Guillaume DELEVOYE

Lab Meeting 09/04/19

Everything is unique

Everyone is unique

What makes you unique ?

Blood type

Genetic variants

DNA

Measurable attributes

Personal history

Personnality

Tastes

Health status

Name

Date of birth

Parents

Combination makes you unique

Blood type

Genetic variants

DNA

Measurable attributes

Personal history

Personnality

Tastes

Health status

Name

Date of birth

Parents

A x B x C x D x E x F ...

Spoofing 101

Security checks are efficient, quick, and therefore rely on checking proxies to your identity

ID Card

Whitelist

Appearance

 

Password

What specification for a security system ?

So how would the nature do ?

Comment fait la nature pour:

 

1 - Faire la même chose que nous ?

2 - Le faire aussi bien mieux que nous ?

In practice

How would the nature do ? (Immune System)

Natural killer, missing self immunuity

HLA system

PRR

Th1 cells

Antibody selection

Cell proliferation

PAMP

CMH/HLA-DR

Inflammation

Dendritic Cells, Anergic T cells &

Isotypical conversion, memory B Cell

T Cells interactions

Opsonisation

Hormonal stress

Self, non-self, ID-spoofing

How is it related to my work

Pharm D Thesis:

• Donor-recipient compatibility in graft: Hacking the stem cell's ID-card

 

PhD Thesis:

• How the genetical non-self is recognized in Paramecium

How the genetical non-self is recognized in Paramecium

=

Present = Ruins that remained after the apocalypse(s)

Apocalypse now

Transposable elements

Horizontal transfer of TE

• TE are considered as "sharing an ancestor with viruses"
• They could transfer horizontally by their own or through pathogens, pollinators, symbiosis, plasmids...

... And many others

Autonomous copy/paste + horizontal transfer = Global Invasion

TE = Chaotic invasion ? Yes !

Genome Biol Evol. 2017

"Evolution and Diversity of Transposable Elements in Vertebrate Genomes" (Cibele G.)

Extreme case 1)

Maize

Up to 86%

He dead ?

Extreme case 2)

• Prokaryote
• One of the smallest genome ever sequenced
• No TE, no transposase
• Only known exception to day

Prochlorococcus marinus SS120

The selfish gene - 1976

• Finalist/Anthropomorphist analogy: "The DNA is selfish and only 'wants' to reproduce itself" --> Parasitic DNA

 

• With limited resources, the best DNA replicators "win"

 

• The evolution and natural selection could be better described by "DNA replicators" rather than species

 

=

If it survived

 

It should have been adapted to TE

Many strategies exist against TE

piRNA, siRNA

RNA Guided Methylation of DNA

Histone modification

CNVs

Hypermutation (neurospora crassa)

Random excision

RNA decays against non-sens ORFs

...

The global story remains a mystery

• A wide range of strategies exist
• Eucaryotes, procaryotes and archea have very different mechanisms
• This suggest a progressive, separate, even constant adaptation

The ciliates: a specific case

Paramecium tetraurelia

• Eucaryote, Ciliate
• 3 nuclei:
  • 2xMIC nuclei (2n)
    • Reproduction
  • 1xMAC nucleus (up to 800n)
    • Transcription
    • Partial MIC

 

 

 

 

MIC/MAC Differenciation

Transposable elements are suppressed in the MAC, where the transcription occurs

 

Avoids the negative effect of TE

PiggyMac

IES

In 2018, question is...

...How does the cell know where to cut ?

And even more than that

• WGD potentially implies a lot of ohnologous TE

• How would the cell still recognize them over the time ?

Genetic drift...

Answer:

It's not fully understood

Hypothesis

RNA mediated methylation ?

antisens RNA ?

Nucleosome positionning ?

Modified bases: 3 modifications tracked among many others

PacBio sequencing

99% accuracy

Max

75% accuracy

Methylation analysis needs local > 25X

Trained model (ML) allows detection of suspect downturns of polymerase (function of the -3/+8 nt context) --> IPD are captured

Sorting the sequences

Differential mapping

Sequences that come from MIC

N changes

"=" becomes "I"

Diffential mapping

Sequences that come from MAC

The score threshold

The modification/identification scores are sold by PacBio as PHRED scores

For our experiments: we should have about ~30% of modified bases if this is true

--> Modification scores are NOT prhed scores (at least in our case)

Modification scores overall

 

Score distributions: The case of the adenines

 

Can we apply the GMM to other samples ?

Score distributions: The case of cytosines

Score distributions: The case of G and T

Available Data

 

HT2

HT6

HTVEG

 

MAB

MT1A-1B

MT1A-1B-2

MT2

NM9_10

NM4_9_10

WT

 

Silenced

Sorting stats

Using only the GMM

Adenines

All A in GMM

• Same MIC/MAC in AT
• No difference between experiments
• ~95% methylated symetrically

 

All A in GMM

out the AT

HTVEG

~ Same for every silencing experiment

 

Lack of sequences (~50 VS ~2.000) don't really allow comparaison between MIC and MAC

Using idQv20 + GMM

Adenines

GMM + idQV20

 

• Raises the % located in AT
• Methylated fraction goes down to 0.9-1%
• NM4-9-10 goes down to 50% in the MAC
• Logos don't change significantly

Cytosines

Qv20/IdQv20

Logo from HTVEG MAC

Identical everywhere

Conclusion

Other

Oila oila

Thx :)