Alternative splicing can occur in at least 3/4th of human genes to encode two or more splice isoforms. These isoforms occur in different proportions over time, and between sexes. Thus, we present a method to characterize these isoforms, so to better understand gene regulation happening in normal and diseased states. Time2splice identifies temporal and sex-specific alternative splicing combinding multi-omic (i.e. both expression via RNA-seq, and protein-DNA interaction via CUT&RUN and ChIP-seq) data. Analysis is done in 3 parts. 1) Temporal expression analysis, 2) Temporal protein-DNA analysis, and 3) Temporal multi-omics integration.
NOTE: Snakemake pipeline coming soon for time2splice!
Ray*, M., Conard*, A. M., Urban, J., & Larschan, E. (2021). Sex-specific transcript diversity is regulated by a maternal pioneer factor in early Drosophila embryos. bioRxiv.
*contributed equally
- Clone repo
git clone https://github.com/ashleymaeconard/time2splice.git - In the time2splice directory, build conda environment
conda env create --name time2splice --file=time2splice.yml - Install reference and other data files here. We suggest placing them in
time2splice/data/.
- Preprocess
- Temporal expression analysis
- Temporal protein-DNA analysis
- Temporal multi-omics integration
1_parse_sraRunTable.sh
Creates time2splice/ folder structure, as well as metadatafile.csv and SraAccList.txt (which is needed for next command to get .fastq files).
1_get_fastq_files.sh
Retrieves .fastq files by passing in SraAccList.txt from aforementioned step.
2_run_fastQC.sh
Runs FastQC for all .fastq files in a given directory.
3_run_trim_galore.sh
Run Trim Galore! followed by FastQC to trim any reads below quality threshold.
3_merge_lines.sh
Merges all the different lanes of the same flow cell .fastq files.
4_run_Bowtie2.sh or preprocess/4_run_BWA.sh or preprocess/4_run_HISAT2.sh.
Run one or more of these three aligners (Bowtie2, BWA, or HISAT2) on .fastq data in a given directory.
5_plot_alignment.py
Plot the alignments from either one or two different aligners (Bowtie2 or HISAT2).
1_run_salmon.sh
Run salmon to quantify transcript expression for case and control samples.
e.g. ./1_run_salmon.sh /nbu/compbio/aconard/larschan_data/sexed_embryo/ /data/compbio/aconard/splicing/results/salmon_results_ncbi_trans/ /data/compbio/aconard/BDGP6/transcriptome_dir/pub/infphilo/hisat2/data/bdgp6_tran/genome.fa 3 10 1 _001.fastq.gz
2_run_suppa.sh
Run Suppa for differential splicing analysis of case and control samples.
e.g. ./2_run_suppa.sh /data/compbio/aconard/splicing/results/salmon_results/ /data/compbio/aconard/splicing/results/suppa_results_ncbi_trans/ /data/compbio/aconard/BDGP6/transcriptome_dir/pub/infphilo/hisat2/data/bdgp6_tran/genome.fa 20
3_suppa_formatting.py
Converts NM_ gene names to flybase name, then merging outputs from run_suppa (NM_ gene names by 1 TPM value column for each replicate)
4_suppa.sh
Identifies various forms of differential splicing (e.g. using PSI and DTU). NOTE: ensure that your column names have a treatment and control name differentiator of the following format: TREATMENT.REP and CONTROL.REP. Examples for 2 replicates and 0-2 timepoint clamp RNAi could be: 0-2clampNull.1, 0-2clampNull.2, 0-2rescue.1, 0-2rescue.2.
5_calc_total_alt_splicing.py
Calculate and plot proportions of alternative splicing (in pie chart) in samples. <!> NOTE: Run this for every timepoint and condition separately.<!>
6_get_bias_genes.py
Find bias genes using control samples. <!> NOTE: Run this for every group pairs (2 only) comparison separately (e.g. females vs. males, females time 1 vs. females time 2, etc.) <!>
7_plots_splicing.ipynb
Plotting transcript abundance using PSI and DTU measures.
8_plots_splicing_time.ipynb
Plot alternative splicing genes within 2 categories (e.g. all females, all males, females sex specific, male sex specific, female all rest, male all rest, female non-sex specific, male non-sex specific, female new sex specific, male new sex specific). Each timepoint analysis should be run separately.
1_run_picard_markduplicates.sh
Run Picard's MarkDuplicates in for all .sorted.bam files in a given directory.
2_run_macs2.sh
Run MACS2 to call peaks for all .sorted.bam files in a given directory.
3_run_macs2_fold_enrich.sh
Generate signal track using MACS2 to profile transcription factor modification enrichment levels genome-wide.
Note, there is no order to these scripts. Each analysis / results exploration is independent. More analysis scripts to come.
overlap_protein_DNA_peaks.sh
Run Intervene to view intersection of each narrowpeak file.
enrichment_analysis.r
Perform gene ontology and gene set enrichment analysis given a list of genes.
get_coord_run_meme.sh
Get coordinates of bed file and run through MEME.
histogram_peak_val_intensity.ipynb
Plot peak intensity for a given narrow peak file.
alt_splicing_chi_squared.ipynb
Perform chi-squared test on alternative splicing categories. Mutually Exclusive Exons (MXE) used in this example.