scholarly journals In Silico Identification of MYB and bHLH Families Reveals Candidate Transcription Factors for Secondary Metabolic Pathways in Cannabis sativa L.

Plants ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1540
Author(s):  
Laura Bassolino ◽  
Matteo Buti ◽  
Flavia Fulvio ◽  
Alessandro Pennesi ◽  
Giuseppe Mandolino ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Metabolic Pathways ◽  
Cannabis Sativa ◽  
Scale Up ◽  
Candidate Gene Approach ◽  
Main Role ◽  
Genome Wide ◽  
Comprehensive Knowledge ◽  
Genomic Studies ◽  
Comparative Phylogenetic Analysis

Plant secondary metabolic pathways are finely regulated by the activity of transcription factors, among which members of the bHLH and MYB subfamilies play a main role. Cannabis sativa L. is a unique officinal plant species with over 600 synthesized phytochemicals having diverse scale-up industrial and pharmaceutical usage. Despite comprehensive knowledge of cannabinoids’ metabolic pathways, very little is known about their regulation, while the literature on flavonoids’ metabolic pathways is still scarce. In this study, we provide the first genome-wide analysis of bHLH and MYB families in C. sativa reference cultivar CBDRx and identification of candidate coding sequences for these transcription factors. Cannabis sativa bHLHs and MYBs were then classified into functional subfamilies through comparative phylogenetic analysis with A. thaliana transcription factors. Analyses of gene structure and motif distribution confirmed that CsbHLHs and CsMYBs belonging to the same evolutionary clade share common features at both gene and amino acidic level. Candidate regulatory genes for key metabolic pathways leading to flavonoid and cannabinoid synthesis in Cannabis were also retrieved. Furthermore, a candidate gene approach was used to identify structural enzyme-coding genes for flavonoid and cannabinoid synthesis. Taken as a whole, this work represents a valuable resource of candidate genes for further investigation of the C. sativa cannabinoid and flavonoid metabolic pathways for genomic studies and breeding programs.

scholarly journals In silico identification of MYB and bHLH families reveals candidate transcription factors for secondary metabolic pathways in Cannabis sativa L.

2020 ◽  
Author(s):  
Laura Bassolino ◽  
Matteo Buti ◽  
Flavia Fulvio ◽  
Alessandro Pennesi ◽  
Giuseppe Mandolino ◽  
...  
Keyword(s):  
Transcription Factors ◽  
In Silico ◽  
Metabolic Pathways ◽  
Cannabis Sativa

scholarly journals Beyond the biosynthetic gene cluster paradigm: Genome-wide co-expression networks connect clustered and unclustered transcription factors to secondary metabolic pathways

2020 ◽  
Author(s):  
Min Jin Kwon ◽  
Charlotte Steiniger ◽  
Timothy C. Cairns ◽  
Jennifer H. Wisecaver ◽  
Abigail Lind ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Aspergillus Niger ◽  
Secondary Metabolites ◽  
Metabolic Pathways ◽  
Correlation Coefficients ◽  
Genetic Networks ◽  
Cell Factory ◽  
Biosynthetic Gene ◽  
Genome Wide ◽  
Novel Drug

AbstractFungal secondary metabolites are widely used as therapeutics and are vital components of drug discovery programs. A major challenge hindering discovery of novel secondary metabolites is that the underlying pathways involved in their biosynthesis are transcriptionally silent in typical laboratory growth conditions, making it difficult to identify the transcriptional networks that they are embedded in. Furthermore, while the genes participating in secondary metabolic pathways are typically found in contiguous clusters on the genome, known as biosynthetic gene clusters (BGCs), this is not always the case, especially for global and pathway-specific regulators of pathways’ activities. To address these challenges, we used 283 genome-wide gene expression datasets of the ascomycete cell factory Aspergillus niger generated during growth under 155 different conditions to construct two gene co-expression networks based on Spearman’s correlation coefficients (SCC) and on mutual rank-transformed Pearson’s correlation coefficients (MR-PCC). By mining these networks, we predicted six transcription factors named MjkA – MjkF to concomitantly regulate secondary metabolism in A. niger. Over-expression of each transcription factor using the Tet-on cassette modulated production of multiple secondary metabolites. We found that the SCC and MR-PCC approaches complemented each other, enabling the delineation of global (SCC) and pathway-specific (MR-PCC) transcription factors, respectively. These results highlight the great potential of co-expression network approaches to identify and activate fungal secondary metabolic pathways and their products. More broadly, we argue that novel drug discovery programs in fungi should move beyond the BGC paradigm and focus on understanding the global regulatory networks in which secondary metabolic pathways are embedded.ImportanceThere is an urgent need for novel bioactive molecules in both agriculture and medicine. The genomes of fungi are thought to contain vast numbers of metabolic pathways involved in the biosynthesis of secondary metabolites with diverse bioactivities. Because these metabolites are biosynthesized only under specific conditions, the vast majority of fungal pharmacopeia awaits discovery. To discover the genetic networks that regulate the activity of secondary metabolites, we examined the genome-wide profiles of gene activity of the cell factory Aspergillus niger across hundreds of conditions. By constructing global networks that link genes with similar activities across conditions, we identified six global and pathway-specific regulators of secondary metabolite biosynthesis. Our study shows that elucidating the behavior of the genetic networks of fungi under diverse conditions harbors enormous promise for understanding fungal secondary metabolism, which ultimately may lead to novel drug candidates.

scholarly journals Beyond the Biosynthetic Gene Cluster Paradigm: Genome-Wide Coexpression Networks Connect Clustered and Unclustered Transcription Factors to Secondary Metabolic Pathways

2021 ◽  
Author(s):  
Min Jin Kwon ◽  
Charlotte Steiniger ◽  
Timothy C. Cairns ◽  
Jennifer H. Wisecaver ◽  
Abigail L. Lind ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Secondary Metabolites ◽  
Gene Cluster ◽  
Metabolic Pathways ◽  
Biosynthetic Gene Cluster ◽  
Bioactive Molecules ◽  
Biosynthetic Gene ◽  
Genome Wide ◽  
Coexpression Networks

There is an urgent need for novel bioactive molecules in both agriculture and medicine. The genomes of fungi are thought to contain vast numbers of metabolic pathways involved in the biosynthesis of secondary metabolites with diverse bioactivities.

Migraine: Genetic Variants and Clinical Phenotypes

2019 ◽  
Vol 26 (34) ◽  
pp. 6207-6221 ◽  
Author(s):  
Innocenzo Rainero ◽  
Alessandro Vacca ◽  
Flora Govone ◽  
Annalisa Gai ◽  
Lorenzo Pinessi ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Mthfr Gene ◽  
Genome Wide Association Studies ◽  
Clinical Phenotypes ◽  
Network Analyses ◽  
Genome Wide ◽  
Genomic Studies ◽  
The Common ◽  
The Relationship

Migraine is a common, chronic neurovascular disorder caused by a complex interaction between genetic and environmental risk factors. In the last two decades, molecular genetics of migraine have been intensively investigated. In a few cases, migraine is transmitted as a monogenic disorder, and the disease phenotype cosegregates with mutations in different genes like CACNA1A, ATP1A2, SCN1A, KCNK18, and NOTCH3. In the common forms of migraine, candidate genes as well as genome-wide association studies have shown that a large number of genetic variants may increase the risk of developing migraine. At present, few studies investigated the genotype-phenotype correlation in patients with migraine. The purpose of this review was to discuss recent studies investigating the relationship between different genetic variants and the clinical characteristics of migraine. Analysis of genotype-phenotype correlations in migraineurs is complicated by several confounding factors and, to date, only polymorphisms of the MTHFR gene have been shown to have an effect on migraine phenotype. Additional genomic studies and network analyses are needed to clarify the complex pathways underlying migraine and its clinical phenotypes.

scholarly journals Dynamic histone acetylation in floral volatile synthesis and emission in petunia flowers

2021 ◽  
Author(s):  
Ryan M Patrick ◽  
Xing-Qi Huang ◽  
Natalia Dudareva ◽  
Ying Li
Keyword(s):  
Transcriptional Activation ◽  
Metabolic Pathways ◽  
Transcriptional Repression ◽  
Metabolic Networks ◽  
Underlying Mechanism ◽  
Expression Of Genes ◽  
Genome Wide ◽  
Chemical Inhibitors ◽  
Volatile Organic ◽  
Floral Volatile

Abstract Biosynthesis of secondary metabolites relies on primary metabolic pathways to provide precursors, energy, and cofactors, thus requiring coordinated regulation of primary and secondary metabolic networks. However, to date, it remains largely unknown how this coordination is achieved. Using Petunia hybrida flowers, which emit high levels of phenylpropanoid/benzenoid volatile organic compounds (VOCs), we uncovered genome-wide dynamic deposition of histone H3 lysine 9 acetylation (H3K9ac) during anthesis as an underlying mechanism to coordinate primary and secondary metabolic networks. The observed epigenome reprogramming is accompanied by transcriptional activation at gene loci involved in primary metabolic pathways that provide precursor phenylalanine, as well as secondary metabolic pathways to produce volatile compounds. We also observed transcriptional repression among genes involved in alternative phenylpropanoid branches that compete for metabolic precursors. We show that GNAT family histone acetyltransferase(s) (HATs) are required for the expression of genes involved in VOC biosynthesis and emission, by using chemical inhibitors of HATs, and by knocking down a specific HAT gene, ELP3, through transient RNAi. Together, our study supports that regulatory mechanisms at chromatin level may play an essential role in activating primary and secondary metabolic pathways to regulate VOC synthesis in petunia flowers.

Cold Sweetening in Diploid Potato: Mapping Quantitative Trait Loci and Candidate Genes

Genetics ◽  
2002 ◽  
Vol 162 (3) ◽  
pp. 1423-1434
Author(s):  
Cristina M Menéndez ◽  
Enrique Ritter ◽  
Ralf Schäfer-Pregl ◽  
Birgit Walkemeier ◽  
Alexandra Kalde ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Cold Storage ◽  
Quantitative Trait ◽  
Metabolic Pathways ◽  
Sugar Content ◽  
Candidate Gene Approach ◽  
Diploid Potato ◽  
Glucose Content ◽  
Gene Markers ◽  
Cold Sweetening

Abstract A candidate gene approach has been used as a first step to identify the molecular basis of quantitative trait variation in potato. Sugar content of tubers upon cold storage was the model trait chosen because the metabolic pathways involved in starch and sugar metabolism are well known and many of the genes have been cloned. Tubers of two F1 populations of diploid potato grown in six environments were evaluated for sugar content after cold storage. The populations were genotyped with RFLP, AFLP, and candidate gene markers. QTL analysis revealed that QTL for glucose, fructose, and sucrose content were located on all potato chromosomes. Most QTL for glucose content mapped to the same positions as QTL for fructose content. QTL explaining >10% of the variability for reducing sugars were located on linkage groups I, III, VII, VIII, IX, and XI. QTL consistent across populations and/or environments were identified. QTL were linked to genes encoding invertase, sucrose synthase 3, sucrose phosphate synthase, ADP-glucose pyrophosphorylase, sucrose transporter 1, and a putative sucrose sensor. The results suggest that allelic variants of enzymes operating in carbohydrate metabolic pathways contribute to the genetic variation in cold sweetening.

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