Transcript Lab Meeting #2 12-13-2010 Expression profiles and transcriptional networks in the CNS midline Wheeler et al., 2006

Lab Meeting #2
12-13-2010
Expression profiles and
transcriptional networks in the
CNS midline
Wheeler et al., 2006
High-throughput sequencing
of the midline transcriptome
Sequence
Isolate midline
cells
Generate adapterligated cDNA library
Steps to RNA-seq
Isolate Cells  Prepare cDNA Library  Sequence  Analyze
Find midline specific GAL4 driver
Stage embryos @ 25oC
Dissociate cells
Sort cells via FACS
3.7sim-GAL4; UAS-mCD8.GFP-LL6
Fluorescence Activated Cell Sorting
(FACS)
w1118
sim > LL6
Sorted GFP-
Sorted GFP+
Sort results
2 hr collection  ~75 – 125 uL of embryos
~20,000 cells / uL or ~20 x 106 cells / collection
Sort #1
14Gp01
14Gp02
Sorted Events
42,000
43,000
total RNA extracted
32ng
32ng
Sort #2
14Gp03
14Gp04
62,000
59,000
55ng
65ng
Sort #3
14Gp05
14Gp06
42,000
45,000
25ng
35ng
Steps to RNA-seq
Isolate Cells  Prepare cDNA Library  Sequence  Analyze
Isolate total RNA
Purify mRNA
Fragment mRNA
Generate double-stranded cDNA
Blunt, Phosphorylate 5’
end, Adenylate 3’ end
Ligate Adapter Sequence
Size select fragments
Enrich with PCR
Fragmenting and Size-Selecting
Size Selection
Enrichment
Product
Adapter dimer
Primer dimer
Size Selection
Product
Fragmenting and Size-Selecting
Size Selection
Enrichment
Adapters and enrichment
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Steps to RNA-seq
Isolate Cells  Prepare cDNA Library  Sequence  Analyze
Walk to Mary Ellen Jones
Take Elevator to 9th Floor
Hand off sample and
Pay lots of money
Wait
Steps to RNA-seq
Isolate Cells  Prepare cDNA Library  Sequence  Analyze
Programs Involved
Bowtie
SAMTools
Ultra-fast, memory efficient, small sequence aligner
Uses Burrows-Wheeler Transform (BWT) indexing
Sequence Alignment/Map
Tools for indexing, sorting, formatting sequence alignment data
TopHat
Fast splice-junction mapping tool
Aligns RNAseq reads to genome using Bowtie, taking into
consideration the existence of splice junctions
Cufflinks
Takes TopHat alignment data and:
Assembles transcripts
Estimates transcript abundance
Measures differential expression between samples
assemblers such as
ments to transcripts
Dilworth’s theorem18
of haplotypes from
s extends these ideas,
finding a maximum
hat represents comand Supplementary
d microRNAs21 have
nd development, and
g isoforms as a means
e-mediated decay22.
assembler does not
open reading frame
ng gene annotations
kes as input cDNA
enome by software
opHat. (b–e) With
agment reads as
pping ‘bundles’ of
s running time and
s the fragments from
the abundances of
gment assembly is
ust have originated
s are connected in an
alignments overlap
graph, and an edge,
new isoforms, 7,395 (58%) contain novel splice junctions, with the
remainder being novel combinations of known splicing outcomes;
11,712 (92%) have an ORF, 8,752 of which end at an annotated stop
codon. Although we sequenced deeply by current standards, 73% of
theInput
moderately
file: abundant transcripts
.txt .fa (15–30
.fq expected fragments per
kilobase of transcript per million fragments mapped, abbreviated
FPKM;
see below for further
explanation)
detected at the 60-h time
Options:
-i 20
(70)
point with three lanes of GAII transcriptome sequencing were fully
-I 142000 (500,000)
recovered with just a single lane. Because distinguishing a full-length
--solexa1.3-quals
transcript from a partially assembled fragment is difficult, we con(0) analyses the novel isoforms that
servatively excluded from -m
further
-g (40)
were unique to a single time
point. Out of the new isoforms, 3,724
were present in multiple time points, and 581 were present at all
time
points;files:
6,518 (51%) accepted_hits.bam
of the new isoforms and 2,316 (62%) of
Output
the multiple time point novel
isoforms were tiled by high-identity
junctions.bed
TopHat
a
Map paired cDNA
fragment sequences
to genome
TopHat
Spliced fragment
alignments
Trapnell et al., 2010
fragof known
genes.
Wegenes.
estimate
77% of
the
reads
originated
forms
of
known
Wethat
estimate
that
77%
ofbetween
the reads originated
ed
byleft
ourforms
fragom
to right
along
the
genome,
is placed
each
from previously
known transcripts
(Supplementary
Table 2). Of
the2). Of the
ssem- assemriptome
from previously
known transcripts
(Supplementary
Table
mpatible
this
example,
the
yellow,
blue
red
ch as such
newfragments.
isoforms,
7,395In
(58%)
contain
splice
junctions,
with
the and
mblers
as
new isoforms,
7,395
(58%)novel
contain
novel
splice junctions,
with the
cripts
remainder
being
novel
combinations
of
known
splicing
outcomes;
must
have
originated
from
separate
isoforms,
but
any
other
s to 18
transcripts remainder being novel combinations of known splicing outcomes;
11,712
have
an ORF,
of which
at an annotated
stop
rem
18 (92%)
rth’s theorem
11,712
(92%)
have8,752
an ORF,
8,752end
of which
endone
at an annotated
could
have
come
from
the
same
transcript
as
of ofthesestop
from
codon.
Although
we
sequenced
deeply
by
current
standards,
73%
aplotypes from codon. Although we sequenced deeply by current standards, 73% of
ideas,
the
moderately
abundant abundant
transcripts
(15–30
expected
fragments
per Paths
orms
are
thentheassembled
from transcripts
the
overlap
moderately
(15–30graph
expected(c).
fragments
per
nds
these
ideas,
kilobase
of
transcript
per
million
fragments
mapped,
abbreviated
mum
ng
a maximum
kilobase ofto
transcript
million fragments
mapped, fragments
abbreviated
e graph
correspond
sets ofpermutually
compatible
com- FPKM;
below see
for below
furtherfor
explanation)
detected atdetected
the 60-hattime
epresents
com- see
FPKM;
further explanation)
the 60-h time
be
merged
into
complete
isoforms.
The
overlap
graph
here
can
ntary
point
with
three
lanes
of
GAII
transcriptome
sequencing
were
fullywere
fully
Supplementary point with three lanes of GAII transcriptome sequencing
recovered
with
just
a
single
lane.
Because
distinguishing
a
full-length
have
21
ally
‘covered’
by
three
paths
(shaded
in
yellow,
blue
and
red),
roRNAs have recovered with just a single lane. Because distinguishing a full-length
t, and transcript
from a partially
fragment fragment
is difficult,
con- we contranscript
from aassembled
partially
assembled
iswe
difficult,
velopment,
and
esenting
a different
isoform.
Dilworth’s
Theorem
states
that
means
servatively
excluded
from
further
analyses
the
novel
isoforms
isoforms that
orms
as a means servatively excluded from further analyses the novel that
22. mutually
er
of
incompatible
reads
is
the
same
as
the
minimum
were
unique
to
a
single
time
point.
Out
of
the
new
isoforms,
3,724
cay
diated decay22. were unique to a single time point. Out of the new isoforms, 3,724
es
not does
were
multiple
time
points,
581fragments.
were
present
all
wereinpresent
multiple
time
points,
and 581
wereatCufflinks
present
at all
mbler
notpresent
transcripts
needed
to in
‘explain’
alland
the
points;
6,518
(51%)
of (51%)
the newofisoforms
2,316and
(62%)
of (62%) of
rame
time
points;
6,518
the new and
isoforms
2,316
readingtime
frame
ts
a
proof
of
Dilworth’s
Theorem
that
produces
a
minimal
set
the multiple
pointtime
novel
isoforms
tiledwere
by high-identity
ations
ene
annotations
thetime
multiple
point
novel were
isoforms
tiled by high-identity
Cufflinks
Cufflinks
Mutually
incompatible
fragments
d
c
3
3
Sequence
quality
e
Maximum likelihood
abundances
Log-likelihood
2
1
Minimum path cover
NATURE BIOTECHNO LO GY
3
2
1
Transcripts
3
Transcripts
and their
abundances
MAY 2010
Transcripts
and their
abundances
2
VO LU M E 28
VOLUME 28
NUMBER 5
1
2
3
Fragment
length
distribution
Transcript coverage
and compatibility
Sequence
c
3
1
2
1
Abundance estimation
Overlap graph
Transcripts
2
3
Minimum path cover
1
2
1
Transcripts
b
Log-likelihood
e
1
Overlap graph
Minimum pathMinimum
cover path cover
Transcripts
Maximum likelihood
abundances
Transcript coverage
and compatibility
d
Mutually
incompatible
fragments
2
Assembly
to genome
TopHat
Cufflinks
Abundance estimation
Spliced fragment
alignments
Fragment
length
distribution
name
hat cover allSequence
the fragments
in the CIGAR
overlap graph by finding the
of reads with a
the
that no two could have originated
Map property
paired cDNA
Map paired cDNA
Ainput cDNAa
fragment sequences
fragment sequences
re
ame
isoform.
Next,
transcript
abundance is estimated
to
genome
e by software
to genome
TopHat
TopHat
h (b–e) With
ents are matched (denoted here using color) to the transcripts
nt reads as
hfbundles’
they ofcould have originated. The violet fragment could have
nd
ing time and
from the blue or red isoform. Gray fragments could have come
rom
ragments from
of
fragment
bundances
of
ofis the three
shown. Cufflinks estimatesSpliced
transcript
abundances
Spliced fragment
alignments alignments
assembly is
ed
atistical
model
in
which
the
probability
of
observing
each
ve originated
Position of first base
nonnected
an
in an
s a overlap
linear function of the abundances of the transcripts from
ap
ments
ge,
and anhave
edge, originated. Because only the ends of each fragment
ould
Cufflinks
Cufflinks
ween each
nced,
ed
blue andthe
red length of each may be unknown. Assigning a fragment
Assembly
Abundance estimation
erut any other
Assembly
Abundance estimation
t isoforms
a different
length
for it. Cufflinks
b often
d
Mutually
b implies
d
Mutually
e of these
incompatible incompatible
shes
fragments
lengths to help assign fragments
(c).the
Pathsdistribution of fragment
fragments
nts
ble fragments
s.graph
Forhere
example,
the violet fragment would be much longer, and
e
can
can
Fragment
d),
Fragment from
lue and red),
bable
according to the Cufflinks model,
if it were
to come
length
Transcript coverage
length
Transcript coverage
states that
distribution distribution
and compatibility
and
compatibility
oform
instead of the blue isoform. Last, the program numerically
mum
s the minimum
Overlap
graphOverlap a
ssets.aCufflinks
function that
assigns
likelihood to all possible sets of
graph
a minimal set
hefinding the
undances
( 1, 2 , 3)
by
c of the
e blueeisoforms
c yellow, red and
Maximum likelihood
Maximum likelihood
ed
ve originated
abundances
abundances
cing
the
abundances
that
best
explain
the
observed
fragments,
mated
ipts
Log-likelihood
transcripts
Log-likelihood
athepie
chart.
vecould have
nt
ome have come
ould
ces
t abundances
ving each
m
nscripts
from
ent fragment
each
ment a fragment
gning
. Cufflinks
ments fragments
assign
Assembly
.sam formatted alignment
3
Input file:
b
NUMBER 5
MAY 2010
NATU RE BI O TECH NO LO GY
Trapnell et al., 2010
Cufflinks
Options:
Output:
-G Reference Annotation .gtf
-M Mask File .gtf
genes.expr
transcripts.expr
transcripts.gtf
FBgn #
bundle ID
Chromosome
Left Boundary
Right Boundary
FPKM
FPKM_conf_lo
FPKM_conf_hi
Status
FBtr #
bundle ID
Chromosome
Left Boundary
Right Boundary
FPKM
FMI
Frac
FPKM_conf_lo
FPKM_conf_hi
Coverage
Length
Effective Length
Status
Chromosome name
“Cufflinks”
feature: “exon” “transcript”
Start
End
Score
Strand
Frame
Attributes
Cuffcompare
Hcs
ksr
CG31550
CG31550
CG31550
CG31547
CG31547
Nmdar1
FBtr0078683
FBtr0078766
FBtr0113409
FBtr0078684
FBtr0078685
FBtr0078765
FBtr0078764
FBtr0078763
Input:
transcripts.gtf
Options:
-r
Output:
transcripts.refmap
transcripts.tmap
Gene symbol
FBtr #
Class code
FBgn#|FBtr#
Gene symbol
FBtr #
Class code
FBgn #
FBtr #
FMI
FPKM
FPKM_conf_lo
FPKM_conf_hi
Coverage
Length
Major isoform FBtr #
=
=
=
=
=
=
=
=
FBgn0037332
FBgn0015402
FBgn0051550
FBgn0051550
FBgn0051550
FBgn0051547
FBgn0051547
FBgn0010399
FBtr0078683
FBtr0078766
FBtr0113409
FBtr0078684
FBtr0078685
FBtr0078765
FBtr0078764
FBtr0078763
100
100
100
7
13
2
100
100
15.613557
62.015780
59.515339
4.176125
7.805313
0.192514
8.893786
104.835138
7.710759
46.265760
43.526016
0.000000
1.577164
0.000000
2.888758
84.357332
23.516356
77.765800
75.504663
9.549375
14.033462
1.396952
14.898814
125.312945
10.575610
42.005461
40.311825
2.828636
5.286812
0.130397
6.024073
71.008514
3970
3737
2584
2702
1849
3297
3891
4186
Issues that had to be overcome…
Chromosome Names in Genome File from UCSC :
Chromosome Names in Annotation File from ensemble:
FPKM
chr2L chr2R etc.
2L
2R
etc.
Issues that had to be overcome…
Genome Chromosomes
2L
4
2LHet
U
2R
Uextra
2RHet
X
3L
XHet
3LHet
YHet
3R
3RHet
FPKM
Annotation Chromosomes
2L
4
2LHet
U
2R
X
2RHet
XHet
3L
YHet
3LHet
3R
3RHet
Quality and Confidence
Number of reads generated
Midline Cells
23,995,806
Non-Midline Cells
23,758,803
Filtered due to low quality
67,921 (0.28%)
63,308 (0.27%)
Good quality reads
23,927,885
23,695,495
sim
ple
Vmat
argos
wrapper
elav
gcm
Midline FPKM
91.4569
77.3427
2130.63
53.4021
47.9539
176.195
1.77936
Non-Midline FPKM
0.935763
2.77772
65.0964
4.33003
21.0768
131.928
6.59764
Cursory Analysis of TFs
gene_ontology_obo.txt
[Term]
id: GO:0000117
name: regulation of transcription involved in G2/M-phase of mitotic cell cycle
namespace: biological_process
def: "Any process that regulates transcription such that the target genes are
transcribed as part of the G2/M phase of the mitotic cell cycle." [GOC:dph,
GOC:mah, GOC:tb]
related_synonym: "G2/M-specific transcription in mitotic cell cycle" []
related_synonym: "regulation of transcription from RNA polymerase II promoter
during G2/M-phase of mitotic cell cycle" []
xref_analog: Reactome:69274 "G2/M-specific transcription in mitotic cell cycle"
is_a: GO:0006357 ! regulation of transcription from RNA polymerase II promoter
is_a: GO:0022402 ! cell cycle process
relationship: part_of GO:0000086 ! G2/M transition of mitotic cell cycle
is_a:
is_a:
is_a:
is_a:
is_a:
is_a:
is_a:
is_a:
is_a:
GO:0010551
GO:0006357
GO:0005667
GO:0045892
GO:0045990
GO:0000409
GO:0045013
GO:0045991
GO:0000429
!
!
!
!
!
!
!
!
!
regulation of gene-specific transcription from RNA polymerase II promoter
regulation of transcription from RNA polymerase II promoter
transcription factor complex
negative regulation of transcription, DNA-dependent
carbon catabolite regulation of transcription
regulation of transcription by galactose
carbon catabolite repression of transcription
carbon catabolite activation of transcription
carbon catabolite regulation of transcription from RNA polymerase II promoter
181 GO terms with “transcription”
Finding Transcription Factors
gene_association.fb
“FB”
FBgn #
Gene symbol
Qualifier
GO #
10 Additional Fields
Is GO # associated with “transcription”
If Yes, copy FBgn #, gene symbol and GO#
FBgn0052062
FBgn0052062
FBgn0250816
FBgn0261953
FBgn0261953
FBgn0261953
FBgn0261953
FBgn0261953
FBgn0261953
FBgn0039946
FBgn0039946
FBgn0039946
FBgn0039946
FBgn0039946
FBgn0039946
A2bp1
A2bp1
AGO3
AP-2
AP-2
AP-2
AP-2
AP-2
AP-2
ATbp
ATbp
ATbp
ATbp
ATbp
ATbp
GO:0008134
GO:0045941
GO:0035194
GO:0003704
GO:0010552
GO:0003700
GO:0006355
GO:0003702
GO:0003700
GO:0016563
GO:0006355
GO:0006357
GO:0006357
GO:0030528
GO:0030528
FBgn0052062
FBgn0250816
FBgn0261953
FBgn0039946
FBgn0000015
FBgn0027620
FBgn0037555
FBgn0000054
FBgn0005694
FBgn0261238
FBgn0010774
FBgn0260642
FBgn0029512
FBgn0026598
FBgn0261823
A2bp1
AGO3
AP-2
ATbp
Abd-B
Acf1
Ada2b
Adf1
Aef1
Alh
Aly
Antp
Aos1
Apc2
Asx
842 genes
Extracting TFs from RNAseq Data
transcripts.tmap
FBgn0052062
FBgn0250816
FBgn0261953
FBgn0039946
FBgn0000015
FBgn0027620
FBgn0037555
FBgn0000054
FBgn0005694
FBgn0261238
FBgn0010774
FBgn0260642
FBgn0029512
FBgn0026598
FBgn0261823
Gene symbol
FBtr #
Class code
FBgn #
FBtr #
FMI
FPKM
FPKM_conf_lo
FPKM_conf_hi
Coverage
Length
Major isoform FBtr #
Name
hkb
CG9775
CG9775
CG9775
MED31
MED31
opa
corto
Trascript
FBtr0078951
FBtr0078895
FBtr0301297
FBtr0078894
FBtr0078856
FBtr0078857
FBtr0078836
FBtr0078844
Gene ID
FBgn0261434
FBgn0037261
FBgn0037261
FBgn0037261
FBgn0037262
FBgn0037262
FBgn0003002
FBgn0010313
FMI
0
100
87
2
46
100
0
100
A2bp1
AGO3
AP-2
ATbp
Abd-B
Acf1
Ada2b
Adf1
Aef1
Alh
Aly
Antp
Aos1
Apc2
Asx
FPKM
0.000000
48.615585
42.165026
0.807909
20.250985
44.226801
0.000000
123.936859
Dangers discovered so far…
biology462:cuff_with_ref Fontana$ grep MED8 transcripts.tmap
MED8
FBtr0086297 =
FBgn0034503 FBtr0086297 100
34.558291
0.000000
12.612187
biology462:cuff_with_ref Fontana$ grep FBgn0034503 genes.expr
FBgn0034503 15535
chr2R
16213345
16214311
34.5583
0
12.6122
FAIL
biology462:cuff_with_ref Fontana$ grep Vmat transcripts.tmap
Vmat
FBtr0091491 =
FBgn0260964 FBtr0091491 4
Vmat
FBtr0091492 =
FBgn0260964 FBtr0091492 0
108.881571
9.646350
91.482036
4.141926
126.281106
15.150773
biology462:cuff_with_ref Fontana$ grep FBgn0260964 genes.expr
FBgn0260964 14703
chr2R
9400631
9420494
2635.91
2550.95
2720.87
OK
18.924431
transcripts.tmap
genes.expr
Gene symbol
FBtr #
Class code
FBgn #
FBtr #
FMI
FPKM
FPKM_conf_lo
FPKM_conf_hi
Coverage
Length
Major isoform FBtr #
FBgn0052062
FBgn0250816
FBgn0261953
FBgn0039946
FBgn0000015
FBgn0027620
FBgn0037555
FBgn0000054
FBgn0005694
FBgn0261238
FBgn0010774
FBgn0260642
FBgn0029512
FBgn0026598
FBgn0261823
A2bp1
AGO3
AP-2
ATbp
Abd-B
Acf1
Ada2b
Adf1
Aef1
Alh
Aly
Antp
Aos1
Apc2
Asx
FBgn #
bundle ID
Chromosome
Left Boundary
Right Boundary
FPKM
FPKM_conf_lo
FPKM_conf_hi
Status
Transcription Factor Tally
FPKM
>5
> 20
Midline cells
512
319
Non-midline cells
604
340
FPKM ≥ 20 in midline
< 5 non-midline
MED8
FBgn0034503
34.558291
Status = Fail; FPKM 0.425
Nurf-38
FBgn0016687
24.349477
FPKM = 32 in non-midline
FMI = 44
cry
FBgn0025680
27.772590
dmrt99B FBgn0039683
55.270044
sim
87.116834
FBgn0004666
Symbol
FBgn
cry
dmrt99B
HLH3B
per
sim
Tip60
vg
FBgn0025680
FBgn0039683
FBgn0011276
FBgn0003068
FBgn0004666
FBgn0026080
FBgn0003975
Mid
FPKM
22.4535
44.6845
157.235
31.2259
91.4569
20.3645
27.9836
Mid
Status
OK
OK
OK
OK
OK
OK
OK
NonMid
FPKM
2.15868
1.98577
4.7074
3.31479
0.935763
4.5745
4.21669
NonMid
Status
OK
OK
OK
OK
OK
OK
OK
Known expression patterns
cryptochrome
period
dmrt99B
HLH3B
vg
sim
No Images for Tip60…yet!
All genes
CG33056
Midline ≥ 20;
Amyrel
argos
CG1077
CG13685
CG14044
CG14052
CG14082
CG14237
CG14238
CG31323
CG33056
CG34325
CG42456
CG6426
CG6709
CG7059
CR31846
cry
dmrt99B
HLH3B
Hsp67Ba
Pdf
per
ple
Sh
sim
Tdc2
Tip60
Tsp42En
vg
FBgn0020506
FBgn0004569
FBgn0037405
FBgn0035816
FBgn0031650
FBgn0029606
FBgn0036851
FBgn0039428
FBgn0039429
FBgn0051323
FBgn0053056
FBgn0085354
FBgn0259933
FBgn0034162
FBgn0036056
FBgn0038957
FBgn0051846
FBgn0025680
FBgn0039683
FBgn0011276
FBgn0001227
FBgn0023178
FBgn0003068
FBgn0005626
FBgn0003380
FBgn0004666
FBgn0050446
FBgn0026080
FBgn0033135
FBgn0003975
Nonmidline < 5
21.5749
53.4021
39.7551
20.2799
29.8253
22.3947
20.7989
26.0363
23.4602
21.5139
24.8664
27.8598
42.585
37.2291
33.3694
20.8566
25.6772
22.4535
44.6845
157.235
27.0698
203.259
31.2259
77.3427
29.2139
91.4569
592.613
20.3645
28.5682
27.9836
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
FAIL
OK
OK
OK
OK
OK
4.5629 OK
4.33003 OK
0.337708 OK
0
OK
3.27032 OK
0
OK
3.89604 OK
3.62562 OK
2.67148 OK
3.97617 OK
2.0825 OK
4.44943 OK
6.7805e-09
4.32297 OK
3.55502 OK
2.71942 OK
4.52441 OK
2.15868 OK
1.98577 OK
4.7074 OK
2.76941 OK
3.65838 OK
3.31479 OK
2.77772 OK
4.74804 FAIL
0.935763
3.05323 OK
4.5745 OK
4.60738 OK
4.21669 OK
OK
OK
Things to do:
Biological Replicate of Midline Sample
Earlier time-point to compare with
Validate with in situs
Look at interesting mutants
Down the line…
RNAseq of mutants or transgenically overexpressed genes
Isolate individual cell types for RNAseq
Future Direction
3.7sim-QF > QUAS-mtdTomato-3xHA
CoolEnhancer-GAL4 > UAS-GFP
3.7sim > LL5
2 Insertions on second chromosome:
Line A : 2R, 55E1 in 3’UTR of CG42697
Line B : 2R, 47F7 in 5’UTR of TapΔ
CG32105

Lmx1a

Msx1

Otx
(orthodenticle,
ocelliless)
Nkx6.1
(HGTX)
(indirectly)
Ngn2, TH, Nurr1, Pitx3
(tap) (pale) (Hr38) (Ptx1)
Runt
CG32105
3.7sim > tauGFP
T1
1
*
*
T2
1
*
*
Abdominal segments
Runt
CG32105
3.7sim > tauGFP
1
1
*
*
*
*
zfh1
CG32105
Stage 12-anterior segments
**
*
**
*
*
*
*
sim>tau-GFP
Castor
CG32105
sim>tau-GFP
Castor
CG32105
Summary of CG32105 expression
Stage 11 – not expressed early
expressed in mVUMs as soon as they are born
Stage 12 – expressed in mVUMs of all segments looked at
Stage 15-16 – not expressed in all thoracic mVUMs
may be expressed in 1-2 thoracic MNBp
expressed in abdominal mVUMs