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      Arabidopsis transcription factor TCP4 represses chlorophyll biosynthesis to prevent petal greening

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          Abstract

          Green petals pose a challenge for pollinators to distinguish flowers from leaves, but they are valuable as a specialty flower trait. However, little is understood about the molecular mechanisms that underlie the development of green petals. Here, we report that CINCINNATA (CIN)-like TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP) proteins play key roles in the control of petal color. The septuple tcp2/3/4/5/10/13/17 mutant produced flowers with green petals due to chlorophyll accumulation. Expression of TCP4 complemented the petal phenotype of tcp2/3/4/5/10/13/17. We found that chloroplasts were converted into leucoplasts in the distal parts of wild-type petals but not in the proximal parts during flower development, whereas plastid conversion was compromised in the distal parts of tcp2/3/4/5/10/13/17 petals. TCP4 and most CIN-like TCPs were predominantly expressed in distal petal regions, consistent with the green–white pattern in wild-type petals and the petal greening observed in the distal parts of tcp2/3/4/5/10/13/17 petals. RNA-sequencing data revealed that most chlorophyll biosynthesis genes were downregulated in the white distal parts of wild-type petals, but these genes had elevated expression in the distal green parts of tcp2/3/4/5/10/13/17 petals and the green proximal parts of wild-type petals. We revealed that TCP4 repressed chlorophyll biosynthesis by directly binding to the promoters of PROTOCHLOROPHYLLIDE REDUCTASE ( PORB), DIVINYL REDUCTASE ( DVR), and SUPPRESSOR OF OVEREXPRESSION OF CO 1 ( SOC1), which are known to promote petal greening. We found that the conversion of chloroplasts to leucoplasts and the green coloration in the proximal parts of petals appeared to be conserved among plant species. Our findings uncover a major molecular mechanism that underpins the formation of petal color patterns and provide a foundation for the breeding of plants with green flowers.

          Abstract

          Green petals pose a challenge for pollinators to distinguish flowers from leaves but are valuable as a specialty flower trait. This study demonstrates that CIN-like TCP transcription factors repress petal greening by directly and indirectly inhibiting chlorophyll biosynthesis, revealing a molecular mechanism that underpins the formation of green petals and providing a foundation for the breeding of green-flowered cultivars.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

            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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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Contributors
                Journal
                Plant Commun
                Plant Commun
                Plant Communications
                Elsevier
                2590-3462
                03 March 2022
                11 July 2022
                03 March 2022
                : 3
                : 4
                : 100309
                Affiliations
                [1 ]State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, People's Republic of China
                Author notes
                []Corresponding author qingenji@ 123456pku.edu.cn
                Article
                S2590-3462(22)00056-6 100309
                10.1016/j.xplc.2022.100309
                9284284
                35605201
                ac7b77da-447f-4aa0-996d-063d63d7bf44
                © 2022 The Author(s)

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 20 October 2021
                : 16 January 2022
                : 1 March 2022
                Categories
                Research Article

                flower development,petal greening,plastid conversion,chlorophyll biosynthesis,tcp transcription factors

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