Background: Transcriptomics is being increasingly applied to generate new insight into the interactions between plants and their pathogens. For the wheat yellow (stripe) rust pathogen (Puccinia striiformis f. sp. tritici, Pst) RNA-based sequencing (RNA-Seq) has proved particularly valuable, overcoming the barriers associated with its obligate biotrophic nature. This includes the application of RNA-Seq approaches to study Pst and wheat gene expression dynamics over time and the Pst population composition through the use of a novel RNA-Seq based surveillance approach called "field pathogenomics". As a dual RNA-Seq approach, the field pathogenomics technique also provides gene expression data from the host, giving new insight into host responses. However, this has created a wealth of data for interrogation.
Results: Here, we used the field pathogenomics approach to generate 538 new RNA-Seq datasets from Pst-infected field wheat samples, doubling the amount of transcriptomics data available for this important pathosystem. We then analysed these datasets alongside 66 RNA-Seq datasets from four Pst infection time-courses and 420 Pst-infected plant field and laboratory samples that were publicly available. A database of gene expression values for Pst and wheat was generated for each of these 1024 RNA-Seq datasets and incorporated into the development of the rust expression browser ( http://www.rust-expression.com ). This enables for the first time simultaneous 'point-and-click' access to gene expression profiles for Pst and its wheat host and represents the largest database of processed RNA-Seq datasets available for any of the three Puccinia wheat rust pathogens. We also demonstrated the utility of the browser through investigation of expression of putative Pst virulence genes over time and examined the host plants response to Pst infection.
Conclusions: The rust expression browser offers immense value to the wider community, facilitating data sharing and transparency and the underlying database can be continually expanded as more datasets become publicly available.
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http://dx.doi.org/10.1186/s12864-021-07488-3 | DOI Listing |
Plant Signal Behav
December 2025
School of Medical Technology, Chongqing Three Gorges Medical College, Chongqing, China.
The most damaging disease affecting citrus globally is Huanglongbing (HLB), primarily attributed to the infection by ' asiaticus' (Las). Based on comparative transcriptome data, two cellulose synthase (CESA) genes responsive to Las infection induction were screened, and one gene cloned with higher differential expression level was selected and named . we verified the interaction between CsCESA1 and citrus exopolysaccharide 2 (CsEPS2) proteins.
View Article and Find Full Text PDFElife
December 2024
Howard Hughes Medical Institute, Stanford University, Stanford, United States.
Defining the cellular factors that drive growth rate and proteome composition is essential for understanding and manipulating cellular systems. In bacteria, ribosome concentration is known to be a constraining factor of cell growth rate, while gene concentration is usually assumed not to be limiting. Here, using single-molecule tracking, quantitative single-cell microscopy, and modeling, we show that genome dilution in cells arrested for DNA replication limits total RNA polymerase activity within physiological cell sizes across tested nutrient conditions.
View Article and Find Full Text PDFCell Oncol (Dordr)
December 2024
Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
Purpose: Renal cell carcinoma (RCC), exhibiting remarkable heterogeneity, can be highly infiltrated by regulatory T cells (Tregs). However, the relationship between Treg and the heterogeneity of RCC remains to be explored.
Methods: We acquired single-cell RNA-seq profiles and 537 bulk RNA-seq profiles of TCGA-KIRC cohort.
Discov Oncol
December 2024
School of Clinical Medicine, Dali University, Dali, 671000, Yunnan, People's Republic of China.
Objective: Searching for potential biomarkers and therapeutic targets for early diagnosis of gynecological tumors to improve patient survival.
Methods: Microarray datasets of cervical cancer (CC) and ovarian cancer (OC) were downloaded from the Gene Expression Omnibus (GEO) database, then, differential gene expression between cancerous and normal tissues in the datasets was analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to screen for co-expression modules associated with CC and OC.
Discov Oncol
December 2024
Department of Neurosurgery, West China Hospital of Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, China.
Background: Gliomas, particularly glioblastoma (GBM), are the most common and aggressive primary brain tumors in adults, characterized by high malignancy and frequent recurrence. Despite standard treatments, including surgery, radiotherapy, and chemotherapy, the prognosis for GBM remains poor, with a median survival of less than 15 months and a five-year survival rate below 10%. Tumor heterogeneity and resistance to treatment create significant challenges in controlling glioma progression.
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