Quantitative Neurogenetics & QTL Mapping
Genetic Correlates of Gene Expression in Recombinant Inbred Strains: A Relational Model System to Explore Neurobehavioral Phenotypes
The BXD recombinant inbred strains are a versatile reference mapping
panel for genetic dissection of complex phenotypes. These strains
can be used in a relational fashion to combine multi-level data
ranging from sequence gene expression analysis to brain and behavioral
phenotypes. Published winter 2003 in
Neuroinformatics by Elissa J. Chesler, Jintao Wang,
Lu Lu, Yanhua Qu, Kenneth F. Manly and Rob Williams. The paper
is available in
Genetic Structure of Recombinant Inbred Mice.
A comprehensive analysis of linkage maps of recombinant inbred strains
with comparisons to F2, N2, and advanced intercross maps. We genotyped
just over 100 RI strains using a set of approximately 1600 microsatellite
markers. Published October 2001 in
Genome Biology by Rob Williams, Jing Gu, Shuhua Qi, and Lu Lu.
The papers is available both in
HTML versions. Our own local
HTML version includes updated links to new RI genotype data files.
Users of RI strains (AXB-BXA, BXD, BXH, and CXB) will find the mapping
data sets useful.
Complexities of Cancer Research: Mouse Genetics Models.
Cancer susceptibility is a complex interaction of an individual's genetic composition and
environmental exposures. Huge strides have been made in understanding cancer over the
past 100 yr, from recognition of cancer as a genetic disease, to identification of specific
carcinogens, isolation of oncogenes, and recognition of tumor suppressors. A tremendous
amount of knowledge has accumulated about the etiology of cancer. Cancer genetics has
played a significant role in these discoveries. Analysis of high-risk familial cancers has
led to the discovery of new tumor suppressor genes and important cancer pathways.
These families, however, represent only a small fraction of cancer in the general
population. Most cancer is instead probably the result of an intricate interaction of
polymorphic susceptibility genes with the sea of environmental exposures that humans
experience. Although the central cadre of cancer genes is known, little is understood
about the peripheral genes that likely comprise the polymorphic susceptibility loci. The
challenge for cancer genetics is therefore to move forward from the Mendelian genetics
of the rare familial cancer syndromes into the field of quantitative trait loci, susceptibility
factors, and modifier genes. By identifying the genes that modulate an individual's
susceptibility to cancer after an environmental exposure, researchers will be able to gain
important insights into human biology, cancer prevention, and cancer treatment.
Strength in Numbers: Chasing the Engram Using Microarrays.
A short report of a symposium at the 2001 IBANGS meeting.
QTL analysis and genome-wide mutagenesis in mice: Complementary genetic
approaches to the dissection of complex traits .
An upbeat commentary in Behavior Genetics on complex trait analysis
and "cloning" QTLs that we hope will counterbalance the gloomy assessment
by Joe Nadeau and Wayne Frankel (2000). Our review (John Belknap and
colleagues) is in a special issue of Behavior Genetics devoted to QTL
mapping and complex trait analysis. Spread the word: QTL analysis is
thriving, and yes they can be cloned.
Short Course Tutorial in Quantitative Neurogenetics
An introduction to mapping quantitative trait loci (QTLs) written for
neuroscientists taking the 1998 Short Course in Quantitative
Neuroanatomy. Updated August 2000 with new figures and text on RIX
Mapping Genes that Modulate Mouse Brain Development: A Quantitative
A review chapter from Mouse Brain Development that explains the
power of QTL mapping in exploring CNS development. This review included
original data on brain weight and neuron number in different strains of
mice (C57BL/6J mice have about 100 million cells in their brains). My
thanks to Richelle Strom, Guomin Zhou, and Dan Goldowitz for allowing me
use some of our unpublished data in this review.
Genetic Control of Neuron Number
Richelle C. Strom's Ph.D. dissertation (July 1999) on the quantitative
genetic analysis of brain weight and retinal ganglion cell number in mice.
Seven chapters containing lots of great new data on QTLs that modulate
brain weight and neuron number.
Genetic Architecture of the Mouse Hippocampus
An example of a hippocampus used for gene mapping. This dissection is
from the left hemisphere. Five cross-sections illustrate internal
structure. For more details on this work and information on QTLs that
control hippocampal size and structure, see the
JN paper by Lu and colleages below.
Reprint of a paper by Lu Lu and colleagues published in
The Journal of Neuroscience (May 2001). We discovered QTLs on
chromosomes 1 and 5 that modulate size and neuron number in the mouse
hippocampus. In addition to the mapping, this paper contains extensive
morphometric data and cell counts on hippocampus and its components as a
function of age, sex, and brain weight. We found an interesting gain in
hippocampal weight with age that may be related to continuous adult
neurogenesis. We see a similar increase in the olfactory bulbs, but not in
Neurogenetic Analysis of the Olfactory Bulbs in Mice
The olfactory bulbs are a great neural system for quantitative genetic
analysis (they are modular, discrete, and easy to dissect). Here we
describe a set of four QTLs that control the weight of the olfactory
bulbs. This paper also details differences in bulb as a function of age,
sex, and brain weight. Published in Behavior Genetics, 2001.
Biometric and QTL Analysis of the Cerebellum
Graphic illustration of the segregation of genotypes and phenotypes
modulating cerebellar size. Select the figure to get a higher quality
image. The left panel illustrates the distribution of cerebellar
weights for BXD strains that have been categorized by genotype at the
Cbs1a interval on Chr 1. C57BL/6J alleles (BB) at Cbs1a are marked by
blue circles; DBA/2J alleles at Cbs1a are marked by red circles. The
middle panel illustrates the even more striking difference between
strains categorized as BB or DD in the Cbs8a interval on Chr 8. The
right panel illustrates the conjoint and almost perfectly additive
action of these two QTLs.
Reprint of a paper in
The Journal of Neuroscience by David C. Airey and colleagues.
This study covers both the total size of the cerebellum and the fractional
volume of different cerebellar compartments. David and I mapped five QTLs
with relatively intense effects on cerebellar size in a cross between
C57BL/6J and DBA/2J and in BXD recombinant inbred strains. The figure
above shows the effects of two of these QTLs—singly and jointly—on
cerebellar weight in the BXD RI strains.
Complex Trait Analysis of the Mouse Striatum
A stereological and genetic analysis of the caudate nucleus by Rosen and
Williams published in BMC Neuroscience (2001; available online at
www.biomedcentral.com/browse/biology). While there is considerable
strain variation in caudate volume, there is less variation in the number
of caudate neurons (mostly medium spiny neurons). Using an F2 intercross
we were able to map two QTLs that independently control striatal volume (Chr
10) and striatal neuron number (Chr 19).
Combining Mutagensis and QTL Analysis: The Consomic Mutagenesis Screen
This paper describes a new technique to exploit consomic mice (also known
as chromosome substitution strains) to increase the sensitivity of a
recessive mutagenesis screen by restricting analysis to entire litters of
nearly isogenic mice. The method is sensitive enough to detect QTLs and
weak alleles. The consomic mutatgenesis screen is being used by the
Tenneessee Mouse Genomics Consortium to generate and map CNS and
behavioral mutations on chromosome 19. This paper was published in
Mammalian Genome (1999).
Genetic Dissection of Retinal Development
A paper on the genetic basis of variation in the eye and retina published
in Seminars in Cell & Developmental Biology (1998) 9:249-255. We
explain how QTL analysis can be used to detect and characterize genes that
modulate the architecture of the eye and retina. We include original data
on the genetic control of (1) eye weight, (2) numbers of horizontal cells,
and (3) numbers of retinal ganglion cells. This paper was coauthored with
Richelle Strom, Guomin Zhou, and Yan Zhen.
Sketch of the retina, optic stalk, chiasm, and the lateral geniculate
nucleus of a mammal at an early stage of development. The retina
(lower left) has two walls-the outer pigment epithelium and the inner
neural retina. The choroid fissure splits the lower half of the retina
and continues as a groove on the base of the optic stalk. Growth cones
of ganglion cells (not shown) extend across the inner surface of the
retina and grow toward the root of the fissure (the future optic nerve
head) and into the ventral part of the optic stalk (see oblique sketch
at bottom right). Illustration adapted by RWW from the Undiscovered
An Analysis of Variation in Retinal Ganglion Cell Number in Mice
An updated and extended version of a paper published in
The Journal of Neuroscience (1996,
pdf). This paper address the role of genes and envrionmental factors
in controlling the size of cell populations in the central nervous system.
Quantitative electron microscopy was used to count neurons in retinas of
over 450 animals. We measured effects of sex and age, heritability of
differences in neuron populations, and the number of genes responsible for
the substantial differences among strains of mice. Updated May 30,
A Major QTL on Chr 11 Controls Variation in Ganglion Cell Number
This paper follows up on the previous article and was published in
The Journal of Neuroscience (1998,
pdf). Our aim in this work was to map genes that produce large
differences in numbers of neurons in the retina. We succeeded in mapping a
gene locus called Neuron Number Control 1 or Nnc1, on chromosome 11
between Hoxb and Krt1. There are several great candidate
genes in this region, particularly the thyroid hormone alpha receptor.
Nnc1 is the first gene locus known to control normal variation in
neuron number in a vertebrate.
Cell Production and Cell Death in the Generation of Variation in Neuron
Number published in
The Journal of Neuroscience (1998,
Our third paper in this series on the genetic control of the retinal
ganglion cell population in mice. By estimating total cell production in
neonates from 10 different inbred strains of mice, Richelle Strom was able
to determine that the distinct bimodality of strain averages is caused by
differences in cell production. This paper demonstrates that Nnc1
modulates cell production and must be expressed before birth. However,
there are some very interesting differences in the severity of cell death
among strains that would be worth following up on.