P1 neurons

Male-specific P1 neuron analysis

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.

Setting Up

## glX 
##   1

Finding the P1 Neurons

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)