Gene families contain genes that come from the same ancestor and have similar sequences and structures. They perform certain specific functions within and among different species. Currently, there is no complete process or platform for the rapid analysis of plant gene families. In this study, a comprehensive query and analysis platform of plant gene families, the Plant Gene Family Platform (PlantGF), was constructed. The platform is composed of four main parts: Search, Tools, Statistics and Auxiliary. A total of 2 909 580 gene family members were identified from 138 plant species in PlantGF. The data can be queried in the Search section through a user-friendly interface. A general process for gene family analysis, having nine steps, is provided. The platform also includes four online tools (HMM-Search, BLAST, MAFFT and HMMER) in the Tools section for useful additional analyses. The statistical analysis of the relevant gene families is shown on the Statistics page. Auxiliary pages are provided for data downloading. The datasets for all 138 plant species’ protein sequences and their gene families can be acquired on the Download page. A user’s manual and some useful links are displayed on the Manual and Links pages, respectively. To the best of our knowledge, PlantGF is the first comprehensive platform for studying plant gene families, and it will make important contributions to plant gene family-related research. Database URL: http://biodb.sdau.edu.cn/PGF/index.html
Nicotiana is one of the most important economic crops and model plants; however, its growth is affected by various biotic and abiotic stresses. In this study, 27,142 potential resistance genes were identified in six Nicotiana species, belonging to fourteen gene families and transcription factors related to stress resistance. The results indicate that Nicotiana has a potential abundance resistance background to biotic and abiotic stress, and these genes could be used in resistance breeding in the future. Analyzing the genome sequences of 19 pathogens, 5,421,414 Single Nucleotide Polymorphisms and 1958 Simple Sequence Repeats of pathogens have been obtained. The abundance loci show that the biotic pathogens have a high variability and biodiversity. An open-access database, named the Nicotiana Resistance Database (NRD), has been developed as a user-friendly resistance research platform for Nicotiana. The platform provides theoretical and technical support for the resistance research, including the cultivation of resistant varieties, and the genetics and breeding of Nicotiana and relative species.
Host-microbiome interaction is known to play a pivotal role in the cancer ecosystem, yet the associations have not been systematically investigated at the pan-cancer and the multi-omics level. Here, we evaluated nearly 10,000 samples across 32 cancer types collected from The Cancer Genome Atlas (TCGA), to investigate the association between the tumor microbiome (taxa, n=1,630) and tumor microenvironment composition (cell types, n=20), epigenome (CpG island methylation, n=30,716), transcriptome (gene expression, n=10,216) and proteome (protein expression, n=193). We identified 836,738 candidate associations between the tumor microbiome and host molecular aberrations across multiple cancers. Besides cancer-specific associations, we also revealed recurrent pan-cancer associations between microbes (Lachnoclostridium, Flammeovirga, Terrabacter and Campylobacter) and immune cells, as well as between microbes (Collimonas and Sutterella) and fibroblasts, which were further validated by cell type estimations derived from pathological images and methylation data. We also identified several potential microbe and gene/protein expression associations mediated by DNA methylation using the sequential mediation analysis. Furthermore, our survival analysis demonstrated that tumor microbes may affect the patient's overall survival and progression-free survival. Finally, a user-friendly web portal, Multi-Omics and Microbiome Associations in Cancer (MOMAC) was constructed for users to explore potential host-microbe interactions in cancer.
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