(s)
- Wendell J Pereira
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA
| | - Jade Boyd
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA
| | - Daniel Conde
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA; Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, 28223 Madrid, Spain
| | - Paolo M Triozzi
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA; PlantLab, Center of Plant Sciences, Sant'Anna School of Advanced Studies, 56010 Pisa, Italy
| | - Kelly M Balmant
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA; Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA
| | - Christopher Dervinis
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA
| | - Henry W Schmidt
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA
| | | | - Sanhita Chakraborty
- Department of Bacteriology, University of Wisconsin - Madison, Madison, WI 53706, USA
| | - Sara A Knaack
- Wisconsin Institute for Discovery, University of Wisconsin, Madison, WI 53715, USA
| | - Yueyao Gao
- Department of Genetics & Biochemistry, Clemson University, Clemson, SC 29634, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Frank Alexander Feltus
- Department of Genetics & Biochemistry, Clemson University, Clemson, SC 29634, USA; Biomedical Data Science and Informatics Program, Clemson University, Clemson, SC, USA; Clemson Center for Human Genetics, Clemson University, Greenwood, SC 29646, USA
| | - Sushmita Roy
- Wisconsin Institute for Discovery, University of Wisconsin, Madison, WI 53715, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI 53726, USA; Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA
| | - Jean-Michel Ané
- Department of Bacteriology, University of Wisconsin - Madison, Madison, WI 53706, USA
| | - Julia Frugoli
- Department of Genetics & Biochemistry, Clemson University, Clemson, SC 29634, USA
| | - Matias Kirst
- School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA.
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Donovan LJ, Bridges CM, Nippert AR, Wang M, Wu S, Forman TE, Haight ES, Huck NA, Bond SF, Jordan CE, Gardner AM, Nair RV, Tawfik VL. Repopulated spinal cord microglia exhibit a unique transcriptome and contribute to pain resolution. Cell Rep 2024; 43:113683. [PMID: 38261512 PMCID: PMC10947777 DOI: 10.1016/j.celrep.2024.113683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 11/15/2023] [Accepted: 01/02/2024] [Indexed: 01/25/2024] Open
Abstract
Microglia are implicated as primarily detrimental in pain models; however, they exist across a continuum of states that contribute to homeostasis or pathology depending on timing and context. To clarify the specific contribution of microglia to pain progression, we take advantage of a temporally controlled transgenic approach to transiently deplete microglia. Unexpectedly, we observe complete resolution of pain coinciding with microglial repopulation rather than depletion. We find that repopulated mouse spinal cord microglia are morphologically distinct from control microglia and exhibit a unique transcriptome. Repopulated microglia from males and females express overlapping networks of genes related to phagocytosis and response to stress. We intersect the identified mouse genes with a single-nuclei microglial dataset from human spinal cord to identify human-relevant genes that may ultimately promote pain resolution after injury. This work presents a comprehensive approach to gene discovery in pain and provides datasets for the development of future microglial-targeted therapeutics.
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Affiliation(s)
- Lauren J Donovan
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Caldwell M Bridges
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Amy R Nippert
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Meng Wang
- Stanford Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Shaogen Wu
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Thomas E Forman
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Elena S Haight
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Nolan A Huck
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Sabrina F Bond
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Claire E Jordan
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Aysha M Gardner
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA
| | - Ramesh V Nair
- Stanford Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Vivianne L Tawfik
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA 94305, USA.
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Yu M, Risacher SL, Nho KT, Wen Q, Oblak AL, Unverzagt FW, Apostolova LG, Farlow MR, Brosch JR, Clark DG, Wang S, Deardorff R, Wu YC, Gao S, Sporns O, Saykin AJ. Spatial transcriptomic patterns underlying amyloid-β and tau pathology are associated with cognitive dysfunction in Alzheimer's disease. Cell Rep 2024; 43:113691. [PMID: 38244198 PMCID: PMC10926093 DOI: 10.1016/j.celrep.2024.113691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/29/2023] [Accepted: 01/03/2024] [Indexed: 01/22/2024] Open
Abstract
Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aβ and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. These findings may explain the discordance between regional Aβ and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA.
| | - Shannon L Risacher
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik T Nho
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA
| | - Qiuting Wen
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adrian L Oblak
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Frederick W Unverzagt
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martin R Farlow
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jared R Brosch
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David G Clark
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sophia Wang
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Rachael Deardorff
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sujuan Gao
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA.
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Zhu F, Lu J, Sun K, Deng C, Xu Y. Polyploidization of Indotyphlops braminus: evidence from isoform-sequencing. BMC Genom Data 2024; 25:23. [PMID: 38408920 PMCID: PMC10895795 DOI: 10.1186/s12863-024-01208-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 02/14/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND Indotyphlops braminus, the only known triploid parthenogenetic snake, is a compelling species for revealing the mechanism of polyploid emergence in vertebrates. METHODS In this study, we applied PacBio isoform sequencing technology to generate the first full-length transcriptome of I. braminus, aiming to improve the understanding of the molecular characteristics of this species. RESULTS A total of 51,849 nonredundant full-length transcript assemblies (with an N50 length of 2980 bp) from I. braminus were generated and fully annotated using various gene function databases. Our analysis provides preliminary evidence supporting a recent genome duplication event in I. braminus. Phylogenetic analysis indicated that the divergence of I. braminus subgenomes occurred approximately 11.5 ~ 15 million years ago (Mya). The full-length transcript resource generated as part of this research will facilitate transcriptome analysis and genomic evolution studies in the future.
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Affiliation(s)
- Fei Zhu
- School of Life Sciences, Guizhou Normal University, 550025, Guiyang, Guizhou, China.
| | - Jing Lu
- School of Life Sciences, Guizhou Normal University, 550025, Guiyang, Guizhou, China
| | - Ke Sun
- School of Life Sciences, Guizhou Normal University, 550025, Guiyang, Guizhou, China
| | - Cao Deng
- Department of Bioinformatics, DNA Stories Bioinformatics Center, 610000, Chengdu, China
| | - Yu Xu
- School of Life Sciences, Guizhou Normal University, 550025, Guiyang, Guizhou, China
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Liu X, Gao H, Radani Y, Yue S, Zhang Z, Tang J, Zhu J, Zheng R. Integrative transcriptome and metabolome analysis reveals the discrepancy in the accumulation of active ingredients between Lycium barbarum cultivars. Planta 2024; 259:74. [PMID: 38407665 DOI: 10.1007/s00425-024-04350-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 01/23/2024] [Indexed: 02/27/2024]
Abstract
MAIN CONCLUSION The combined analysis of transcriptome and metabolome provided molecular insight into the dynamics of multiple active ingredients biosynthesis and accumulation across different cultivars of Lycium barbarum. Lycium barbarum L. has a high concentration of active ingredients and is well known in traditional Chinese herbal medicine for its therapeutic properties. However, there are many Lycium barbarum cultivars, and the content of active components varies, resulting in inconsistent quality between Lycium barbarum cultivars. At present, few research has been conducted to reveal the difference in active ingredient content among different cultivars of Lycium barbarum at the molecular level. Therefore, the transcriptome of 'Ningqi No.1' and 'Qixin No.1' during the three development stages (G, T, and M) was constructed in this study. A total of 797,570,278 clean reads were obtained. Between the two types of wolfberries, a total of 469, 2394, and 1531 differentially expressed genes (DEGs) were obtained in the 'G1 vs. G10,' 'T1 vs. T10,' and 'M1 vs. M10,' respectively, and were annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology identifiers. Using these transcriptome data, most DEGs related to the metabolism of the active ingredients in 'Ningqi No.1' and 'Qixin No.1' were identified. Moreover, a widely targeted metabolome analysis of the metabolites of 'Ningqi 1' and 'Qixin 1' fruits at the maturity stage revealed 1,135 differentially expressed metabolites (DEMs) in 'M1 vs. M10,' and many DEMs were associated with active ingredients such as flavonoids, alkaloids, terpenoids, and so on. We further quantified the flavonoid, lignin, and carotenoid contents of the two Lycium barbarum cultivars during the three developmental stages. The present outcome provided molecular insight into the dynamics of multiple active ingredients biosynthesis and accumulation across different cultivars of Lycium barbarum, which would provide the basic data for the formation of Lycium barbarum fruit quality and the breeding of outstanding strains.
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Affiliation(s)
- Xuexia Liu
- College of Life Science, Key Laboratory of Ministry of Education for Protection and Utilization of Special Biological Resources in Western China, Ningxia University, Yinchuan, 750021, China
| | - Han Gao
- College of Life Science, Key Laboratory of Ministry of Education for Protection and Utilization of Special Biological Resources in Western China, Ningxia University, Yinchuan, 750021, China
| | - Yasmina Radani
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China
| | - Sijun Yue
- College of Life Science, Key Laboratory of Ministry of Education for Protection and Utilization of Special Biological Resources in Western China, Ningxia University, Yinchuan, 750021, China.
| | - Ziping Zhang
- College of Life Science, Key Laboratory of Ministry of Education for Protection and Utilization of Special Biological Resources in Western China, Ningxia University, Yinchuan, 750021, China
| | - Jianning Tang
- Wolfberry Industry Development Center, Yinchuan, 750021, China
| | - Jinzhong Zhu
- Qixin Wolfberry Seedling Professional Cooperatives of Zhongning County, Zhongning, 755100, China
| | - Rui Zheng
- College of Life Science, Key Laboratory of Ministry of Education for Protection and Utilization of Special Biological Resources in Western China, Ningxia University, Yinchuan, 750021, China.
- State Key Laboratory of Efficient Production of Forest Resources, Beijing, 100091, China.
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Yang D, Li D, Jiang L, Lin J, Yue G, Xiao K, Hao X, Ji Q, Hong Y, Cai P, Yang J. Antennal transcriptome analysis of Psyttalia incisi (silvestri) (Hymenoptera: Braconidae): identification and tissue expression profiling of candidate odorant-binding protein genes. Mol Biol Rep 2024; 51:333. [PMID: 38393425 DOI: 10.1007/s11033-024-09281-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 01/23/2024] [Indexed: 02/25/2024]
Abstract
BACKGROUND Olfaction plays an important role in host-seeking by parasitoids, as they can sense chemical signals using sensitive chemosensory systems. Psyttalia incisi (Silvestri) (Hymenoptera: Braconidae) is the dominant parasitoid of Bactrocera dorsalis (Hendel) in fruit-producing regions of southern China. The olfactory behavior of P. incisi has been extensively studied; however, the chemosensory mechanisms of this species are not fully understood. RESULTS Bioinformatics analysis of 64,515 unigenes from the antennal transcriptome of both male and female adults P. incisi identified 87 candidate chemosensory genes. These included 13 odorant-binding proteins (OBPs), seven gustatory receptors (GRs), 55 odorant receptors (ORs), 10 ionotropic receptors (IRs), and two sensory neuron membrane proteins (SNMPs). Phylogenetic trees were constructed to predict evolutionary relationships between these chemosensory genes in hymenopterans. Moreover, the tissue expression profiles of 13 OBPs were analyzed by quantitative real-time PCR, revealing high expression of seven OBPs (1, 3, 6, 7, 8, 12, and 13) in the antennae. CONCLUSION This study represents the first identification of chemosensory genes and the determination of their expression patterns in different tissues of P. incisi. These results contribute to a better understanding of the function of the chemosensory system of this parasitoid species.
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Affiliation(s)
- Deqing Yang
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- Department of Horticulture, College of Tea and Food Science, Wuyi University, Wuyishan, China
| | - Dongliang Li
- College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, Fujian Province, China
- Department of Horticulture, College of Tea and Food Science, Wuyi University, Wuyishan, China
| | - Lili Jiang
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jia Lin
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Guoqing Yue
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Kang Xiao
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Xuxing Hao
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Qinge Ji
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Yongcong Hong
- Department of Horticulture, College of Tea and Food Science, Wuyi University, Wuyishan, China
| | - Pumo Cai
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China.
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China.
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China.
- Department of Horticulture, College of Tea and Food Science, Wuyi University, Wuyishan, China.
| | - Jianquan Yang
- Institute of Biological Control, Plant Protection College, Fujian Agriculture and Forestry University, Fuzhou, China.
- Key Laboratory of Biopesticide and Chemical Biology, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China.
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Institute of Plant Protection, Fujian Agriculture and Forestry University, Fuzhou, China.
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Kreis J, Aybey B, Geist F, Brors B, Staub E. Stromal Signals Dominate Gene Expression Signature Scores That Aim to Describe Cancer Cell-intrinsic Stemness or Mesenchymality Characteristics. Cancer Res Commun 2024; 4:516-529. [PMID: 38349551 PMCID: PMC10885853 DOI: 10.1158/2767-9764.crc-23-0383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/14/2023] [Accepted: 02/09/2024] [Indexed: 02/24/2024]
Abstract
Epithelial-to-mesenchymal transition (EMT) in cancer cells confers migratory abilities, a crucial aspect in the metastasis of tumors that frequently leads to death. In multiple studies, authors proposed gene expression signatures for EMT, stemness, or mesenchymality of tumors based on bulk tumor expression profiling. However, recent studies suggested that noncancerous cells from the microenvironment or macroenvironment heavily influence such signature profiles. Here, we strengthen these findings by investigating 11 published and frequently referenced gene expression signatures that were proposed to describe EMT-related (EMT, mesenchymal, or stemness) characteristics in various cancer types. By analyses of bulk, single-cell, and pseudobulk expression data, we show that the cell type composition of a tumor sample frequently dominates scores of these EMT-related signatures. A comprehensive, integrated analysis of bulk RNA sequencing (RNA-seq) and single-cell RNA-seq data shows that stromal cells, most often fibroblasts, are the main drivers of EMT-related signature scores. We call attention to the risk of false conclusions about tumor properties when interpreting EMT-related signatures, especially in a clinical setting: high patient scores of EMT-related signatures or calls of "stemness subtypes" often result from low cancer cell content in tumor biopsies rather than cancer cell-specific stemness or mesenchymal/EMT characteristics. SIGNIFICANCE Cancer self-renewal and migratory abilities are often characterized via gene module expression profiles, also called EMT or stemness gene expression signatures. Using published clinical tumor samples, cancer cell lines, and single cancer cells, we highlight the dominating influence of noncancer cells in low cancer cell content biopsies on their scores. We caution on their application for low cancer cell content clinical cancer samples with the intent to assign such characteristics or subtypes.
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Affiliation(s)
- Julian Kreis
- The healthcare business of Merck KGaA, Darmstadt, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Bogac Aybey
- The healthcare business of Merck KGaA, Darmstadt, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Felix Geist
- The healthcare business of Merck KGaA, Darmstadt, Germany
| | - Benedikt Brors
- Division of Applied Bioinformatics, German Cancer Research Center (DKFZ), Heidelberg University, Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg University, Heidelberg, Germany
- Medical Faculty Heidelberg and Faculty of Biosciences, Heidelberg University, and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Eike Staub
- The healthcare business of Merck KGaA, Darmstadt, Germany
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