Distinct signaling center and progenitor identity dynamics initiate human forebrain patterning
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The authors' code
Jupyter notebook · 110 lines · 4.3 KB · no license
- # %% [markdown]
- # Pybridizer basic usage example:
- #
- # This notebook demonstrates how to use Pybridizer to design HCR probes
- # %% [markdown]
- # Import essential functions from the pybridizer probe design module
- # %%
- from pybridizer import read_fasta, create_oligos, blast_oligos, fetch_geneIDs, filter_and_rank, add_hairpin, plot_sequence_alignment
- # %% [markdown]
- # Read a FASTA file containing the transcript sequence for which HCR probes need to be designed. The file should be in a .fasta/.fa/.faa format.
- # %%
- ID, desc, sequence = read_fasta("Pybridizer\\input\\sox10_zebrafish.fasta")
- # %% [markdown]
- # Now, the transcript sequence needs to be tiled into oligos (default:25 base length, 2 base gap).
- #
- # Optional: You can also adjust the length of the oligo, gap between oligos and frame start position (0 i.e. beginning of the transcript by default)
- # %%
- oligos_all = create_oligos(sequence,oligo_length=25,gap_length=2,frame_start_position=0)
- # %% [markdown]
- # Next, perform a batch BLAST for each of the oligos against your database and save the BLAST results.
- #
- # !!!Warning!!! : BLAST+ must be installed and a BLAST database should be built using 'makeblastdb' command on the data downloaded from vector base. This is a pre-requisite for the BLAST function to work.
- #
- # The database name ('dbname') should be your custom BLAST database and the taxonomy ID ('taxid') argument is optional.
- # Taxonomy ID is essential if you want to run BLAST for a specific species in a database with multiple species.
- # %%
- blast_result = blast_oligos(oligos_all, dbname='refseq', taxid=7955)
- # %% [markdown]
- # You can view the BLAST results now.
- #
- # The dataframe lists the query results for each oligo including hits (matches with other transcripts) in the database, length of the matches, match positions and match scores.
- # %%
- blast_result.head()
- # %% [markdown]
- # The next step is to retreive gene IDs that correspond to transcript IDs. This would be useful if multiple transcript IDs exist for a single gene.
- #
- # This step is completely optional.
- # %%
- blast_result_genes = fetch_geneIDs(blast_result,taxid='zebrafish')
- # %% [markdown]
- # View the blast results with gene IDs appended
- # %%
- blast_result_genes.head()
- # %% [markdown]
- # The oligos need to be filtered based on the GC content and the Melting Temperature. Default range for GC: 37-85 % & Default range for MT: 47-85 C These can also be adjusted in the 'filter and rank' function but is optional.
- #
- # Based on the BLAST results, neighbouring oligos that hit the same transcript (other than our target gene) should be filtered out. This is to ensure specificity of HCR probes
- #
- # Lastly, the neighbouring oligo pairs are ranked according to their specificity
- # %%
- probe_datasheet = filter_and_rank(oligos_all,blast_result_genes,Tm_range=[47,85],GC_range=[0.37,0.85])
- # %% [markdown]
- # View the probe datasheet for the optimal set of HCR oligo pairs after filtering
- # %%
- probe_datasheet.head()
- # %% [markdown]
- # Choose hairpin (B1-B5) for the selected probes to generate final HCR probe pairs
- # %%
- hcr_probes = add_hairpin(probe_datasheet,'B3')
- # %% [markdown]
- # View final HCR probes for the chosen hairpin.
- # The hcr_probes datasheet has the following columns:
- #
- # 'Oligo1_position' and 'Oligo2_position' columns represent the location of the oligo along the transcript
- #
- # 'Oligo1_Sequence' and 'Oligo2_Sequence' are reverse complement oligos of the two neighbouring 25 base sequence along the transcript
- #
- # 'Score (avg hits)' represents how many other transcripts on average could partially bind to one of the two oligos, but not both. Lower the score, higher the specificity of the probe pair
- #
- # 'HCRprobe1' and 'HCRprobe2' are the final hairpin appended oligos that should be ordered as ssDNA.
- # %%
- hcr_probes.head()
- # %% [markdown]
- # Now we can visualize the alignment of the probe pairs to our target transcript sequence and save the output alignment as an image and a FASTA file.
- # %%
- fig_path = "Pybridizer\\output\\sox10_zebrafish_probe_alignment.png"
- align_fasta_path = "Pybridizer\\output\\sox10_zebrafish_probe_alignment.fasta"
- # %%
- fig,records = plot_sequence_alignment(sequence, ID, probe_datasheet, top_n=None,figsize=(16,8),save_path=fig_path,output_fasta=align_fasta_path)
- # %% [markdown]
- # You can save the designed hcr probes datasheet as an excel file
- # %%
- hcr_probes.to_excel('Pybridizer\\output\\sox10_hcr_probes_B3.xlsx')
pybridizer_basic_usage.ipynb at commit 28caf8b, no license · at the source
Overview
- Centre for Developmental Neuroscience, King’s College London, London, United Kingdom
- The Francis Crick Institute, London, United Kingdom
Abstract
At which developmental stage does the human brain start to differ from other mammals? We uncover human features of telencephalic patterning as early as the fourth post-conception week, comparing the early mouse and human forebrains using single-cell transcriptomics and 3D spatial multi-transcript imaging. In comparison to mice, the human telencephalon is delayed in ventral SHH signaling, accompanied by a human signature of anterior FGF signaling. These observations correlate with a less-resolved patterning and reduced progenitor diversity along the dorsoventral and anteroposterior axes, as well as a human early neurogenic signature. Our complementary approaches reveal a human divergence in allocation of telencephalic progenitor identities, propelled by temporal and qualitative differences in ventro-anterior signals following neural tube closure in the developing forebrain.
Reproduced under the paper's license (CC BY), from the paper cited above.
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ctucl/pybridizer
28caf8bd6f48145e334fd39afc5585bd5c76117b, 31 October 2025Availability: 1 check, the latest on 30 September 2026: the link answers
- 30 September 2026: the link answers
5 files
- examples/
pybridizer_basic_usage.i , Jupyter, 110 linespynb - pybridizer/
__init__.py , Python, 12 lines - pybridizer/
pybridizer.py , Python, 533 lines - setup.py, Python, 30 lines
- README.md, Text, 45 lines
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Cite
This paper
Azizi, A., Fakhreddine, D., Hamid, F., Messi, Z., Strohbuecker, S., Guillemot, F., & Houart, C. (2026). Distinct signaling center and progenitor identity dynamics initiate human forebrain patterning. bioRxiv (preprint). https://
BibTeX
@article{azizi2026distin
author = {Azizi, Afnan and Fakhreddine, Dana and Hamid, Fursham and Messi, Zeno and Strohbuecker, Stephanie and Guillemot, Francois and Houart, Corinne},
title = {{Distinct signaling center and progenitor identity dynamics initiate human forebrain patterning}},
journal = {bioRxiv (preprint)},
year = {2026},
month = mar,
publisher = {bioRxiv},
issn = {2692-8205},
doi = {10.64898/
url = {https://
}
RIS
TY - JOUR
AU - Azizi, Afnan
AU - Fakhreddine, Dana
AU - Hamid, Fursham
AU - Messi, Zeno
AU - Strohbuecker, Stephanie
AU - Guillemot, Francois
AU - Houart, Corinne
TI - Distinct signaling center and progenitor identity dynamics initiate human forebrain patterning
T2 - bioRxiv (preprint)
J2 - bioRxiv
PY - 2026
DA - 2026/
SN - 2692-8205
PB - bioRxiv
DO - 10.64898/
UR - https://
ER -
CSL-JSON
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