Genomic Regulatory Elements ENcyclopedia

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This is the home of the GREEN-DB and companion tools (GREEN-VARAN)

Genomic Regulatory Elements ENcyclopedia Database A collection of ~2.4M regulatory regions in the human genome, with information about controlled genes, tissues of activity and associated phenotypes. GREEN-DB is available for free for academic usage in a Zenodo repository

Genomic Regulatory Elements ENcyclopedia VARiant ANnotation Annotate non-coding regulatory variants in a VCF with information from GREEN-DB

• possibly controlled genes
• overlapping regulatory region IDs and data sources
• overlapping regulatory regions max constraint value

A Nextflow workflow for complete VCF processing Given a VCF, ideally annotated for gene consequences with snpEff or bcftools, the workflow can be used to automate processing:

• annotate with functional regions (TFBS, DNase, UCNE)
• annotate with the 3 best non-coding variant prediction scores (ncER, FATHMM-MKL, ReMM)
• annotate population AF from gnomAD genomes
• perform regulatory variant prioritization using GREEN-VARAN

See the workflow readme for more details or look at the full documentation.

Detailed documentation on GREEN-DB and GREEN-VARAN tool and workflow is provided in ReadTheDocs

GREEN-VARAN tools are written in Nim. GREEN-VARAN relies on hts-nim by Brent Pedersen for fast VCF processing. The GREEN-DB BED files are needed for annotation (see Download the supporting files)

The easiest way to run GREEN-VARAN is to download the pre-compiled binaries from the latest release at https://github.com/edg1983/GREEN-VARAN

Alternatively, you can clone the repository git clone https://github.com/edg1983/GREEN-VARAN.git

And then compile the greenvaran using Nim compiler. GREEN-VARAN requires

• nim >= 0.10
• hts-nim >= 0.3.4
• argparse 0.10.1

If you have Singularity installed, you can use the script nim_compile.sh to create a static binary with no dependencies This uses musl-hts-nim as described in hts-nim repository (see https://github.com/brentp/hts-nim#static-binary-with-singularity)

The accessory greendb_query tool can be compiled using nim compile greendb_query.nim

GREEN-VARAN performs annotation of small variants or structural variants VCF adding information on potential regulatory variants from GREEN-DB. Especially, it can annotate possible controlled genes and a prioritization level (this latter need the presence of some additional annotations, see below) It provides also ability to tag variants linked to genes of interest and update existing gene-level annotations from SnpEff or bcftools.

greenvaran [run mode] [options]

The running mode can be one of:

• smallvars

  In this mode the tool will perform annotation for a small variants VCF. It will annotate variants with information on the possible regulatory role based on GREENDB and eventually provide prioritization levels

• sv

  In this mode the tool will perform annotation for a structural variants VCF. Capability in this case is limited to annotation of overlapping GREENDB regions and controlled genes. No prioritization is provided

• querytab

  This mode is a convenient way to automatically prepare input table to be used with the query tool to extract detailed information from GREENDB database.

• version

  Print the tool version

NB. To perform prioritization of small variants some additional annotation fields are expected in the input VCF, see the prioritization section below. By default, when these information are not present the prioritization level will be set to zero for all annotated variants. We also provide pre-processed datasets (see resources) and Nextflow workflow to automate the whole process (see workflow).

Fields in the following table are added to INFO fields by GREEN-VARAN. greendb_level will be added only for small variants

By default, GREEN-VARAN update gene consequences in the SnpEff ANN field or the bcftools BCSQ if one is present in the input VCF file. In this way the annotation can be processed by most downstream tools evaluating segregation. If none is found, GREEN-VARAN will create a new ANN field. To switch off gene consequence update use the --noupdate option.

The tool will add a new consequence for each possibly controlled gene, limited by the --connection option. The new consequence will follow standard format according to SnpEff or bcftools and have MODIFIER impact by default. This can be adjusted using the --impact option. The gene effect will be set according to the GREEN-DB region type, adding 5 one of the terms: bivalent, enhancer, insulator, promoter, silencer.

Example ANN / BCSQ field added by GREEN-VARAN.

ANN=C|enhancer|MODIFIER|GeneA||||||||||||
BCQS=enhancer|GeneA||

GREEN-VARAN will consider GREEN-DB annotations, additional functional regions and non-coding impact prediction scores to provide a prioritization level for each annotated variant. This level is annotated under greenvaran_level tag in the INFO field.

This fields is an integer from 0 to N which summarize evidences supporting a regulatory impact for the variant. Higher values are associated to a higher support of regulatory impact.

You need 3 set of information in your input VCF to run prioritization mode when using the default config provided.

1. gnomAD_AF, gnomAD_AF_nfe: float values describing global and NFE population AF from gnomAD
2. ncER, FATHMM-MKL and ReMM: float values providing scores predictions
3. TFBS, DNase and UCNE: flags describing overlap with additional functional regions

The prioritization schema can be adjusted by modifying the .json file passed to --config. A default file is provided in config folder.

The default behaviour is --prioritization_strategy levels which reproduce the 4 levels as described in the paper. Alternatively, you can chose a "pile-up" approach setting --prioritization_strategy pileup which simply sum evidences across levels. This means that the criteria described above are tested independently and the level reported is increased by one for each satisfied criteria.

See documentation for more details documentation.

The tool binaries should work on most linux based system. In case you have any issue, we also provide GREEN-VARAN as Singularity image (tested on singularity >= 3.2). A Singularity recipe is included in the repository or you can pull the image from Singularity Library using

singularity pull library://edg1983/greenvaran/greenvaran:latest

The image contains both greenvaran and greendb_query tools. The general usage is:

singularity exec \
  greenvaran.sif \
  tool_name [tool arguments]

The tool needs access to input VCF file, the GREEN-DB bed file and the config files so remember to bind the corresponding locations in the container

See the following example where we use the current working directory for input/output, while other files are located in the default config / resources folder within greenvaran folder (greenvaran_path). In the example we use GRCh38 genome build

singularity exec \
  --bind /greenvaran_path/resources/GRCh38:/db_files \
  --bind /greenvaran_path/config:/config_files \
  --bind ${PWD}:/data \
  greenvaran.sif \
  greenvaran -i /data/input.vcf.gz \
  -o /data/output.vcf.gz \
  --db /db_files/GRCh38_GREEN-DB.bed.gz \
  --dbschema /config_files/greendb_schema_v2.5.json \
  --config /config_files/prioritize_smallvars.json
  [additional tool arguments]

greenvaran smallvars \
  --invcf test/VCF/GRCh38.test.smallvars.vcf.gz \
  --outvcf test/out/smallvars.annotated.vcf.gz \
  --config config/prioritize_smallvars.json \
  --dbschema config/greendb_schema_v2.5.json \
  --db resources/GRCh38/GRCh38_GREEN-DB.bed.gz \
  --genes test/VCF/genes_list_example.txt

greenvaran sv \
  --invcf test/VCF/GRCh38.test.SV.vcf.gz \
  --outvcf test/out/SV.annotated.vcf.gz \
  --dbschema config/greendb_schema_v2.5.json \
  --db resources/GRCh38/GRCh38_GREEN-DB.bed.gz \
  --minbp 10

When you use GREEN-DB or GREEN-VARAN tools please cite: GREEN-DB: a framework for the annotation and prioritization of non-coding regulatory variants in whole-genome sequencing Giacopuzzi E., Popitsch N., Taylor JC. BiorXiv (2021)

When you use GREEN-VARAN workflow for small variants annotation please also cite:

Vcfanno: fast, flexible annotation of genetic variants Brent S. Pedersen, Ryan M. Layer & Aaron R. Quinlan. Genome Biology volume 17, Article number: 118 (2016)

Additionally, when you use any prediction score for annotation, please cite the corresponding publication.