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-76fb5796d-9pm4c Total loading time: 0 Render date: 2024-04-26T08:28:51.388Z Has data issue: false hasContentIssue false

1 - An introduction to systems genetics

Published online by Cambridge University Press:  05 July 2015

By
Florian Markowetz  and
Michael Boutros
Edited by
Florian Markowetz  and
Michael Boutros
Florian Markowetz
Affiliation:
Cancer Research UK Cambridge Institute
Michael Boutros
Affiliation:
German Cancer Research Center, Heidelberg
Florian Markowetz
Affiliation:
Cancer Research UK Cambridge Institute
Michael Boutros
Affiliation:
German Cancer Research Center, Heidelberg
Get access

Summary

Systems genetics is an emerging field based on old approaches going back to the genetic studies performed by Gregor Mendel (Mendel 1866). Mendel's experiments primarily focused on explaining inheritance of single traits and their phenotypes – for example how specific genetic alleles influence colour or size of peas – but recently developed technologies can comprehensively dissect the genetic architecture of complex traits and quantify how genes interact to shape phenotypes by using natural variation or experimental perturbations as a basis to understand links from genotypes to phenotypes. This exciting new area has recently been termed ‘systems genetics’ (Civelek & Lusis 2014).

While the basic, underlying questions are not new, systems genetics builds upon major methodological advances that facilitate the measurement of genotypes and pheno-types in a previously unforeseen and comprehensive manner. With this arsenal at hand, one of the major aims of systems genetics is to understand “how genetic information is integrated, coordinated and ultimately transmitted through molecular, cellular and physiological networks to enable the higher-order functions and emergent properties of biological systems” (Nadeau & Dudley 2011).

Definition of systems genetics

Systems genetics is born out of a synthesis of multiple fields: it integrates approaches of genetics, genomics, systems biology and ‘phenomics’, that is, our increased ability to obtain quantitative and detailed measurements on a broad spectrum of phenotypes. One of the first papers using the term ‘systems genetics’ defines it as “the integration and anchoring of multi-dimensional data-types to underlying genetic variation” (Threadgill 2006). Since then, many studies have aimed at integrating genome-wide data across many different levels, and possibly different environments, in approaches that are closely related to quantitative genetics.

In our view, a systems genetic approach should bring together three dimensions: it should combine (i) a genome-wide analysis with (ii) many quantitative phenotypes, both at the molecular and organismal level, (iii) in many different conditions or environments (Fig. 1.1).

Type
Chapter
Information
Systems Genetics
Linking Genotypes and Phenotypes
 , pp. 1 - 11
Publisher: Cambridge University Press
Print publication year: 2015

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

Ali, H. R., Irwin, M., Morris, L., Dawson, S.-J., Blows, F. M. et al. (2013), ‘Astronomical algorithms for automated analysis of tissue protein expression in breast cancer.’Br J Cancer 108 (3), 602–612.CrossRefGoogle Scholar
Avery, L., & Wasserman, S., (1992), ‘Ordering gene function: the interpretation of epistasis in regulatory hierarchies.’Trends Genet 8 (9), 312–316.CrossRefGoogle Scholar
Ayroles, J. F., Carbone, M. A., Stone, E. A., Jordan, K. W., Lyman, R. F. et al. (2009), ‘Systems genetics of complex traits in Drosophila melanogaster.’Nat Genet 41 (3), 299–307.CrossRefGoogle Scholar
Barabási, A.-L. & Oltvai, Z. N. (2004), ‘Network biology: understanding the cells functional organization.’Nat Rev Genet 5 (2), 101–113.CrossRefGoogle Scholar
Baryshnikova, A., Costanzo, M., Myers, C. L., Andrews, B., & Boone, C., (2013), ‘Genetic interaction networks: toward an understanding of heritability.’Annu Rev Genomics Hum Genet 14, 111–133.CrossRefGoogle Scholar
Bateson, W., (1909), Mendel's principles of heredity, Cambridge University Press.CrossRefGoogle Scholar
Beck, A. H., Sangoi, A. R., Leung, S., Marinelli, R. J., Nielsen, T. O. et al. (2011), ‘Systematic analysis of breast cancer morphology uncovers stromal features associated with survival.’Sci Transl Med 3 (108), 108–113.CrossRefGoogle Scholar
Berns, K., Hijmans, E. M., Mullenders, J., Brummelkamp, T. R., Velds, A., et al. (2004), ‘A largescale RNAi screen in human cells identifies new components of the p53 pathway.’Nature 428(6981), 431–437.CrossRefGoogle Scholar
Boutros, M., & Ahringer, J., (2008), ‘The art and design of genetic screens: RNA interference.’Nat Rev Genet 9 (7), 554–566.CrossRefGoogle Scholar
Boutros, M., Kiger, A. A., Armknecht, S., Kerr, K., Hild, M., et al. (2004), ‘Genome-wide RNAi analysis of growth and viability in Drosophila cells.’Science 303(5659), 832–835.CrossRefGoogle Scholar
Califano, A., Butte, A. J., Friend, S., Ideker, T., & Schadt, E., (2012), ‘Leveraging models of cell regulation and GWAS data in integrative network-based association studies.’Nat Genet 44 (8), 841–847.CrossRefGoogle Scholar
Celniker, S. E., Dillon, L. A. L., Gerstein, M. B., Gunsalus, K. C., Henikoff, S., et al. (2009), ‘Unlocking the secrets of the genome.’Nature 459(7249), 927–930.CrossRefGoogle Scholar
Cheung, H. W., Cowley, G. S.,Weir, B. A., Boehm, J. S., Rusin, S., et al. (2011), ‘Systematic investigation of genetic vulnerabilities across cancer cell lines reveals lineage-specific dependencies in ovarian cancer.’Proc Natl Acad Sci USA 108 (30), 12 372–12 377.CrossRefGoogle Scholar
Cheung, V. G. & Spielman, R. S. (2009), ‘Genetics of human gene expression: mapping DNA variants that influence gene expression.’Nat Rev Genet 10 (9), 595–604.CrossRefGoogle Scholar
Civelek, M., & Lusis, A. J. (2014), ‘Systems genetics approaches to understand complex traits.’Nat Rev Genet 15 (1), 34–48.CrossRefGoogle Scholar
Cordell, H. J. (2002), ‘Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans.’Hum Mol Genet 11 (20), 2463–2468.CrossRefGoogle Scholar
Cordell, H. J. (2009), ‘Detecting gene–gene interactions that underlie human diseases.’Nat Rev Genet 10 (6), 392–404.CrossRefGoogle Scholar
Costanzo, M., Baryshnikova, A., Bellay, J., Kim, Y., Spear, E., et al. (2010), ‘The genetic landscape of a cell.’Science 327(5964), 425.CrossRefGoogle Scholar
Curtis, C., Shah, S. P., Chin, S. -F.Turashvili, G., Rueda, O. M. et al. (2012), ‘The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups.’Nature 486(7403), 346–352.CrossRefGoogle Scholar
Eichler, E. E., Flint, J., Gibson, G., Kong, A., Leal, S. M. et al. (2010), ‘Missing heritability and strategies for finding the underlying causes of complex disease.’Nat Rev Genet 11 (6), 446–450.CrossRefGoogle Scholar
ENCODE Consortium, Bernstein, B. E., Birney, E., Dunham, I., Green, E. D. et al. (2012), ‘An integrated encyclopedia of DNA elements in the human genome.’Nature 489(7414), 57–74.Google Scholar
Fisher, R. A. (1918), ‘The correlations between relatives on the supposition of Mendelian inheritance.’Trans R Soc Edinburgh 52, 399–433.Google Scholar
Flintoft, L., (2014), ‘Disease genetics: phenome-wide association studies go large.’Nat Rev Genet 15 (1), 2.Google Scholar
Friend, S. H. & Ideker, T., (2011), ‘Point: are we prepared for the future doctor visit?’Nat Biotechnol 29 (3), 215–218.CrossRefGoogle Scholar
Fuchs, F., Pau, G., Kranz, D., Sklyar, O., Budjan, C., et al. (2010), ‘Clustering phenotype populations by genome-wide RNAi and multiparametric imaging.’Mol Syst Biol 6, 370.CrossRefGoogle Scholar
Fuchs, T. J. & Buhmann, J. M. (2011), ‘Computational pathology: challenges and promises for tissue analysis.’Comput Med Imaging Graph 35(7–8), 515–530.CrossRefGoogle Scholar
Hemani, G., Knott, S., & Haley, C., (2013), ‘An evolutionary perspective on epistasis and the missing heritability.’PLoS Genet 9 (2), e1003295.CrossRefGoogle Scholar
Ideker, T., & Krogan, N. J. (2012), ‘Differential network biology.’Mol Syst Biol 8, 565.CrossRefGoogle Scholar
Kiger, A. A., Baum, B., Jones, S., Jones, M. R., Coulson, A., et al. (2003), ‘A functional genomic analysis of cell morphology using RNA interference.’J Biol 2 (4), 27.CrossRefGoogle Scholar
Mackay, T. F. C. (2014), ‘Epistasis and quantitative traits: using model organisms to study gene–gene interactions.’Nat Rev Genet 15 (1), 22–33.CrossRefGoogle Scholar
Marcotte, R., Brown, K. R., Suarez, F., Sayad, A., Karamboulas, K., et al. (2012), ‘Essential gene profiles in breast, pancreatic, and ovarian cancer cells.’Cancer Discov 2 (2), 172–189.CrossRefGoogle Scholar
Mendel, G., (1866), ‘Versuche über Pflanzen-Hybriden.’Verhandl Naturforsch Vereines Brünn 4, 3–47.Google Scholar
Muellner, M. K., Uras, I. Z., Gapp, B. V., Kerzendorfer, C., Smida, M., et al. (2011), ‘A chemical–genetic screen reveals a mechanism of resistance to PI3K inhibitors in cancer.’Nat Chem Biol 7 (11), 787–793.CrossRefGoogle Scholar
Nadeau, J. H. & Dudley, A. M. (2011), ‘Genetics: systems genetics.’Science 331(6020), 1015–1016.CrossRefGoogle Scholar
Phillips, P. C. (1998), ‘The language of gene interaction.’Genetics 149 (3), 1167–1171.Google Scholar
Phillips, P. C. (2008), ‘Epistasis: the essential role of gene interactions in the structure and evolution of genetic systems.’Nat Rev Genet 9 (11), 855–867.CrossRefGoogle Scholar
Schadt, E. E., Lamb, J., Yang, X., Zhu, J., Edwards, S., et al. (2005), ‘An integrative genomics approach to infer causal associations between gene expression and disease.’Nat Genet 37 (7), 710–717.CrossRefGoogle Scholar
Schüffler, P. J., Fuchs, T. J., Ong, C. S., Roth, V., & Buhmann, J. M. (2010), ‘Computational TMA analysis and cell nucleus classification of renal cell carcinoma.’Pattern Recognition: Proceedings of 32nd DAGM Symposium, Darmstadt, Germany, 22–24 September 2010, pp. 202–211.Google Scholar
Schüffler, P. J., Fuchs, T. J., Ong, C. S., Wild, P. J., Rupp, N. J. et al. (2013), ‘TMARKER: a free software toolkit for histopathological cell counting and staining estimation.’J Pathol Inform 4(Suppl), S2.Google Scholar
Shapiro, E., Biezuner, T., & Linnarsson, S., (2013), ‘Single-cell sequencing-based technologies will revolutionize whole-organism science.’Nat Rev Genet 14 (9), 618–630.CrossRefGoogle Scholar
Skelly, D. A., Merrihew, G. E., Riffle, M., Connelly, C. F., Kerr, E. O. et al. (2013), ‘Integrative phenomics reveals insight into the structure of phenotypic diversity in budding yeast.’Genome Res 23 (9), 1496–1504.CrossRefGoogle Scholar
Smith, J. C. & Melton, J., (1964), ‘Manipulation of autopsy diagnoses by computer technique.’JAMA 188, 958–962.CrossRefGoogle Scholar
Snijder, B., Sacher, R., Rämö, P., Damm, E., Liberali, P., et al. (2009), ‘Population context determines cell-to-cell variability in endocytosis and virus infection.’Nature 461(7263), 520–523.CrossRefGoogle Scholar
Snijder, B., Sacher, R., Rämö, P., Liberali, P., Mench, K., et al. (2012), ‘Single-cell analysis of population context advances RNAi screening at multiple levels.’Mol Syst Biol 8 (1), 579.CrossRefGoogle Scholar
Sozzani, R., & Benfey, P. N. (2011), ‘High-throughput phenotyping of multicellular organisms: finding the link between genotype and phenotype.’Genome Biol 12 (3), 219.CrossRefGoogle Scholar
The Cancer Genome Atlas Network (2012), ‘Comprehensive molecular portraits of human breast tumours.’Nature 490(7418), 61–70.
Threadgill, D. W. (2006), ‘Meeting report for the 4th Annual Complex Trait Consortium meeting: from QTLs to systems genetics.’Mamm Genome 17 (1), 2–4.CrossRefGoogle Scholar
Topp, C. N., Iyer-Pascuzzi, A. S., Anderson, J. T., Lee, C. -R.Zurek, P. R. et al. (2013), ‘3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture.’Proc Natl Acad Sci USA 110 (18), E1695–E1704.CrossRefGoogle Scholar
Vizeacoumar, F. J., Arnold, R., Vizeacoumar, F. S., Chandrashekhar, M., Buzina, A., et al. (2013), ‘A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.’Mol Syst Biol 9, 696.CrossRefGoogle Scholar
Yin, Z., Sadok, A., Sailem, H., McCarthy, A., Xia, X., et al. (2013), ‘A screen for morphological complexity identifies regulators of switch-like transitions between discrete cell shapes.’Nat Cell Biol 15 (7), 860–871.CrossRefGoogle Scholar
Yuan, Y., Failmezger, H., Rueda, O. M., Ali, H. R., Gräf, S., et al. (2012), ‘Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.’Sci Transl Med 4 (157), 143–157.CrossRefGoogle Scholar
Zuk, O., Hechter, E., Sunyaev, S. R. & Lander, E. S. (2012), ‘The mystery of missing heritability: genetic interactions create phantom heritability.’Proc Natl Acad Sci USA 109 (4), 1193–1198.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org 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
×