BACKGROUND: New genes continuously emerge from non-coding DNA or by diverging from existing genes, but most of them are rapidly lost and only a few become fixed within the population. We hypothesized that young genes are subject to transcriptional and post-transcriptional regulation to limit their expression and minimize their exposure to purifying selection. RESULTS: We performed a protein-based homology search across the tree of life to determine the evolutionary age of protein-coding genes present in the rice genome. We found that young genes in rice have relatively low expression levels, which can be attributed to distal enhancers, and closed chromatin conformation at their transcription start sites (TSS). The chromatin in TSS regions can be re-modeled in response to abiotic stress, indicating conditional expression of young genes. Furthermore, transcripts of young genes in Arabidopsis tend to be targeted by nonsense-mediated RNA decay, presenting another layer of regulation limiting their expression. CONCLUSIONS: These data suggest that transcriptional and post-transcriptional mechanisms contribute to the conditional expression of young genes, which may alleviate purging selection while providing an opportunity for phenotypic exposure and functionalization.

Central European Institute of Technology Masaryk University Brno Czech Republic

Department of Botany University of Delhi Delhi 110007 India

Zobrazit více v PubMed

Dujon B. The yeast genome project: what did we learn? Trends Genet. 1996;12(7):263–270. doi: 10.1016/0168-9525(96)10027-5. PubMed DOI

Fischer D, Eisenberg D. Finding families for genomic ORFans. Bioinformatics. 1999;15(9):759–762. doi: 10.1093/bioinformatics/15.9.759. PubMed DOI

Stein JC, Yu Y, Copetti D, Zwickl DJ, Zhang L, Zhang CJ, et al. Genomes of 13 domesticated and wild rice relatives highlight genetic conservation, turnover and innovation across the genus Oryza. Nat Genet. 2018;50(2):285. doi: 10.1038/s41588-018-0040-0. PubMed DOI

Arendsee ZW, Li L, Wurtele ES. Coming of age: orphan genes in plants. Trends Plant Sci. 2014;19(11):698–708. doi: 10.1016/j.tplants.2014.07.003. PubMed DOI

Rodelsperger C, Prabh N, Sommer RJ. New gene origin and deep taxon phylogenomics: opportunities and challenges. Trends Genet. 2019;35(12):914–922. doi: 10.1016/j.tig.2019.08.007. PubMed DOI

Tautz D, Domazet-Loso T. The evolutionary origin of orphan genes. Nat Rev Genet. 2011;12(10):692–702. doi: 10.1038/nrg3053. PubMed DOI

Van Oss SB, Carvunis AR. De novo gene birth. Plos Genet. 2019;15:5. PubMed PMC

Schlotterer C. Genes from scratch - the evolutionary fate of de novo genes. Trends Genet. 2015;31(4):215–219. doi: 10.1016/j.tig.2015.02.007. PubMed DOI PMC

Cai JJ, Petrov DA. Relaxed purifying selection and possibly high rate of adaptation in primate lineage-specific genes. Genome Biol Evol. 2010;2:393–409. doi: 10.1093/gbe/evq019. PubMed DOI PMC

Wolf YI, Novichkov PS, Karev GP, Koonin EV, Lipman DJ. The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages. P Natl Acad Sci USA. 2009;106(18):7273–7280. doi: 10.1073/pnas.0901808106. PubMed DOI PMC

Drummond DA, Bloom JD, Adami C, Wilke CO, Arnold FH. Why highly expressed proteins evolve slowly. P Natl Acad Sci USA. 2005;102(40):14338–14343. doi: 10.1073/pnas.0504070102. PubMed DOI PMC

Drummond DA, Wilke CO. Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell. 2008;134(2):341–352. doi: 10.1016/j.cell.2008.05.042. PubMed DOI PMC

Palmieri N, Kosiol C, Schlotterer C. The life cycle of Drosophila orphan genes. Elife. 2014;3:e01311. PubMed PMC

Werner MS, Sieriebriennikov B, Prabh N, Loschko T, Lanz C, Sommer RJ. Young genes have distinct gene structure, epigenetic profiles, and transcriptional regulation. Genome Res. 2018;28(11):1675–1687. doi: 10.1101/gr.234872.118. PubMed DOI PMC

Donoghue MT, Keshavaiah C, Swamidatta SH, Spillane C. Evolutionary origins of Brassicaceae specific genes in Arabidopsis thaliana. Bmc Evol Biol. 2011;11:47. PubMed PMC

Majic P, Payne JL. Enhancers facilitate the birth of de novo genes and gene integration into regulatory networks. Mol Biol Evol. 2020;37(4):1165–1178. doi: 10.1093/molbev/msz300. PubMed DOI PMC

Vinckenbosch N, Dupanloup I, Kaessmann H. Evolutionary fate of retroposed gene copies in the human genome. P Natl Acad Sci USA. 2006;103(9):3220–3225. doi: 10.1073/pnas.0511307103. PubMed DOI PMC

Cui X, Lv Y, Chen ML, Nikoloski Z, Twell D, Zhang DB. Young genes out of the male: an insight from evolutionary age analysis of the pollen transcriptome. Mol Plant. 2015;8(6):935–945. doi: 10.1016/j.molp.2014.12.008. PubMed DOI

Arendsee Z, Li J, Singh U, Seetharam A, Dorman K, Wurtele ES. phylostratr: a framework for phylostratigraphy. Bioinformatics. 2019;35(19):3617–3627. doi: 10.1093/bioinformatics/btz171. PubMed DOI

Zhang JY, Zhou Q. On the regulatory evolution of new genes throughout their life history. Mol Biol Evol. 2019;36(1):15–27. doi: 10.1093/molbev/msy206. PubMed DOI

Li ZW, Chen X, Wu Q, Hagmann J, Han TS, Zou YP, et al. On the origin of de novo genes in Arabidopsis thaliana populations. Genome Biol Evol. 2016;8(7):2190–2202. doi: 10.1093/gbe/evw164. PubMed DOI PMC

Zhu B, Zhang WL, Zhang T, Liu B, Jiang JM. Genome-wide prediction and validation of intergenic enhancers in Arabidopsis using open chromatin signatures. Plant Cell. 2015;27(9):2415–2426. doi: 10.1105/tpc.15.00537. PubMed DOI PMC

Sun J, He N, Niu L, Huang Y, Shen W, Zhang Y, et al. Global quantitative mapping of enhancers in rice by STARR-seq. Genomics Proteomics Bioinformatics. 2019;17(2):140–153. doi: 10.1016/j.gpb.2018.11.003. PubMed DOI PMC

Andersson R, Gebhard C, Miguel-Escalada I, Hoof I, Bornholdt J, Boyd M, et al. An atlas of active enhancers across human cell types and tissues. Nature. 2014;507(7493):455. doi: 10.1038/nature12787. PubMed DOI PMC

Spitz F, Furlong EEM. Transcription factors: from enhancer binding to developmental control. Nat Rev Genet. 2012;13(9):613–626. doi: 10.1038/nrg3207. PubMed DOI

Villar D, Berthelot C, Aldridge S, Rayner TF, Lukk M, Pignatelli M, et al. Enhancer evolution across 20 mammalian species. Cell. 2015;160(3):554–566. doi: 10.1016/j.cell.2015.01.006. PubMed DOI PMC

Prud’homme B, Gompel N, Carroll SB. Emerging principles of regulatory evolution. P Natl Acad Sci USA. 2007;104:8605–8612. doi: 10.1073/pnas.0700488104. PubMed DOI PMC

Carvunis AR, Rolland T, Wapinski I, Calderwood MA, Yildirim MA, Simonis N, et al. Proto-genes and de novo gene birth. Nature. 2012;487(7407):370–374. doi: 10.1038/nature11184. PubMed DOI PMC

Santos ME, Le Bouquin A, Crumiere AJJ, Khila A. Taxon-restricted genes at the origin of a novel trait allowing access to a new environment. Science. 2017;358(6361):386–389. doi: 10.1126/science.aan2748. PubMed DOI

Chen SD, Krinsky BH, Long MY. New genes as drivers of phenotypic evolution. Nat Rev Genet. 2013;14(9):645–660. doi: 10.1038/nrg3521. PubMed DOI PMC

Yang HW, He BZ, Ma HJ, Tsaur SC, Ma CY, Wu Y, et al. Expression profile and gene age jointly shaped the genome-wide distribution of premature termination codons in a Drosophila melanogaster population. Mol Biol Evol. 2015;32(1):216–228. doi: 10.1093/molbev/msu299. PubMed DOI PMC

He F, Jacobson A. Nonsense-mediated mRNA decay: degradation of defective transcripts is only part of the story. Annu Rev Genet. 2015;49:339–366. doi: 10.1146/annurev-genet-112414-054639. PubMed DOI PMC

Lloyd JPB. The evolution and diversity of the nonsense-mediated mRNA decay pathway. F1000Res. 2018;7:1299. doi: 10.12688/f1000research.15872.1. PubMed DOI PMC

Raxwal VK, Simpson CG, Gloggnitzer J, Entinze JC, Guo WB, Zhang RX, et al. Nonsense-mediated RNA decay factor UPF1 is critical for posttranscriptional and translational gene regulation in Arabidopsis. Plant Cell. 2020;32(9):2725–2741. doi: 10.1105/tpc.20.00244. PubMed DOI PMC

Riehs-Kearnan N, Gloggnitzer J, Dekrout B, Jonak C, Riha K. Aberrant growth and lethality of Arabidopsis deficient in nonsense-mediated RNA decay factors is caused by autoimmune-like response. Nucleic Acids Res. 2012;40(12):5615–5624. doi: 10.1093/nar/gks195. PubMed DOI PMC

Chantarachot T, Sorenson RS, Hummel M, Ke HY, Kettenburg AT, Chen DN, et al. DHH1/DDX6-like RNA helicases maintain ephemeral half-lives of stress-response mRNAs. Nat Plants. 2020;6(6):675. doi: 10.1038/s41477-020-0681-8. PubMed DOI

Raxwal VK, Riha K. Nonsense mediated RNA decay and evolutionary capacitance. Biochim Biophys Acta. 2016;1859(12):1538–1543. doi: 10.1016/j.bbagrm.2016.09.001. PubMed DOI

Hug N, Longman D, Caceres JF. Mechanism and regulation of the nonsense-mediated decay pathway. Nucleic Acids Res. 2016;44(4):1483–1495. doi: 10.1093/nar/gkw010. PubMed DOI PMC

Raxwal VK, Ghosh S, Singh S, Katiyar-Agarwal S, Goel S, Jagannath A, et al. Abiotic stress-mediated modulation of the chromatin landscape in Arabidopsis thaliana. J Exp Bot. 2020;71(17):5280–5293. doi: 10.1093/jxb/eraa286. PubMed DOI

Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–U54. doi: 10.1038/nmeth.1923. PubMed DOI PMC

Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137. PubMed PMC

Zhu LJ, Gazin C, Lawson ND, Pages H, Lin SM, Lapointe DS, et al. ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data. Bmc Bioinformatics. 2010;11:237. PubMed PMC

Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016;34(5):525–527. doi: 10.1038/nbt.3519. PubMed DOI

Guo WB, Tzioutziou NA, Stephen G, Milne I, Calixto CPG, Waugh R, et al. 3D RNA-seq: a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists. Rna Biol. 2021;18(11):1574–1587. doi: 10.1080/15476286.2020.1858253. PubMed DOI PMC

Sorenson RS, Deshotel MJ, Johnson K, Adler FR, Sieburth LE. Arabidopsis mRNA decay landscape arises from specialized RNA decay substrates, decapping-mediated feedback, and redundancy. P Natl Acad Sci USA. 2018;115(7):E1485–E1E94. doi: 10.1073/pnas.1712312115. PubMed DOI PMC

Raxwal VK, Singh S, Agarwal M, Riha K. Landscape of open chromatin regions in Rice upon exposure to abiotic stresses. 2022.

Fang Y, Wang X, Wang L, Pan X, Xiao J, Wang XE, et al. Functional characterization of open chromatin in bidirectional promoters of rice. Sci Rep. 2016;6:32088. PubMed PMC