A multi-cell model for the C4 photosynthetic pathway in developing wheat grains based upon tissue-specific transcriptome data

IF 1.9 4区 生物学 Q2 BIOLOGY Biosystems Pub Date : 2024-03-29 DOI:10.1016/j.biosystems.2024.105195
Parimalan Rangan , Agnelo Furtado , Viswanathan Chinnusamy , Robert Henry
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Abstract

A non-Kranz C4 photosynthesis of the NAD-ME subtype, specifically in developing wheat grains (14 dpa, days post-anthesis) was originally demonstrated using transcriptome-based RNA-seq. Here we present a re-examination of evidence for C4 photosynthesis in the developing grains of wheat and, more broadly, the Pooideae and an investigation of the evolutionary processes and implications. The expression profiles for the genes associated with C4 photosynthesis (C4- and C3-specific) were evaluated using published transcriptome data for the outer pericarp, inner pericarp, and endosperm tissues of the developing wheat grains. The expression of the C4-specific genes across these three tissues revealed the involvement of all three tissues in an orderly fashion to accomplish the non-Kranz NAD-ME-dependent C4 photosynthesis. Based on their expression levels in RPKM (reads per kilobase per million mapped reads) values, a model involving multiple cell- and tissue-types is proposed for C4 photosynthesis involved in the refixation of the respired CO2 from the endosperm tissues in the developing wheat grains. This multi-cell C4 model, proposed to involve more than two cell types, requires further biochemical validation.

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基于组织特异性转录组数据的发育中麦粒的 C4 光合途径多细胞模型
最初是利用基于转录组的 RNA-seq 技术证明了 NAD-ME 亚型的非克兰兹 C4 光合作用,特别是在发育中的小麦粒中(14 dpa,开花后几天)。在此,我们重新研究了小麦以及更广泛意义上的普氏植物发育中谷粒的 C4 光合作用证据,并对其进化过程和影响进行了调查。利用已发表的转录组数据,对发育中麦粒的外果皮、内果皮和胚乳组织中与 C4 光合作用相关的基因(C4 特异基因和 C3 特异基因)的表达谱进行了评估。C4 特异基因在这三种组织中的表达表明,所有三种组织都以有序的方式参与完成了非克兰兹 NAD-ME 依赖性 C4 光合作用。根据这些基因在 RPKM(每百万映射读数中每千个碱基的读数)值中的表达水平,提出了一个涉及多种细胞和组织类型的 C4 光合作用模型,该模型参与了发育中麦粒中胚乳组织呼吸的 CO2 的再固定。这种多细胞 C4 模型涉及两种以上的细胞类型,需要进一步的生化验证。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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