In silico whole genome association scan for murine prepulse inhibition

Genome-Wide Association Mapping for Female Infertility in Inbred Mice

The genetic factors underlying female infertility in humans are only partially understood. Here, we performed a genome-wide association study of female infertility in 25 inbred mouse strains by using publicly available SNP data. As a result, a total of four SNPs were identified after chromosome-wise multiple test correction. The first SNP rs29972765 is located in a gene desert on chromosome 18, about 72 kb upstream of Skor2 (SKI family transcriptional corepressor 2). The second SNP rs30415957 resides in the intron of Plce1 (phospholipase C epsilon 1). The remaining two SNPs (rs30768258 and rs31216810) are close to each other on chromosome 19, in the vicinity of Sorbs1 (sorbin and SH3 domain containing 1). Using quantitative RT-PCR, we found that Sorbs1 is highly expressed in the mouse uterus during embryo implantation. Knockdown of Sorbs1 by siRNA attenuates the induction of differentiation marker gene Prl8a2 (decidual prolactin-related protein) in an in vitro model of decidualization using mouse endometrial stromal cells, suggesting that Sorbs1 may be a potential candidate gene for female infertility in mice. Our results may represent an opportunity to further understand female infertility in humans.

Integration of genome-wide association and extant brain expression QTL identifies candidate genes influencing prepulse inhibition in inbred F1 mice

Genetic association mapping in structured populations of model organisms can offer a fruitful complement to human genetic studies by generating new biological hypotheses about complex traits. Here we investigated prepulse inhibition (PPI), a measure of sensorimotor gating that is disrupted in a number of psychiatric disorders. To identify genes that influence PPI, we constructed a panel of half-sibs by crossing 30 females from common inbred mouse strains with inbred C57BL/6J males to create male and female F1 offspring. We used publicly available single nucleotide polymorphism (SNP) genotype data from these inbred strains to perform a genome-wide association scan using a dense panel of over 150,000 SNPs in a combined sample of 604 mice representing 30 distinct F1 genotypes. We identified two independent PPI-associated loci on Chromosomes 2 and 7, each of which explained 12-14% of the variance in PPI. Searches of available databases did not identify any plausible causative coding polymorphisms within these loci. However, previously collected expression quantitative trait locus (eQTL) data from hippocampus and striatum indicated that the SNPs on Chromosomes 2 and 7 that showed the strongest association with PPI were also strongly associated with expression of several transcripts, some of which have been implicated in human psychiatric disorders. This integrative approach successfully identified a focused set of genes which can be prioritized for follow-up studies. More broadly, our results show that F1 crosses among common inbred strains can be used in combination with other informatics and expression datasets to identify candidate genes for complex behavioral traits.

Forward genetic approaches to understanding complex behaviors

Assigning function to genes has long been a focus of biomedical research.Even with complete knowledge of the genomic sequences of humans, mice and other experimental organisms, there is still much to be learned about gene function and control. Ablation or overexpression of single genes using knockout or transgenic technologies has provided functional annotation for many genes, but these technologies do not capture the extensive genetic variation present in existing experimental mouse populations. Researchers have only recently begun to truly appreciate naturally occurring genetic variation resulting from single nucleotide substitutions,insertions, deletions, copy number variation, epigenetic changes (DNA methylation,histone modifications, etc.) and gene expression differences and how this variation contributes to complex phenotypes. In this chapter, we will discuss the benefits and limitations of different forward genetic approaches that capture the genetic variation present in inbred mouse strains and present the utility of these approaches for mapping QTL that influence complex behavioral phenotypes.

In silico QTL mapping of basal liver iron levels in inbred mouse strains

Both iron deficiency and iron excess are detrimental in many organisms, and previous studies in both mice and humans suggest that genetic variation may influence iron status in mammals. However, these genetic factors are not well defined. To address this issue, we measured basal liver iron levels in 18 inbred strains of mice of both sexes on a defined iron diet and found ∼4-fold variation in liver iron in males (lowest 153 μg/g, highest 661 μg/g) and ∼3-fold variation in females (lowest 222 μg/g, highest 658 μg/g). We carried out a genome-wide association mapping to identify haplotypes underlying differences in liver iron and three other related traits (copper and zinc liver levels, and plasma diferric transferrin levels) in a subset of 14 inbred strains for which genotype information was available. We identified two putative quantitative trait loci (QTL) that contain genes with a known role in iron metabolism: Eif2ak1 and Igf2r. We also identified four putative QTL that reside in previously identified iron-related QTL and 22 novel putative QTL. The most promising putative QTL include a 0.22 Mb region on Chromosome 7 and a 0.32 Mb region on Chromosome 11 that both contain only one candidate gene, Adam12 and Gria1, respectively. Identified putative QTL are good candidates for further refinement and subsequent functional studies.

The genetics of albuminuria: from haplotype association mapping in mice to genetic causation in humans

Genome-wide haplotype association mapping (HAM) in inbred mouse strains emerged as an efficient method for identifying novel quantitative trait loci for disease-related phenotypes. In this issue of Kidney International, Tsaih et al. present the results of the first HAM for age-related kidney damage in mice and examine the detected loci in the context of the human genome-wide association study for diabetic nephropathy.

Genetics of osteoporosis: accelerating pace in gene identification and validation

Osteoporosis is characterized by low bone mineral density and structural deterioration of bone tissue, leading to an increased risk of fractures. It is the most common metabolic bone disorder worldwide, affecting one in three women and one in eight men over the age of 50. In the past 15 years, a large number of genes have been reported as being associated with osteoporosis. However, only in the past 4 years we have witnessed an accelerated pace in identifying and validating osteoporosis susceptibility loci. This increase in pace is mostly due to large-scale association studies, meta-analyses, and genome-wide association studies of both single nucleotide polymorphisms and copy number variations. A comprehensive review of these developments revealed that, to date, at least 15 genes (VDR, ESR1, ESR2, LRP5, LRP4, SOST, GRP177, OPG, RANK, RANKL, COLIA1, SPP1, ITGA1, SP7, and SOX6) can be reasonably assigned as confirmed osteoporosis susceptibility genes, whereas, another >30 genes are promising candidate genes. Notably, confirmed and promising genes are clustered in three biological pathways, the estrogen endocrine pathway, the Wnt/beta-catenin signaling pathway, and the RANKL/RANK/OPG pathway. New biological pathways will certainly emerge when more osteoporosis genes are identified and validated. These genetic findings may provide new routes toward improved therapeutic and preventive interventions of this complex disease.

Genomic survey of prepulse inhibition in mouse chromosome substitution strains

Prepulse inhibition (PPI) is a measure of sensorimotor gating, a pre-attentional inhibitory brain mechanism that filters extraneous stimuli. Prepulse inhibition is correlated with measures of cognition and executive functioning, and is considered an endophenotype of schizophrenia and other psychiatric illnesses in which patients show PPI impairments. As a first step toward identifying genes that regulate PPI, we performed a quantitative trait locus (QTL) screen of PPI phenotypes in a panel of mouse chromosome substitution strains (CSSs). We identified five CSSs with altered PPI compared with the host C57BL/6J strain: CSS-4 exhibited decreased PPI, whereas CSS-10, -11, -16 and -Y exhibited higher PPI compared with C57BL/6J. These data indicate that A/J chromosomes 4, 10, 11, 16 and Y harbor at least one QTL region that modulates PPI in these CSSs. Quantitative trait loci for the acoustic startle response were identified on seven chromosomes. Like PPI, habituation of the startle response is also disrupted in schizophrenia, and in the present study CSS-7 and -8 exhibited deficits in startle habituation. Linkage analysis of an F(2) intercross identified a highly significant QTL for PPI on chromosome 11 between positions 101.5 and 114.4 Mb (peak LOD = 4.54). Future studies will map the specific genes contributing to these QTLs using congenic strains and other genomic approaches. Identification of genes that modulate PPI will provide insight into the neural mechanisms underlying sensorimotor gating, as well as the psychopathology of disorders characterized by gating deficits.