These authors contributed equally to this work. SUMMARYMany Actinidia cultivars are characterized by anthocyanin accumulation, specifically in the inner pericarp, but the underlying regulatory mechanism remains elusive. Here we report two interacting transcription factors, AcMYB123 and AcbHLH42, that regulate tissue-specific anthocyanin biosynthesis in the inner pericarp of Actinidia chinensis cv. Hongyang. Through transcriptome profiling analysis we identified five MYB and three bHLH transcription factors that were upregulated in the inner pericarp. We show that the combinatorial action of two of them, AcMYB123 and AcbHLH42, is required for activating promoters of AcANS and AcF3GT1 that encode the dedicated enzymes for anthocyanin biosynthesis. The presence of anthocyanin in the inner pericarp appears to be tightly associated with elevated expression of AcMYB123 and AcbHLH42. RNA interference repression of AcMYB123, AcbHLH42, AcF3GT1 and AcANS in 'Hongyang' fruits resulted in significantly reduced anthocyanin biosynthesis. Using both transient assays in Nicotiana tabacum leaves or Actinidia arguta fruits and stable transformation in Arabidopsis, we demonstrate that co-expression of AcMYB123 and AcbHLH42 is a prerequisite for anthocyanin production by activating transcription of AcF3GT1 and AcANS or the homologous genes. Phylogenetic analysis suggests that AcMYB123 or AcbHLH42 are closely related to TT2 or TT8, respectively, which determines proanthocyanidin biosynthesis in Arabidopsis, and to anthocyanin regulators in monocots rather than regulators in dicots. All these experimental results suggest that AcMYB123 and AcbHLH42 are the components involved in spatiotemporal regulation of anthocyanin biosynthesis specifically in the inner pericarp of kiwifruit.
Background Kiwifruit ( Actinidia spp.) is a dioecious plant with fruits containing abundant vitamin C and minerals. A handful of kiwifruit species have been domesticated, among which Actinidiaeriantha is increasingly favored in breeding owing to its superior commercial traits. Recently, elite cultivars from A. eriantha have been successfully selected and further studies on their biology and breeding potential require genomic information, which is currently unavailable. Findings We assembled a chromosome-scale genome sequence of A. eriantha cultivar White using single-molecular sequencing and chromatin interaction map–based scaffolding. The assembly has a total size of 690.6 megabases and an N50 of 21.7 megabases. Approximately 99% of the assembly were in 29 pseudomolecules corresponding to the 29 kiwifruit chromosomes. Forty-three percent of the A. eriantha genome are repetitive sequences, and the non-repetitive part encodes 42,988 protein-coding genes, of which 39,075 have homologues from other plant species or protein domains. The divergence time between A. eriantha and its close relative Actinidia chinensis is estimated to be 3.3 million years, and after diversification, 1,727 and 1,506 gene families are expanded and contracted in A. eriantha , respectively. Conclusions We provide a high-quality reference genome for kiwifruit A . eriantha . This chromosome-scale genome assembly is substantially better than 2 published kiwifruit assemblies from A . chinensis in terms of genome contiguity and completeness. The availability of the A . eriantha genome provides a valuable resource for facilitating kiwifruit breeding and studies of kiwifruit biology.
BackgroundEarly-onset scoliosis (EOS), defined by an onset age of scoliosis less than 10 years, conveys significant health risk to affected children. Identification of the molecular aetiology underlying patients with EOS could provide valuable information for both clinical management and prenatal screening.MethodsIn this study, we consecutively recruited a cohort of 447 Chinese patients with operative EOS. We performed exome sequencing (ES) screening on these individuals and their available family members (totaling 670 subjects). Another cohort of 13 patients with idiopathic early-onset scoliosis (IEOS) from the USA who underwent ES was also recruited.ResultsAfter ES data processing and variant interpretation, we detected molecular diagnostic variants in 92 out of 447 (20.6%) Chinese patients with EOS, including 8 patients with molecular confirmation of their clinical diagnosis and 84 patients with molecular diagnoses of previously unrecognised diseases underlying scoliosis. One out of 13 patients with IEOS from the US cohort was molecularly diagnosed. The age at presentation, the number of organ systems involved and the Cobb angle were the three top features predictive of a molecular diagnosis.ConclusionES enabled the molecular diagnosis/classification of patients with EOS. Specific clinical features/feature pairs are able to indicate the likelihood of gaining a molecular diagnosis through ES.
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Kiwifruit (Actinidia spp.) plants produce economically important fruits containing abundant, balanced phytonutrients with extraordinarily high vitamin C contents. Since the release of the first kiwifruit reference genome sequence in 2013, large volumes of genome and transcriptome data have been rapidly accumulated for a handful of kiwifruit species. To efficiently store, analyze, integrate, and disseminate these large-scale datasets to the research community, we constructed the Kiwifruit Genome Database (KGD; http://kiwifruitgenome.org/). The database currently contains all publicly available genome and gene sequences, gene annotations, biochemical pathways, transcriptome profiles derived from public RNA-Seq datasets, and comparative genomic analysis results such as syntenic blocks and homologous gene pairs between different kiwifruit genome assemblies. A set of user-friendly query interfaces, analysis tools and visualization modules have been implemented in KGD to facilitate translational and applied research in kiwifruit, which include JBrowse, a popular genome browser, and the NCBI BLAST sequence search tool. Other notable tools developed within KGD include a genome synteny viewer and tools for differential gene expression analysis as well as gene ontology (GO) term and pathway enrichment analysis.
BackgroundAlthough the genetic spectrum of human colorectal cancer (CRC) is mainly characterized by APC, KRAS and TP53 mutations, driver genes in tumor initiation have not been conclusively demonstrated. In this study, we aimed to identify novel markers for CRC.MethodsWe performed exome analysis of sporadic colorectal cancer (sCRC) coding regions to screen loss of function (LoF) mutation genes, and carried out systems-level approaches to confirm top rank gene in this study.ResultsWe identified loss of BMP5 is an early event in CRC. Deep sequencing identified BMP5 was mutated in 7.7% (8/104) of sCRC samples, with 37.5% truncating mutation frequency. Notably, BMP5 negative expression and its prognostic value is uniquely significant in sCRC but not in other tumor types. Furthermore, BMP5 expression was positively correlated with E-cadherin in CRC patients and its dysregulation play a vital role in epithelial-mesenchymal transition (EMT), thus triggering tumor initiation and development. RNA sequencing identified, independent of BMP/Smads pathway, BMP5 signaled though Jak-Stat pathways to inhibit the activation of oncogene EPSTI1.ConclusionsOur result support a novel concept that the importance of BMP5 in sCRC. The tumor suppressor role of BMP5 highlights its crucial role in CRC initiation and development.Electronic supplementary materialThe online version of this article (10.1186/s12943-018-0925-7) contains supplementary material, which is available to authorized users.
Each type of cancer usually has several subtypes with distinct clinical implications, and therefore the discovery of cancer subtypes is an important and urgent task in disease diagnosis and therapy. Using single-omics data to predict cancer subtypes is difficult because genomes are dysregulated and complicated by multiple molecular mechanisms, and therefore linking cancer genomes to cancer phenotypes is not an easy task. Using multi-omics data to effectively predict cancer subtypes is an area of much interest; however, integrating multi-omics data is challenging. Here, we propose a novel method of multi-omics data integration for clustering to identify cancer subtypes (MDICC) that integrates new affinity matrix and network fusion methods. Our experimental results show the effectiveness and generalization of the proposed MDICC model in identifying cancer subtypes, and its performance was better than those of currently available state-of-the-art clustering methods. Furthermore, the survival analysis demonstrates that MDICC delivered comparable or even better results than many typical integrative methods.
Congenital scoliosis (CS) is a birth defect with variable clinical and anatomical manifestations due to spinal malformation. The genetic etiology underlying about 10% of CS cases in the Chinese population is compound inheritance by which the gene dosage is reduced below that of haploinsufficiency. In this genetic model, the trait manifests as a result of the combined effect of a rare variant and common pathogenic variant allele at a locus. From exome sequencing (ES) data of 523 patients
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