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Journal of Anatomy. 2022;00:1–19. wileyonlinelibrary.com/journal/joa
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1© 2022 Anatomical Society
Received: 7 July 2021
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Revised: 11 Februar y 2022
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Accepted: 8 March 2022
DOI : 10.1111/joa.13657
ORIGINAL ARTICLE
The genetic basis of neurocranial size and shape across varied
lab mouse populations
Christopher J. Percival1 | Jay Devine2 | Chaudhry Raza Hassan3 |
Marta Vidal- Garcia2 | Christopher J. O'Connor- Coates1 | Eva Zaffarini2 |
Charles Roseman4 | David Katz2 | Benedikt Hallgrimsson5
1Anthropology, Stony Brook University,
Stony Brook, New York, USA
2Cell Biology and Anatomy, University of
Calgary Cumming School of Medicine,
Calgary, Canada
3Biomedical Engineering, Stony Brook
University, Stony Brook, New York, USA
4Department of Evolution, Ecolog y, and
Behavior, University of Illinois, Urbana,
Illinois, USA
5Cell Biology and Anatomy, Albert a
Children's Hospital Research Institute,
Cumming School of Medicine, University
of Calgary, Calgary, Canada
Correspondence
Christopher J. Percival, Anthropology,
Stony Brook University, Stony Brook, New
York, USA.
Email: christopher.percival@stonybrook.
edu
Funding information
Start- up funds to CJP from Stony Brook
University; NSERC Grant #238992– 17,
CIHR Foundation grant #159920 and NIH
2R01DE019638 to BH
Abstract
Brain and skull tissues interact through molecular signalling and mechanical forces dur-
ing head development, leading to a strong correlation between the neurocranium and
the external brain surface. Therefore, when brain tissue is unavailable, neurocranial en-
docasts are often used to approximate brain size and shape. Evolutionary changes in
brain morphology may have resulted in secondary changes to neurocranial morphology,
but the developmental and genetic processes underlying this relationship are not well
understood. Using automated phenotyping methods, we quantified the genetic basis of
endocast variation across large genetically varied populations of laboratory mice in two
ways: (1) to determine the contributions of various genetic factors to neurocranial form
and (2) to help clarify whether a neurocranial variation is based on genetic variation that
primaril y imp acts bone developm ent or on genetic variation that primar ily impac ts brain
development, leading to secondary changes in bone morphology. Our results indicate
that endocast size is highly heritable and is primarily determined by additive genetic
factors. In addition, a non- additive inbreeding effect led to founder strains with lower
neurocranial size, but relatively large brains compared to skull size; suggesting stronger
canalization of brain size and/or a general allometric effect. Within an outbred sample
of mice, we identified a locus on mouse chromosome 1 that is significantly associated
with variation in several positively correlated endocast size measures. Because the
protein- coding genes at this locus have been previously associated with brain develop-
ment and not with bone development, we propose that genetic variation at this locus
leads primarily to variation in brain volume that secondarily leads to changes in neuro-
cranial globularity. We identify a strain- specific missense mutation within Akt3 that is a
strong causal candidate for this genetic effect. Whilst it is not appropriate to generalize
our hypothesis for this single locus to all other loci that also contribute to the complex
trait of neurocranial skull morphology, our results further reveal the genetic basis of
neurocranial variation and highlight the importance of the mechanical influence of brain
growth in determining skull morphology.
KEYWORDS
AKT3, CEP170, Collaborative Cross, diallel analysis, Diversity Outbred, endocast,
neurocranium, PLD5, SDCCAG8, skull brain interaction, ZBTB18
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PER CIVAL Et AL .
1 | INTRODUCTION
The skull develops as an integrated structure within the context
of other head tissues, including external muscles and the growing
brain. When mechanical forces imposed by adjacent soft tissue
are modified, changes in skull morphology may result. For exam-
ple, the lack of an eye results in changes to the adjacent bone mor-
phology (Dufton et al., 2012; Dufton & Franz- Odendaal, 2015; Kish
et al., 2011; Smith et al., 2014). Similarly, growth of the brain is nec-
essary for normal cranial vault shape, and the cranial vault will adapt
to accommodate increases in brain size (Adameyko & Fried, 2016;
Moss & Young, 1960; Richtsmeier et al., 2006; Richtsmeier &
Flaherty, 2013).
This close developmental relationship produces morphological
covariation between the interior surface of the neurocranium and
the exterior surface of a mammal's brain. Because skeletal materials
are more common within the fossil record and museum collections,
the internal surface of the neurocranium has frequently been used
to approximate brain size and shape for comparative studies of brain
evolution (see citations within Balanoff et al., 2016). Casts of the
internal neurocranial surface called endocasts come in the form of
(1) naturally occurring fossilized sediment, (2) artificial casts made
with a moulding material and (3) digital surfaces generated from
three- dimensional (3D) images of bone (e.g. computed tomography)
(Holloway, 2018).
Although the brain occupies more than 80% of the endocranial
volume within mammals (Watanabe et al., 2019; Zollikofer & Ponce
de León, 2013) and approximately 97% of the endocranial volume
within mice (Nieman et al., 2012), endocasts are not direct casts of
the brain. In life, the neurocranial space is filled with the brain, the
meningeal connective tissues that protect the brain, and the blood
vessels found ex ternal to the brain. Howeve r, there is a stro ng corre-
spondence between endocast measures and brain measures within
the context of comparative mammalian anatomy, as supported by a
comparison of endocast volume and brain weight amongst marsu-
pials (Haight & Nelson, 1987), the correspondence of endocast and
brain surface features (Dumoncel et al., 2021; Nieman et al., 2012),
and by many unpublished anatomical observations.
There is also a strong allometric relationship between brain size
and body size across a broad range of taxa. Indices of encephaliza-
tion, such as the encephalization quotient (originally proposed by
Jerison, 1973), represent the size of an animal's brain relative to its
overall body size. These encephalization measures have been widely
associated with behavioural and cognitive complexity (de Miguel &
Henneberg, 1998; Jerison, 1973; Marino, 1998; Zollikofer & Ponce
de León, 2013). In addition, recent analyses of variation in the allo-
metric relationship between brain and body size across a variety of
mammalian and avian clades have illuminated the macroevolutionary
history of encephalization (Ksepka et al., 2020; Smaers et al., 2012;
Weisbecker et al., 2021). Regardless of the comparative method
used, choosing appropriate measures of both brain size and organis-
mal size is critical for producing valid and interpretable encephaliza-
tion measures (Hallgrímsson et al., 2019).
It has long been proposed that evolutionary changes in brain size
across primate and human evolution resulted in secondary changes
to skull morphology (e.g. De Beer, 1937). However, it is not clear
whether known evolutionary changes in primate skull shape are
primarily based on a plastic developmental response of the skull to
mechanical forces during ontogeny or if they are instead based on
natural selective pressures for modified skull morphology (reviewed
by Lesciotto & Richtsmeier, 2019). For this reason, it is important
to (1) identify the types of genetic factors that contribute most
strongly to variation in neurocranial morphology and (2) to deter-
mine whether these factors play a primary role in skeletal develop-
ment, brain development, or both via pleiotropy.
If neurocranial morphology is associated with variation in genes
that significantly influence bone development, this would support
the hypothesis that skull morphology is the direct result of evolution
acting on genes with major effects on skull growth and skull shape.
If neurocranial morphology is associated with genes that have major
roles in brain development, this supports the hypothesis that sec-
ondary mechanical forces imposed by the growing brain contribute
substantially to evolutionary changes in skull morphology. Whilst
past evolutionary pressures and active phenotypic plasticity likely
both play a role in determining adult neurocranial morphology, the
underlying genetic factors remain poorly understood. Some genes
may also have parallel pleiotropic effects on bone and brain devel-
opment, so it is critical to consider all functions of identified genes
when testing these predictions.
We perform a large- scale analysis to identify the genetic and
developmental factors underlying evolutionary changes in neu-
rocranial form. We use an automated image registration method
(Percival et al., 2019) to extract and quantify endocasts for a genet-
ically diverse sample of laboratory mice. We then complete a diallel
analysis on eight inbred founder strains of the Collaborative Cross
(CC) mice (Chesler et al., 2008; Churchill et al., 2004; Collborative
Cross Consortium, 2012) and their reciprocal F1 crosses to estimate
the types of additive and non- additive (e.g. maternal and inbreeding
effects) genetic factors that underlie variation in endocast size and
encephalization indices, as well as the heritability of those measures.
Given that endocasts are an accurate estimate of brain size derived
from neurocranial skull features in mice and are highly correlated
with brain size, we anticipate that the heritability and the propor-
tional importance of genetic factor types in determining endocast
measures will be similar to values reported for other skull measure-
ments in this sample (Percival et al., 2016a).
Finally, we perform genome- wide association studies (GWAS)
of the genetically heterogeneous Diversity Outbred (DO) mice
to identify genomic regions where the eight original CC founder
strain haplotypes are associated with endocast size variation.
After identifying a single significant association, we investigated
whether protein- coding genes in this genomic region were pre-
viously linked to processes of bone development or brain devel-
opment. We anticipated that any GWAS identified chromosomal
regions would be enriched for genes that are important for brain
growth rather than bone formation and growth. This result would
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PERCIVAL Et AL .
match our expectation that processes of brain growth play a sig-
nificant role in determining the shape of the skeletal neurocranium
and that a substantial proportion of neurocranial size variation
across our experimental sample is based on the plastic responses
of developing skull bones to variation in the speed and intensity
of brain growth.
2 | METHODS
2.1 | Sample and image acquisition
Our sample of 1204 mouse skull micro- computed tomography (μCT)
images of the eight inbred founder strains of the Collaborative Cross
(CC) (Chesler et al., 2008; Churchill et al., 2004; Collborative Cross
Consortium, 2012) and 54 (of 56 possible) reciprocal F1 crosses
was previously used to elucidate the genetic structure of ‘normal’
laboratory mouse skull morphology (Pavličev et al., 2017; Percival
et al., 2016a). Each cross is identified first by the maternal founder
strain and second by the paternal founder strain (Collborative Cross
Consortium, 2012). Because all founder strains are inbred, speci-
mens within each founder strain and F1 cross are isogenic. Strain
identity is referred to as specimen genotype throughout the analy-
sis. These mice were bred as part of the Collaborative Cross breed-
ing project at the University of North Carolina under the approval of
the University of North Carolina Animal Care and Use Committee.
These mice were housed at UNC for 8– 12 weeks with standard
chow and housing.
Our original sample of 1071 Diversity Outbred (DO) mice are
a subset of a sample whose skull morphology was previously an-
alyzed (Aponte et al., 2021; Devine et al., 2020; Katz et al., 2020;
Percival et al., 2018). DO mice (J:DO, JAX stock #009376) are
derived from the eight CC founder strains (Churchill et al., 2012;
Svenson et al. , 2012). As a result of outcrossing , the DO population
has relatively high genetic diversity and increasingly fine- mapping
resolution with each generation. Therefore, this sample was used
to (1) identify QTL associated with endocast measurement varia-
tion and their corresponding confidence intervals and (2) deter-
mine which CC founder strain haplotypes are associated with that
endocast variation. Specimens were originally raised in several
labs for unrelated experiments under the approval and conducted
in accordance with the guidelines set forth by the Institutional
Animal Care and Use Committees (IACUC) of the University of
North Carolina (protocol #11– 299), Jackson Laboratories (proto-
cols #99 066 and #15026), and The Sc ripps Resear ch Institute (pro-
t o c o l # 0 8 – 0 1 5 0 - 3 ) .
Tissue specimens were received and imaged at the University
of Calgary in accordance with IACUC protocols #AC13- 0268 and
A C 1 8 - 0 0 2 6 . μCT images of mouse skulls were obtained in the 3D
Morphometrics Centre at the University of Calgary with a Scanco
vivaCT40 scanner (Scanco Medical, Brüttisellen, Switzerland) at
0.035– 0.038 mm voxel dimensions at 55 kV and 72– 145 μA . Our
CC founder/F1, DO mouse samples, and relevant image analysis
pipelines are available as part of the MusMorph public mouse data-
set (Devine et al., 2021) and associated github repository (https://
github.com/jayde vine/MusMorph).
2.2 | Manual endocast estimation.
Endocasts were previously manually extracted from μCT images
of specimens from 36 out of 54 available CC founder and F1 cross
genotypes (Percival et al., 2016b). This manual extraction process
included rough reorientation of CT skull images to a standard orien-
tation, digital removal of all non- skull bones, and the use of Endex
software (Subsol et al., 2010) to fill the neurocranial space of the CT
scan with an iteratively expanding endocast surface. This procedure
was manual in the sense that a researcher preprocessed each CT
image and made decisions about when to stop the Endex endocast
expansion algorithm. More than 1 hour was required to generate an
endocast from each specimen using this method. Most of this time
was spent manually segmenting and removing non- skull bones from
the CT images.
2.3 | Nonlinear image registration and automated
endocast estimation
Using the Symmetric Normalization (SyN) algorithm (Avants
et al., 2011) in the MINC toolkit (Vincent et al., 2016), the CC
founder and F1 cross skull μCT images were all previously registered
to a single common skull image average (atlas) during the process
of automated landmark identification (Percival et al., 2019). As the
basis for automated endocast estimation of the CC sample, Endex
software was used to segment an endocast from the CC sample atlas
image using the manual endocast estimation method. This CC atlas
endocast was modified so that it did not overlap with skull bone in
the atlas image and so that it represented a single continuous vol-
ume. It was then inverse transformed back onto the original skull
μCT images of each individual CC founder/F1 specimen using previ-
ously calculated nonlinear volumetric image registrations (Percival
et al., 2019). Measurements of each specimen's endocast were cal-
culated from the resulting automated segmentations.
Following the non- linear registration pipeline described above,
we transformed all available DO mouse skull μCT images to a DO
sample average image (atlas). Like the CC founder and F1 cross mice,
a DO sample atlas endocast was produced and used to automati-
cally extract an endocast for each μCT DO specimen. We repeated
the process of (1) producing an endocast segmentation of the DO
sample atlas and (2) automatically segmenting all DO specimens
twice more to quantify the repeatability of endocast size measure-
ment methods. This led to a total of three sets of endocast mea-
surements for each DO mouse specimen in our sample. All variation
between replicate measurements of DO specimens reflects differ-
ences between the three endocast segmentations of a single DO
skull atlas image. After a replication analysis comparing these three
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PER CIVAL Et AL .
measurement sets, the first set of DO endocast measurements were
used as the basis for further analysis.
2.4 | Endocast size measures and measurement
validation
Five endocast measurements were estimated for each CC founder/F1
specimen automatically generated endocast, for each manually cre-
ated CC founder/F1 specimen endocast, and all three automatically
generated endocasts for each DO specimen. First, endocast volume
and surface area were estimated. STL format meshes were gener-
ated from volumetric image endocast estimates with the marching
cubes algorithm within the VTK library (Schroeder et al., 2006) in
Python (version 3.7). These 3D surfaces were post- processed by fill-
ing holes, checking for consistency, adjusting the surface normals
to project from a single surface, and smoothing to remove duplicate
surfaces. The su r face area and vo lum e of th ese 3D mesh repr esenta-
tions were estimated using the vtkMassProperties subroutine. Total
processing time for STL surface creation and measurement was ap-
proximately 1 min for each specimen. A custom Python script was
written to automate this process (File S2).
Dimensions of endoc ast length, width, and height were automat-
ically estimated from the previously produced STL mesh surfaces
after rotating each surface to its principal axes with the Python
Trimesh package (https://github.com/miked h/trimesh). A 4 × 4
transformat ion matrix include d rotatio n of the surface principal in er-
tia vectors to a standard orientation and translation of the surface’s
centre of mass to a standard position. After the standard orientation
of each surface to align with principal axes, the dimensions of an en-
docast surface's rectangular bounding box approximate the length,
width, and height of that endocast (Figure 1). Whilst the described
Python- based methods were used to estimate measures for all au-
tomatically generated endocasts, equivalent measurements were
collected in MeshLab (Cignoni et al., 2008) for manually generated
endocasts after orientation of endocast surfaces to their principal
axes.
The accuracy of endocast measures estimated from automati-
cally generated endocasts was verified by comparing automatically
and manually generated endocast measures of the 688 CC founder/
F1 specimens for which we have both automated and manual mea-
surements (Table S1). Differences between automated and manual
measures of each specimen were calculated, as were correlations
of those measures across our sample. To directly compare endocast
overlap in the Endex and MINC image spaces, a random subsam-
ple of ten CC images with both automated and manual endocasts
were aligned using manual landmark defined 3D transformations.
Dice similarity scores (Dice, 1945) were calculated as the ratio of
the intersection of two endocast volumes to the union of the same
volumes. Landmark- based transformations were needed to align
manual and automated endocasts because of major differences in
software pipelines and resulting coordinate systems, so our Dice
score es timates are likely an unde rest imat ion of true volum e ove rlap.
To identify specimens with automated endocast segmentation
errors, we implemented two strategies, both of which can be used
for samples without manual measurements. First, we computed a
ratio of endocast length to volume, as an inappropriate posterior
extension of the endocast via registration error can lead to a major
increase in endocast length whilst having a minor effect on overall
endocast volume. Second, we quantified placement errors in the fo-
ramen magnum landmarks (Devine et al., 2020; Percival et al., 2019).
If the automated placement was inaccurate, it is likely that the posi-
tion of the foramen magnum was misidentified, which may also lead
to an error in identif ying the posterior end of the endoc ast. We visu-
ally inspected these outliers manually to confirm this error.
2.5 | Relative size (encephalization) measures
Measures of relative endocast size (encephalization indices) were
estimated for all CC founder/F1 and DO specimens to determine
whether the genetic structure of raw neurocranial size is simi-
lar to the genetic structure of relative neurocranial size. First, the
index of relative encephalization (IRE) was calculated as the cube
root of endocast volume divided by cranial base length (Lieberman
et al., 2008). Cranial base length is the sum of midline linear distance
from the basion to the presphenoid/sphenoid synchondrosis and the
linear distance between the presphenoid/sphenoid synchondrosis
to the crista galli. These linear distances were measured from ana-
tomical landmarks previously collected manually on the founder/F1
(Percival et al., 2016a) and automatically on DO mice prior to neural
network optimization (Devine et al., 2020).
Because the length of the cranial base is likely influenced by
some of the same genetic factors that influence the overall neuro-
cranial size, we also calculated a measure of encephalization for the
founder/F1 sample that is standardized by tibia length, a postcra-
nial proxy for body size. The ‘Vol/Tib’ measure was calculated as the
cube root of endocast volume divided by tibia length. Tibia length
was measured between a landmark placed on the anterior midline
FIGURE 1 Endocast length, width and height measures are
collected from the surface bounding box after the surface has been
reoriented along principal axes
Length
Height
Width
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PERCIVAL Et AL .
tibial tuberosity and a landmark placed on the inferior posterior
point on the long bony prominence lateral to the malleolar groove
(Figure S1). Body weight was not chosen as the proxy for postcranial
body size in the founder/F1 sample because the NZO/HlLtJ mice
and associated crosses tend to have large fat deposits. Instead, we
preferred tibia length as a measure of postcranial skeletal size, be-
cause we wanted to standardize endocast size by a size measure that
should be impacted by the same general systemic growth factors
(not factors specifically associated with fat deposition). Because
tibias were not available for all CC founder/F1 specimens, we es-
timated Vol/Tib measures for only 1089 specimens. Given a lack of
postcranial data for our DO mouse sample, our only encephalization
measure for DO mice is IRE.
2.6 | Diallel analysis of CC founder/F1
strain measures
After removing specimens with substantial errors in automated en-
doc as t ex traction and a few with unknown sex, we completed a dial-
lel analysis of CC founder/F1 specimens to identify the contribution
of various genetic factors to mouse endocast size and encephaliza-
tion. We followed the procedures used for a previous diallel analysis
of skull dimensions for the same sample (Percival et al., 2016a). A
separate diallel analysis was carried out for four measures of endo-
cast size (volume, length, height, and width) and two measures of
encephalization (IRE and Vol/Tib) using BayesDiallel v0.982 pack-
age (Lenarcic et al., 2012) within R v3.2.5 (R Developmental Core
Team, 2008). The results indicated which additive and nonaddi-
tive factors make a significant contribution to endocast variation.
Additionally, estimates of herita bility indicate the pro portion of phe-
notypic variation that is associated with each type of additive and
nonadditive genetic factor.
2.7 | Genome- wide association mapping of
DO measures
After removing specimens with substantial errors in automated en-
docast extraction and those with potential errors in matching μCT
images to genotype data, 884 DO specimens were available as the
sample for our association analyses. Association mapping was per-
formed to identify quantitative trait loci (QTL) that contribute to
endocast size and encephalization variation. DO mice from genera-
tions 9, 10 and 15 were genotyped with the MegaMUGA genotyp-
ing array (77,808 markers), whilst the GigaMUGA genotyping array
(143,259 markers) was used to genotype DO mice from genera-
tions 19, 21, 23 and 27 (Morgan et al., 2016). To prepare the genetic
data for QTL analysis, we selected 58,907 markers found in both
the MegaMUGA and GigaMUGA arrays. Next, we eliminated 2022
markers from the centre of Chromosome 2 (40– 140 Mb) because
genetic diversity in early DO generations is highly skewed in this re-
gion because of female meiotic drive favouring WSB/EiJ at the R2d2
locus (Chesler et al., 2016; Morgan et al., 2016). Finally, we used the
qtl2 package (Broman et al., 2019) within R v3.6.1 statistical soft-
ware (R Developmental Core Team, 2008) to insert pseudomarkers
in sparsely typed genomic regions, such that no two markers in the
dataset were separated by more than 1 kilobase, resulting in a final
genotype array of 57,658 markers for QTL analysis. Genome loca-
tions are based on Mus musculus genome assembly GRCm38 (mm10).
A genome scan for QTL was completed for endocast volume,
surface area, length, width, height and IRE. At each marker, we fit a
mixed model with fixed effect coefficients for sex and the additive
effect of each CC founder haplotype, a random effect of kinship,
and an error term (Gatti et al., 2014). A predictor of DO generation
number was also included in this model. Statistical significance of
marker- phenotype association was identified when the LOD score
exceeded the 95% quantile of genome- wide maximum LOD scores
computed from 1000 random permutations of genotype- phenotype
associations (Churchill & Doerge, 1994). Genome- wide heritability
for endocast measures was estimated based on the results of this
analysis within the qtl2 package. R- squared (R2) values were es-
timated from the peak LOD scores of phenotypes with significant
associations using the following formula: R2 = 1– 10^ [−LOD*(2/n)]
(Broman & Sen, 2009).
We used a 1.5 LOD- drop rule to define the boundaries of QTL
support intervals (Manichaikul et al., 2006). Genome scans and QTL
support intervals were estimated for each endocast measurement.
We then inspected the support intervals for genes that had been
previously linked to skeletal, craniofacial or neural tissue develop-
ment or morphological variation.
3 | RESULTS
3.1 | Automated measurement validation
Comparing measurements derived from manually defined endocasts
and automatically defined endocasts indicated that the automated
endocast measures are accurate for most specimens. High correla-
tions (r = 0.938 to 0.995) were noted for all measurements (Table 1).
Nevertheless, there were some systematic differences in manual
TAB LE 1 Comparison of manual and automated endocast measurements
Endocast measurement Volume Surface area Length Width Height
Manual vs automated correlation 0.99 0.97 0.93 0.98 0.98
Mean % difference of automated from manual −2. 2 4.5 1.3 0.3 0.1
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PER CIVAL Et AL .
and automated measures. Automated volumes are, on average, 2.2%
smaller than manual volumes, whilst automated surface area meas-
ures are 4.5% larger than manual surface areas (Table 1).
Dice scores comparing automated and manual endocast volumes
for ten randomly chosen CC specimens range from 0.92 to 0.96, with
a mean of 0.95, a standard deviation of 0.01, and a 1% coefficient of
variation. A Dice score of 1 indicates complete correspondence of
identified volumes, whilst 0 indicates no correspondence. Our mea-
sured scores are high, indicating a very strong correspondence of
the manually and automatically identified endocast volumes.
Direct visual comparison of the automated and manual endocast
surfaces indicated that the automated endocasts typically include
more precise contours that closely match the edges of bone surfaces.
Whilst this precision is important, more precise contours result in
less smooth surfaces. Differences in smoothness largely explain the
increased endocast surface area and the decreased endocast volume
for automated measures. Although automated endocast contours are
generally more precise, the non- linear image registration algorithm ar-
tifactually produces a wavier automated endocast surface (Figure 2),
so subtle endocast surface features may not be consistently visible.
The weakest correlation between automated and manual mea-
sures was noted for endocast length (Table 1). Specimens with the
largest difference between manual and automated endocast length
tended to have either (1) automated endocasts that extended poste-
riorly through the foramen magnum or (2) manual endocasts where
the olfactory bulb was shorter than it should have been due to an
incomplete manual endocast expansion. Incomplete olfactory bulb
expansion of some manual endocasts will not impact the results of
our genetic analyses, which are based on automatic endocast mea-
surements. However, errors in automated endocast estimation can
have an impact on our results. The inappropriate posterior extension
of some automatically estimated endocasts is the result of image
registration errors where a vertebra is accidentally identified as the
foramen magnum of the occipital bone. This same issue previously
led to errors in automated landmark placement on the occipital bone
(Percival et al., 2019). We successfully identified specimens with au-
tomated measurement errors in our samples and removed them as
outliers prior to statistical analysis.
For the CC founder/F1 genotype sample, we identified 27 outlier
specimens out of an original sample of 1204 specimens. Two spec-
imens had incorrectly cropped original CT images, three specimens
had major failures in nonlinear image registration, 20 specimens
were identified based on extreme length to volume ratios, and two
additional specimens were identified by looking at specimens with
high foramen magnum landmark placement error. After removing
outliers, a sample of 1177 CC Founder/F1 mice remained for all sub-
sequent analyses (Table 2).
The repeatability of our automated endocast estimation method
was qu antified by comparing the meas urements of eac h DO specimen
produced using three independently generated segmentations of the
DO sample atlas. The correlations between endocast size measures
are close to maximum (rounded up to r = 1.00) for all measures ex-
cept endocast length, where length estimates of replicate 1 diverge
somewhat from the original length estimates and from replicate 2
length estimates (Table 3). A comparison of the independently pro-
duced atlas endocasts for each replicate indicates that the replicate
FIGURE 2 Surface images of manual method (Endex) and automated method endocast surfaces of the same specimen, from a lateral view
(a&c) and a superior view (b&d). Asterisks indicate examples of common manual Endex endocast segmentation errors where thin portions of
the skull bone are included in the endocast segmentations. Compared to other specimens, this specimen shows a moderate to low level of
this type of manual endocast segmentation error
Manual Endocast
Automatic Endocast
(a) (b)
(c) (d)
**
*
*= common areas of
Endex endocast
segmentation error
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PERCIVAL Et AL .
1 endocast has a greater expansion of the olfactory bulb area and
a more posterior extent at the foramen magnum. It is likely that the
Endex endocast expansion algorithm ran longer during atlas image
endocast creation for replicate 1 than for the other replicates. This
deviation of atlas endocast segmentation between replicates led to a
systematic shift in specimen endocast length estimates, highlighting
the importance of verifying the accuracy and consistency of atlas en-
docast segmentations across studies before combining measurements
collected based on different atlases or using different segmentations
of the same atlas image. The original DO endocast measurements
were used as the basis for all subsequent analyses.
Using the methods of outlier identification tested on the CC
founder/F1 sample, we identified 23 outlier specimens out of a
total of 1071 DO specimens. Twenty- one specimens were identified
based on extreme length to volume ratios and two specimens were
identified based on high foramen magnum landmark error. In addi-
tion, because of potential errors in matching μCT images of DO mice
to genotype data, a subset of 884 specimens was available as the
sample for our association analyses (File S4).
3.2 | CC founder/F1 genotype variation
Many of the most extreme endocast size values belong to inbred
founder strain specimens (Figure 3; Table 4; File S3). However,
F1 cross specimens tend to be larger across all size measures (but
not encephalization indices) than the average of their associated
founder strains, which indicates a consistent non- additive effect on
overall size. This increase is likely explained by the inbreeding effect
in our diallel models (see below). It also means that the largest end o-
cast volumes belong to F1 cross specimens. The three wild- derived
inbred strains (CAST/EiJ, PWK/PhJ and WSB/EiJ) tend to be small-
est, with intermediate values for A/J and 129S1/SvlmJ. Amongst
founder strains, the New Zealand obese mice (NZO/HlLtJ) have the
longest endocast length and overall skull size (i.e. centroid size of
skull landmarks from Percival et al., 2019), whilst NOD/ShiLtJ and
C57BL/6J have the tallest endocast heights. In fact, the correlation
between endocast height and length (Figure 3a; r = 0.639) is weaker
than the correlations between height and width (r = 0.751) and be-
tween length and width (Figure 3c; r = 0.800). In this way, height
appears to vary under the influence of forces that do not similarly
affect the other two endocast distance measures.
Similar distributions of founder strains are noted when compar-
ing endocast volume to endocast surface area (Figure 3b) and overall
skull size (Figure 3d; i.e. skull centroid size). Based on these compar-
isons and estimates of IRE, the founder strains with the highest en-
cephalization measures include NOD/ShiLtJ, WSB/EiJ, 129S1/SvlmJ
and C57BL/6J, whilst those with the lowest encephalization are
PWK/PhJ and NZO/HlLtJ (Figure 3; Table 4). However, when look-
ing at the Vol/Tib encephalization measure, the relative brain size
of PWK/PhJ is estimated to be high compared to the other founder
strains (Table 4; Figure S2).
3.3 | Diallel analysis
Diallel analysis indicates similar sex, inbreeding, and strain- specific
additive effects for four raw endocast size measurements (length,
TAB LE 2 Sample sizes for all CC founder strains and F1 crosses, after removing specimens with high automated endocast segmentation
error. A = A/J; B = C57BL/6J; C = 129S1/SvlmJ; D = NOD/ShiLtJ; E = NZO/HlLtJ; F = CAST/EiJ; G = PWK/PhJ; H = WSB/EiJ
Paternal strain
A B C D E F G H
Maternal strain A18 18 19 18 18 20 20 20
B20 19 20 18 18 20 16 18
C21 17 19 17 13 19 19 22
D19 21 19 13 22 24 21 17
E19 18 22 20 7 0 0 19
F20 26 19 17 21 17 22 18
G19 20 20 17 19 17 18 17
H19 19 20 20 19 28 20 17
TAB LE 3 Correlations between DO replicate endocast measurements
Replicate measurement correlations
Data 1 Data 2 Volume Surf. area Length Width Height
Original Replicate 1 1.00 1.00 0.96 1.00 1.00
Original Replicate 2 1.00 1.00 1.00 1.00 1.00
Replicate 1 Replicate 2 1.00 1.00 0.98 1.0 0 1.00
8
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PER CIVAL Et AL .
FIGURE 3 Plots of endocast and skull size measurements for inbred founder strains (triangles) and F1 hybrid mice (dots). Comparisons of
(a) endocast height versus length, (b) endocast volume versus surface area, (c) endocast width versus length, and (d) endocast volume versus
skull centroid size. The correlation coefficients (r) of each pair of variables are listed. A comparison of IRE versus Vol/Tib is found in Figure S2
Volume (mm3)
350
400
450
500
550
42.5 45.0 47.5 50.0 52.5 55.0
Overall Skull Centroid Size
Surface Area (mm2)
Volume (mm3)
350
400
450
500
550
320 360 400
Length (mm)
Width (mm)
14 15 16
9.0
9.5
10.0
10.5
11.0
Length (mm)
14 15 16
6.0
6.5
7.0
7.5
Height (mm)
Genotypes
A/J
C57BL/6L
129S1/SvlmJ
NOD/ShiLtJ
NZO/HlLtJ
CAST/EiJ
PWK/PhJ
WSB/EiJ
F1 Hybrid
(b)(a)
(d)
(c)
r = 0.639
r = 0.800
r = 0.984
r = 0.831
TAB LE 4 Endocast measurement mean (SD) values for whole CC founder/F1 strain sample and each founder strain
Volume (mm3)
Surface area
(mm2)Length (mm) Width (mm) Height (m m) IRE Vol/ Ti b
Whole sample 461.71 (40.96) 365.11 (22.90) 15.40 (0.54) 10.16 (0.32) 6.87 (0.28) 0.55 (0.01) 0.47 (0.01)
A/J 402.33 (14.72) 333.36 (9.79) 14.71 (0.29) 9.73 (0.15) 6.48 (0.12) 0.54 (0.01) 0.46 (0.01)
C57BL/6J 470.06 (9.48) 363.22 (4.79) 15.19 (0.16) 10.20 (0.10) 7.13 (0.09) 0.57 (0.01) 0.47 (0.01)
129S1/SvlmJ 458.68 (21.16) 357.97 (11.72) 15.01 (0.28) 10.06 (0.12) 6.92 (0.16) 0.56 (0.01) 0.47 (0.01)
NOD/ShiLt J 521.26 (7.95) 388.50 (4.22) 15.39 (0.16) 10.45 (0.10) 7.48 (0.10) 0.57 (0.01) 0.47 (0.01)
NZO/HlLtJ 461.25 (12.21) 375.70 (7.18) 15.89 (0.28) 10.47 (0.21) 6.64 (0.12) 0.52 (0.01) 0.46 (0.00)
CAST/E i J 349.94 (6.87) 298.11 (4.17) 13.71 (0.14) 9.34 (0.13) 6.13 (0.10) 0.56 (0.01) 0.48 (0.01)
PWK/PhJ 359.84 (12.00) 306.66 (7.75) 14.25 (0.21) 9.18 (0.15) 6.43 (0.07) 0.54 (0.00) 0.50 (0.01)
WSB/EiJ 394.51 (13.37) 318.69 (7.27) 14.04 (0.22) 9.60 (0.14) 6.70 (0.14) 0.58 (0.01) 0.50 (0.01)
|
9
PERCIVAL Et AL .
height, width, volume) (Figure 4). Both female sex and inbreeding
(i.e. having two parents of the same founder strain genotype) are
associated with smaller endocast dimensions. The interaction of in-
breeding and sex leads to a significant increase in endocast length
but has no effect on other raw size measures. This means that female
founder strain mice tend to have longer endocasts than expected
based on the additive combination of overall inbreeding and sex ef-
fects, which are both individually associated with a reduced length.
Almost all strain- specific additive effects on endocast size are sig-
nificant. C57BL/6J, 129S1/SvlmJ, NOD/ShiLtJ and NZO/HlLtJ typi-
cally lead to a larger endocast, whereas A/J, CAST/EiJ, PWK/PhJ and
WSB/EiJ typically lead to a smaller endocast (Figures 4 and 5). These
strain- specific additive effects generally make sense, with strains
of more extreme size having stronger estimated additive effects on
each size measurement. One major exception to this is the endocast
height of NZO/HlLt J. This is the largest of the inbred founder strains
and its strain- specific additive effect is strongly positive for length,
width and volume. But the additive effect of NZO/HlLtJ genotype
on endocast height is not significantly different than zero.
The diallel results for the index of relative encephalization (IRE)
and the cube root of volume over tibia length (Vol/Tib) indicate a
significant positive effect of female sex and inbreeding on encephal-
ization (Figures 4 and 5). However, opposite to raw size measures,
the positive inbreeding effect leads to higher encephalization index
measures. Half of the strain- specific additive effects are significant
for IRE and Vol/Tib. The NOD/ShiLtJ effect is positive for IRE as
it is for raw volume. The A/J Vol/Tib effect is negative as it is for
raw volume. PWK/PhJ is negative for IRE as it is for raw volume,
but (surprisingly) is positive for Vol/Tib. The WSB/EiJ genotype,
which leads to a smaller endocast size, is associated with relatively
high encephalization for both measures. The NZO/HlLtJ genotype,
which is associated with large endocast size, exhibits relatively low
encephalization.
Although a minority of non- additive factors and their interac-
tions have a significant effect on endocast measures, there are some
non- additive genetic factors that frequently show significant effects
(Table 5). For example, 50% of strain- specific maternal factors have a
significant effect on endocast length, whilst 62.5% have a significant
effect on IRE. Between 10% and 22% of the cross- specific symmet-
ric effects are significant for each of the six endocast measures.
Whilst each significant non- additive genetic factor typically ex-
plains a small amount of phenotypic variation, the combined effect
of all non- additive factors explains a sizable proportion of pheno-
typic variation. Strain- specific additive factors explain between 32%
and 78% of phenotypic variation, whereas the combined influence
of non- additive effects explains between 10% and 35% of pheno-
typic variation (Table 6). Generally, additive genetic factors explain
much more of the total variation for the raw size measures and IRE.
In contrast, non- additive genetic factors explain approximately as
much phenotypic variation as additive genetic factors for the Vol/
Tib encephalization measure, which has a heritability (narrow- sense)
estimate of 32% and non- additive factors explaining 35% of the
variation.
3.4 | Significant DO QTL peaks
Genome scans for the endocast measurements (Figure 6) identified
a shared QTL for endocast volume, surface area, width and height
at approximately 177.04 Mb on Chromosome 1 (Figure 5; α = 0.05
LOD thresholds between 7.307 and 7.487). An R2 value was calcu-
lated from the LOD score at this QTL, separately for each of the
FIGURE 4 Diallel estimated mean effects of a subset of major additive and non- additive genetic factors (circles) on endocast
measurements, with 95% confidence intervals (horizontal lines). Genetic factors with a significant effect on an endocast measurement are
those with a confidence interval that does not include zero (vertical dashed line)
Female Sex Factor
Inbreeding Factor
Inbreeding x Sex Interaction
A/J - Additive
C57BL/6J - Additive
129S1/SvlmJ - Additive
NOD/ShiLtJ - Additive
NZO/HlLtJ - Additive
CAST/EiJ - Additive
PWK/PhJ - Additive
WSB/EiJ - Additive
Factor Coefficient Estimates
-30
-10
0
10
20
-30
-10
0
10
20
-30
-10
0
10
20
-30
-10
0
10
20
-30
-10
0
10
20
-30
-10
0
10
20
Length Width Height Volume IREVol/Tib
FIGURE 5 Visual representation of significant positive (+)
and negative (−) additive strain- specific effects on endocast
measurements, as estimated using Diallel analysis
Significant Additive Effects
Strain
A/J
A/J
C57BL/6L
C57BL/6L
129S1/SvlmJ
129S1/SvlmJ
NOD/ShiLtJ
NOD/ShiLtJ
NZO/HlLtJ
NZO/HlLtJ
CAST/EiJ
CAST/EiJ
PWK/PhJ
PWK/PhJ
WSB/EiJ
WSB/EiJ
Length
Height
Width
Volume
IRE
_
_
_
_
_
_
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
_
+
+
Vol/Tib
_
_
_
_
+
+
+
+
10
|
PER CIVAL Et AL .
measurements with a significant association. A 0.08 value for endo-
cast volume indicates that 8% of endocast volume phenotypic vari-
ance is explained by genetic variation under this QTL. The R2 value is
0.07 for surface area, 0.06 for width, and 0.07 for height. Within the
DO mouse sample, the genome- wide heritability of these measures
was estimated as 0.71 for volume, 0.66 for surface area, 0.76 for
width and 0.71 for height.
A 1.5 LOD score drop interval around the significant peak
includes the Chromosome 1 region between 176.0610 and
177.4748 Mb (GRCm38 [mm10]; Table 7). The five protein- coding
genes found under this peak are Pld5, C ep170, Sdccag8, Akt3 and
Zb tb18 (Figure 7). Variation in some of these genes has been previ-
ously associated with brain size phenotypes.
No mutations in human PLD5 have been associated with disease.
A mouse knockout of Pld5 displayed abnormal vertebral arch tho-
racic process morphology, but no other significant abnormalities
(www.mouse pheno type.org; Dickinson et al., 2016). CEP170 is a
centrosome protein that is downstream of WDR62 in a pathway im-
portant for brain development. Mutations of WDR62 within cerebral
organoids disrupt this pathway, leading to a depletion of CEP170,
which may contribute to autosomal recessive primary microcephaly
(Zhang et al., 2019). However, no specific mutations within CEP170
are known to contribute to microcephaly.
SDCCAG8 is a centrosome protein that is important for neuron
differentiation and radial migration to the cortical plate of the brain
(Insolera et al., 2014). Mutations in SDCCG8 have been previously
TAB LE 5 The number and percentage (in parentheses) of additive and non- additive factors with a significant effect on endocast
measurements
# of factors Length Height Width Volume IRE Vo l/ Ti b
Female sex factor 11 (100%) 1 (100%) 1 (100%) 1 (100%) 1 (100%) 1 (100%)
Inbreeding factor 11 (100%) 1 (100%) 1 (100%) 1 (100%) 1 (100%) 1 (100%)
Inbreeding/sex interaction 11 (100%) 0 (0%) 0 (0%) 0 (0%) 1 (100%) 0 (0%)
Strain- specific additive 8 7 (87.5%) 7 (87.5%) 8 (100%) 8 (100%) 4 (50%) 4 (50%)
Strain- specific additive/sex 8 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 2 (25%)
Strain- specific maternal 8 4 (50%) 0 (0%) 0 (0%) 1 (12.5%) 5 (62.5%) 3 (37.5%)
Strain- specific maternal/sex 8 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%)
Strain- specific inbreeding 8 2 (25%) 1 (12.5%) 2 (25%) 0 (0%) 2 (25%) 4 (50%)
Strain- specific inbreeding/sex 8 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%)
Cross- specific symmetric 28 5 (17.9%) 5 (17.9%) 3 (10.7%) 6 (21.4%) 6 (21.4%) 5 (17.9%)
Cross- specific symmetric/sex 28 4 (14.3%) 1 (3.6%) 0 (0%) 3 (10.7%) 0 (0%) 0 (0%)
Cross- specific asymmetric 28 1 (3.6%) 3 (10.7%) 1 (3.6%) 2 (7.1%) 2 (7.1%) 2 (7.1%)
Cross- specific asymmetric/sex 28 0 (0%) 1 (3.6%) 0 (0%) 1 (3.6%) 0 (0%) 0 (0%)
TAB LE 6 Heritability estimates for each endocast measurement, broken down to indicate the amount of phenotypic variation explained
by every category of additive and non- additive genetic factors
Length Height Width Volume IRE Vol/ Ti b
Sum additive 0.64 0. 76 0.71 0.78 0.68 0.32
Strain- specific additive 0.63 0 .76 0 .71 0.78 0.68 0.30
Strain- specific additive/sex 0.00 0.00 0.00 0.00 0.00 0.02
Sum non additive 0.19 0.12 0.14 0.10 0.16 0.35
Strain- specific maternal 0.03 0.00 0.01 0.01 0.04 0.04
Strain- specific maternal/sex 0.01 0.01 0.00 0.01 0.01 0.01
Strain- specific inbreeding 0.03 0.02 0.03 0.01 0.02 0.09
Strain- specific inbreeding/sex 0.00 0.0 0 0.00 0.00 0.00 0.00
Cross- specific symmetric 0.09 0.07 0.09 0.06 0.09 0.17
Cross- specific symmetric/sex 0.02 0.01 0.00 0.01 0.00 0.02
Cross- specific asymmetric 0.00 0.00 0.01 0.00 0.01 0.01
Cross- specific asymmetric/sex 0.00 0.00 0.00 0.00 0.00 0.00
Sum all 0.83 0.87 0.85 0.88 0.84 0.67
% additive 0.77 0.87 0.84 0.89 0.81 0.48
|
11
PERCIVAL Et AL .
associated with ciliopathy, cystic kidney and retinal disorder and
syndromic patients that suffer from intellectual disability, seizures
and schizophrenia (Flynn et al., 2020; Hamshere et al., 2013). Mice
deficient in SDCCAG8 have the retinal- renal phenotype, but also rib
cage abnormalities and polydactyly with triphalangeal thumbs (Airik
et al., 2016).
Akt family genes encode protein kinase enzymes that are
important for growth and metabolism. Akt3 is most highly ex-
pressed in the developing brain and testes. Ak t3 null mutant
FIGURE 6 The results of genome- wide scan using an additive haplotype model to identify genomic regions significantly associated with
six endocast measurements
135791113151719246810 12 14 16 18 X
0
5
10
15
Chromosome
LOD Score
135791113151719246810 12 14 16 18 X
0
5
10
15
LOD Score
135791113151719246810 12 14 16 18 X
0
5
10
15
LOD Score
135791113151719246810 12 14 16 18 X
0
5
10
15
LOD Score
135791113151719246810 12 14 16 18 X
0
5
10
15
LOD Score
135791113151719246810 12 14 16 18 X
0
5
10
15
LOD Score
Length
Width
Height
Volume
Surface Area
IRE
TAB LE 7 Chromosome peak locations associated with significant
LOD scores, with 1.5 LOD drop confidence intervals defined
Measurement
Peak position
(Mb) LOD score 1.5 LOD interval (Mb)
Volume Chr1: 177.0402 16.36296 176.0744– 177.3097
Surface area Chr1: 177.0402 13.83357 176.074 4– 177.30 97
Width Chr1: 177.0402 12 .5 6471 176.4709– 177.4748
Height Chr1: 176.5670 14.42699 176.0610– 17 7.4748
12
|
PER CIVAL Et AL .
mice display normal body size, normal glucose levels and 20–
25% smaller brains by weight when compared to controls (Easton
et al., 20 05; Tschopp et al ., 20 05). These mu tant mice are healthy
with normal brain structural organization, suggesting an overall
scaled decrease in brain size rather than a specific reduction in
a particular brain region. Brain cell size reduction and cell num-
ber reduction contribute to producing a smaller brain (Easton
et al., 2005; Tschopp et al., 2005). Mice with increased AKT3 sig-
nalling activity in the developing brain had a larger brain and an
increased frequency of seizures. These brains also display normal
anatomical organization, although there may be a relatively large
hippocampus (Tokuda et al., 2011). Humans with microdeletions
that include AKT3 display microcephaly, agenesis of the corpus
callosum, and epilepsy. However, it is likely that loss of AKT3 is
primarily responsible for microcephaly whilst loss of other genes
is responsible for the other phenotypes (Depienne et al., 2017).
ZBTB18 plays an important role in neurogenesis and nor-
mal cortical growth within the brain. Mice with ZBTB18 loss of
function mutations die at birth with neocortical defects. Central
nervous system specific loss of function leads to reduced neu-
ronal differentiation and increased glial differentiation, in turn
producing a serious postnatal phenotype with microencephaly,
agenesis of the corpus callosum, and cerebellar hypoplasia (Xiang
et al., 2012). Patients with microdeletions that include ZBTB18
(and often AKT3), display microcephaly, agenesis of the corpus
callosum, and epilepsy. It is likely that loss of ZK TB18 is the pri-
mary cause of agenesis of the corpus callosum, although it may
contribute secondarily to microcephaly phenotypes (Depienne
et al., 2017).
3.5 | DO QTL haplotype effects
The estimated effect of each CC founder strain haplotype indi-
cates that a major negative effect of the NZO/HlLtJ haplotype
drives the significant QTL on Chromosome 1 (Figure 8; Figure
S3). On average, the NZO/HlLtJ haplotype in this genomic region
leads to a decrease in endocast height, width, surface area and
volume. No other founder strain haplot ype has a notable ef fect on
endocast phenotype in this region. This implies that one or more
genetic variants found in the NZO/HlLtJ genome, but not in the
other founder strain genomes, leads to significantly smaller endo-
cast size across this region.
To identify candidate variants that might be functionally re-
sponsible for this endocast association, a search for variants was
completed using the Wellcome Sanger Institute Mouse Genomes
Project online query tool (https://www.sanger.ac.uk/sange r/
Mouse_SnpVi ewer), which identifies SNPs and other variants
that differ between the aligned genomes of many inbred mouse
strains (Keane et al., 2011; Yalcin et al., 2011). We searched for
missense mutations, frameshift variants, stop codon mutations,
indels and structural variants within our region of interest on
Chromosome 1 (1:176061000– 177474800) across the eight CC
founder strains because these variant types are most likely to
lead to a change in protein expression and function.
Twenty missense mutations were identified across the eight CC
founder strains, with 13 of them being CAST/EiJ specific variants,
one being a WSB/EiJ specific variant, one a C57BL/6J specific vari-
ant, and one being an NZO/HlLtJ variant. Because our haplotype
coefficient plots (Figure 8; Figure S3) indicate that the genetic vari-
ant(s) of interest are likely to be NZO/HlLtJ specific, we suggest SNP
rs247597104 at 1:177050102 within Akt3 as the most promising
causal mutation candidate within the QTL interval.
Amongst 59 structural variants identified in this region across
the eight CC founder strains, three of them are NZO/HlLtJ specific
insertions (176,406,258- 176,406,284; 176,441,538- 176,463,577;
176,867,926- 176,867,928). These insertions may also be interesting
candidates to explore further.
FIGURE 7 Map of the protein- coding genes found under our
interval of interest on mouse Chromosome 1
Pld5 Cep170
Sdccag8
Akt3 Zbtb18
176.1 Mb 176.5 Mb 177.0 Mb 177.4 Mb
Chromosome 1
FIGURE 8 CC founder strain- specific phenotype coefficients (above) and LOD scores from the genome- wide scan (below) for the
significant association between founder strain haplotype and endocast volume. Coefficient plots for other significant association
phenotypes are found in Figure S3
420
440
460
480
50 100150
0
5
10
15
Chromosome 1 position (Mb)
QTL effects (mm³)LOD
A/J
C57BL/6J
129S1/SvlmJ
NOD/ShiLtJ
NZO/HlLtJ
CAST/EiJ
PWK/PhJ
WSB/EiJ
|
13
PERCIVAL Et AL .
4 | DISCUSSION
The skull is a complex skeletal structure that supports many criti-
cal organismal functions. Simultaneous growth and development
of multiple interacting tissues, including skull, brain and muscles, is
required to produce a fully functional head. Molecular interactions
are known to help regulate synchronous brain and face formation
processes early in development, but physical- mechanical interac-
tions between tissues are also necessary for the development of
typical adult head morphology (reviewed by Marcucio et al., 2011;
Richtsmeier & Flaherty, 2013; Adameyko & Fried, 2016). Variation in
skull morphology between populations or species may be based on
some combination of (1) direct changes to bone developmental pro-
cesses and (2) plastic responses of the developing bone to variation
in the size of nearby soft tissue structures like the brain. Here, we
quantified the importance of genetic factors in determining overall
neurocranial form to help determine the mechanistic basis of neuro-
cranial variation.
We investigated the genetic basis of total endocast size and rel-
ative brain size (i.e. encephalization) across a range of morphologi-
cally ‘normal’ adult mouse skulls. Our diallel analysis of eight inbred
strains and their F1 crosses indicated that endocast size measures
are highly heritable and are primarily determined by additive genetic
factors, although some non- additive genetic factors have a signifi-
cant imp act on phenotyp e. Our as sociati on stud y of an out bred po p-
ulation derived from the same founder strains identified a significant
association between several endocast size measures and haplotype
variation within a short interval on mouse Chromosome 1. The list of
protein- coding genes within this genomic interval supports the hy-
pothesis that genes primarily driving brain growth to contribute sec-
ondarily to determining neurocranial size and shape. In this case, it
appears that increased mouse endocast size relative to overall skull
size is accommodated by increased neurocranial height.
4.1 | Automated method validation
Our automated endocast segmentation method produced measure-
ments that closely matched those collected using a time- consuming
process of manual μCT image preparation and Endex software ap-
plication on the same specimens. However, a few sources of error
were noted. Most important for our genetic analysis, the incorrect
identification of the foramen magnum by our nonlinear registration
process led to inaccurate endocast length measurements in some of
the specimens. However, specimens with high automated endocast
length error were successfully identified as outliers based on residu-
als of an endocast volume to endocast length regression. This is be-
cause errors in foramen magnum identification cause proportionally
greater errors in endocast length estimates compared to endocast
volume estimates. These outlier specimens were removed from the
sample before other analyses were performed. Other notable dif-
ferences between automated and manual endocast segmentations
were based primarily on manual endocast identification error and
had no impact on the quality of our diallel analysis or GWAS. A more
detailed discussion/comparison of segmentation methods can be
found in the Supporting Methods, Figures and Tables document
(File S1).
4.2 | Normal mouse endocast variation
Across our sample of CC founder strains and F1 crosses, raw endo-
cast measurements were positively correlated with each other and
with overall skull size (Figure 3). Founder strains can be differenti-
ated by mean endocast size values, with wild- derived strains being
the smallest for most measures. The NZO/HlLtJ strain pops out as
unusual because it has the largest overall skull size, but an interme-
diate endocast volume. This strain was bred for increased obesity
(Bielschowsky & Bielschowsky, 1956), resulting in a mouse with
both higher fat and lean body mass (Ackert- Bicknell et al., 2008).
This strain also displays a longer body length (Center for Genome
Dynamics, 2009) and a large but flat skull compared to the other CC
founder strains (Percival et al., 2016a). The NZO/HlLtJ strain has a
high endocast surface area relative to endocast volume (Figure 3b),
which likely reflects a relatively elongated and disproportionately
flat neurocranium.
Pairwise correlations suggest that endocast height can vary
somewhat independently from volume, width, and length. From a
genotype- specific perspective, the additive effect of the NZO/HlLtJ
genotype is associated with the increased size of most measures, but
there is no significant additive effect for the NZO/HlLtJ genotype on
endocast height. More broadly, we argue that variation in endocast
length and width are driven more by the growth of the endochon-
drally ossified cranial base bones whilst endocast height depends
more on the growth of intram embranously ossif ie d bones of the cra-
nial vault. The longitudinal growth of the cranial base is limited by
the speed of cellular proliferation and hypertrophy in cartilaginous
synchondroses between ossified centres. On the contrary, intram-
embranous ossification at cranial vault sutures is possible in multi-
ple directions at once as these bones continue to expand towards
each other dorsally and medially. Additionally, mechanical forces
are important for maintaining open cranial vault sutures with via-
ble precursor cell populations at the suture margins (Herring, 2008).
Therefore, cranial vault shape and size may be more directly affected
by the mechanical forces (or lack of forces) imposed during postnatal
brain growth. In other words, vault bone sutures are likely to remain
patent and growing as long as there is a tensile force caused by brain
growth, and they are likely to meet and fuse when this force de-
creases below a certain threshold (or even with the appearance of
compressive forces across the suture as bone fronts touch).
If an adult brain is small in proportion to overall skull size, we
expect the size of the early ossifying cranial base to be roughly
proportional to overall skull size whilst the cranial vault will more
closely match brain size. We expect low encephalization organisms
to have flatter neurocrania based on the argument that cranial vault
height has a more plastic response to variation in brain size. Similarly,
14
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PER CIVAL Et AL .
we expect organisms with high encephalization to have taller and
rounder cranial vaults that accommodate their proportionally larger
brains. Previous analysis of the CC founder/F1 skull dataset identi-
fied a pattern where specimens with larger overall skull size showed
proportionally smaller and less globular neurocrania with greater
basicranial flexion (Pavličev et al., 2017). We assume that this result
is largely driven by the presence of the NZO/HlLtJ genotype in F1
crosses leading to relatively small brain to skull size ratios. Our ex-
pectations are also supported by the fact that increased endocranial
pressure and intracranial fluid volume in rodent models of hydro-
cephaly tend to have more domed or globular cranial vaults rather
than proportionally longer cranial bases (Holdener et al., 2019;
Ibañez- Tallon et al., 2002; Moss & Young, 1960).
If the cranial vault is more developmentally plastic than length
or width, it might easily accommodate evolutionary changes in brain
size and encephalization, potentially leading it to covary strongly with
encephalization across species. However, multiple regression analy-
sis indicates that (out of length, width and height) maximum brain
width contributes most to variation in endocast volume across avian
species and has increased relative to brain endocast volume over
the course of evolutionary history in birds and mammals (Kawabe
et al., 2009). A subsequent analysis of mammalian endocast width
and volume indicated a strong linear relationship, although mam-
malian brains tend to be more slender than avian brains (Kawabe
et al., 2013). Neurocranial globularity and endocast length were also
identified as a major axis of endocast shape variation across marsu-
pials (Weisbecker et al., 2021). So, although variation in vault height
might be a major basis for the intr aspecies neurocranial shape dif fer-
ences across mice, evolution has produced inter- species differences
that vary strongly along other axes of neurocranial shape variation.
4.3 | Mouse endocast quantitative genetics
Our results indicate a high heritability of endocast size and en-
cephalization measures, with a low proportion of variance explained
by non- additive factors; except in the case of endocast volume
relative to tibia length (Vol/Tib). Endocast heritability values (0.32–
0.78) are higher or similar to those previously reported for measures
of relative skull length (0.46) in the same sample of mice (Percival
et al., 2016a) and those estimated for principal components of
DO mouse facial shape (generally between 0.42 and 0.57) (Katz
et al. , 2020) . Alt hou gh it is te mpting to th ink that the se hi gher herita-
bility values indicate a greater potential for heritable change in mor-
phology, lower values in the previous analyses might be expected
based on scaling of linear skull measures (Percival et al., 2016a), dif-
ferences in the type of measurement and the list of covariates (Katz
et al., 2020). Either way, our results confirm a high heritability for
endocast size measures.
Although strain- specific additive factors explain three to four
times more endocast variation than non- additive factors, there is a
substantial nonadditive inbreeding effect for each measure. As with
previous analyses of these and other mouse populations, inbred
mice tend to be smaller than expected based on additive genotypic
predictions (Ingram et al., 1982; Kurnianto et al., 1999; Leamy, 1982;
Pavličev et al., 2017; Percival et al., 2016a), although the inbreeding
effect on encephalization measures is reversed. So, inbred mice tend
to have reduced total body and neurocranial size, but large brains
relative to skull size and body size. This may indicate stronger canal-
ization of brain size, in the sense that brain size varies less than skull
size or body size within an intraspecies contex t. Studies of en cephal-
ization indices across species covering a much wider range of body
sizes indicate an allometric relationship where larger organisms tend
to have proportionally smaller brains (Marugán- Lobón et al., 2016)
and proportionally larger faces (Cardini, 2019) than small organisms.
Strong brain size canalization or this broad allometric pattern may
partially explain why artificial selection for increased body size in
the NZO/HlLtJ strain has produced mice with a large body and skull
size, but brain volumes equivalent to mice with moderate body sizes
(e.g. C57BL/6J) (Figure 3).
The Vol/Tib encephalization measure has a lower heritability,
where an equal proportion of phenotypic variance is associated with
additive and non- additive genetic factors. This lower heritability
might be expected if there are fewer genetic factors that pleiotropi-
cally influence neurocranial and tibia variation than those that pleio-
tropically influence neurocranial and cranial base variation. A lower
number of shared additive genetic factors is expected to lead to a
lower proportional additive heritability component.
Cross- specific symmetric genetic effects explain about half
of the non- additive factor contributions to Vol/Tib variance.
This indicates that specific founder strain combinations in first-
generation crosses produce Vol/Tib values that consistently di-
verge from the additive genetic expectations, regardless of which
strain is the mother (because it is a ‘symmetric’ effect). The sec-
ond highest non- additive contribution to Vol/Tib variance is from
strain- specific inbreeding factors. Fifty percent of the founder
strains display a statistically significant inbreeding effect that di-
ver ges from th e over all mouse inbreeding effect for this encephal-
ization measurement.
Differences between the direction and strength of additive ge-
notypic effects on the IRE and Vol/Tib encephalization indices are
mathematically based on the choice of size standardization measure-
ments. Tibia length is an aspect of hind limb length, whilst cranial
base length measures an aspect of neurocranial size that we believe is
more strongly representative of body size than other skull measures.
However, because cranial base length is a skull measurement, we an-
ticipate that it will covary more strongly than overall body size with
neurocranial measurements. Tibia length was chosen as a proxy for
the overall skeletal size of the body because we were concerned that
body size measures like weight would be inappropriately skewed by
variation in body fat between mouse strains. Unfortunately, both of
our proxies for body size are imperfect and we cannot currently de-
termine which of these measures is a better basis for encephalization
estimation at this time. A post hoc comparison indicated that NZO/
HlLtJ and PWK/PhJ have an unusually high overall skull size (i.e. cen-
troid size) compared to tibia length, whilst the other founder strain
|
15
PERCIVAL Et AL .
specimens fall close to a single regression line. This difference be-
tween skull and tibia size measures partially explains the divergent
interpretations of additive strain encephalization effects within our
results. It also confirms that different body size measures can lead
to notably different conclusions (see also Hallgrímsson et al., 2019).
4.4 | Chromosome 1 QTL for neurocranial size
We identified a significant QTL on mouse Chromosome 1 for meas-
ures of endocast width, height, volume and surface area (Figure 6).
In each case, the QTL effect at this locus is entirely driven by the
contrast between the NZO/HlLtJ strain and remaining strain haplo-
types. Mice carrying the NZO/HlLtJ haplotype tend to have smaller
endocasts (Figure 8; Figure S3) in all measured dimensions except
length. This failure to discover a neurocranial length QTL may mean
that neurocranial length is determined by different genetic loci. It is
also possible that a relatively high level of endocast leng th measure-
ment error serves to obscure a true causal effect of this locus, de-
spite the successful removal of major endocast measurement error
outlier specimens prior to analysis. Whether or not endocast length
should display a significant association with haplotype variation in
this region, we interpret this QTL as being associated with the over-
all neurocranial size.
Given that our endocast size measurements have a high heritabil-
ity for both CC Founder/F1 and DO samples and most strain- specific
additive genetic effects on endocast size are significant, it is surpris-
ing that only one QTL was identified in our analysis and that only
one of the founder strains displays a significant haplotype effect at
this QTL. Other portions of the additive variance in endocast size
measures may be distributed across many loci, making them difficult
to identify as QTL. Given our relatively high sample size, it is disap-
pointing that so much of the endocast size heritabilit y remains unex-
plained by our association study. The clear presence of this missing
heritability suggests that seemingly simple strain- specific additive
genetic effects are usually the result of allelic variation at many loci.
A variety of QTL related to skull size, organ size and overall body
size have been previously identified in mice, although none of them
appears to overlap our Chromosome 1 QTL. For example, multiple
QTL associated with a skeletal size and organ weights in a mouse in-
tercross of SM/J and LG/J inbred strains have been identified, but do
not overlap with our QTL (Kenney- Hunt et al., 2006, 2008; Norgard
et al., 2009; Wolf et al., 2005). QTL associated with skull morpho-
logical variation for recombinant congenic strains of Mus spretus
(SEG/Pas) and Mus musculus (C57BL/6) (Burgio et al., 2009; Burgio
et al., 2012a, 2012b), hybrids of wild Mus musculus domesticus and
Mus musculus (Pallares et al., 2014), a backcross of C57BL/6J and
A/J (Maga et al., 2015), and a different outbred population of mice
(Carworth Farms White) (Pallares et al., 2015) also do not overlap
with our region of interest.
Given that neurocranial size is a major contributor to overall skull
size and there are systemic growth factors that impact many as-
pects of organismal growth, it is surprising that our QTL for general
neurocranial size was not identified in previous mouse studies of
size variation, especially since we estimate it explains 8% of endo-
cast volume variation in our sample. This may mean the QTL con-
tributes specifically to endocast size and/or brain size. Alternatively,
this might be an important locus for determining overall organismal
size, but for which most mouse strains are genetically fixed. In this
case, the QTL might only be identifiable when a mouse strain with an
otherwise rare allele is included in the analysis (hypothetically, the
NZO/HlLtJ strain in this case).
The fact that all protein- coding genes under the region of inter-
est have been previously associated with brain growth and/or brain
pathology supports the idea that genetic variation at this QTL pri-
marily impacts brain developmental processes rather than bone de-
velopmental processes. One alternative explanation for this result is
that the identified ‘brain’ factor also has undocumented pleiotropic
effects on bone development. Although we are unable to systemati-
cally reject this hypothesis, we believe it is unlikely, particularly if the
causal mutation falls within Akt3. AKT3 is reported to be strongly
expressed within the developing brain and testes, but not within de-
veloping bone.
Of particular interest as a candidate for the measured QTL effect
is an NZO/HlLtJ specific missense mutation within Akt3. Decreased
AKT3 expression during early development leads to significant re-
ductions in brain size without notable abnormalities in brain struc-
ture or body size (Easton et al., 2005; Tschopp et al., 2005). Similarly,
mice with increased AKT3 expression have larger brains with largely
normal anatomical organization and higher seizure risk (Tokuda
et al., 2011). A human genome- wide significant locus for brain shape
is also found centred on AKT3 (Naqvi et al., 2021), reinforcing the
importance of this locus for determining gross brain phenotype in
other mammalian species. However, it is one of the hundreds of
genome- wide significant loci for human brain shape, reinforcing the
fact that a ver y large number of genetic factors contribute to brain
development and adult phenotype.
If the identified missense mutation reduces AKT3 expression,
activity or downstream signalling, this might explain why the NZO/
HlLtJ haplotype within our candidate region leads to reduced en-
docast dimensions. Since the total loss of AKT3 does not appear to
modify brain structural organization, we do not anticipate that this
mutation will influence brain structure or mouse behaviour. Further
investigation of various candidate mutations and the study of brain
growth processes in the CC inbred strains will help to determine the
true causal mutation underlying the identified phenotype- genotype
association. However, a single A kt3 missense mutation is quite ap-
pealing as a candidate. If this or another single NZO/HlLtJ specific
mutation is responsible for reduced adult brain and neurocranial
size, inserting this mutation into other inbred mouse backgrounds
could provide a great way to test how a major non- pathogenic
change in brain size is accommodated by the normal developmental
processes of the growing skull. In this case, we would anticipate a
reduction in early brain growth and adult brain size when compared
to the inbred background strain without the mutation. Based on our
current results, we would expect mutant mouse neurocrania to be
16
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PER CIVAL Et AL .
relatively flat compared to control specimens from the associated
inbred backgrounds.
4.5 | Concluding statement
Endocast size variation across mouse strains is highly heritable and
explained largely by additive genetic factors. Our results suggest
that variation in brain volume leads to secondary variation in neuro-
cranial shape, with a particular impact on the degree of neurocranial
globularity. We propose that a mutation found under the identified
Chromosome 1 peak within the NZO/HlLtJ haplotype primarily
modifies brain developmental processes, leading to a smaller brain,
a notably reduced encephalization index, and a relatively flat neuro-
cranium. If a single mutation in a gene that regulates brain growth is
responsible for this phenotypic shift, it is evidence that substantial
evolutionary change in brain size can happen quite abruptly after a
simple mutation event. Furthermore, it may lead to major second-
ary changes in neurocranial shape based on developmental plastic-
ity of bone growth processes without any subsequent mutations in
genes that directly regulate changes in bone cell activity. Although
increased brain volume in mice may be accommodated largely by
increased neurocranial globularity, other aspects of shape may be
more developmentally plastic in other species. Of course, both skull
shape and brain size are complex traits that are driven by variation
within many genetic loci, some of which may influence both pheno-
types pleiotropically. The fact that so much additive endocast size
variation remains unexplained by our association analysis suggests
that most relevant mutations have small effects on neurocranial
size and encephalization, with our QTL being an outlier. This anal-
ysis does not prove that the close covariation of neurocranial and
brain size and shape is driven primarily by variation in genes of brain
growth. Instead, our results highlight the importance of accounting
for the mechanical influence of nearby soft tissues on the develop-
ment and the evolution of skull shape, where some small subset of
simple mutations might lead to substantial evolutionary changes in
both brain size and skull shape.
ACKNOWLEDGMENTS
Thanks to Gilles Gesquière & Gérard Subsol for developing Endex
endocast segmentation software and providing it for public use
(available at https://perso.liris.cnrs.fr/gilles.gesqu iere/wiki/doku.
php?id=endex). The authors appreciate Louis Borsellino's necessary
contributions during automatic endocast quality control. Thanks
also to the Hallgrímsson lab members who made important early
contributions to manual endocast data collection, including Natasha
Hoehn, Aaron Szymanowski and Francis Smith.
The authors have no conflicts of interest to declare in relation to
this manuscript or its associated methods and results.
AUTHOR CONTRIBUTIONS
CJP – concept/design, acquisition of data, data analysis/interpreta-
tion, drafting of the manuscript, critical revision of the manuscript,
approval of the article. JD – concept/design, acquisition of data, criti-
cal revision of the manuscript, approval of the article. CRH – concept/
design, acquisition of data, drafting of the manuscript, approval of
the article. MV – data analysis/interpretation, critical revision of the
manuscript, approval of the article. CJOC – acquisition of data, data
analysis/interpretation, approval of the article. EZ – data analysis/in-
terpretation, critical revision of the manuscript, approval of the arti-
cle. CR – concept/design, critical revision of the manuscript, approval
of the article. DK – concept/design, data analysis/interpret ation, criti-
cal revision of the manuscript, approval of the article. BH – concept/
design, critical revision of the manuscript, approval of the article.
OPEN RESEARCH BADGES
This article has been awarded Open Data Badge for making publicly
available the digitally- shareable data necessary to reproduce the re-
ported results. Data is available at Open Science Framework
DATA AVAIL AB I LI T Y STATE MEN T
All data included as the basis for our analysis are publicly available.
Endocast measurements and covariates of analyzed specimens are
included as supporting files for this manuscript. μCT images of the
CC Founder/F1 specimens can be found on FaceBase (https://www.
f a c e b a s e . o r g / c h a i s e / r e c o r d / # 1 / i s a : d a t a s e t / R I D =1 - 4 3 F 6 ) . μCT
images and genotype data of the DO specimens can be found on
FaceBase (https://www.faceb ase.org/chais e/recor d/#1/isa:datas
et/RID=1- 731C). Further details on the MusMorph public mouse
dataset are found in a recent publication (Devine et al., 2021)
and associated github repository (https://github.com/jayde vine/
MusMorph), which contain all the information, links, and code nec-
essary for automated image registration, atlas creation, and auto-
mated segmentation. The code and files used as the basis for our
GWAS analysis are found in a different github repository (https://
github.com/marta vidal garci a/endoc ast_qtl).
ORCID
Christopher J. Percival https://orcid.org/0000-0002-8883-9737
David Katz https://orcid.org/0000-0002-0827-5602
Benedikt Hallgrimsson https://orcid.org/0000-0002-7192-9103
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How to cite this article: Percival, C.J., Devine, J., Hassan,
C.R., Vidal- Garcia, M., O’Connor- Coates, C.J. & Zaffarini, E.
et al. (2022) The genetic basis of neurocranial size and shape
across varied lab mouse populations. Journal of Anatomy, 00,
1– 19. Available from: https://doi.org /10.1111/joa .13657
