Functional genomics complements quantitative genetics in identifying disease-gene associations

An ultimate goal of genetic research is to understand the connection between genotype and phenotype in order to improve the diagnosis and treatment of diseases. The quantitative genetics field has developed a suite of statistical methods to associate genetic loci with diseases and phenotypes, including quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, each of these approaches have technical and biological shortcomings. For example, the amount of heritable variation explained by GWAS is often surprisingly small and the resolution of many QTL linkage mapping studies is poor. The predictive power and interpretation of QTL and GWAS results are consequently limited. In this study, we propose a complementary approach to quantitative genetics by interrogating the vast amount of high-throughput genomic data in model organisms to functionally associate genes with phenotypes and diseases. Our algorithm combines the genome-wide functional relationship network for the laboratory mouse and a state-of-the-art machine learning method. We demonstrate the superior accuracy of this algorithm through predicting genes associated with each of 1157 diverse phenotype ontology terms. Comparison between our prediction results and a meta-analysis of quantitative genetic studies reveals both overlapping candidates and distinct, accurate predictions uniquely identified by our approach. Focusing on bone mineral density (BMD), a phenotype related to osteoporotic fracture, we experimentally validated two of our novel predictions (not observed in any previous GWAS/QTL studies) and found significant bone density defects for both Timp2 and Abcg8 deficient mice. Our results suggest that the integration of functional genomics data into networks, which itself is informative of protein function and interactions, can successfully be utilized as a complementary approach to quantitative genetics to predict disease risks. All supplementary material is available at http://cbfg.jax.org/phenotype.     

Biochemical genetics of phosphohydrolase polymorphism in Culex pipiens complex.

1. Single 4th-instar larvae were used in the investigation of alkaline phosphohydrolase (APH) variability in Culex pipiens quinequefasciatus. The genetic basis of isozyme variability was determined from genetic crosses performed with isogenic and hybrid strains of mosquitoes. 2. Isozyme electromorphs presented four enzyme activity zones, three monomorphic and one polymorphic, correspondent with four APH gene loci (aph1, aph2, aph3 and aph4). 3. All isozymes migrated anodically, with aph4 isozymes migrating most rapidly. 4. Enzyme polymorphism was evident only at aph4 locus, with three allozymes present. 5. aph4 allozymes are conditioned by multiple, co-dominant alleles transmitted in a Mendelian manner. 6. Differential frequencies and selection for aph4 alleles and genotypes are suggested by data from genetic crosses.     

Difference in the response of two hybrid stocks of mice to X-ray induction of chromosome aberrations in spermatogonial stem cells

Ionizing radiation induces balanced reciprocal translocations in spermatogonial stem cells of mice. From cells carrying these rearrangements, which can be scored cytologically in the diakinesis-metaphase I stage, balanced normal, balanced translocated and unbalanced (duplication/deficiency) sperm can be produced. The relationship between expected (calculated from cytological data) and observed frequencies of embryonic lethality (presumably as a result of unbalanced sperm fertilizing the egg) following exposure of spermatogonial stem cells to X-rays was studied in two hybrid stocks. A marked difference in the incidence of induced embryonic lethality was found between the two stocks. Similarly, a difference in the cytological frequencies of translocations was also found, although smaller than that observed for embryonic lethality. Thus, it appears that the difference between the two stocks in the frequencies of embryonic lethality may be attributable both to processes occurring prior to metaphase I and to a difference in the rate of transmission of unbalanced chromosome constitutions.     

Receptors for luteinizing hormone and follicle-stimulating hormone in largest follicles of postpartum beef cows

Follicles collected from cows destined to enter relatively normal or short luteal phases if induced to ovulate were compared for numbers of receptors for luteinizing hormone (LH) in granulosal and thecal cells and for follicle-stimulating hormone (FSH) in granulosal cells. Eleven suckled beef cows received ear implants of 6 mg norgestomet for 9 days (expected normal luteal phase) and 11 served as controls (expected short luteal phase). At 48 h after implants were removed (average 34 days postpartum), the ovary containing the largest follicle was identified by transrectal ultrasound and removed. The largest follicle was dissected free of surrounding ovarian stroma and frozen in liquid nitrogen. Thecal and granulosal cells were isolated, and numbers of receptors for LH and FSH in granulosal cells and for LH in thecal cells were quantified. Concentrations of estradiol were measured in follicular fluid. Both granulosal and thecal cells from norgestomet-treated cows had greater numbers of receptors for LH than did those from control cows (p less than 0.01). Numbers of receptors for FSH in granulosal cells did not differ between treated and control cows. Follicles from norgestomet-treated cows were heavier (p less than 0.01) than follicles from control cows, mostly due to greater amounts of follicular fluid (p less than 0.01). Concentrations of estradiol were higher in follicular fluid from the treated cows (p less than 0.05). It is suggested that increases in numbers of follicular receptors for LH and secretion of estradiol are integral components of a sequence of events by which norgestomet prepares follicles to become fully functional corpora lutea.     

An autonomic routing framework for sensor networks

Current routing services for sensor networks are often designed for specific applications and network conditions, thus have difficulty in adapting to application and network dynamics. This paper proposes an autonomic framework to promote the adaptivity of routing services in sensor networks. The key idea of this framework is to maintain some feature functions that are decoupled from originally-integrated routing services. This separation enables significant service changes to be done by only tuning these functions. Measures including parameterization are taken to save the energy for changing these functions. Further, this framework includes a monitoring module to support a policy-based collaborative adaptation. This paper shows an example autonomic routing service conforming to this framework. Some of this work was done while the author was at ISI     

Quantitative Detection of Trace Explosive Vapors by Programmed Temperature Desorption Gas Chromatography-Electron Capture Detector

The direct liquid deposition of solution standards onto sorbent-filled thermal desorption tubes is used for the quantitative analysis of trace explosive vapor samples. The direct liquid deposition method yields a higher fidelity between the analysis of vapor samples and the analysis of solution standards than using separate injection methods for vapors and solutions, i.e., samples collected on vapor collection tubes and standards prepared in solution vials. Additionally, the method can account for instrumentation losses, which makes it ideal for minimizing variability and quantitative trace chemical detection. Gas chromatography with an electron capture detector is an instrumentation configuration sensitive to nitro-energetics, such as TNT and RDX, due to their relatively high electron affinity. However, vapor quantitation of these compounds is difficult without viable vapor standards. Thus, we eliminate the requirement for vapor standards by combining the sensitivity of the instrumentation with a direct liquid deposition protocol to analyze trace explosive vapor samples.