This is Mini mum (photo by Andolalao Rakotoarison), a species I had the pleasure to name—together with a team of amazing colleagues—back in 2019.
That was the start of a fascination with the process and consequences of miniaturisation for vertebrates. How the hell does this tiny frog manage to fit all of its vital organs—more or less all the same senses and organs that we have—into a package the size of a tic-tac‽ Why and how has it evolved to be so small? And why don't we get frogs that are much smaller?
Well, I just secured 1.5 MILLION Euros (!!!) in the form of a European Research Commission Starting Grant, to answer these and other related questions in the genomes of Mini frogs and other miniaturised vertebrates.
Because it turns out, there are *lots* of miniaturised vertebrates, and they push the boundaries of how small we think it is possible for a vertebrate to be! Here is a little graphic of some of them, scaled to a BIC ballpoint pen.
The project is called GEMINI: The Genomics of Miniaturisation in Vertebrates! You can read more about it on my website here, and in the press release, here!
This odd fish has 30 times as much DNA as humans—a new record for animals
Lacking key genes that control selfish bits of DNA, the South American lungfish’s genome just grew and grew.
A species of lungfish found in South America has claimed the title of the animal with the biggest genome sequenced so far.
The DNA of Lepidosiren paradoxa comprises a staggering 91 billion chemical letters or “bases,” 30 times as many as the human genome, researchers report today in Nature.
However, those 91 billion bases of DNA only contain about the same number of genes that humans have—roughly 20,000—with the rest consisting of noncoding, perhaps even “junk” DNA.
By comparing this genome with those of other lungfishes, the researchers determined that L. paradoxa adds the equivalent of a human genome to its DNA every 10 million years...
For centuries, naturalists have puzzled over what might constitute the head of a sea star, commonly called a "starfish." When looking at a w
This just in, starfish are a radially symmetrical head with a stomach.
God I love echinoderms
If you told someone that there’s an entire group of animals that develop butt first as embryos are born bilateral but then grow a radially symmetrical head like a cancer in their side that then bursts out and lives as a completely separate organism from its birth form and moves via hydraulic systems…
They wouldn’t believe you. Yet one of the most beloved cartoon characters is one of them.
Gerstner Postdoctoral Fellow Daniel Hooper (@danielmhooper) studies the genetics of color evolution in Australian finches at the Museum. He recently published a study on the genetics of color variation in Long-tailed Finches and shares his findings on why some of these finches have red beaks, while others have yellow or orange beaks. This research, recently published in Current Biology, was all catch and release.
Fieldwork photos courtesy of Daniel Hooper, Geoffrey Giller, and Simon Griffith.
re: annoyance at how AI has ruined the reputation of the field I love dearly, but this was the type of shit that got me into data science:
like. a shit ton of incredibly hard-working, amazing scientists had to do a LOT of work in order to figure out how the hell to analyze and display this type of data in a way that made sense to the human brain. the sheer amount of work that went into these two graphs is not properly understood just by looking at it
these are gene expression graphs using single-cell genomic RNA sequencing data (the top one is mouse, bottom is human)
each cell in your body has the same genome⁽¹⁾. but you're not using all of your genes in every single one of your cells (that would be disastrous lol). so, in any given cell in your body, the only genes being transcribed (copied into messenger RNA) and turned into proteins are the genes that that specific cell type uses. and since messenger RNA (mRNA) is what those genes get copied into before being made into protein, you can get a pretty good guesstimate about which genes are actively being used in which cells, by simply sequencing the mRNA in that cell⁽²⁾
so with single cell genomics, instead of sequencing the RNA from a chunk of tissue (or blood or whatever) where you get aggregate results for a bunch of cells all at once (with no way to differentiate which transcript came from which cell; imagine if you just emptied out the cells and put them all in one vat), you are instead sequencing everything that was inside each cell individually.
if you've got 1,000,000 cells in a piece of tissue, this is effectively like doing sequencing for 1 million different samples
how the fuck do you visualize that? you've got different levels of gene expression⁽³⁾ for each of those cells. maybe one cell has a bunch of Gene A, but another cell has like half as much. if you represented that on a graph, you'd basically have a 1 million dimensional object
so you need to collapse those dimensions into 2 or 3 dimensions. that's what's being done here. they collapsed all that information into a couple of dimensions. each dot is 1 cell, given a fancy mathematical score to determine where it sits on those plots (the UMAP axes don't mean anything comprehensible to the human mind) based on how similar it is to other cells, creating clusters.
but like!!!! that's data science!!! this is data science!!! AI was created out of this field, yes, and you can probably see how given the similarities with this type of data calculating. but AI is not the SOLE thing within the field of data science. it wants to market itself that way but it is far from it
⁽¹⁾technically somatic mutations are a thing and lots of your cells have them but shhhhhh shhhhhhhhhhh
⁽²⁾since mRNA isn't copying the entire genome; each mRNA is just 1 gene. so if you need to make a new hemoglobin protein, you'll go to your DNA recipe book and write down (transcribe) your recipe for hemoglobin onto your mRNA notecard, and then walk over to your kitchen (ribosome) to go cook up that hemoglobin protein
⁽³⁾measured by counting how many transcripts ["reads"] were found in each cell; you've got multiple copies of different genes floating around at any given moment. you can write down the same recipe on multiple note cards multiple times, since you're not changing anything about the original recipe book in order to do that lol. so if you need to make a bunch of copies, you can
Genomic sequencing of nearly all living kākāpō reveals its variations in plumage color evolved to avoid the sharp eyes of their predators
Genome Sequencing Shows Kākāpō Evolved Two Plumage Colors To Evade Predators, study Helmholtz Pioneer Campus, Aotearoa New Zealand Department of Conservation & Māori iwi Ngāi Tahu, pub'd by PLOSBiology
