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Biology subjects

Uszczynska-Ratajczak, B.

Publications and source records attributed to Uszczynska-Ratajczak, B..

2 recordsLinked to original sources

Nearly all new protein-coding predictions in the CHESS database are not protein-coding

In a 2018 paper posted to bioRxiv, Pertea et al. presented the CHESS database, a new catalog of human gene annotations that includes 1,178 new protein-coding predictions. These are based on evidence of transcription in human tissues and homology to earlier annotations in human and other mammals. Here, we reanalyze the evidence used by CHESS, and find that nearly all protein-coding predictions are false positives. We find that 86% overlap transposons marked by RepeatMasker that are known to frequently result in false positive protein-coding predictions. More than half are homologous to only nine Alu-derived primate sequences corresponding to an erroneous and previously withdrawn Pfam protein domain. The entire set shows poor evolutionary conservation and PhyloCSF protein-coding evolutionary signatures indistinguishable from noncoding RNAs, indicating lack of protein-coding constraint. Only four predictions are supported by mass spectrometry evidence, and even those matches are inconclusive. Overall, the new protein-coding predictions are unsupported by any credible experimental or evolutionary evidence of function, result primarily from homology to genes incorrectly classified as protein-coding, and are unlikely to encode functional proteins.

genomics

High-throughput annotation of full-length long noncoding RNAs with Capture Long-Read Sequencing (CLS)

Accurate annotations of genes and their transcripts is a foundation of genomics, but no annotation technique presently combines throughput and accuracy. As a result, reference gene collections remain incomplete: many gene models are fragmentary, while thousands more remain uncatalogued-particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), combining targeted RNA capture with third-generation long-read sequencing. We present an experimental re-annotation of the GENCODE intergenic lncRNA population in matched human and mouse tissues, resulting in novel transcript models for 3574 / 561 gene loci, respectively. CLS approximately doubles the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enable us to definitively characterize the genomic features of lncRNAs, including promoter- and gene-structure, and protein-coding potential. Thus CLS removes a longstanding bottleneck of transcriptome annotation, generating manual-quality full-length transcript models at high-throughput scales.\n\nAbbreviations

genomics