ISCO 2023
March 3, 2023

Long non-coding RNAs in cellular networks andgenome regulation
Piero Carninci
RIKEN Center for Integrative Medical Sciences (IMS)Team Leader
Email: carninci@riken.jp
Human Technopole
Head of the Genomics Research Centre
Email: piero.carninci@fht.org
09/03/23

Twitter: @carninci

Trieste, Italy
ICGEB (AREA science Park)

G. Del Sal

My bench

DNA sequencing!

Starting with my passion to DNA
sequencing in late 80’s
Lesson learned:

Technologies make revolutions… Often leading far from hypotheses

Technology development and the establishment of FANTOM
l @ Yoshihide Hayashizaki’s lab at RIKEN (1995)
l RIKEN wanted to develop technology to identify genes ingenome-wide scale.
l How to construct a catalogue of genes;l How genes are regulated• (1) Full-length cDNA technologies• (2) Mapping regulatory elements: Cap Analysis of Gene
Expression (CAGE; later in the presentation)

A key technology: 1. Cap chemicalbiotinylation
Cap-trapper
2. cDNA synthesis

3. Digest incomplete
cDNAs

4. Selecting only cDNAs
that reach the cap site
KEY: a method to capture complete mRNA molecules and eliminate noise
made by fragments of mRNAs (cDNAs)

Where to go, as RIKEN/Japan?
1990-95

Discussion around the Genome Project•

All discussions on how to sequence the genome.

•

How could possibly RIKEN contributesignificantly to a such large project?

1995: started technology development, 1998 started data production for the:“Mouse genome encyclopedia project”
Development of a series of technologies.

••

Full length cDNA technologies
A large-scale sequencing system
384 Capillary sequencer
40000 clones/ day capacity of plasmid preparator

How to analyze lots of sequences??
n We made the project (the experimental part at least)!
n Libraries from all mouse tissues/developmental
stages,n Millions cDNAs (= expressed genes) end-sequencedn >103,000 cDNAs fully sequenced
n How to analyze so much data?
• Call your friends• Make new friends!
• Bold proposal: invite many new friends to look at thedatan FANTOM Project:
Functional ANnoTation Of Mammalian Genome

8Unexpected discoveries
There is much more than what in textbooks

Expectations ß???à Data
Old Textbook image of a gene
Intended as “protein coding gene”

New reality- many more RNAs (mRNA, other “non coding” RNAs)

Discovery of “non-coding” RNAStill we know very little>72.7%
Discovery of the “RNAIntensively
continent” (2005)
studied.

mRNA>20,000

Transcription

Transcription

47%
mRNAs
20,929Regulation

Regulation

Regulation

53%
ncRNAs23,218~30,000
ncRNA

Translation
Regulation

95.6%
Function unknown.

cDNAsCharting genome output: gene forests, lncRNAs, antisense> 200,000 diﬀerent
types of transcripts

Transcriptional units (~groups) (44,000)

Gene forest (<19,000)
Gene desert

Regions of the genome are used multiple times, multiple RNAs as output

The new transcriptional landscapeThe traditional image ofthe transcriptome“transcriptome” refers to the collection of all the RNA transcripts

The RNA world is crowdy:“DARK MATTER”
of the transcriptome?

Controversy? from 2002- 2012 and beyondü Some attacks
ü The RIKEN cDNA libraries are full of “junk”.
à Discovery of lncRNAs
ü The RIKEN library are full of cDNA in the wrong orientation.
à Discovery of antisense RNAs.
ü Papers attacking the findings
ü Papers supporting the findings
ü Subsequent papers confirming the findings“Dogma” versus evidence from new data

16

Slide courtesy of John MattickNext to the “gene catalogue”:
How to broadly study gene regulation?

- Long journey to map regulatory elements andidentify, characterize and use novel RNAs
- Technologies ßà biology and medicine

Understanding regulatory elements in genome
Regulation ofGene Expression?
Potential Rolesin Diseases?

ncRNAs

eRNAs

mRNAs

non-coding gene
Non-coding RNAs

coding gene
Enhancers

Promoters

non-coding

non-coding

non-coding

codingvariants

variants

variants

variants

non-coding

codingCAGE to broadly map promoters (and enhancers) à 5’ UTRsCAGE
Cap Analysis of Gene Expression

Identify accurate 5’-ends of RNAs

Technology
CAP

RNA

5’

3’

Genome

Gene

RNA 1

B CAP

AAAAA

cDNA
Cap-trapping

Exon

RNA 2
CAGE
reads

RNA-seqreads• Genome-wide

CAGE
interpretation
Sequencing
RNA-seq
interpretation
Mapping

GenomeExon
Exon

Expression• Quantitative
analysis of TSS
activity andpromoter maps

AAAAA

Expression• Preciseidentification of
TSSs.

Exon
Exon

FANTOM5: Regulatory elements in most primary cell types
Samples: Variety of cells~3,000 human and mouse libraries in total• 261 authors• 120 international collaborators• 19 countries
Forrest et al. Nature 507, 462 (2014)

Overview of approaches; 3000 libraries

Primarycellcompendium

Integrated transcript sequencing• CAGE promoter map• RNA-seq transcript map• Short RNA processing map

Transcript discovery• Better gene models• New lncRNAs• New insights on processing• Promoter-centered expression map
13210 TPMGFAPMedian0

Expression
level
039635 TPMACTBMedian5067

Expression
level

Cell specific network models
Key transcription factors, Key motifs

021

947 samples

Forrest et al. Nature 507, 462 (2014)

Expected/unexpected resultsn Measure gene expressionn Infer networks globallyn Map promotersn Surprises?

FANTOM5: Promoter architectures differ in different cells~270bp, unprecedented high resolution
B4GALT1

Astrocyte donor1
Astrocyte donor2
Astrocyte donor3
CD14+ donor1
CD14+ donor2
CD14+ donor3
CD4+ donor1

CpGCpG TATA

CpGCpG CpGCpG

CD4+ donor2
CD4+ donor3
SW-13 cell line

TSS preferences:• B4GALT1 core promoter• Primary Astrocytes• CD14+ monocytes• CD4+ T-cells

Cell1 Cell2 Cell3 Cell4••

Blue, yellow and green:
Broadly usedRed:
Cell2 specific andhighly expressed

223,428 in human and 162,264 in mouse of reference TSS
Forrest et al. Nature 507, 462 (2014)

Regulatory network analysis. Why using CAGE?

CAGE tagMOGRIFY: direct cellular reprogramming

Rackham et al. A predictive computational framework for direct reprogramming
between human cell types,
Nature Genetics, 2016

hHps://mogrify.co.uk/, a FANTOM5 spinoff

More surprises

Bidirectional transcription identifies cell specific enhancers

Enhancers have bidirectional
CAGE transcription.
Bidirectional transcription
identifies the nucleosome
boundary.
Based on this, we make a rule
to locate novel transcribedenhancers over the whole
FANTOM collection.

Andersson et al. Nature 507, 455 (2014)

Gata2 TSS
Human expression ofenhancer(TPM)

Human enhancer

Reporter gene

8

6

4

2

0

Systematic in vivo characterization of active enhancers across the human body
Salivary gland

•
•
•
•

CRE1

iv

Blood vesselof epithlial cell
Endothelial cell of
hepatic sinusoid
Kidneyepithelial cell
Urothelial cell

identified 65,423 and 44,459 enhancers in human and mouse.
mu
60% are over-represented in one cell/tissue group.
Human GWAS SNPs map often on enhancers and yslpromoters (less frequently on coding exons).
Promoter and enhancer usage and QTL analysis. Garieri et al.100μm
Nat Commun. (2017)ysl
100μm
Respiratory
epithelial cell

Spleen
Heart

Brain

Cardiac fibroblast

3.0
2.5
2.0
1.5
1.0
0.5
0.0

CRE2

fp

Neuronal
stem cellnefp

NeuronAstrocyte
Spinal cord
Brain

100μm

100μm
1.5

1.0

0.5

0.0

CRE3
nt

Neuronnt

Astrocyte

Brain

100μm

100μm

Andersson et al. Nature 507, 455 (2014)

Disease-associated SNPs are enriched in enhancers

Mapping the genome regions that regulate gene activity in diseases

Andersson et al. Nature 507, 455 (2014)

Transcriptome for ALL human cells- Promoters, enhancers, lncRNAs as FANTOM5 but in “single
cells”: from cell classification to precision genomics

Giladi et al. Nature (2017)

Taking advantage of single cell work- single cell CAGE
CAGE approach to map regulatory elements and map Predispositions to Diseases
Diseases
Chromosome

ProteinSlide, Chung Chau Hon

Non-Coding Genetic Variants

Dysregulationof expression

RNA

Non-coding

GeneThe Focus : Cis-Regulatory Elements (CRE) at SINGLE CELL
Non-Coding Elements
Diseasesin Gene Regulation (promoters, enhancers)
Chromosome

ProteinSlide, Chung Chau Hon

Dysregulationof expression

RNA

Non-codingGeneWe can now profile transcription and regulatory elements in single cells
5’end sc-RNA-Seq : Testing random and oligo-dT priming on 10X Genomics Chromium

Enhancers : Both random and oligo-dT priming detects eRNA in single cells

Enhancer active in

Loci defined by bulk-CAGE+
Enhancer RNAs at
single base resolution
in single cells

Moody & Kouno et al 2021

From Kouno T., Moody J.,
Kwon AT, et al. Nature
Communications 2019

Alternative toPromoter: Differential
Usage
Upon Stimulation
Technology:
identify
regulatory
elements
in genome
Gene A
5’Seq
SignalControl5’

Different promoter usage upon
stimulation in different cells?

???

Isoform 1

3’

Isoform 2

5’Seq
SignalStimulation 5’
Cell type3’

Control vs Stimulation

Yes CAGE works at single cell, can detect expression, promoters, enhancers, lncRNAs…

Slide, Chung Chau Hon and Jonathan MoodyGWAS interpretation : Linking GWAS variants to candidate genes
We infer how genome sequence variants influence gene
expression, in health and diseases, in all human cells

Enhancer expression
in single cells

co-activity

Chung Chau Hon

Promoter expression
in single cells

Comprehensively linking gene expression to human genetics
Ø eQTL with much higher resolution at single cell levelØ unbiased cell-type specific expression controlled by genomic elements
Ø easier to understand if a given genome variation is responsible for the
onset/progression of a disease
Ø eQTL needs ~100 individuals for each cell type to be profiled

Courtesy of Jay W. Shin

Human Cell Atlas (HCA)
Comprehensive reference maps of all human cells at single cell level

US

EU
Japan

HCA meetings
1st :LaunchLondonOct 2016

2nd:
Technology
Stanford
Feb 2017

3rd :Computation
Stockholm
June 2017

4th :GeneralRehovot
Oct 2017
1st :Asia
Okinawa
Nov 2017• Single cell genomics• High-resolution 3D
imaging analysis• Bioinformatics

5th :GeneralHinxtonMar 2018

6th :GeneralCambridge
Nov 2018
2nd :
Asia
Jeju
Nov 2018

7th :GeneralTokyo
May 2019

8th :GeneralBarcelonaOct 2019
3rd:
Asia
SingaporeNov 2019

9th :GeneralVirtualJune 2021
4th:
Asia
VirtualOct 2020

……
……

5th:
Asia
VirtualNov 2021

Ø Reformulate our fundamental definition ofcell types/development & human biology.
Ø Understand health & diseases at highresolution.

A periodic table of ourcellsGraphics credit: Ania Hupalowska

The 7th HCA General Meeting in Japan

Coordination of HCA in Japan and in Asia (HCA executive office at RIKEN)

Back to the non-coding RNAs
(Is this a good name?)

CAGE to recount number of lncRNAs

Recounting lncRNAs
Number of Human lncRNA Genes

27,919robust63,132
permissive

Versus GENCODEv25 lncRNA Catalogue(number of genes)
FANTOM CAT

GENECODE
v25

9,318
stringent

19,668

7,228

7,790

with

without

CAGE

CAGE

supportsupportHon et al., Nature 543, 199 (2017)

Function:
Do we need experimental evidence?

FANTOM6: Functional lncRNA catalogue
Molecular phenotype induced by lncRNA KD

Characterization of the “new continent” of lncRNA:- lncRNA functional- Regulatory role among others- Many genes with natural antisense RNAs
Ramilowski et al. Genome Res. 30, 1060 (2020)

Jay W. Shin, Michiel de Hoon, Jordan Ramilowski

Example: KD of ZNF213-AS1 impacts cell growth and migration
Wound healing assay for ASOs targeting ZNF213-AS1

35-73% impairment of wound-closure in fibroblasts lacked ZNF213-AS1

Selected enriched biological pathways
Extracellular structure organization
Extracellular matrix disassembly
Regulation of growth
Developmental growth
GrowthRegulation of epithelial cell proliferation
Positive regulation of cell proliferation
Cell motility45

After thousands of experiments: many lncRNAs have function

HDF

Knockdown

Cell Phenotype

LQ-CAGE Transcriptomic Profiling

285 lncRNAs

194 lncRNAs

119 lncRNAs

Growth194 lncRNAs
Successful KD
68%

390 lncRNAs

iPSC

187 lncRNAs
Successful KD
48%

Slide courtesy of Jay Shin and Chi Wai Yip

Permissive
Growth8%+27%

187 lncRNAs
GrowthPermissive
Growth6%+12%

Molecular
phenotype11%

Ramilowki JA, Yip CW.
Genome Research 2019123 lncRNAs
Molecular
phenotype11%

Stem Specific
ChangeCell-type Specific
Change5%+16%

Note: lncRNAs
may befuncWonal inanother cell
type or assay

How to collect information about lncRNAs,
faster?

Can we collect how and where lncRNAs
interact, their “interactome”?

RNA-DNA interactions affect epigenome and gene regulationin cis
RNAs

Local regulation- DNA repair- Structure- XIST,etc.

in trans-More interaction
Role?

e.g. HOTAIRTranslation

e.g. Transcription
Factor

37% of lncRNAs chromatin-bound
What is the role of RNA-chromatin interaction in cis and in trans ?
- Activate genes? Promoter? Enhancer?
- Repress genes? Insulator?

RADICL-seq captures RNA-DNA interactions in intact crosslinked nuclei
mESCs, crosslinked with Formaldehyde.
aDNase digestion,chromatin
preparation& Rnase H treatment

nucleusAA

RNA ligation

DNA ligation

A

A

A

A

T A

A

T
A

A

A

A

Reactions in the nucleus
RNA
A

A

Reversal of crosslinks
RNA

T
A

adapter

adapter

gDNA
gDNA

Reverse transcription,
second stand synthesis

gDNA

cDNA

adapter

cDNA
cDNA

adapter

gDNA

EcoP15I
digestion

Single read 150bp,
HiSeq2500

Sequencing linkers ligation,
biotin pull-down

gDNA

A

Other cell types that have been successfully tested with RADICL seq: miPSCs, mMEF, mOPC.
Typicalbseq. depth: 11FAlane HiSeq2500/each
replica. c 1FA_n1 0.90 0.91 0.90 0.90 0.90
2FA
1

10 100 1000

1

10

100

1

10 100 1000
1000
100
10

1.00

1
1000
100

0.75

10

0.91

0.90

0.92

0.90
1000

Bonetti et al. Nature Communications 11, 1018 (2020)
Reads Fraction

1FA_n2

1

1FA_n3

100

0.91

0.92

0.93

0.50

10
1

100
10

0.25

2FA_n1

0.89

0.89

1
1000

2FA_n2

0.92

100
10

Alessandro Bonetti

Interactome analysis: mostly introns in cis; lncRNAs interact more often in transBonetti et al. Nature Communications 11, 1018 (2020)

Translation
AAAAAAAAA

mRNA
hnRNA

E

I

E

I

E

14K transcripts
Degraded

For eachcell type, basedon iPS cells
data

RNA

~8 M interactions

lncRNA/ncRNA

1400 transcripts

RNA sequence and structure unknown, need full-length RNA seq

Chromosome 19 zoom in

Chromosome 19 zoom in

Different cell types with different interactions patterns of lncRNAs in transmouse embryonic stem cells

Slide courtesy of Alessandro Bonetti

mouse oligodendrocyte progenitor cells

Bonetti et al. Nature Communications 11, 1018 (2020)

Cell models and FANTOM6 RADICL libraries (~15 cell types)
iPSC-Neuron series (2 reps each): iPS to neurons

THP-1 series: THP-1 monocyte to macrophage

iPSC-mNGN2 / NSC from iPSC-mNGN2 / Neuron from iPSC-mNGN2Each rep 120~240 M(mapq10)

THP-1 (DMSO, PMA 24h, 96h)
Each rep 80~120 M(mapq10)

Pre F6 cell lines

iPSC (F6)(3 reps)Each rep~200 M(mapq10)

HDF(humandermalfibroblast)(2 reps)Each rep~130 M(mapq10)

ENCODE cell lines

MCF7
MCF10A
K562
HCT116(breast cancer (mammary gland, (chronic myeloid (colorectal
cell line)
non-tumorigenic leukemia (CML) carcinoma(2 reps)epithelial) (2 reps) cell line) (2 reps) cell line )Each rep(2 reps)~80 M
Each rep ~120 M(mapq10)(mapq10)T cell CD4+(naïve and active(Th1))(Beatrice Bodega lab)
(2 donors each)

Each rep
22~33 M(mapq10)AML samples
from paNents(acute myeloid
leukemia)(Andreas Lennartssonlab) (2 donors)

Each rep ~15 M(mapq10)

In trans interactions increase along differentiation process;lncRNAs and intronic RNAs have different targets
Type of interactions- initial

60%

88.4%

11.6%

25%

25%

11,6% transbeforeafter

before

cis
trans

25%

after

Type
interactionsin DMSO
interactions
and after Chicane
interactions before
andof
after
Chicanebefore

cis
trans

40%

25%

40% trans

50%

Interactions
cis
trans

after
beforeafter

Laura Carpen, IIT
25%

3.1%

cis
trans

0%
beforeafter

beforeafter

Typeof before
interactionsin Chicane
PMA96
and afterinteractions before andinteractions
after
ChicaneTypeofChicaneinteractionsin PMA24
interactions before andafterinteractions
before andafter Chicane

100%

60.6%
75%

Interactions

50%

cis
trans

19.2%

25%

3,1% trans a+er
Chicanepercentage

cis
trans

Interactions

cis
trans

68.8%

80.8%

Interactions

Interactions

68,8% trans

75%

50%

50%

25%

25%

0%

0%

beforepercentage

percentage

Interactions

50%

96.9%

75%

0%

Interactions

0%

0%

0%

50%

percentage

cis
trans

75%

75%

75%

percentage

Interactions

50%

percentage

percentage

75%

31.2%

percentage

75%

50%

Type
of interactions in PMA96
Type of interactions in
PMA96

Type of interactions inType
PMA24
of interactions in PMA24

of interactions in DMSOType of interactions inType
DMSO

75%

Type of interactions in PMA 96 h

Type of interactions in stimulation PMA 24 h

Interactions
50%

cis
trans

39.4%

25%

19,2% trans after
Chicane39,4% trans after
Chicane

Laura Carpen,
after_w/oMALAT1
Aslihan
Karabakack
Calvielllointeractions before and after Chicane
interactions before
and after
Chicaneinteractions before and after Chicane
Signals sent through RNAs from gene to other genesand regulatory elements? Rodrigo Pracana, HT
0%

beforeafter_w/oMALAT1

beforeafter_w/oMALAT1

0%

beforeA new type of crosstalk: RNA - genome
in the nuclei

Further characterization of functions:- structural?
- (epi)genome control?

SINEUPs
More unexpected function of lncRNAs andrepetitive elements• COI disclosure• I am co-founder of Transine Therapeutics, a UK company that aims to develop
therapeutics based on the SINEUP technology discussed in the presentation.
https://www.transinetx.com/

SINEUPs: an important example of antisense RNA function
AS Uch-l1 regulates endogenous UCH-L1 protein expression
Uch-l1

AS Uch-l1 mRNA (original non-coding RNA)
pcDNA3-AS Uch-l1 (cDNA in plasmid)

qRT-PCR

AS Uch-l1

Uch-l1

Empty vector

pcDNA3-AS Uch-l1

Western blotting
torScv e A3 -A
y
t
p
DN
Em
pc
KDa
UCH-L1

34
26

Uc

h -l

1

Empty vector

pcDNA3-AS Uch-l1

No changes at RNA level
Protein level:dramatically enhanced!!

β-ACTIN

Carrieri et al, Nature 491, 454 (2012)

SINEUPs: an important example of antisense RNA function
AS Uch-l1 activity requires the inverted SINEB2(Alu)

Uch-l1
AS Uch-l1

Inverted SINEB2
pcDNA3-AS Uch-l1
pcDNA3-AS Uch-l1 D Alu
DAlu
DSINEB2

pcDNA3-AS Uch-l1 D SINEB2
pcDNA3-AS Uch-l1 flipSINEB2

flipSINEB2

REPEAT MASKER analysis of AS Uch-l1 sequence*

UCH-L1

2

B2
N E A lu
I
S
D
f lip
1 D h - l1
1
l
- l1
h
h
h-l
c
c
c
c
U
U
U
U
S
S
S
AS
-A
3-A A 3-A A 33
A
N
N
N
NA
pty
cD
c D *p c D p c D
m
p
p
*
E
*
*
**
***
N
SI

EB

X X

β-ACTIN
Carrieri et al, Nature 491, 454 (2012)

SINEUPs
Antisense lncRNAs for therapy

Using SINEUPs (antisense lncRNAs)SINEUP

Effector Domain (ED)ü Having function to enhance proteintranslation|||||||

Target mRNA

Binding Domain (BD)ü Complementary sequence to aregion of target mRNAü Can be synthesized for any targetmRNAsØ Customizable design for any proteinsØ Up-regulates protein synthesis 2-5 folds (physiological range)
Ø Acts on endogenous mRNA and exogenous targets

SINEUPs: in vivo model of human diseases in Medaka
Microphtalmia with Linear Skin Lesions (MLS)
Cox7B mRNA

SINEUP-Cox7B|||||||

SINEUP-Cox7B
Figure 1. Photographs of Individuals in whom COX7B Mutations Were Identified(A and B) Photographs of case 2 at the ages of 1 year and 10 months (A) and 7 years (B). She had an asymmetric face with limited eyelid
closure and linear skin defects (which became less obvious with age) on the face and neck.
(C) Pedigree of family 1. Proband II.4 is the fourth child of healthy and unrelated parents. The couple has three healthy daughters, II.1,
II.2, and II.3, and one healthy son, II.5. Three pregnancies ended with spontaneous abortions of unknown sex early in the first trimester.
(D–H) Photographs of individual II.4 (F–H) and her mother (I.2). At birth, individual I.2 presented with linear skin defects, which healedwith scaring (arrows in D and E). Individual II.4 had facial dysmorphism with telecanthus, long upslanting palpebral fissures, a shortnose, mild retrognathia, and posteriorly rotated ears (G). Linear and patchy erythroderma is located on the cheeks and neck; it wasmore pronounced at birth (F) than at the age of 5 years (H).

Cox7B proteinsrepresents a remarkable example of a truly developmental
phenotype associated with mitochondrial dysfunction.
Moreover, the skin involvement in mitochondrial diseases
is atypical and can include hirsutism and hypertrichosis as
described in Leigh syndrome (MIM 256000) and twisted
hairs as reported in Bjornstad syndrome (MIM 262000).13
HCCS is highly conserved throughout evolution fromfungi to metazoan and catalyzes the incorporation ofheme moieties on both cytochrome (Cyt) c1, an integral
component of MRC complex (C) III, and Cytc, the mitochondrial CIII–CIV electron shuttle.14,15 A few clinicallydiagnosed MLS cases in whom no mutations in HCCS could
be found have been identified16,17 (B.F. and K.K., unpublished results), thus suggesting genetic heterogeneity forthis disorder. In all these cases, analysis of the methylation
pattern revealed 100% skewing of X chromosome inactivation in peripheral-blood cells (data not shown).
We postulated that mutations affecting other components of CIII–CIV could lead to the MLS phenotype. Cytochrome c oxidase (COX), a fundamental MRC complex(CIV), in humans comprises three mitochondrial-encoded
proteins (COX1, COX2, and COX3) that assemble withten nuclear-encoded proteins (COX4, COX5A, COX5B,
COX6A, COX6B, COX6C, COX7A, COX7B, COX7C, andCOX8) to form the mature holocomplex.18–21 Because of
the expected X-linked inheritance pattern, we selected,
among possible candidates, the only X-linked gene,

Embryo: WT
Eye:Normalanalysis failed to detect mutations in HCCS, and we foundthree mutations in COX7B.
Case 1 is the first child of unrelated Jewish parents. She
was born at term and displayed linear skin lesions on theneck and face at birth. Her mother had had two previous
spontaneous abortions of unknown sex during the firsttrimesterof pregnancy. This individual presented with facial
Figure 1. Photographs of Individuals in whom COX7B Mutations Were Identified
dysmorphisms,
short stature,
microcephaly,
andandpoor(A and B) Photographsof case 2
at the ages of 1 year
10 months (A) and 7 years (B). She hadclosurelinear skin was
defects(whichbecameless obvious
growth.
Eye andexamination
normalandshowedneither with age) on the face and neck.
(C) Pedigree offamily1. Proband
II.4 is Her
the fourthchild of healthy and unrelated parents. The
microphthalmia
norvisualimpairment.
psychomotor
II.2, and II.3, and one healthy son, II.5. Three pregnancies ended with spontaneous abortions ofdevelopment
was
normal.
A
full
descriptionof
thiscase is(D–H)
Photographs of individual II.4 (F–H) and her mother (I.2). At birth, individual I.2 present
24
available.
Fluorescenthybridization
studieswith scaring(arrowsin
in situ
D andE). Individual(FISH)
II.4 hadfacial dysmorphism with telecanthus, lo
nose,deletion
mild retrognathia,
and posteriorly
ears (G). Linear and patchy erythroderma is
excluded
and translocationof the rotated
Xp22 region.
more
pronounced
at birththan atthe age of 5 years (H).
Case
2 was
born atterm(F)from
nonconsanguineousparents. She presented with poor growth, microcephaly,
multiple linear skin defects on the face and neck, an asymrepresents a remarkable example of a truly developmental analysis failed to detec
metric face with limited eyelid closure, a small chin, and aphenotype associatedmitochondrial dysfunction. three mutations in CO
A. withetal.,right clumped Indrierifoot. A right
diaphragmatic
hernia wasCase 1 is the first ch
Moreover,Scientific
the skin involvementin mitochondrial diseases
Reports,
surgically corrected. A cranial
ultrasound2016
revealed a thinis atypical and can include hirsutism and hypertrichosis as was born at term andcorpus callosum. No ocular abnormalities were detected.
described in Leigh syndrome (MIM 256000) and twisted neck and face at birth.
An echocardiogram showed ventricular hypertrophy,
hairs as reported in Bjornstad syndrome (MIM 262000).13 spontaneous abortions
pulmonary hypertension, and a small atrial septal defect.
HCCS is highly conserved throughout evolution from trimester of pregnancy.
She also had left renal agenesis and ureteral duplication
fungi to metazoan and catalyzes the incorporation of dysmorphisms, shortof the right kidney. During a follow-up examination, sheheme moieties on both cytochrome (Cyt) c1, an integral growth. Eye examinati
showed short stature. Linear skin defects healed
overcomponent of MRC complex (C) III, and Cytc, the mito- microphthalmia nor vitime, although they were still evident on 14,15
the cheeks andchondrial CIII–CIV electron shuttle.
A few clinically development was norm
chin (Figures 1A and 1B). She had mild psychomotor

MLS

MLS + SINEUP

Diseased

Rescued~50%

SINEUPs Therapeutics – haploinsufficiencies & others
At least 300 haploinsufficiency genes known(Dang et al., European Journal of Human Genetics, DOI: 10.1038/ejhg.2008.111, 2008)

targettargettargettargetSINEUP-Target

targettargetlack of a copy of a genecause diseases

Healthy

Haploinsufficiencies
Or conditions that require more protein

Therapeutic SINEUPs

Regulating genome activitynMany lncRNAs have regulatory +structural role, sometimes otherfunctions.
nnLarge scale ahead

We always need novel
technologies to answer newquestions in gene regulation

Including computational approaches
to measure large networks
n Common diseases are caused by small
unbalances of gene regulation for longtime. lncRNA are the new frontier for
drug development.
nProtein coding
targeting, well known
Non-coding
genome,essential
regulatory role
Future opportunities in gene regulation

https://humantechnopole.it/en/

Piero Carninci
Genomics Research Center,
Human Technopole, Milan,
Italy
RIKEN IMS, Yokohama- Creating bridges between
Japanese and Italian science- New positions and chances
to collaborate
09/03/23

Special thanks to:
RIKEN
Michiel de Hoon
Chung Chau Hon
Jonathan Moody
Takeya Kasukawa
Tsukasa Kouno
Jessica Severin
Masayoshi Itoh
Harukazu Suzuki
Hazuki Takahashi
Harshita Sharma
Masaki Kato
Naoko Toki
Erik Arner
Alessandro Bonetti
Jay W. Shin
Chi Wai (Wallace) Yip
Matthew Valentine
Xufeng Shu
Lokesh Tripathi

Human Technopole

Univ. Copenhagen
KAUST
Funding
Yoshimi Inaba
Albin Sandelin
Valerio Orlando- Horizon2020,
Laura Carpen
Robin Andersson
Univ. Melbourne- ZENCODE-ITN
Marco Gaviraghi
Kristoffer Vitting-Seerup
Christine Wells- MEXT, Japan
Ilaria Nisoli
The Roslin InstituteUniv. Piedmont- AMED, Japan
Chiara Medaglia
Kenneth Baillie
Claudio Santoro
Aslihan Karabacak
Tom Freeman
Diego CotellaInstitutional funding
Rodrigo Pracana
Kim SummersTIGEM- RIKEN
Magda Bienko
Univ. Edinburgh
Alessia Indrieri- Human Technopole
Lorenzo CalvielloMartin Taylor
Brunella FrancoTokyo Metropolitan
Birmingham Univ.
Universitá degli Studi
Institute of Medical
Ferenc Mueller
di Milano
Science
Imperial College
Beatrice Bodega
Hideya Kawaji
LondonIIT Istituto Italiano di
Yokohama City
Boris Lenhard
Tecnologia
University
Univ. Hosp Regensburg Stefano Gustincich
Jordan Ramilowski
Harry Perkins Institute Michael Rehli
DZNE
of Medical ResearchPeter Heutink
Alistair Forrest
Telethon Kids Institute
Timo Lassmann
Karolinska Institutet
And to many more FANTOM Consortium members, lab members, students,
Carsten Daubhistorical collaborators…
Andreas Lennartsson

Thank you

The proportion of noncoding DNA broadly increases with
developmental complexity
Vertebrates
Vertebrates

Urochordate

Ciona (urochordate)

Invertebrates

Invertebrates

PlantsPlantsComplex fungi (Neurospora)
Simple eukaryotes (yeasts, plasmodium, Dictyostelium)

Complex fungi

Prokaryotes
Simple eukaryotes

Prokaryotes

Irrespective of the extent of non-coding sequences, it is now
evident that the vast majority of the genomes of all organisms
is transcribed in a dynamic manner in different cells and tissues
at different developmental stages.
J.S. Mattick Nature Reviews Genetics 5, 316-323 (2004)
R.J. Taft, M. Pheasant and J.S. Mattick, Bioessays 29, 288-299 (2007)

Non-coding RNA expression in mouse brain

1,328 ncRNAs examined:
849 found to be expressed in brain
60 ubiquitous
623 highly cell- or region-specific[Mercer et al. (2008) PNAS 105: 716-721]

Subcellular localization of ncRNAs

Subcellular localisation of long ncRNAs in Purkinje cells
Subcellular localization ~ putative function

Cell-type-specific lncRNAs implicated in GWAS traits

Hon et al.,Nature 543, 199(2017)

Many lncRNAs with potential function
Co-expression of lncRNA-mRNApairs linked by eQTL

Identified 19,175 potentiallyfunctional lncRNAs in humanHon et al., Nature 543, 199 (2017)

Considerations: localization of lncRNAs
And functional interactions
Heterochromatin(inactive)

NucleusEuchromatin
RNA

Nucleolus

CytoplasmØ 64% in the nucleus- 37% in chromatin-bound- 27% in the nuclear soluble fraction

Ø 36% in the cytoplasm
72Analyzing tCREs : Gene expression + enhancer activity in one assay
SCAFE : Software to define, quantify and link tCREs from 10x 5’data
Make the most of your 10x 5’data…..for FREE!

on
It’s

!
b
u
H
Git

https://github.com/chung-lab/scafe
Slide courtesy of Chung Chau Hon

End-to-end solution for 10x 5’dataProgress in HCA

e.g.

Brain: 172 Donors, 466 specimens, 9.9M Estimated cells
Blood: 664 Donors, 2.5k specimens, 2.2M Estimated cells
Immune: 9 Donors, 69 specimens, 274.2k Estimated cells
As of December 1, 2021, https://data.humancellatlas.org