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File Version Author Date Message
Rmd abc6dc8 Jing Gu 2025-11-01 TF regulation to explain cross-tissue DE genes

Cross-tissue DE tested in bulk by DESeq2

100-650 cross-tissue DE genes were found across cell types with single-cell approach. About half amount were detected with bulk approach, except for Memory B cells.

          CD4-T CD8-T NK Memory-B Naive-B
lung_up      26    17 27      273      24
spleen_up    41    46 38      281       1

Top 10 lung-upregulated genes in each cell type

Spleen-upregulated genes were strictly enriched in B cell functions

Somehow spleen-upregulated genes in T cells are enriched for B cell activation.

In summary, genes with higher expression in lungs are broadly enriched for T cell related functions, while those in spleens are broadly enriched for B cell related functions. We still see lung up-regulated genes enriched in pathways of heat-shock protein genes. Overall, the GO enrichment results are consistent between bulk or single-cell approach.

Testing whether TFs mediate cross-tissue GE differences

We have shown that chromatin accessibility for cross-tissue DE genes are very similar. Thus, some other mechanisms may drive the differences, which motivates us to test whether TF activity is responsible for the up-regulation of genes in lung.

Cell composition for both tissues cell comosition

We examined GRNs for B cells because both tissues have relatively similar number of cells. Though half amount of memory B cells found in lung compared to spleen, we still detected several lung TFs with higher activity relative to spleen. The differences in naive B cells are small, which is consistent with lack of differences in cross-tissue DE genes in naive B cells.

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[[2]]

Let’s focus on TFs specific to lung memory B cells and ask whether they explain up-regulated genes in lungs

Testing whether lung-specific TFs regulated more DE genes

Here I performed the tests on DE genes identified using single-cell or bulk approach. I identified lung-specific TFs by only requiring its expression to be 1.5 fold higher in lung than spleen. I relaxed the differential regulation criteria because the quantity of target counts do not truly reflect the difference.

[1] "Results for single-cell approach DE genes:"
      p_value odds_ratio conf_low conf_high        FDR
CEBPD 1.3e-03       1.69     1.23      2.29 0.02643333
IRF1    8e-04       1.79     1.26      2.50 0.02643333
RUNX2 1.2e-03       1.88     1.27      2.72 0.02643333
[1] "Results for bulk approach DE genes:"
      p_value odds_ratio conf_low conf_high        FDR
GATA3   2e-02       3.41     1.07      8.41 0.24400000
PRDM1 3.4e-03       3.48     1.45      7.23 0.06913333

Examining the effect sizes between TF regulation and differential expression

As we identified lung-specific TFs enriched for DE genes, we further asked if TFs that have stronger links tend to have DE genes with larger differences between lung and spleen. Let’s use gene expression in spleen as baseline. If specific lung TFs drive gene expression in lung to be higher than baseline, we would expect to higher TF activity leads to higher expression.

Method For each lung-specific TF, we identified lung up-regulated genes in its network. Then we plotted TF strength and differential expression and showed the fitted line.

Bulk DE genes

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Single-cell DE genes

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We saw positive trends for the two TFs enriched for bulk-level DE genes, but much weaker trend for the three TFs enriched for single-cell level DE genes.


R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.3.13-el7-x86_64/lib/libopenblas_haswellp-r0.3.13.so

locale:
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[10] LC_TELEPHONE=C       LC_MEASUREMENT=C     LC_IDENTIFICATION=C 

attached base packages:
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other attached packages:
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[5] tidyr_1.3.1       dplyr_1.1.4      

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