Dhanoa JK, Sethi RS, Verma R, Arora JS, Mukhopadhyay CS. Long non-coding RNA: its evolutionary relics and biological implications in mammals: a review. J Anim Sci Technol. 2018;60(1):25.
Necsulea A, Kaessmann H. Evolutionary dynamics of coding and non-coding transcriptomes. Nat Rev Genet. 2014;15(11):734–48.
Patthy L. Genome evolution and the evolution of exon-shuffling — a review. Gene. 1999;238(1):103–14.
Ulitsky I. Evolution to the rescue: using comparative genomics to understand long non-coding RNAs. Nat Rev Genet. 2016;17(10):601–14.
Ulitsky I, Bartel DP. lincRNAs: Genomics, Evolution, and Mechanisms. Cell. 2013;154(1):26–46.
Zhang J, Yang J-R. Determinants of the rate of protein sequence evolution. Nat Rev Genet. 2015;16(7):409–20.
Fraser P, Bickmore W. Nuclear organization of the genome and the potential for gene regulation. Nature. 2007;447(7143):413–7.
Haraksingh RR, Snyder MP. Impacts of variation in the human genome on gene regulation. J Mol Biol. 2013;425(21):3970–7.
He L, Hannon GJ. MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet. 2004;5(7):522–31.
Li Y, Hu M, Shen Y. Gene regulation in the 3D genome. Hum Mol Genet. 2018;27(R2):R228–33.
Pennacchio LA, Rubin EM. Genomic strategies to identify mammalian regulatory sequences. Nat Rev Genet. 2001;2(2):100–9.
Simonis M, Klous P, Splinter E, Moshkin Y, Willemsen R, de Wit E, et al. Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture–on-chip (4C). Nat Genet. 2006;38(11):1348–54.
Smallwood A, Ren B. Genome organization and long-range regulation of gene expression by enhancers. Curr Opin Cell Biol. 2013;25(3):387–94.
Würtele H, Chartrand P. Genome-wide scanning of HoxB1-associated loci in mouse ES cells using an open-ended Chromosome Conformation Capture methodology. Chromosome Res. 2006;14(5):477–95.
Zhao Z, Tavoosidana G, Sjölinder M, Göndör A, Mariano P, Wang S, et al. Circular chromosome conformation capture (4C) uncovers extensive networks of epigenetically regulated intra- and interchromosomal interactions. Nat Genet. 2006;38(11):1341–7.
Belokopytova P, Fishman V. Predicting genome architecture: challenges and solutions. Front Genet. 2021;22(11):617202.
Chen K, Rajewsky N. The evolution of gene regulation by transcription factors and microRNAs. Nat Rev Genet. 2007;8(2):93–103.
Hobert O. Gene regulation by transcription factors and microRNAs. Science. 2008;319(5871):1785–6.
Kim TH, Ren B. Genome-wide analysis of protein-DNA interactions. Annu Rev Genomics Hum Genet. 2006;7(1):81–102.
Baack EJ, Rieseberg LH. A genomic view of introgression and hybrid speciation. Curr Opin Genet Dev. 2007;17(6):513–8.
Cain AK, Barquist L, Goodman AL, Paulsen IT, Parkhill J, van Opijnen T. A decade of advances in transposon-insertion sequencing. Nat Rev Genet. 2020;21(9):526–40.
Farré M, Ruiz-Herrera A. The plasticity of genome architecture. Genes. 2020;11(12):1413.
Matz MV. Fantastic beasts and how to sequence them: ecological genomics for obscure model organisms. Trends Genet. 2018;34(2):121–32.
Hooper ET, Carleton MD. Hooper & Carleton 1976. Available from: https://deepblue.lib.umich.edu/bitstream/handle/2027.42/56395/MP151.pdf?sequence=1. [Cited 2017 Aug 16].
Fernández-Vargas M, Tang-Martínez Z, Phelps SM. Singing, allogrooming, and allomarking behaviour during inter- and intra-sexual encounters in the Neotropical short-tailed singing mouse (Scotinomys teguina). Behaviour. 2011;148(8):945–65.
Miller JR, Engstrom MD. Vocal Stereotypy and Singing Behavior in Baiomyine Mice. J Mammal. 2007;88(6):1447–65.
Pasch B, George AS, Hamlin HJ, Guillette LJ, Phelps SM. Androgens modulate song effort and aggression in Neotropical singing mice. Horm Behav. 2011;59(1):90–7.
Pasch B, George AS, Campbell P, Phelps SM. Androgen-dependent male vocal performance influences female preference in Neotropical singing mice. Anim Behav. 2011;82(2):177–83.
Campbell P, Pasch B, Pino JL, Crino OL, Phillips M, Phelps SM. Geographic variation in the songs of neotropical singing mice: testing the relative importance of drift and local adaptation. Evolution. 2010;64(7):1955–72.
Okobi DE, Banerjee A, Matheson AMM, Phelps SM, Long MA. Motor cortical control of vocal interaction in neotropical singing mice. Science. 2019;363(6430):983–8.
Burkhard TT, Westwick RR, Phelps SM. Adiposity signals predict vocal effort in Alston’s singing mice. Proc R Soc B Biol Sci. 1877;2018(285):20180090.
Giglio EM, Phelps SM. Leptin regulates song effort in Neotropical singing mice (Scotinomys teguina). Anim Behav. 2020;1(167):209–19.
Smith SK, Burkhard TT, Phelps SM. A comparative characterization of laryngeal anatomy in the singing mouse. J Anat. Available from: http://onlinelibrary.wiley.com/doi/abs/10.1111/joa.13315. [Cited 2021 Jan 6].
Zimin AV, Marçais G, Puiu D, Roberts M, Salzberg SL, Yorke JA. The MaSuRCA genome assembler. Bioinformatics. 2013;29(21):2669–77.
Smit, AFA, Hubley, R & Green, P. RepeatMasker Open-4.0.2013–2015. http://www.repeatmasker.org.
Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol. 2011;29(7):644–52.
Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity. Nat Protoc. 2013;8(8). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3875132/. [Cited 2021 Jan 20].
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinforma Oxf Engl. 2013;29(1):15–21.
Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics. 2015;31(19):3210–2.
Picard Tools – By Broad Institute. Available from: http://broadinstitute.github.io/picard/. [Cited 2021 Aug 30].
Anders S, Pyl PT, Huber W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31(2):166–9.
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–2.
Davis CA, Hitz BC, Sloan CA, Chan ET, Davidson JM, Gabdank I, et al. The Encyclopedia of DNA elements (ENCODE): data portal update. Nucleic Acids Res. 2018;46(D1):D794-801.
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57–74.
R: The R Project for Statistical Computing. Available from: https://www.r-project.org/. [Cited 2021 Aug 30].
Wright RM, Kenkel CD, Dunn CE, Shilling EN, Bay LK, Matz MV. Intraspecific differences in molecular stress responses and coral pathobiome contribute to mortality under bacterial challenge in Acropora millepora. Sci Rep. 2017;7(1):2609.
Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019;28(11):1947–51.
Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. Available from: http://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkaa970/5943834. [Cited 2020 Dec 6].
Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000;28(1):27–30.
Matz MV. Rank-based gene ontology analysis with adaptive clustering. 2021. Available from: https://github.com/z0on/GO_MWU. [Cited 2021 Aug 19].
Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H, et al. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res. 2019;47(W1):W191–8.
Reimand J, Isserlin R, Voisin V, Kucera M, Tannus-Lopes C, Rostamianfar A, et al. Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap. Nat Protoc. 2019;14(2):482–517.
Merico D, Isserlin R, Stueker O, Emili A, Bader GD. Enrichment map: a network-based method for gene-set enrichment visualization and interpretation. PLoS One. 2010;5(11):e13984.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.
Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK, Hannick LI, et al. Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res. 2003;31(19):5654–66.
The UniVec Database. Available from: https://www-ncbi-nlm-nih-gov.ezproxy.lib.utexas.edu/tools/vecscreen/univec/. [Cited 2021 Aug 30].
Roberts A, Pimentel H, Trapnell C, Pachter L. Identification of novel transcripts in annotated genomes using RNA-Seq. Bioinformatics. 2011;27(17):2325–9.
Roberts A, Trapnell C, Donaghey J, Rinn JL, Pachter L. Improving RNA-Seq expression estimates by correcting for fragment bias. Genome Biol. 2011;12(3):R22.
Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28(5):511–5.
Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol. 2013;31(1):46–53.
Kovaka S, Zimin AV, Pertea GM, Razaghi R, Salzberg SL, Pertea M. Transcriptome assembly from long-read RNA-seq alignments with StringTie2. Genome Biol. 2019;20(1):1–3.
Majoros WH, Pertea M, Salzberg SL. TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics. 2004;20(16):2878–9.
Lukashin AV, Borodovsky M. GeneMark. hmm: new solutions for gene finding. Nucleic Acids Res. 1998;26(4):1107–15.
Stanke M, Diekhans M, Baertsch R, Haussler D. Using native and syntenically mapped cDNA alignments to improve de novo gene finding. Bioinformatics. 2008;24(5):637–44.
Li H. Protein-to-genome alignment with miniprot. Bioinformatics. 2023;39(1):btad014.
Suzek BE, Huang H, McGarvey P, Mazumder R, Wu CH. UniRef: comprehensive and non-redundant UniProt reference clusters. Bioinformatics. 2007;23(10):1282–8.
Haas BJ, Salzberg SL, Zhu W, Pertea M, Allen JE, Orvis J, White O, Buell CR, Wortman JR. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biol. 2008;9:1–22.
Haas BJ, Zeng Q, Pearson MD, Cuomo CA, Wortman JR. Approaches to fungal genome annotation. Mycology. 2011;2(3):118–41.
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10.
UniProt. Available from: https://www.uniprot.org/. [Cited 2021 Aug 30].
Bortolin L. Extraction of nuclei from brain tissue. 2020. Available from: https://www.protocols.io/view/extraction-of-nuclei-from-brain-tissue-2srged6. [Cited 2021 Aug 30].
Zheng GXY, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R, et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun. 2017;8(1):14049.
Stuart T, Butler A, Hoffman P, Hafemeister C, Papalexi E, Mauck WM, et al. Comprehensive integration of single-cell data. Cell. 2019;177(7):1888-1902.e21.
van der Maaten L, Hinton G. Visualizing data using t-SNE. J Mach Learn Res. 2008;9(11):2579–605.
Becht E, McInnes L, Healy J, Dutertre C-A, Kwok IWH, Ng LG, et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2019;37(1):38–44.
McInnes L, Healy J, Melville J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. ArXiv180203426 Cs Stat. 2020. Available from: http://arxiv.org/abs/1802.03426. [Cited 2021 Jul 16].
Almanzar N, Antony J, Baghel AS, Bakerman I, Bansal I, Barres BA, et al. A single-cell transcriptomic atlas characterizes ageing tissues in the mouse. Nature. 2020;583(7817):590–5.
Yao Z, van Velthoven CTJ, Nguyen TN, Goldy J, Sedeno-Cortes AE, Baftizadeh F, et al. A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation. Cell. 2021;184(12):3222-3241.e26.
Zhang Y, Chen K, Sloan SA, Bennett ML, Scholze AR, O’Keeffe S, et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J Neurosci. 2014;34(36):11929–47.
Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature. 2008;456(7218):53–9.
Bentley DR. Whole-genome re-sequencing. Curr Opin Genet Dev. 2006;16(6):545–52.
Goodwin S, McPherson JD, McCombie WR. Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet. 2016;17(6):333–51.
Merker JD, Wenger AM, Sneddon T, Grove M, Zappala Z, Fresard L, et al. Long-read genome sequencing identifies causal structural variation in a Mendelian disease. Genet Med. 2018;20(1):159–63.
Roberts RJ, Carneiro MO, Schatz MC. The advantages of SMRT sequencing. Genome Biol. 2013;14(6):405.
Jain M, Olsen HE, Paten B, Akeson M. The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biol. 2016;17(1):239.
Rang FJ, Kloosterman WP, de Ridder J. From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy. Genome Biol. 2018;19(1):90.
Yuan Y, Bayer PE, Batley J, Edwards D. Improvements in Genomic Technologies: Application to Crop Genomics. Trends Biotechnol. 2017;35(6):547–58.
Jain M, Koren S, Miga KH, Quick J, Rand AC, Sasani TA, et al. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nat Biotechnol. 2018;36(4):338–45.
Chinwalla AT, Cook LL, Delehaunty KD, Fewell GA, Fulton LA, Fulton RS, et al. Initial sequencing and comparative analysis of the mouse genome. Nature. 2002;420(6915):520–62.
Long AD, Baldwin-Brown J, Tao Y, Cook VJ, Balderrama-Gutierrez G, Corbett-Detig R, et al. The genome of Peromyscus leucopus, natural host for Lyme disease and other emerging infections. Sci Adv. 2019;5(7):eaaw6441.
Zheng DJ, Okobi DE, Shu R, Agrawal R, Smith SK, Long MA, et al. Mapping the vocal circuitry of Alston’s singing mouse with pseudorabies virus. bioRxiv. 2021 Jul 17;2021.07.16.452718.
Li R, Fan W, Tian G, Zhu H, He L, Cai J, et al. The sequence and de novo assembly of the giant panda genome. Nature. 2010;463(7279):311–7.
Tamazian G, Simonov S, Dobrynin P, Makunin A, Logachev A, Komissarov A, et al. Annotated features of domestic cat – Felis catus genome. GigaScience. 2014;3(1). Available from: https://doi.org/10.1186/2047-217X-3-13. [Cited 2021 Sep 1].
Geppert M, Goda Y, Hammer RE, Li C, Rosahl TW, Stevens CF, et al. Synaptotagmin I: A major Ca2+ sensor for transmitter release at a central synapse. Cell. 1994;79(4):717–27.
Maximov A, Südhof TC. Autonomous Function of Synaptotagmin 1 in Triggering Synchronous Release Independent of Asynchronous Release. Neuron. 2005;48(4):547–54.
Yoshihara M, Littleton JT. Synaptotagmin I Functions as a Calcium Sensor to Synchronize Neurotransmitter Release. Neuron. 2002;36(5):897–908.
Erlander MG, Tillakaratne NJ, Feldblum S, Patel N, Tobin AJ. Two genes encode distinct glutamate decarboxylases. Neuron. 1991;7(1):91–100.
Johnson DS, Mortazavi A, Myers RM, Wold B. Genome-Wide Mapping of in Vivo Protein-DNA Interactions. Science. 2007;316(5830):1497–502.
Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat Methods. 2013;10(12):1213–8.
Booker TR, Jackson BC, Keightley PD. Detecting positive selection in the genome. BMC Biol. 2017;15(1):98.
Fu W, Akey JM. Selection and adaptation in the human genome. Annu Rev Genomics Hum Genet. 2013;14(1):467–89.
Pavlidis P, Alachiotis N. A survey of methods and tools to detect recent and strong positive selection. J Biol Res-Thessalon. 2017;24(1):7.
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