Genome-Wide Identification, Characterization and Function Analysis of Lineage-Specific Genes in the Tea Plant Camellia sinensis

Zhao, Zhonglong; Ma, Dongna

doi:10.3389/fgene.2021.770570

Cited by 8 publications

(8 citation statements)

References 67 publications

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“…Similarly, 18 OGs were proven to be related to male sterility in watermelon (Citrullus lanatus), and the research also confirmed that 182 OGs were involved in flower development in cucumber (Cucumis sativus), 520 OGs may help with the large fruit size in wax gourd (Benincasa hispida) (Ma et al, 2022). Study showed that 18 CSGs were mainly associated with phenylalanine biosynthesis, biosynthesis of amino acids, pentose phosphate pathway, photosynthesis, and carbon metabolism (Zhao and Ma, 2021). TSGs were proven to be associated with reproductive organ development, and 25 flower-specific TSGs showed specific expression in developing anthers and had an even higher expression level (Ma et al, 2020).…”

Section: Role Of Orphan Genes In Primary Substance Metabolism and Res...mentioning

confidence: 66%

“…The rapid accumulation of genomic data on a large variety of plants will allow increasing integrity of identification of OGs. So far the presence of OGs has been reported in many plants or lineages [such as B. rapa (Jiang et al, 2018), A. thaliana (Yang et al, 2009;Lin et al, 2010;Donoghue et al, 2011;Cui et al, 2015), O. sativa (Guo et al, 2007;Yang et al, 2009;Cui et al, 2015;Jin et al, 2019), P. trichocarpa (Yang et al, 2009), V. unguiculata (Li G. et al, 2019), Poaceae (Campbell et al, 2007), Aegiceras corniculatum (Ma et al, 2021), C. sinensis (Xu et al, 2015), Amaranthus hypochondriacus (Cabrales-Orona and Délano-Frier, 2021), Camellia sinensis (Zhao and Ma, 2021), and eight Cucurbitaceae family members (Ma et al, 2022)]. Every sequenced genome contains OGs whose origins are obscure because of the absence of homologs (Blanco-Melo et al, 2016).…”

Section: Orphan Genes Identification and Its Fast Evolving Characteri...mentioning

confidence: 99%

“…Thus, the above evidence indicates that BrOGs play a certain role in developmental stages, different tissues, organs, and biotic stress responses. Camellia-specific genes (CSGs) had more tissuespecific expression compared to evolutionary conserved genes (Zhao and Ma, 2021). The Arabidopsis-specific genes tend to possess an upregulated expression in mature pollen and under heat stress (Yang et al, 2009).…”

Section: Special Expression Regulatory Mode Of Orphan Genesmentioning

confidence: 99%

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Research Advances and Prospects of Orphan Genes in Plants

Jiang

Dong

et al. 2022

Front. Plant Sci.

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Orphan genes (OGs) are defined as genes having no sequence similarity with genes present in other lineages. OGs have been regarded to play a key role in the development of lineage-specific adaptations and can also serve as a constant source of evolutionary novelty. These genes have often been found related to various stress responses, species-specific traits, special expression regulation, and also participate in primary substance metabolism. The advancement in sequencing tools and genome analysis methods has made the identification and characterization of OGs comparatively easier. In the study of OG functions in plants, significant progress has been made. We review recent advances in the fast evolving characteristics, expression modulation, and functional analysis of OGs with a focus on their role in plant biology. We also emphasize current challenges, adoptable strategies and discuss possible future directions of functional study of OGs.

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Section: Role Of Orphan Genes In Primary Substance Metabolism and Res...mentioning

confidence: 66%

Section: Orphan Genes Identification and Its Fast Evolving Characteri...mentioning

confidence: 99%

Section: Special Expression Regulatory Mode Of Orphan Genesmentioning

confidence: 99%

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Research Advances and Prospects of Orphan Genes in Plants

Jiang

Dong

et al. 2022

Front. Plant Sci.

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“…BLAST (2.11.0+) [ 26 ] was used to identify OG based on previous studies [ 6 , 27 – 29 ]. Moso bamboo protein sequences were downloaded from Bamboo GDB [ 30 ].…”

Section: Methodsmentioning

confidence: 99%

A deep learning approach for orphan gene identification in moso bamboo (Phyllostachys edulis) based on the CNN + Transformer model

et al. 2022

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Background Orphan gene play an important role in the environmental stresses of many species and their identification is a critical step to understand biological functions. Moso bamboo has high ecological, economic and cultural value. Studies have shown that the growth of moso bamboo is influenced by various stresses. Several traditional methods are time-consuming and inefficient. Hence, the development of efficient and high-accuracy computational methods for predicting orphan genes is of great significance. Results In this paper, we propose a novel deep learning model (CNN + Transformer) for identifying orphan genes in moso bamboo. It uses a convolutional neural network in combination with a transformer neural network to capture k-mer amino acids and features between k-mer amino acids in protein sequences. The experimental results show that the average balance accuracy value of CNN + Transformer on moso bamboo dataset can reach 0.875, and the average Matthews Correlation Coefficient (MCC) value can reach 0.471. For the same testing set, the Balance Accuracy (BA), Geometric Mean (GM), Bookmaker Informedness (BM), and MCC values of the recurrent neural network, long short-term memory, gated recurrent unit, and transformer models are all lower than those of CNN + Transformer, which indicated that the model has the extensive ability for OG identification in moso bamboo. Conclusions CNN + Transformer model is feasible and obtains the credible predictive results. It may also provide valuable references for other related research. As our knowledge, this is the first model to adopt the deep learning techniques for identifying orphan genes in plants.

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“…With an increasing number of studies on the epigenetic variations and compositional changes of secondary metabolites in tea plants under different experimental conditions (Zhao et al, 2022;Wang et al, 2022;Liao et al, 2022), the omics dataset of Camellia sinensis has also become increasingly extensive. This has led to the use of systems biology approaches on sequencing data hosted on public databases (Tai et al, 2018;Xia et al, 2020;Zhao et al, 2021), such as gene co-expression analysis, becoming a trend in analyzing omics data of Camellia sinensis, providing tea researchers with a more macroscopic and comprehensive perspective. Researchers have further downloaded large-scale transcriptome data of tea plants and created a more systematic and comprehensive co-expression database TeaCoN (http://teacon.wchoda.com) (Zhang et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

A method for mining condition-specific co-expressed genes inCamellia sinensisbased on K-means clustering: A case study of “Anji Baicha” tea cultivar

Zheng,

Lim,

Mutwil

et al. 2024

Preprint

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As one of the world's most important beverage crops, tea plants (Camellia sinensis) are renowned for their unique flavors and numerous beneficial secondary metabolites, attracting researchers to investigate the formation of tea quality. With the increasing availability of transcriptome data on tea plants in public databases, conducting large-scale co-expression analyses has become feasible to meet the demand for functional characterization of tea plant genes. However, as the multidimensional noise increases, larger-scale co-expression analyses are not always effective. Analyzing a subset of samples generated by effectively downsampling and reorganizing the global sample set often leads to more accurate results in co-expression analysis. Meanwhile, global-based co-expression analyses are more likely to overlook condition-specific gene interactions, which may be more important and worthy of exploration and research. Here, we employed the k-means clustering method to organize and classify the global samples of tea plants, resulting in clustered samples. Metadata annotations were then performed on these clustered samples to determine the "conditions" represented by each cluster. Subsequently, we conducted gene co-expression network analysis (WGCNA) separately on the global samples and the clustered samples, resulting in global modules and cluster-specific modules. Comparative analyses of global modules and cluster-specific modules have demonstrated that cluster-specific modules exhibit higher accuracy in co-expression analysis. To measure the degree of condition specificity of genes within condition-specific clusters, we introduced the correlation difference value (CDV). By incorporating the CDV into co-expression analyses, we can assess the condition specificity of genes. This approach proved instrumental in identifying a PPR-type RNA editing factor gene (CWM1) that specifically functions during the bud-prealbinism stage of the Camellia sinensis cultivar "Anji Baicha". We hypothesize that this gene may be upregulated and play a role in inhibiting chloroplast development, ultimately resulting in albino phenotypes in "Anji Baicha".

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Genome-Wide Identification, Characterization and Function Analysis of Lineage-Specific Genes in the Tea Plant Camellia sinensis

Cited by 8 publications

References 67 publications

Research Advances and Prospects of Orphan Genes in Plants

Research Advances and Prospects of Orphan Genes in Plants

A deep learning approach for orphan gene identification in moso bamboo (Phyllostachys edulis) based on the CNN + Transformer model

A method for mining condition-specific co-expressed genes inCamellia sinensisbased on K-means clustering: A case study of “Anji Baicha” tea cultivar

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