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Knit directory: Lung_scMultiomics_paper/

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Rmd 6528782 Jing Gu 2025-11-03 correct batches

Cross-tissue DE tested in pseudobulk by DESeq2 (batch corrected)

Previous results were due to a mistake in filtering DE results by requiring expressed in at least three cells. For pseudobulk samples, we only have three samples for spleens. So genes not expressed in spleens were filtered out.

After batch correction, the numbers of DE genes are similar between two approaches.

Pseudo-bulk appraoch

          CD4-T CD8-T  NK Memory-B Naive-B
lung_up     233   201 242     1329     138
spleen_up   182   129 108      859      74

Single-cell approach

          CD4_T CD8_T  NK Memory_B Naive_B
lung_up     216   111 152      647     131
spleen_up   257   452 678     1163     172

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 drive 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.

[[1]]


[[2]]

Let’s use TFs with >= 100 targets genes in 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.

[1] "Results for single-cell approach DE genes:"
[1] p_value    odds_ratio conf_low   conf_high  FDR       
<0 rows> (or 0-length row.names)
[1] "Results for bulk approach DE genes:"
      p_value odds_ratio conf_low conf_high        FDR
GATA3 2.8e-03       2.28     1.30      3.81 0.06906667
RUNX3 4.4e-03       2.00     1.21      3.16 0.09302857

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

[[1]]


[[2]]

No clear positive trends for the two TFs enriched for bulk-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
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