A Continuum of Evolving De Novo Genes Drives Protein-Coding Novelty in Drosophila
暂无分享,去创建一个
Erich Bornberg-Bauer | E. Bornberg-Bauer | Brennen Heames | Jonathan Schmitz | Jonathan F. Schmitz | Brennen Heames
[1] Paul Theodor Pyl,et al. HTSeq—a Python framework to work with high-throughput sequencing data , 2014, bioRxiv.
[2] D. Karolchik,et al. The UCSC Genome Browser database: 2016 update , 2015, bioRxiv.
[3] Claudio Casola,et al. From De Novo to “De Nono”: The Majority of Novel Protein-Coding Genes Identified with Phylostratigraphy Are Old Genes or Recent Duplicates , 2018, Genome biology and evolution.
[4] Huifeng Jiang,et al. De Novo Origination of a New Protein-Coding Gene in Saccharomyces cerevisiae , 2008, Genetics.
[5] Chao Xie,et al. Fast and sensitive protein alignment using DIAMOND , 2014, Nature Methods.
[6] Lukasz Kurgan,et al. Genome‐scale prediction of proteins with long intrinsically disordered regions , 2014, Proteins.
[7] M. Nei,et al. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. , 2007, Molecular biology and evolution.
[8] Lili Zhang,et al. SmProt: a database of small proteins encoded by annotated coding and non‐coding RNA loci , 2017, Briefings Bioinform..
[9] L. Serrano,et al. Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins , 2004, Nature Biotechnology.
[10] C. Kosiol,et al. The life cycle of Drosophila orphan genes , 2014, eLife.
[11] Gregory D. Schuler,et al. Database resources of the National Center for Biotechnology , 2003, Nucleic Acids Res..
[12] César A. Hidalgo,et al. Proto-genes and de novo gene birth , 2012, Nature.
[13] D. Nurminsky,et al. Analysis of the Drosophila melanogaster Testes Transcriptome Reveals Coordinate Regulation of Paralogous Genes , 2008, Genetics.
[14] Sean R. Davis,et al. NCBI GEO: archive for functional genomics data sets—update , 2012, Nucleic Acids Res..
[15] Joel Dudley,et al. TimeTree: a public knowledge-base of divergence times among organisms , 2006, Bioinform..
[16] A. Elofsson,et al. The number of orphans in yeast and fly is drastically reduced by using combining searches in both proteomes and genomes , 2017, bioRxiv.
[17] S. Sayols,et al. The developmental proteome of Drosophila melanogaster , 2017, Genome research.
[18] Andrew D Kern,et al. Evidence for de Novo Evolution of Testis-Expressed Genes in the Drosophila yakuba/Drosophila erecta Clade , 2007, Genetics.
[19] Hideaki Sugawara,et al. The Sequence Read Archive , 2010, Nucleic Acids Res..
[20] Jianzhi Zhang,et al. Further Simulations and Analyses Demonstrate Open Problems of Phylostratigraphy , 2017, Genome biology and evolution.
[21] Andrew D Kern,et al. Novel genes derived from noncoding DNA in Drosophila melanogaster are frequently X-linked and exhibit testis-biased expression. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[22] Bartek Wilczynski,et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics , 2009, Bioinform..
[23] Manyuan Long,et al. New Genes in Drosophila Quickly Become Essential , 2010, Science.
[24] Eugene V Koonin,et al. The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages , 2009, Proceedings of the National Academy of Sciences.
[25] E. Bornberg-Bauer,et al. Incipient de novo genes can evolve from frozen accidents that escaped rapid transcript turnover , 2018, Nature Ecology & Evolution.
[26] Josephine A. Reinhardt,et al. De Novo ORFs in Drosophila Are Important to Organismal Fitness and Evolved Rapidly from Previously Non-coding Sequences , 2013, PLoS genetics.
[27] D. Tautz,et al. The evolutionary origin of orphan genes , 2011, Nature Reviews Genetics.
[28] Aaron R. Quinlan,et al. BIOINFORMATICS APPLICATIONS NOTE , 2022 .
[29] J. Masel,et al. Putatively Noncoding Transcripts Show Extensive Association with Ribosomes , 2011, Genome biology and evolution.
[30] Eve Syrkin Wurtele,et al. Recycling RNA-Seq Data to Identify Candidate Orphan Genes for Experimental Analysis , 2019 .
[31] J. Masel,et al. Young Genes are Highly Disordered as Predicted by the Preadaptation Hypothesis of De Novo Gene Birth , 2017, Nature Ecology &Evolution.
[32] Peer Bork,et al. Comparative Genome and Proteome Analysis of Anopheles gambiae and Drosophila melanogaster , 2002, Science.
[34] E. Bornberg-Bauer,et al. Evolutionary dynamics of simple sequence repeats across long evolutionary time scale in genus Drosophila , 2012 .
[35] D. Petrov,et al. Pervasive Natural Selection in the Drosophila Genome? , 2009, PLoS genetics.
[36] Z. Yang,et al. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. , 2000, Molecular biology and evolution.
[37] Jing Li,et al. Landscape of the Dark Transcriptome Revealed Through Re-mining Massive RNA-Seq Data , 2019, bioRxiv.
[38] Ying Chen Eyre-Walker,et al. Extensive translation of small Open Reading Frames revealed by Poly-Ribo-Seq , 2014, eLife.
[39] G. Fischer,et al. A Molecular Portrait of De Novo Genes in Yeasts , 2018, Molecular biology and evolution.
[40] Arne Elofsson,et al. High GC content causes orphan proteins to be intrinsically disordered , 2017, bioRxiv.
[41] T. Bosch,et al. More than just orphans: are taxonomically-restricted genes important in evolution? , 2009, Trends in genetics : TIG.
[42] L. Hurst,et al. Open questions in the study of de novo genes: what, how and why , 2016, Nature Reviews Genetics.
[43] Desmond G. Higgins,et al. GWIPS-viz: development of a ribo-seq genome browser , 2013, Nucleic Acids Res..
[44] Patrick G. A. Pedrioli,et al. A high-quality catalog of the Drosophila melanogaster proteome , 2007, Nature Biotechnology.
[45] Doron Lancet,et al. Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification , 2005, Bioinform..
[46] Jiří Vondrášek,et al. Random protein sequences can form defined secondary structures and are well-tolerated in vivo , 2017, Scientific Reports.
[47] T. Riemensperger,et al. Dopamine drives Drosophila sechellia adaptation to its toxic host , 2014, eLife.
[48] Ziheng Yang,et al. PAML: a program package for phylogenetic analysis by maximum likelihood , 1997, Comput. Appl. Biosci..
[49] Mihaela Zavolan,et al. Comparative assessment of methods for the computational inference of transcript isoform abundance from RNA-seq data , 2015, Genome Biology.
[50] Annamária F. Ángyán,et al. Estimating intrinsic structural preferences of de novo emerging random‐sequence proteins: Is aggregation the main bottleneck? , 2012, FEBS letters.
[51] Tomislav Domazet-Loso,et al. A phylostratigraphy approach to uncover the genomic history of major adaptations in metazoan lineages. , 2007, Trends in genetics : TIG.
[52] M. Albà,et al. Translation of neutrally evolving peptides provides a basis for de novo gene evolution , 2018, Nature Ecology & Evolution.
[53] J. Kocher,et al. CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model , 2013, Nucleic acids research.
[54] Arne Elofsson,et al. Remote homology detection of integral membrane proteins using conserved sequence features , 2007, Proteins.
[55] Mario Stanke,et al. Simultaneous gene finding in multiple genomes , 2016, Bioinform..
[56] Ning Ma,et al. BLAST+: architecture and applications , 2009, BMC Bioinformatics.
[57] A. Elofsson,et al. Identifying and quantifying orphan protein sequences in fungi. , 2010, Journal of molecular biology.
[58] Robert C. Edgar,et al. MUSCLE: multiple sequence alignment with high accuracy and high throughput. , 2004, Nucleic acids research.
[59] H. Bussemaker,et al. The human transcriptome map reveals extremes in gene density, intron length, GC content, and repeat pattern for domains of highly and weakly expressed genes. , 2003, Genome research.
[60] E. Myers,et al. Basic local alignment search tool. , 1990, Journal of molecular biology.
[61] Anne-Ruxandra Carvunis,et al. Synteny-based analyses indicate that sequence divergence is not the main source of orphan genes , 2020, eLife.
[62] Joshua G. Dunn,et al. Ribosome profiling reveals pervasive and regulated stop codon readthrough in Drosophila melanogaster , 2013, eLife.
[63] A. Barbadilla,et al. iMKT: the integrative McDonald and Kreitman test , 2019, Nucleic Acids Res..
[64] Li Zhao,et al. Testis single-cell RNA-seq reveals the dynamics of de novo gene transcription and germline mutational bias in Drosophila , 2019, bioRxiv.
[65] A. McLysaght,et al. New genes from non-coding sequence: the role of de novo protein-coding genes in eukaryotic evolutionary innovation , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.
[66] Giulia Antonazzo,et al. FlyBase 2.0: the next generation , 2018, Nucleic Acids Res..
[67] D. Tautz,et al. Fast turnover of genome transcription across evolutionary time exposes entire non-coding DNA to de novo gene emergence , 2016, eLife.
[68] E. Bornberg-Bauer,et al. Detection of orphan domains in Drosophila using "hydrophobic cluster analysis". , 2015, Biochimie.
[69] I. Longden,et al. EMBOSS: the European Molecular Biology Open Software Suite. , 2000, Trends in genetics : TIG.
[70] Jianzhi Zhang,et al. Phylostratigraphic bias creates spurious patterns of genome evolution. , 2015, Molecular biology and evolution.
[71] E. Bornberg-Bauer,et al. Fact or fiction: updates on how protein-coding genes might emerge de novo from previously non-coding DNA , 2017, F1000Research.
[72] Kuldip K. Paliwal,et al. Capturing non‐local interactions by long short‐term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility , 2017, Bioinform..
[73] M. Moore. From Birth to Death: The Complex Lives of Eukaryotic mRNAs , 2005, Science.
[74] A. Elofsson,et al. The number of orphans in yeast and fly is drastically reduced by using combining searches in both proteomes and genomes , 2017, bioRxiv.
[75] E. Bornberg-Bauer,et al. Mechanisms and Dynamics of Orphan Gene Emergence in Insect Genomes , 2013, Genome biology and evolution.
[76] Sònia Casillas,et al. PopFly: the Drosophila population genomics browser , 2017, Bioinform..
[77] Li Zhao,et al. Origin and Spread of de Novo Genes in Drosophila melanogaster Populations , 2014, Science.
[78] A. McLysaght,et al. Computational Prediction of De Novo Emerged Protein-Coding Genes. , 2018, Methods in molecular biology.
[79] Zhiyu Peng,et al. Rapid evolution of protein diversity by de novo origination in Oryza , 2019, Nature Ecology & Evolution.
[80] D. Bartel,et al. Widespread changes in the posttranscriptional landscape at the Drosophila oocyte-to-embryo transition. , 2014, Cell reports.
[81] Baojun Wu,et al. Tracing the De Novo Origin of Protein-Coding Genes in Yeast , 2018, mBio.
[82] Yun Ding,et al. On the origin of new genes in Drosophila. , 2008, Genome research.
[83] Zsuzsanna Dosztányi,et al. IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding , 2018, Nucleic Acids Res..
[84] J. Masel,et al. Foldability of a Natural De Novo Evolved Protein. , 2017, Structure.
[85] Anna-Sophie Fiston-Lavier,et al. Drosophila melanogaster recombination rate calculator. , 2010, Gene.
[86] M. Albà,et al. Long non-coding RNAs as a source of new peptides , 2014, eLife.
[87] J. M. Comeron,et al. The Many Landscapes of Recombination in Drosophila melanogaster , 2012, PLoS genetics.
[88] Anne-Ruxandra Carvunis,et al. De novo gene birth , 2019, PLoS genetics.
[89] C. Landry,et al. Differences Between the Raw Material and the Products of de Novo Gene Birth Can Result from Mutational Biases , 2019, Genetics.
[90] Alisha K Holloway,et al. Recently Evolved Genes Identified From Drosophila yakuba and D. erecta Accessory Gland Expressed Sequence Tags , 2005, Genetics.