Male-specific P1 neurons are believed to be key regulators of male sexual behaviour. These neurons originate from a single neuroblast (which appears to be present in both sexes) but the action of doublesex (in both sexes) results in the selective presence of a group of at least 30 neurons only in males [kimura 2008].
We have found that some of these neurons are present in females. And also found different subtypes of the male ones.
## glX
## 1
Plot of single P1 neuron, showing the male enlarged regions (MER).
First let’s plot the MER defined by Cachero, Ostrovsky et al 2010.
MER=read.hxsurf("tvalsIS2-ascii.surf", RegionChoice = 'Outer')
MER=xform_brain(MER, ref=FCWB, sample=IS2)
op=structure(list(FOV = 0, userMatrix = structure(c(1, 0, 0, 0,
0, -1, 0, 0, 0, 0, -1, 0, -11.4369961735046, 0.409557479101537,
0, 1), .Dim = c(4L, 4L)), scale = c(1, 1, 1), zoom = 0.694575011730194), .Names = c("FOV",
"userMatrix", "scale", "zoom"))
par3d(op)
plot3d(MER,col='red',alpha=0.3)
and then plot the P1 neuron fru-M-400046.
clear3d()
plot3d(FCWB)
op=structure(list(FOV = 0, userMatrix = structure(c(1, 0, 0, 0,
0, -1, 0, 0, 0, 0, -1, 0, -12.0171653055846, -48.5492559524481,
0, 1), .Dim = c(4L, 4L)), scale = c(1, 1, 1), zoom = 0.288610458374023), .Names = c("FOV",
"userMatrix", "scale", "zoom"))
par3d(op)
plot3d("FruMARCM-M000769_seg002", col='black', soma=T, lwd=5)
plot3d(MER,col='red',alpha=0.3)
Plot again in a posterior view.
clear3d()
plot3d(FCWB)
op=structure(list(FOV = 0, userMatrix = structure(c(-1, 0, 0, 0,
0, -1, 0, 0, 0, 0, 1, 0, 12.0171653055846, -48.5492559524481,
0, 1), .Dim = c(4L, 4L)), scale = c(1, 1, 1), zoom = 0.288610458374023), .Names = c("FOV",
"userMatrix", "scale", "zoom"))
par3d(op)
plot3d("FruMARCM-M000769_seg002", col='black', soma=T, lwd=5)
plot3d(MER,col='red',alpha=0.3)
We’ve already made a data.frame containing a set of P1 neurons along with other very similar neurons, starting from a search using a tracing of the P1 stalk from a neuroblast clone. Let’s load that up.
p1df=load_si_data('p1df.rds')
# see below for origin of this
missing.p1s=c("FruMARCM-M002554_seg001", "FruMARCM-M000150_seg004", "FruMARCM-F001932_seg001",
"FruMARCM-F001491_seg001", "TPHMARCM-242F_seg1", "TPHMARCM-811F_seg1")
p1s=dps[union(p1df$item,missing.p1s)]
Let’s check the sex and driver line for these neurons.
with(p1s,table(Driver,Gender))
## Gender
## Driver F M
## Cha-Gal4 9 0
## fru-Gal4 8 93
## Gad1-Gal4 3 0
## Trh-Gal4 13 5
## VGlut-Gal4 12 0
So male fru-Gal4 neurons are the clear majority but, there is a significant number of non-fru and female neurons. Let’s cluster by morphology, also labelling the neurons by driver and showing the sex by the colour of the labels.
First we need to fetch/set a score matrix for these P1 neurons (to save time/bandwidth compared with downloading the 2Gb 16k x 16k scorematrix).
p1scoremat <- load_si_data("p1scoremat.rds")
options(flycircuit.scoremat="p1scoremat")
Now we can run the clustering.
hcp1s=hclustfc(names(p1s), unsquare = T)
dendp1s=color_clusters(hcp1s,k=2)
dendp1s=set_leaf_colours(dendp1s, col_to_set = 'label',
col=with(p1s,structure(c(M='cyan',F='magenta')[Gender],.Names=gene_name)))
labels(dendp1s)=subset(p1s, subset = labels(dendp1s), rval='data.frame')$Driver
par(mar=c(4,2,0,0), cex=.6)
plot(dendp1s)
So there is a large group in which male fru neurons are the majority.
Plotting the neurons coloured by drivers emphasised that the main group are fru-Gal4 positive.
clear3d()
par3d(op)
par3d(zoom=0.7)
plot3d(p1s, col=factor(Driver), soma=T)