RGPDB: database of root-associated genes and promoters in maize, soybean, and sorghum

Moisseyev, Gleb; Park, Kiyoul; Cui, Alix; Freitas, D. B. de; Rajagopal, Divith; Konda, Anji Reddy; Martin-Olenski, Madalayne; Mcham, Mackenzie; Liu, Kan; Du, Qian; Schnable, James C.; Moriyama, Etsuko N.; Cahoon, Edgar B.; Zhang, Chi

doi:10.1093/database/baaa038

Cited by 11 publications

(5 citation statements)

References 48 publications

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“…Therefore, a more targeted exploration of Tabula Glycine might reveal additional interesting cell-type marker candidate genes. As another reflection of the uses of Tabula Glycine, we also reevaluated the expression pattern of 318 soybean genes identified as preferentially expressed in the soybean root system [44]. While we confirmed the preferential activity of these genes in the root and the nodule, we noticed their differential expression between clusters (Figs.…”

Section: Evaluating the Transcriptomic Heterogeneity Of The Soybean C...mentioning

confidence: 73%

Tabula Glycine: The whole-soybean single-cell resolution transcriptome atlas

Cervantes-Pérez,

Thibivilliers,

Amini

et al. 2024

Preprint

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SummarySoybean (Glycine max) is an essential source of protein and oil with high nutritional value for human and animal consumption. To enhance our understanding of soybean biology, it is essential to have accurate information regarding the expression of each of its 55,897 protein-coding genes. Here, we present “Tabula Glycine”, the soybean single-cell resolution transcriptome atlas. This atlas is composed of single-nucleus RNA-sequencing data of nearly 120,000 nuclei isolated from 10 differentGlycine maxorgans and morphological structures comprising the entire soybean plant. These nuclei are grouped into 157 different clusters based on their transcriptomic profiles. Among genes, the pattern of activity of transcription factor genes is sufficient to define most cell types and their organ/morphological structure of origin, suggesting that transcription factors are key determinants of cell identity and function. This unprecedented level of resolution makes the Tabula Glycine a unique resource for the plant and soybean communities.

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Section: Evaluating the Transcriptomic Heterogeneity Of The Soybean C...mentioning

confidence: 73%

Tabula Glycine: The whole-soybean single-cell resolution transcriptome atlas

Cervantes-Pérez,

Thibivilliers,

Amini

et al. 2024

Preprint

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“…To verify the accuracy of all the tissue-specific genes, we conducted a comprehensive literature search and finally collected 2,108, 1,908, 1,516, and 2,122 tissue-specific genes in total for leaf, root, seed, and nodule, respectively ( Supplementary File 2 ), which are used as the benchmark datasets ( Libault et al, 2009 , 2010 ; Severin et al, 2010 ; Asakura et al, 2012 ; Jones and Vodkin, 2013 ; Brown and Hudson, 2015 ; Machado et al, 2020 ; Moisseyev et al, 2020 ). Supplementary Figure 6 shows the common genes between our results (denoted as O) and genes found in the eight benchmark studies (from A to H, with some detailed information from each study shown in Supplementary File 2 ).…”

Section: Resultsmentioning

confidence: 99%

Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model

Zeng

et al. 2022

Front. Plant Sci.

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Plant tissues are distinguished by their gene expression patterns, which can help identify tissue-specific highly expressed genes and their differential functional modules. For this purpose, large-scale soybean transcriptome samples were collected and processed starting from raw sequencing reads in a uniform analysis pipeline. To address the gene expression heterogeneity in different tissues, we utilized an adversarial deconfounding autoencoder (AD-AE) model to map gene expressions into a latent space and adapted a standard unsupervised autoencoder (AE) model to help effectively extract meaningful biological signals from the noisy data. As a result, four groups of 1,743, 914, 2,107, and 1,451 genes were found highly expressed specifically in leaf, root, seed and nodule tissues, respectively. To obtain key transcription factors (TFs), hub genes and their functional modules in each tissue, we constructed tissue-specific gene regulatory networks (GRNs), and differential correlation networks by using corrected and compressed gene expression data. We validated our results from the literature and gene enrichment analysis, which confirmed many identified tissue-specific genes. Our study represents the largest gene expression analysis in soybean tissues to date. It provides valuable targets for tissue-specific research and helps uncover broader biological patterns. Code is publicly available with open source at https://github.com/LingtaoSu/SoyMeta.

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“…Many efficient technologies have been developed in plants based on the superposition of modular cloning systems with predefined standardization. TDTHub A web server tool for the analysis of transcription factor binding sited in plants [23] PPDB A web-based plant promoter database [24] PlantCARE A database of plant cis-acting regulatory elements, enhancers and repressors [25] OptoBase An online platform for molecular optogenetics [26] TRANSFAC A database on eukaryotic transcription factors [27] RGPDB A database of root-associated genes and promoters in maize, soybean, and sorghum [28] TSSFinder A tool for prediction and annotation of different organisms [29] PlantProm A database of plant promoter sequences [30] TSSP Prediction of plant promoters [31] NSITE-PL Recognition of plant regulatory motifs [32] AGRIS The Arabidopsis gene regulatory information server [33] AthaMap A genome-wide map of putative transcription factor binding sites in Arabidopsis thaliana [34] multiple gene cassettes [61]. Building on the standard Type IIS syntax, jStack leverages in vivo yeast homologous recombination to assemble large DNA fragments, such as multiple gene expression cassettes, into plant transformation vectors by one-pot [62].…”

Section: Standardized Assemblymentioning

confidence: 99%

From qualitative to quantitative: the state of the art and challenges for plant synthetic biology

Tian,

Li,

Wang

2023

Quant. Biol.

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The flourishing plant science promotes the exploding number of data and the expansion of toolkits. Plant synthetic biology is still in its early stages and requires more quantitative and predictable study. Despite the challenges, some pioneering examples have been successfully demonstrated in model plants.BackgroundsAs an increasing number of synthetic switches and circuits have been created for plant systems and of synthetic products produced in plant chassis, plant synthetic biology is taking a strong foothold in agriculture and medicine. The ever‐exploding data has also promoted the expansion of toolkits in this field. Genetic parts libraries and quantitative characterization approaches have been developed. However, plant synthetic biology is still in its infancy. The considerations for selecting biological parts to design and construct genetic circuits with predictable functions remain desired.ResultsIn this article, we review the current biotechnological progresses in field of plant synthetic biology. Assembly standardization and quantitative approaches of genetic parts and genetic circuits are discussed. We also highlight the main challenges in the iterative cycles of design‐build‐test‐learn for introducing novel traits into plants.ConclusionPlant synthetic biology promises to provide important solutions to many issues in agricultural production, human health care, and environmental sustainability. However, tremendous challenges exist in this field. For example, the quantitative characterization of genetic parts is limited; the orthogonality and the transfer functions of circuits are unpredictable; and also, the mathematical modeling‐assisted circuits design still needs to improve predictability and reliability. These challenges are expected to be resolved in the near future as interests in this field are intensifying.

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RGPDB: database of root-associated genes and promoters in maize, soybean, and sorghum

Cited by 11 publications

References 48 publications

Tabula Glycine: The whole-soybean single-cell resolution transcriptome atlas

Tabula Glycine: The whole-soybean single-cell resolution transcriptome atlas

Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model

From qualitative to quantitative: the state of the art and challenges for plant synthetic biology

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