Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of NF1 copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups.

The population genomics of rhesus macaques (Macaca mulatta) based on whole-genome sequences.

Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primate in biomedical research, have the largest natural geographic distribution of any nonhuman primate, and have been the focus of much evolutionary and behavioral investigation. Consequently, rhesus macaques are one of the most thoroughly studied nonhuman primate species. However, little is known about genome-wide genetic variation in this species. A detailed understanding of extant genomic variation among rhesus macaques has implications for the use of this species as a model for studies of human health and disease, as well as for evolutionary population genomics. Whole-genome sequencing analysis of 133 rhesus macaques revealed more than 43.7 million single-nucleotide variants, including thousands predicted to alter protein sequences, transcript splicing, and transcription factor binding sites. Rhesus macaques exhibit 2.5-fold higher overall nucleotide diversity and slightly elevated putative functional variation compared with humans. This functional variation in macaques provides opportunities for analyses of coding and noncoding variation, and its cellular consequences. Despite modestly higher levels of nonsynonymous variation in the macaques, the estimated distribution of fitness effects and the ratio of nonsynonymous to synonymous variants suggest that purifying selection has had stronger effects in rhesus macaques than in humans. Demographic reconstructions indicate this species has experienced a consistently large but fluctuating population size. Overall, the results presented here provide new insights into the population genomics of nonhuman primates and expand genomic information directly relevant to primate models of human disease.

The effect of dietary fat intake on hepatic gene expression in LG/J AND SM/J mice.

BACKGROUND: The liver plays a major role in regulating metabolic homeostasis and is vital for nutrient metabolism. Identifying the genetic factors regulating these processes could lead to a greater understanding of how liver function responds to a high-fat diet and how that response may influence susceptibilities to obesity and metabolic syndrome. In this study we examine differences in hepatic gene expression between the LG/J and SM/J inbred mouse strains and how gene expression in these strains is affected by high-fat diet. LG/J and SM/J are known to differ in their responses to a high-fat diet for a variety of obesity- and diabetes-related traits, with the SM/J strain exhibiting a stronger phenotypic response to diet. RESULTS: Dietary intake had a significant effect on gene expression in both inbred lines. Genes up-regulated by a high-fat diet were involved in biological processes such as lipid and carbohydrate metabolism; protein and amino acid metabolic processes were down regulated on a high-fat diet. A total of 259 unique transcripts exhibited a significant diet-by-strain interaction. These genes tended to be associated with immune function. In addition, genes involved in biochemical processes related to non-alcoholic fatty liver disease (NAFLD) manifested different responses to diet between the two strains. For most of these genes, SM/J had a stronger response to the high-fat diet than LG/J. CONCLUSIONS: These data show that dietary fat impacts gene expression levels in SM/J relative to LG/J, with SM/J exhibiting a stronger response. This supports previous data showing that SM/J has a stronger phenotypic response to high-fat diet. Based upon these findings, we suggest that SM/J and its cross with the LG/J strain provide a good model for examining non-alcoholic fatty liver disease and its role in metabolic syndrome.

Characterization of single-nucleotide variation in Indian-origin rhesus macaques (Macaca mulatta).

BACKGROUND: Rhesus macaques are the most widely utilized nonhuman primate model in biomedical research. Previous efforts have validated fewer than 900 single nucleotide polymorphisms (SNPs) in this species, which limits opportunities for genetic studies related to health and disease. Extensive information about SNPs and other genetic variation in rhesus macaques would facilitate valuable genetic analyses, as well as provide markers for genome-wide linkage analysis and the genetic management of captive breeding colonies. RESULTS: We used the available rhesus macaque draft genome sequence, new sequence data from unrelated individuals and existing published sequence data to create a genome-wide SNP resource for Indian-origin rhesus monkeys. The original reference animal and two additional Indian-origin individuals were resequenced to low coverage using SOLiD™ sequencing. We then used three strategies to validate SNPs: comparison of potential SNPs found in the same individual using two different sequencing chemistries, and comparison of potential SNPs in different individuals identified with either the same or different sequencing chemistries. Our approach validated approximately 3 million SNPs distributed across the genome. Preliminary analysis of SNP annotations suggests that a substantial number of these macaque SNPs may have functional effects. More than 700 non-synonymous SNPs were scored by Polyphen-2 as either possibly or probably damaging to protein function and these variants now constitute potential models for studying functional genetic variation relevant to human physiology and disease. CONCLUSIONS: Resequencing of a small number of animals identified greater than 3 million SNPs. This provides a significant new information resource for rhesus macaques, an important research animal. The data also suggests that overall genetic variation is high in this species. We identified many potentially damaging non-synonymous coding SNPs, providing new opportunities to identify rhesus models for human disease.

Evolution of pleiotropy: epistatic interaction pattern supports a mechanistic model underlying variation in genotype-phenotype map.

The genotype-phenotype (GP) map consists of developmental and physiological mechanisms mapping genetic onto phenotypic variation. It determines the distribution of heritable phenotypic variance on which selection can act. Comparative studies of morphology as well as of gene regulatory networks show that the GP map itself evolves, yet little is known about the actual evolutionary mechanisms involved. The study of such mechanisms requires exploring the variation in GP maps at the population level, which presently is easier to quantify by statistical genetic methods rather than by regulatory network structures. We focus on the evolution of pleiotropy, a major structural aspect of the GP map. Pleiotropic genes affect multiple traits and underlie genetic covariance between traits, often causing evolutionary constraints. Previous quantitative genetic studies have demonstrated population-level variation in pleiotropy in the form of loci, at which genotypes differ in the genetic covariation between traits. This variation can potentially fuel evolution of the GP map under selection and/or drift. Here, we propose a developmental mechanism underlying population genetic variation in covariance and test its predictions. Specifically, the mechanism predicts that the loci identified as responsible for genetic variation in pleiotropy are involved in trait-specific epistatic interactions. We test this prediction for loci affecting allometric relationships between traits in an advanced intercross between inbred mouse strains. The results consistently support the prediction. We further find a high degree of sign epistasis in these interactions, which we interpret as an indication of adaptive gene complexes within the diverged parental lines.

The importance of context to the genetic architecture of diabetes-related traits is revealed in a genome-wide scan of a LG/J × SM/J murine model.

Variations in diabetic phenotypes are caused by complex interactions of genetic effects, environmental factors, and the interplay between the two. We tease apart these complex interactions by examining genome-wide genetic and epigenetic effects on diabetes-related traits among different sex, diet, and sex-by-diet cohorts in a Mus musculus model. We conducted a genome-wide scan for quantitative trait loci that affect serum glucose and insulin levels and response to glucose stress in an F(16) Advanced Intercross Line of the LG/J and SM/J intercross (Wustl:LG,SM-G16). Half of each sibship was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (parent-of-origin imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. We found that different cohorts often have unique genetic effects at the same loci, and that genetic signals can be masked or erroneously assigned to specific cohorts if they are not considered individually. Our data demonstrate that the effects of genes on complex trait variation are highly context-dependent and that the same genomic sequence can affect traits differently depending on an individual's sex and/or dietary environment. Our results have important implications for studies of complex traits in humans.

Diet-dependent genetic and genomic imprinting effects on obesity in mice.

Although the current obesity epidemic is of environmental origin, there is substantial genetic variation in individual response to an obesogenic environment. In this study, we perform a genome-wide scan for quantitative trait loci (QTLs) affecting obesity per se, or an obese response to a high-fat diet in mice from the LG/J by SM/J Advanced Intercross (AI) Line (Wustl:LG,SM-G16). A total of 1,002 animals from 78 F16 full sibships were weaned at 3 weeks of age and half of each litter placed on high- and low-fat diets. Animals remained on the diet until 20 weeks of age when they were necropsied and the weights of the reproductive, kidney, mesenteric, and inguinal fat depots were recorded. Effects on these phenotypes, along with total fat depot weight and carcass weight at necropsy, were mapped across the genome using 1,402 autosomal single-nucleotide polymorphism (SNP) markers. Haplotypes were reconstructed and additive, dominance, and imprinting genotype scores were derived every 1 cM along the F16 map. Analysis was performed using a mixed model with additive, dominance, and imprinting genotype scores, their interactions with sex, diet, and with sex-by-diet as fixed effects and with family and its interaction with sex, diet, and sex-by-diet as random effects. We discovered 95 trait-specific QTLs mapping to 40 locations. Most QTLs had additive effects with dominance and imprinting effects occurring at two-thirds of the loci. Nearly every locus interacted with sex and/or diet in important ways demonstrating that gene effects are primarily context dependent, changing depending on sex and/or diet.

Genetic, epigenetic, and gene-by-diet interaction effects underlie variation in serum lipids in a LG/JxSM/J murine model.

Variation in serum cholesterol, free-fatty acids, and triglycerides is associated with cardiovascular disease (CVD) risk factors. There is great interest in characterizing the underlying genetic architecture of these risk factors, because they vary greatly within and among human populations and between the sexes. We present results of a genome-wide scan for quantitative trait loci (QTL) affecting serum cholesterol, free-fatty acids, and triglycerides in an F(16) advanced intercross line of LG/J and SM/J (Wustl:LG,SM-G16). Half of the population was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. Here we examine genetic, environmental, and genetic-by-environmental interactions of QTL overlapping previously identified loci associated with CVD risk factors, and we add to the serum lipid QTL landscape by identifying new loci.

Calpain-10 is a component of the obesity-related quantitative trait locus Adip1.

We previously mapped Adip1, an obesity quantitative trait locus (QTL), to the central portion of murine chromosome 1 containing the calpain-10 (Capn10) gene. Human studies have associated calpain-10 (CAPN10) variants with type 2 diabetes and various metabolic traits. We performed a quantitative hybrid complementation test (QHCT) to determine whether differences attributed to Adip1 are the result of variant Capn10 alleles in LG/J and SM/J mice. We crossed LG/J and SM/J to wild-type (C57BL/6J) and Capn10 knockout (Capn10(-/-)) mice to form four F(1) hybrid groups: LG/J by wild-type, LG/J by Capn10(-/-), SM/J by wild-type, and SM/J by Capn10(-/-). We performed a two-way ANOVA with the experimental strain, tester strain, and their interaction as the factors. Significant interaction indicates a quantitative failure to complement. We found failure to complement for fat, organ, and body weights, and leptin, female free fatty acid, and triglyceride levels. Capn10(-/-) resulted in heavier weights and higher serum levels in LG/J crosses but not in SM/J crosses. For glucose tolerance and insulin response tests, the Capn10(-/-) allele resulted in lower glucose levels in crosses with SM/J but had no effect in the LG/J crosses. Differences between the LG/J and SM/J Capn10 alleles are the likely source of some of the QTL effects mapped to Adip1 in the LG/J-by-SM/J cross. Capn10 plays an important role in regulating obesity and diabetes in mice.

Fine-mapping of obesity-related quantitative trait loci in an F9/10 advanced intercross line.

Obesity develops in response to a combination of environmental effects and multiple genes of small effect. Although there has been significant progress in characterizing genes in many pathways contributing to metabolic disease, knowledge about the relationships of these genes to each other and their joint effects upon obesity lags behind. The LG,SM advanced intercross line (AIL) model of obesity has been used to characterize over 70 loci involved in fatpad weight, body weight, and organ weights. Each of these quantitative trait loci (QTLs) encompasses large regions of the genome and require fine-mapping to isolate causative sequence changes and possible mechanisms of action as indicated by the genetic architecture. In this study we fine-map QTLs first identified in the F(2) and F(2/3) populations in the combined F(9/10) advanced intercross generations. We observed significantly narrowed QTL confidence regions, identified many single QTL that resolve into multiple QTL peaks, and identified new QTLs that may have been previously masked due to opposite gene effects at closely linked loci. We also present further characterization of the pleiotropic and epistatic interactions underlying these obesity-related traits.

Replication of long-bone length QTL in the F9-F10 LG,SM advanced intercross.

Quantitative trait locus (QTL) mapping techniques are frequently used to identify genomic regions associated with variation in phenotypes of interest. However, the F(2) intercross and congenic strain populations usually employed have limited genetic resolution resulting in relatively large confidence intervals that greatly inhibit functional confirmation of statistical results. Here we use the increased resolution of the combined F(9) and F(10) generations (n = 1455) of the LG,SM advanced intercross to fine-map previously identified QTL associated with the lengths of the humerus, ulna, femur, and tibia. We detected 81 QTL affecting long-bone lengths. Of these, 49 were previously identified in the combined F(2)-F(3) population of this intercross, while 32 represent novel contributors to trait variance. Pleiotropy analysis suggests that most QTL affect three to four long bones or serially homologous limb segments. We also identified 72 epistatic interactions involving 38 QTL and 88 novel regions. This analysis shows that using later generations of an advanced intercross greatly facilitates fine-mapping of confidence intervals, resolving three F(2)-F(3) QTL into multiple linked loci and narrowing confidence intervals of other loci, as well as allowing identification of additional QTL. Further characterization of the biological bases of these QTL will help provide a better understanding of the genetics of small variations in long-bone length.

Genetic architecture of adiposity and organ weight using combined generation QTL analysis.

We present here a detailed study of the genetic contributions to adult body size and adiposity in the LG,SM advanced intercross line (AIL), an obesity model. This study represents a first step in fine-mapping obesity quantitative trait loci (QTLs) in an AIL. QTLs for adiposity in this model were previously isolated to chromosomes 1, 6, 7, 8, 9, 12, 13, and 18. This study focuses on heritable contributions and the genetic architecture of fatpad and organ weights. We analyzed both the F(2) and F(3) generations of the LG,SM AIL population single-nucleotide polymorphism (SNP) genotyped with a marker density of approximately 4 cM. We replicate 88% of the previously identified obesity QTLs and identify 13 new obesity QTLs. Nearly half of the single-trait QTLs were sex-specific. Several broad QTL regions were resolved into multiple, narrower peaks. The 113 single-trait QTLs for organs and body weight clustered into 27 pleiotropic loci. A large number of epistatic interactions are described which begin to elucidate potential interacting molecular networks. We present a relatively rapid means to obtain fine-mapping details from AILs using dense marker maps and consecutive generations. Analysis of the complex genetic architecture underlying fatpad and organ weights in this model may eventually help to elucidate not only heritable contributions to obesity but also common gene sets for obesity and its comorbidities.

Identification of quantitative trait loci affecting murine long bone length in a two-generation intercross of LG/J and SM/J Mice.

INTRODUCTION: Study of mutations with large phenotypic effects has allowed the identification of key players in skeletal development. However, the molecular nature of variation in large, phenotypically normal populations tends to be characterized by smaller phenotypic effects that remain undefined. MATERIALS AND METHODS: We use interval mapping and quantitative trait locus (QTL) mapping techniques in the combined F2-F3 populations (n = 2111) of an LG/J x SM/J mouse intercross to detect QTLs associated with the lengths of the humerus, ulna, femur, and tibia. RESULTS: Seventy individual trait QTLs affecting long bone lengths were detected, with several chromosomes harboring multiple QTLs. The genetic architecture suggests mainly small, additive effects on long bone length, with roughly one third of the QTLs displaying dominance. Sex interactions were common, and four sex-specific QTLs were observed. Pleiotropy could not be rejected for most of the QTLs identified. Thirty-one epistatic interactions were detected, almost all affecting regions including or immediately adjacent to QTLs. CONCLUSIONS: A complex regulatory network with many gene interactions modulates bone growth, possibly with integrated skeletal modules that allow fine-tuning of developmental processes present. Candidate genes in the QTL CIs include many genes known to affect endochondral bone growth and genes that have not yet been associated with bone growth or body size but have a strong potential to influence these traits.

Mutant analysis of the Shal (Kv4) voltage-gated fast transient K+ channel in Caenorhabditis elegans.

Shal (Kv4) alpha-subunits are the most conserved among the family of voltage-gated potassium channels. Previous work has shown that the Shal potassium channel subfamily underlies the predominant fast transient outward current in Drosophila neurons (Tsunoda, S., and Salkoff, L. (1995) J. Neurosci. 15, 1741-1754) and the fast transient outward current in mouse heart muscle (Guo, W., Jung, W. E., Marionneau, C., Aimond, F., Xu, H., Yamada, K. A., Schwarz, T. L., Demolombe, S., and Nerbonne, J. M. (2005) Circ. Res. 97, 1342-1350). We show that Shal channels also play a role as the predominant transient outward current in Caenorhabditis elegans muscle. Green fluorescent protein promoter experiments also revealed SHL-1 expression in a subset of neurons as well as in C. elegans body wall muscle and in male-specific diagonal muscles. The shl-1 (ok1168) null mutant removed all fast transient outward current from muscle cells. SHL-1 currents strongly resembled Shal currents in other species except that they were active in a more depolarized voltage range. We also determined that the remaining delayed-rectifier current in cultured myocytes was carried by the Shaker ortholog SHK-1. In shl-1 (ok1168) mutants there was a significant compensatory increase in the SHK-1 current. Male shl-1 (ok1168) animals exhibited reduced mating efficiency resulting from an apparent difficulty in locating the hermaphrodite vulva. SHL-1 channels are apparently important in fine-tuning complex behaviors, such as mating, that play a crucial role in the survival and propagation of the species.