Article series: Non-coding RNA

Evolution to the rescue: using comparative genomics to understand long non-coding RNAs

Journal name:
Nature Reviews Genetics
Year published:
Published online
Corrected online


Long non-coding RNAs (lncRNAs) have emerged in recent years as major players in a multitude of pathways across species, but it remains challenging to understand which of them are important and how their functions are performed. Comparative sequence analysis has been instrumental for studying proteins and small RNAs, but the rapid evolution of lncRNAs poses new challenges that demand new approaches. Here, I review the lessons learned so far from genome-wide mapping and comparisons of lncRNAs across different species. I also discuss how comparative analyses can help us to understand lncRNA function and provide practical considerations for examining functional conservation of lncRNA genes.

At a glance


  1. A generic pipeline for the identification of lncRNAs from RNA-seq data.
    Figure 1: A generic pipeline for the identification of lncRNAs from RNA-seq data.

    Long non-coding RNAs (lncRNAs) are identified separately in each species and in each tissue or sample. RNA sequencing (RNA-seq) reads are either first mapped to the genome and then assembled into transcripts (genome-guided assembly, such as that performed by Cufflinks120), or first assembled into transcripts (de novo assembly, such as that performed by Trinity121) and then mapped to the genome. Transcripts from all samples are then merged, multiple filtering steps remove various artefacts and protein-coding genes, and the remaining transcripts are classified into one of the lncRNA classes. lincRNAs, long intergenic non-coding RNAs.

  2. Classes of lncRNA conservation.
    Figure 2: Classes of lncRNA conservation.

    a | Proposed classes of sequence conservation among long non-coding RNAs (lncRNAs) and their correlation with genomic features. See the main text for a description of the individual features and references to the publications supporting the positive and negative correlations with the level of conservation. b | High conservation of exon–intron structure; for example, the MIAT (myocardial infarction associated transcript; also known as GOMAFU) lncRNA locus in human and mouse. The RNA sequencing (RNA-seq) track shows the coverage of reads from the human cortex from the Human Proteome Atlas (HPA) transcriptome database122 and the mouse cerebellar granular neurons123. Phylogenetic P value (PhyloP) scores124, which describe base-wise conservation during vertebrate evolution, were taken from the University of California, Santa Cruz (UCSC) Genome Browser. Whole-genome alignment (WGA) track shows alignable regions between human and mouse genomes. c | A lncRNA with conserved sequence, but divergent exon-intron structure; for example, a lncRNA found downstream of the ONECUT1 gene in human and mouse. Human adult liver RNA-seq is from the HPA and mouse adult liver RNA-seq is from the Encyclopedia of DNA Elements (ENCODE) project. d | A lncRNA with a conserved position and very limited sequence conservation: the forkhead box F1 (FOXF1) gene and the FOXF1 adjacent non-coding developmental regulatory RNA (FENDRR) lncRNA. RNA-seq from adult lung from the HPA and ENCODE projects. e | A mouse lncRNA with no evidence of expression in human, the Haunt (also known as Halr1 or linc-Hoxa1) locus. RNA-seq from human125 and mouse126 embryonic stem (ES) cells. TEs, transposable elements.

  3. Pathways for origination and diversification of lncRNA loci.
    Figure 3: Pathways for origination and diversification of lncRNA loci.

    Possible scenarios for the formation of new long non-coding RNA (lncRNA) loci. An ancestral lncRNA locus can be duplicated (part Aa). An ancestral protein-coding gene can lose its coding potential owing to a sequence change, but the transcriptional programme in the locus can be retained (part Ab). A transposable element (TE) carrying a functional promoter, or sequences resembling one, can be integrated next to sequences encoding cryptic exons (part Ac). An unstable transcript product of bidirectional transcription can be stabilized by changes favouring splicing and the formation of a stable product (part Ad). Last, a combination of genetic changes occurring in the vicinity of each other can lead to the formation of promoter and RNA processing elements in an orientation that is required for lncRNA production (part Ae). Two main known mechanisms for lncRNA locus complexity increase, exonization of TEs (part Ba) and local sequence duplications (part Bb). Lightning signs indicate a series of mutations and the blue rectangles indicate newly integrated TEs; pA indicates a polyadenylation signal.

  4. Manifestations of conserved functionality in lncRNA genes.
    Figure 4: Manifestations of conserved functionality in lncRNA genes.

    a | Loss of a homologous long non-coding RNA (lncRNA) in different species can result in the same phenotype. b | Homologous lncRNAs can act through a conserved mechanism. c | Target genes regulated by the lncRNAs can be the same. d | The loss of function of a lncRNA in one species can be rescued by the exogenous expression of the homologue from a different species. lncRNAs are shown as curved lines, with a 5′ cap (circle) and 3′ polyadenlylated tail (A(n)). lncRNAs from different species are shown in blue versus yellow. Conserved function is indicated by the green bar and triangles; red dashed lines indicate experimental loss-of-function of a lncRNA; and the black hexagon represents an RNA-binding protein.

Change history

Corrected online 06 September 2016
In the original version of this article, the sentence “A study using a different background model recently reported more than 4 million regions that are evolving under selection to preserve secondary structure” (section ‘Secondary structure and its conservation’) was missing a citation of reference 65 (Smith, M. A., Gesell, T., Stadler, P. F. & Mattick, J. S. Widespread purifying selection on RNA structure in mammals. Nucleic Acids Res. 41, 8220–8236 (2013)). This citation dropped out during journal typesetting of the article and has now been reinstated. The editors apologize for this error.


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  1. Department of Biological Regulation, Weizmann Institute of Science, 234 Herzl Street, Rehovot 76100, Israel.

    • Igor Ulitsky

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  • Igor Ulitsky

    Igor Ulitsky is a senior scientist at the Weizmann Institute of Science in Rehovot, Israel, where he holds the Sygnet Career Development Chair for Bioinformatics. Before establishing his own laboratory at the Weizmann Institute in 2013, he obtained his Ph.D. in computational genomics at Tel Aviv University, Israel, with Ron Shamir, and held a postdoctoral position in the laboratory of David Bartel at the Whitehead Institute for Biomedical Research in Cambridge, Massachusetts, USA. His research is on the evolution, functions and modes of action of long non-coding RNAs. To investigate these topics his laboratory is combining computational and experimental methods across multiple systems, from human and mouse embryonic stem cells to in vivo models in mice, zebrafish and insects. Igor Ulitsky's homepage

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