Weikuan Gu

Quantitative Trait Loci for Bone Density in Mice: The Genes Determining Total Skeletal Density and Femur Density Show Little Overlap in F2 Mice

Bone mineral density variation is a highly heritable trait and is the best predictor of skeletal fragility. Total skeletal density was determined by PIXIMUS™, and femur density was determined by pQCT. The data were analyzed for quantitative trait loci (QTL) to determine if bone density at a specific skeletal site (femur) would identify new gene loci or the same gene loci as total body (PIXIMUS™). In order to show concordance and differences in QTL for total body bone density versus femur bone density, we performed a genome-wide scan from 633 (MRL × SJL) F2 mice. The bone mineral density (BMD) data from pQCT were used to identify nine QTL on chromosomes 1, 3, 4, 9, 12, 17, and 18, while nine QTL on chromosomes 1, 2, 4, 9, 11, 14, and 15 were identified by PIXIMUS™ data, accounting for 32.5% and 30.4% variation in F2 mice, respectively. QTL on chromosomes 1, 2, 3, 9, 11, 12, 14, 15, 17, and 18 are unique to our study, as they have never been described before. Chromosome 1 (D1Mit33 and D1Mit362) had similar QTL between pQCT and PIXIMUS™. Several QTL were identified for both femur and total body BMD but only two QTL were common for both of these phenotypes. This suggests that genes regulating bone density differ depending on the skeletal site analyzed.

Genetic control of the rate of wound healing in mice

There have been few studies of the inheritance of wound healing in mammals. In this study, we demonstrate that inbred strains of mice differ significantly in the rate of wound healing. Of the 20 strains tested, fast healers (MRL/MpJ-Faslpr and LG/J) healed wounds four times faster than slow healers (Balb/cByJ and SJL/J). The genetic basis underlying the difference in the healing capacity was analysed using F2 populations of two different crosses. We show that the wound healing is a polygenically determined quantitative trait with an average estimated heritability of 86%. The modes of gene action in these two crosses are different. In the (MRL/MpJ × SJL/J) cross, genes regulating fast healing in MRL/MpJ mice exhibited additive effects, whereas these effects were suppressed by a dominant repressor gene in CBA/J mice in the (MRL/MpJ-Faslpr × CBA/J) cross. Information gained from this investigation provides insight into further study of molecular mechanisms underlying the rate of wound healing in mammals.

Analysis of gene expression in the wound repair/regeneration process

Abstract. Wound repair/regeneration is a complex process consisting of three stages: inflammation, tissue regrowth, and remodeling, which together involve the action of hundreds of genes. In order to i) identify and analyze the genes that are expressed at the inflammatory stage of repair (i.e., 24 h after injury) and ii) evaluate the molecular basis of fast-wound repair/regeneration in adult mammals, we examined the expression of 8734 sequence-verified genes in response to ear punch in a fast wound-repair/regeneration strain, MRL/MpJ-Faslpr mice, and a slow-wound-repair strain, C57BL/6J mice. Many differentially expressed genes can be assigned to wound-repairing pathways known to be active during the inflammatory phase, whereas others are involved in pathways not previously associated with wound repair. Many genes of unknown function (ESTs) exhibited a more than twofold increase in MRL/MpJ-Faslpr or C57BL/6J mice, suggesting that current understanding of the molecular events at the inflammatory stage of repair is still limited. A comparison of the differential expression profiles between MRL/MpJ-Faslpr and C57BL/6J mice suggests that fast-wound-repair in MRL/MpJ-Faslpr mice is mediated by a metabolic shift toward a low inflammatory response and an enhanced tissue repair.

DNA Microarrays: Their Use and Misuse

DNA microarray represents one of the major advances in functional genomics. Its ability to study expression of several thousands of genes or even all genes in the entire genome in a single experiment has changed the way in which we address basic biomedical questions. Numerous publications have shown its utility in drug discovery, disease diagnosis, novel gene identification, and understanding complex biological systems. However, there are substantive technical issues associated with the use of this technology that limit the interpretation of microarray data. In this review, we first give an overview of DNA microarray technology and then focus on uncertainty areas of microarray technology that include making microarrays, isolation of RNA and labeling, hybridization and scanning, and data analysis. The center theme of this review is to improve microarray reproducibility by addressing common technical problems. Finally, we briefly summarize microarrays applications in biomedical research.

Differential protein profile in the ear-punched tissue of regeneration and non-regeneration strains of mice: a novel approach to explore the candidate genes for soft-tissue regeneration.

Wound repair/regeneration is a genetically controlled, complex process. In order to identify candidate genes regulating fast wound repair/regeneration in soft-tissue, the temporal protein profile of the soft-tissue healing process was analyzed in the ear-punched tissue of regeneration strain MRL/MpJ-Fas(lpr) (MRL) mice and non-regeneration strain C57BL/6J(B6) mice using surface-enhanced laser desorption and ionization (SELDI) ProteinChip technology. Five candidate proteins were identified in which responses of MRL to the ear punch were 2-4-fold different compared to that of B6. Their corresponding genes were predicted using an antigen-antibody assay validated mass-based approach. Most of the predicted genes are known to play a role or are likely to play a role in the wound repair/regeneration. Of the five candidate proteins, the amount of the 23560 Da protein in the ear-punched tissue was significantly correlated with the rate of ear healing in six representative strains of mice, making it a good candidate for fast wound repair/regeneration. We speculate that the increased concentration of the 23560 Da protein in the wound tissue could stimulate the expression of various growth-promoting proteins and consequently speed up the wound repair/regeneration processes. Here, we have shown that examination of protein expression profile using SELDI technology, coupled with database search, is an alternative approach to search for candidate genes for wound repair/regeneration. This novel approach can be implemented in a variety of biological applications.

Quantitative Assessment of Forearm Muscle Size, Forelimb Grip Strength, Forearm Bone Mineral Density, and Forearm Bone Size in Determining Humerus Breaking Strength in 10 Inbred Strains of Mice

Bone strength is an important clinical endpoint of osteoporosis research. The evaluation of the relative importance of bone and muscle components to bone strength has widespread implications for the understanding and preventing of osteoporosis. The objectives of this study were to understand the interrelationship between the different components of the muscular skeletal system and to determine the effect of forearm muscle size, forelimb grip strength, forearm bone mineral density (BMD), and forearm bone size on the humerus breaking strength among 10 inbred strains of mice. The forearm muscle size was measured using a peripheral quantitative computed tomography (pQCT). The forearm BMD and forearm bone size were measured using a PIXIMUS Densitometer. The forelimb grip strength and humerus breaking strength were measured using an Instron Mechanical Tester. Significant correlations were found among the five regional phenotypes. All variables have a moderately high genetic component with heritability estimates of 0.83 for forelimb grip strength, 0.76 for forearm muscle size, 0.6 for forearm BMD, 0.63 for forearm bone size, and 0.68 for humerus breaking strength. Forward stepwise multiregression analysis showed that the forearm BMD, forelimb grip strength, and forearm bone size were three major determinants of bone strength and explained 61% of the variation in bone breaking strength. These data suggest that evaluation of these three parameters together, rather than BMD alone, is a more effective, noninvasive approach for predicting fracture risk.

Gene expression between a congenic strain that contains a quantitative trait locus of high bone density from CAST/EiJ and its wild-type strain C57BL/6J.

Abstract. Peak bone density is an important determining factor of future osteoporosis risk. We previously identified a quantitative trait locus (QTL) that contributes significantly to high bone density on mouse chromosome 1 from a cross between C57BL/6J (B6) and CAST/EiJ (CAST) mouse strains. We then generated a congenic strain, B6.CAST-1T, in which the chromosomal fragment containing this QTL had been transferred from CAST to the B6 background. The congenic mice have a significantly higher bone density than the B6 mice. In this study we performed cDNA microarray analysis to evaluate the gene expression profile that might yield insights into the mechanisms controlling the high bone density by this QTL. This study led to several interesting observations. First, approximately 60% of 8,734 gene accessions on GEM I chips were expressed in the femur of B6 mice. The expression and function of two-thirds of these expressed genes and ESTs have not been documented previously. Second, expression levels of genes related to bone formation were lower in congenic than in B6 mice. These data are consistent with a low bone formation in the congenic mice, a possibility that is confirmed by reduced skeletal alkaline phosphatase activity in serum compared with B6 mice. Third, expression levels of genes that might have negative regulatory action on bone resorption were higher in congenic than in B6 mice. Together these findings suggest that the congenic mice might have a lower bone turnover rate than B6 mice and raise the possibility that the high bone density in the congenic mice could be due to reduced bone resorption rather than increased bone formation.

Chromosomal regions harboring genes for the work to femur failure in mice

Abstract. The work to failure is defined as the maximum energy bone can absorb before breaking, and therefore is a direct test of the risk of fracture. To determine the genetic loci influencing work to failure, we have performed a high density genome-wide scan in 633 (MRL × SJL) F2 female mice. Five loci (P <0.005) with significant effects on work to failure were found on chromosomes 2, 7, 8, 9, and X, which collectively explained around 20% variance of work to femur failure in F2 mice. Of those, only the QTL on chromosome 9 was concordant with bone mineral density (BMD) QTLs. Eight significant interactions (P <0.01) between marker loci were identified, which accounted for an equivalent amount of F2 variance (23%) to combined single QTL effects. Our results demonstrate that most of the genetic loci regulating work to failure are different from those for BMD in the 7-week-old female mice. If this is also true in humans, this finding will challenge the predictive value of BMD for the risk of fracture.

Quantitative trait loci (QTL) for lean body mass and body length in MRL/MPJ and SJL/J F2 mice

Abstract. Studies on the genetic mechanisms involved in the regulation of lean body mass (LBM) in mammals are minimal, although LBM is associated with a competent immune system and an overall good (healthy) body functional status. In this study, we performed a high-density genome-wide scan using 633 (MRL/MPJ × SJL/J) F2 intercross to identify the quantitative trait loci (QTL) involved in the regulation of LBM. We hypothesized that additional QTL can be identified using a different mouse cross (MRL/SJL cross). Ten QTL were identified for LBM on chromosomes (chrs) 2, 6, 7, 9,13 and 14. Of those ten, QTL on chrs 6, 7 and 14 were exclusive to LBM, while QTL on chrs 4 and 11 were exclusively body length. LBM QTL on chrs 2 and 9 overlap with those of size. Altogether, the ten LBM QTL explained 41.2% of phenotypic variance in F2 mice. Five significantly interacting loci that may be involved in the regulation of LBM were identified and accounted for 24.4% of phenotypic variance explained by the QTL. Five epistatic interactions, contributing 22.9% of phenotypic variance, were identified for body length. Interacting loci on chr 2 may influence LBM by regulating body length. Therefore, epistatic interactions as well as single QTL effects play an important role in the regulation of LBM.

Quantitative trait loci that harbor genes regulating muscle size in (MRL/MPJ x SJL/J) F(2) mice.

Abstract. The genetic mechanisms that determine muscle size have not been elucidated, even though it is a key musculoskeletal parameter that reflects muscle strength. In this study, we performed a high-density genome-wide scan using 633 (MRL/MPJ × SJL/J) F2 intercross 7-week-old mice to identify quantitative trait loci (QTL) involved in the determination of muscle size. Significant QTL were identified for muscle size and body length. Muscle size (adjusted by body length) QTL were identified on chromosomes 7, 9, 11, 14 (two QTL) and 17, which together explained 19.2% of phenotypic variance in F2 mice, while body length QTL were located on chromosome 2 (two QTL), 9, 11 and 17 which accounted for 28.3% of phenotypic variance in F2 mice. Three significant epistatic interactions between different QTL positions from muscle size and body length were identified (P <0.01) on chromosomes 2, 9, 14 and 17, which explained 16.1% of the variance in F2 mice.