Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices

The diversity of bibliometric indices today poses the challenge of exploiting the relationships among them. Our research uncovers the best core set of relevant indices for predicting other bibliometric indices. An added difficulty is to select the role of each variable, that is, which bibliometric indices are predictive variables and which are response variables. This results in a novel multioutput regression problem where the role of each variable (predictor or response) is unknown beforehand. We use Gaussian Bayesian networks to solve the this problem and discover multivariate relationships among bibliometric indices. These networks are learnt by a genetic algorithm that looks for the optimal models that best predict bibliometric data. Results show that the optimal induced Gaussian Bayesian networks corroborate previous relationships between several indices, but also suggest new, previously unreported interactions. An extended analysis of the best model illustrates that a set of 12 bibliometric indices can be accurately predicted using only a smaller predictive core subset composed of citations, g-index, q2-index, and hr-index. This research is performed using bibliometric data on Spanish full professors associated with the computer science area.

A genetic record of population isolation in pocket gophers during Holocene climatic change

A long-standing question in Quaternary paleontology is whether climate-induced, population-level phenotypic change is a result of large-scale migration or evolution in isolation. To directly measure genetic variation through time, ancient DNA and morphologic variation was measured over 2,400 years in a Holocene sequence of pocket gophers (Thomomys talpoides) from Lamar Cave, Yellowstone National Park, Wyoming. Ancient specimens and modern samples collected near Lamar Cave share mitochondrial cytochrome b sequences that are absent from adjacent localities, suggesting that the population was isolated for the entire period. In contrast, diastemal length, a morphologic character correlated with body size and nutritional level, changed predictably in response to climatic change. Our results demonstrate that small mammal populations can experience the long-term isolation assumed by many theoretical models of microevolutionary change.

Effect of genetic background on the contribution of New Zealand Black loci to autoimmune lupus nephritis

Autoimmune diseases such as systemic lupus erythematosus are complex genetic traits with contributions from major histocompatibility complex (MHC) genes and multiple unknown non-MHC genes. Studies of animal models of lupus have provided important insight into the immunopathogenesis of disease, and genetic analyses of these models overcome certain obstacles encountered when studying human patients. Genome-wide scans of different genetic crosses have been used to map several disease-linked loci in New Zealand hybrid mice. Although some consensus exists among studies mapping the New Zealand Black (NZB) and New Zealand White (NZW) loci that contribute to lupus-like disease, considerable variability is also apparent. A variable in these studies is the genetic background of the non-autoimmune strain, which could influence genetic contributions from the affected strain. A direct examination of this question was undertaken in the present study by mapping NZB nephritis-linked loci in backcrosses involving different non-autoimmune backgrounds. In a backcross with MHC-congenic C57BL/6J mice, H2z appeared to be the strongest genetic determinant of severe lupus nephritis, whereas in a backcross with congenic BALB/cJ mice, H2z showed no influence on disease expression. NZB loci on chromosomes 1, 4, 11, and 14 appeared to segregate with disease in the BALB/cJ cross, but only the influence of the chromosome 1 locus spanned both crosses and showed linkage with disease when all mice were considered. Thus, the results indicate that contributions from disease-susceptibility loci, including MHC, may vary markedly depending on the non-autoimmune strain used in a backcross analysis. These studies provide insight into variables that affect genetic heterogeneity and add an important dimension of complexity for linkage analyses of human autoimmune disease.

Web-based access to mouse models of human cancers: the Mouse Tumor Biology (MTB) Database

The Mouse Tumor Biology (MTB) Database serves as a curated, integrated resource for information about tumor genetics and pathology in genetically defined strains of mice (i.e., inbred, transgenic and targeted mutation strains). Sources of information for the database include the published scientific literature and direct data submissions by the scientific community. Researchers access MTB using Web-based query forms and can use the database to answer such questions as ‘What tumors have been reported in transgenic mice created on a C57BL/6J background?’, ‘What tumors in mice are associated with mutations in the Trp53 gene?’ and ‘What pathology images are available for tumors of the mammary gland regardless of genetic background?’. MTB has been available on the Web since 1998 from the Mouse Genome Informatics web site (http://www.informatics.jax.org). We have recently implemented a number of enhancements to MTB including new query options, redesigned query forms and results pages for pathology and genetic data, and the addition of an electronic data submission and annotation tool for pathology data.

A genetic model provides evidence that the receptor for atrial natriuretic peptide (guanylyl cyclase-A) inhibits cardiac ventricular myocyte hypertrophy

Guanylyl cyclase-A (NPR-A; GC-A) is the major and possibly the only receptor for atrial natriuretic peptide (ANP) or B-type natriuretic peptide. Although mice deficient in GC-A display an elevated blood pressure, the resultant cardiac hypertrophy is much greater than in other mouse models of hypertension. Here we overproduce GC-A in the cardiac myocytes of wild-type or GC-A null animals. Introduction of the GC-A transgene did not alter blood pressure or heart rate as a function of genotype. Cardiac myocyte size was larger (approximately 20%) in GC-A null than in wild-type animals. However, introduction of the GC-A transgene reduced cardiac myocyte size in both wild-type and null mice. Coincident with the reduction in myocyte size, both ANP mRNA and ANP content were significantly reduced by overexpression of GC-A, and this reduction was independent of genotype. This genetic model, therefore, separates a regulation of cardiac myocyte size by blood pressure from local regulation by a GC-mediated pathway.

Genetic evidence for different male and female roles during cultural transitions in the British Isles

Human history is punctuated by periods of rapid cultural change. Although archeologists have developed a range of models to describe cultural transitions, in most real examples we do not know whether the processes involved the movement of people or the movement of culture only. With a series of relatively well defined cultural transitions, the British Isles present an ideal opportunity to assess the demographic context of cultural change. Important transitions after the first Paleolithic settlements include the Neolithic, the development of Iron Age cultures, and various historical invasions from continental Europe. Here we show that patterns of Y-chromosome variation indicate that the Neolithic and Iron Age transitions in the British Isles occurred without large-scale male movements. The more recent invasions from Scandinavia, on the other hand, appear to have left a significant paternal genetic legacy. In contrast, patterns of mtDNA and X-chromosome variation indicate that one or more of these pre-Anglo-Saxon cultural revolutions had a major effect on the maternal genetic heritage of the British Isles.

The genetic mediation of individual differences in sensitivity to pain and its inhibition

The underlying bases of the considerable interindividual variability in pain-related traits are starting to be revealed. Although the relative importance of genes versus experience in human pain perception remains unclear, rodent populations display large and heritable differences in both nociceptive and analgesic sensitivity. The identification and characterization of particularly divergent populations provides a powerful initial step in the genetic analysis of pain, because these models can be exploited to identify genes contributing to the behavior-level variability. Ultimately, DNA sequence differences representing the differential alleles at pain-relevant genes can be identified. Thus, by using a combination of “top-down” and “bottom-up” strategies, we are now able to genetically dissect even complex biological traits like pain. The present review summarizes the current progress toward these ends in both humans and rodents.

The role of genetic and genomic attributes in the success of polyploids

In 1950, G. Ledyard Stebbins devoted two chapters of his book Variation and Evolution in Plants (Columbia Univ. Press, New York) to polyploidy, one on occurrence and nature and one on distribution and significance. Fifty years later, many of the questions Stebbins posed have not been answered, and many new questions have arisen. In this paper, we review some of the genetic attributes of polyploids that have been suggested to account for the tremendous success of polyploid plants. Based on a limited number of studies, we conclude: (i) Polyploids, both individuals and populations, generally maintain higher levels of heterozygosity than do their diploid progenitors. (ii) Polyploids exhibit less inbreeding depression than do their diploid parents and can therefore tolerate higher levels of selfing; polyploid ferns indeed have higher levels of selfing than do their diploid parents, but polyploid angiosperms do not differ in outcrossing rates from their diploid parents. (iii) Most polyploid species are polyphyletic, having formed recurrently from genetically different diploid parents. This mode of formation incorporates genetic diversity from multiple progenitor populations into the polyploid “species”; thus, genetic diversity in polyploid species is much higher than expected by models of polyploid formation involving a single origin. (iv) Genome rearrangement may be a common attribute of polyploids, based on evidence from genome in situ hybridization (GISH), restriction fragment length polymorphism (RFLP) analysis, and chromosome mapping. (v) Several groups of plants may be ancient polyploids, with large regions of homologous DNA. These duplicated genes and genomes can undergo divergent evolution and evolve new functions. These genetic and genomic attributes of polyploids may have both biochemical and ecological benefits that contribute to the success of polyploids in nature.

Genetic drift and within-host metapopulation dynamics of HIV-1 infection

Most HIV replication occurs in solid lymphoid tissue, which has prominent architecture at the histological level, which separates groups of productively infected CD4+ cells. Nevertheless, current population models of HIV assume panmixis within lymphoid tissue. We present a simple “metapopulation” model of HIV replication, where the population of infected cells is comprised of a large number of small populations, each of which is established by a few founder viruses and undergoes turnover. To test this model, we analyzed viral genetic variation of infected cell subpopulations within the spleen and demonstrated the action of founder effects as well as significant variation in the extent of genetic differentiation between subpopulations among patients. The combination of founder effects and subpopulation turnover can result in an effective population size much lower than the actual population size and may contribute to the importance of genetic drift in HIV evolution despite a large number of infected cells.

Analysis of genetic instability during mammary tumor progression using a novel selection-based assay for in vivo mutations in a bacteriophage lambda transgene target.

Genetic instability is thought to be responsible for the numerous genotypic changes that occur during neoplastic transformation and metastatic progression. To explore the role of genetic instability at the level of point mutations during mammary tumor development and malignant progression, we combined transgenic mouse models of mutagenesis detection and oncogenesis. Bitransgenic mice were generated that carried both a bacteriophage lambda transgene to assay mutagenesis and a polyomavirus middle T oncogene, mammary gland-targeted expression of which led to metastatic mammary adenocarcinomas. We developed a novel assay for the detection of mutations in the lambda transgene that selects for phage containing forward mutations only in the lambda cII gene, using an hfl- bacterial host. In addition to the relative ease of direct selection, the sensitivity of this assay for both spontaneous and chemically induced mutations was comparable to the widely used mutational target gene, lambda lacI, making the cII assay an attractive alternative for mutant phage recovery for any lambda-based mouse mutagenesis assay system. The frequencies of lambda cII- mutants were not significantly different in normal mammary epithelium, primary mammary adenocarcinomas, and pulmonary metastases. The cII mutational spectra in these tissues consisted mostly of G/C-->A/T transitions, a large fraction of which occurred at CpG dinucleotides. These data suggest that, in this middle T oncogene model of mammary tumor progression, a significant increase in mutagenesis is not required for tumor development or for metastatic progression.

Gene targeting approaches to complex genetic diseases: atherosclerosis and essential hypertension.

Gene targeting allows precise, predetermined changes to be made in a chosen gene in the mouse genome. To date, targeting has been used most often for generation of animals completely lacking the product of a gene of interest. The resulting "knockout" mice have confirmed some hypotheses, have upset others, but have rarely been uninformative. Models of several human genetic diseases have been produced by targeting--including Gaucher disease, cystic fibrosis, and the fragile X syndrome. These diseases are primarily determined by defects in single genes, and their modes of inheritance are well understood. When the disease under study has a complex etiology with multiple genetic and environmental components, the generation of animal models becomes more difficult but no less valuable. The problems associated with dissecting out the individual genetic factors also increases substantially and the distinction between causation and correlation is often difficult. To prove causation in a complex system requires rigorous adherence to the principle that the experiments must allow detection of the effects of changing only a single variable at one time. Gene targeting experiments, when properly designed, can test the effects of a precise genetic change completely free from the effects of differences in any other genes (linked or unlinked to the test gene). They therefore allow proofs of causation.

Three-dimensional inverse modelling of magnetic anomaly sources based on a genetic algorithm.

We present a modelling method to estimate the 3-D geometry and location of homogeneously magnetized sources from magnetic anomaly data. As input information, the procedure needs the parameters defining the magnetization vector (intensity, inclination and declination) and the Earth's magnetic field direction. When these two vectors are expected to be different in direction, we propose to estimate the magnetization direction from the magnetic map. Then, using this information, we apply an inversion approach based on a genetic algorithm which finds the geometry of the sources by seeking the optimum solution from an initial population of models in successive iterations through an evolutionary process. The evolution consists of three genetic operators (selection, crossover and mutation), which act on each generation, and a smoothing operator, which looks for the best fit to the observed data and a solution consisting of plausible compact sources. The method allows the use of non-gridded, non-planar and inaccurate anomaly data and non-regular subsurface partitions. In addition, neither constraints for the depth to the top of the sources nor an initial model are necessary, although previous models can be incorporated into the process. We show the results of a test using two complex synthetic anomalies to demonstrate the efficiency of our inversion method. The application to real data is illustrated with aeromagnetic data of the volcanic island of Gran Canaria (Canary Islands).

Molecular Characterization of Three Canine Models of Human Rare Bone Diseases: Caffey, van den Ende-Gupta, and Raine Syndromes.

One to two percent of all children are born with a developmental disorder requiring pediatric hospital admissions. For many such syndromes, the molecular pathogenesis remains poorly characterized. Parallel developmental disorders in other species could provide complementary models for human rare diseases by uncovering new candidate genes, improving the understanding of the molecular mechanisms and opening possibilities for therapeutic trials. We performed various experiments, e.g. combined genome-wide association and next generation sequencing, to investigate the clinico-pathological features and genetic causes of three developmental syndromes in dogs, including craniomandibular osteopathy (CMO), a previously undescribed skeletal syndrome, and dental hypomineralization, for which we identified pathogenic variants in the canine SLC37A2 (truncating splicing enhancer variant), SCARF2 (truncating 2-bp deletion) and FAM20C (missense variant) genes, respectively. CMO is a clinical equivalent to an infantile cortical hyperostosis (Caffey disease), for which SLC37A2 is a new candidate gene. SLC37A2 is a poorly characterized member of a glucose-phosphate transporter family without previous disease associations. It is expressed in many tissues, including cells of the macrophage lineage, e.g. osteoclasts, and suggests a disease mechanism, in which an impaired glucose homeostasis in osteoclasts compromises their function in the developing bone, leading to hyperostosis. Mutations in SCARF2 and FAM20C have been associated with the human van den Ende-Gupta and Raine syndromes that include numerous features similar to the affected dogs. Given the growing interest in the molecular characterization and treatment of human rare diseases, our study presents three novel physiologically relevant models for further research and therapy approaches, while providing the molecular identity for the canine conditions.

Contribution of Genetic Background and Clinical Risk Factors to Low-Trauma Fractures in Human Immunodeficiency Virus (HIV)-Positive Persons: The Swiss HIV Cohort Study.

Background.  The impact of human genetic background on low-trauma fracture (LTF) risk has not been evaluated in the context of human immunodeficiency virus (HIV) and clinical LTF risk factors. Methods.  In the general population, 6 common single-nucleotide polymorphisms (SNPs) associate with LTF through genome-wide association study. Using genome-wide SNP arrays and imputation, we genotyped these SNPs in HIV-positive, white Swiss HIV Cohort Study participants. We included 103 individuals with a first, physician-validated LTF and 206 controls matched on gender, whose duration of observation and whose antiretroviral therapy start dates were similar using incidence density sampling. Analyses of nongenetic LTF risk factors were based on 158 cases and 788 controls. Results.  A genetic risk score built from the 6 LTF-associated SNPs did not associate with LTF risk, in both models including and not including parental hip fracture history. The contribution of clinical LTF risk factors was limited in our dataset. Conclusions.  Genetic LTF markers with a modest effect size in the general population do not improve fracture prediction in persons with HIV, in whom clinical LTF risk factors are prevalent in both cases and controls.

Learning Models of Gene Expression from Synthetic DNA Sequences

Thesis (Ph.D.)--University of Washington, 2016-06