New publication: Long non-coding RNA atlas published in Nature!

Schmeier Research Group // Massey University

PUBLICATION

Today, the FANTOM collaboration published their latest work in Nature. Elena and Sebastian were fortunate enough to be able to work together with a great team of researchers on this exciting project. Here, we studied a poorly understood and highly controversial class of genes, known as long non-coding RNAs (lncRNAs). There is a long standing debate in the scientific community questioning if most of these lncRNAs are functional. Here, we generated a comprehensive collection of ~28000 lncRNAs and summarised, for the first time, their expression patterns across the major human cell types and tissues. We found compelling evidence of evolutionary selection and links with major diseases, including cancer, hinting at potential functionality of many of these genes.

The findings of the study have far reaching implications. To date, several lncRNAs have been implicated in many important biological processes as well as diseases, including cancer. The data generated here provides a platform for selecting additional lncRNAs for further targeted studies. The lncRNA catalogue is available at http://fantom.gsc.riken.jp/cat.

We like to congratulate Chung-Chau Hon and Alistair Forrest and the rest of the FANTOM team for their excellent work!

About FANTOM

The FANTOM project (functional annotation of the mammalian genome) is a RIKEN-initiative launched in 1998 by genomics pioneer Professor Yoshihide Hayashizaki (http://fantom.gsc.riken.jp/). Now completing this 5th stage, FANTOM5 has aimed to provide the first holistic view of transcriptional regulatory network models for the majority of the cell types that make up a human. To do this the RIKEN organisers recruited a multidisciplinary network of experts in primary cell biology and bioinformatics. Over a 5-year period, the group met 3 times in Yokohama and used weekly teleconferences and emails to manage the project.

Publications // latest

MinION Sequencing of colorectal cancer tumour microbiomes – a comparison with amplicon-based and RNA-Sequencing. PLoS One, 2020, accepted.

Molecular subtyping improves prognostication of Stage 2 colorectal cancer. BMC Cancer, 2019, 19, 1155

DeePEL: Deep learning architecture to recognize p-lncRNA and e-lncRNA promoters. In proceedings: IEEE International Conference on Bioinformatics and Biomedicine, 2019, B516, accepted.

News&Blog // latest

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[ 20180703 | news ] New publication: Nature Methods

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