Whole Genome Approach Hits Home Run in Ecology

There exists tremendous excitement in the biological community concerning the application of next generation sequencing (NGS) to do everything from generating complete genomes for previously “un-fundable” organisms to world peace. In reading the myriad of reviews, tech notes, and methods-based papers it is easy to become convinced that biology has much to gain from the application of NGS to solve interesting ecological problems.

Interestingly, in a review of a new computational model to detect loci under selection in structured populations, Hermisson (2009) suggested that population ecologists should embrace whole-genome approaches as a way to get around the vexing problem of determining what structural signals in population genetics studies under selection. NGS offers not only a possible way forward for describing population structure, but also the means to identify portions of the genome directly involved in adaptation. However, it seems ecologists have been slow to embrace this idea outside aside from a several studies involving model organisms.

For certain, too often ecologists have been frustrated by the inability to generate studies of the appropriate depth (numbers of individuals and/or populations) and breadth (number of genes or other informative loci) to identify many of the genes that underpin adaptation. In a recent call to arms, Stapley et al. (2010) neatly describe how NGS can aid ecologists to better understanding adaptation. This review was well written for a general audience,describing how different NGS sequencing techniques can be applied toward understanding adaptation (citing a number of previous studies using model organisms, see below).

Examples of recent studies that used next generation sequencing technology to study adaptation in ecological model species (Figure 1 from Stapley et al. 2010).

What is most interesting for me to think about in context of this review is that there now exists the ability to characterize the entire gene set involved in any particular adaptation event under investigation. Furthermore, given enough depth and breadth (at a fraction of previous cost), investigators can use NGS to not only describe the mechanism for adaptation, but also characterize whether these events are driven by existing variation or new mutations.  Lastly, we can also determine the relative contributions from regulatory and structural variants (such as duplications, inversions or large-scale indels).

Gobler et al. (2011) have just shown how helpful NGS can be in terms of understanding larger-scale processes such as harmful algal blooms (HABs). Aureococcus anophagenefferens forms large HABs in the western Atlantic Ocean, and their frequency and intensity seem to be increasing worldwide.  How Aureococcus has increased its dominance in some recent blooms has been a mystery until now. Enter “ecogenomics”.

The authors of this study characterized the biogeochemical conditions and phytoplankton constituents surrounding Aureococcus blooms in Quantuck Bay, NY as a way to understand Aureococcus’ bloom dynamics. There was no clear correlation between physical factors and Aureococcus bloom events; however, a whole genome approach proved enlightening not only for this study, but also in terms of explaining how boom dynamics are changing in response to human activity worldwide. While this investigation does not use high throughput technologies, its approach is certainly informed by and benefits from the whole genome approach that is a hallmark of NGS.  The complete gene genomes for the six most abundant organisms present during Aureococcus blooms were scanned for genes involved in light harvesting, carbon and nitrogen metabolism, and those genes coding for proteins that requiring metal cofactors. In each of these areas, Aureococcus coded for more genes that the other organisms. Many of these larger genes sets in Aureococcus represent either gene family expansions or duplications. The whole genome analysis in this investigation clearly that NGS not only can tackle tough questions regarding adaptation within species, but also how different species’ genomes can evolve to out compete distant related taxa. What is still left open here (though unattainable with the data already in hand) is the question of just how this large gene set came to be housed in such a small organism that would normally be predicted to have a much smaller genome. I would not be surprised if we soon find out.

Literature cited:

Gobler CJ, Berry DL, Dyhrman ST, Wilhelm SW, Salamov A, Lobanov AV, Zhang Y, Collier JL, Wurch LL, Kustka AB, Dill BD, Shah M, VerBerkmoes NC, Kuo A, Terry A, Pangilinan J, Lindquist EA, Lucas S, Paulsen IT, Hattenrath-Lehmann TK, Talmage SC, Walker EA, Koch F, Burson AM, Marcoval MA, Tang YZ, Lecleir GR, Coyne KJ, Berg GM, Bertrand EM, Saito MA, Gladyshev VN, & Grigoriev IV (2011). Niche of harmful alga Aureococcus anophagefferens revealed through ecogenomics. Proceedings of the National Academy of Sciences of the United States of America, 108 (11), 4352-7 PMID: 21368207

Hermisson J (2009). Who believes in whole-genome scans for selection? Heredity, 103 (4), 283-4 PMID: 19654610

Stapley J, Reger J, Feulner PG, Smadja C, Galindo J, Ekblom R, Bennison C, Ball AD, Beckerman AP, & Slate J (2010). Adaptation genomics: the next generation. Trends in ecology & evolution, 25 (12), 705-12 PMID: 20952088


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