DevoWorm Lab Meetings, 21 Dec 2020

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From YouTube: DevoWorm (2020, Meeting 43): Physics, Embryos, and Evolution, Manuscripts in Prep and GSoC 2021

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DevoWorm (2020, Meeting 43): Papers on Physics, Embryogenesis, and Evolution. Manuscripts in the Pipeline (Boring Billion, Periodicity in the Embryo, DevoLearn), Google Summer of Code applications for 2021. Attendees: Susan Crawford-Young, Mainak Deb, Mayukh Deb, Richard Gordon, Ujjwal Singh, Shruti Rajvanshsingh, and Bradly Alicea.

A

Hello, hello, how are you.

B

I'm fine wow. Are you in a different room? There.

C

Yeah yeah, I moved to a different room. I usually don't have this room available at this time, so.

B

Oh okay, I fixed up this room and I could move across the room.

D

C

Another computer, but.

B

B

I built a shelf for what I have.

C

Part of it pre-made.

B

But yeah I don't know it's being quite the project, nothing fit. Oh.

C

It's like one of the pre-fabricated ones or.

B

Yeah yeah three parts pre-fabricated I made the fourth part and then there's a top that they made for me, that was too long and too too shallow in two directions. So I got.

E

To alter the whole thing.

B

And I have with one of the papers that I sent you um I had I I need to show.

F

B

I'm going to try it out, um see there, you go that's better and then you pull on it. Well, you pull on it. So.

C

This is, I think, that's what they're trying to describe.

B

But I I keep reading.

C

That paper, because it was so convoluted, so I was wondering if it was just.

B

C

She didn't show them.

B

Saying that things intercalated and then they went out to the side and then it was sort of a feedback loop moving. Well, yes, I guess you could call it.

C

Well, yeah: we can talk about that.

C

Welcome everyone uh I see yeah, mozwal and minok, and my hook are here yeah, so uh welcome to the meeting. This is, I think, the final meeting of the year.

C

um I I have a couple things I want to talk about. uh I have uh update on the periodicity in the embryo paper. uh Susan had some paper. She wanted to talk about, no, not really, but mostly yeah.

C

We can talk about the one and then we can talk about some other things, uh maybe some things for the upcoming year and then um then, next year you know early in january, I'll present on uh like a recap of 2020 I'll kind of go over where we are and that'll include, like a lot of the diva learn stuff and the other things that we've been doing this year.

C

We, I did this in my other group this last week, but I'll do it like in the new year for this group, uh it's always good to keep stock of where you've been and where you are and like some of the things that you've accomplished in the group. I think that's. uh If you look back, you know over like a 12 month period. It's actually quite impressive.

C

Sometimes what happens over that time instead of just like you know what did I do last week and um anyways and then maybe a plan out for the new year um I talked yesterday, I talked to heidi hutner from openworm and she um uh we were talking about like educational opportunities, so you know there's a move. I think uh between her and myself and maybe stephen larson is going to be back active again in open worm to sort of revitalize some of the educational outreach stuff.

C

um So you know, we've been at the open worm level. We've been trying to do this for a while trying to like uh do some outreach education.

C

uh You know c elegans related and then we've done stuff in this group with like machine learning and tutorials, and she wants to actually take that a step further and like build a you know, uh almost like an educational platform for people who might be interested say in computational skills, but they don't. You know they need to learn like new programming languages or new techniques or whatever and then uh but using the worm. Or you know, computational biology is a way around way towards that.

C

So I mean that might be an interesting thing, maybe this summer we'll be doing some of that. So hopefully I dick so yeah if you're interested in that. Let me know um it's pretty early, so we all be talking about it again.

C

So susan did you have you were going to talk about those pit that paper.

C

Oh you're, muted, susan.

C

Susan you're, muted,.

B

C

It's not up at the top with.

B

C

B

It's at the bottom of the screen: yeah, okay, um so this is actually dick's idea and um the title of the paper is mechanical. Coupling coordinates the co-elongation of axial and paraxial tissue in avian embryos, so I would like to know a little bit more about how avian embryos operate, um but this is giving me a headache to read so um there's they're, suggesting that the tissue at the sides of the um neural um tube um go to the side and feed back into the lengthening.

B

Neural neural tube anyway, sort of it's a elongation of the embryo or part of it, and after reading it I thought well, this is this is to you bit see: there's there's a rubber band, and if you pull on it it does that they all do so. There you go that that's probably what's happening or what they're trying to describe by the intercollation of cells, etc.

B

So um um the verbal part of that was a bit much for me and the other paper that I I had is just a description. Susan.

D

Yeah yeah, that's not original with me. The idea goes back to papers around 1900., oh okay, all right.

B

Yep all right, 1900.

C

Oh, I guess I.

B

Dropped the reference but okay, but that's kind of what I think they're trying to describe in that paper.

E

Okay- and they.

B

Said it's a feedback loop? Well, it sort of is mechanically what happens when you stretch stretch something, um and then I had. The other paper was about a stem cell niches and how, if you push and pull the stem cells to, uh they become another type of tissue, and then what are some of the protein markers that occur.

B

While this is happening, so it was kind of a nice. I thought it was sort of a review paper, but I haven't gone through it thoroughly. So I can't can't really talk about it, because it's just that's what I think.

C

B

Yeah, so it's the mechanical forces, direct stem cell behavior and development, and regeneration and they're they're, trying to um apply forces to stem cells to see if what happens and see, if that's that they can replace those forces which, with what's happening in the embryo as a whole, and it's always better, if you can keep it- they embryo intact, of course, but they're trying to take it apart. The other way, yeah.

B

Okay, that's that that's.

C

The two papers- yeah, you see, if I have, I think I have the papers in the collection here.

C

Let me check the folder.

C

Not sure if this is it.

C

I may not have put them in here, but.

B

It's called mechanical.

B

Mechanical anyway, the ridges of the neural tube to close close, the brain cavity and the spinal cord part of the force comes from the tension of the elongation like their the notochord is, is growing and pulling on the tissue and it naturally folds it's just what happens with elastic tissue, so yeah. I thought.

C

I should point that, out with that.

B

Deeper because the um like I say, the verbal description is uh made my eyes cross.

C

Yeah sometimes.

B

C

Can do that but uh yeah, that's good! Thank you. I don't think I have the paper in that uh collection of papers. I know how you sent them to me, but I didn't. I don't know if I put them in the folder right folder. So yeah, that's good. I think that's a pretty good description. um Thank you for that.

B

Okay, yeah now find the bottom very well shut myself.

F

B

C

Okay, um yeah, so that's good, um so uh I don't know if we could jump. Maybe we can. Oh here's surety hello.

C

Maybe we can jump into papers since I had that folder out. So let me present now.

C

All right, you can see my yeah. I can see my screen coming up here, so I had a bunch of things to talk about this week. um So the first thing is that there's this workshop synthetic morphogenesis from gene circuits to tissue architecture and it's coming up in the uh early march period it's put on by embl, it's a a virtual conference or workshop, and I think it does cost some money. So I don't know if you're you know, you don't think it's worth your. You know the money that they're asking.

C

Then you don't have to attend. I don't know if they're going to have the lectures online afterwards, but it looks like there's a. There are a lot of good speakers here and they're going to be talking about different topics in this area.

C

I don't really know what the what the agenda looks like yet so that you know, if you go to this website, you'll find you can find out more. I was thinking of maybe submitting something to this, but we'll see um it's probably something maybe we're doing already. But if you have a good idea for that, uh let me know I think that would be an interesting.

C

You know, I don't know if we would get accepted, because when they say you know from gene circuit to tissue architecture, it's hard to know what they're looking for it looks like they have a mechanical hummingbird here, but I don't know if that means that that's just like an artistic, styling or they're, really interested in. Like virtual.

C

uh You know things about. You know modeling and things like that. So I'm not really sure what the sort of the uh perspective is, because sometimes you know people will have maybe a more biological perspective or a more computational perspective and that'll affect what they're really looking for, but it might be good, you know, might be something if we can submit an abstract by the 6th of january, see if it gets accepted.

C

It's just one opportunity.

C

So, there's that uh I think this was the one.

D

Bradley yeah, let's put a damper on it, but the web page says registration closed.

C

Okay, well, I don't know yeah, it says and your registration was uh february 24th. So I don't know.

C

I don't know yeah well anyways. I I I've been talking actually with my other group about like putting together a list of deadlines. um That's another thing we might do. uh Is you know if we find opportunities on line or wherever?

C

If we get like, you know things that float around uh to make like a list, a common list of deadlines?

C

So if you know, maybe if you find something interesting put it on the list, I can make a list. You know and we can review it on a regular basis and you know that'll help like if something is coming up. We can prepare for it and includes like special paper deadlines as well. If we want to do something like that, so, um okay, so the other thing one other thing I want to talk about was not this one.

C

Okay, so this is a paper I found. uh Animal egg is evolutionary innovation, a solution to the embryonic hourglass puzzle. This is by stuart, a newman. I think we've encountered this person before.

C

The abstract says the evolutionary origin of the egg stage of animal development presents several difficulties for conventional, developmental and evolutionary narratives. If the egg's internal organization represents a template for key features of the developed organism, why can taxa within a given phylum exhibit very different egg types pass through a common intermediate morphology?

C

They call the phylotypic stage only to diverge again in this exemplifying the embryonic hourglass, and so this is a problem in developmental biology where you get these, uh you have this phyotypic stage and it's sort of a place where there's a sort of a common morphology between like early, very early embryogenesis and later embryogenesis.

C

So uh if, moreover, if different egg types typically represent adaptations of different environmental conditions, why do birds and mammals, for example, have such vastly different eggs with respect to size, shape and post fertilization dynamics, whereas all these features are more similar for obsidians and mammals? So obsidians are like see uh marine invertebrates and, of course, mammals. Are you know like us or like dogs or cats?

C

And so why is it that those two groups of organisms have features that are more similar than something like birds and birds and mammals, which are actually closer phylogenetically?

C

And so that's the question they're asking there uh here. I consider the possibility that different body plans had their origin in self-organizing physical processes in ancient clusters of cells and suggest that eggs represented a set of independent evolutionary innovations subsequently inserted into the developmental trajectories of such aggregates.

C

So last week we talked about a paper dick found on aggregate cell aggregates, and they were doing these experiments uh with cell aggregates, and so but this is actually not a trivial thing for experiments. This is actually something that is thought to be like when you go from like single cells to a bunch of uh multicellular.

C

You know a multicellular population of cells, like a you, know, an organism that we would call an organism. But when you.

B

C

This transition from those two types of uh cell types or cell arrangements- you get these aggregates, and so you know there's this whole literature on multicellular transitions, if you're interested in it. But this is uh the this is kind of what they're kind of getting at here. They're talking about this possibility that different body plans had uh origin and something to do with like these ancient clusters of cells, kind of coming together.

C

Next I describe how adaptive specialization of cells released from such aggregates could have become proto eggs, which regenerated the parental cell clusters by cleavage, conserving the characteristic dpms available to a lineage.

C

Then I show how known processes of cytoplasmic reorganization following fertilization are often based on spontaneous self-organizing physical effects, what he calls egg patterning processes. He gives a acronym epp, which is you know, I don't know people like acronyms.

C

uh I suggest that, rather than acting as developmental blueprints or pre-patterns, the epps refine the phylotypic body plans determined by the dpms by setting the boundary in initial conditions under which these multicellular patterning mechanisms operate, and so this is the this paper kind of goes through. So this is the phylotypic stage here. So what he's talking about is that you have eggs and they're fertilized and there's this sort of diversity of egg shapes.

C

We talked about this uh a while back this year. um We talked about like maybe it wasn't even this year. It was the year before, where they looked at all these different types of eggs that exist in nature and they were classifying them.

C

um I don't know if people remember this paper, but it was a science paper and they had all these different egg shapes and they were classifying them and looking at the diversity of eggs in nature and so there's actually quite a diversity of shapes but anyways. All these different shapes come together and at some point called the phylotypic stage. They have this common morphology and then this uh I guess this is invertebrates.

C

So it's you know not totally universal, but then you end up with these different morphologies from rabbits to ducks to turtles, and they all you know, birds and amphibians and mammals, and they all come out of this same sort of hourglass of a common shape here, common form, and so so. This is the standard representation of this hourglass model.

C

And then this is an example of differential development here, where you have these cell aggregates and then they form into these different eggs, and then this this shows the developmental trajectory for each of these. You know you have this. um So, let's see if we can find in the bottom here.

C

So this is something they call body plans, so you know across uh across development, you have, you know, only a couple of different types of body plans, and so the body plans represent things like arms and legs or you know other types of you know other types of segmentation, and so you know with with mammals, you have um a certain body plan, but in invertebrates you have another type of body plan, and this is something that you know: there's a whole literature and body plans or ball plans, and so that's what they're getting at here with this rest of the figure, um then he talks about dynamic, patterning modules, which is this idea about gene expression being responsible for these different body plans, and so he goes through this here.

C

um I'm trying to find if there are any nice figures in this paper, it talks about ex's, evolutionary innovations and morphological novelties.

C

So this is where you know we kind of get into this idea that you're getting eggs from the single you know the cell aggregates, and that you get these evolut they're actually themselves in evolutionary innovations that they appear in evolution. As this thing to solve a problem.

C

So the the paper says once primitive animal body plans have emerged, there would have been a selective premium on starting the developmental sequence, not with a cluster of development developmentally equivalent cells, but with a cell aggregate that was prepared, so that development would proceed in a more reliable fashion.

C

Generally accepted scenarios predict the changes made at the early stages of development should have dramatic consequences at later stages.

C

The fact that such varied changes can occur even in related lineages during the peri leading up to gastrulation, with little effect on the body plane, is the crux of the pre-construction hourglass puzzle. So this fits into this. Our developmental hourglass model.

C

um So this kind of shows again like this idea of uh dynamic patterning, how gene expression in different parts of the egg lead to patterning over developmental time, so you get in in the drosophila or the um we talk. We talk about drosophila embryos from time to time. In this group uh the fruit fly.

C

You have these eggs, that um you know you get uh gene expression patterns and different parts of the egg and over time, these uh different areas of genetics, differential gene expression from these stripes and then they form banding patterns in the embryo, and then that leads to the pattern, the sort of the segments of the body of the of the fly. So this is uh sort of laying this out here, I'm just trying to go over this for people who probably aren't very aware of like some of these things development.

C

um So he just has a bunch of conclusions and then a lot of literature cited. So if you're interested in this paper, you know you can read more about it. Another paper we had. I think this was from a while back. I think this was susan that sent this. This is actually a news story to this art article, uh smaller salamander species associated with smaller genomes.

C

So um this is a salamander, and uh so this, this type of salamander from the genus thorius, is you know about the size of this coin.

C

So it's not very large, and their statement is, is that this salamander must pack enough cells into a tiny form to build a complex physio to build all the complex physiological structures that you find in a salamander. So this isn't you know it's an amphibian. It's not like uh you know it's not like a worm or something where you don't have. You know you have all the structures of a vertebrate packed into this tiny body. So how do they do it?

C

um So the world's tiniest salamanders are so small that some body parts appear to get the short shrift. Those in the genus thorius, for example, have heads that are mind-bogglingly small, maybe half the size of a pencil eraser.

C

uh So that's actually pretty small and you think about like the brains that they have. You know that they have an uh vertebrate nervous system and they have uh you know. So how do they fit? This into such a small body um within this tiny skull, the eyes bulge and the brain is in relative terms. Massive the teeth in the upper jaw are usually missing entirely.

C

So one way they solve this small size of their body is that their trade-off. So you have a brain. You know the brain can't shrink down to. Maybe you know it's a minimal size, maybe not smaller than that, and so, if you're, even getting smaller than that in terms of your body size, you know where. How do you make room for that? And so apparently there's some changes with respect to the eyes and the teeth.

C

So the major challenge for miniaturized organisms is packing enough cells into a tiny form to build these complex structures and salamander cells can only be so small because they are chock full of dna. Their genomes range from about three to forty times the size of the human genome, so this is an organism with a particularly large genome and that and that genome exists in chromatin.

C

You know we're liter, we're literally talking about a size reduction of such that you're. Trying to find you know ways to pack this into this: the cells that you have available. So you know we usually don't think of that as a constraint, but in these organisms they are um so they have these large genomes.

C

You know they're, you know you would think. Well, yeah you can. You know. Dna is small, but the cells are getting so small. Now that they're having problems fitting that in into the cell. So that's the problem uh now rovito and collaborators in slovenia in the united states have discovered the genome size tends to decrease with body size across the group of 60 salamander species.

C

The research reported in the american naturalist suggests that salamander genomes may evolve to make room for more cells in a miniature frame. So what these salamanders do is they reduce their genome size and that's the way they're able to do this size reduction. It's worth noting that in general- and I don't know if we've talked about it too much in this group, but there's this idea of allometric scaling.

C

So organisms can grow larger or grow smaller in a different group of organic related organisms, and these this mechanism called elemetric scaling, and what that means is that the body size usually grows. You know with maybe with environment or with some other ecological niche and as the body grows, everything else grows so the head grows and you get other body parts like the brain that grow along with it, and in this case it's so small that you're kind of reaching the bottom level of that scaling. And so you know it's a little bit difficult.

C

um You know, maybe you don't have a viable organism at a certain. You know uh size scale. You can have organisms that might be too big to survive as well. But in this case what they've solved is they've solved this problem by getting rid of genes in their genome. Now you say.

D

C

D

Right, uh there's there's some very interesting work. That was done, I think in the 1930s or 40s. That uh is somewhat similar to this. They took a salamander and made.

D

In other words, duplicates of the whole genome. Now what this results in is larger cells?

D

Okay, because for some I don't think this problem's been solved yet, for some mysterious reason, the size of the cells is proportional to the size of the genome.

D

Okay, okay. Now the observation is in this case was that the animals were the same size as the standard diploid.

D

I think they got up to seven employee, okay, okay, which means that the brain had fewer cells, the body.

A

Size was the same.

D

Okay and the animals seem to be stupider, yeah, okay, so it's it's a little bit related to this work.

F

A

Okay, yeah, so the high point you had fewer brain.

F

Souls and were stupid.

A

C

Yeah, that's uh yeah! That's an interesting uh we've talked about this before in the group. I think from time to time about salamander genomes and cell size and things like that, yeah yeah yeah. This is interesting work. It complements.

D

This older work.

C

Yeah yeah, so now you might be asking: why do we? You know? How can we get rid of dna? uh We, you know what what happens when we get rid of dna, and so you know, did they do a test for so-called junk dna right they less right yeah they have so they have uh uh this idea. You know yeah, so the genome isn't all like functional. There's a lot of dna like retrotransposons that exist in the uh you know.

C

They call it junk dna that that terminology is always being revised and what it exactly include is included in junk dna. But basically, what they're saying is that they're getting rid of a lot of this stuff?

C

That is not directly coding dna, so it looks like they say: the genome, size balloons and salamanders owning, at least in part, to abundance of repetitive dna sequences and that's known as retrotransposons, but they're. Basically things in the genome that you don't that you don't necessarily need but exists in the in the dna, and so uh retrotransposons are things that have inserted themselves into the genome.

C

You know they might be of ancient origin, but they've never been selected out because for various reasons and so that in salamanders you have a lot of this apparently okay, there's some funny.

D

Predictions here, if they try to take this miniature salamander and make a it shouldn't, survive, or it should be very stupid.

D

Okay and there's nothing to prevent them from doing it. It's the employee. Experiments are done at the.

D

Okay, yeah or I think, the fertilizer. What you.

C

Do is you prevent the cell division even.

D

Though the nucleus is divided, okay and there are standard experiments for doing that now, there's another.

C

Funny side effect.

D

We now know how to make a much higher human population, because we are supposedly 95 junk dna.

D

We could eliminate our junk dna and then select for size. We could become very tiny and become the little pushes.

A

E

D

So there's a lot of experimenting ahead.

C

So, um okay, so, let's see uh to explore this possibility collected salamanders in the forests of mexico and guatemala that belonged to a group known as the uh politu glossiness.

C

The group included salamanders spinning a wide range of sizes from this thorius, which is very small. It's roughly eight times longer it's more gigantea. So these are, you know, range of different sizes as well as species.

C

The smallest salamander is the hardest to find and they go through that. Then they say the team estimated physical size of each species based on head volume and measurements of length to nose to waste. So this is the cellometry I'm talking about where you have this relationship between say like head size, brain size and body size and it scales with the size of the organism.

C

They then looked at the relationship between genome size and physical size, while accounting for relatedness between species genome size tended to decrease, as physical size decreased, suggesting that evolution may favor smaller genomes for smaller salamanders, and so we yeah that goes back to the thing about changing the genome size for a salamander of a certain size.

C

There seems to be the scaling and genome size that is sort of.

A

C

Guess so the team also constructed a phylogenetic tree using previously published genetic data to reveal genome size changed over time as salamander species diverged.

C

The tree shows several instances of genome size reduction, including the ancestors of all of victoria's species, and so they calculated a measure called biological size for each species, which is the number of cells, an organism organism can fit within a fixed amount of space.

C

So, let's see uh the number of cells an organism can fit within a fixed amount of space. I guess that's just the packing of it, but if the yeah we talked about the dna determining the size of the cell, so that's related to that one species has a greater biological size than another of equal physical stature when it cells are smaller thanks to a smaller genome. Salamanders at this, relatively smaller cell, with relatively smaller cells, essentially of more bi cellular building blocks available, meaning they're capable of having more complex bodies.

C

The team found that the species within that species within thorius are actually larger in terms of biological size than some of the physically larger salamanders, perhaps helping them compensate for their miniature form.

C

So this is uh this: is you know this kind of goes on about like how the cell size is determining you know? There's uh there are two different things here: their cell size, which can shrink down due to uh less dna and then there's body size, and the idea is that if you have smaller cells, even if you have a smaller body, you can have a more or less complex uh phenotype, and so that may have something to do with the uh the brain function in that experiment.

C

um So they quote: ryan gregory from the university of guelph. Both possibilities may be true.

C

He points to an earlier study suggesting that small genome size evolved in the dinosaur ancestors of birds before they learn to fly, as well as his own research, suggesting that metabolic demands of flight cause modern-day birds to continue to evolve smaller genomes, you can have the prerequisite and the enhancement, and so there are other factors that can be at play.

C

uh This person here ole, miss mystery suggests that climate can have an indirect effect on genome size and frogs, uh and so there are a lot of causal factors for this, um but it there is. This phenomena of extreme miniaturization in nature- and so this is something that uh this this work kind of points to in salamanders, but this is more general, where you have this, where you get in in an organism, you know that has a range of sizes.

C

You get different species or variants that are really really tiny, and so the question is: how do you get that tiny? I mean you know you have to shrink down all of your cells and they have to function in. You know they have to maintain their function, and so how do you get to be really really small or a really really small version of a say like a salamander or you know some other organism? That's not typically that small, and so that's yeah.

D

C

D

C

D

Smaller than c elements.

C

um I'm not aware of that. I I know they're ones that are bigger in terms of cell size, oh yeah yeah as big as yeah they meet or what you know, I'm not sure yeah, I'm not sure if they're ones that are smaller, I've not heard of them they're. I can check into that.

D

Because we're presuming that, except for cell pairs, uh every cell is unique in the nematode right, which means that you couldn't reduce the number of cells.

C

Yeah yeah well yeah. You can't, I guess from c elegans I mean you could have like an common ancestor with something else that would have um yeah.

D

Yeah, maybe yeah okay, but can it let's see elegance for fewer cells for miniaturization.

C

I don't know yeah, I'm not really.

D

You you're running through a culture encounter or something like that to measure their size.

C

D

Then select the small ones and keep reading the small ones.

C

Yeah, you could do that yeah. I mean that, like people have done experimental evolution in c elegans and uh that's actually a good organism to do that in because you have a generation length of about three days and you can just keep going and.

G

E

So, okay, yeah yeah good. You got some desk space behind your lid.

E

C

Yeah not today, so so that yeah that's that paper um and I think that's pretty much it for now. um There's this other paper that we've had for a while uh tension, heterogeneity directs, foramen fate to pattern the myocardial wall.

C

I don't know if this was something that susan sent me or if I found this, but it's an interesting paper on how to diverse sulfates in complex forms and feed back to each other to sculpt. Functional organs remains unclear in the developing heart, the myocardium transitions from a simple epithelium to an intricate tissue that consists of distinct layers, the outer compact and intratrabecular layers. Defects in this process, which is known as cardiac trauma, uh trabeculation causes cardiomyopa uh myopathies and embryonic lethality, yet how tissue symmetry is broken to specify these cardiomyocytes is unknown.

C

Here we show that local tension, heterogeneity drives organ scale, patterning and sulfate decisions during this uh process in zebrafish proliferation into cellular crowding at the tissue scale triggers tension, heterogeneity among cardiomyocytes of the compact layer. It drives those with higher contractility to delaminate and see the trabecular layer. So this means that, let's see if there are any figures, I know that's a lot of words.

C

It's hard to really know what they're talking about, but basically you have this, what they call crowding induced tension, and so you have cells that are crowding together and they're, generating this tension force, and so this is triggering another process called cardiomyocyte delamination, and so I don't know if you can see these. These are pretty small figures, but they kind of show a little bit of what's going on in the embryo.

C

um I'm wondering if there's a better figure for this probably is not um but yeah. So that's another interesting paper, um so yeah they get into a bunch of different genetic experiments here in the paper. So you know.

B

C

Things you for those of you who don't read uh the biological literature much at all or don't have any experience with it. You know people will do these different experiments. Will they well where they will take out different genes or knock them down in some way that removes their function? And then the idea is in these mutants or in these knockdown models.

C

Can you observe the same process or what's the difference between say, like a normally functioning uh organism and something with this? um You know this knockdown generated, and so you know you can see different. You know see different variations and different things, and if you get the pathway, you know, if you understand the pathway, you can knock down different genes in that pathway and see what's going on in terms of the in terms of the genetics and things like that.

C

So that's actually quite common in biology to see those kind of studies, um and you know it should tell you something about the process. um So that's that's that paper. I have a bunch of things that I've kind of collected over the last couple weeks. You know we usually don't have time to go through all of them, but um I'm going to kind of leave the rest of them there. And if you want access to this folder, it will put it in the chat for you.

C

Okay, next order of business is, I think, we'll shift to talking about different manuscripts that we have sitting around and things that we need to clear the clear off the decks in the next couple weeks. You know months whatever these two I'm going to talk about. First are due for this special issue of biosystems. I believe so. This is the stuff that I'm working on with dick and with uh george mikolovsky who's, not doesn't attend the meetings, but uh this is the this geological events during the boring billion.

C

So we have this paper that we've uh been talking about. uh There's this area of evolution called the boring billion, so you go from you know the last universal common ancestor, which is one of the first organisms in the history of earth. It's very uh simple, uh and then you go maybe about a billion years before you start to get more complex organisms, and so the question is what's in this billion year period.

C

So this is a table that I think dick assembled where you have different times, estimating the boring billion, because we don't really know the exact times. We have to estimate.

D

That, oh george,.

C

Okay, george did this table, so you know we don't really know when exactly it happened, it's not like a calendar where we can look at it and check off. You know when something started and ended. We can estimate from molecular data.

C

I don't know if there's a lot of fossil data for this period, simply because of the nature of the organisms, but we can get a sense of it, and so we can get these estimates. So these estimates then, are um you know they look pretty variable. I mean they look like there's we're trying to think of how to average out this interval. Like you know, uh how do you determine the beginning? How do you determine the end? You could use an average.

C

um You know there. I I'm probably gonna. I'm gonna do some work on this. Where I'll look at the I'll match. These dates up to a phylogeny which is a tree of life and try to see if we can find like you know, maybe define some of these dates on the tree and see what it looks like, but that's something I'm gonna be doing over the holiday, um so the boring billion term did not exist. uh You know the it's basically the dullest time in earth's deep earth's, deep history, so.

D

I think it refers to lack of fossils okay, but people have been finding some fossils in that period, which is also which is literature we'll have to find.

C

I'm going to make a note here, yeah, so yeah I mean the the fossil record is going to be pretty sparse in any case, but it's basically when there is nothing really going on in terms of uh innovation and evolution. So after this time you know you get this great diversification of organisms and it didn't take a billion years. I mean it was like you know, pretty quickly relative to that time. So you know the question is: uh what is the what's going on? So I mean some of the things that were going on.

C

Were you know you had the uh the atmosphere was of a different composition, so you know we had different uh compositions of the atmosphere.

C

You had something called snowball earth, which was where the earth got really cold uh due to a series of events, and then um so I mean these sorts of things were sort of playing a role in maintaining this period of boringness, and so you know here's a review of some of the things from the fossil record.

C

um Setting up you know establishing this set this era.

C

um So it looks like a lot of good work here um and then we have features that may be on route to mosaic or regulating embryo animals, uh so this is from hyman 1940.

C

So I take this as dick's uh work because of the hymen reference. um So is that right.

D

Yeah, I pulled it out it's a 1940 book and you have to realize it's before dna before any phylogeny by genomes etc. But there's a lot of good pictures. A lot of discussion.

C

D

Things you're not going to find easily in more modern literature.

C

Yeah definitely, this is really good. um This has a lot of different species in their features here.

D

I have to scan the pictures, the figures that I, um that I quote there- okay put them in, so you can see what they're about oh.

C

Okay, yeah yeah: this is yeah.

F

C

Is really good, so that's that's gonna be forthcoming and and then we can see steps towards something called differentiation waves and features of the protozoa in table one.

C

So this is where uh we're going back to protozoa and proposing that there's something going on that looks like what's going on in development in their descendant organisms, so differentiation waves are something we find in development and then we, but we find precursors of these in much earlier uh single cell organisms, and so or I guess we also have colonies of cells like we said you know, you have single cells and then there were these aggregates of cells, and then you know you didn't step directly from a single cell to like multicellular organisms.

C

There were these intermediate steps like a bunch of different cells that were identical and so forth. So um and so that's that's yeah! That's this paper! um It's like! We have some pretty good references here too.

C

So that's due pretty soon um at the end of january. um Next paper is the periodicity of the embryo or in the embryo. uh This is something that is going to be due soon. um It made a lot of progress on it, uh the abstract the introduction.

C

So this is again the paper where there's an argument being made that there's this tempo and mode in development that there's this uh you know you can look at like development- is having this mode of cell division and cell differentiation and so to sort of show this uh this phenomena. We have a bun a couple of data sets. uh We have the c elegans data set and we have a zebrafish data set, and these two data sets are the cell tracking data sets where they track nuclei throughout development, and they provide.

C

You know information about when the cell was born, uh some differentiation information and it even its position in a in a space that we can normalize and create graphs and analysis from so we have the c elegans data set. We have the zebrafish data set and then we also have some numeric uh results that are, you know, simulations of a cell division process, and so then we go through the results and we I I redid these figures, the ones I've shown in previous meetings were not very clear.

C

These are a little bit clearer in terms of the you know, some of the data, the distributions of the data, so this is c elegans. This is uh these: are cell divisions in the out in the embryo? These are cell differentiations, both in the embryo and in the post-embryonic developmental period.

C

This is these are intervals between cell divisions, so you get these intervals between cell divisions, and this is something we discussed in the paper as to what this might mean.

C

Then you go to zebrafish in the zebrafish. You have to measure it a little bit differently. You know the way that data is presented. You have a lot more cells, so you're, looking at the total number of cells at any given point and you're looking at the number of new cells in that population, and so this is the distribution of that, and you can see this very interesting pattern of like this very strong periodicity here and then at some point in development. It breaks down and there's this aperiodic uh uh division pattern.

C

So you know why is that? Well, we don't really know, but we've kind of put- you know, pinpointed this in the graph and discuss this, and then this is of course, this sort of the same thing we did with c elegans, but because it's measured a little bit differently.

C

You have to basically look at the frequency of relative frequency of birth rate across developmental time, so it's a little bit different, but it gives a maybe a similar type of distribution because there's a sort of a long tail going on. So we have. We have that and that's discussed in the paper.

C

These are intervals between peaks so now taking the peaks of these different fluctuations and defining it in a certain way. We can get these graphs and it's discussed in the paper. This is c elegans and this is zebrafish. The zebrafish you tend to have this multi-modal distribution for whatever.

B

C

I can't remember why that is a it might be in the paper uh then. But what we do, then we go step further in zebrafish and we create this embryo network, which is uh we've. We've done. We've done research on this, where we've looked at these, where we look at the cells and we look at their proximity to one another and we can actually get a distance between them and then threshold that data set so that we create sort of a connectivity between cells.

C

So if cells are pretty close to one another they're connected if they're further apart, they're not connected, and then we get this graph here, which shows that you know we have a lot of uh there's a certain area of the cells that you know where there's like tight clustering and there are other parts of the embryo where there isn't- and so you get these modules of uh connectivity here, and so that translates into this 3d graph, which shows a lot of the sort of what's going on in space, which is that there's this cluster of cells in the middle that are forming that there there's a cluster right down.

C

The middle that have a very high degree of clustering, which means they have a lot of closely packed neighbors and then some cells further out that are a little bit less dense and then cells, even further out, which are very far apart, and so we can already start to see like so maybe some of the precursors of you know uh differentiation in this pattern, um and so then we get down to this simulation, which I won't go through, but I think I've talked about it a couple weeks ago, where you're just measuring the number of cell divisions over time, and you can use different statistical distributions to figure out.

C

You know to generate different patterns of divisions over time and we discussed this model- I'm not done with this yet, but there. You know, there's some interesting uh findings here and then this is a supplemental figure showing an embryo network and in in a model of an embryo, it's a 3d, ma cartoon, but just giving people an idea. What that looks like and then we have our, I need to add. We need to add references into this we have like.

C

Maybe I have it numbered weird, but basically our 20 references or so, and so we need probably twice that number uh to be a viable thing. So I mean you know I like to have references.

C

I always think when there are very few references that like well, you could probably put more in so it's very much yeah, it's very much a it's! It's it's come far a long way since I last showed this to people.

A

G

After some time the, uh if you can go to that image where you have separated out from the middle okay or like an orange patch, is there so I guess the video may be there. We can find it, but it's not on the same scale that we are picking right now.

G

So if you or if we can like or can go up this.

G

G

So I guess, like there is still a few periodicity that we can observe, but we have to change the scale for that, and I think like uh this can be like put it in the next graph and you can observe still some patterns because, like the scale is totally uh different, as you can see in the first half in the last time, it is moving up to 200.

C

G

So there might be some periodicity there as well, not as clear but yes, some questions.

C

Yeah, that's yeah. Look into that a little bit too.

B

I can put it into matlab and get it to do some signal processing on it. Yes,.

C

Yeah you do that.

G

Like oh, I'm now acting like, I am completely recovered from it so like. If you want like, I can contribute to these papers as well.

C

Oh yeah yeah this this paper, you know we could run out. We could run an analysis. I can send you a link to the data and you can uh look at it and see um yeah. I think this I think the zebrafish data might you might be able to do signal processing on uh the c elegans yeah. I might be able to see elegance too.

C

Yeah yeah great that yeah, that's that's good, um so this is coming.

B

C

And we're you know: um it's yeah, it's still a bit short in terms of word length too, so we could add a couple more things to it. I think it would be fine, um anyways, that's good and then the final paper- and I know mayuk, was here, but he left um there. We had this. uh We had the journal of open source software paper and that was ujwal and myself and mayok and the the people at open source software didn't like it because it wasn't like notable enough.

C

um I think they're looking for more things like things are going to be broadly used by the community. So I don't know you know there there's like scientific software, that's like very central to certain fields, and so maybe that's what they're. Looking for but anyways, uh I told mayor, you know what we'll do with the paper and you know it's not a lot of work so far, but it's it's actually.

C

You know it's. It's sort of a description of his software that he'd made and then I put in some description of divo learn the platform. So you have the platform, the software, and then um you know we didn't really talk too much about some of the other. You know we didn't get into depth about the diva learn platform in terms of like, what's what it consists of and all the different parts. So I was thinking what we could do with that is start to expand it out into something.

C

That's a lot more uh descriptive of the diva learn platform.

G

Yes, when I was going through that paper recently, I also like observed uh the paper is not as much descriptive as it has to be like in the development platform itself. We have lots of things going on so like I will uh start working on that or I guess from today, and we get completed, offer.

G

C

Yeah, you know what would be good for. You is like, if you know the stuff that you did this summer with uh reorganizing divo zoo and like the different species, specific models, if you could spell out more clearly what those are like, how those you see those fitting together and what those consist of basically describing what you did uh we you know we can have different parts of it. Like you know, I think the problem is it's it's.

C

You know it's kind of hard to kind of describe every part of it, but if we scale it up to describing the diva learn platform, what we want to have essentially is a paper that kind of spells out each part of it. So if I go to the repository, I don't have to dig around and try to figure out how it fits together and then you know we can publish this uh and it can spell out everything in the platform. So then it can drive future development.

C

So we have like the you know: diva learn software. We have uh the c elegans software that uh for open dv what we called opendivo cell from last year. We had the devo zoo part, and so all those parts are kinda. I don't know if they're fully described uh right now and then I know they're not in that paper, because we're trying to make it compact for that venue, but now that we don't have the limitations of of the journal of open source software, now we can make it. You know a much longer paper.

C

We can, you know, pull you know, pull things apart and kind of describe them in a little bit more detail, and I know my knock contacted me on slack and he said you know, I don't really understand I'd love to contribute to divalern I'd like to understand.

C

What's going on with it a bit more in more detail like he wasn't totally clear about what what the goal was. So my knock. Do you want to talk about that experience or what would be your suggestion for making that clearer.

F

Yeah, I can hear you hello, yeah hi yeah, so you are talking about the divo right, yeah, the library.

F

So uh as far as I saw library like I dived into the code a bit so from what I saw, I can conclude that it's it's still in its early stage and it still needs a lot of work to be done. So I guess we have a lot of room for improvement for the library I guess yeah. So that's it like. We need need a lot more work to be done on the software yeah.

C

Yeah yeah, you know it's, it's it's the nature of open source, we get, we start off and then we just keep working on it um but yeah. I think in terms of like when you you go to the repository, you know there there is a like, and what I'm talking about is a paper that would be like a pre-print where we would release new versions of the paper as we kind of develop things.

C

So it's not like it's not a paper set in stone, but we'd like I'd like to have something: that's you know uh descriptive that people can go to and say this is the current state of what we have, and so, uh if people want to add on, they could just say: oh yeah. This is an area uh that we can add on to and it's you know we can put. They can point to that part where you know oh in this uh directory or in this area I can definitely contribute.

C

I think that would be a good way to go and I think it would be like it would. You know foster, if not you know, development, some adoption and, of course, with open source you're adopting and people who are adopting tend to start to contribute to it. You know if they need to improve it or if they need to like add in modules.

F

And yeah, another thing that I would like to add is that, like at the divolent library right, it's like it's only like seven months or eight months old. So considering that uh we have come a very.

C

F

Yeah and like uh a year's worth of work from now and we'll be we'll definitely reach somewhere. So that's what I'm expecting from the next year.

C

F

We'll be growing.

C

A lot yeah, yeah yeah, that's good and then the other thing- and I know my oak left so I was going to talk about this, but- and I don't know if I have it in here but well- I might as well talked about with you guys about this.

C

Is that we're starting off with uh the next round of google summer of code so for 2021 and they started the process very early? They started in late january. I think, is the time that we have to have the proposals in. um So let me see if I can find the proposal on github. I know I put it up.

C

I will share my screen in a minute when I find this, but I wanted to go over this a little bit.

C

Okay, I got it so let me share my screen.

C

And so this would follow up on like developing diva learn, uh as minox said, we have a lot of opportunities, and so one of the things is to have a good proposal for uh gsoc, because gsoc is a good place to start developing things, so uh mayak has already seen these. Obviously this is his document that he sent me and I invite people if you want to be involved with this.

C

If you want to, if you have suggestions for changes, uh this is the link here and you can actually add a you know, pull request on this or you, I think a lot of you might already have access to it. But basically, if you want to make changes or suggest new things, you can issue a pull request to this markdown file. So we have a couple of ideas here, and these are all largely related to divalern.

C

uh The first is model robustness, so uh this idea that we uh just improved performance on the divo learn platform itself, the one that mayo created last year.

C

So there's there are ways to test for model robustness and what he's saying is that the project would basically be organized around this instead of just kind of like trying to run, you know like data sets, you would actually look at these things to test to see how robust the model was and then improve upon it, where the statistics show that it needs improvement. So there are all sorts of different methods that one can use the project.

C

I guess would be running through each of these methods and having someone go through and test it and see how they can improve the platform.

C

um So there's that idea- and it's not like written up very formally- so I'm not really sure what that would look like in the end it might. That may be enough see. The thing you have to remind remember about gsoc projects is that you know you have to make it so that it's they have like a criterion for usefulness, and so they want to make sure that the student is getting like a useful experience.

C

They want to make sure there's enough work there for them, so this would have to be fashioned into something like we would test the model for robustness and then, where there's less, you know where things are less robust. If we see that the models, having particular trouble in these areas on different data sets, then we would try to propose solutions to that or fix. You know come up with a solution.

C

The second uh one is usability, and so this is a general usability. This is kind of like what uh uh bojol was doing last year um in that you know there's this idea that we need a better usability strategy for diva, learn, and I think myocare was talking about documentation for the platform and for the diva learn software in particular. But you know that's something. The usability idea, I think, has legs.

C

I think we can kind of figure out, like you know, a bet, a bit a bit more sort of robust usability strategy for the entire platform and then have that person do something very specific within that. So he's talking about like having a place to host documentation like get book which is a way to host documentation or like a read the docs type thing, and so then you have that uh you can also um add use cases.

C

So use cases are things where you add in like support for more species or you can have other species where they have a deep pre-trained, deep learning model. So basically expanding diva learn to specialize in other species, because right now, we've trained it mostly on c elegans and there's an opportunity, maybe to expand that, to you, know: zebra fish or drosophila, or some other uh or model organism where there's a lot of data and so power.

B

C

Maybe yeah yeah just yeah, we, I think that's yeah and we'll have all these data. um So it's a matter of like getting you know getting a project together where we can say we have data, we have a way to wait for the person to come in and just start testing data testing the program itself, and then we can. um You know.

G

Yeah so like like a few points like uh in this proposal, that uh can you go to composer.

G

Sorry uh so it said like uh the model, obviously uh parameters that you're using right now, uh it's not uh worthy like for the whole gsoft project like the k4k4 cross, validation or certified splits and like using ensembl models.

G

So I think that might means here like gradient, boosting or something so these uh might not be uh able to like extend throughout the summer. Like oh, like it is. Oh, I don't know like oh work for a week, two or three nights at max.

C

Yeah, though that was my yeah, so my understanding too, is that the summer they're gonna shrink the gsoc program down a bit so last summer it was like, I think, how many weeks did we have like 14.

F

C

Yeah, I think it's going to shrink down by about half this year is reading. I don't remember exactly the details, but they had sent out some emails earlier and they're proposing that I don't know if that's going to actually happen, but they're, not it's not going to be as long but you're you're. Quite right about the uh the the amount of work that this involves. I mean this could be just like a weekend where I just put these things in and say: oh yeah, here's some recommendations.

C

So when we write this up, we need to make it like you're going to do you're going to start here, maybe take some different types of data sets, maybe from different species and then test the you know the robustness and we'll probably find that there's you know if we add in more data that it's going to be.

C

You know, there's.

B

Going to be something.

C

There and then from there we can have them. Do something. That's um you know like improve upon the model, but that's that in even there it's hard, because you know just saying, like you'll you'll see what happens, isn't really gonna cut it. You know like uh well, you know, I don't know we'll see what happens when we uh test the data. Maybe it's. The model is very robust and maybe it doesn't isn't robust at all. I don't think the gsa people are going to go for that very well, but yeah.

G

C

G

Me and like oh, do you uh if you remember that.

G

A bacillus project itself this year, like we, have uh left the work by identifying like where the cells are and how the cells are. Segmented like there are a lot of work to be do like the centroid, where the centroid and how the motion is running and like uh making uh the prediction of the motion that is being carried out and other techniques like. So I think, like a proposal can around. This, could also be included like if possible, because it has like a work for around one and a half or two months.

C

It sounds good, yeah yeah. It's definitely uh is there like yeah, you can probably uh you know, write up like put together some slides and sort of show what that would entail. Maybe in the new year yeah.

G

To make it a complete work, actually.

C

Right, yeah yeah. Definitely, if you have so, if you have ideas you can well, you can send them to me in slack if, if that's better or commit them to this repo, just notes or just like a a little bit of a description, a short description in words- I mean you know it's um yeah. This is a pretty rough draft here of what we would do for a project. So definitely, if you have ideas for this, uh especially in terms of targeting different species, different data sets, because you know we're gonna.

C

We don't want to have people searching for things like hey this year. We want to really have give them something like right off the bat and say here's the data and use this, especially since we have a lot of data now that we've been talking about like the salamanders, the uh bacillaria yeah. Sure. That's great! Thank you.

C

So all right that I think that's it, for this meeting um have a happy new year, and this is the last meeting of the year uh I'll be sending an email about the first meeting next year, which will be uh probably in january. Maybe the first or second week um and that at that meeting I'm gonna have a presentation, a summary for 2020, so we're going to go over everything that happened in 2020.

C

uh Some of the highlights, uh just you know, maybe planning for this coming year um and you'll- be surprised, I think, to see what we actually did over the course of this last year. I think it's been quite a nice year for uh on a number of fronts and um thank you for everyone for attending the meetings and sticking with it, and uh even you know, through the covet crisis, everyone's been pretty pretty active.

C

So I'm glad to see that everyone's been doing very well here in the group, and so um thanks for attending and talk to you later have a good new.

C