DNA-shape

← Back to Tools

Overview

Based on the long-read assembly of the Mus musculus genome from Ton et al., Sci. Data 2020 (PMID: 33203859) (run SRR11606870), and using the major and minor satellite reads from Packiaraj & Thakur, Genome Biol. 2024 (PMID: 38378611) as templates, the scripts compute:

1. The number of contiguous A/T stretches (default minimum length = 4).
2. The number of tetranucleotides associated with a narrow minor groove (per Rohs et al., Nature 2009; PMID: 19865164).

Links

• Source code: github.com/DDudka9/DNA-shape
• License: MIT
• Companion paper: Dudka et al., Nature 2025 (see Publications).

Requirements

• Operating system tested: MacOS (M1) Ventura
• Language: Python 3.11
• Installer: Miniconda
• Installation time: ~10 minutes
• Code run time: 10–30 minutes
• Modules: blast (v2.6.0), biopython (v1.83), mkl-service (v2.4.0), regex (v2024.5.15)

Tools to download

(Recommended: terminal / bash.)

1. Download Miniconda.
2. Install BLAST via Miniconda — see anaconda.org/bioconda/blast.
3. Install sra-tools. Useful guides: fasterq-dump wiki · fastq-dump blog.
4. (Recommended) PyCharm 2023.2.5 Community Edition for running majsat.py and minsat.py.

Prepare the dataset

(Recommended: terminal / bash.)

1. Download SRR11606870 from NCBI SRA.
2. Prefetch the dataset:

   prefetch SRR11606870

3. Download all reads unsorted in FASTA format:

   fasterq-dump pathtoSRAfile --outdir pathtoSRAfile/fasta --fasta-unsorted

4. Rename the output to SRR11606870.fasta.
5. Copy the two template FASTA files (major satellite SRR11606870_2342980.fasta and minor satellite SRR11606870_111923.fasta) from the repo into the same folder as SRR11606870.fasta.

Run the scripts

(In PyCharm 2023.2.5 Community Edition.)

1. Clone the GitHub repository: Git → Clone → URL https://github.com/DDudka9/DNA-shape.git
2. Create a new interpreter: Python interpreter (bottom right) → Add New Interpreter → Add Local Interpreter → Conda Environment → Create New Environment (provide the path to Miniconda; select Python 3.11).
3. Select requirements.txt and click Install requirements.
4. Follow instructions inside majsat.py and minsat.py. Use PyCharm's built-in Python Console to run subsequent parts of the scripts by copy-pasting the code into the console and pressing Return.
5. Output appears in the folder containing SRR11606870_2342980.fasta and SRR11606870_111923.fasta.

Expected output files

Tetranucleotide column order in all CSV/FASTA outputs: AAAT · AATA · AATC · AATT · AAAA · AAGT · GAAT · GAAA · TAAT · AAAC.

1. SRR11606870_Maj_2342980_tetranucleotides.csv — per-1 kb counts of narrow-major-groove tetranucleotides along a representative major satellite array (SRR11606870_2342980).
2. SRR11606870_Min_111923_tetranucleotides.csv — per-1 kb counts of narrow-minor-groove tetranucleotides along a representative minor satellite array (SRR11606870_111923).
3. SRR11606870_Maj_tetranucleotides_average.fasta — narrow-major-groove tetranucleotide counts per 234 bp across 500 major satellite arrays (averages at the end of the file).
4. SRR11606870_Min_tetranucleotides_average.fasta — same for 500 minor satellite arrays.
5. SRR11606870_Maj_ATstretches_average.fasta — AT-stretch counts (default minimum length 4) per 234 bp across 500 major satellite arrays.
6. SRR11606870_Min_ATstretches_average.fasta — same for 500 minor satellite arrays.

You can modify the array ID inside the scripts to analyze any other array, or substitute a different dataset entirely.