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      N 6-Methyladenine DNA Modification in the Woodland Strawberry ( Fragaria vesca) Genome Reveals a Positive Relationship With Gene Transcription

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          Abstract

          N 6-methyladenine (6mA) DNA modification has been detected in several eukaryotic organisms, where it plays important roles in gene regulation and epigenetic memory maintenance. However, the genome-wide distribution patterns and potential functions of 6mA DNA modification in woodland strawberry ( Fragaria vesca) remain largely unknown. Here, we examined the 6mA landscape in the F. vesca genome by adopting single-molecule real-time sequencing technology and found that 6mA modification sites were broadly distributed across the woodland strawberry genome. The pattern of 6mA distribution in the long non-coding RNA was significantly different from that in protein-coding genes. The 6mA modification influenced the gene transcription and was positively associated with gene expression, which was validated by computational and experimental analyses. Our study provides new insights into the DNA methylation in F. vesca.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          Kenneth Livak, Thomas D. Schmittgen (2001)
          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms

            Cole Trapnell, Brian A Williams, Geo M Pertea … (2013)
            High-throughput mRNA sequencing (RNA-Seq) holds the promise of simultaneous transcript discovery and abundance estimation 1-3 . We introduce an algorithm for transcript assembly coupled with a statistical model for RNA-Seq experiments that produces estimates of abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Analysis of transcript expression over the time series revealed complete switches in the dominant transcription start site (TSS) or splice-isoform in 330 genes, along with more subtle shifts in a further 1,304 genes. These dynamics suggest substantial regulatory flexibility and complexity in this well-studied model of muscle development.
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              TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

              Daehwan Kim, Geo M Pertea, Cole Trapnell … (2016)
              TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat.
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                Author and article information

                Contributors
                Journal
                Journal ID (nlm-ta): Front Genet
                Journal ID (iso-abbrev): Front Genet
                Journal ID (publisher-id): Front. Genet.
                Title: Frontiers in Genetics
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 1664-8021
                Publication date (Electronic): 10 January 2020
                Publication date Collection: 2019
                Volume: 10
                Electronic Location Identifier: 1288
                Affiliations
                [1] 1Key Laboratory of Ministry of Education for Genetics and Germplasm Innovation of Tropical Special Trees and Ornamental Plants, Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, College of Forestry, Natural Rubber Cooperative Innovation Centre of Hainan Province & Ministry of Education of China, Hainan University , Haikou, China
                [2] 2State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University , Guangzhou, China
                [3] 3Institute of Wheat Research, Shanxi Academy of Agricultural Sciences , Linfen, China
                Author notes

                Edited by: Mattia Pelizzola, Italian Institute of Technology, Italy

                Reviewed by: Fei Li, Zhejiang University, China; Tingting Gu, Nanjing Agricultural University, China

                *Correspondence: Xi-Qiang Song, songstrong@ 123456hainanu.edu.cn ; Jun Zheng, sxnkyzj@ 123456126.com ; Ying Chen, chenying2016@ 123456gmail.com

                †These authors have contributed equally to this work and share first authorship

                This article was submitted to Bioinformatics and Computational Biology, a section of the journal Frontiers in Genetics

                Article
                DOI: 10.3389/fgene.2019.01288
                PMC ID: 6967393
                PubMed ID: 31998359
                SO-VID: beea1238-05af-4981-8c0b-d7f1a5342654
                Copyright © Copyright © 2020 Xie, Xing, Zhang, Liu, Luan, Zhu, Ling, Xiao, Song, Zheng and Chen
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 28 April 2019
                Date accepted : 22 November 2019
                Page count
                Figures: 6, Tables: 1, Equations: 0, References: 49, Pages: 13, Words: 6142
                Categories
                Subject: Genetics
                Subject: Original Research

                ScienceOpen disciplines: Genetics
                Keywords: fragaria vesca,dna 6ma modification,single-molecule real time,gene expression,long non-coding rna
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: fragaria vesca, dna 6ma modification, single-molecule real time, gene expression, long non-coding rna

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