Transcriptomics for Conservation

Conservation genetics is in the middle of a transition period towards conservation genomics. Conservation genomics promises greater accuracy of the metrics we currently estimate with conservation genetics techniques, (e.g. population structure, gene flow, effective population size, etc), as well as the opportunity to ask new questions including those about local adaptation. It’s easy to see how understanding local adaptation could help conserve biodiversity, if we knew what species can (and cannot) adapt to, then we may be able to preserve those elements of a landscape for long term persistence. Alternatively, understanding local adaptation has been proposed to identify new suitable habitat for species translocations if their current range can no longer support them.

Thus far at WildlifeSNPits, when we’ve talked about how genetics informs conservation, we’ve always drawn upon data collected from DNA, or the genome. Every individual has a unique genome, the sequence of base pairs that code all of your genetic information. However, there are other molecules that contain information including RNA which produces a transcriptome. The transcriptome contains all of the information coding for a cell given both the cell type and how the cell was responding to its environment when the sample was collected. It is in this way where both your liver and skin cells have the same genome but different transcriptomes, as the liver cell expresses genes needed for the liver to function, and the skin cell expresses genes needed for skin function.

When to Use a Transcriptome
A really helpful aspect of transcriptomics is that they are smaller than genomes. Genomes contain “junk DNA,” introns in genes, and structural repetitive regions such as centromeres and telomeres which are not transcribed, thus they are not sequenced in transcriptomics projects. As mentioned above, transcriptomes are tissue specific so a researcher also reduces the amount of data because they are only sequencing one tissue and the genes expressed in that tissue (e.g. leaves, liver, blood, etc). Researchers may want to use a transcriptome if the genome of the organism they study is very large. (Mammalian genomes are ~3Gb or 3,000,000,000 base pairs, whereas salamanders are 30-50Gb.)

A second use of transcriptomics for conservation occurs when you want to understand how organisms respond to environmental change. For example, you could set up an experiment in the lab or field where your study species is exposed to different temperatures, CO2 concentrations, or hypoxia levels then measure how their gene expression changed between the different treatments. The studies that used this approach to understand the responses of corals to both increased ocean temperatures, decreased dissolved oxygen, and pollutants are some of my favorite conservation genomics studies (here and here). I like these papers because of the clear link to policies that could be used to conserve coral reef ecosystems including monitoring pollutant loads or temperatures and mitigating these systems before corals bleach and die.

When Not to Use a Transcriptome
I’ve glossed over a big experimental design part of transcriptomics, namely that individuals are often sacrificed to collect a tissue specific transcriptome. Maybe a non-lethal skin, blood, or leaf transcriptome will answer your question; however, for many species of conservation concern, sacrificing an individual is neither possible (e.g. permits) nor ethical.  Further, gene expression begins to change upon death as RNA is degraded, thus improper handling or storage of tissues may affect results.

Also, transcriptomes show you the sequence of genes, which have lower mutation rates than some of the neutral markers that effectively address conservation questions. Thus gene sequences may not give high quality estimates for the parameters that conservationists are interested in estimating.

The connection between the Central Dogma of Biology and the type of 'Omics data obtained from each molecule.
The connection between the Central Dogma of Biology and the type of ‘Omics data obtained from each molecule.

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