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Liu X, Chen H, Li Z, Yang X, Jin W, Wang Y, Zheng J, Li L, Xuan C, Yuan J, Yang Y. InPACT: a computational method for accurate characterization of intronic polyadenylation from RNA sequencing data. Nat Commun 2024; 15:2583. [PMID: 38519498 PMCID: PMC10960005 DOI: 10.1038/s41467-024-46875-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 03/12/2024] [Indexed: 03/25/2024] Open
Abstract
Alternative polyadenylation can occur in introns, termed intronic polyadenylation (IPA), has been implicated in diverse biological processes and diseases, as it can produce noncoding transcripts or transcripts with truncated coding regions. However, a reliable method is required to accurately characterize IPA. Here, we propose a computational method called InPACT, which allows for the precise characterization of IPA from conventional RNA-seq data. InPACT successfully identifies numerous previously unannotated IPA transcripts in human cells, many of which are translated, as evidenced by ribosome profiling data. We have demonstrated that InPACT outperforms other methods in terms of IPA identification and quantification. Moreover, InPACT applied to monocyte activation reveals temporally coordinated IPA events. Further application on single-cell RNA-seq data of human fetal bone marrow reveals the expression of several IPA isoforms in a context-specific manner. Therefore, InPACT represents a powerful tool for the accurate characterization of IPA from RNA-seq data.
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Affiliation(s)
- Xiaochuan Liu
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, The Second Hospital of Tianjin Medical University, Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Hao Chen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Zekun Li
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, The Second Hospital of Tianjin Medical University, Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Xiaoxiao Yang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, The Second Hospital of Tianjin Medical University, Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Wen Jin
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, The Second Hospital of Tianjin Medical University, Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Yuting Wang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, The Second Hospital of Tianjin Medical University, Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Jian Zheng
- Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Long Li
- Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China
| | - Chenghao Xuan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
| | - Jiapei Yuan
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, 300020, China.
- Tianjin Institutes of Health Science, Tianjin, 301600, China.
| | - Yang Yang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammatory Biology, The Second Hospital of Tianjin Medical University, Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
- Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China.
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Identification and in silico characterization of CSRP3 synonymous variants in dilated cardiomyopathy. Mol Biol Rep 2023; 50:4105-4117. [PMID: 36877346 DOI: 10.1007/s11033-023-08314-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 01/31/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Synonymous variations have always been ignored while studying the underlying genetic mechanisms for most of the human diseases. However, recent studies have suggested that these silent changes in the genome can alter the protein expression and folding. METHODS AND RESULTS CSRP3, which is a well-known candidate gene associated with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM), was screened for 100 idiopathic DCM cases and 100 controls. Three synonymous variations were identified viz., c.96G > A, p.K32=; c.336G > A, p.A112=; c.354G > A, p.E118=. A comprehensive in silico analysis was performed using various web based widely accepted tools, Mfold, Codon Usage, HSF3.1 and RNA22. Mfold predicted structural changes in all the variants except c.96 G > A (p.K32=), however it predicted changes in the stability of mRNA due to all the synonymous variants. Codon bias was observed as evident by the Relative Synonymous Codon Usage and Log Ratio of Codon Usage Frequencies. The Human Splicing Finder also predicted remarkable changes in the regulatory elements in the variants c.336G > A and c.354 G > A. The miRNA target prediction using varied modes available in RNA22 revealed that 70.6% of the target sites of miRNAs in CSRP3 were altered due to variant c.336G > A while 29.41% sites were completely lost. CONCLUSION Findings of the present study suggest that synonymous variants revealed striking deviations in the structural conformation of mRNA, stability of mRNA, relative synonymous codon usage, splicing and miRNA binding sites from the wild type suggesting their possible role in the pathogenesis of DCM, either by destabilizing the mRNA structure, or codon usage bias or else altering the cis-acting regulatory elements during splicing.
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Khan A, Singh K, Jaiswal S, Raza M, Jasrotia RS, Kumar A, Gurjar AKS, Kumari J, Nayan V, Iquebal MA, Angadi UB, Rai A, Datta TK, Kumar D. Whole-Genome-Based Web Genomic Resource for Water Buffalo (Bubalus bubalis). Front Genet 2022; 13:809741. [PMID: 35480326 PMCID: PMC9035531 DOI: 10.3389/fgene.2022.809741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 02/14/2022] [Indexed: 11/13/2022] Open
Abstract
Water buffalo (Bubalus bubalis), belonging to the Bovidae family, is an economically important animal as it is the major source of milk, meat, and drought in numerous countries. It is mainly distributed in tropical and subtropical regions with a global population of approximately 202 million. The advent of low cost and rapid sequencing technologies has opened a new vista for global buffalo researchers. In this study, we utilized the genomic data of five commercially important buffalo breeds, distributed globally, namely, Mediterranean, Egyptian, Bangladesh, Jaffrarabadi, and Murrah. Since there is no whole-genome sequence analysis of these five distinct buffalo breeds, which represent a highly diverse ecosystem, we made an attempt for the same. We report the first comprehensive, holistic, and user-friendly web genomic resource of buffalo (BuffGR) accessible at http://backlin.cabgrid.res.in/buffgr/, that catalogues 6028881 SNPs and 613403 InDels extracted from a set of 31 buffalo tissues. We found a total of 7727122 SNPs and 634124 InDels distributed in four breeds of buffalo (Murrah, Bangladesh, Jaffarabadi, and Egyptian) with reference to the Mediterranean breed. It also houses 4504691 SSR markers from all the breeds along with 1458 unique circRNAs, 37712 lncRNAs, and 938 miRNAs. This comprehensive web resource can be widely used by buffalo researchers across the globe for use of markers in marker trait association, genetic diversity among the different breeds of buffalo, use of ncRNAs as regulatory molecules, post-transcriptional regulations, and role in various diseases/stresses. These SNPs and InDelscan also be used as biomarkers to address adulteration and traceability. This resource can also be useful in buffalo improvement programs and disease/breed management.
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Affiliation(s)
- Aamir Khan
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Kalpana Singh
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Sarika Jaiswal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Mustafa Raza
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Rahul Singh Jasrotia
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Animesh Kumar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Anoop Kishor Singh Gurjar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Juli Kumari
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Varij Nayan
- ICAR-Central Institute for Research on Buffaloes, Hisar, India
| | - Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
- *Correspondence: Mir Asif Iquebal,
| | - U. B. Angadi
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | - Anil Rai
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
| | | | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India
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Vanvanhossou SFU, Giambra IJ, Yin T, Brügemann K, Dossa LH, König S. First DNA Sequencing in Beninese Indigenous Cattle Breeds Captures New Milk Protein Variants. Genes (Basel) 2021; 12:1702. [PMID: 34828308 PMCID: PMC8625544 DOI: 10.3390/genes12111702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 11/16/2022] Open
Abstract
This study investigated polymorphisms in the milk protein genes CSN1S1, CSN2, CSN1S2, CSN3, LALBA, and LGB, and casein haplotypes in Beninese indigenous cattle. Considering 67 animals, DNA sequencing of the genes' exons, flanking regions and parts of the 5'-upstream regions identified 1058 genetic variants including 731 previously unknown. In addition, four novel milk protein variants were detected, including CSN3K (p.Ala66Val), LALBAF (p.Arg58Trp), LGBB1 (p.Ala134Val) and LGBK (p.Thr92Asnfs*13). CSN3K is caused by a novel SNP (BTA6:85656526C>T, exon 4) whereas LALBAF and LGBB1 are due to rs714688595C>T (exon 1) and rs109625649C>T (exon 4), respectively. Regarding LGBK, a frameshift insertion of one adenine residue at BTA11:103257980 (exon 3) induces a premature translation termination resulting in a 46% reduction of the reference protein sequence. The casein polymorphisms formed five main CSN1S1-CSN2-CSN1S2-CSN3 haplotypes including B-A1-A-B, B-A1-A-A and C-A2-A-B which are predominant in the investigated cattle breeds. Moreover, in silico analyses of polymorphisms within the 5'- and 3'- untranslated regions of all six milk proteins revealed effects on microRNA and transcription factor binding sites. This study suggests a large genetic variation of milk protein genes in Beninese cattle, which should be investigated in further studies for their effects on milk production, including quality and yield traits.
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Affiliation(s)
- Sèyi Fridaïus Ulrich Vanvanhossou
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany; (S.F.U.V.); (I.J.G.); (T.Y.); (K.B.)
| | - Isabella Jasmin Giambra
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany; (S.F.U.V.); (I.J.G.); (T.Y.); (K.B.)
| | - Tong Yin
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany; (S.F.U.V.); (I.J.G.); (T.Y.); (K.B.)
| | - Kerstin Brügemann
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany; (S.F.U.V.); (I.J.G.); (T.Y.); (K.B.)
| | - Luc Hippolyte Dossa
- School of Science and Technics of Animal Production, Faculty of Agricultural Sciences, University of Abomey-Calavi, Abomey-Calavi, 03 BP 2819 Jéricho Cotonou, Benin;
| | - Sven König
- Institute of Animal Breeding and Genetics, Justus-Liebig-University Gießen, 35390 Gießen, Germany; (S.F.U.V.); (I.J.G.); (T.Y.); (K.B.)
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Gao Y, Hao Q, Cang M, Wang J, Yu H, Liu Y, Zhang W, Tong B. Association between novel variants in BMPR1B gene and litter size in Mongolia and Ujimqin sheep breeds. Reprod Domest Anim 2021; 56:1562-1571. [PMID: 34543455 DOI: 10.1111/rda.14020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 09/17/2021] [Indexed: 11/27/2022]
Abstract
Prolificacy is an important trait of animals, specifically for sheep. The Bone morphogenetic protein receptor 1B (BMPR1B) is a major gene affecting the litter size of many sheep breeds. The well-known FecB mutation (Q249R) was associated fully with the hyper prolific phenotype of Booroola Merino. However, the identification of variation in all exonic regions of BMPR1B was rare. In this study, we sequenced all exonic regions of BMPR1B gene of Mongolia sheep breed, and ten novel variants were detected by direct sequencing. Among them, the litter size of the Mongolia ewes with the CC genotype was significantly higher (0.34 additional lambs, p < .05) than those with the TT genotype of the g.29346567C>T single nucleotide polymorphism (SNP). The litter size of the Mongolia ewes with the TT genotype was significantly higher (0.19 additional lambs, p < .05 and .31 additional lambs, p < .01, respectively) than those with the GT and GG genotypes of the c.1470G>T SNP. The silent c.1470G>T mutation is predicted to increase the stability of the mRNA secondary structure through reducing minimum free energy and is predicted to change the mRNA secondary structure of BMPR1B. Our findings may give potentially useful genetic markers for increasing litter size in sheep.
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Affiliation(s)
- Yuanyuan Gao
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Qi Hao
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Ming Cang
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Jianguo Wang
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Haiquan Yu
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Yongbin Liu
- Institute of Animal Science, Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Hohhot, China
| | - Wenguang Zhang
- College of Animal Sciences, Inner Mongolia Agricultural University, Hohhot, China
| | - Bin Tong
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
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