Overview
In simpler terms, Evolutionary Genetics is the study to understand how genetic
variation leads to evolutionary change.
Evolutionary Genetics attempts to account for evolution in terms of changes in gene
and genotype frequencies within populations and the processes that convert the
variation with populations into more or less permanent variation between species.
The central challenge of Evolutionary Genetics is to describe how the evolutionary
forces shape the patterns of biodiversity.
Evolutionary Genetics majorly deals with;
a. Evolution of genome structure
b. The genetic basis of speciation and adaptation
c. Genetic change in response to selection within populations
this ppt traces the evolutionary history of humans and presents the description of evolution on the basis of various theories put forward by various eminent scientists
Evolutionary Genetics by: Kim Jim F. Raborar, RN, MAEd(ue)Kim Jim Raborar
This presentation was created as a partial fulfillment of the requirements in the subject Advanced Genetics. Everything that was here were kinda symbolic. I mean, you could recognize that this was a product of so much data interpretation. I therefore suggest you read and read a lot first before you go back to this presentation. Or you could just contact me so i could send you the key-pointers.
Have a super nice day.
Kimy
First year SBC174 Evolution course - week 2
1. NeoDarwinism/ModernSynthesis
2. Major transitions in Evolution
3. Geological Timescales
4. Some drivers of evolution
This document will help you and will clear your concepts about the terms of Orthogenesis, Allometry & Adaptive Radiations, which are usually studied in evolution.
Overview
In simpler terms, Evolutionary Genetics is the study to understand how genetic
variation leads to evolutionary change.
Evolutionary Genetics attempts to account for evolution in terms of changes in gene
and genotype frequencies within populations and the processes that convert the
variation with populations into more or less permanent variation between species.
The central challenge of Evolutionary Genetics is to describe how the evolutionary
forces shape the patterns of biodiversity.
Evolutionary Genetics majorly deals with;
a. Evolution of genome structure
b. The genetic basis of speciation and adaptation
c. Genetic change in response to selection within populations
this ppt traces the evolutionary history of humans and presents the description of evolution on the basis of various theories put forward by various eminent scientists
Evolutionary Genetics by: Kim Jim F. Raborar, RN, MAEd(ue)Kim Jim Raborar
This presentation was created as a partial fulfillment of the requirements in the subject Advanced Genetics. Everything that was here were kinda symbolic. I mean, you could recognize that this was a product of so much data interpretation. I therefore suggest you read and read a lot first before you go back to this presentation. Or you could just contact me so i could send you the key-pointers.
Have a super nice day.
Kimy
First year SBC174 Evolution course - week 2
1. NeoDarwinism/ModernSynthesis
2. Major transitions in Evolution
3. Geological Timescales
4. Some drivers of evolution
This document will help you and will clear your concepts about the terms of Orthogenesis, Allometry & Adaptive Radiations, which are usually studied in evolution.
Apresentação feita pela Monica M Fernandes, consultora e designer de interfaces, especialista em usabilidade, arquitetura da informação, design centrado no usuário.
Understanding the origin and evolution of the eukaryotic cell and the full diversity of eukaryotes is relevant to many biological disciplines.
However, our current understanding of eukaryotic genomes is extremely biased, leading to a skewed view of eukaryotic biology.
We argue that a phylogeny-driven initiative to cover the full eukaryotic diversity is needed to overcome this bias.
•
◦There is an important bias in eukaryotic knowledge, affecting cultures and genomes.
Eukaryotic genomics are biased towards multicellular organisms and their parasites.
◦A phylogeny-driven initiative is needed to overcome the eukaryotic genomic bias.
◦We propose to sequence neglected cultures and increase culturing efforts.
◦Single-cell genomics should be embraced as a tool to explore eukaryotic diversity
Life-Span Human Development 9th Edition Sigelman Solutions ManualTimothyPadilla
Full download : https://alibabadownload.com/product/life-span-human-development-9th-edition-sigelman-solutions-manual/
Life-Span Human Development 9th Edition Sigelman Solutions Manual
It states that the present day complex plants and animals have evolved from earlier simpler forms of life by gradual changes. SEQUENTIAL EVOLUTION ,DIVERGENT EVOLUTION, Theories of evolution.
1. Playing Evolution With a Full
House
Fitness trade-offs between spores and
nonaggregating cells can explain the
coexistence of diverse genotypes in cellular
slime molds
Tarnita CE, Washburne A, Martinez-Garcia R, Sgro AE, Levin AS
(2015) PNAS 112(9):2776-2781
Joshua Gefen
2.
3. Say hello to slime molds…
Dictyostelium discoideum – a soil-living amoeba
from the phylum mycetozoa
Capable of unicellular - multicellular transition
Capable of asexual and sexual reproduction
Genome was sequenced and mapped in 2005.
Consists of 34Mb haploid genome with a base
composition of 77% (A+T) and 6 chromosomes
4. Life Cycle and Reproduction
Mound
Slug/Finger
Mexican Hat
Fruiting Body
5. “Loner” cells left behind after aggregation are fully viable and capable of
aggregation during future starvation cycles.
Left behind
6. Why I decided to study biology
A selfish pause…
The problem with anthropocentrism
Decisions decisions decisions…
…Evolution!
7. Social Behavior
Farming
Brock DA, Douglas TE, Queller DC, Strassmann JE
(2011). “Primitive agriculture in a social amoeba.”
Nature 469 (7330): 393–396
Cooperation and cheating
Strassman JE, Queller DC (2011). “Evolution of
cooperation and control of cheating in social
microbe.” Proc Natl Acad Sci USA 108 (Suppl
2):10855-10862
Cannibalistic sexual phagocytosis
Lewis KE, O’Day DH (1994). “Cannibalistic sexual
phagocytosis in Dictyostelium discoideum is
modulated by adenosine via an A2-like receptor.”
Cellular Signalling 6(2): 217-222
8. Questions
How is it that in nature we find a big
genotypic diversity when the main
process for spore dispersal is a reducing
mechanism?
What are the processes that lead to
bet-hedging and long-term
optimization strategies: dormancy vs.
dispersal, persistence vs. normal
growth, and exploitation vs.
exploration?
9. 𝑑𝑅
𝑑𝑡
= −
𝑐𝑅
𝑅1 2 + 𝑅
𝛼
𝑋 𝛼
𝑑𝑋 𝛼
𝑑𝑡
=
𝑐𝑅
𝑅1 2 + 𝑅
𝑋 𝛼 − 𝜇𝑋 𝛼
Methods & Terms
Several clonal natural strains were
collected and cultivated. Strains were
manipulated to begin the spore/loner
function
Michaelis-Menten kinetics were used in
order to describe the dynamic of the
spore/loner distribution
10. In order to synchronize between starvation
time, spore germination time, aggregating
time, etc., there was a need to build an
algorithm of numerical simulations (M=25
patches) undergoing desynchronized growth-
starvation cycles
11.
12. Assumptions
2. The model doesn’t test the selection of a
stock-to-spore investment ratio or the
average length of slug migration
3. The model describes only starvation
selective pressure and doesn’t deal with
other ecological terms (e.g. soil type, light,
moisture, etc.)
1. Even if there is interaction within chimeric
fruiting bodies, they are not necessary to
explain the existence of a reproductive
skew
13. More Assumptions
4. Spores are very resistant to environmental
stress but nevertheless incur a small decay
rate (δ), which is smaller than the loner
amoeba dying rate (μ)
5. If resources dwindle before the germination
period is over, the writers assumed, that the
spore returned to dormancy without
incurring any cost associated with the
abortion of germination process.
19. Discussion
Chimeric interactions between genotypes are
not necessary to explain the reproductive
skew
In a rich ecology context (variable food,
recovery environments, weak to moderate
dispersal), the loners can provide a better
explanation for the great genotypic diversity
observed in nature
The viability of loners is consistent with the
bet-hedging strategy
The quorum sensing is instrumental in the
decision to aggregate. A direct signal
mediated quorum can be behind the
mechanism of a loner/spore distribution
Editor's Notes
My name, I’m from Avigdor’s lab; I usually deal with when B decide to sporolate. I work with Tasneem…etc.
Today I’ll be talking about slime molds.
So – Zombies/Sorry, slime molds. I just like the visual analogy between the fruiting bodying and the zombie tower; both of them apparently can sporulate.
A little bit about their life cycle:
Begins with spores landing in a new place, full of food (usually e-coli).
When food dwindles, they start to aggregate – meaning: they move toward each other, stick to each other, and start to build formations: Mound Slug/Finger Mexican Hat Fruiting body, etc.
A slug is interesting fomration that can move as a multi-cellular formation which is quite a phenomenon. No central nerve system here.
So, until now, surprisingly, the main thought that the genotype diversity in the slime molds comes from the fruiting body. This article shows that it’s not. According to them, the main force for the diversity mechanism is ‘loner’ cells that were left behind or that failed to aggregate.
“Loner” cells left behind after aggregation are fully viable and capable of aggregation during future starvation cycles. (A) Freshly starved cells plated on agar (day 0). (B) Two fruiting bodies formed from starving cells in A (day 2). (C) Fruiting bodies removed from B, leaving behind only stalk and loner cells (day 2). (D) Bacteria added to loner cells left on agar in C (day 2). (E) New fruiting bodies resulting from viable loner cells from B–D (day 5). (Scale bar, 1 mm.) At this scale, individual cells cannot be observed. This image is representative of multiple replicates run with different genotypes.
Before I go on, a small selfish pause about why I decided to study biology. Maybe falsely or mistakenly, I am a non-humanist by nature which usually makes me interested in a different perspective for life; other than the anthropocentric one.
The problem with the anthropocentric perspective is that it usually fools us to believe that everything surrounds us, and we attribute to humans all the complexities we find in nature. Here we can see a very interesting social phenomoneon of a very ‘primitive’ life form.
And everything is about decisions – in fact, we don’t actually decide; we are just part of evolution.
Some examples of social behaviour we can find in slime molds:
Farming: several amoebals form a cyclical form and then cultivate e-coli germs in order to eat them later (kind of like we do with cows!)
Cannibalistic sexual phagocytosis: I think the analogy is clear
Last, cooperation and cheating: another social beviour witnessed in the lab and in nature
So the questions the article asks are:
A.
B. …bet-hedging = spread your bets evenly;
Several strains were cultivated…in order to perform a many-cycled experiment.
They used the MMK formula in order to describe the dynamic of spore/loner distribution
I don’t want to dwell on the mathematics – if you’re curious about the equations you can find a fuller explanation in the Supplementary.
In order to synchronize all these cycles (to make an even experiment), they developed a numerical simulation, using MathLab. This helped them to control all the cycles.
So you can see here, a nice diagram that can explain all the time-gaps (phases) in each cycle:
Events k and k+1 with their growth and starvation phases, showing where the spores S and loners L are measured in the diagram.
A nice diagram that represents how the Reproductive Skew is built when you have different fractions of different genotypes building fruiting bodies and a loner population.
Chimeric interactions are not necessary to produce reproductive skew in spores. Genotype A (blue) invests a fraction α1 in aggregation and (1-α1) in loners; genotype B (red) invests α2 in aggregation and (1-α2) in loners. Of the aggregating cells, 20% become stalk and 80% spores. Then, (i) if A is clonal (N initial cells), we should observe: (1-α1)N loners and a fruiting body with 0.2α1N stalk cells and 0.8α1N spore cells; (ii) if B is clonal (N initial cells), we should observe: (1-α2)N loners and a fruiting body with 0.2α2N stalk cells and 0.8α2N spore cells; and (iii) if N A cells and N B cells are plated together, and assuming there are no interactions in the chimera so that the two genotypes contribute to the stalk and spores exactly as they would within clonal aggregates, then we should observe: (1-α1)N A + (1-α2)N B loners and a chimeric fruiting body with stalk = (0.2α1N A + 0.2α2N B) and a spore mass = (0.8α1N A + 0.8α2N B). Unless α1 = α2, the chimeric spore investment appears skewed, but the same skew is also present in the stalk and is simply accounted for by the differences in loner versus spore investment between genotypes.
This is the main part of the experiment: they measured 25 different genotypes on the Y-axis, distributed between 0-1.
The X-axis represents the Mean Starvation Time (that changes stochastically between cycles), distributed between 80-2000
The value of D represents how dispersed is the system. While we don’t have any dispersal in figure A, we can see it made a well mixed population but without coexistance; meaning that in the MST of 500 (in A) we get only two kinds of genotypic population , very similar to each other. And the same, let’s say, with a MST of 1400.
When you with the dispersal process of the spores, we start to get a different kind of distribution. We can see several genotypic populations in one MST.
Different environments connected via weak-to-moderate dispersal, D, can maintain coexistence of genotypes. Mean genotype frequency of 21 genotypes (α = 0.05i; i = 0,…,20) in 25 environments. Average is taken over 60 replicates after 1,500 growth/starvation cycles in the slowest environment. (A) Without dispersal, stochastic starvation times can select for mixed strategies but no coexistence. In each environment, there is only one evolutionarily stable strategy. The surviving genotype in the simulations alternates between both highlighted genotypes in the figure due to the discretization in α. The actual winning strategy is one in between (details in SI Appendix). (B–E) In multiple environments, if food recovery is stochastic and the environments are sufficiently different, coexistence between a multitude of strategies is possible for weak-to-moderate dispersal. (F) For high dispersal, coexistence will tend to be lost—one winning genotype emerges, which bet hedges over all existing genotypes. Parameters are as in SI Appendix, Table S1. The colors correspond to frequencies such that dark blue = 0–0.0075; blue = 0.0075–0.025; green = 0.025–0.05; yellow = 0.05–0.0875; orange = 0.0875–0.125; magenta = 0.125–0.375; red = 0.375–0.625; and dark red = 0.625–1. Transitions between colors are given by gradients.
Fast-recovery environments select for investment in loners; slow-recovery environments select for investment in spores. Fast- and slow-recovery environments connected via weak-to-moderate dispersal allow for coexistence of strategies—each strategy dominates its home environment but dispersal allows for it to be present in the other environment as well.
