Deep‐sequencing of <i>Solanum commersonii</i> small <scp>RNA</scp> libraries reveals riboregulators involved in cold stress response

Esposito, Salvatore; Aversano, Riccardo; Bradeen, James M.; Matteo, Antonio Di; Villano, Clizia

doi:10.1111/plb.12955

Cited by 23 publications

(14 citation statements)

References 78 publications

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“…Interestingly, two ScWRKYs (ScWRKY010 and ScWRKY002) carried three WDs. This might be the result of the acquisition of a WRKY domain during evolution, supporting findings of Aversano et al 15 and Esposito et al 31,55 , who reported that S. commersonii prosper lineage-specific segmental duplications during evolution. Not only WDs number, but also WDs structural divergences identified in S. commersonii and S. chacoense might be the consequence of mutations during the process of evolution.…”

Section: Structural Analysis Of Scwrkys and Schwrkys Revealed Interspsupporting

confidence: 83%

WRKY genes family study reveals tissue-specific and stress-responsive TFs in wild potato species

Villano

Esposito

D’Amelia

et al. 2020

Sci Rep

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Wild potatoes, as dynamic resource adapted to various environmental conditions, represent a powerful and informative reservoir of genes useful for breeding efforts. WRKY transcription factors (TFs) are encoded by one of the largest families in plants and are involved in several biological processes such as growth and development, signal transduction, and plant defence against stress. In this study, 79 and 84 genes encoding putative WRKY TFs have been identified in two wild potato relatives, Solanum commersonii and S. chacoense. Phylogenetic analysis of WRKY proteins divided ScWRKYs and SchWRKYs into three Groups and seven subGroups. Structural and phylogenetic comparative analyses suggested an interspecific variability of WRKYs. Analysis of gene expression profiles in different tissues and under various stresses allowed to select ScWRKY045 as a good candidate in woundingresponse, ScWRKY055 as a bacterial infection triggered WRKY and ScWRKY023 as a multiple stressresponsive WRKY gene. Those WRKYs were further studied through interactome analysis allowing the identification of potential co-expression relationships between ScWRKYs/SchWRKYs and genes of various pathways. Overall, this study enabled the discrimination of WRKY genes that could be considered as potential candidates in both breeding programs and functional studies.Plants experience environmental constrains and pathogen attacks during their life. Being sessile organisms, their survival depends on the ability to properly and promptly reprogram cellular networks. Several and different classes of transcription factors (TFs) work as "master regulators" and "selector genes", being able to control processes that specify cell types and developmental patterning and modulate specific pathways. Among them, WRKY factors are drawing a great deal of interest in the scientific community due to their ability to simultaneously cope with multiple stresses 1,2 . They are notorious for coordinating signals in plant immunity response against several pathogens and pest attacks 3,4 . More recently, it has been confirmed that WRKYs also base defence mechanism to abiotic stresses and play a key role in cross-talk pathway networks between plant response and development 5,6 . Their involvement into multiple stress response and in plant growth regulation is evidenced by their W-box specific DNA binding 7,8 . Besides, WRKY binds sugar responsive elements and, very recently, it has been demonstrated that they activate sugar responsive genes through an epigenetic mechanism of control 9 . The systematic classification of components of the WRKY family is well organized. It is based on the WRKY binding domain (WD) characteristics along with those of the Zinc Finger (ZF) motif, which is typically present downstream the WD. WD consists of 60 amino acids structured as four-stranded β-sheets able to enter the major groove of B-form DNA. The highly conserved motif is "WRKYGQK". According to the number of WDs and the type of zinc finger motif, WRKY proteins can be classified into three Groups,...

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Section: Structural Analysis Of Scwrkys and Schwrkys Revealed Interspsupporting

confidence: 83%

WRKY genes family study reveals tissue-specific and stress-responsive TFs in wild potato species

Villano

Esposito

D’Amelia

et al. 2020

Sci Rep

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“…The expression profiles of the HMG genes across four different tissues of S. commersonii and S. tuberosum (flower, leaf, root and stolon) were also studied. In particular, raw data for S. commersonii (deposited under the study SRP050412) and S. tuberosum (ERR029909, ERR029910, ERR029914 and ERR029917) were downloaded and analyzed, using Cufflinks-Cuffquant software (version 2.2.1); expression values for each gene were expressed as RPKM (Reads Per Kilobase of transcript per Million mapped reads), as described by Esposito et al [24,31,32].…”

Section: Identification Of Candidate Hmg Genes and Phylogenetic Analysismentioning

confidence: 99%

Genome-Wide HMG Family Investigation and Its Role in Glycoalkaloid Accumulation in Wild Tuber-Bearing Solanum commersonii

Villano

D’Amelia

Esposito³

et al. 2020

Life

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Steroidal glycoalkaloids (SGAs) are a class of nitrogen-containing glycosides occurring in several plant families and biosynthesized through a specific pathway. HMG-CoA reductase is the first enzyme of this pathway, and its transcription can be regulated by biotic and abiotic stressors and even in a tissue-specific manner. This study aimed to characterize the HMG genes family in a tuber-bearing potato species, Solanum commersonii, using transcriptional and functional approaches. Our results provided evidence that four ScHMGs with different tissue-specificities represent the HMG gene family in S. commersonii and that they originated from ScHMG1 through segmental duplications. Phylogenetic analysis suggests that ScHMG1 is the direct ortholog of AtHMG1, which is associated with SGAs accumulation in plants. Its overexpression in S. commersonii revealed that this gene plays a key role in the accumulation of glycoalkaloids regulating the production of dehydrocommersonine.

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“…Since the first discovery of miRNAs, the basic understanding of how gene expression is controlled deeply changed. In the last ten years, studies demonstrated that miRNAs play crucial roles in modulating stress response, including salinity [78], drought [79], waterlogging [80], UV-B radiation and cold stress [81,82], and in several cases their biological role has been clarified. For instance, miR394 and miR397 have been reported to positively regulate cold tolerance via the CBF-dependent pathway [83,84], whereas miR319 activates the CBF regulon and triggers reactive oxygen species (ROS) elimination from the cells [85].…”

Section: Genomics and Machine Learning: A Case Study To Predict Diffementioning

confidence: 99%

Applications and Trends of Machine Learning in Genomics and Phenomics for Next-Generation Breeding

Esposito¹,

Carputo

Cardi³

et al. 2019

Plants

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Crops are the major source of food supply and raw materials for the processing industry. A balance between crop production and food consumption is continually threatened by plant diseases and adverse environmental conditions. This leads to serious losses every year and results in food shortages, particularly in developing countries. Presently, cutting-edge technologies for genome sequencing and phenotyping of crops combined with progress in computational sciences are leading a revolution in plant breeding, boosting the identification of the genetic basis of traits at a precision never reached before. In this frame, machine learning (ML) plays a pivotal role in data-mining and analysis, providing relevant information for decision-making towards achieving breeding targets. To this end, we summarize the recent progress in next-generation sequencing and the role of phenotyping technologies in genomics-assisted breeding toward the exploitation of the natural variation and the identification of target genes. We also explore the application of ML in managing big data and predictive models, reporting a case study using microRNAs (miRNAs) to identify genes related to stress conditions.

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Deep‐sequencing of Solanum commersonii small RNA libraries reveals riboregulators involved in cold stress response

Cited by 23 publications

References 78 publications

WRKY genes family study reveals tissue-specific and stress-responsive TFs in wild potato species

WRKY genes family study reveals tissue-specific and stress-responsive TFs in wild potato species

Genome-Wide HMG Family Investigation and Its Role in Glycoalkaloid Accumulation in Wild Tuber-Bearing Solanum commersonii

Applications and Trends of Machine Learning in Genomics and Phenomics for Next-Generation Breeding

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