 |
Previous Article | Next Article 
The Journal of Neuroscience, December 1, 1998, 18(23):9948-9953
Cell Production and Cell Death in the Generation of Variation in
Neuron Number
Richelle C.
Strom and
Robert W.
Williams
Center for Neuroscience, Department of Anatomy and Neurobiology,
University of Tennessee, Memphis, Tennessee 38163
 |
ABSTRACT |
Retinal ganglion cell numbers in adult mice vary from 40,000 to
80,000. Much of this variation and the prominent bimodality of strain
averages are generated by allelic variants at the neuron number control
1 (Nnc1) locus on chromosome 11. The
Nnc1 locus may modulate either ganglion cell production
or the severity of ganglion cell death. Here we have determined what
the relative contributions of these two processes are to variation in
adult cell number by estimating total ganglion cell production in 10 strains of mice (A/J, BALB/cJ, BXD32, C57BL/6J, CAST/Ei, CARL/ChGo, CE/J, C3H/HeSnJ, DBA/2J, and LP/J). These strains have adult
populations that range from 45,000 to 76,000 (data available at
http://qtl.ml.org). We estimated cell production by counting ganglion
cell axons after ganglion cell neurogenesis but before the onset of
significant cell death. Total cell production ranges from 131,000 to
224,000, and most of the variation in adult ganglion cell number is
explained by this significant variation in cell production. In
contrast, the percentage of cell death is relatively uniform in most
strains (~69% cell loss). The exceptions are BXD32, a strain that
has an extremely high adult cell population, and Mus
caroli (CARL/ChGo), a wild southeast Asian species that is
distantly related to laboratory strains. In BXD32 and M.
caroli, ~62% of the population dies. Our analysis indicates
that substitutions of single alleles at the Nnc1 locus
are responsible for production differences of ~8000 ganglion cells.
Key words:
neurogenesis; cell death; genetic variation; Nnc1; retinal ganglion cell; strain variation; retinal
development
 |
INTRODUCTION |
Numbers of retinal ganglion cells
range from 50,000 in nocturnal rodents to several million in diurnal
birds and primates (Rager and Rager, 1978 ; Rakic and Riley, 1983 ;
Finlay and Pallas, 1989 ; Williams et al., 1996 ). Variation is also
marked within species; numbers range from 0.7 to 1.5 million in humans
(Curcio and Allen, 1990 ) and from 40,000 to 80,000 in mice (Williams et al., 1996 ). In mice, the distribution of strain averages is bimodal, with distinct modes centered at 55,000 and 64,000. We have demonstrated that this variation is primarily genetic, with a heritability of ~0.8
(Williams et al., 1996 ). We subsequently discovered that most of the
bimodality in strain averages is controlled by a major quantitative
trait locus, neuron number control 1 (Nnc1). This quantitative trait locus is located on chromosome (Chr) 11 and is closely linked to three genes known to influence retinal
development the retinoic acid receptor , neuregulin, and the
thyroid hormone receptor (Williams et al., 1998a ). Nnc1
may influence ganglion cell number by modulating either cell production
or the severity of natural cell death.
Our principal objectives in this study were to determine the
developmental mechanism by which allelic variants at Nnc1
control neuron number and to assess the relative contributions of cell production and cell death to the consistent and pronounced differences in population size among strains of mice. We examined ganglion cell
production in 10 strains four selected from the low mode, four from
the high mode, and one each from the high and low extreme (see Fig. 1).
We specifically included strains C57BL/6J and DBA/2J, the parental
strains of the set of recombinant inbred mice used to map
Nnc1. Mechanisms generating neuron number differences
between these two strains can be more confidently assigned to
Nnc1. Total ganglion cell production was estimated by
counting retinal ganglion cell axons at birth, a time at which ganglion
cell generation in mice is complete (Dräger, 1985 ) but before
significant ganglion cell death has begun (Linden and Pinto, 1985 ).
 |
MATERIALS AND METHODS |
Animals. As illustrated in Figure
1, strains of mice were chosen primarily
to represent the two major modes in ganglion cell number (Williams et
al., 1996 ). Three standard inbred strains were selected from the low
mode (C57BL/6J, A/J, and LP/J) and four standard inbred strains were
selected from the high mode (BALB/cJ, C3H/HeSnJ, CE/J, and DBA/2J). All
of these strains were obtained from the Jackson Laboratory (Bar Harbor,
ME). In addition, we selected two strains, CAST/Ei and BXD32, that have
exceptionally low and high ganglion cell numbers, respectively. BXD32
was obtained from Dr. Benjamin Taylor at the Jackson Laboratory.
CAST/Ei is an inbred strain derived from Mus musculus
castaneus that we obtained from Dr. Eva Eicher at the
Jackson Laboratory. Finally, we studied an outbred sample of Mus
caroli that we refer to as CARL/ChGo, a strain that falls into the
low ganglion cell mode. CARL/ChGo is a partially inbred strain of
M. caroli given to us by Dr. Dan Goldowitz at the University
of Tennessee. Both CARL/ChGo and CAST/Ei are representatives of wild
species endemic to southeast Asia. All mice were mated in our colony to
produce neonates. The day of birth was designated postnatal day 0 (P0).

View larger version (31K):
[in this window]
[in a new window]
|
Figure 1.
Bimodal distribution of adult ganglion cell
averages for 60 inbred strains. The strains include 38 recombinant and
17 standard inbred strains listed by Williams et al. (1996) and 5 additional strains, 3 of which are included in this study. A Gaussian
probability distribution was computed for each strain and summed to
obtain a probability density plot (for methods, see Williams et al.,
1996 ). The figure shows that most strains fall into two main
modes. The Gaussian function drawn in the
background has a mean of 60.6 ± 6.3 (× 1000), the
average ± SD of the 60 strains. The arrows
designate the strain averages for the 10 strains examined in this
study.
|
|
Tissue preparation. We anesthetized neonates by placing them
on ice for several minutes. Neonates were then perfused transcardially with 0.1 M PBS (0.9%), followed by fixative (2.5%
glutaraldehyde and 2.0% paraformaldehyde in 0.1 M
phosphate buffer). Midorbital segments of optic nerves were dissected,
osmicated, and embedded in Spurr's resin. Nerves were thin-sectioned,
placed on formvar-coated grids, and stained with lead citrate and
uranyl acetate.
Estimating ganglion cell number. We estimated ganglion cell
numbers by counting axons in optic nerve cross-sections (Williams et
al., 1996 ). Previous studies have demonstrated that axon counts are
reliable estimates of ganglion cell number; bifurcating axons, retinopetal axons, and retinoretinal axons are comparatively rare in
mammals even during development [Perry et al. (1983) ; Chalupa et al.
(1984) ; Lia et al. (1986) ; Williams et al. (1986) ; Rice et al. (1995) ,
see their Table 2]. Nerves were photographed in a grid pattern at
~30,000× using a JEOL EX2000II electron microscope. High and
low magnifications were calibrated for each case by photographing a
grid replica (2160 lines/mm; EMS, Fort Washington, PA).
Unmyelinated axons were easily identified (Fig.
2). Axons were counted directly on
negatives within a 63 mm × 86 mm counting frame. Total axon estimates were calculated by multiplying the mean axon density by the
total area of the optic nerve.

View larger version (217K):
[in this window]
[in a new window]
|
Figure 2.
Electron micrograph from a cross-section of a
neonatal optic nerve (C3H/HeSnJ). Magnification is 15,000×. Axons at
this stage have a relatively uniform diameter, with a mean fiber
diameter of ~0.4 µm. Axons can be recognized unambiguously in
well-fixed tissue. The two structures marked by arrows
are astrocyte processes and were not counted. Scale bar, 1 µm.
|
|
We counted necrotic axons in neonatal optic nerves from two strains
belonging to the high mode and two strains belonging to the low mode.
We did this by systematically scanning the entire optic nerve
cross-section for necrotic axons at 15,000×. The criteria for
distinguishing necrotic axons are those described by Williams et al.
(1986) . We also searched for growth cones in the sample of photographs
used for counting axons and by scanning several optic nerves at high
magnification (>40,000×).
Random numbers for Monte Carlo simulations were generated in Microsoft
Excel 98. These numbers were drawn from a normal distribution with seed
parameters (mean ± SD) taken from our experimental
ganglion cell distributions (see Fig. 4 legend for more details).
 |
RESULTS |
The retinal ganglion cell population at birth ranged from 131,000 to 224,000 (Table 1). The mean for all 46 cases is 182,500 ± 4400 (± SE). This value is almost three times
higher than the average for an equally diverse sample of adult mice
(Williams et al., 1996 ). On average we counted five neonates per
strain. The coefficient of variation within strains averaged 8.2%,
only slightly higher than the 7.2% value obtained for adult mice
(Williams et al., 1996 ). The small increase is probably caused by the
technical difficulty of counting axons before they are myelinated.
Given the anticipated variation in the stage of maturation of sets of neonatal mice killed at birth, this coefficient of variation is low and suggests that the ganglion cell population within a strain is
comparatively stable at this stage of development. The average coefficient of error (the SE divided by the sample mean)
averaged 4.5% in neonates and 2.5% in adults. These values provide an
assessment of the reliability of adult and neonatal ganglion cell
counts.
Cell production
If strain differences in adult ganglion cell numbers result from
differences in the number of neurons that are generated, then at birth
each strain should have a population that is approximately threefold
higher than its adult mean. The slope of the regression should be close
to 1/3, and the correlation should be high. This is what we
found. The slope of a free regression for the 10 strains is 0.26 ± 0.07 (Fig. 3). Forcing the regression
line through the origin produces the expected slope of 1/3 with
an excellent fit (Fig. 3, inset). The positive
y-intercept (11,600 adult cells) in the free regression may
result from sampling error or nonlinearity of cell death or may
indicate a basal level of cell production. The correlation coefficient
of the free regression in Figure 3 is 0.81, and the corresponding
coefficient of determination (r2) is
0.66. Thus, two-thirds of the variance in adult cell number can be
readily explained by strain differences in cell genesis.

View larger version (22K):
[in this window]
[in a new window]
|
Figure 3.
Regression of P0 and adult ganglion cell number
averages for 10 strains. The error bars represent 1 SE. The
thin regression line includes all strains, and the
coefficient of determination for these data is 0.66, whereas the
dark regression line excludes strains CAST/Ei and BXD32,
and the coefficient of determination is 0.77. Inset, A
plot of the same data but with the regression line forced through the
origin.
|
|
We were particularly interested in understanding the process that
produces the bimodality of adult strain averages, and for this reason
we also restricted the analysis to the eight strains belonging to high
and low modes (Fig. 3, dark line). The coefficient of
determination for this subset of points is 0.77, indicating that the
bimodality is generated primarily by differences in ganglion cell
production. The remaining "unexplained" variance must result from
strain differences in the severity of cell death, developmental noise,
and technical error.
Our statistical analysis is complicated by two factors. First, the
parameters plotted in Figure 3 are not formally independent because
total cell production cannot be less than the adult population. Second,
the distribution of adult values is far from normal (Fig. 1).
Conventional statistical estimates are therefore difficult to
interpret. To address these problems, we performed Monte Carlo simulations to test cell production and cell death models using seed
parameters taken from the adult distribution. We also subtracted the
adult population from the neonatal population to insure independence between the parameters (Fig.
4A). Figure 4,
B and C, shows the outcomes of two typical Monte
Carlo simulations in which we plot adult cell number against the number
of lost cells. The first model (Fig. 4B) assumes that
all differences in adult cell number are caused by matched differences
in cell production and that cell death is strictly proportional to cell
production. The second model (Fig. 4C) assumes that all
differences among adult strains are caused by variation in the severity
of cell death and that at birth all strains have approximately the same
cell population (~180,400 ± 18,400 cells). In the cell
production simulation (Fig. 4B), the regression slope
is +1.2, whereas in the cell death simulation (Fig. 4C), the
slope is 1.1. Our actual data set (Fig. 4A) with its slope of +1.5 strongly supports a cell production model.

View larger version (20K):
[in this window]
[in a new window]
|
Figure 4.
Regression of the number of cells that are lost
(number at P0 minus the number at maturity) and adult ganglion cell
number from our data (A) and two alternative
Monte Carlo simulations (B, C). The first
model (B) assumes that all differences in
ganglion cell number are caused by cell production differences, whereas
the second model (C) assumes that all differences
are caused by variation in the severity of cell death. Monte Carlo data
sets consisted of 200 numbers randomly selected from normal
distributions. In both models, high and low adult ganglion cell groups
(n = 100 each) were selected from two normal
distributions with seed parameters (mean ± SD) from the five high
(66,800 ± 5400) and five low (50,920 ± 3800) strains that
we studied. In the production model (B), means
were obtained from two normal distributions with seed parameters
(mean ± SD) from the five high (202,680 ± 15,500) and five
low (158,100 ± 21,200) strains. In the case of the cell death
model (C), in which no production differences are
assumed, the neonatal means were obtained from a single distribution,
with a mean ± SD of all 10 strains combined (180,390 ± 18,400). The slope obtained with our real data is +1.5
(A), whereas the slopes of the cell production
(B) and cell death (C)
models are +1.2 and 1.1, respectively. The positive slope from our
data is close to that of the simulated cell production model,
demonstrating that differences in adult ganglion cell number are
predominantly caused by differences in cell production. In these
analyses, we used model I linear least-square regression, because the
measurement error term is without bias. Adult ganglion cell number was
subtracted from P0 ganglion cell number to make the
y-axis formally independent of adult ganglion cell
number plotted on the x-axis.
|
|
The 10 inbred strains were divided into high (BALB/cJ, C3H/HeSnJ, CE/J,
BXD32, and DBA/2J) and low (C57BL/6J, A/J, CAST/Ei, CARL/ChGo, and
LP/J) groups. Mean adult ganglion cell numbers for these groups are
66,800 ± 2700 and 50,900 ± 1900, respectively. There are
highly significant differences in ganglion cell production between
these groups, with means of 202,700 ± 7800 and 158,100 ± 10,600, respectively (t test, p < 0.001).
In contrast, there is no significant difference in the percentage of
ganglion cell loss between high and low groups, with mean percentages
of cell loss relative to neonatal values of 66.9 and 67.5%,
respectively (p = 0.42).
Nnc1 was mapped using recombinant inbred strains generated
from the parental strains DBA/2J and C57BL/6J. For this reason a
comparison between these two strains is especially germane in discovering how Nnc1 modulates ganglion cell number. The
severity of cell death was closely matched between DBA/2J and C57BL/6J (69 and 70%, respectively). In contrast, DBA/2J produces ~16,400 more cells than does C57BL/6J. This result, together with our previous
finding of additive gene action (Williams et al., 1998a ), indicates
that the substitution of a single allele at Nnc1 is associated with a production difference of ~8000 cells.
Cell death
With the exception of strains BXD32, CARL/ChGo, and BALB/cJ, the
average percentage of cell death among strains is relatively uniform
(Table 1, 69 ± 1.2%). Although the percentage of cell death is
relatively uniform, the absolute magnitude of ganglion cell death is
variable among strains and is highly correlated with production values
(Table 1). There are some notable exceptions to this generality. The
percentage of cell death in BXD32 and CARL/ChGo is significantly lower
than that in other strains (t test, p < 0.05, with Bonferroni correction). Estimates of ganglion cell
production are similar in BALB/cJ and C57BL/6J, yet these strains have
adult populations that differ by ~8000 cells (Table 1). A slight
reduction in the severity of cell death in BALB/cJ (65% loss) seems to
account for the relatively high cell number of this strain at maturity.
In this instance, the marked strain difference in adult population size
results primarily from variation in the severity of cell death.
Differences in cell death can also compensate for differences in cell
production. For example, CARL/ChGo produces an average of 131,000 ganglion cells, 20,000-40,000 fewer cells than A/J and LP/J produce,
respectively, yet all three strains have closely matched adult
populations (Table 1).
Necrotic axons and growth cones
The validity of our quantitative analysis depends on the assurance
with which we can estimate total ganglion cell production in mice. If
much cell loss occurs before birth or much cell addition occurs after
birth, then production estimates based on axon counts in the optic
nerve at P0 will be too low. To eliminate the possibility that
significant cell death occurs prenatally, we counted necrotic axons in
neonatal optic nerves from strains belonging to the high and low modes
using criteria described by Williams et al. (1986) . Necrotic axons are
relatively easy to see, and it was practical to count all sites of
necrosis in single optic nerve cross-sections. Necrotic axons at P0
make up 0.02 and 0.05% of the fiber population in cases selected from
the low strains, A/J and C57BL/6J, respectively, whereas they make up
0.07 and 0.09% of the population in cases selected from the high
strains, BXD32 and C3H/HeSnJ, respectively. The fact that a somewhat
higher incidence of necrosis was noted in nerves taken from the high
strains makes it very unlikely that variation in early axon loss
accounts for differences between adult values. Growth cones were
exceeding rare in all material, and fewer than five profiles among all
cases met even a relatively lax criteria for these structures (Williams
et al., 1986 ; Williams et al., 1991 ; Colello and Guillery, 1992 ).
Specificity of strain differences
Do strain differences in retinal ganglion cell number correspond
to differences in total brain weight, or are differences among strains
specific to the ganglion cell population? The correlation of ganglion
cell number and brain weight across individual mice is 0.37, but when
strain averages are used, the correlation rises to 0.75. This suggests
that approximately one-half of the variance in neonatal ganglion cell
number can be explained directly or indirectly by differences in brain
weight. As assessed by quantitative DNA analysis, brain weight
differences among neonatal mice are primarily attributable to
differences in total cell number (Zamenhof and Marthens, 1976 ). Thus,
mechanisms modulating ganglion cell number may have common effects on
cell number in the other parts of the CNS. The correlation between
strain averages of adult brain weight and ganglion cell number for the
same strains is only 0.51. Given the wide confidence intervals of
correlations computed with low numbers of cases, the difference
between the adult and neonatal correlations (0.51 and 0.75, respectively) may be caused by sampling error. But it is also
conceivable that strain variation in cell death decreases an initially
high correlation between brain weight and retinal ganglion cell number.
In any case, the cellular specificity of the strain differences is
likely to be low, and we expect differences in numerous other neuronal
cell populations to be closely matched with the differences we find in
ganglion cell number.
 |
DISCUSSION |
Synopsis
Our analysis demonstrates that most of the variation in adult
ganglion cell number among strains of mice can be traced to differences
in cell production. Allelic variants at the Nnc1 locus on
Chr 11 (Williams et al., 1996 , 1998a ) generate the pronounced bimodality in ganglion cell population size by modulating ganglion cell production.
Generation and death of retinal ganglion cells
Generation of retinal ganglion cells in mice begins on embryonic
day 11 (E11) and lasts until just before birth (Dräger, 1985 ).
There is a short delay between neurogenesis and the time at which
ganglion cell axons extend into the optic nerve (Colello and Guillery,
1992 ). This delay could deflate estimates of total cell
production. However, very few ganglion cells are produced after E18
(Dräger, 1985 ), and as anticipated from the work of Colello and
Guillery (1992) , we did not observe growth cones in neonatal optic
nerves. It is therefore unlikely that our estimates of total production
are biased downward by late ganglion cell generation.
In contrast, ganglion cell death begins at, or just before, birth,
peaks between postnatal days 4-6, and is essentially complete by P12
(Linden and Pinto, 1985 ). At the peak of cell loss, between 5,000 and 10,000 ganglion cells are eliminated per day (Williams et
al., 1990 ). However, fewer than 2000 cells are lost on the day of birth
in mice, consistent with our observation of very few necrotic axons,
<300 per nerve. At this rate it is improbable that more than a total
of 10,000 ganglion cells are lost prenatally. In chickens there is as
much as a 3 d delay between the onset of ganglion cell
degeneration in the retina and the elimination of axons in the optic
nerve (Rager and Rager, 1978 ). If there is a similar delay in
mice, then our axon counts should more directly reflect production
numbers. Nonetheless, our estimates of total production may be biased
downward slightly by the early loss of ganglion cell axons. However,
the magnitude of this error is sufficiently small (~10,000 cells)
that we did not think this loss warranted correction.
Mechanism generating differences in ganglion cell production
We recently mapped a gene, Nnc1, that is responsible
for more than one-half of the genetic variance in ganglion cell number in mice and that generates the pronounced bimodality that we discovered among strain averages (Williams et al., 1998a ). Nnc1 is the
first locus known to control normal variation in cell number in the vertebrate CNS. The thyroid hormone receptor gene (Thra)
is a superb candidate gene. Thra maps within 1-2 cM
of Nnc1 on chromosome 11 (Montgomery et al., 1997 ) and is
expressed within the developing chick retina (Sjöberg et al.,
1992 ). The ligand of THRA, triiodothyronine, is known to influence
retinal ganglion cell fate determination (Hoskins, 1985 ) and retinal
maturation rate (Macaione et al., 1984 ), and hypothyroidism during
retinal development results in decreased cell density in the ganglion
cell layer (Hoskins, 1985 ; Navagantes et al., 1996 ).
Nnc1, possibly Thra, could influence ganglion
cell production by affecting (1) the numbers of retinal
progenitor cells, (2) the pathways of cell determination, or (3) the
kinetics of progenitor cell proliferation. Genetically determined
differences in numbers of multipotent retinal progenitors would have
consistent effects on the number of many retinal cell types. However, a
comparison of horizontal cell and ganglion cell numbers for six strains
demonstrates that ratios in these early-generated cell types are not
always matched (Williams et al., 1998b ). We have also examined other retinal cell populations and in preliminary work have found a weak
negative correlation between ganglion cells and photoreceptors (Williams et al., 1998a ). This suggests that there may be a reciprocal relationship between the generation of early- and late-generated retinal cell types. An example of this type of reciprocal relationship is found when the Notch signaling pathway is perturbed. This results in
a shift in the ratio of early- to late-generated retinal cell types
(Dorsky et al., 1997 ). The idea of temporally regulated competence is
supported by a confluence of work (Watanabe and Raff, 1990 ; Anchan et
al., 1991 ; Williams and Goldowitz, 1992 ; Guillemot and Joyner, 1993 ;
Cepko et al., 1996 ; Alexiades and Cepko, 1997 ).
The progressive slowing of the cell cycle and its eventual cessation
result in part from decreased availability of key exogenous factors
(Jacobson, 1991 ; Alexiades and Cepko, 1996 ). Studies have identified
multiple mitogenic factors for retinal progenitors: FGF, TGF
(Lillien and Cepko, 1992 ), TGF , epidermal growth factor (Anchan et al., 1991 ), and IGF-1 (Hernández-Sánchez et al., 1995 ; Frade et al., 1996 ). Interestingly, the addition of the THRA
ligand triiodothyronine to cultured fetal rat hypothalamus cells
stimulates the release of IGF-1 into the culture medium (Binoux et al.,
1985 ). Finally, genetic variants of Nnc1 could alter the
proliferation kinetics of progenitors that give rise to ganglion cells.
Rates of mitosis may be influenced via inhibitory molecules and
pathways. One extremely interesting example is dopa, a tyrosine
metabolite that normally has inhibitory effects on cell genesis in
retina (Ilia and Jeffery, 1996 ). The absence of dopa in albino rats
leads to an anomalous upregulation of ganglion cell production followed
by an increase in the severity of cell death (Ilia and Jeffery,
1998 ). Nnc1 could have effects within any of these
mitotic regulatory pathways.
Variation in retinal ganglion cell death
The severity of cell death is close to 68-70% in most strains of
mice. However, there are three exceptional strains with less severe
loss. Three to nine percent fewer cells are lost in BXD32, CARL/ChGo,
and BALB/cJ. BXD32 is particularly interesting because it has the
highest adult population (75,800 ± 1900) among the 60 strains we
have now examined. Yet at birth BXD32 has an unexceptional number,
199,500, that is lower than that of other strains. Clearly, one or more
genes controlling rates of ganglion cell death are responsible for the
high adult cell number in this strain. It would be feasible to map a
cell death gene by crossing BXD32 to a strain with similar ganglion
cell production but higher cell death.
Variation in the severity of cell death may result from differences in
titers of neurotrophic factors. The neurotrophins (BDNF and
neurotrophin-3/4) have been found to increase survival of retinal
ganglion cells in chicken and rat (Rosa et al., 1993 ; Ma et al., 1998 ).
Neuregulin, found on the cell surface and as a secreted protein, can
also increase survival of neonatal rat retinal ganglion cells in
culture (Bermingham-McDonogh et al., 1996 ). Differences in the time of
expression or concentration of these neurotrophic factors, their
receptors, or components within their signaling pathways could produce
variation in the severity of naturally occurring ganglion cell death.
Nnc1 controls cell production
We have shown that as much as 77% of the variation among adult
strains results from differences in the production of ganglion cells.
The percentage of cell death in high and low groups does not differ
significantly (66.9 and 67.5%, respectively). We conclude that
variation in adult ganglion cell number among inbred mouse strains
results predominantly from differences in cell production. Comparison
of our data with the Monte Carlo simulations (Fig. 4) corroborates this conclusion.
A major motivation for undertaking the present study was to determine
how and when allelic variants at Nnc1 influence the size of
the ganglion cell population. Collectively, our results strongly
indicate that Nnc1 modulates ganglion cell number by influencing cell production, and because ganglion cell production occurs before birth, our results indicate a time frame for the action
of Nnc1.
 |
FOOTNOTES |
Received June 4, 1998; revised Sept. 15, 1998; accepted Sept. 18, 1998.
This research was supported by grants from the National Institutes of
Health to R.W. (National Institute of Neurological Disorders and Stroke
Grant R01 NS35485 and NEI Grant EY08868). R.C.S. was supported
in part by the United States Public Health Service Training Grant
RNS-07323. We thank K. Troughton for technical help and D. Goldowitz
for providing us with M. caroli pups.
Correspondence should be addressed to Dr. Robert W. Williams,
Department of Anatomy and Neurobiology, 855 Monroe Avenue, Memphis, TN 38163.
 |
REFERENCES |
-
Alexiades M,
Cepko C
(1996)
Quantitative analysis of proliferation and cell cycle length during development of the rat retina.
Dev Dyn
205:293-307[Web of Science][Medline].
-
Alexiades MR,
Cepko CL
(1997)
Subsets of retinal progenitors display temporally regulated and distinct biases in the fates of their progeny.
Development
124:1119-1131[Abstract].
-
Anchan RM,
Reh TA,
Angello J,
Balliet A,
Walker M
(1991)
EGF and TGF-
stimulate retinal neuroepithelial cell proliferation in vitro.
Neuron
6:923-936[Web of Science][Medline]. -
Bermingham-McDonogh O,
McCabe KL,
Reh TA
(1996)
Effects of GGF/neuregulins on neuronal survival and neurite outgrowth correlate with erbB2/neu expression in developing rat retina.
Development
122:1427-1438[Abstract].
-
Binoux M,
Faivre-Bauman A,
Lassarre C,
Barret A,
Tixier-Vidal A
(1985)
Triiodothyronine stimulates the production of insulin-like growth factor (IGF) by fetal hypothalamus cells cultured in serum-free medium.
Dev Brain Res
21:319-321.
-
Cepko CL,
Austin CP,
Yang X,
Alexiades M,
Ezzeddine D
(1996)
Cell fate determination in the vertebrate retina.
Proc Natl Acad Sci USA
93:589-595[Abstract/Free Full Text].
-
Chalupa L,
Williams R,
Henderson Z
(1984)
Binocular interaction in the fetal cat regulates the size of the ganglion cell population.
Neuroscience
12:1139-1146.
-
Colello RJ,
Guillery RW
(1992)
Observations on the early development of the optic nerve and tract of the mouse.
J Comp Neurol
317:357-378[Medline].
-
Curcio CA,
Allen KA
(1990)
Topography of ganglion cells in human retina.
J Comp Neurol
300:5-25[Web of Science][Medline].
-
Dorsky RI,
Chang WS,
Rapaport DH,
Harris WA
(1997)
Regulation of neuronal diversity in the Xenopus retina by Delta signalling.
Nature
385:67-70[Medline].
-
Dräger U
(1985)
Birth dates of retinal ganglion cells giving rise to the crossed and uncrossed optic projections in the mouse.
Proc R Soc Lond [Biol]
224:57-77[Medline].
-
Finlay BL,
Pallas SL
(1989)
Control of cell number in the developing mammalian visual system.
Prog Neurobiol
32:207-234[Web of Science][Medline].
-
Frade JM,
Martí E,
Bovolenta P,
Rodríguez-Peña MA,
Pérez-García D,
Rohrer H,
Edgar D,
Rodríguez-Tébar A
(1996)
Insulin-like growth factor-I stimulates neurogenesis in chick retina by regulating expression of the
6 integrin subunit.
Development
122:2497-2506[Abstract]. -
Guillemot F,
Joyner AL
(1993)
Dynamic expression of the murine Achaete-Scute homologue Mash-1 in the developing nervous system.
Mech Dev
42:171-185[Web of Science][Medline].
-
Hernández-Sánchez C,
López-Carranza A,
Alarcón C,
Rosa EJ,
Pablo F
(1995)
Autocrine/paracrine role of insulin-related growth factors in neurogenesis: local expression and effects on cell proliferation and differentiation in retina.
Proc Natl Acad Sci USA
92:9834-9838[Abstract/Free Full Text].
-
Hoskins SG
(1985)
Control of the development of the ipsilateral retinothalamic projection in Xenopus laevis by thyroxine: results and speculation.
J Neurobiol
17:203-229.
-
Ilia M,
Jeffery G
(1996)
Delayed neurogenesis in the albino retina: evidence of a role for melanin in regulating the pace of cell generation.
Dev Brain Res
95:176-183[Medline].
-
Ilia M, Jeffery G (1998) Retinal mitosis is regulated by
dopa, a melanin precursor that may influence the time at which cells
exit the cell cycle: analysis of patterns of cell production in
pigmented and albino retinae. J Comp Neurol, in press.
-
Jacobson M
(1991)
In: Developmental neurobiology. New York: Plenum.
-
Lia B,
Williams RW,
Chalupa LM
(1986)
Does axonal branching contribute to the overproduction of optic nerve fibers during early development of the cat's visual system?
Brain Res
390:296-301[Medline].
-
Lillien L,
Cepko C
(1992)
Control of proliferation in the retina: temporal changes in responsiveness to FGF and TGF
.
Development
115:253-266[Abstract]. -
Linden R,
Pinto LH
(1985)
Developmental genetics of the retina: evidence that the pearl mutation in the mouse affects the time course of natural cell death in the ganglion cell layer.
Exp Brain Res
60:79-86[Web of Science][Medline].
-
Ma Y-T,
Hsieh T,
Forbes ME,
Johnson JE,
Frost DO
(1998)
BDNF injected into the superior colliculus reduces developmental retinal ganglion cell death.
J Neurosci
18:2097-2107[Abstract/Free Full Text].
-
Macaione S,
Di-Giorgio R,
Nicotina P,
Lentile R
(1984)
Retina maturation following administration of thyroxine in developing rats: effects on polyamine metabolism and glutamate decarboxylase.
J Neurochem
43:303-315[Medline].
-
Montgomery JC,
Silverman KA,
Buchberg AM
(1997)
Chromosome 11.
Mamm Genome
7:190-208.
-
Navagantes LC,
Silveira LC,
Santos GL
(1996)
Effect of congenital hypothyroidism on cell density in the ganglion cell layer of the rat retina.
Braz J Med Biol Res
29:665-668[Web of Science][Medline].
-
Perry VH,
Henderson Z,
Linden R
(1983)
Postnatal changes in retinal ganglion cell and optic axon populations in the pigmented rat.
J Comp Neurol
219:356-368[Web of Science][Medline].
-
Rager G,
Rager U
(1978)
Systems-matching by degeneration.
Exp Brain Res
33:65-78[Web of Science][Medline].
-
Rakic P,
Riley K
(1983)
Overproduction and elimination of retinal axons in the fetal rhesus monkey.
Science
219:1441-1444[Abstract/Free Full Text].
-
Rice DS,
Williams RW,
Goldowitz D
(1995)
Genetic control of retinal projections in inbred strains of albino mice.
J Comp Neurol
354:459-469[Web of Science][Medline].
-
Rosa EJ,
Arribas A,
Frade JM,
Rodríguez-Tébar A
(1993)
Role of neurotrophins in the control of neural development: neurotrophin-3 promotes both neuron differentiation and survival of cultured chick retinal cells.
Neuroscience
58:347-352.
-
Sjöberg M,
Vennström B,
Forrest D
(1992)
Thyroid hormone receptors in chick retinal development: differential expression of mRNAs for
and N-terminal variant receptors.
Development
114:39-47[Abstract]. -
Watanabe T,
Raff MC
(1990)
Rod photoreceptor development in vitro: intrinsic properties of proliferating neuroepithelial cells change as development proceeds in the rat retina.
Neuron
2:461-467.
-
Williams MA,
Piñon LGP,
Linden R,
Pinto LH
(1990)
The pearl mutation accelerates the schedule of natural cell death in the early postnatal retina.
Exp Brain Res
82:393-400[Web of Science][Medline].
-
Williams RW,
Borodkin M,
Rakic P
(1991)
Growth cone distribution patterns in the optic nerve of fetal monkeys: implications for mechanisms of axonal guidance.
J Neurosci
11:1081-1094[Abstract].
-
Williams RW,
Goldowitz D
(1992)
Lineage versus environment in embryonic retina: a revisionist perspective.
Trends Neurosci
15:368-373[Web of Science][Medline].
-
Williams RW,
Bastiani MJ,
Lia B,
Chalupa LM
(1986)
Growth cones, dying axons and developmental fluctuations in the fiber population of the cat's optic nerve.
J Comp Neurol
246:32-69[Web of Science][Medline].
-
Williams RW,
Strom RC,
Rice DS,
Goldowitz D
(1996)
Genetic and environmental control of variation in retinal ganglion cell number in mice.
J Neurosci
16:7193-7205[Abstract/Free Full Text].
-
Williams RW,
Strom RC,
Goldowitz D
(1998a)
Natural variation in neuron number in mice is linked to a major quantitative trait locus on Chr 11.
J Neurosci
18:138-146[Abstract/Free Full Text].
-
Williams RW,
Strom RS,
Zhou G,
Yan Z
(1998b)
Genetic dissection of retinal development.
Semin Cell Dev Biol
9:249-255[Web of Science][Medline].
-
Zamenhof S,
Marthens E
(1976)
Neonatal and adult brain parameters in mice selected for adult brain weight.
Dev Psychobiol
9:587-593[Medline].
Copyright © 1998 Society for Neuroscience 0270-6474/98/18239948-06$05.00/0
This article has been cited by other articles:

|
 |

|
 |
 
P. Heine, E. Dohle, K. Bumsted-O'Brien, D. Engelkamp, and D. Schulte
Evidence for an evolutionary conserved role of homothorax/Meis1/2 during vertebrate retina development
Development,
March 1, 2008;
135(5):
805 - 811.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
F. Mabuchi, M. Aihara, M. R. Mackey, J. D. Lindsey, and R. N. Weinreb
Optic Nerve Damage in Experimental Mouse Ocular Hypertension
Invest. Ophthalmol. Vis. Sci.,
October 1, 2003;
44(10):
4321 - 4330.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
M. Schubert, D. P. Brazil, D. J. Burks, J. A. Kushner, J. Ye, C. L. Flint, J. Farhang-Fallah, P. Dikkes, X. M. Warot, C. Rio, et al.
Insulin Receptor Substrate-2 Deficiency Impairs Brain Growth and Promotes Tau Phosphorylation
J. Neurosci.,
August 6, 2003;
23(18):
7084 - 7092.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
J. H. LaVail, A. N. Tauscher, E. Aghaian, O. Harrabi, and S. S. Sidhu
Axonal Transport and Sorting of Herpes Simplex Virus Components in a Mature Mouse Visual System
J. Virol.,
June 1, 2003;
77(11):
6117 - 6126.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
A. Ravary, A. Muzerelle, D. Herve, V. Pascoli, K. N. Ba-Charvet, J.-A. Girault, E. Welker, and P. Gaspar
Adenylate Cyclase 1 as a Key Actor in the Refinement of Retinal Projection Maps
J. Neurosci.,
March 15, 2003;
23(6):
2228 - 2238.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
X. Huang, D.-Y. Wu, G. Chen, H. Manji, and D. F. Chen
Support of Retinal Ganglion Cell Survival and Axon Regeneration by Lithium through a Bcl-2-Dependent Mechanism
Invest. Ophthalmol. Vis. Sci.,
January 1, 2003;
44(1):
347 - 354.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
D. C. Airey, L. Lu, and R. W. Williams
Genetic Control of the Mouse Cerebellum: Identification of Quantitative Trait Loci Modulating Size and Architecture
J. Neurosci.,
July 15, 2001;
21(14):
5099 - 5109.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
L. Lu, D. C. Airey, and R. W. Williams
Complex Trait Analysis of the Hippocampus: Mapping and Biometric Analysis of Two Novel Gene Loci with Specific Effects on Hippocampal Structure in Mice
J. Neurosci.,
May 15, 2001;
21(10):
3503 - 3514.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
R. B. R. Azevedo and A. M. Leroi
A power law for cells
PNAS,
April 25, 2001;
(2001)
91485998.
[Abstract]
[Full Text]
|
 |
|
|

|