About the blog author: Brinkley Thornton wrote this blog for Dr. Krueger-Hadfield’s Spring 2022 Science Communication course. Brinkley is currently a graduate student in the Department of Biology at the University of Alabama at Birmingham seeking her MS degree in Biology. She currently works in the Krueger-Hadfield Evolutionary Ecology Lab. Her MS research focuses on uncovering the life cycle and underlying reproductive mode in an invasive green alga in Hawaii.
You’re taking a walk down the beach, unwinding from a long week.
You stumble across a curious green seaweed.
You’ve never seen it before, not at this beach, nor anywhere else you’ve traveled to collect seaweed.
Your curiosity gets the best of you, so you take a few samples in a makeshift bag back to your lab. Knowing that identification based solely on morphology can be fraught with problems (Twist et al. 2020), you decide to reach into your molecular toolbox.
But where to start?
Your first thought is to use a single gene. Since you found a green alga, you maybe start with a plastid gene, such as tufA (Famá et al. 2002). If it were a red, you might pull out your mitochondrial cox1 primers (Saunders 2005). If it were a brown, you might grab a different mitochondrial marker, such as trnW/trnI (Engel et al. 2008). Not only are there tons of data available, though some of the species IDs on GenBank can leave something to be desired, it’s pretty easy to generate some preliminary genetic structure data at the same time! Are your samples all one haplotype? Multiple haplotypes?
While useful for identification and coarse population structure data, these types of markers can only get you so far. So, what do you use when you have deeper questions regarding gene flow? Ploidy levels? Modes of reproduction? You might want to reach for microsatellites (if they exist but see below) or maybe you go down the road of generating single nucleotide polymorphisms (SNPs).
Microsatellites are simple sequence repeats of 1 to 6 nucleotides. While these markers were very popular, they’ve seemed to have gone a bit out of fashion. However, they are anything but passé. There are several advantages to using these loci, including their high levels of polymorphism and multi-allelic nature (Guichoux et al. 2011). Microsatellites have uncovered strange reproductive modes in kelps (Oppliger et al. 2014), the importance of genetic diversity for aquaculture (Valero et al. 2011), the source regions of a charismatic invader (Krueger-Hadfield et al. 2017), and the consequences of short-range dispersal in a mat forming seaweed (Van Der Strate et al. 2002).
But what if you don’t have microsatellite loci at the ready? Do you develop them? Or do you use one of the myriads of RAD-seq methods out there to identify SNPs?
SNPs are the most abundant and widespread loci in the genome. Various RAD-seq methods have been used to discover hundreds or thousands of SNPs in species with little to no prior genomic information available, which is the case for many seaweeds (Andrews et al. 2016). More markers mean more information, even looking for loci under selection. However, what if you don’t know the ploidy of the thallus you’ve picked up? Could it be haploid? Diploid? Polyploid? We simply lack a lot of basic natural history information about seaweeds that might complicate decisions when it comes to calling genotypes in typical SNP bioinformatic pipelines.
Over time, you’ve found more putative populations of your mysterious seaweed and you decided to use RAD-seq to genotype your original collections. But a short while later, you find more populations … can you iteratively add to your data set? Not easily with typical approaches. However, there are new methods emerging, such as the methods outlined by Delord et al. (2018), that develop locus-specific primers for SNP amplification in multiplex PCRs. This means the specific SNP loci can be genotyped again in future studies!
In addition to missing natural history data that are necessary to inform genetic data, we also lack genetic data for many seaweeds (see as an example Krueger-Hadfield et al. 2021). Most population genetic tools to date have been developed from species that are exclusively sexual with one free-living life cycle stage, but what if this isn’t the case for your seaweed? Additionally, many seaweeds engage in a life cycle where there are two free-living stages, generally the haploid and diploid stages (Otto & Marks, 1996). More genetic data needs to be generated in such natural populations as predictions for these taxa cannot be easily transferred from purely sexual taxa (Krueger-Hadfield et al. 2021). Such studies will require more extensive sampling efforts as you will need data from populations of each free-living stage. Therefore, it is crucial to develop markers be reused for genotyping as you come across more populations to add to your study.
The development of effective genetic markers for seaweeds not only allows for the potential of discovery, but also paves a way to address problematic species. Such is seen in the case of Hawaiian populations of Avrainvillea lacerata (Figure 1; Figure 2). This alga was first seen during a dive near O’ahu in 1981 (Brostoff, 1989). It has incredibly plastic morphology, allowing it to hide under the name of Avrainvillea amadelpha for years. This was until the use of single gene markers allowed the true identity of this green seaweed to be revealed (Wade, 2019). Since its initial discovery, populations of A. lacerata have boomed at an alarming rate (Smith et al. 2002; Cox et al. 2017). Along with having a life cycle that is yet to be determined, there are no molecular data available to describe these growing populations.
Understanding these will be critical in future efforts to manage this species and preserve the native seaweeds that are integral to Hawaiian culture!
What you have found on your leisurely walk is not just some simple seaweed. What you have found is the opportunity for discovery, to see evolution at work, to understand what is happening in the ecosystem, and so much more. All you need is to develop markers that can allow you to see such things, and that can be used again as you ask more questions and find more populations of this mysterious green seaweed.
Delord, C., Lassalle, G., Oger, A., Barloy, D., Coutellec, M.-A., Delcamp, A., … Petit, E. J. (2018). A cost-and-time effective procedure to develop SNP markers for multiple species: A support for community genetics. Methods in Ecology and Evolution, 9, 1959– 1974.
Famà, Wysor, B., Kooistra, W. H. C. F., & Zuccarello, G. C. (2002). Molecular phylogeny of the genus Caulerpa (Caulerpales, Chlorophyta) inferred from chloroplast tufA gene1. Journal of Phycology, 38, 1040–1050.
Guichoux, Lagache, L., Wagner, S., Chaumeil, P., Léger, P., Lepais, O., Lepoittevin, C., Malausa, T., Revarddel, E., Salin, F., & Petit, R. (2011). Current trends in microsatellite genotyping. Molecular Ecology Resources, 11, 591–611.
Krueger-Hadfield, Kollars, N. M., Strand, A. E., Byers, J. E., Shainker, S. J., Terada, R., Greig, T. W., Hammann, M., Murray, D. C., Weinberger, F., & Sotka, E. E. (2017). Genetic identification of source and likely vector of a widespread marine invader. Ecology and Evolution, 7, 4432–4447.
Oppliger, von Dassow, P., Bouchemousse, S., Robuchon, M., Valero, M., Correa, J. A., Mauger, S., & Destombe, C. (2014). Alteration of sexual reproduction and genetic diversity in the kelp species Laminaria digitata at the southern limit of its range. PloS One, 9, e102518.
Twist, Cornwall, C., McCoy, S., Gabrielson, P., Martone, P., & Nelson, W. (2020). The need to employ reliable and reproducible species identifications in coralline algal research. Marine Ecology. Progress Series (Halstenbek), 654, 225–231.
Valero, Myriam & Destombe, Christophe & Mauger, Stéphane & Ribout, Cécile & Engel-Gautier, Carolyn & Daguin-Thiebaut, Claire & Tellier, Florence. (2011). Using genetic tools for sustainable management of kelps: A literature review and the example of Laminaria Digitata. Cahiers de Biologie Marine. 52. 467-483.
Van Der Strate, Van De Zande, L., Stam, W. ., & Olsen, J. L. (2002). The contribution of haploids, diploids and clones to fine-scale population structure in the seaweed Cladophoropsis membranacea (Chlorophyta). Molecular Ecology, 11, 329–345.