Molecular ecology is a subdiscipline of ecology that is concerned with applying molecular genetic techniques to ecological questions (e.g., population structure, phylogeography, conservation, speciation, hybridization, biodiversity). It is virtually synonymous with the field of "Ecological Genetics" as pioneered by Theodosius Dobzhansky, E. B. Ford, Godfrey M. Hewitt, and others. Molecular ecology is related to the fields of population genetics and conservation genetics.
Methods frequently include using microsatellites to determine gene flow and hybridization between populations. The development of molecular ecology is also closely related to the use of DNA microarrays, which allows for the simultaneous analysis of the expression of thousands of different genes. Quantitative PCR may also be used to analyze gene expression as a result of changes in environmental conditions or different responses by differently adapted individuals.
Molecular ecology uses molecular genetic data to answer ecological question related to biogeography, genomics, conservation genetics, and behavioral ecology. Studies mostly use data based on DNA sequences. This approach has been enhanced over a number of years to allow researchers to sequence thousands of genes from a small amount of starting DNA. Allele sizes are another way researchers are able to compare individuals and populations which allows them to quantify the genetic diversity within a population and the genetic similarities among populations.
Bacterial diversity
Molecular ecological techniques are used to study in situ questions of bacterial diversity. Many microorganisms are not easily obtainable as cultured strains in the laboratory, which would allow for identification and characterization. It also stems from the development of PCR technique, which allows for the rapid amplification of genetic material.
The amplification of DNA from environmental samples using general or group-specific primers leads to a mix of genetic material, requiring sorting before sequencing and identification. The classic technique to achieve this is through cloning, which involves incorporating the amplified DNA fragments into bacterial plasmids. Techniques such as temperature gradient gel electrophoresis, allow for a faster result. More recently, the advent of relatively low-cost, next-generation DNA sequencing technologies, such as 454 and Illumina platforms, has allowed exploration of bacterial ecology concerning continental-scale environmental gradients such as pH that was not feasible with traditional technology.
Fungal diversity
Exploration of fungal diversity in situ has also benefited from next-generation DNA sequencing technologies. The use of high-throughput sequencing techniques has been widely adopted by the fungal ecology community since the first publication of their use in the field in 2009. Similar to the exploration of bacterial diversity, these techniques have allowed high-resolution studies of fundamental questions in fungal ecology such as phylogeography, fungal diversity in forest soils, stratification of fungal communities in soil horizons, and fungal succession on decomposing plant litter.
The majority of fungal ecology research leveraging next-generation sequencing approaches involves sequencing of PCR amplicons of conserved regions of DNA (i.e. marker genes) to identify and describe the distribution of taxonomic groups in the fungal community in question, though more recent research has focused on sequencing functional gene amplicons (e.g. Baldrian et al. 2012). The locus of choice for a description of the taxonomic structure of fungal communities has traditionally been the internal transcribed spacer (ITS) region of ribosomal RNA genes due to its utility in identifying fungi to genus or species taxonomic levels, and its high representation in public sequence databases. A second widely used locus (e.g. Amend et al. 2010, Weber et al. 2013), the D1-D3 region of 28S ribosomal RNA genes, may not allow the low taxonomic level classification of the ITS, but demonstrates superior performance in sequence alignment and phylogenetics. Also, the D1-D3 region may be a better candidate for sequencing with Illumina sequencing technologies. Porras-Alfaro et al. showed that the accuracy of classification of either ITS or D1-D3 region sequences was largely based on the sequence composition and quality of databases used for comparison, and poor-quality sequences and sequence misidentification in public databases is a major concern. The construction of sequence databases that have broad representation across fungi, and that are curated by taxonomic experts is a critical next step.
Next-generation sequencing technologies generate large amounts of data, and analysis of fungal marker-gene data is an active area of research. Two primary areas of concern are methods for clustering sequences into operational taxonomic units by sequence similarity and quality control of sequence data. Currently, there is no consensus on preferred methods for clustering, and clustering and sequence processing methods can significantly affect results, especially for the variable-length ITS region. In addition, fungal species vary in intra-specific sequence similarity of the ITS region. Recent research has been devoted to the development of flexible clustering protocols that allow sequence similarity thresholds to vary by taxonomic groups, which are supported by well-annotated sequences in public sequence databases.
Extra-pair fertilizations In recent years, molecular data and analyses have been able to supplement traditional approaches of behavioral ecology, the study of animal behavior in relation to its ecology and evolutionary history. One behavior that molecular data has helped scientists better understand is extra-pair fertilizations (EPFs), also known as extra-pair copulations (EPCs). These are mating events that occur outside of a social bond, like monogamy and are hard to observe. Molecular data has been key to understanding the prevalence of and the individuals participating in EPFs.
While most bird species are socially monogamous, molecular data has revealed that less than 25% of these species are genetically monogamous. EPFs complicate matters, especially for male individuals, because it does not make sense for an individual to care for offspring that are not their own. Studies have found that males will adjust their parental care in response to changes in their paternity. Other studies have shown that in socially monogamous species, some individuals will employ an alternative strategy to be reproductively successful since a social bond does not always equal reproductive success.
It appears that EPFs in some species is driven by the good genes hypothesis, In red-back shrikes (Lanius collurio) extra-pair males had significantly longer tarsi than within-pair males, and all of the extra-pair offspring were males, supporting the prediction that females will bias their clutch towards males when they mate with an "attractive" male. In house wrens (Troglodytes aedon), extra-pair offspring were also found to be male-biased compared to within-offspring.
Without molecular ecology, identifying individuals that participate in EPFs and the offspring that result from EPFs would be impossible.
Isolation by distance Isolation by distance (IBD), like reproductive isolation, is the effect of physical barriers to populations that limit migration and lower gene flow. The shorter the distance between populations the more likely individuals are to disperse and mate and thus, increase gene flow. The use of molecular data, specifically allele frequencies of individuals among populations in relation to their geographic distance help to explain concepts such as, sex-biased dispersal, speciation, and landscape genetics.
The Mantel test is an assessment that compares genetic distance with geographic distance and is most appropriate because it doesn't assume that the comparisons are independent of each other. There are three main factors that influence the chances of finding a correlation of IBD, which include sample size, metabolism, and taxa. For example, based on the meta-analysis, ectotherms are more likely than endotherms to display greater IBD.
Metapopulation theory
Metapopulation theory dictates that a metapopulation consists of spatially distinct populations that interact with one another on some level and move through a cycle of extinctions and recolonizations (i.e. through dispersal). The most common metapopulation model is the extinction-recolonization model which explains systems in which spatially distinct populations undergo stochastic changes in population sizes which may lead to extinction at the population level. Once this has occurred, dispersing individuals from other populations will immigrate and "rescue" the population at that site. Other metapopulation models include the source-sink model (island-mainland model) where one (or multiple) large central population(s) produces disperses to smaller satellite populations that have a population growth rate of less than one and could not persist without the influx from the main population.
Metapopulation structure and the repeated extinctions and recolonizations can significantly affect a population's genetic structure. Recolonization by a few dispersers leads to population bottlenecks which will reduce the effective population size (Ne), accelerate genetic drift, and deplete genetic variation. However, dispersal between populations in the metapopulation can reverse or halt these processes over the long term. Therefore, in order for individual sub-populations to remain healthy, they must either have a large population size or have a relatively high rate of dispersal with other subpopulations. Molecular ecology focuses on using tests to determine the rates of dispersal between populations and can use molecular clocks to determine when historic bottlenecks occurred. As habitat becomes more fragmented, dispersal between populations will become increasingly rare. Therefore, subpopulations that may have historically been preserved by a metapopulation structure may start to decline. Using mitochondrial or nuclear markers to monitor dispersal coupled with population Fst values and allelic richness can provide insight into how well a population is performing and how it will perform into the future.
Molecular clock hypothesis
The molecular clock hypothesis states that DNA sequences roughly evolve at the same rate and because of this the dissimilarity between two sequences can be used to tell how long ago they diverged from one another. The first step in using a molecular clock is it must be calibrated based on the approximate time the two lineages studied diverged. The sources usually used to calibrate the molecular clocks are fossils or known geological events in the past. After calibrating the clock the next step is to calculate divergence time by dividing the estimated time since the sequences diverged by the amount of sequence divergence. The resulting number is the estimated rate at which molecular evolution is occurring. The most widely cited molecular clock is a 'universal' mtDNA clock of approximately two percent sequence divergence every million years. Although referred to as a universal clock, this idea of the "universal" clock is not possible considering rates of evolution differ within DNA regions. Another drawback to using molecular clocks is that they ideally need to be calibrated from an independent source of data other than the molecular data. This poses a problem for taxa that don't fossilize/preserve easily, making it almost impossible to calibrate their molecular clock. Despite these inconveniences, the molecular clock hypothesis is still used today. The molecular clock has been successful in dating events happening up to 65 million years ago.
Mate choice hypotheses