Students:
- Kuznetsov Stepan
- Fofanov Mikhail
- Suponin Andrey
Supervisor:
- Kasyanov Artem, IITP RAS
Currently, there are a large number of ways to annotate genetic variants and various databases containing results of variant calling from different experiments. Here, we used the OpenCRAVAT pipeline able to annotate SNPs and other genetic variants using more than 150 databases and added a novel module to it that contains ADASTRA database. The ADASTRA database contains information about allele-specific transcription factor binding events. A Transcription Factor (TF) might prefer to bind one of two alternative alleles of homologous chromosomes and thus exhibit allele-specific binding (ASB). ASB highlights regulatory SNPs with high potential to affect gene expression.
This project has been tested using the following software:
| Feature | Version |
|---|---|
| Operating system | Ubuntu 20.04 |
| Python | Python 3.9 |
| OpenCRAVAT | open-cravat 2.2.7 |
| ADASTRA database | ADASTRA v4.0 |
You can install the versions of the python libraries that were used during the testing of the pipeline using the requirements.txt:
pip install -r requirements.txt
Adastra annotator source code and config, describes input and output interfaces between an annotator and rest of OpenCravat.
adastra/
|───adastra.md
|───adastra.yml
└───adastra.py
Adastra widget source code and config:
wgadastra/
|───wgadastra.yml
└───wgadastra.js
For more information on development, see https://open-cravat.readthedocs.io/en/latest/Developer-onboarding.html
Cloning the OpenCravat-Adastra github repository and install requirements.
git clone https://github.com/gottalottarock/OpenCravat-Adastra.git
cd OpenCravat-Adastra
pip install -r requirements.txt
To download the Adastra database, you need to contact developer of this repository: stepan.v.kuznetsov@phystech.edu
Move adastra.sqlite to adastra/data
Next, you need to transfer the module and widget to the open-cravat repo.
OC_MODULES_PATH=$(oc config md)
cp -r ./OpenCravat-Adastra/adastra/ $OC_MODULES_PATH/annotators/
cp -r ./OpenCravat-Adastra/wgadastra/ $OC_MODULES_PATH/webviewerwidgets/
NOTE:
Make sure you can open adastra.slick and select the contents of the tables,
otherwise you need to fix permissions.
To check if the module is working properly you can use the following command:
oc util test -m adastra
Run OpenCRAVAT pipeline with a novel ADASTRA annotator module
oc run input.vcf -a adastra -l hg38
Open the results from OpenCRAVAT pipeline with a novel ADASTRA annotator module in browser
oc gui input.vcf.sqlite
Test files (both positive and negative) are located in the directory ./test/
Background Allelic Dosage (BAD) is the expected ratio of major to minor allelic frequencies in a particular genomic region. For example, if a copy number of two alternating alleles is the same (e.g. 1:1 (diploid), 2:2, or 3:3), then the respective region has BAD=1, i.e. the expected ratio of reads mapped to alternative alleles on heterozygous SNVs is 1. All triploid regions have BAD=2 and the expected allelic read ratio is either 2 or ½. In general, if BAD of a particular region is known, then the expected frequencies of allelic reads are 1/(BAD +1) and BAD/(BAD + 1). ASB significance (FDR)
ASB stands for Allele-Specific Binding. A Transcription Factor (TF) might prefer to bind one of two alternative alleles of homologous chromosomes and thus exhibit allele-specific binding. ASB highlights regulatory SNPs with high potential to affect gene expression.
Allele-Specific Binding
The alignment of the motif relative to the SNP is shown at the top. Motif P-values indicate the predicted binding specificities for the alternative alleles. The preferred allele according to ADASTRA data along with the ASB FDR and Effect Size is shown at the bottom. The higher bell corresponds to the allele preferentially bound by the TF in vivo according to the underlying ChIP-Seq data. The DNA strand/orientation is marked in the bottom left corner.
The Effect Size of an ASB event is calculated separately for Reference and Alternative alleles and is defined as the weighted mean of log-ratios of observed and expected allelic read counts, with weights being -log10 of the respective P-values.
Motif Concordance indicates whether the allelic read imbalance is consistent with the transcription factor motif Fold Change (FC, predicted from sequence analysis). The following notation is used:
- n/a: Motif is not available;
- No hit: The best hit P-value is higher than 0.0005 threshold;
- Weak concordant: The absolute value of FC is less than 2 but consistent with the allelic read imbalance;
- Weak discordant: The absolute value of FC is less than 2 and not consistent with the allelic read imbalance;
- Concordant: The absolute value of FC is greater or equal to 2 and consistent with allelic read imbalance;
- Discordant: The absolute value of FC is greater or equal to 2 but not consistent with allelic read imbalance.
For more information please visit: Link or Link
Here, we integrated the ADASTRA database as a novel annotator module in the OpenCRAVAT pipeline and presentad its installation and usage details in this README file. This is a crucial improvement of the OpenCRAVAT, since the vast majority of the other more than 150 databases integrated into this pipeline were designed for variant calling from the human genome coding regions of protein-coding genes, while an ADASTRA database contains information about biologically significant genetic variants, located in its gene regulatory non-coding regions such as enhancers and promoters. Now, everyone can get an ADASTRA database directly from its authors or from open sources (depending on the database creators decision) and use it for annotation of allele-specific transcription factor binding events in his own VCF file using OpenCRAVAT pipeline.
Sergey Abramov, Alexandr Boytsov, Dariia Bykova, Dmitry D. Penzar, Ivan Yevshin, Semyon K. Kolmykov, Marina V. Fridman, Alexander V. Favorov, Ilya E. Vorontsov, Eugene Baulin, Fedor Kolpakov, Vsevolod J. Makeev, Ivan V. Kulakovskiy. Nature communications, 2021. doi: 10.1038/s41467-021-23007-0
ANANASTRA: annotation and enrichment analysis of allele-specific transcription factor binding at SNPs.
Alexandr Boytsov, Sergey Abramov, Ariuna Z Aiusheeva, Alexandra M Kasianova, Eugene Baulin, Ivan A Kuznetsov, Yurii S Aulchenko, Semyon Kolmykov, Ivan Yevshin, Fedor Kolpakov, Ilya E Vorontsov, Vsevolod J Makeev, Ivan V Kulakovskiy. Nucleic Acids Research, 2022 doi: 10.1093/nar/gkac262
Pagel KA, Kim R, Moad K, Busby B, Zheng L, Tokheim C, Ryan M, Karchin R. JCO Clin Cancer Inform, 2020. doi: 10.1200/CCI.19.00132.