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BnaSNPDB: SNP Database of Brasssica napus L.

The SNP database of Brassica napus L. (BnaSNPDB) is an interactive web-based platform and set of analytic tools for effcient retrieve and analysis of SNPs among 1007 rapeseed germplasm accessions based on the data reported by previous research( Wu et al., 2019 ).

Tutorial of BnaSNPDB

To facilitate user access to BnaSNPDB, we create a short and informative tutorial video for the learning purpose. User can click How to use the BnaSNPDB (video from YouTube) or How to use the BnaSNPDB (video from Bilibili) to watch the video.

What's Inside

High Quality SNPs

Germplasm Collections

Countries

Winter Ecotypes

Semi-winter Ecotypes

Spring Ecotypes

Analysis Modules

We here present 5 modules to retrieve and analyze the SNP dataset. Within each module, the user can select different parameters to retrieve and analyze the SNP dataset. You can find some example figures that these modules can generate in the manuscript Wu et al. Whole-Genome Resequencing of a Worldwide Collection of Rapeseed Accessions Reveals the Genetic Basis of Ecotype Divergence, Molecular Plant (2019) and manuscript Xuan et al. Genome-wide association study reveals new genes involved in leaf trichome formation in polyploid oilseed rape (Brassica napus L.), Plant, Cell & Environment (2019).

LDheatmap

This module provides a pipeline to retrieve SNPs and display pairwise linkage disequilibria between SNPs and allows the user select different parameters.

SNP Distribution

This module compares the conserved SNPs specific to different groups of rapeseed.

Phylogenetic

This module implements the functionality to perform phylogenetic analysis in user-specified genomic regions.

Diversity

This module provides the functionality to calculate nucleotide diversity among groups of rapeseed germplasm accessions in user-specified genomic regions.

Extraction

This module allows user to extract the detail informations of SNPs, annotation of genes and essential information on the 1007 rapeseed germplasm accessions used in the BnaSNPDB.

More about of the SNP Dataset

Exploring the rapeseed (Brassica napus L.) genomic variation dataset

 

Rapeseed (Brassica napus L.), an important oilseed crop, has adapted to diverse climate zones and latitudes by forming three main ecotype groups, namely winyer, semi-winter, and spring types. In this database, We collected a worldwide collection of 1,007 B .napus germplasms accessions, including 658 winetr types, 145 semi-winter types, and 188 spring types, from 39 countries (Fig. 1).

 

Fig. 1 The geographic distribution of rapeseed accessions

We generated a total of 7.82 Tb of clean reads from whole-genome resequencing of the world collection from 39 countries across the world with an average of ~6.6-fold-coverage. We used the following pipeline (Fig. 2) to process the data:

 

Fig. 2 The pipeline for data processing procedures

  1. All raw paired-end reads were trimmed for quality control using Trimmomatic
  2. The remaining high-quality reads were aligned to the genome of Darmor-bzh with BWA software
  3. BAM alignments files were sorted and duplicated reads were marked subsequently generated with SAMtools and Picard
  4. SNPs were identified and filtering using GATK. SNPs annotation was performed using SnpEFF software.

 

Finally, 5.56 million SNPs were detected. The distribution of polymorphisms in B. napus genomic regions showed that 202,323, 62,834, 939,553, 899,982, and 2,778,189 SNPs were located within exons, introns, and upstream regions (within 5 kb upstream of transcription start sites), downstream regions (within 5 kb downstream of transcription stop sites), and intergenic regions, respectively (Fig. 3).

 

Fig. 3 The distribution of polymorphisms in B. napus genomic regions

LDheatmap:

Download LDheadmap


SNP Informations:

ref: reference allele - The reference allele is whatever is found in the reference genome.
alt: alternative allele - The alternative allele is the allele found in the sample.
major: major allele, is the common allele with high frequency.
minor: minor allele, is the less common allele with lower frequency.
Download SNP Data



SNPdistribution:

Download SNPdistribution


SNP Informations:

ref: reference allele - The reference allele is whatever is found in the reference genome.
alt: alternative allele - The alternative allele is the allele found in the sample.
major: major allele, is the common allele with high frequency.
minor: minor allele, is the less common allele with lower frequency.
Download SNP Data



Phylogenetic Tree:

Download Phylogenetics tree


SNP Informations:

ref: reference allele - The reference allele is whatever is found in the reference genome.
alt: alternative allele - The alternative allele is the allele found in the sample.
major: major allele, is the common allele with high frequency.
minor: minorr allele, is the less common allele with lower frequency.
Download SNP Data



Diversity Plot:


Download Diversity Plot


Allele Informations (Major/Minor):

ref: reference allele - The reference allele is whatever is found in the reference genome.
alt: alternative allele - The alternative allele is the allele found in the sample.
major: major allele, is the common allele with high frequency.
minor: monir allele, is the less common allele with lower frequency.
Download Allele Data



SNP data:

ref: reference allele - The reference allele is whatever is found in the reference genome.
alt: alternative allele - The alternative allele is the allele found in the sample.
major: major allele, is the common allele with high frequency.
minor: minor allele, is the less common allele with lower frequency.
Download SNP Data

Gene annotation:


Download Genes Informations



Geographic distribution:


Download Geographic distribution

Accession Info:


Download Accession Informations



BnaSNPDB: SNP Database of Brassica napus L.

 

Overview

The SNP database of Brassica napus L. (BnaSNPDB) is an interactive web portal that provides multiple analysis modules to explore and visualize SNPs among 1,007 rapeseed germplasm accessions based on the data reported by previous research (Wu et al., 2019). The app is deployed at https://bnapus-zju.com/bnasnpdb for online use.

BnaSNPDB is idle until you activate it. So it may take some time to load for the first time. Once it was activated, BnaSNPDB could be used smoothly and easily.

The portal is built entirely in R and Shiny using the RStudio development environment.

Install

Requirements

Initialize app

To run the app locally:

1.Clone this repository

git clone https://github.com/YTLogos/BnaSNPDB.git

The repository is large so it may need some time to finish it.

2.Open BnaSNPDB.Rproj

3.Install packages. In the RStudio console, run:

# try an http CRAN (Bioc) mirror if https CRAN (Bioc) mirror doesn't work
# First install Bioconductor
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install(version = "3.11")

BiocManager::install("shiny")
BiocManager::install("ggplot2")
BiocManager::install("stringr")
BiocManager::install("dplyr")
BiocManager::install("tidyr")
BiocManager::install("forcats")
BiocManager::install("patchwork")
BiocManager::install("glue")
BiocManager::install("ggpubr")
BiocManager::install("writexl")
BiocManager::install("snpStats")
BiocManager::install("IRanges")
BiocManager::install("LDheatmap")
BiocManager::install("ape")
BiocManager::install("pegas")
BiocManager::install("gridExtra")
BiocManager::install("grid")
BiocManager::install("ggtree")
BiocManager::install("shinycssloaders")
BiocManager::install("shinydashboard")
BiocManager::install("shinydisconnect")
BiocManager::install("shinyWidgets")
BiocManager::install("gggenes")
BiocManager::install("DT")
BiocManager::install("shinythemes")
BiocManager::install("NAM")
BiocManager::install("adegenet")

if (require(devtools)) install.packages("devtools")#if not already installed
devtools::install_github("AnalytixWare/ShinySky")

This may take some time to complete - walk away from your computer, rest your eyes, and catch up on those stretching exercises you are meant to be doing :)

4.Start tha app by running

shiny::runApp(launch.browser = TRUE)

Deploy BnaSNPDB on web Linux server

1.Clone/Upload this repository into /srv/shiny-server

$ cd /srv/shiny-server
git clone https://github.com/YTLogos/BnaSNPDB.git
# Or clone it locally and upload the directory to /srv/shiny-server using scp or other tools

2.Configure Shiny Server (/etc/shiny-server/shiny-server.conf)

# Instruct Shiny Server to run applications as the user "shiny"
preserve_logs true;
sanitize_errors false;
run_as shiny;

# Define a server that listens on port 3838
server {
  listen 3838;

  # Define a location at the base URL
  location / {

    # Host the directory of Shiny Apps stored in this directory
    site_dir /srv/shiny-server;

    # Log all Shiny output to files in this directory
    log_dir /var/log/shiny-server;

    # When a user visits the base URL rather than a particular application,
    # an index of the applications available in this directory will be shown.
    directory_index on;
  }
}

3.Change the owner of the BnaSNPDB directory

$ chown -R shiny /srv/shiny-server/BnaSNPDB

4.Start Shiny-Server

$ start shiny-server

Now you can access the BnaSNPDB app at http://IPAddressOfYourServer:3838/BnaSNPDB.

About this app

This app (BnaSNPDB) has been built by Tao Yan. It’s based on the genomic dataset reported by previous research (Wu et al., 2019).

The current release of BnaSNPDB contains 2,404,340 high-quality SNPs and provides set of analytic tools for efficient retrieve and analysis of SNPs across 1,007 accessions (658 winter ecotypes, 145 semi-winter ecotypes and 188 spring ecotypes) of worldwide rapeseed germplasm.

Citation

Yan, T., Wang, Q., Maodzeka, A., Wu, D., and Jiang, L. (2020) BnaSNPDB: An interactive web portal for the efficient retrieval and analysis of SNPs among 1,007 rapeseed accessions. Computational and Structural Biotechnology Journal, 18, 2766–2773. https://doi.org/10.1016/j.csbj.2020.09.031

Analysis Modules

We here present 5 modules to retrieve and analyze the SNP dataset. Within each module, the user can select different parameters to retrieve and analyze the SNP dataset. You can find some example figures that these modules can generate in the manuscript Wu et al. and Xuan et al.

LDheatmap

This module provides a pipeline to retrieve SNPs and display pairwise linkage disequilibria between SNPs and allows the user select different parameters.

SNP Distribution

This module compares the conserved SNPs specific to different groups of rapeseed.

Phylogenetic

This module implements the functionality to perform phylogenetic analysis in user-specified genomic regions.

Diversity

This module provides the functionality to calculate nucleotide diversity among groups of rapeseed germplasm accessions in user-specified genomic regions.

Extraction

This module allows user to extract the detail informations of SNPs, annotation of genes and essential information on the 1,007 rapeseed germplasm accessions used in the BnaSNPDB.

     

Tech used in this app

Browse the full source code at https://github.com/YTLogos/BnaSNPDB.

Packages used in this app