The Protein‐Coding Human Genome: Annotating High‐Hanging Fruits

Abstract

The major transcript variants of human protein-coding genes are annotated to a certain degree of accuracy combining manual curation, transcript data, and proteomics evidence. However, there is considerable disagreement on the annotation of about 2000 genes-they can be protein-coding, noncoding, or pseudogenes-and on the annotation of most of the predicted alternative transcripts. Pure transcriptome mapping approaches seem to be limited in discriminating functional expression from noise. These limitations have partially been overcome by dedicated algorithms to detect alternative spliced micro-exons and wobble splice variants. Recently, knowledge about splice mechanism and protein structure are incorporated into an algorithm to predict neighboring homologous exons, often spliced in a mutually exclusive manner. Predicted exons are evaluated by transcript data, structural compatibility, and evolutionary conservation, revealing hundreds of novel coding exons and splice mechanism re-assignments. The emerging human pan-genome is necessitating distinctive annotations incorporating differences between individuals and between populations.

Besca, a single-cell transcriptomics analysis toolkit to accelerate translational research

“…Setting aside the controversy in cell type definition ( 110 ), our work already provides tools and best practices to achieve better reference annotations and to share the gene signatures that capture the knowledge about how they were derived, which is novel compared to most current studies. As the human reference genome, which does not ultimately reflect a human genome consensus ( 111 ), but serves many practical purposes ( 112 ), accelerated genomic research, such reference cell type annotations will accelerate our understanding of biological systems even though they reflect only a subset of a cell's characteristics.…”

The effects of sequencing depth on the assembly of coding and noncoding transcripts in the human genome

“…However, using the GENCODE transcript set as a reference increased the sensitivity, with the sensitivity of coding transcripts of some samples going above 60% and the noncoding sensitivity of some samples reaching 43%. Previous studies have reported that some genuine transcripts are missing in the GENCODE annotation [25,42,47,48]. Therefore, we repeated the analyses using the hPSC filtered transcript set [42].…”

Metastatic EMT Phenotype Is Governed by MicroRNA-200-Mediated Competing Endogenous RNA Networks

“…While mutations in driver genes do facilitate the development of pro-metastatic traits, the baffling complexity of the mechanism seems to originate from crosstalk between regulatory networks. The recent revelation that less than 2% of the human genome is related to protein-coding genes has thus emphasized the importance of unravelling these networks beyond frontline transcriptional control in order to fully comprehend cancer dissemination [ 3 ]. Here, we set out to examine the dynamics of the main intrinsic regulatory mechanisms governing cancer-related epithelial–mesenchymal transition (EMT) and identify the stoichiometry of vital players in the competing endogenous (ceRNA) network with a focus on cancer progression and metastasis.…”