Splice-O-Mat applied to adhesion GPCRs transcript variants

This repository contains all informations and scripts for the paper:

The repertoire and structure of adhesion GPCR transcripts assembled from deep-sequenced human samples.
Christina Katharina Kuhn, Udo Stenzel, Sandra Berndt, Ines Liebscher, Torsten Schöneberg, Susanne Horn
published at Nuclar Acid Research (NAC) https://doi.org/10.1093/nar/gkae145

This includes preprocessing of the datasets (/analysis), the scripts for the webtool (/scripts), and additional analysis for the manuscript (/analysis).

Table of Contents

• Objective
• Data
  • GSE182321_OpiodUseDisorder_braintissues
  • GSE173955_Alzeihmer_braintissue
  • GSE174478_Non_alcoholic_fatty_liver
  • GSE217427_kidney
  • GSE165303_SRP302848_heart
  • SRP225193_many_tissues
  • melanoma
• Analysis
• Results
• Webtool Scripts
• Additional
• Contact
• Todos

Objective

The main objective of this project was to analyze tissue-specific splicing of adhesion GPCRs (aGPCRs). For this a webtool was created based on a database including over 900 samples and 48 different tissue types. For investigation of tissue-specific splice pattern a gene of interest, please visit: https://tools.hornlab.org/Splice-O-Mat/

Data

GSE173955_Alzeihmer_braintissue

• GSE173955
• BioProject: PRJNA727602
• SRP ID: SRP318632
• Samples: 40
• Description: Analysis of postmortem human hippocampus brains from 8 subjects with Alzheimer's disease (AD) and 10 non-AD subjects using Illumina TruSeq stranded mRNA LT Sample Prep kit. Sequencing performed on HiSeq1500. One AD and one non-AD sample were applied independently twice to increase read coverage.
• Sequencing Depth: 9-25M reads per sample
• Participants: 8 AD subjects and 10 non-AD subjects
• PMID: 23595620

GSE182321_OpiodUseDisorder_braintissues

• GSE182321
• Description: RNA sequencing analysis of postmortem human Brodmann Area 9 in the University of Texas Health Science Center at Houston Brain Collection for individuals with Opioid Use Disorder; 27 opioid users and 14 nonpsychiatric controls, as determined by postmortem consensus diagnosis by two trained psychiatrists.
• BioProject: PRJNA755746
• SRP ID: SRP332964
• Samples: 41
• Description: RNA sequencing analysis of postmortem human Brodmann Area 9 in the University of Texas Health Science Center at Houston Brain Collection for individuals with Opioid Use Disorder.
• Sequencing Depth: 27-34M reads per sample
• PMID: 34385598

GSE101521 Brain Dataset

• GSE101521
• Decription: on-psychiatric controls (CON, N=29), DSM-IV major depressive disorder suicides (MDD-S, N=21) and MDD non-suicides (MDD, N=9) in the dorsal lateral prefrontal cortex (Brodmann Area 9)
• Samples: 59
• Sequencing Depth: 7-61 million reads per sample
• Participants: 8 AD subjects and 10 non-AD subjects
• PMID: 27528462

GSE174478_Non_alcoholic_fatty_liver

• GSE174478
• Description: a fatty liver diagnosed ultrasonically by an increase in hepatorenal contrast, a history of alcohol consumption of less than 30 g/d for men and less than 20 g/d for women, seronegativity for hepatitis B virus surface antigen and hepatitis C virus antibody, and the absence of autoimmune hepatitis, primary biliary cholangitis, primary sclerosing cholangitis, Budd-Chiari syndrome, Wilson disease, and drug-induced liver injury
• SRP ID: SRP319881
• BioProject: PRJNA730024
• Samples: 94
• Sequencing Depth: 31-44M reads per sample
• PMID: 35380992

GSE217427_kidney

• GSE217427
• Description: medulla and coretex, with human kidney damage (KD) (n=22) and without KD (22),
• BioProject:
• Samples: 44
• Sequencing Depth:37-51M reads per sample
• Not published yet

GSE165303_SRP302848_heart

• GSE165303
• Description: with dilated cardiomyopathy, 50 non-failing, 2 Transfected with control adenovirus and 2 transfected with HAND1 overexpressing adenovirus, only paired end was selected
• BioProject: SRP302848
• Samples: 101
• Sequencing Depth:57-80M reads per sample
• Not published yet

SRP225193_many_tissues

• GSE138734
• Description: 300 human samples, including 45 tissues, 162 cell types, and 93 cell lines, some paired some single end, total RNA (296 samples), only full RNA-seq (paired end) of 45 tissues was selected (cell line and cell types excluded)
• BioProject: SRP225193
• Samples: 457
• Sequencing Depth:76-111M reads per sample
• PMID: 34140680

melanoma

• Description: RNA-seq of metastatic melanoma patients treated with anti-PD-1 alone or combined anti-PD-1 and anti-CTLA-4 immunotherapy
• BioProject: PRJEB23709 at ENA
• Samples: 91
• Sequencing Depth: around 50M reads per sample
• PMID: 30753825

Analysis

The following steps were followed to perform the mapping/assembly and creation of the database:
All files are within directory analysis/

1. SRR data retrieval:

   • Execute ../get_SRR_data.sh to retrieve the SRR data.

2. STAR + StringTie:

   • Execute ../splice-variant-analysis.sh to perform STAR mapping (sorting and indexing) and StringTie Assembly with hg38. Run this script in the data/cohort/ directory, using "cohort" as the output name in the analysis/cohort/ directory.

3. StringTie merged mode:

   • Execute ../stringtie_expression_estimation.sh to generate a merged GTF file. This file combines multiple GTFs based on the directories.txt file. If a combo file already exists, include it in new_mergefile.txt. Requantification is performed using the combo GTF file.

4. Building StringTie.db:

   • Clone the repository: git clone https://chrissi_kath@bitbucket.org/ustenzel/stringtiedb.git
   • Build: cabal build
   • Update (if necessary): cabal update
   • Run StringTie-db:
     • cabal run stringtie-db -- -d stringtie_2.db -m ../analysis/combo_new.gtf ../analysis/ballgown_version2//.gff -C ../analysis/pheno_data.csv
     • cabal run stringtie-db -- -d stringtie_2.db -C ../analysis/pheno_data.csv (to update the samples table)
   • The resulting stringtie_2.db is the new database.

Other necessary files:

• ../analysis/hg38.fna

Additional analysis in the manuscript:

• ../analysis/compare_CLSR1_with_genocode_and_diagostics/: Comparison with diagnostic exome sequencing of CELSR1/ADGRC1
• ../analysis/tissue_specific_splicing/: Spearman and violin plot of tissue-specific splicing
• ../analysis/high_number_newly_transcripts/: Analysis if ratio of newly identified transcript are influenced by expression threshold, tissues type, number of samples

Results

Inside the analysis/ directory, you will find the following directories for each dataset:

• ../cohort/star: Contains mappings generated by STAR.
• ../cohort/stringtie: Contains transcripts obtained from StringTie.
• ../cohort/ballgown: Contains outputs for database, including requantification with merged GTF.
• ..bzw ballgown_redone: Additional output for database, requantification with merged GTF.

Webtool Scripts

The following scripts are available for the webtool:
All files are within directory scripts/

• ../webtool.py: DASH webtool named "Splice-o-mat".
• ../bootstrap.min: CSS file for styling.
• ../assets/: Images related to the webtool.
• /var/tmp/process_id/: Temporary storage directory for intermediate data, including SVG, TXT, and FASTA files.

Dependencies

Python and Packages

• python version: Python 3.10.6
• used pyhton packages under: ../scripts/requirements.txt

my_interproscan

The is a need to include a local version of interproscan
to search domains in longest ORF of transcript
version used: interproscan-5.60-92.0

• ../my_interproscan includes a local Pfam database so search for domains in proteins

• with the script: ..analysis/insertDomainsinDb.py domains can be added into the stringtie_2.db as additional domain table to save computation time of the webtool (has to be generated with the structure: domains (transcript, domain, start, end))

Contact

Do you have any questions, suggestions about the webtool or the analysis please write me an email

---

ToDos:

• 'gene_name' benutzt anstatt 'gene_id' benutzen
• mitochondriale Gene löschen
• Reinzoomen
• alle Domänen anzeigen
• responsive
• an eine SNP Datenbank anknüpfen
• Svg flippen
• Eigene Domänen eintragen
• Mutation labeln können (rs Code)
• Eigene Daten einspeißen (pipeline, datenbank etc)
  • müssen deep sequenced sein, paired-end, datenbank local speichern?
• gene_id entfernen, stattdessen gene_name

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