ArticleBMC genomics2014
SFGD: a comprehensive platform for mining functional information from soybean transcriptome data and its use in identifying acyl-lipid metabolism pathways.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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28 citing papers in PubMed, 48 citations in OpenAlex.
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- New insights into Arabidopsis transcriptome complexity revealed by direct sequencing of native RNAs.Nucleic acids research · 2020Article
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- Homeostasis in the soybean miRNA396-GRF network is essential for productive soybean cyst nematode infections.Journal of experimental botany · 2019Article
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- An integrated omics analysis reveals molecular mechanisms that are associated with differences in seed oil content between Glycine max and Brassica napus.BMC plant biology · 2018Article
- Soybean (Glycine max) WRINKLED1 transcription factor, GmWRI1a, positively regulates seed oil accumulation.Molecular genetics and genomics : MGG · 2018Article
- PCSD: a plant chromatin state database.Nucleic acids research · 2018Article
- Co-expression Gene Network Analysis and Functional Module Identification in Bamboo Growth and Development.Frontiers in genetics · 2018Article
- PlantEAR: Functional Analysis Platform for Plant EAR Motif-Containing Proteins.Frontiers in genetics · 2018Article
- Genome-wide mapping of DNase I hypersensitive sites reveals chromatin accessibility changes in Arabidopsis euchromatin and heterochromatin regions under extended darkness.Scientific reports · 2017Article
- Integration of omics approaches to understand oil/protein content during seed development in oilseed crops.Plant cell reports · 2017Review
- Selection for a Zinc-Finger Protein Contributes to Seed Oil Increase during Soybean Domestication.Plant physiology · 2017Article
- ccNET: Database of co-expression networks with functional modules for diploid and polyploid Gossypium.Nucleic acids research · 2017Article
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Authors and funding
6 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSoybean (Glycine max L.) is one of the world's most important leguminous crops producing high-quality protein and oil. Increasing the relative oil concentration in soybean seeds is many researchers' goal, but a complete analysis platform of functional annotation for the genes involved in the soybean acyl-lipid pathway is still lacking. Following the success of soybean whole-genome sequencing, functional annotation has become a major challenge for the scientific community. Whole-genome transcriptome analysis is a powerful way to predict genes with biological functions. It is essential to build a comprehensive analysis platform for integrating soybean whole-genome sequencing data, the available transcriptome data and protein information. This platform could also be used to identify acyl-lipid metabolism pathways. DESCRIPTION: In this study, we describe our construction of the Soybean Functional Genomics Database (SFGD) using Generic Genome Browser (Gbrowse) as the core platform. We integrated microarray expression profiling with 255 samples from 14 groups' experiments and mRNA-seq data with 30 samples from four groups' experiments, including spatial and temporal transcriptome data for different soybean development stages and environmental stresses. The SFGD includes a gene co-expression regulatory network containing 23,267 genes and 1873 miRNA-target pairs, and a group of acyl-lipid pathways containing 221 enzymes and more than 1550 genes. The SFGD also provides some key analysis tools, i.e. BLAST search, expression pattern search and cis-element significance analysis, as well as gene ontology information search and single nucleotide polymorphism display.
conclusionThe SFGD is a comprehensive database integrating genome and transcriptome data, and also for soybean acyl-lipid metabolism pathways. It provides useful toolboxes for biologists to improve the accuracy and robustness of soybean functional genomics analysis, further improving understanding of gene regulatory networks for effective crop improvement. The SFGD is publically accessible at http://bioinformatics.cau.edu.cn/SFGD/, with all data available for downloading.
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