MW 11:00-12:15 in Beckman B302 Prof: Gill Bejerano TAs: Jim Notwell & Harendra Guturu
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Transcript of MW 11:00-12:15 in Beckman B302 Prof: Gill Bejerano TAs: Jim Notwell & Harendra Guturu
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MW 11:00-12:15 in Beckman B302Prof: Gill BejeranoTAs: Jim Notwell & Harendra Guturu
CS173
Lecture 6: NON protein coding genes
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Announcements• HW1 due in one week.
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TTATATTGAATTTTCAAAAATTCTTACTTTTTTTTTGGATGGACGCAAAGAAGTTTAATAATCATATTACATGGCATTACCACCATATACATATCCATATCTAATCTTACTTATATGTTGTGGAAATGTAAAGAGCCCCATTATCTTAGCCTAAAAAAACCTTCTCTTTGGAACTTTCAGTAATACGCTTAACTGCTCATTGCTATATTGAAGTACGGATTAGAAGCCGCCGAGCGGGCGACAGCCCTCCGACGGAAGACTCTCCTCCGTGCGTCCTCGTCTTCACCGGTCGCGTTCCTGAAACGCAGATGTGCCTCGCGCCGCACTGCTCCGAACAATAAAGATTCTACAATACTAGCTTTTATGGTTATGAAGAGGAAAAATTGGCAGTAACCTGGCCCCACAAACCTTCAAATTAACGAATCAAATTAACAACCATAGGATGATAATGCGATTAGTTTTTTAGCCTTATTTCTGGGGTAATTAATCAGCGAAGCGATGATTTTTGATCTATTAACAGATATATAAATGGAAAAGCTGCATAACCACTTTAACTAATACTTTCAACATTTTCAGTTTGTATTACTTCTTATTCAAATGTCATAAAAGTATCAACAAAAAATTGTTAATATACCTCTATACTTTAACGTCAAGGAGAAAAAACTATAATGACTAAATCTCATTCAGAAGAAGTGATTGTACCTGAGTTCAATTCTAGCGCAAAGGAATTACCAAGACCATTGGCCGAAAAGTGCCCGAGCATAATTAAGAAATTTATAAGCGCTTATGATGCTAAACCGGATTTTGTTGCTAGATCGCCTGGTAGAGTCAATCTAATTGGTGAACATATTGATTATTGTGACTTCTCGGTTTTACCTTTAGCTATTGATTTTGATATGCTTTGCGCCGTCAAAGTTTTGAACGATGAGATTTCAAGTCTTAAAGCTATATCAGAGGGCTAAGCATGTGTATTCTGAATCTTTAAGAGTCTTGAAGGCTGTGAAATTAATGACTACAGCGAGCTTTACTGCCGACGAAGACTTTTTCAAGCAATTTGGTGCCTTGATGAACGAGTCTCAAGCTTCTTGCGATAAACTTTACGAATGTTCTTGTCCAGAGATTGACAAAATTTGTTCCATTGCTTTGTCAAATGGATCATATGGTTCCCGTTTGACCGGAGCTGGCTGGGGTGGTTGTACTGTTCACTTGGTTCCAGGGGGCCCAAATGGCAACATAGAAAAGGTAAAAGAAGCCCTTGCCAATGAGTTCTACAAGGTCAAGTACCCTAAGATCACTGATGCTGAGCTAGAAAATGCTATCATCGTCTCTAAACCAGCATTGGGCAGCTGTCTATATGAATTAGTCAAGTATACTTCTTTTTTTTACTTTGTTCAGAACAACTTCTCATTTTTTTCTACTCATAACTTTAGCATCACAAAATACGCAATAATAACGAGTAGTAACACTTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCACAAACTTTAAAACACAGGGACAAAATTCTTGATATGCTTTCAACCGCTGCGTTTTGGATACCTATTCTTGACATGATATGACTACCATTTTGTTATTGTACGTGGGGCAGTTGACGTCTTATCATATGTCAAAGTTGCGAAGTTCTTGGCAAGTTGCCAACTGACGAGATGCAGTAACACTTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCACAAACTTTAAAACACAGGGACAAAATTCTTGATATGCTTTCAACCGCTGCGTTTTGGATACCTATTCTTGACATGATATGACTACCATTTTGTTATTGTACGTGGGGCAGTTGACGTCTTATCATATGTCAAAGTCATTTGCGAAGTTCTTGGCAAGTTGCCAACTGACGAGATGCAGTTTCCTACGCATAATAAGAATAGGAGGGAATATCAAGCCAGACAATCTATCATTACATTTAAGCGGCTCTTCAAAAAGATTGAACTCTCGCCAACTTATGGAATCTTCCAATGAGACCTTTGCGCCAAATAATGTGGATTTGGAAAAAGAGTATAAGTCATCTCAGAGTAATATAACTACCGAAGTTTATGAGGCATCGAGCTTTGAAGAAAAAGTAAGCTCAGAAAAACCTCAATACAGCTCATTCTGGAAGAAAATCTATTATGAATATGTGGTCGTTGACAAATCAATCTTGGGTGTTTCTATTCTGGATTCATTTATGTACAACCAGGACTTGAAGCCCGTCGAAAAAGAAAGGCGGGTTTGGTCCTGGTACAATTATTGTTACTTCTGGCTTGCTGAATGTTTCAATATCAACACTTGGCAAATTGCAGCTACAGGTCTACAACTGGGTCTAAATTGGTGGCAGTGTTGGATAACAATTTGGATTGGGTACGGTTTCGTTGGTGCTTTTGTTGTTTTGGCCTCTAGAGTTGGATCTGCTTATCATTTGTCATTCCCTATATCATCTAGAGCATCATTCGGTATTTTCTTCTCTTTATGGCCCGTTATTAACAGAGTCGTCATGGCCATCGTTTGGTATAGTGTCCAAGCTTATATTGCGGCAACTCCCGTATCATTAATGCTGAAATCTATCTTTGGAAAAGATTTACAATGATTGTACGTGGGGCAGTTGACGTCTTATCATATGTCAAAGTCATTTGCGAAGTTCTTGGCAAGTTGCCAACTGACGAGATGCAGTAACACTTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCACAAACTTTAAAACACAGGGACAAAATTCTTGATATGCTTTCAACCGCTGCGTTTTGGATACCTATTCTTGACATGATATGACTACCATTTTGTTATTGTTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATGTTTTCAATGTAAGAGATTTCGATTATCTTATAGTTCATACATGCTTCAACTACTTAATAAATGATTGTATGATAATAAAG
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“non coding” RNAs (ncRNA)
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Central Dogma of Biology:
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Active forms of “non coding” RNA
reverse transcription
long non-coding RNA
microRNA
rRNA, snRNA, snoRNA
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What is ncRNA?• Non-coding RNA (ncRNA) is an RNA that functions without being
translated to a protein.• Known roles for ncRNAs:
– RNA catalyzes excision/ligation in introns.– RNA catalyzes the maturation of tRNA.– RNA catalyzes peptide bond formation.– RNA is a required subunit in telomerase.– RNA plays roles in immunity and development (RNAi).– RNA plays a role in dosage compensation.– RNA plays a role in carbon storage.– RNA is a major subunit in the SRP, which is important in protein trafficking.– RNA guides RNA modification.
– RNA can do so many different functions, it is thought in the beginning there was an RNA World, where RNA was both the information carrier and active molecule.
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“non coding” RNAs (ncRNA)
Small structural RNAs (ssRNA)
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AAUUGCGGGAAAGGGGUCAACAGCCGUUCAGUACCAAGUCUCAGGGGAAACUUUGAGAUGGCCUUGCAAAGGGUAUGGUAAUAAGCUGACGGACAUGGUCCUAACCACGCAGCCAAGUCCUAAGUCAACAGAUCUUCUGUUGAUAUGGAUGCAGUUCA
ssRNA Folds into Secondary and 3D Structures
P 6b
P 6a
P 6
P 4
P 5P 5a
P 5b
P 5c
120
140
160
180
200
220
240
260
AAU
UGCGGG
AAA
GGGGUCA
ACAGCCG UUCAGU
ACCA
AGUCUCAGGGGAAA
CUUUGAGAU
GGCCUUGCA A A G G G U A U
GGUAA
UA AGC
UGACGGACA
UGGUCC
UAA
CCA CGCA
GC
CAA
GUCC
UAA G
UCAACAG
AU C U
UCUGUUGAU
AU
GGAU
GC
AGU
UC A
Cate, et al. (Cech & Doudna).(1996) Science 273:1678.
Waring & Davies. (1984) Gene 28: 277.
We would like to predict them from sequence.
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For example, tRNA
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tRNA Activity
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ssRNA structure rules• Canonical basepairs:
– Watson-Crick basepairs:• G – C• A – U
– Wobble basepair:• G - U
• Stacks: continuous nested basepairs. (energetically favorable)
• Non-basepaired loops:– Hairpin loop– Bulge– Internal loop– Multiloop
• Pseudo-knots
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Ab initio RNA structure prediction: lots of Dynamic Programming
• Objective: Maximizing the number of base pairs (Nussinov et al, 1978)
simple model:(i, j) = 1 if allowedfancier model:GC > AU > GU
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Pseudoknots drastically increase computational complexity
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Objective: Minimize Secondary StructureFree Energy at 37 OC:
C G U U U G G GUU
CACAAACG
-2 .0
-2 .1
-0 .9
-0 .9
-1 .8
-1 .6
+ 5 .0
G helix = GC GG C
+ G
G UC A
+ 2G
U UA A
+ G
U GA C
=
-2.0 kcal/mol - 2.1 kcal/mol + 2x(-0.9) kcal/mol - 1.8 kcal/mol = -7.7 kcal/mol
Ghairpin loop = G
initiation (6 nucleotides) + Gmismatch
G GC A
=
5.0 kcal/mol - 1.6 kcal/mol = 3.4 kcal/mol
Gtotal = G
hairpin + Ghelix = 3.4 kcal/mol - 7.7 kcal/mol = -4.3 kcal/mol
Mathews, Disney, Childs, Schroeder, Zuker, & Turner. 2004. PNAS 101: 7287.
Instead of (i, j), measure and sum energies:
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Zuker’s algorithm MFOLD: computing loop dependent energies
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Bafna 1
RNA structure
• Base-pairing defines a secondary structure. The base-pairing is usually non-crossing.
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S aSu
S cSg
S gSc
S uSa
S a
S c
S g
S u
S SS
1. A CFG
S aSu
acSgu
accSggu
accuSaggu
accuSSaggu
accugScSaggu
accuggSccSaggu
accuggaccSaggu
accuggacccSgaggu
accuggacccuSagaggu
accuggacccuuagaggu
2. A derivation of “accuggacccuuagaggu”3. Corresponding structure
Stochastic context-free grammar
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Cool algorithmics. Unfortunately…
– Random DNA (with high GC content) often folds into low-energy structures.
– We will mention powerful newer methods later on.
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ssRNA transcription• ssRNAs like tRNAs are usually encoded by short
“non coding” genes, that transcribe independently.• Found in both the UCSC “known genes” track, and
as a subtrack of the RepeatMasker track
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“non coding” RNAs (ncRNA)
microRNAs (miRNA/miR)
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MicroRNA (miR)
mRNA
~70nt ~22nt miR match to target mRNAis quite loose.
a single miR can regulate the expression of hundreds of genes.
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MicroRNA Transcription
mRNA
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MicroRNA Transcription
mRNA
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MicroRNA (miR)
mRNA
~70nt ~22nt miR match to target mRNAis quite loose.
a single miR can regulate the expression of hundreds of genes.
Computational challenges:Predict miRs.Predict miR targets.
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MicroRNA Therapeutics
mRNA
~70nt ~22nt miR match to target mRNAis quite loose.
a single miR can regulate the expression of hundreds of genes.
Idea: bolster/inhibit miR production tobroadly modulate protein productionHope: “right” the good guys and/or “wrong” the bad guysChallenge: and not vice versa.
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Other Non Coding Transcripts
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lncRNAs (long non coding RNAs)
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Don’t seem to fold into clear structures (or only a sub-region does).Diverse roles only now starting to be understood.
Hard to detect or predict function computationally (currently)
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lncRNAs come in many flavors
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X chromosome inactivation in mammals
X X X Y
X
Dosage compensation
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Xist – X inactive-specific transcript
Avner and Heard, Nat. Rev. Genetics 2001 2(1):59-67
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Transcripts, transcripts everywhere
Human Genome
Transcribed* (Tx)
Tx from both strands*
* True size of set unknown
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Or are they?
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The million dollar question
Human Genome
Transcribed* (Tx)
Tx from both strands*
* True size of set unknown
Leaky tx?
Functional?
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Coding and non-coding gene production
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The cell is constantly making new proteins and ncRNAs.
These perform their function for a while,
And are then degraded.
Newly made coding and non coding gene products take their place.
The picture within a cell is constantly “refreshing”.
To change its behavior a cell can change the repertoire of genes and ncRNAs it makes.
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Cell differentiation
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To change its behavior a cell can change the repertoire of genes and ncRNAs it makes.
That is exactly what happens when cells differentiate during development from stem cells to their different final fates.
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Human manipulation of cell fate
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To change its behavior a cell can change the repertoire of genes and ncRNAs it makes.
We have learned (in a dish) to:1 control differentiation2 reverse differentiation3 hop between different states
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Cell replacement therapies
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We want to use this knowledge to provide a patient with healthy self cells of a needed type.
We have learned (in a dish) to:1 control differentiation2 reverse differentiation3 hop between different states
(iPS = induced pluripotent stem cells)
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How does this happen?
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Different cells in our body hold copies of (essentially) the same genome.
Yet they express very different repertoires of proteins and non-coding RNAs.
How do cells do it?
A: like they do everything else: using their proteins & ncRNAs…
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Gene Regulation
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Some proteins and non coding RNAs go “back” to bind DNA near genes, turning these genes on and off.
GeneDNA
Proteins
To be continued…
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ReviewLecture 6• Central dogma recap
–Genes, proteins and non coding RNAs• RNA world hypothesis• Small structural RNAs
–Sequence, structure, function–Structure prediction–Transcription mode
• MicroRNAs–Functions–Modes of transcription
• lncRNAs–Xist
• Genome wide (and context wide) transcription–How much?–To what goals?
• Gene transcription and cell identity–Cell differentiation–Human manipulation of cell fates
• Gene regulation control
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(On Mondays) ask students to stack the chairs without wheels at the back of the room at the end of class.