Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-09T06:40:44.318Z Has data issue: false hasContentIssue false

10 - Perspective: Systematics in the age of genomics

from Part III - Next Generation Challenges and Questions

Published online by Cambridge University Press:  05 June 2016

By
Antonis Rokas
Edited by
Peter D. Olson ,
Joseph Hughes  and
James A. Cotton
Antonis Rokas
Affiliation:
Vanderbilt University, Nashville, Tennessee, USA
Peter D. Olson
Affiliation:
Natural History Museum, London
Joseph Hughes
Affiliation:
University of Glasgow
James A. Cotton
Affiliation:
Wellcome Trust Sanger Institute, Cambridge
Get access

Summary

The advent of the data age

The study of the DNA and protein record is a key component of systematic biology research. Recent technological advances in genome science have enabled researchers to routinely generate unprecedented, genome-scale, amounts of sequence data, opening the floodgates for the study of the genome content and function of any organism across the Tree of Life (ToL) (Rokas and Abbot 2009). The main catalyst for these changes has been the development of several different so-called next generation DNA sequencing technologies (NGS) that are capable of producing orders of magnitude more data, for orders of magnitude lower cost than Sanger sequencing approaches (Glenn 2011).

Astonishingly, the amount of sequence data that a single NGS machine currently produces in a few days is larger than the total amount of sequence data collected by individual users via traditional methods that is deposited in GenBank (Gilad et al. 2009). This phenomenal increase in data generation has not only enabled the collection of more sequence data, but also the systematic collection of new types of sequence data (e.g. microRNAs, SINEs, LINEs and other rare genomic changes) that were previously laborious to obtain, as well as the development of new protocols (e.g. RAD-Tags, Baird et al. 2008) and computational pipelines (e.g. phylogenomics, Hittinger et al. 2010b; metagenomics, Patil et al. 2011) for doing so. Furthermore, NGS technologies yield not only qualitative information about the sequence of every DNA fragment analysed, but also quantitative information about the relative abundance of each DNA fragment in the library sequenced (Rokas and Abbot 2009).

The abundance of NGS data, their qualitative and quantitative nature, and their applicability to the study of any organism for which fresh DNA or RNA is available (this volume, Chapter 14) has enabled researchers to adopt NGS not only for answering old questions with new data rigour, but also for formulating and tackling a new ‘generation’ of questions (Rokas and Abbot 2009).

Type
Chapter
Information
Next Generation Systematics , pp. 219 - 228
Publisher: Cambridge University Press
Print publication year: 2016

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abzhanov, A., Extavour, C. G., Groover, A., et al. (2008). Are we there yet? Tracking the development of new model systems. Trends in Genetics, 24, 353–60.CrossRefGoogle ScholarPubMed
Baird, N. A., Etter, P. D., Atwood, T. S., et al. (2008). Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS One, 3, e3376.CrossRefGoogle ScholarPubMed
Benson, D. A., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J. and Sayers, E. W. (2009). GenBank. Nucleic Acids Research, 37, D26–31.CrossRefGoogle ScholarPubMed
Campbell, M. A., Rokas, A. and Slot, J. C. (2012). Horizontal transfer and death of a fungal secondary metabolic gene cluster. Genome Biology and Evolution, 4, 289–93.CrossRefGoogle ScholarPubMed
Darwin, C. (1859). On the Origin of Species. London, John Murray.Google Scholar
Domazet-Loso, T., Brajkovic, J. and Tautz, D. (2007). A phylostratigraphy approach to uncover the genomic history of major adaptations in metazoan lineages. Trends in Genetics, 23, 533–9.CrossRefGoogle ScholarPubMed
Domazet-Loso, T. and Tautz, D. (2010a). A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns. Nature, 468, 815–8.CrossRefGoogle ScholarPubMed
Domazet-Loso, T. and Tautz, D. (2010b). Phylostratigraphic tracking of cancer genes suggests a link to the emergence of multicellularity in metazoa. BMC Biology, 8, 66.CrossRefGoogle Scholar
Edwards, S. V. (2009). Is a new and general theory of molecular systematics emerging?Evolution, 63, 1–19.CrossRefGoogle ScholarPubMed
Felsenstein, J. (1981). Evolutionary trees from DNA sequences: a maximum likelihood approach. Journal of Molecular Evolution, 17, 368–76.CrossRefGoogle ScholarPubMed
Felsenstein, J. (1985). Confidence limits on phylogenies: an approach using the bootstrap. Evolution, 39, 783–91.CrossRefGoogle ScholarPubMed
Felsenstein, J. (2003). Inferring Phylogenies. Sunderland, MA, Sinauer.Google Scholar
Fleischmann, R. D., Adams, M. D., White, O., et al. (1995). Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science, 269, 496–512.CrossRefGoogle ScholarPubMed
Genome 10K Community of Scientists (2009). Genome 10K, a proposal to obtain whole-genome sequence for 10,000 vertebrate species. Journal of Heredity, 100, 659–74.Google Scholar
Gibbons, J. G., Janson, E. M., Hittinger, C. T., et al. (2009). Benchmarking next-generation transcriptome sequencing for functional and evolutionary genomics. Molecular Biology and Evolution, 26, 2731–44.CrossRefGoogle ScholarPubMed
Gilad, Y., Pritchard, J. K. and Thornton, K. (2009). Characterizing natural variation using next-generation sequencing technologies. Trends in Genetics, 25, 463–71.CrossRefGoogle ScholarPubMed
Glenn, T. C. (2011). Field guide to next-generation DNA sequencers. Molecular Ecology Resources, 11, 759–69.CrossRefGoogle ScholarPubMed
Goffeau, A., Barrell, B. G., Bussey, H., et al. (1996). Life with 6000 genes. Science, 274, 546, 563–7.CrossRefGoogle ScholarPubMed
Hillis, D. M. (2010). Phylogenetic progress and applications of the tree of life. In Evolution Since Darwin: The First 150 Years, ed. Bell, M., Futuyma, D. J., Eanes, W. F. and Levinton, J. S.. Sunderland, MA, Sinauer; pp. 421–49.Google Scholar
Hittinger, C. T., Goncalves, P., Sampaio, J. P., et al. (2010a). Remarkably ancient balanced polymorphisms in a multi-locus gene network. Nature, 464, 54–8.CrossRefGoogle Scholar
Hittinger, C. T., Johnston, M., Tossberg, J. T. and Rokas, A. (2010b). Leveraging skewed transcript abundance by RNA-Seq to increase the genomic depth of the tree of life. Proceedings of the National Academy of Sciences of the United States of America, 107, 1476–81.Google ScholarPubMed
Huber, J. A., Mark Welch, D. B., Morrison, H. G., et al. (2007). Microbial population structures in the deep marine biosphere. Science, 318, 97–100.CrossRefGoogle ScholarPubMed
Kahn, S. D. (2011). On the future of genomic data. Science, 331, 728–9.CrossRefGoogle ScholarPubMed
Koonin, E. V. (2009). Evolution of genome architecture. The International Journal of Biochemistry and Cell Biology, 41, 298–306.CrossRefGoogle ScholarPubMed
Kumar, S., Filipski, A. J., Battistuzzi, F. U., Kosakovsky Pond, S. L. and Tamura, K. (2012). Statistics and truth in phylogenomics. Molecular Biology and Evolution, 29, 457–72.CrossRefGoogle ScholarPubMed
Lee, E. K., Cibrian-Jaramillo, A., Kolokotronis, S. O., et al. (2011). A functional phylogenomic view of the seed plants. PLoS Genetics, 7, e1002411.CrossRefGoogle ScholarPubMed
Lynch, M. (2007). The Origins of Genome Architecture. Sunderland, MA, Sinauer.Google Scholar
Lynch, M., Sung, W., Morris, K., et al. (2008). A genome-wide view of the spectrum of spontaneous mutations in yeast. Proceedings of the National Academy of Sciences of the United States of America, 105, 9272–7.Google ScholarPubMed
Maddison, W. P. (1997). Gene trees in species trees. Systematic Biology, 46, 523–36.CrossRefGoogle Scholar
Moore, M. J., Bell, C. D., Soltis, P. S. and Soltis, D. E. (2007). Using plastid genome-scale data to resolve enigmatic relationships among basal angiosperms. Proceedings of the National Academy of Sciences of the United States of America, 104, 19363–8.Google ScholarPubMed
Nehrt, N. L., Clark, W. T., Radivojac, P. and Hahn, M. W. (2011). Testing the ortholog conjecture with comparative functional genomic data from mammals. PLoS Computational Biology, 7, e1002073.CrossRefGoogle ScholarPubMed
Patil, K. R., Haider, P., Pope, P. B., et al. (2011). Taxonomic metagenome sequence assignment with structured output models. Nature Methods, 8, 191–2.CrossRefGoogle ScholarPubMed
Pena-Castillo, L. and Hughes, T. R. (2007). Why are there still over 1000 uncharacterized yeast genes?Genetics, 176, 7–14.CrossRefGoogle ScholarPubMed
Proctor, L. M. (2011). The Human Microbiome Project in 2011 and beyond. Cell, Host and Microbe, 10, 287–91.CrossRefGoogle ScholarPubMed
Rokas, A. and Abbot, P. (2009). Harnessing genomics for evolutionary insights. Trends in Ecology and Evolution, 24, 192–200.CrossRefGoogle ScholarPubMed
Rokas, A. and Carroll, S. B. (2006). Bushes in the tree of life. PLoS Biology, 4, e352.CrossRefGoogle ScholarPubMed
Rokas, A. and Chatzimanolis, S. (2008). From gene-scale to genome-scale phylogenetics: the data flood in, but the challenges remain. Methods in Molecular Biology, 422, 1–12.Google ScholarPubMed
Rokas, A., King, N., Finnerty, J. and Carroll, S. B. (2003a). Conflicting phylogenetic signals at the base of the metazoan tree. Evolution and Development, 5, 346–59.CrossRefGoogle ScholarPubMed
Rokas, A., Williams, B. L., King, N. and Carroll, S. B. (2003b). Genome-scale approaches to resolving incongruence in molecular phylogenies. Nature, 425, 798–804.CrossRefGoogle ScholarPubMed
Sanderson, M. J. (2008). Phylogenetic signal in the eukaryotic tree of life. Science, 321, 121–3.CrossRefGoogle ScholarPubMed
Scannell, D. R., Zill, O. A., Rokas, A., et al. (2011). The awesome power of yeast evolutionary genetics: new genome sequences and strain resources for the Saccharomyces sensu stricto genus. G3, 1, 11–25.CrossRefGoogle ScholarPubMed
Slot, J. C. and Rokas, A. (2010). Multiple GAL pathway gene clusters evolved independently and by different mechanisms in fungi. Proceedings of the National Academy of Sciences of the United States of America, 107, 10136–41.Google ScholarPubMed
Slot, J. C. and Rokas, A. (2011). Horizontal transfer of a large and highly toxic secondary metabolic gene cluster between fungi. Current Biology, 21, 134–9.CrossRefGoogle ScholarPubMed
Vera, J. C., Wheat, C. W., Fescemyer, H. W., et al. (2008). Rapid transcriptome characterization for a nonmodel organism using 454 pyrosequencing. Molecular Ecology, 17, 1636–47.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×