Molecular Ecology

Abstract

Molecular ecology uses molecular genetic data (typically deoxyribonucleic acid (DNA) sequences) from natural populations to address ecological questions. Historically, either relatively short DNA sequences or highly variable sequences known as microsatellites were most commonly used to genetically characterise populations and species. More recently, however, large amounts of DNA sequences are being generated using a relatively new approach known as high‐throughput sequencing (HTS), which allows researchers to simultaneously sequence thousands of genes from one or numerous individuals. HTS allows whole‐genome sequencing, and also the characterisation of natural populations on the basis of numerous (often thousands of) single nucleotide polymorphisms (SNPs), which are DNA sequence variations that arise when a single nucleotide differs between individuals. Genetic characterisation allows researchers to quantify the genetic diversity within populations and the genetic similarity among populations, which in turn provides insight into specific questions pertaining to the ecology and evolution of populations and species.

Key Concepts

  • Molecular ecology uses molecular genetic data to address ecological questions.
  • A variety of molecular markers can be used to genetically characterise species and populations.
  • Next‐generation (high‐throughput) sequencing has greatly enhanced our ability to collect very large amounts of genetic data at relatively low cost.
  • Molecular genetic data from natural populations allow researchers to quantify the genetic diversity within populations and the genetic similarity among populations.
  • Genetic diversity is required for the long‐term survival of populations and species, and is influenced by a range of different factors.
  • Gene flow among populations strongly influences their genetic similarity.
  • Landscape genetics helps researchers to understand barriers to gene flow across different types of landscapes.
  • Landscape genomics investigates ways in which local adaptation influences the distribution of conspecifics across different types of habitat.
  • Behavioural molecular ecology uses highly variable molecular markers to quantify the relatedness among individuals, and thus describe dipsersal patterns or mating systems.
  • Phylogeography uses molecular genetic data to infer some of the ways in which historical events and processes have shaped the current distributions of species.

Keywords: genetic diversity; genetic differentiation; gene flow; polymerase chain reaction; DNA sequencing; high‐throughput sequencing; SNPs; microsatellites; phylogeography; behavioural ecology; landscape genetics

Figure 1. Part of the DNA sequence that comprises the mitochondrial genome of the common green darner dragonfly (Anax junius). Each large peak represents an individual base, and the corresponding sequence is written along the top of the image.
Figure 2. (a) Alignment of five sequences that include SNPs, representing five different individuals from a single population: the two SNPs are in bold, marked with asterisks. (b) Alignment of five sequences that include microsatellites, representing five different individuals from a single population. In this case the microsatellite is the region in bold that is defined as a series of AT repeats. Sequence 1 has six AT repeats [(AT)6]; sequence 2 has five AT repeats [(AT)5] and sequences 3, 4 and 5 each have seven AT repeats [(AT)7]. The differences between the three alleles portrayed in this alignment [(AT)5, (AT)6, (AT)7] are reflected in the sizes of each amplified allele, for example the total length of sequence 2 is 53 bp, whereas sequence 3 is 57 bp in length; the difference in the lengths of these alleles is explained by the numbers of microsatellite repeats.
Figure 3. Results of a Structure analysis that was done on orchids sampled from nine sites in Ontario. Each colour represents a genetic cluster, or lineage. In this example, orchids were sampled from nine sites, but Structure analysis concluded that they comprised four genetic lineages (denoted as red, blue, green and yellow). Each genetic cluster was recovered from two or more sites (e.g. the yellow genetic cluster was found in sites 8 and 9). Individuals are represented by vertical lines, and these can be most clearly identified for individuals with mixed genetic ancestry, and which are therefore made up of two different colours, for example individuals that are half red and half blue comprise roughly 50% the blue genetic lineage and 50% the red genetic lineage (which is seen in several individuals from each of sites 2 and 3).
Figure 4. Illustration of how a combination of morphological characters and DNA barcoding was used to characterise a highly diverse group of weevils. (a) Unsorted sample of edaphic weevils including Trigonopterus and other genera in ethanol. (b,c) Sorted samples containing each ‘initial morphospecies’ of Trigonopterus. (d,e) Dry‐mounted specimens of Trigonopterus after DNA extraction and the preparation of genitalia; ‘refined morphospecies’; examples of four characteristic edaphic species (d) and foliage‐frequenting species (e).
Figure 5. Evolutionary network showing the relationships among different lineages of the narrow‐leaved cattail, Typha angustifolia, sampled from different parts of the world. Small filled circles on the lines that separate the different lineages represent mutations. NA, North America, EU, Europe. Each circle has a number that corresponds to its lineage number. Lineage 1 was found around the world, and its closest relatives are lineage 2 from Asia (two mutational differences from lineage 1) and lineage 3 also from Asia (one mutational difference from lineage 1). Lineage 4, which was found in both Asia and North America, differs from lineage 7 (found only in Asia) by three mutations, and so on. Lineage 10, found in both Europe and North America, is the most genetically divergent lineage, being separated from its nearest neighbour (lineage 8) by 14 mutations. The sizes of the circles are proportionate to the numbers of individuals in which each lineage was found (Ciotir and Freeland, ). Modified from Ciotir C and Freeland J (2016) Cryptic intercontinental dispersal, commercial retailers, and the genetic diversity of native and non‐native cattails (Typha spp.) in North America Hydriobiologia 768: 137–150.
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Further Readings

Allendorf FW (2017) Genetics and the conservation of natural populations: allozymes to genomes. Molecular Ecology 26 (2): 420–430.

Andrews R, Good KR, Millar MR, et al. (2016) Harnessing the power of RADseq for ecological and evolutionary genomics. Nature Reviews. Genetics 17: 81–92.

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Cristescu ME (2014) From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity. Trends in Ecology & Evolution 29: 566–571.

Creer S, Deiner K, Freer S, et al. (2016) The ecologist's field guide to sequence‐based identification of biodiversity. Methods in Ecology and Evolution 7: 1008–1018.

Deiner K, Bik HM, Mächler E, et al. (2017) Environmental DNA metabarcoding: transforming how we survey animal and plant communities. Molecular Ecology 26: 5872–5895.

Epps CW and Keyghobadi N (2015) Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change. Molecular Ecology 24: 6021–6040.

Freeland JR, Kirk H and Petersen S (2011) Molecular Ecology, 2nd edn. Chichester: John Wiley & Sons, Ltd.

Hall LA and Beissinger SR (2014) A practical toolbox for design and analysis of landscape genetics studies. Landscape Ecology 29: 1487–1504.

Heather JM and Chain B (2016) The sequence of sequencers: the history of sequencing DNA. Genomics 107: 1–8.

Hodel RGJ, Segovia‐Salcedo MC, Landis JB, et al. (2016) The report of my death was an exaggeration: a review for researchers using microsatellites in the 21st century. Application in Plant Sciences 4: 1600025.

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Rellstab C, Gugerli F, Eckert AJ, et al. (2015) A practical guide to environmental association analysis in landscape genomics. Molecular Ecology 24: 4348–4370.

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Freeland, Joanna R(Jun 2018) Molecular Ecology. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0003268.pub3]