Parameters of bone geometry such as width, length, and cross-sectional area are major determinants of bone strength. Although these traits are highly heritable, few genes influencing bone geometry have been identified. Here, we dissect a major quantitative trait locus (QTL) influencing femur size. This QTL was originally identified in an F2 cross between the C57BL/6J-hg/hg (HG) and CAST/EiJ strains and was referred to as femur length in high growth mice 2 (Feml2). Feml2 was located on chromosome (Chr.) 9 at ∼20 cM. Here, we show that the HG.CAST-(D9Mit249-D9Mit133)/Ucd congenic strain captures Feml2 In an F2 congenic cross, we fine-mapped the location of Feml2 to an ∼6 Mbp region extending from 57.3 to 63.3 Mbp on Chr. 9. We have identified candidates by mining the complete genome sequence of CAST/EiJ and through allele-specific expression (ASE) analysis of growth plates in C57BL/6J × CAST/EiJ F1 hybrids. Interestingly, we also find that the refined location of Feml2 overlaps a cluster of six independent genome-wide associations for human height. This work provides the foundation for the identification of novel genes affecting bone geometry.

Background

High growth (hg) modifier and background independent quantitative trait loci (QTL) affecting growth, adiposity and carcass composition were previously identified on mouse chromosomes (MMU) 1, 2, 5, 8, 9, 11 and 17. To confirm and further characterize each QTL, two panels of speed congenic strains were developed by introgressing CAST/EiJ (CAST) QTL alleles onto either mutant C57Bl/6J-hg/hg (HG) or wild type C57Bl/6J (B6) genetic backgrounds.

Results

The first speed congenic panel was developed by introgressing four overlapping donor regions spanning MMU2 in its entirety onto both HG and B6 backgrounds, for a total of eight strains. Phenotypic characterization of the MMU2 panel confirmed the segregation of multiple growth and obesity QTL and strongly suggested that a subset of these loci modify the effects of the hg deletion. The second panel consisted of individual donor regions on an HG background for each QTL on MMU1, 5, 8, 9, 11 and 17. Of the six developed strains, five were successfully characterized and displayed significant differences in growth and/or obesity as compared to controls. All five displayed phenotypes similar to those originally attributed to each QTL, however, novel phenotypes were unmasked in several of the strains including sex-specific effects.

Conclusion

The speed congenic strains developed herein constitute an invaluable genomic resource and provide the foundation to identify the specific nature of genetic variation influencing growth and obesity.

Most quantitative trait loci (QTL) studies fail to account for the effect that the maternal genotype may have on an individual’s phenotypes, even though maternal effect QTL have been shown to account for considerable variation in growth and obesity traits in mouse models. Moreover, the fetal programming theory suggests that maternal effects influence an offspring’s adult fitness, although the genetic nature of fetal programming remains unclear. Within this context, our study focused on mapping genomic regions associated with maternal effect QTL by analyzing the phenotypes of chromosomes 2 and 7 subcongenic mice from genetically distinct dams. We analyzed 12 chromosome 2 subcongenic strains that spanned from 70 to 180 Mb with CAST/EiJ donor regions on the background of C57BL/6 J, and 14 chromosome 7 subcongenic strains that spanned from 81 to 111 Mb with BALB/cByJ donor regions on C57BL/6ByJ background. Maternal QTL analyses were performed on the basis of overlapping donor regions between subcongenic strains. We identified several highly significant (P < 5 × 10−4) maternal QTL influencing total body weight, organ weight, and fat pad weights in both sets of subcongenics. These QTL accounted for 1.9-11.7% of the phenotypic variance for growth and obesity and greatly narrowed the genomic regions associated with the maternal genetic effects. These maternal effect QTL controlled phenotypic traits in adult mice, suggesting that maternal influences at early stages of development may permanently affect offspring performance. Identification of maternal effects in our survey of two sets of subcongenic strains, representing approximately 5% of the mouse genome, supports the hypothesis that maternal effects represent significant sources of genetic variation that are largely ignored in genetic studies.

Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL). However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD) regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL) showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP). Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes that were not tested. Together, our results explain the tendency to report QTL candidates as differentially expressed and indicate that the utility of the QTL/microarray as currently implemented is limited. Alternatives are proposed that make use of microarray data from multiple experiments to overcome the outlined limitations.

One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.

Background

Mouse chromosome 2 is linked to growth and body fat phenotypes in many mouse crosses. With the goal to identify the underlying genes regulating growth and body fat on mouse chromosome 2, we developed five overlapping subcongenic strains that contained CAST/EiJ donor regions in a C57BL/6J (hg/hg) background (hg is a spontaneous deletion of 500 Kb on mouse chromosome 10). To fine map QTL on distal mouse chromosome 2 a total of 1,712 F2 mice from the five subcongenic strains, plus 278 F2 mice from the HG2D founder congenic strain were phenotyped and analyzed. Interval mapping (IM) and composite IM (CIM) were performed on body weight and body fat traits on a combination of SNP and microsatellite markers, which generated a high-density genotyping panel.

Results

Phenotypic analysis and interval mapping of total fat mass identified two QTL on distal mouse chromosome 2. One QTL between 150 and 161 Mb, Fatq2a, and the second between 173.3 and 175.6 Mb, Fatq2b. The two QTL reside in different congenic strains with significant total fat differences between homozygous cast/cast and b6/b6 littermates. Both of these QTL were previously identified only as a single QTL affecting body fat, Fatq2. Furthermore, through a novel approach referred here as replicated CIM, Fatq2b was mapped to the Gnas imprinted locus.

Conclusions

The integration of subcongenic strains, high-density genotyping, and CIM succesfully partitioned two previously linked QTL 20 Mb apart, and the strongest QTL, Fatq2b, was fine mapped to a ~2.3 Mb region interval encompassing the Gnas imprinted locus.

Background

The identification of novel genes is critical to understanding the molecular basis of body weight. Towards this goal, we have identified secretogranin V (Scg5; also referred to as Sgne1), as a candidate gene for growth traits.

Results

Through a combination of DNA microarray analysis and quantitative PCR we identified a strong expression quantitative trait locus (eQTL) regulating Scg5 expression in two mouse chromosome 2 congenic strains and three additional F2 intercrosses. More importantly, the eQTL was coincident with a body weight QTL in congenic mice and Scg5 expression was negatively correlated with body weight in two of the F2 intercrosses. Analysis of haplotype blocks and genomic sequencing of Scg5 in high (C3H/HeJ, DBA/2J, BALB/cByJ, CAST/EiJ) and low (C57BL/6J) expressing strains revealed mutations unique to C57BL/6J and possibly responsible for the difference in mRNA abundance. To evaluate the functional consequence of Scg5 overexpression we measured the pituitary levels of 7B2 protein and PCSK2 activity and found both to be increased. In spite of this increase, the level of pituitary alpha-MSH, a PCSK2 processing product, was unaltered.

Conclusion

Together, these data support a role for Scg5 in the modulation of body weight.

Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.

The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development, growth, and maintenance. Over the past decade, many of the signaling cascades that regulate this lineage have been elucidated; however, little is known of the networks that coordinate, modulate, and transmit these signals. Here, we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel (HMDP) inbred strains. Of the 21 modules that comprised the bone network, module 9 (M9) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells. In addition, the M9 contained many of the key genes that define the osteoblast-lineage, which together suggested that it was specific to this lineage. To use the M9 to identify novel osteoblast genes and highlight its biological relevance, we knocked-down the expression of its two most connected "hub" genes, Maged1 and Pard6g. Their perturbation altered both osteoblast proliferation and differentiation. Furthermore, we demonstrated the mice deficient in Maged1 had decreased bone mineral density (BMD). It was also discovered that a local expression quantitative trait locus (eQTL) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9. We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies. In conclusion, we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells. Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types.

Background

Multiple testing to understand global changes in gene expression based on genetic and epigenetic modifications is evolving. Chorionic villi, obtained for prenatal testing, is limited, but can be used to understand ongoing human pregnancies. However, optimal storage, processing and utilization of CVS for multiple platform testing have not been established.

Results

Leftover CVS samples were flash-frozen or preserved in RNAlater. Modifications to standard isolation kits were performed to isolate quality DNA and RNA from samples as small as 2-5 mg. RNAlater samples had significantly higher RNA yields and quality and were successfully used in microarray and RNA-sequencing (RNA-seq). RNA-seq libraries generated using 200 versus 800-ng RNA showed similar biological coefficients of variation. RNAlater samples had lower DNA yields and quality, which improved by heating the elution buffer to 70 °C. Purification of DNA was not necessary for bisulfite-conversion and genome-wide methylation profiling. CVS cells were propagated and continue to express genes found in freshly isolated chorionic villi.

Conclusions

CVS samples preserved in RNAlater are superior. Our optimized techniques provide specimens for genetic, epigenetic and gene expression studies from a single small sample which can be used to develop diagnostics and treatments using a systems biology approach in the prenatal period. © 2016 John Wiley & Sons, Ltd.