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Hao S, Zhang L, Zhao D, Zhou J, Ye C, Qu H, Li QQ. Inhibitor AN3661 reveals biological functions of Arabidopsis CLEAVAGE and POLYADENYLATION SPECIFICITY FACTOR 73. PLANT PHYSIOLOGY 2023; 193:537-554. [PMID: 37335917 DOI: 10.1093/plphys/kiad352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 05/09/2023] [Accepted: 05/21/2023] [Indexed: 06/21/2023]
Abstract
Cleavage and polyadenylation specificity factor (CPSF) is a protein complex that plays an essential biochemical role in mRNA 3'-end formation, including poly(A) signal recognition and cleavage at the poly(A) site. However, its biological functions at the organismal level are mostly unknown in multicellular eukaryotes. The study of plant CPSF73 has been hampered by the lethality of Arabidopsis (Arabidopsis thaliana) homozygous mutants of AtCPSF73-I and AtCPSF73-II. Here, we used poly(A) tag sequencing to investigate the roles of AtCPSF73-I and AtCPSF73-II in Arabidopsis treated with AN3661, an antimalarial drug with specificity for parasite CPSF73 that is homologous to plant CPSF73. Direct seed germination on an AN3661-containing medium was lethal; however, 7-d-old seedlings treated with AN3661 survived. AN3661 targeted AtCPSF73-I and AtCPSF73-II, inhibiting growth through coordinating gene expression and poly(A) site choice. Functional enrichment analysis revealed that the accumulation of ethylene and auxin jointly inhibited primary root growth. AN3661 affected poly(A) signal recognition, resulted in lower U-rich signal usage, caused transcriptional readthrough, and increased the distal poly(A) site usage. Many microRNA targets were found in the 3' untranslated region lengthened transcripts; these miRNAs may indirectly regulate the expression of these targets. Overall, this work demonstrates that AtCPSF73 plays important part in co-transcriptional regulation, affecting growth, and development in Arabidopsis.
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Affiliation(s)
- Saiqi Hao
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystem, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China
| | - Lidan Zhang
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystem, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China
| | - Danhui Zhao
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystem, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China
| | - Jiawen Zhou
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystem, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China
| | - Congting Ye
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystem, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China
| | - Haidong Qu
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystem, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China
| | - Qingshun Q Li
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystem, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian 361102, China
- Biomedical Sciences, College of Dental Medicine, Western University of Health Sciences, Pomona, CA 91766, USA
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Lu DYH, Liao JY, Fajar A, Chen JB, Wei Y, Zhang ZH, Zhang Z, Zheng LM, Tan XQ, Zhou XG, Shi XB, Liu Y, Zhang DY. Co-infection of TYLCV and ToCV increases cathepsin B and promotes ToCV transmission by Bemisia tabaci MED. Front Microbiol 2023; 14:1107038. [PMID: 37007483 PMCID: PMC10061087 DOI: 10.3389/fmicb.2023.1107038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 02/15/2023] [Indexed: 03/18/2023] Open
Abstract
Tomato disease is an important disease affecting agricultural production, and the combined infection of tomato chlorosis virus (ToCV) and tomato yellow leaf curl virus (TYLCV) has gradually expanded in recent years, but no effective control method has been developed to date. Both viruses are transmitted by Bemisia tabaci Mediteranean (MED). Previously, we found that after B. tabaci MED was fed on ToCV-and TYLCV-infected plants, the transmission efficiency of ToCV was significantly higher than that on plants infected only with ToCV. Therefore, we hypothesize that co-infection could enhance the transmission rates of the virus. In this study, transcriptome sequencing was performed to compare the changes of related transcription factors in B. tabaci MED co-infected with ToCV and TYLCV and infected only with ToCV. Hence, transmission experiments were carried out using B. tabaci MED to clarify the role of cathepsin in virus transmission. The gene expression level and enzyme activity of cathepsin B (Cath B) in B. tabaci MED co-infected with ToCV and TYLCV increased compared with those under ToCV infection alone. After the decrease in cathepsin activity in B. tabaci MED or cathepsin B was silenced, its ability to acquire and transmit ToCV was significantly reduced. We verified the hypothesis that the relative expression of cathepsin B was reduced, which helped reduce ToCV transmission by B. tabaci MED. Therefore, it was speculated that cathepsin has profound research significance in the control of B. tabaci MED and the spread of viral diseases.
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Affiliation(s)
- Ding-Yi-Hui Lu
- Subcollege of Longping, College of Biology, Graduate School of Hunan University, Changsha, China
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
| | - Jin-Yu Liao
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
| | - Anugerah Fajar
- Department of Entomology, University of Kentucky, Lexington, KY, United States
- Research Center for Biomaterials, Indonesia Institute of Sciences, Cibinong, Indonesia
| | - Jian-Bin Chen
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
| | - Yan Wei
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
| | - Zhan-Hong Zhang
- Institute of Vegetable, Hunan Academy of Agricultural Sciences, Changsha, China
| | - Zhuo Zhang
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
| | - Li-Min Zheng
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
| | - Xin-Qiu Tan
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
| | - Xu-Guo Zhou
- Department of Entomology, University of Kentucky, Lexington, KY, United States
| | - Xiao-Bin Shi
- Subcollege of Longping, College of Biology, Graduate School of Hunan University, Changsha, China
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
- *Correspondence: Xiao-Bin Shi, ; Yong Liu, ; De-Yong Zhang,
| | - Yong Liu
- Subcollege of Longping, College of Biology, Graduate School of Hunan University, Changsha, China
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
- *Correspondence: Xiao-Bin Shi, ; Yong Liu, ; De-Yong Zhang,
| | - De-Yong Zhang
- Subcollege of Longping, College of Biology, Graduate School of Hunan University, Changsha, China
- Hunan Academy of Agricultural Sciences, Institute of Plant Protection, Changsha, China
- *Correspondence: Xiao-Bin Shi, ; Yong Liu, ; De-Yong Zhang,
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Ye W, Lian Q, Ye C, Wu X. A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq. GENOMICS, PROTEOMICS & BIOINFORMATICS 2022:S1672-0229(22)00121-8. [PMID: 36167284 PMCID: PMC10372920 DOI: 10.1016/j.gpb.2022.09.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 08/17/2022] [Accepted: 09/19/2022] [Indexed: 05/08/2023]
Abstract
Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA sequencing (RNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Particularly, we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques, and provided our perspective on how computational methodologies might evolve in the future for non-3' untranslated region, tissue-specific, cross-species, and single-cell pA prediction.
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Affiliation(s)
- Wenbin Ye
- Pasteurien College, Suzhou Medical College of Soochow University, Soochow University, Suzhou 215000, China
| | - Qiwei Lian
- Pasteurien College, Suzhou Medical College of Soochow University, Soochow University, Suzhou 215000, China; Department of Automation, Xiamen University, Xiamen 361005, China
| | - Congting Ye
- Key Laboratory of the Coastal and Wetland Ecosystems, Ministry of Education, College of the Environment and Ecology, Xiamen University, Xiamen 361005, China
| | - Xiaohui Wu
- Pasteurien College, Suzhou Medical College of Soochow University, Soochow University, Suzhou 215000, China.
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scAPAmod: Profiling Alternative Polyadenylation Modalities in Single Cells from Single-Cell RNA-Seq Data. Int J Mol Sci 2022; 23:ijms23158123. [PMID: 35897701 PMCID: PMC9329739 DOI: 10.3390/ijms23158123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 07/01/2022] [Accepted: 07/21/2022] [Indexed: 11/17/2022] Open
Abstract
Alternative polyadenylation (APA) is a key layer of gene expression regulation, and APA choice is finely modulated in cells. Advances in single-cell RNA-seq (scRNA-seq) have provided unprecedented opportunities to study APA in cell populations. However, existing studies that investigated APA in single cells were either confined to a few cells or focused on profiling APA dynamics between cell types or identifying APA sites. The diversity and pattern of APA usages on a genomic scale in single cells remains unappreciated. Here, we proposed an analysis framework based on a Gaussian mixture model, scAPAmod, to identify patterns of APA usage from homogeneous or heterogeneous cell populations at the single-cell level. We systematically evaluated the performance of scAPAmod using simulated data and scRNA-seq data. The results show that scAPAmod can accurately identify different patterns of APA usages at the single-cell level. We analyzed the dynamic changes in the pattern of APA usage using scAPAmod in different cell differentiation and developmental stages during mouse spermatogenesis and found that even the same gene has different patterns of APA usages in different differentiation stages. The preference of patterns of usages of APA sites in different genomic regions was also analyzed. We found that patterns of APA usages of the same gene in 3′ UTRs (3′ untranslated region) and non-3′ UTRs are different. Moreover, we analyzed cell-type-specific APA usage patterns and changes in patterns of APA usages across cell types. Different from the conventional analysis of single-cell heterogeneity based on gene expression profiling, this study profiled the heterogeneous pattern of APA isoforms, which contributes to revealing the heterogeneity of single-cell gene expression with higher resolution.
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Zhu S, Lian Q, Ye W, Qin W, Wu Z, Ji G, Wu X. scAPAdb: a comprehensive database of alternative polyadenylation at single-cell resolution. Nucleic Acids Res 2021; 50:D365-D370. [PMID: 34508354 PMCID: PMC8728153 DOI: 10.1093/nar/gkab795] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 08/26/2021] [Accepted: 09/02/2021] [Indexed: 01/08/2023] Open
Abstract
Alternative polyadenylation (APA) is a widespread regulatory mechanism of transcript diversification in eukaryotes, which is increasingly recognized as an important layer for eukaryotic gene expression. Recent studies based on single-cell RNA-seq (scRNA-seq) have revealed cell-to-cell heterogeneity in APA usage and APA dynamics across different cell types in various tissues, biological processes and diseases. However, currently available APA databases were all collected from bulk 3′-seq and/or RNA-seq data, and no existing database has provided APA information at single-cell resolution. Here, we present a user-friendly database called scAPAdb (http://www.bmibig.cn/scAPAdb), which provides a comprehensive and manually curated atlas of poly(A) sites, APA events and poly(A) signals at the single-cell level. Currently, scAPAdb collects APA information from > 360 scRNA-seq experiments, covering six species including human, mouse and several other plant species. scAPAdb also provides batch download of data, and users can query the database through a variety of keywords such as gene identifier, gene function and accession number. scAPAdb would be a valuable and extendable resource for the study of cell-to-cell heterogeneity in APA isoform usages and APA-mediated gene regulation at the single-cell level under diverse cell types, tissues and species.
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Affiliation(s)
- Sheng Zhu
- Pasteurien College, Soochow University, Suzhou, Jiangsu 215000, China.,Department of Automation, Xiamen University, Xiamen, Fujian 361005, China
| | - Qiwei Lian
- Department of Automation, Xiamen University, Xiamen, Fujian 361005, China
| | - Wenbin Ye
- Department of Automation, Xiamen University, Xiamen, Fujian 361005, China
| | - Wei Qin
- Department of Automation, Xiamen University, Xiamen, Fujian 361005, China
| | - Zhe Wu
- Department of Automation, Xiamen University, Xiamen, Fujian 361005, China
| | - Guoli Ji
- Department of Automation, Xiamen University, Xiamen, Fujian 361005, China
| | - Xiaohui Wu
- Pasteurien College, Soochow University, Suzhou, Jiangsu 215000, China
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Meng X, Kuang K, Zhang Y, Guan K, Liu B, Zhou X. Alternative polyadenylation events differ dramatically between Tongcheng and Large White pigs in response to PRRSV infection. Anim Genet 2021; 52:744-748. [PMID: 34309053 DOI: 10.1111/age.13125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/05/2021] [Indexed: 12/01/2022]
Abstract
Alternative polyadenylation (APA) is a widespread post-transcriptional regulation mechanism that increases the biological complexity of transcriptome and proteome. However, it is unclear whether APA regulation plays a role in genetic resistance to porcine reproductive and respiratory syndrome virus (PRRSV). Here, we reported genome-wide APA regulation of porcine alveolar macrophages in PRRSV-resistant Tongcheng (TC) pigs and PRRSV-susceptible Large White (LW) pigs upon PRRSV infection. Using 3' mRNA sequencing strategy, we detected 75 981 high-quality APA sites in porcine alveolar macrophages of TC and LW pigs. Furthermore, 1202 and 1089 differentially expressed APA sites, as well as 79 and 117 untranslated region-APA switching genes were identified in TC pigs and LW pigs upon PRRSV infection respectively. The APA events in TC pigs and LW pigs were involved in different biological pathways, while APA events in TC pigs are directly associated with the immune response to PRRSV infection. In addition, we identified genetic variations affecting polyadenylation signal between TC pigs and LW pigs. These findings would provide helpful information on APA regulation for further understanding of genetic resistance to PRRSV.
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Affiliation(s)
- X Meng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - K Kuang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Y Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - K Guan
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - B Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Engineering Technology Research Center of Hubei Province Local Pig Breed Improvement, Wuhan, 430070, China
| | - X Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.,The Engineering Technology Research Center of Hubei Province Local Pig Breed Improvement, Wuhan, 430070, China
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Wu X, Liu T, Ye C, Ye W, Ji G. scAPAtrap: identification and quantification of alternative polyadenylation sites from single-cell RNA-seq data. Brief Bioinform 2020; 22:5952304. [PMID: 33142319 DOI: 10.1093/bib/bbaa273] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Revised: 09/17/2020] [Accepted: 09/20/2020] [Indexed: 02/06/2023] Open
Abstract
Alternative polyadenylation (APA) generates diverse mRNA isoforms, which contributes to transcriptome diversity and gene expression regulation by affecting mRNA stability, translation and localization in cells. The rapid development of 3' tag-based single-cell RNA-sequencing (scRNA-seq) technologies, such as CEL-seq and 10x Genomics, has led to the emergence of computational methods for identifying APA sites and profiling APA dynamics at single-cell resolution. However, existing methods fail to detect the precise location of poly(A) sites or sites with low read coverage. Moreover, they rely on priori genome annotation and can only detect poly(A) sites located within or near annotated genes. Here we proposed a tool called scAPAtrap for detecting poly(A) sites at the whole genome level in individual cells from 3' tag-based scRNA-seq data. scAPAtrap incorporates peak identification and poly(A) read anchoring, enabling the identification of the precise location of poly(A) sites, even for sites with low read coverage. Moreover, scAPAtrap can identify poly(A) sites without using priori genome annotation, which helps locate novel poly(A) sites in previously overlooked regions and improve genome annotation. We compared scAPAtrap with two latest methods, scAPA and Sierra, using scRNA-seq data from different experimental technologies and species. Results show that scAPAtrap identified poly(A) sites with higher accuracy and sensitivity than competing methods and could be used to explore APA dynamics among cell types or the heterogeneous APA isoform expression in individual cells. scAPAtrap is available at https://github.com/BMILAB/scAPAtrap.
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Affiliation(s)
- Xiaohui Wu
- Department of Automation in Xiamen University
| | - Tao Liu
- Department of Automation in Xiamen University
| | - Congting Ye
- College of the Environment and Ecology in Xiamen University
| | - Wenbin Ye
- Department of Automation in Xiamen University
| | - Guoli Ji
- Department of Automation in Xiamen University
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