Project Description
Investigator: Zaid Abu-Rumman Mentor/Principal Investigator: Dr. Ma (Penn State University) Program: National Remote Research Experience (NRRE) Period: August/September 2026 through December 2026 (one academic semester)
Background and Significance
Sex differences in gene expression contribute to physiological differences between males and females and help explain why disease risk, disease progression, and drug response often differ by sex. These differences are not uniform across the body. The same gene can be strongly sex-biased in one tissue and show no bias in another, so sex-biased expression is best understood tissue by tissue rather than as a single organism-wide signature.
The three tissues in this project sit at different points along that range. Gonadal tissue shows the strongest and most extensive sex bias of any tissue, since it carries out sex-specific reproductive function directly. Liver has a well-characterized program of sex-biased expression tied to metabolism, hormone signaling, and the processing of drugs and other xenobiotics, driven in large part by sex differences in growth hormone secretion. Neural tissue tends to show more limited but functionally meaningful sex-biased expression.
My prior NRRE work applied a differential expression and enrichment workflow to neural tissue of young adult Mus musculus. Using iDEP 2.0 with DESeq2 (FDR less than or equal to 0.1, absolute fold-change greater than or equal to 1.5), we identified 93 sex-biased genes, with an overall male-biased pattern (75 upregulated in males and 18 upregulated in females). We confirmed the integrity of the analysis using known sex-linked markers: the Y-linked genes Ddx3y, Kdm5d, and Eif2s3y were downregulated in females, and Xist was highly expressed in females, both as expected. Enrichment analysis pointed to female-upregulated neuroactive signaling genes (Oxytocin, Pro-Opiomelanocortin, and Prolactin) and male-upregulated synaptic and stress or neurodegeneration pathways, including SNARE complex assembly. One direction that came out of that work was a possible link between the male-biased upregulation of SNARE complex assembly and the known female predominance in Alzheimer's disease.
This project extends that same workflow from neural tissue alone to a direct comparison across neural, liver, and gonadal tissue, so that sex-biased expression can be characterized within each tissue and then compared across all three.
Research Question
How does sex-biased gene expression differ across neural, liver, and gonadal tissue in mouse, and which sex-biased genes are shared across tissues versus specific to a single tissue?
Specific Aims
1. Extend the existing workflow to a multi-tissue dataset. Apply the differential expression and enrichment workflow I used on neural tissue to a larger mouse RNA-seq dataset covering neural, liver, and gonadal samples from both sexes [dataset name, GEO accession or in-house source, and sample counts per tissue and per sex to be confirmed].
2. Identify sex-biased genes within each tissue. Run male versus female differential expression separately for each tissue and produce a statistically corrected, ranked set of sex-biased genes per tissue, validating labeling in each with sex-linked markers.
3. Compare sex-biased expression across tissues. Determine which sex-biased genes overlap across the three tissues and which are tissue-specific, and compare functional enrichment across tissues.
Approach
Data. Mouse RNA-seq samples from neural, liver, and gonadal tissue, balanced across sex where possible [insert sample counts once confirmed]. Gonadal tissue here refers to testis and ovary, the pairing that makes the sex comparison most direct.
Differential expression. Male versus female comparison within each tissue using iDEP 2.0 with DESeq2, starting from the same thresholds as the neural analysis (FDR less than or equal to 0.1, absolute fold-change greater than or equal to 1.5). I plan to revisit these thresholds if the larger and more variable multi-tissue dataset calls for it.
Validation. Confirm sex labeling in each tissue using sex-linked markers such as Xist and the Y-linked genes Ddx3y, Kdm5d, and Eif2s3y, as I did for neural tissue.
Functional enrichment. Gene Ontology enrichment and compound or pathway enrichment (for example through STITCH) within iDEP 2.0, run separately for the male-biased and female-biased gene sets in each tissue.
Cross-tissue comparison. Overlap analysis across the three tissue-level results to separate shared from tissue-specific sex-biased genes, followed by comparison of enrichment patterns across tissues and visualization.
I plan to keep modifying the workflow as the analysis proceeds, since moving from a single tissue to three tissues with very different expression profiles is likely to surface issues that the neural-only version did not.
Expected Outcomes
I hope to produce a set of sex-biased genes for each of the three tissues and a comparison that shows how much of the sex-biased signal is shared and how much is tissue-specific. Based on the biology, I anticipate the strongest and largest set of sex-biased genes in gonadal tissue, a metabolic and hormone-linked set in liver, and a continuation of the neural findings from last year, but the comparison itself is the point of the project and I am not assuming the result in advance. Adding liver and gonad also lets me test whether the neurodegeneration-linked signal I saw in neural tissue, including the SNARE complex assembly result, is specific to neural tissue or appears more broadly.