Genomics Techniques
Genomic Techniques in Ecological Genomics
Ecological genomics is “an interdisciplinary field that seeks to understand the genetic and physiological basis of species interactions for evolutionary inferences” (Renn, Siemens 2010). Here I will focus on the genomic techniques that can be used to answer ecological genomic questions. An overarching goal in the field of ecological genomics is to find the genes that matter in species interactions, and then to study the ecological consequences of natural genetic variation in these genes for evolutionary inferences. Depending upon the type of information already acquired for the question, that is, whether or not there already exists candidate genes, various forward or reverse genetic tools may be implemented to find candidate genes. Forward genetics implies that the phenotype or function is known and can be used to figure out which gene causes the specific phenotype or function. Reverse genetics starts from genes that have been identified from sequencing projects, but the function or phenotype is not yet known. Many genomic techniques are used in forward and reverse genetics. However, the ones I will be addressing in this paper are Microarray, Next Generation Sequencing (NGS), population genomics, quantitative trait loci mapping (QTL mapping), proteomics, and metabolomics. In both forward and reverse genetics, the comparative method may be used in order to identify phenotype/function or candidate genes. For example, a related species or other closely related phylogenetic group can be used to evaluate whether a gene sequence is conserved and therefore probably not a pseudogene. However, often, at best, closely related organisms are only sequenced at specific non-overlapping genes. Due to the lack of information available in regards to the organism of interest and its most direct relatives, a reference related organism (genomic model species) is needed. For example, Windsor et al. (2006) used the
Ecological genomics is “an interdisciplinary field that seeks to understand the genetic and physiological basis of species interactions for evolutionary inferences” (Renn, Siemens 2010). Here I will focus on the genomic techniques that can be used to answer ecological genomic questions. An overarching goal in the field of ecological genomics is to find the genes that matter in species interactions, and then to study the ecological consequences of natural genetic variation in these genes for evolutionary inferences. Depending upon the type of information already acquired for the question, that is, whether or not there already exists candidate genes, various forward or reverse genetic tools may be implemented to find candidate genes. Forward genetics implies that the phenotype or function is known and can be used to figure out which gene causes the specific phenotype or function. Reverse genetics starts from genes that have been identified from sequencing projects, but the function or phenotype is not yet known. Many genomic techniques are used in forward and reverse genetics. However, the ones I will be addressing in this paper are Microarray, Next Generation Sequencing (NGS), population genomics, quantitative trait loci mapping (QTL mapping), proteomics, and metabolomics. In both forward and reverse genetics, the comparative method may be used in order to identify phenotype/function or candidate genes. For example, a related species or other closely related phylogenetic group can be used to evaluate whether a gene sequence is conserved and therefore probably not a pseudogene. However, often, at best, closely related organisms are only sequenced at specific non-overlapping genes. Due to the lack of information available in regards to the organism of interest and its most direct relatives, a reference related organism (genomic model species) is needed. For example, Windsor et al. (2006) used the
Cited: Anderson, JT, CR Lee, T Mitchell-Olds. 2010. Life-history QTLS and natural selection on flowering time in Boechera stricta, a perennial relative of Arabidopsis. Evolution 65:771-787. Anderson, JT, T Mitchell-Olds. 2011. Ecological genetics and genomics of plant defenses: Evidence and approaches. Funct Ecol 25:312-324. Evanno, G, S Regnaut, J Goudet. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611-2620. Giardine, B, C Riemer, RC Hardison, et al. 2005. Galaxy: a platform for interactive large-scale genome analysis. Genome Res 15:1451-1455. Goecks, J, A Nekrutenko, J Taylor, T Galaxy. 2010. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol 11:R86. Kammenga, JE, MA Herman, NJ Ouborg, L Johnson, R Breitling. 2007. Microarray challenges in ecology. Trends Ecol Evol 22:273-279. Laird, NM, C Lange. 2011. Statistics for Biology and Health; The Fundamentals of Modern Statistical Genetics Springer New Yourk Dordrecht Heidelberg London: Springer Science+Business Media, LLC. Manel, S, OE Gaggiotti, RS Waples. 2005. Assignment methods: matching biological questions techniques with appropriate. Trends in Ecology & Evolution 20:136-142. Martyniuk, CJ, KJ Kroll, NJ Doperalski, DS Barber, ND Denslow. 2010. Environmentally relevant exposure to 17alpha-ethinylestradiol affects the telencephalic proteome of male fathead minnows. Aquat Toxicol 98:344-353. Mauricio, R. 2001. Mapping Quantitiative Trait Loci in Plants: Uses and Caveats for Evolutionary Biology. Nature 2:370-381. Nekrutenko, A, J Taylor. 2012. Next-generation sequencing data interpretation: enhancing reproducibility and accessibility. Nat Rev Genet 13:667-672. Pritchard, JK, M Stephens, PJ Donnelly. 2000. Inference of population structure using multilocus genotype data. Genetics 155:945-959. Renn, SCP, DH Siemens. 2010. Meeting Review: Ecological Genomics -- Changing perspectives on Darwin 's basic concerns. Molecular Ecology 19:3025-3030. Shendure, J, H Ji. 2008. Next-generation DNA sequencing. Nat Biotechnol 26:1135-1145. Shiu, SH, JO Borevitz. 2008. The next generation of microarray research: applications in evolutionary and ecological genomics. Heredity (Edinb) 100:141-149. Siemens, D, B Roy. 2005. Tests for Parasite-mediated Frequency-dependent Selection in Natural Populations of an Asexual Plant Species. Evolutionary Ecology 19:321-338. Siemens, DH, R Haugen, S Matzner, N VanAsma. 2009. Plant chemical defense allocation constrains evolution of local range. Molecular Ecology 18:4974-4983. Song, BH, MJ Clauss, A Pepper, T Mitchell-Olds. 2006. Geographic patterns of microsatellite variation in Boechera stricta, a close relative of Arabidopsis. Mol Ecol 15:357-369. Stinchcombe, JR, HE Hoekstra. 2008. Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits. Heredity (Edinb) 100:158-170. Straalen, NMV, D Roelofs. 2012. An Introduction to Ecological Genomics. New York: Oxford University Press Inc. Tautz, D, H Ellegren, D Weigel. 2010. Next generation molecular ecology. Mol Ecol 19 Suppl 1:1-3. Toth, AL, K Varala, TC Newman, et al. 2007. Wasp gene expression supports an evolutionary link between maternal behavior and eusociality. Science 318:441-444. Whitham, TG, JK Bailey, JA Schweitzer, et al. 2006. A framework for community and ecosystem genetics: from genes to ecosystems. Nature Reviews Genetics 7:510-523. Wilkins, MR, RD Appel, JE Van Eyk, et al. 2006. Guidelines for the next 10 years of proteomics. Proteomics 6:4-8.