A method to identify temporal and sex-specific alternative splicing from multi-omics data.

Author: Ashley Mae Conard

Motivation

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!

Paper

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

Installation

1. Clone repo

   git clone https://github.com/ashleymaeconard/time2splice.git 
   

2. In the time2splice directory, build conda environment

   conda env create --name time2splice --file=time2splice.yml
   

3. Install reference and other data files here. We suggest placing them in time2splice/data/.

Outline

1. Preprocess
2. Temporal expression analysis
3. Temporal protein-DNA analysis
4. Temporal multi-omics integration

Preprocess (scripts/preprocess)

Retrieve raw data, quality control, trimming, alignment. Perform steps as needed.

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).

Temporal expression analysis (scripts/rna)

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.

Temporal protein-DNA analysis (scripts/protein_dna)

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.

Temporal multi-omics integration (scripts/multio_analysis)

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.