Last week I was whining about gaps in our
understanding of evolutionary processes in the ocean. The universe heard me,
and today I am satisfied to write about the published genome of Euprymna scolopes – the Hawaiian bobtail
squid and the implications this genome has for the study of (marine)
E. scolopes presents a very potent model species for understanding how symbioses between animals and bacteria form and evolve (Nyholm and McFall-Ngai 2004). It has two specialized organs to host bacterial symbionts, the light organ and the accessory nidamental gland. The former maintains a monoculture of bioluminescent bacteria (Vibrio fischeri). During the night when the squid is active, it can glow with the help of its symbiont bacteria. From below, its glowing silhouette will disappear in the surrounding moon light and this provides camouflage from predators. Check out a video on nature’s cutest symbiosis here! (This is a must see.) The latter specialized organ is important for reproduction and only found in females (Collins et al. 2012; Kerwin and Nyholm 2017). It hosts a microbial consortium that has been hypothesized to protect developing embryos from fouling and infection. Colonization of these two symbiotic organs has been studied in great detail leveraging a plethora of articles on microscopic structures in the host tissue, biochemical pathways, microbial genomics, gene expression patterns, and ultimately the evolution of symbiosis in this system. Microbial comparative genomics has been especially helpful in identifying elements important for the bacterial symbiont. For example, microbial biofilm formation, which was eloquently summarized by Julian Jackson. Yet, so far, most insight about the evolutionary trajectory of this symbiosis came from studies of the bacterial symbiont. Now, with the public availability of the host genome, we can learn about the evolutionary history from the host’s perspective. Once more, the charismatic little shallow water creature from Hawai’i is opening new avenues for exciting research.
The current American administration is excited about its space program on extraterrestrial exploration and discovery. A mission to the moon, several ones to Mars, and perhaps others someday to other planets are part of the current funding plan. NASA has chosen Jezero Crater as the landing site for its upcoming Mars 2020 rover mission after almost six years of scrutinizing and debating which location might be optimal. This rover mission will include rock and soil collections to find signs of habitable conditions and microbial life. Jazero Crater is located just north of the Martian equator. The 45 kilometers wide crater had most probably been a huge river delta in ancient Mars times more than 3 billion years ago. The explorers hope to find preserved ancient organic molecules in the delta’s sediment and learn about any type of previous and current life on Mars.
Since August 2018, we also know about liquid water under Mars’ southern ice cap thanks to a study published in Science by Roberto Orosei et al. (2018). These authors detected a 20 kilometer wide lake of liquid water underneath solid ice, similar to an aquifer, using a MARSIS (Mars Advanced Radar for Subsurface and Ionosphere Sounding). ‘The presence of liquid water on Mars has implications for astrobiology, evolution and future human exploration’ (as the authors state). Now I can understand why Jeremy Y. is watching First Contact on a Sunday night. The idea of finding water sources on other planets, studying extraterrestrial molecules, and learning about Martian ecology is so romantic! How exciting it would be if we could just take off and start human settlements on other planets?! Now that we have officially entered theAnthropocene and humankind has heralded Earth’s sixth major extinction event, it only makes sense to consider migration as an option.
If you’ve ever had to explain how all the elements of a big, multi-part project come together, you’ve probably at least considered making something like a Gantt chart. A Gantt chart is a horizontal bar plot with time as the x-axis, illustrating the time required for different activities within a larger project. The basic design is named for turn-of-the-20th-Century American engineer and management consultant Henry Gantt, though examples from Poland and Germany predate Gantt’s original charts.
I’ve just spent more time than I care to admit squinting at draft Gantt charts for a proposal that’s going in soonish, and I’m happy to report that actually making the chart, and making it look nice, was not the hardest part of the process. (That would be, um, figuring out how to fit everything in the proposed project into the allotted funding period.) As you might expect, I did it in R, taking full advantage of the tidyverse packages — as you might not expect, I also used that ancient nemesis of modern data science, Microsoft Excel.
I’ve recently made a career change. Actually, I’m not even sure whether to call it that, or the next step of a natural, if meandering progression of a scientist not on the academic career path. Even though I see more and more articles and social media threads showcasing the career opportunities outside of academics and the need to emphasize those opportunities, it can still feel like a walk in the wilderness to someone with a non-medical, non-human, non-microbial genetics background. With genetics and genomics data gathering and analysis skills, it SEEMS like it would be easy to slide into a biomedical lab, either with the government, or private industry, though the job applications tend to require clinical lab experience as well as expertise with data and analyses on a scale much larger than what the typical ecological geneticist is used to. On my job seeking journey, I worried that I would have to give up “interesting” science in favor of drug testing and humanGWAS data analysis or continue to look for the unicorn research position whereI had job stability and could work on projects with a more conservation and ecological slant.
Luckily, I managed to land at Eagle Fish Genetics Lab (EFGL) in Eagle, Idaho where resources and funding are available to power large scale genetics projects that inform management decisions affecting endangered and threatened fish species along with the management of non-native and invasive species. There are several conservation genetics labs across the country that have created a similar niche where applied and pure research is being conducted (see Robin Waple’s illustrious career at NOAA’s Northwest Fisheries Science Center, for one example). The projects here at EFGL fall into three major categories: Genetic Stock Identification (GSI), Parentage Based Tagging (PBT), and Sex Marker Discovery. Every year, juvenile and adult steelhead and Chinook salmon return to the Lower Granite Dam on the Snake River. These fish are genotyped using a species-specific SNP panel consisting of several hundred markers. The genotypes are compared to baseline genetic data of known stocks in the region to ascertain the stock composition of the returning fish.
In addition, hatchery supplementation of several species is employed throughout the Columbia River and Snake River Basin. Several hatcheries rear smolts to be released at various places throughout the river systems in order to decrease fishing pressure on the natural populations. The broodstock generating the smolts are replaced annually. Since 2008, there has been a concerted effort to genotype every broodstock fish at every hatchery facility (~17,000 fish per year), so that any hatchery-generated fish collected in the system can be traced back to their broodstock parents using genetic pedigree information. The success of PBT relies upon the thorough genotyping of the broodstock annually. This is accomplished using the Genotyping-in-Thousands by sequencing (GTseq) methodology. Beyond yearly monitoring of hatchery and wild populations, the data generated can be used to assess the most effective hatchery practices, salmonid life history harvest patterns, and trait heritability.
Another focus of EFGL work is finding genetic markers to determine the sex of various fish species as a way to track the success of Trojan Y invasive species control. In this scenario, males are exposed to estradiol, a female hormone, which causes some to produce eggs. These feminized males are mated with untreated males, which results in ~25% YY “super” or “Trojan” males. Any subsequent cross with the resultant YY fish will result in male progeny. The hope is to extirpate the non-native population with continued releases of Trojan males. A codominant, genetic marker that can distinguish XY males from YY males helps to track the efficacy and efficiency of the technique. We employ the modified RadSeq protocol, BestRAD, to a mixture of phenotypically male and female samples, then use Stacks (see previous TME posts here and here for an overview and interview with the author, Julian Catchen) and Python scripts to sort putative SNPs into piles that segregate with sex. Though steelhead and Chinook salmon are the main species of interest, other projects involve carp, burbot, sculpins, and other species of salmonids.
It takes a village to collect, inventory, extract, genotype, and analyze these samples annually. The jobs here at this facility include technicians, biologists (including geneticists), a data manager, and a supervisor and we work in close proximity to a fish health lab, a wildlife forensics lab, and many personnel tasked with maintaining the on-site Sockeye salmon hatchery. At EFGL, the technicians are well versed in DNA extraction (often performing several hundred to thousands of them per project), SNP genotyping, and RadSeq to name a few. There are also ample opportunities to help with fish sampling throughout the state and spawning events within hatcheries.The biologists/geneticists coordinate the various projects and analyze the data for reports and manuscripts. The data manager is the gate keeper making sure that all samples sent to the facility have all the required labeling and metadata and those in the field taking samples across the region are adequately briefed and prepared. The data manager also runs QC scripts on sequencing runs and maintains a gigantic database of sampling, pedigree, and genotype information on every fish that we’ve sampled. The database system we use is Progeny (designed for human disease pedigree data, of course) and it ain’t cheap (naturally), but considering the enormity of the task at hand, and the fact that it’s built for storing metadata AND genotypes, it does a great job.
My motivation for providing this brief overview of the facility here is to pique the interest of beginning researchers thinking about their future career paths and assuage some doubts about opportunities for those not interested in the academic career eight-lane highway (that may end in a brick wall with a tunnel painted on it). If you are in the early stages of your career, and you want some experience in a lab generating and analyzing genomic data for a project likely to have a beginning and end during your tenure, I suggest you seek out these types of programs. Furthermore, if the thought of relentless and never ending grant writing (and the stress of running out of funding) leaves you cold, a well-funded wildlife genetics lab with multiple long-term, ongoing projects on species people love to hunt/fish/photograph/eat may be the niche you are looking for. Not to say that opportunities are not available for securing your own funding and/or pursuing a pet project, necessarily, though that would be lab specific. Collaborations within the agency, with other non-profits and governmental agencies, and academic labs are common as well.
Another motivation of mine is to put these types of labs on the radar of researchers that are attempting to ramp up their program to larger scale/higher throughput pipelines. If you are overwhelmed with data and sample tracking and organization or concerned about tailoring protocols and/or scripts to fit your needs, it may be that wildlife genetics labs have already done the tweaking and QC for you and some of those resources can be found outside of the primary literature (e.g agency reports, https://www.monitoringresources.org/). Reaching out to your fellow scientists at wildlife labs would surely be mutually beneficial. Lastly, and most importantly, tell your students interested in wildlife genetics and bioinformatics about these jobs! Sure, they’re rare, but so are tenure track positions.
For a little more detail about our little corner of the world, click here.
The use of preprints has increased drastically in the life sciences over the past few years. Preprints are manuscripts submitted to open access servers prior to, or in some cases instead of, formal publication. One popular preprint server is bioRxiv (although there are an increasing number of servers to choose from). Since bioRxiv came online in 2013 the number of preprints posted there each month has increased dramatically, from 39 in November of 2013 to 2,241 in November of 2018 (Figure 1; bioRxiv). This trend is not limited to the life sciences, and other fields, particularly physics, have embraced preprints for decades (Kaiser 2017). While supporters of preprints argue that preprint servers will accelerate the pace of science by allowing researchers to rapidly disseminate and get feedback on their work, others worry that preprints will lead to stolen ideas and a large volume of un-reviewed literature (Kaiser 2017).
Where are preprints leading us?
The future of preprints is unclear. Some have suggested that preprint servers will replace journals altogether (Kaiser 2017). Others see preprints as a step to take prior to publication in a peer-reviewed journal, rather than a replacement. It is also possible that the two could play off of each other. What if journals solicited preprints?
Imagine: you post your paper on bioRxiv. A few weeks later, you receive an email from an Associate Editor inviting you to submit your paper to a particular journal. How would you respond, and how would this change your attitude towards preprint servers? How could this change the fields of evolutionary biology and ecology? The Junior Editorial Board of Molecular Ecology and Molecular Ecology Resources wants your feedback on this subject. Please take this short survey (~3 minutes) to let us know how you feel about preprints and the idea of journals soliciting promising preprints for submission. Thanks in advance for your valuable feedback.
–The Junior Editorial Board
Megan L. Smith
Kaiser, J. “Are preprints the future of biology? A survival guide for scientists.” Science 397 (2017). doi: 10.1126/science.aaq0747
The Earth BioGenome Project aims to sequence all currently described ~1.5 million eukaryotic species on earth (Lewin et al., 2018; Figure 1). The scale and scope are enormous, and it is hard to imagine a more ambitious but exciting goal.
Last month, I attended the launch of the Earth BioGenome Project, held at the Wellcome Trust in London. From the first session you could sense the buzz and anticipation. Harris Lewin opened the meeting with his vision for the project. He sees Earth BioGenome as biology’s ‘moonshot’, as transformative for science as placing a man on the moon. The projected cost of $4.7bn is similar to the Human Genome Project ($2.7bn, equivalent to $5bn today), and is somewhat comparative in the need for collaborative effort from different research groups. The need for global collaboration is clear: to sequence earth’s diversity we need to use samples held in museum, zoo and botanic garden collections from across the globe; we need extensive new field collections (particularly in biodiversity hotspots); we need to develop new sequencing infrastructure and bioinformatic pipelines; and we need scientists to use these data for research, biodiversity monitoring and conservation. Lewin reminded us that not all the uses of the human genome were clear when the project was launched, and the same applies to Earth BioGenome data. But obvious uses are for benefitting human welfare (e.g. drug discovery and crop improvement), protecting biodiversity, and understanding ecosystems.
After this inspiring introduction most the audience were invigorated. My initial doubts were quickly dealt with. I came in questioning whether this goal is really possible. But I hadn’t realised how much had already been achieved. As a plant biologist I’ve been following the progress of the 10,000 Plant Genome Project in detail (Twyford, 2018). But many other ‘big genome’ projects had largely passed me by. There’s the Vertebrate Genomes Project (aim: 66,000 error-free vertebrate genomes), Bat 1K (1,300 bat genomes), 1000 Fungal Genomes, The i5K Initiative (5,000 insects and other arthropods), 10,000 Bird Genomes (B10K), with the list going on and on. Seemingly biologists studying every major organismal lineage have initiated their own genome project. And what’s exciting is that these projects have made substantial progress with many genome sequences published or soon to be released. Earth BioGenome unites these ongoing projects and builds on this experience. By setting data standards, recommending pipelines, providing infrastructure, and offering re-usable templates and agreements for sample sharing, Earth BioGenome makes new genomic-scale science more attainable.
How will Earth BioGenome work? What became clear at the meeting was that Earth BioGenome will be an aggregate of smaller projects with their own governance. Each project will find their own funding and proceed separately, but Earth BioGenome will provide the template for how to proceed and may also provide some centralised funding for specific goals. In particular, centralised funding may help developing countries build their own sequencing infrastructure and biobanks to support genomic research. This will also help train hundreds of the next generation of scientists necessary to make this research happen.
A key message from the meeting was that if we are sequencing representative genomes from all of life we need to do it well. There is little point in assembling fragmented genome sequences from Illumina short-read data if they are to be replaced by contiguous genomes from long-read data in the near future. The route to good genomes will differ depending on the organism, but likely includes a combination of long-read (Pacific Biosciences and/or Oxford Nanopore Technologies) and short-read Illumina technologies, often paired with inexpensive synthetic read data (e.g. 10X Genomics) and scaffolded with Hi-C or BioNano Genomics (see summary here). There was a remarkable consensus that given major innovations in genomic technologies the sequencing is one of the easy parts of the project, and that the greater challenge is in sourcing material (particularly from the tropics), putting a name to each sample, and curating voucher specimens.
At the same meeting, Mike Stratton introduced a second major new sequencing initiative, the Darwin Tree of Life Project. This ‘place-based’ rather than ‘taxon-based’ project aims to sequence a representative from all 66,000 eukaryotic species present in the United Kingdom. Why the UK? Its small size and limited diversity, its existing detailed collections, the presence of related datasets, and the existence of immediate funding for sequencing, all make it a good first choice. This project gets me excited (disclaimer: I’m hoping to be involved with the project by sequencing British plants, along with colleagues at the University of Edinburgh, Royal Botanic Garden Edinburgh, and Royal Botanic Garden Kew) as I see this as a superb opportunity for comparative genomic analyses that incorporate the large existing data sets of ecological attributes and species’ traits.
Where next? I think one important goal is for researchers to launch new comparative genomic projects, and for scientists to lobby funding agencies and governments to support new genomic research. If many new and diverse sequencing projects are started this will build the momentum for broadening the sequencing effort to global diversity. One initial aim should be to produce genome sequences representative of each organismal family, before moving to genera-references and then species (the ‘phylogenetic wave’). Another aim should be to sequence diverse genomes from multiple areas to develop tools for place-based projects. Personally I can’t wait to see the next stage of the genomics revolution take place.
Lewin, H. A. et al. (2018) Earth BioGenome Project: Sequencing life for the future of life. Proceedings of the National Academy of Sciences115, 4325-4333.
Twyford, A. D. (2018) The road to 10,000 plant genomes. Nature Plants4, 312-313, doi:10.1038/s41477-018-0165-2.
Red snow … watermelon snow … green snow … did you know that snow came in so many different colors?
I had never heard of watermelon ice (#🍉❄) until a talk given by Robin Kodner from Western Washington University at the Phycological Society of America meeting in Monterey in 2017. We both gave talks in the last session of the meeting. We chatted at the end of the session, a chance conversation that led to a collaboration that led to Potsdam, Germany and the 2nd Snow Algae Meeting.
I’ll confess I felt a little bit self conscious presenting life cycle theory when I have not seen a snow alga in person (or in situ), let alone worked on them yet (several grant applications didn’t quite reach the summit, pun intended), but the organizers and all participants were incredibly gracious. Though I was suffering from the worst jet lag I’ve ever experienced, this meeting was motivating and exciting, as well as incredibly welcoming to a #🍉❄ novice.
So … what are snow algae? And, why did about 25 people congregate in Potsdam to talk about them?
Back in 2016, Robinson et al. (2016) published a genomic analyses of the Channel Island foxes and they showed that despite extremely low genome-wide diversity, the island foxes do not seem to be suffering from inbreeding depression. Read the post ‘What does the island fox say?’ summarizing this paper.
Most notably, their results question the general validity of the small population paradigm. One of the principal hypotheses in conservation genetics predicts that small populations are more vulnerable to stochastic extinction factors including the genetic processes of inbreeding and genetic drift. As a result, small populations are expected to be more likely to end up in an ‘extinction vortex’ and suffer from mutational meltdown and loss of adaptive potential, which compromise their chances of long-term survival.
Although the island foxes do have drastically reduced genetic variation and increased genetic load, they seem to be surviving just fine. How is it possible? Does it mean that genomic erosion is not a direct path to extinction?
Understanding how organisms are related to each other in the grand scheme of things has been a main goal of taxonomists, ecologists, and evolutionary biologists for centuries. While traditionally, what things look like (morphological characters) and what they eat or produce (phenotypic characters) have been used for classification. However molecular tools have been a game changer in terms of figuring out who is related to who and where they fit on the tree of life.
Last Thursday, a new letter out in Nature led by Alastair G. B. Simpson’s group in collaboration with other labs at Dalhousie University presented evidence that a group of eukaryotic protists (the Hemimastigophora) is MUCH more distinct than anyone thought. Although protists are tiny, they are still eukaryotes, so they have relatively complicated cell organization and are actually more closely related to us than bacteria (prokaryotes). The word “protozoan” means “early animals” and was first used in 1820 (Scamardella 1999). According to Simpson (in this informative article), protists most simply are “…all the eukaryotic organisms that are not animals, plants or fungi”. So…a whole bunch of stuff.
Sarah Livett wrote this post as a final project for Stacy Krueger-Hadfield’s Introduction to Evolutionary Processes course at the University of Alabama at Birmingham. Sarah was a 5th year MS student at UAB in Dr. Thane Wibbel‘s lab. She worked on Kemp’s Ridley sea turtles and is pursuing a MS degree in conservation and sustainability.
Unlike genetic sex determination in mammals, turtle sex is determined by temperature. In sea turtles, for example, males develop at lower temperatures, whereas females develop at higher temperatures. These temperature ranges are very small. We’re talking less than 3⁰C (Woo 2014). This means that a rise in global temperatures of just 3°C could shift the sex ratios from all female (Wibbels 2003).
Not only do higher nest temperatures produce more females, they also increase mortality of turtle hatchlings (Laloë et al, 2017).
Could heat shock proteins combat temperature-linked hatchling mortality?