An advanced web query interface for biological databases

Although most web-based biological databases (DBs) offer some type of web-based form to allow users to author DB queries, these query forms are quite restricted in the complexity of DB queries that they can formulate. They can typically query only one DB, and can query only a single type of object at a time (e.g. genes) with no possible interaction between the objects—that is, in SQL parlance, no joins are allowed between DB objects. Writing precise queries against biological DBs is usually left to a programmer skillful enough in complex DB query languages like SQL. We present a web interface for building precise queries for biological DBs that can construct much more precise queries than most web-based query forms, yet that is user friendly enough to be used by biologists. It supports queries containing multiple conditions, and connecting multiple object types without using the join concept, which is unintuitive to biologists. This interactive web interface is called the Structured Advanced Query Page (SAQP). Users interactively build up a wide range of query constructs. Interactive documentation within the SAQP describes the schema of the queried DBs. The SAQP is based on BioVelo, a query language based on list comprehension. The SAQP is part of the Pathway Tools software and is available as part of several bioinformatics web sites powered by Pathway Tools, including the BioCyc.org site that contains more than 500 Pathway/Genome DBs

Incorporating Genetics into Your Studies: A Guide for Social Scientists

There has been a surge of interest in recent years in incorporating genetic components into on-going longitudinal, developmental studies and related psychological studies. While this represents an exciting new direction in developmental science, much of the research on genetic topics in developmental science does not reflect the most current practice in genetics. This is likely due, in part, to the rapidly changing landscape of the field of genetics, and the difficulty this presents for developmental scientists who are trying to learn this new area. In this review, we present an overview of the paradigm shifts that have occurred in genetics and we introduce the reader to basic genetic methodologies. We present our view of the current stage of research ongoing at the intersection of genetics and social science, and we provide recommendations for how we could do better. We also address a number of issues that social scientists face as they integrate genetics into their projects, including choice of a study design (candidate gene versus genome-wide association versus sequencing), different methods of DNA collection, and special considerations involved in the analysis of genotypic data. Through this review, we hope to equip social scientists with a deeper understanding of the many considerations that go into genetics research, in an effort to foster more meaningful cross-disciplinary initiatives

Modeling Longitudinal Change in Cervical Length Across Pregnancy

Introduction: A short cervix (cervical length \u3c 25 mm) in the mid-trimester (18 to 24 weeks) of pregnancy is a powerful predictor of spontaneous preterm delivery (gestational age at delivery \u3c 37 weeks). Although the biological mechanisms of cervical remodeling have been the subject of extensive investigation, very little is known about the rate of change in cervical length over the course of a pregnancy, or the extent to which rapid cervical shortening increases maternal risk for spontaneous preterm delivery. Methods: A cohort of 5,160 unique women carrying 5,971 singleton pregnancies provided two or more measurements of cervical length during pregnancy. Cervical length was measured in millimeters using a transvaginal 12-3 MHz ultrasound endocavity probe (SuperSonic Imagine). Maternal characteristics, including relevant medical history and birth outcome data, were collected for each participant. Gestational age at delivery was measured from the first day of each woman’s last menstrual period and confirmed by ultrasound. Repeated measurements of cervical length during pregnancy were modeled as a longitudinal, multilevel growth curve in MPlus. A three-level variance structure was used to account for non-independence of repeated measurements clustered within pregnancies, which are clustered within participants. Results: The average number of cervical length measurements per pregnancy is 6. Shorter mid-trimester cervical lengths and accelerated rates of cervical shortening are associated with shorter gestational duration. A smaller initial cervical length (p \u3c 1*10-4) and a faster rate of change in cervical change length during pregnancy (p \u3c 1*10-4) are significantly associated with an earlier gestational age at delivery. A higher pre-pregnancy body mass index (BMI) is associated with shorter initial cervical length in early pregnancy (p \u3c 1*10-4), while maternal age is associated with a more rapid rate of change in cervical length (p \u3c 1*10-4). Parameters describing cervical length and its rate change during pregnancy (i.e., intercept, linear slope, and quadratic slope parameters) explained 59% more variance in gestational age at delivery than a single mid-rimester cervical length measurement, which is the current gold standard in clinical practice. However, a significant amount of residual variance in individual estimates of cervical length growth parameters remains (p \u3c 1*10-4), which could be accounted for, in part, by common variation in the population. Conclusion: We have developed longitudinal models of cervical length that describe individual and group level trajectories of cervical change across pregnancy. Extensions of this model incorporating genomic data, can be used to estimate the heritability of cervical length and its role in mediating the timing of birth.https://scholarscompass.vcu.edu/gradposters/1141/thumbnail.jp

Prospective Longitudinal Study of the Pregnancy DNA Methylome: The US Pregnancy, Race, Environment, Genes (PREG) Study

Purpose The goal of the Pregnancy, Race, Environment, Genes study was to understand how social and environmental determinants of health (SEDH), pregnancy-specific environments (PSE) and biological processes influence the timing of birth and account for the racial disparity in preterm birth. The study followed a racially diverse longitudinal cohort throughout pregnancy and included repeated measures of PSE and DNA methylation (DNAm) over the course of gestation and up to 1 year into the postpartum period. Participants All women were between 18 and 40 years of age with singleton pregnancies and no diagnosis of diabetes or indication of assisted reproductive technology. Both mother and father had to self-identify as either African-American (AA) or European-American (EA). Maternal peripheral blood samples along with self-report questionnaires measuring SEDH and PSE factors were collected at four pregnancy visits, and umbilical cord blood was obtained at birth. A subset of participants returned for two additional postpartum visits, during which additional questionnaires and maternal blood samples were collected. The pregnancy and postpartum extension included n=240 (AA=126; EA=114) and n=104 (AA=50; EA=54), respectively. Findings to date One hundred seventy-seven women (AA=89, EA=88) met full inclusion criteria out of a total of 240 who were initially enrolled. Of the 63 participants who met exclusion criteria after enrolment, 44 (69.8%) were associated with a medical reason. Mean gestational age at birth was significantly shorter for the AA participants by 5.1 days (M=272.5 (SD=10.5) days vs M=277.6 (SD=8.3)). Future plans Future studies will focus on identifying key environmental factors that influence DNAm change across pregnancy and account for racial differences in preterm birth

A critical evaluation of automatic atom mapping algorithms and tools

The identification of the atoms which change their position in chemical reactions is an important knowledge within the field of Metabolic Engineering. This can lead to new advances at different levels from the reconstruction of metabolic networks to the classification of chemical reactions, through the identification of the atomic changes inside a reaction. The Atom Mapping approach was initially developed in the 1960s, but recently suffered important advances, being used in diverse biological and biotechnological studies. The main methodologies used for atom mapping are the Maximum Common Substructure and the Linear Optimization methods, which both require computational know-how and powerful resources to run the underlying tools. In this work, we assessed a number of previously implemented atom mapping frameworks, and built a framework able of managing the different data inputs and outputs, as well as the mapping process provided by each of these third-party tools. We evaluated the admissibility of the calculated atom maps from different algorithms, also assessing if with different approaches we were capable of returning equivalent atom maps for the same chemical reaction.ERDF -European Regional Development Fund(UID/BIO/04469/2013)info:eu-repo/semantics/publishedVersio

Can Genetics Predict Response to Complex Behavioral Interventions? Evidence from a Genetic Analysis of the Fast Track Randomized Control Trial

Early interventions are a preferred method for addressing behavioral problems in high-risk children, but often have only modest effects. Identifying sources of variation in intervention effects can suggest means to improve efficiency. One potential source of such variation is the genome. We conducted a genetic analysis of the Fast Track randomized control trial, a 10-year-long intervention to prevent high-risk kindergarteners from developing adult externalizing problems including substance abuse and antisocial behavior. We tested whether variants of the glucocorticoid receptor gene NR3C1 were associated with differences in response to the Fast Track intervention. We found that in European-American children, a variant of NR3C1 identified by the single-nucleotide polymorphism rs10482672 was associated with increased risk for externalizing psychopathology in control group children and decreased risk for externalizing psychopathology in intervention group children. Variation in NR3C1 measured in this study was not associated with differential intervention response in African-American children. We discuss implications for efforts to prevent externalizing problems in high-risk children and for public policy in the genomic era

EcoCyc: fusing model organism databases with systems biology.

EcoCyc (http://EcoCyc.org) is a model organism database built on the genome sequence of Escherichia coli K-12 MG1655. Expert manual curation of the functions of individual E. coli gene products in EcoCyc has been based on information found in the experimental literature for E. coli K-12-derived strains. Updates to EcoCyc content continue to improve the comprehensive picture of E. coli biology. The utility of EcoCyc is enhanced by new tools available on the EcoCyc web site, and the development of EcoCyc as a teaching tool is increasing the impact of the knowledge collected in EcoCyc

How phenotype and developmental stage affect the genes we find: GABRA2 and impulsivity

CONTEXT: The detection and replication of genes involved in psychiatric outcome has been notoriously difficult. Phenotypic measurement has been offered as one explanation, although most of this discussion has focused on problems with binary diagnoses. OBJECTIVE: This article focuses on two additional components of phenotypic measurement that deserve further consideration in evaluating genetic associations: (1) the measure used to reflect the outcome of interest, and (2) the developmental stage of the study population. We focus our discussion of these issues around the construct of impulsivity and externalizing disorders, and the association of these measures with a specific gene, GABRA2. DESIGN, SETTING, AND PARTICIPANTS: Data were analyzed from the Collaborative Study on the Genetics of Alcoholism Phase IV assessment of adolescents and young adults (ages 12–26; N = 2,128). MAIN OUTCOME MEASURES: Alcohol dependence, illicit drug dependence, childhood conduct disorder, and adult antisocial personality disorder symptoms were measured by psychiatric interview; Achenbach youth/adult self-report externalizing scale; Zuckerman Sensation-Seeking scale; Barratt Impulsivity scale; NEO extraversion and consciousness. RESULTS: GABRA2 was associated with subclinical levels of externalizing behavior as measured by the Achenbach in both the adolescent and young adult samples. Contrary to previous associations in adult samples, it was not associated with clinical-level DSM symptom counts of any externalizing disorders in these younger samples. There was also association with sensation-seeking and extraversion, but only in the adolescent sample. There was no association with the Barratt impulsivity scale or conscientiousness. CONCLUSIONS: Our results suggest that the pathway by which GABRA2 initially confers risk for eventual alcohol problems begins with a predisposition to sensation-seeking early in adolescence. The findings support the heterogeneous nature of impulsivity and demonstrate that both the measure used to assess a construct of interest and the age of the participants can have profound implications for the detection of genetic associations