| Autor: |
Vo K; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA., Sharma Y; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA., Paul A; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA., Mohamadi R; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA., Mohamadi A; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA., Fields PE; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA., Rumi MAK; Department of Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, KS 66160, USA. |
| Abstrakt: |
RNA sequencing (RNA-Seq) has become a widely adopted technique for studying gene expression. However, conventional RNA-Seq analyses rely on gene expression (GE) values that aggregate all the transcripts produced under a single gene identifier, overlooking the complexity of transcript variants arising from different transcription start sites or alternative splicing. Transcript variants may encode proteins with diverse functional domains, or noncoding RNAs. This study explored the implications of neglecting transcript variants in RNA-Seq analyses. Among the 1334 transcription factor (TF) genes expressed in mouse embryonic stem (ES) or trophoblast stem (TS) cells, 652 were differentially expressed in TS cells based on GE values (365 upregulated and 287 downregulated, ≥absolute 2-fold changes, false discovery rate (FDR) p -value ≤ 0.05). The 365 upregulated genes expressed 883 transcript variants. Further transcript expression (TE) based analyses identified only 174 (<20%) of the 883 transcripts to be upregulated. The remaining 709 transcripts were either downregulated or showed no significant changes. Meanwhile, the 287 downregulated genes expressed 856 transcript variants and only 153 (<20%) of the 856 transcripts were downregulated. The other 703 transcripts were either upregulated or showed no significant change. Additionally, the 682 insignificant TF genes (GE values < absolute 2-fold changes and/or FDR p-values > 0.05) between ES and TS cells expressed 2215 transcript variants. These included 477 (>21%) differentially expressed transcripts (276 upregulated and 201 downregulated, ≥absolute 2-fold changes, FDR p-value ≤ 0.05). Hence, GE based RNA-Seq analyses do not represent accurate expression levels due to divergent transcripts expression from the same gene. Our findings show that by including transcript variants in RNA-Seq analyses, we can generate a precise understanding of a gene's functional and regulatory landscape; ignoring the variants may result in an erroneous interpretation. |
