Ecological genetics of Melaleuca quinquenervia (Myrtaceae): Population variation in Florida and its influence on performance of the biological control agent Oxyops vitiosa (Coleoptera: Curculionidae)

Melaleuca quinquenervia (Cav.) Blake (Myrtaceae) was imported into Florida from Australia over a century ago as a landscape plant. A favorable climate and periodic wildfires helped M. quinquenervia thrive; it now occupies about 200,000 hectares in southern Florida. A biological control (i.e., biocontrol) program against M. quinquenervia has been initiated, but not all biocontrol releases are successful. Some scientists have argued that poor biocontrol agent success may relate to genetic differences among populations of invasive weeds. I tested this premise by determining (1) the number and origins of M. quinquenervia introductions into Florida, (2) whether multiple introduction events resulted in the partitioning of Florida's M. quinquenervia populations into discrete biotypes, and (3) whether Oxyops vitiosa, an Australia snout beetle imported to control this weed, might discriminate among putative M. quinquenervia biotypes. Careful scrutiny of early horticultural catalogs and USDA plant introduction records suggested at least six distinct introduction events. Allozyme analyses indicated that the pattern of these introductions, and the subsequent redistribution of progeny, has resulted in geographic structuring of the populations in southern Florida. For example, trees on Florida's Gulf Coast had a greater effective number of alleles and exhibited greater heterozygosity than trees on the Atlantic Coast. Essential oil yields from M. quinquenervia leaves followed a similar trend; Gulf Coast trees yielded nearly twice as much oil as Atlantic Coast trees when both were grown in a common garden. These differences were partially explained by the predominance of a chemical phenotype (chemotype) very rich in the sesquiterpene (E)-nerolidol in M. quinquenervia trees from the Gulf Coast, but rich in a mixture of the monoterpene 1,8-cineole and the sesquiterpene viridiflorol in trees from the Atlantic Coast. Performance of O. vitiosa differed dramatically in laboratory studies depending on the chemotype of the foliage they were fed. Larval survivorship was four-fold greater on the (E)-nerolidol chemotype. Growth was also greater, with adult O. vitiosa gaining nearly 50% more biomass on the (E)-nerolidol plants than on the second chemotype. The results of this study thus confirmed the premise that plant genotype can affect the population dynamics of insects released as weed biocontrols. ^

Reverse Engineering of Modified Genes by Bayesian Network Analysis Defines Molecular Determinants Critical to the Development of Glioblastoma

In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I–IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors.

The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development.

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children's polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development.

Next-Generation Sequencing of Hereditary Hemochromatosis-Related Genes: Novel Likely Pathogenic Variants Found in the Portuguese Population

Hereditary hemochromatosis (HH) is an autosomal recessive disorder characterized by excessive iron absorption resulting in pathologically increased body iron stores. It is typically associated with common HFE gene mutation (p.Cys282Tyr and p.His63Asp). However, in Southern European populations up to one third of HH patients do not carry the risk genotypes. This study aimed to explore the use of next-generation sequencing (NGS) technology to analyse a panel of iron metabolism-related genes (HFE, TFR2, HJV, HAMP, SLC40A1, and FTL) in 87 non-classic HH Portuguese patients. A total of 1241 genetic alterations were detected corresponding to 53 different variants, 13 of which were not described in the available public databases. Among them, five were predicted to be potentially pathogenic: three novel mutations in TFR2 [two missense (p.Leu750Pro and p.Ala777Val) and one intronic splicing mutation (c.967-1G>C)], one missense mutation in HFE (p.Tyr230Cys), and one mutation in the 5'-UTR of HAMP gene (c.-25G>A). The results reported here illustrate the usefulness of NGS for targeted iron metabolism-related gene panels, as a likely cost-effective approach for molecular genetics diagnosis of non-classic HH patients. Simultaneously, it has contributed to the knowledge of the pathophysiology of those rare iron metabolism-related disorders.

Contemporary population genetic structure and phylogeography of pink salmon

Thesis (Master's)--University of Washington, 2016-06

Populations genetics study of the Ammi Genus in the Azores

Dissertação de Mestrado, Biodiversidade e Biotecnologia Vegetal, 6 de Julho de 2016, Universidade dos Açores.

Next-generation sequencing of hereditary hemochromatosis-related genes: novel likely pathogenic variants found in the Portuguese population

Hereditary hemochromatosis (HH) is an autosomal recessive disorder characterized by excessive iron absorption resulting in pathologically increased body iron stores. It is typically associated with common HFE gene mutation (p.Cys282Tyr and p.His63Asp). However, in Southern European populations up to one third of HH patients do not carry the risk genotypes. This study aimed to explore the use of next-generation sequencing (NGS) technology to analyse a panel of iron metabolism-related genes (HFE, TFR2, HJV, HAMP, SLC40A1, and FTL) in 87 non-classic HH Portuguese patients. A total of 1241 genetic alterations were detected corresponding to 53 different variants, 13 of which were not described in the available public databases. Among them, five were predicted to be potentially pathogenic: three novel mutations in TFR2 [two missense (p.Leu750Pro and p.Ala777Val) and one intronic splicing mutation (c.967-1GNC)], one missense mutation in HFE (p.Tyr230Cys), and one mutation in the 5′-UTR of HAMP gene(c.-25GNA). The results reported here illustrate the usefulness of NGS for targeted iron metabolism-related gene panels, as a likely cost-effective approach for molecular genetics diagnosis of non-classic HH patients. Simultaneously, it has contributed to the knowledge of the pathophysiology of those rare iron metabolism-related disorders.

Behavioral and molecular genetics of reading-related AM and FM detection thresholds

Auditory detection thresholds for certain frequencies of both amplitude modulated (AM) and frequency modulated (FM) dynamic auditory stimuli are associated with reading in typically developing and dyslexic readers. We present the first behavioral and molecular genetic characterization of these two auditory traits. Two extant extended family datasets were given reading tasks and psychoacoustic tasks to determine FM 2 Hz and AM 20 Hz sensitivity thresholds. Univariate heritabilities were significant for both AM (h2 = 0.20) and FM (h2 = 0.29). Bayesian posterior probability of linkage (PPL) analysis found loci for AM (12q, PPL = 81 %) and FM (10p, PPL = 32 %; 20q, PPL = 65 %). Bivariate heritability analyses revealed that FM is genetically correlated with reading, while AM was not. Bivariate PPL analysis indicates that FM loci (10p, 20q) are not also associated with reading.