Project description:<p>In this study, we describe a systematic analysis of pseudogene 'transcription' from an RNA-Seq resource of 293 samples, from 13 cancer and normal tissue types. We observed a highly prevalent, genome-wide expression of pseudogenes that could be categorized as universally expressed or lineage- and/or cancer-specific. We also explored disease subtype specificity and functions of selected expressed pseudogenes. We provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.</p>
Project description:<p>In this study, we describe a systematic analysis of pseudogene 'transcription' from an RNA-Seq resource of 293 samples, from 13 cancer and normal tissue types. We observed a highly prevalent, genome-wide expression of pseudogenes that could be categorized as universally expressed or lineage- and/or cancer-specific. We also explored disease subtype specificity and functions of selected expressed pseudogenes. We provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.</p>
Project description:Pseudogene transcripts can provide a novel tier of gene regulation through generation of endogenous siRNAs or miRNA-binding sites. Characterization of pseudogene expression, however, has remained confined to anecdotal observations due to analytical challenges posed by the extremely close sequence similarity with their counterpart coding genes. Here, we describe a systematic analysis of pseudogene "transcription" from an RNA-Seq resource of 293 samples, representing 13 cancer and normal tissue types, and observe a surprisingly prevalent, genome-wide expression of pseudogenes that could be categorized as ubiquitously expressed or lineage and/or cancer specific. Further, we explore disease subtype specificity and functions of selected expressed pseudogenes. Taken together, we provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression, especially in light of the recently described ceRNA networks. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.
Project description:We analyzed transcriptomic data from infected and uninfected T-cells to identify pseudogenes and their parent genes showing differential expression in HIV-1 infection
Project description:We analyzed transcriptomic data from infected and uninfected T-cells to identify pseudogenes and their parent genes showing differential expression in HIV-1 infection H9 T-cell line was infected with NL4-3 strain of HIV-1 obtained by transfection of 293T cells. RNA from infected and uninfected cells was extracted 7 days post infection.
Project description:Pseudogenes are gene copies presumed to mainly be functionless relics of evolution due to acquired deleterious mutations or transcriptional silencing. When transcribed, pseudogenes may encode proteins or enact RNA-intrinsic regulatory mechanisms. However, the extent, characteristics and functional relevance of the human pseudogene transcriptome are unclear. Short-read sequencing platforms have limited power to resolve and accurately quantify pseudogene transcripts owing to the high sequence similarity of pseudogenes and their parent genes. Using deep full-length PacBio cDNA sequencing of normal human tissues and cancer cell lines, we identify here hundreds of novel transcribed pseudogenes. Pseudogene transcripts are expressed in tissue-specific patterns, exhibit complex splicing patterns and contribute to the coding sequences of known genes. We survey pseudogene transcripts encoding intact open reading frames (ORFs), representing potential unannotated protein-coding genes, and demonstrate their efficient translation in cultured cells. To assess the impact of noncoding pseudogenes on the cellular transcriptome, we delete the nucleus-enriched pseudogene PDCL3P4 transcript from HAP1 cells and observe hundreds of perturbed genes. This study highlights pseudogenes as a complex and dynamic component of the transcriptional landscape underpinning human biology and disease.
Project description:The majority of bacterial genomes have high coding efficiencies, but there are an few genomes of the intracellular bacteria that have low gene density. The genome of the endosymbiont Sodalis glossinidius contains almost 50% pseudogenes containing mutations that putatively silence them at the genomic level. We have applied multiple omic strategies: combining single molecule DNA-sequencing and annotation; stranded RNA-sequencing and proteome analysis to better understand the transcriptional and translational landscape of Sodalis pseudogenes, and potential mechanisms for their control. Between 53% and 74% of the Sodalis transcriptome remains active in cell-free culture. Mean sense transcription from Coding Domain Sequences (CDS) is four-times greater than that from pseudogenes. Core-genome analysis of six Illumina sequenced Sodalis isolates from different host Glossina species shows pseudogenes make up ~40% of the 2,729 genes in the core genome, suggesting are stable and/or Sodalis is a recent introduction across the Glossina genus as a facultative symbiont. These data further shed light on the importance of transcriptional and translational control in deciphering host-microbe interactions, and demonstrate that pseudogenes are more complex than a simple degrading DNA sequence. For this reason, we show that combining genomics, transcriptomics and proteomics represents an important resource for studying prokaryotic genomes with a view to elucidating evolutionary adaptation to novel environmental niches.