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Anthocyanins with important physiological functions mainly accumulate in grape berry, but teinturier grape cultivars can accumulate anthocyanins in both reproductive and vegetative tissues. The molecular regulatory mechanisms of anthocyanin biosynthesis in grapevine reproductive and vegetative tissues are different. Therefore, teinturier grapevine cultivar provides opportunities to investigate transcriptional regulation of vegetative anthocyanins, and to compare with mechanisms that regulate grape berry anthocyanins. Yan73 is a teinturier Vitis vinifera variety with vegetative tissues able to accumulate anthocyanins, but the anthocyanin pattern and the molecular mechanism regulating anthocyanin biosynthesis in these tissues remain uncharacterized. We analyzed the anthocyanin metabolic and transcriptome profiles of the vegetative tissues of Yan73 and its male parent with HPLC-ESI-MS/MS and RNA-sequencing technologies. Yan73 vegetative tissues had relatively high 3'-OH, acylated, and methoxylated anthocyanins. Furthermore, peonidin-3-O-(trans-6-coumaryl)-glucoside is the most abundant anthocyanin in Yan73 grapevine vegetative tissues. A total of 30,17 and 10 anthocyanin biosynthesis genes showed up-regulated expression in Yan73 leaf, stem and tendril, respectively, indicating anthocyanin biosynthesis in Yan73 vegetative tissues is regulated by transcription factors. The up-regulated expression of VvMYBA1 on chromosome 2 and VvMYBA5, VvMYBA6, and VvMYBA7 on chromosome 14 are responsible for the anthocyanin patterns of Yan73 vegetative tissues. The expression of a set of R2R3-MYB C2 repressor genes is activated and may negatively regulate anthocyanin biosynthesis in Yan73 vegetative tissues. These findings enhance our understanding of anthocyanin biosynthesis in grapevine.
Pubmed ID: 32457776 RIS Download
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A database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
View all literature mentionsTool for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs). Compared to BLAST, FASTA, and other sequence alignment and database search tools based on older scoring methodology, HMMER aims to be significantly more accurate and more able to detect remote homologs because of the strength of its underlying mathematical models. In the past, this strength came at significant computational expense, but in the new HMMER3 project, HMMER is now essentially as fast as BLAST.
View all literature mentionsMultiple sequence alignment method with reduced time and space complexity.Multiple sequence alignment with high accuracy and high throughput. Data analysis service for multiple sequence comparison by log- expectation.
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