Publication List

@article{Ruiz-Orera2020b,
title = {Evolution of New Proteins From Translated sORFs in Long Non-Coding RNAs},
author = {Jorge Ruiz-Orera, José Luis Villanueva-Cañas, M.Mar Albà},
year = {2020},
date = {2020-06-01},
journal = {Experimental Cell Research, 391 (1), pp. 111940},
keywords = {de novo gene, lncRNA}
}

@article{Reixachs-Solé2020,
title = {Ribosome Profiling at Isoform Level Reveals Evolutionary Conserved Impacts of Differential Splicing on the Proteome},
author = {Marina Reixachs-Solé, Jorge Ruiz-Orera, M.Mar Albà, Eduardo Eyras},
url = {https://www.nature.com/articles/s41467-020-15634-w},
isbn = { 10.1038/s41467-020-15634-w },
year = {2020},
date = {2020-04-14},
journal = {Nature Communications},
volume = {11},
number = {1},
pages = {1768},
abstract = {The differential production of transcript isoforms from gene loci is a key cellular mechanism. Yet, its impact in protein production remains an open question. Here, we describe ORQAS (ORF quantification pipeline for alternative splicing), a pipeline for the translation quantification of individual transcript isoforms using ribosome-protected mRNA fragments (ribosome profiling). We find evidence of translation for 40-50% of the expressed isoforms in human and mouse, with 53% of the expressed genes having more than one translated isoform in human, and 33% in mouse. Differential splicing analysis revealed that about 40% of the splicing changes at RNA level are concordant with changes in translation. Furthermore, orthologous cassette exons between human and mouse preserve the directionality of the change, and are enriched in microexons in a comparison between glia and glioma. ORQAS leverages ribosome profiling to uncover a widespread and evolutionarily conserved impact of differential splicing on translation, particularly of microexon-containing isoforms. },
keywords = {cancer, de novo gene, isoform, lncRNA, microexon, sORF}
}

@article{Ruiz-Orera2020,
title = {Evolution of New Proteins From Translated sORFs in Long Non-Coding RNAs },
author = {Jorge Ruiz-Orera, José Luis Villanueva-Cañas, M.Mar Albà},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0014482720301452?via%3Dihub},
year = {2020},
date = {2020-03-07},
journal = {Experimental Cell Research},
volume = {391},
number = {1},
pages = {111940},
abstract = {High throughput RNA sequencing techniques have revealed that a large fraction of the genome is transcribed into long non-coding RNAs (lncRNAs). Unlike canonical protein-coding genes, lncRNAs do not contain long open reading frames (ORFs) and tend to be poorly conserved across species. However, many of them contain small ORFs (sORFs) that exhibit translation signatures according to ribosome profiling or proteomics data. These sORFs are a source of putative novel proteins; some of them may confer a selective advantage and be maintained over time, a process known as de novo gene birth. Here we review the mechanisms by which randomly occurring sORFs in lncRNAs can become new functional proteins. },
keywords = {de novo gene, lncRNA, microprotein, ribosome profiling, sORF}
}

@article{Blevins2019,
title = {Frequent birth of de novo genes in the compact yeast genome},
author = {William R. Blevins, Jorge Ruiz-Orera, Xavier Messeguer, Bernat Blasco-Moreno, José Luis Villanueva-Cañas, Lorena Espinar, Juana Díez, Lucas B. Carey, M. Mar Albà},
url = {https://doi.org/10.1101/575837 },
year = {2019},
date = {2019-03-13},
journal = {bioRxiv, March 13},
abstract = {Evidence has accumulated that some genes originate directly from previously non-genic sequences, or de novo, rather than by the duplication or fusion of existing genes. However, how de novo genes emerge and eventually become functional is largely unknown. Here we perform the first study on de novo genes that uses transcriptomics data from eleven different yeast species, all grown identically in both rich media and in oxidative stress conditions. The genomes of these species are densely-packed with functional elements, leaving little room for the co-option of genomic sequences into new transcribed loci. Despite this, we find that at least 213 transcripts (~5%) have arisen de novo in the past 20 million years of evolution of baker’s yeast-or approximately 10 new transcripts every million years. Nearly half of the total newly expressed sequences are generated from regions in which both DNA strands are used as templates for transcription, explaining the apparent contradiction between the limited ‘empty’ genomic space and high rate of de novo gene birth. In addition, we find that 40% of these de novo transcripts are actively translated and that at least a fraction of the encoded proteins are likely to be under purifying selection. This study shows that even in very highly compact genomes, de novo transcripts are continuously generated and can give rise to new functional protein-coding genes.},
keywords = {de novo gene, RNA-Seq, Saccharomyces cerevisiae, yeast}
}

@article{Ruiz-Orera2018,
title = {Translation of neutrally evolving peptides provides a basis for de novo gene evolution},
author = {Jorge Ruiz-Orera, Pol Grau-Verdaguer, José Luis Villanueva-Cañas, Xavier Messeguer, M.Mar Albà},
url = {https://www.nature.com/articles/s41559-018-0506-6},
year = {2018},
date = {2018-03-19},
journal = {Nature Ecology and Evolution},
volume = {2},
pages = {890–896},
abstract = {Accumulating evidence indicates that some protein-coding genes have originated de novo from previously non-coding genomic sequences. However, the processes underlying de novo gene birth are still enigmatic. In particular, the appearance of a new functional protein seems highly improbable unless there is already a pool of neutrally evolving peptides that are translated at significant levels and that can at some point acquire new functions. Here, we use deep ribosome-profiling sequencing data, together with proteomics and single nucleotide polymorphism information, to search for these peptides. We find hundreds of open reading frames that are translated and that show no evolutionary conservation or selective constraints. These data suggest that the translation of these neutrally evolving peptides may be facilitated by the chance occurrence of open reading frames with a favourable codon composition. We conclude that the pervasive translation of the transcriptome provides plenty of material for the evolution of new functional proteins.},
keywords = {codon usage bias, de novo gene, natural selection, ribosome profiling}
}

@article{Albà2017,
title = {New genes and functional innovation in mammals},
author = { José Luis Villanueva-Cañas,
Jorge Ruiz-Orera,
M.Isabel Agea,
Maria Gallo,
David Andreu,
M.Mar Albà},
url = {https://academic.oup.com/gbe/article/doi/10.1093/gbe/evx136/3983271/New-genes-and-functional-innovation-in-mammals},
year = {2017},
date = {2017-07-21},
journal = {Genome Biology and Evolution},
volume = {9},
pages = { 1886–1900},
abstract = {The birth of genes that encode new protein sequences is a major source of evolutionary innovation. However, we still understand relatively little about how these genes come into being and which functions they are selected for. To address these questions, we have obtained a large collection of mammalian-specific gene families that lack homologues in other eukaryotic groups. We have combined gene annotations and de novo transcript assemblies from 30 different mammalian species, obtaining ∼6,000 gene families. In general, the proteins in mammalian-specific gene families tend to be short and depleted in aromatic and negatively charged residues. Proteins which arose early in mammalian evolution include milk and skin polypeptides, immune response components, and proteins involved in reproduction. In contrast, the functions of proteins which have a more recent origin remain largely unknown, despite the fact that these proteins also have extensive proteomics support. We identify several previously described cases of genes originated de novo from noncoding genomic regions, supporting the idea that this mechanism frequently underlies the evolution of new protein-coding genes in mammals. Finally, we show that most young mammalian genes are preferentially expressed in testis, suggesting that sexual selection plays an important role in the emergence of new functional genes.},
keywords = {de novo gene, innovation, mammal, protein function}
}

@conference{Ruiz-Orera2017,
title = {De novo gene evolution: How do we transition from non-coding to coding?},
author = {Jorge Ruiz-Orera, José Luis Villanueva-Cañas, William Blevins, M.Mar Albà},
url = {https://doi.org/10.7287/peerj.preprints.3031v2},
year = {2017},
date = {2017-06-28},
journal = {PeerJ Preprints},
volume = {PeerJ preprints 5},
number = {e3031v2},
abstract = {Recent years have witnessed the discovery of protein–coding genes which appear to have evolved de novo from previously non-coding sequences. This has changed the long-standing view that coding sequences can only evolve from other coding sequences. However, there are still many open questions regarding how new protein-coding sequences can arise from non-genic DNA.

Two prerequisites for the birth of a new functional protein-coding gene are that the corresponding DNA fragment is transcribed and that it is also translated. Transcription is known to be pervasive in the genome, producing a large number of transcripts that do not correspond to conserved protein-coding genes, and which are usually annotated as long non-coding RNAs (lncRNA). Recently, sequencing of ribosome protected fragments (Ribo-Seq) has provided evidence that many of these transcripts actually translate small proteins. We have used mouse non-synonymous and synonymous variation data to estimate the strength of purifying selection acting on the translated open reading frames (ORFs). Whereas a subset of the lncRNAs are likely to actually be true protein-coding genes (and thus previously misclassified), the bulk of lncRNAs code for proteins which show variation patterns consistent with neutral evolution. We also show that the ORFs that have a more favorable, coding-like, sequence composition are more likely to be translated than other ORFs in lncRNAs. This study provides strong evidence that there is a large and ever-changing reservoir of lowly abundant proteins; some of these peptides may become useful and act as seeds for de novo gene evolution.},
note = {The SMBE 2017 Collection},
keywords = {de novo gene, long non-coding RNA, Ribo-Seq, ribosome profiling}
}

@conference{Blevins2017,
title = {Comparative transcriptomics and ribo-seq: Looking at de novo gene emergence in Saccharomycotina},
author = {Willam Blevins, M.Mar Albà, Lucas Carey},
year = {2017},
date = {2017-06-20},
journal = {PeerJ Preprints},
volume = {PeerJ preprints 5},
number = {e3030v1},
abstract = {
In de novo gene emergence, a segment of non-coding DNA undergoes a series of changes which enables transcription, potentially leading to a new protein that could eventually acquire a novel function. Due to their recent origins, young de novo genes have no homology with other genes. Furthermore, de novo genes may not initially be under the same selective constraints as other genes. Dozens of de novo genes have recently been identified in many diverse species; however, the mechanisms leading to their appearance are not yet well understood. To study this phenomenon, we have performed deep RNA sequencing (RNA-seq) on 11 species of yeast from the phylum of Ascomycota in both rich media and oxidative stress conditions. Furthermore, we performed ribosome profiling (Ribo-seq) experiments in both conditions with S. cerevisiae. These data have been used to classify the conservation of genes at different depths in the yeast phylogeny. Hundreds of genes in each species were novel (unannotated), and many were identified as putative de novo genes; these candidates were then tested for signals of translation using our Ribo-seq data. We show that putative de novo genes have different properties relative to phylogenetically conserved genes. This comparative phylotranscriptomic analysis advances our understanding of de novo gene origins.
},
note = {The SMBE 2017 Collection},
keywords = {de novo gene, yeast}
}

@article{Domazet-Lošo2017,
title = {No evidence for phylostratigraphic bias impacting inferences on patterns of gene emergence and evolution},
author = {Tomislav Domazet-Lošo, Anne-Ruxandra Carvunis, M.Mar Albà, Martin Sebastijan Šestak, Robert Bakarić, Rafik Neme, Diethard Tautz},
url = {http://mbe.oxfordjournals.org/content/early/2017/01/10/molbev.msw284.abstract},
year = {2017},
date = {2017-01-12},
journal = {Molecular Biology and Evolution},
volume = {doi: 10.1093/molbev/msw284},
abstract = {Phylostratigraphy is a computational framework for dating the emergence of DNA and protein sequences in a phylogeny. It has been extensively applied to make inferences on patterns of genome evolution, including patterns of disease gene evolution, ontogeny and de novo gene origination. Phylostratigraphy typically relies on BLAST searches along a species tree, but new simulation studies have raised concerns about the ability of BLAST to detect remote homologues and its impact on phylostratigraphic inferences. Here, we re-assessed these simulations. We found that, even with a possible overall BLAST false negative rate between 11-15%, the large majority of sequences assigned to a recent evolutionary origin by phylostratigraphy is unaffected by technical concerns about BLAST. Where the results of the simulations did cast doubt on previously reported findings, we repeated the original analyses but now excluded all questionable sequences. The originally described patterns remained essentially unchanged. These new analyses strongly support phylostratigraphic inferences, including: genes that emerged after the origin of eukaryotes are more likely to be expressed in the ectoderm than in the endoderm or mesoderm in Drosophila, and the de novo emergence of protein-coding genes from non-genic sequences occurs through proto-gene intermediates in yeast. We conclude that BLAST is an appropriate and sufficiently sensitive tool in phylostratigraphic analysis that does not appear to introduce significant biases into evolutionary pattern inferences. },
keywords = {BLAST, de novo gene, Homology, Sequence Analysis}
}

@article{Ruiz-Orera2015b,
title = {Origins of de novo genes in human and chimpanzee},
author = {Ruiz-Orera, Jorge, Hernandez-Rodriguez, Jessica, Chiva, Cristina, Sabidó, Eduard, Kondova, Ivanela, Bontrop, Ronald, Marqués-Bonet, Tomàs, Albà, M.Mar},
url = {http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005721},
year = {2015},
date = {2015-12-31},
journal = {Plos Genetics},
volume = {11},
number = {12},
pages = {e1005721},
keywords = {chimpanzee, de novo gene, Evolution, Humans, lncRNA, Promoter, proteomics, ribosome profiling, RNA-Seq, transcription factor binding site, transcriptomics}
}