Recently, Nature published the genome sequence of the marine invertebrate ctenophore Pleurobrachia bachei1. Ctenophores, better known as “comb jellies”, are delicate creatures that superficially resemble jellyfish, yet occupy a distinct phylum unto themselves1,2. The Department of Immunology’s very own Dr. Jonathan Rast and post-doctoral fellow Dr. Kate Buckley are authors on the collaborative Nature paper, where they characterized the ctenophore immune gene complement. Kate was responsible for most of the analysis, so I sat down with her over dinner to discuss the results of her work, how to approach “big-data” sequencing projects, and what the future of genomics holds for understanding animal immunity and evolution.
Immunity and innovation in the ctenophore
Once settled into our table and our orders placed, we dive into how Kate approached annotating immunity in such a divergent creature: genes that play roles in immunity, especially receptors, are quickly evolving and often difficult to identify based on DNA sequences alone, which undergo rapid diversification among animals. Therefore, Kate used a low-stringency, domain-based approach characterize immune genes. She searched for profiles typical of immune receptors (e.g., Ig, NACHT, TIR, LRR, and CARD) within the predicted gene models, translated genome sequences, and transcriptome data of Pleurobrachia. Immune gene candidates were then validated through reciprocal sequence alignments and manual annotation, in some cases directly from the raw sequences used to assemble the genome. Here, one has to tread carefully, warns Kate. “In cases of potential multi-gene families, 50+ similar-looking genes are often classified as repeats and thrown out by the assembly algorithms. But upon closer inspection they do compose a unique gene family, and that says something important about the biology of that organism.”
So what interesting biology has been gleaned from the ctenophore genome? The primary thesis of the Nature paper is that ctenophores are the most ancient lineage of metazoans (multicellular animals), yet have uniquely convergent nervous and muscular systems – that is, they are analogous in function yet completely different in genetic structure to the neuro/muscular systems found in all other animals. I asked Kate, Does the immune system follow suit? She explains, “right away, it’s clear that the ctenophore has a ‘reduced’ immune system compared to other animals” (Figure 1). It lacks most of the major elements that we understand to mediate immunity: there are no toll-like, Nod-like, or interleukin-like receptors, no MyD88 homologs, no antiviral pattern recognition receptors, interleukins, interferons, nor TNFs to be found in the ctenophore. Ctenophores also reveal a primary absence of NF-kB and rel-homology proteins, which are found at the earliest in the sponges, yet are secondarily lost in C. elegans.
The ctenophore genome does, however, contain several TIR-domain-containing proteins, perforin-like molecules, two peptidoglycan recognition domain proteins, and four Interferon Regulatory Factor homologs (IRFs function in several innate signaling systems). Three homologs of macrophage migration inhibitory factor (Mif), a powerful mediator of inflammation, were found as well. The comb-jelly genome also exhibits largely expanded families of innate recognition receptors, a feature common to many basal metazoan immune systems (see Figure 1).
Ctenophore-specific innovations include independent expansions of ETS transcription factors unique to this species, and surprisingly, the highest number of RNA-binding proteins and deaminases ever documented in a metazoan. Kate muses, “RNA editing is likely used extensively for ctenophore development and/or immunity – perhaps a hack of sorts around the [missing] pathways that we’re more familiar with.” After all, ctenophores have very specific structures and physiology, such as comb-like rows of cilia and long, sometimes poisonous, tentacles that trap pray. Unique structures may call for unique approaches – perhaps this is why the nervous and muscular systems are so genetically different from other animals. Though this becomes a bit of a chicken-and-the-egg problem: Have ctenophores evolved so differently because of a different gene complement from square one, or did the need for highly adaptable structures drive drastic gene gains and losses in nervous, mesodermal, and immune systems?
The waiter brings us our second beers, overhears “ctenophore tentacles”, and leaves with a puzzled look.
We’ve gotten a bit puzzled ourselves. But as puzzling as some genomes remain to scientists, surprising biology can be teased out with the right approaches and an open mind. Citing the discovery of convergent adaptive immunity in the lamprey as an example, Kate explains, “In the beginning, researchers kept trying to clone primitive T-cell or B-cell receptor-like molecules (TCR/BCR). Several clones that all resembled each other – but not a TCR/BCR – kept popping up in experiments, but were ignored for a long time…” Upon closer inspection, they identified that the clones all contained many leucine-rich-repeats (LRRs), a classic structure of toll-like receptors. The LRRs are organized in unique genetic cassettes and encode an entirely novel, yet functionally analogous immune receptor, dubbed VLRs (variable lymphocyte receptors)4 that has revolutionized our understanding of the emergence of adaptive immunity.
The moral of the story: don’t ignore features of a genome (or an experiment for that matter) just because they are not exactly what you were looking for. Furthermore, the more we sample animal genomes, the better we can understand what exactly is conserved, and what is unique to certain phyla, such as the VLR system in jawless fish.
New genomes, new insights
The sequencing of the ctenophore genome is the result of a contemporary push to increase such understanding. Other recently published genomes include the tunicate, amphioxus, sea urchin, mosquito, honeybee, beetle, and two jellyfish species. Following in the ctenophore’s footsteps are several other animals to be sequenced: A handful of xenacoelamorpha and hemichordates (marine worms), nine cephalopods (octopi and squid), and many members of the lophotrochozoans and ecdysozoa (snails, arthropods, and other worms). But really, one could ask, why should we bother?
Aside from a cornucopia of interesting names, “these animals represent key gaps to be filled in lineages that have only been represented by one or two model organisms, if any at all,” Kate answers. The advantage to increasing our phylogenetic sampling of genomes is to position important genetic events with higher fidelity. The recent addition of the ctenophore genome has already re-oriented our knowledge of key gains and losses in the tree of life. In terms of immune systems, Kate summarizes, “Data from more animals will help clarify where other convergent adaptive systems may have arisen (e.g., the VLRs in lampreys), and what other aspects of immunity remain conserved, or endure as divergent innovations among closely related phyla.”
Furthermore, as we sequence more animals, we open up the field for entirely new model systems to be established. The species on tap to be sequenced represent huge food and aquaculture industries (shrimp, lobster), as well as significant vectors for parasites and disease (snails). Thus the broad phylogenetic sequencing projects in the works will also have an appreciable impact on socioeconomics, ecology, and human health. Even the humble ctenophore may eventually help us harness the power of regeneration in our own bodies.
Getting into the genomic groove
By now our food has arrived. As we get our hands on some delicious chicken sandwiches, we shift into discussing how Kate got her hands on so many high-impact genome projects – her ever-growing list includes sea urchins, ctenophores, lampreys, marine worms, and snails. “It’s largely been a ‘getting-your-work-out-there-in-the-first-place’ kind of thing,” she confesses. In the years following several papers on immunity in the sea urchin genome, Kate and Jon attended comparative immunology conferences to present unpublished transcriptome analyses on larval immunity. At one of those meetings, Albert Poustka addressed them about annotating immune genes in the Xenoturbella genomes he was putting together (a marine worm). At a later conference, Leonid Moroz asked Jon for help with the ctenophore genome. Cold calls for lamprey and snail projects followed suit. “The point,” Kate concludes, “is that I spent a lot of time at meetings talking about what we’ve annotated and what our approaches were. So if you have an interesting scientific skill, get your expertise out there!”
What about how to get more comfortable with sequencing data to begin with?, I asked next. In the realm of Immunology at University of Toronto, many of us are in fact using sequencing approaches in our research, such as microarrays, differential deep/RNA-sequencing, or cancer genome comparisons. For many students or investigators, “big data” is rather abstract and or just plain overwhelming to interpret well. Analyzing sequencing data in-house is an incredibly valuable skill, but where do you start if you have zero bioinformatics experience?
“First of all, don’t be scared!” she reassures me. “The first thing is to learn some basic scripting (you want to be able to move sequences around various programs easily). Coding doesn’t have to be all-or-nothing – maybe take a class to get over any initial fear, but in the end, you just have to start somewhere, and then get some practice programming.” Free online courses or communities offer a wealth of support as well. All of the programs she uses to search and annotate genes or assemble transcriptomes can be found online or as open source. In terms of performing analyses and storing data, cloud computing offers a cheap but reliable alternative to maintaining expensive processing power and hard drives.
Overall, Kate stresses that, as with any skill, it will take a little bit of time to get efficient at analyzing sequence data well, but programming becomes easier than you think. “At the very least,” she concludes pragmatically, “You’re never going to regret learning how to make a computer work a little better for you.”
Bringing genomes to life
Kate’s other advice for sequence analyses: software and tools should still be taken with a grain of salt. While the technology and programs to analyze sequencing data are becoming increasingly sophisticated and user-friendly, there will always be phenomena that an algorithm will miss, that only the curious scientists’ eye can pick up on. Kate cautions, “Most programs often label data that doesn’t align perfectly with an annotated genome as junk.” Indeed, the many annotation programs for predicting coding sequences in a genome can miss a lot of real genes in the first place (remember the example of multi-gene families). This in turn adds a bias in analyzing differential sequencing data that many researchers may not even be aware of.
An example: in her own research, Kate is using deep transcriptome sequencing to identify novel immune genes that are activated in sea urchin larvae in response to immune challenges. By looking in detail where RNA-sequencing reads hit back to un-annotated parts of the sea urchin genome, she’s been able to find distinct exon/intron structures in what was previously ignored as “blank” DNA sequence. One of the most surprising finds is a divergent IL-17 homolog that had previously escaped her low stringency domain/residue searches (cytokines are notoriously difficult to find through bioinformatics). The IL-17 homolog and other novel genes are not represented in the sea urchin transcriptome databases available online, as those datasets were constructed from quiescent embryos and tissues. But her follow-ups with qPCR and in-situ hybridization in immune-challenged larvae validate the existence of these hidden genes. Similar strategies can be used to find un-documented or cryptic splice variants to genes.
Collectively, Kate’s work demonstrates the power of comparing sequencing data across both developmental time points and experimental conditions, and looking beyond what a computer program says is the “complete” coding complement within a genome. What is “not” there can be just as interesting as what is predicted to be there. This remains true for comparing genomes across animals as well. Even when no true homologs for certain things can be found, as is the case in the ctenophore immune gene complement, the lack of certain pathways hint at entirely new ways to think about biology. Kate advocates, “What really becomes clear as more genomic gaps are filled in the tree of life, is that there is a dazzling number of ways to build [and protect] an animal than what we’ve always ‘known’ to be true.”
We sit back and muse on this statement for a quiet moment, finishing our beer and picking at leftover fries. I ask Kate one final question: which genomes would she most like to add to the list on her computer? After a thoughtful pause, she answers, “Shark, definitely another shark. And the cephalopod (octopus). ‘Ceph-Seq,’ they already call it! How cute is that?”
Cute indeed, and it will certainly hold some aces up its (eight) sleeves.
- Moroz, L. L., Kocot, K. M., Citarella, M. R., Dosung, S., Norekian, T. P., Povolotskaya, I. S., et al. (2014). Nature, 510(7503), 109–114. doi:10.1038/nature13400
- Ryan, J. F., Pang, K., Schnitzler, C. E., Nguyen, A. D., Moreland, R. T., Simmons, D. K., et al. (2013). The Genome of the Ctenophore Mnemiopsis leidyi and Its Implications for Cell Type Evolution. Science (New York, N.Y.), 342(6164), 1242592–1242592. doi:10.1126/science.1242592
- Buckley, K. M. & Rast, J. P. Characterizing immune receptors from new genome sequences. Methods Mol Biol 748, 273-298 (2011).
- Pancer Z.1., Amemiya C.T., Ehrhardt G.R., Ceitlin J, Gartland G.L, Cooper M.D. (2004). Somatic diversification of variable lymphocyte receptors in the agnathan sea lamprey. Jul 8;430(6996):174-80.
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