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Description
Background
Improvements in sequencing technology now allow easy acquisition of large datasets; however, analyzing these data for phylogenetics can be challenging. We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, multiple genome alignment, and annotation.
Results
For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered eight phylogenies that resolved the basal relationships among mammals using datasets with different levels of missing data. The three alternate resolutions of the basal relationships are consistent with the major hypotheses for the relationships among mammals, all of which have been supported previously by different molecular datasets.
Conclusions
SISRS has the potential to transform phylogenetic research. This method eliminates the need for expensive marker development in many studies by using whole genome shotgun sequence data directly. SISRS is open source and freely available at https://github.com/rachelss/SISRS/releases.
Improvements in sequencing technology now allow easy acquisition of large datasets; however, analyzing these data for phylogenetics can be challenging. We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, multiple genome alignment, and annotation.
Results
For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered eight phylogenies that resolved the basal relationships among mammals using datasets with different levels of missing data. The three alternate resolutions of the basal relationships are consistent with the major hypotheses for the relationships among mammals, all of which have been supported previously by different molecular datasets.
Conclusions
SISRS has the potential to transform phylogenetic research. This method eliminates the need for expensive marker development in many studies by using whole genome shotgun sequence data directly. SISRS is open source and freely available at https://github.com/rachelss/SISRS/releases.
ContributorsSchwartz, Rachel (Author) / Harkins, Kelly (Author) / Stone, Anne (Author) / Cartwright, Reed (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2015-06-11
Description
Although conflict is a normative part of parent–adolescent relationships, conflicts that are long or highly negative are likely to be detrimental to these relationships and to youths’ development. In the present article, sequential analyses of data from 138 parent–adolescent dyads (adolescents’ mean age was 13.44, SD = 1.16; 52 % girls, 79 % non-Hispanic White) were used to define conflicts as reciprocal exchanges of negative emotion observed while parents and adolescents were discussing “hot,” conflictual issues. Dynamic components of these exchanges, including who started the conflicts, who ended them, and how long they lasted, were identified. Mediation analyses revealed that a high proportion of conflicts ended by adolescents was associated with longer conflicts, which in turn predicted perceptions of the “hot” issue as unresolved and adolescent behavior problems. The findings illustrate advantages of using sequential analysis to identify patterns of interactions and, with some certainty, obtain an estimate of the contingent relationship between a pattern of behavior and child and parental outcomes. These interaction patterns are discussed in terms of the roles that parents and children play when in conflict with each other, and the processes through which these roles affect conflict resolution and adolescents’ behavior problems.
ContributorsMoed, Anat (Author) / Gershoff, Elizabeth T. (Author) / Eisenberg, Nancy (Author) / Hofer, Claire (Author) / Losoya, Sandra (Author) / Spinrad, Tracy (Author) / Liew, Jeffrey (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor)
Created2015-08-01
Description
We used sex, observed parenting quality at 18 months, and three variants of the catechol-O-methyltransferase gene (Val[superscript 158]Met [rs4680], intron1 [rs737865], and 3′-untranslated region [rs165599]) to predict mothers' reports of inhibitory and attentional control (assessed at 42, 54, 72, and 84 months) and internalizing symptoms (assessed at 24, 30, 42, 48, and 54 months) in a sample of 146 children (79 male). Although the pattern for all three variants was very similar, Val[superscript 158]Met explained more variance in both outcomes than did intron1, the 3′-untranslated region, or a haplotype that combined all three catechol-O-methyltransferase variants. In separate models, there were significant three-way interactions among each of the variants, parenting, and sex, predicting the intercepts of inhibitory control and internalizing symptoms. Results suggested that Val[superscript 158]Met indexes plasticity, although this effect was moderated by sex. Parenting was positively associated with inhibitory control for methionine–methionine boys and for valine–valine/valine–methionine girls, and was negatively associated with internalizing symptoms for methionine–methionine boys. Using the “regions of significance” technique, genetic differences in inhibitory control were found for children exposed to high-quality parenting, whereas genetic differences in internalizing were found for children exposed to low-quality parenting. These findings provide evidence in support of testing for differential susceptibility across multiple outcomes.
ContributorsSulik, Michael (Author) / Eisenberg, Nancy (Author) / Spinrad, Tracy (Author) / Lemery, Kathryn (Author) / Swann, Gregory (Author) / Silva, Kassondra (Author) / Reiser, Mark (Author) / Stover, Daryn (Author) / Verrelli, Brian (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-08-01
Description
Since its introduction, the Rosenberg General Self-Esteem Scale (RGSE, Rosenberg, 1965) has been 1 of the most widely used measures of global self-esteem. We conducted 4 studies to investigate (a) the goodness-of-fit of a bifactor model positing a general self-esteem (GSE) factor and 2 specific factors grouping positive (MFP) and negative items (MFN) and (b) different kinds of validity of the GSE, MFN, and MFP factors of the RSGE. In the first study (n = 11,028), the fit of the bifactor model was compared with those of 9 alternative models proposed in literature for the RGSE. In Study 2 (n = 357), the external validities of GSE, MFP, and MFN were evaluated using objective grade point average data and multimethod measures of prosociality, aggression, and depression. In Study 3 (n = 565), the across-rater robustness of the bifactor model was evaluated. In Study 4, measurement invariance of the RGSE was further supported across samples in 3 European countries, Serbia (n = 1,010), Poland (n = 699), and Italy (n = 707), and in the United States (n = 1,192). All in all, psychometric findings corroborate the value and the robustness of the bifactor structure and its substantive interpretation.
ContributorsAlessandri, Guido (Author) / Vecchione, Michele (Author) / Eisenberg, Nancy (Author) / Laguna, Mariola (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor)
Created2015-06-01
Description
Animal hybridization is well documented, but evolutionary outcomes and conservation priorities often differ for natural and anthropogenic hybrids. Among primates, an order with many endangered species, the two contexts can be hard to disentangle from one another, which carries important conservation implications. Callithrix marmosets give us a unique glimpse of genetic hybridization effects under distinct natural and human-induced contexts. Here, we use a 44 autosomal microsatellite marker panel to examine genome-wide admixture levels and introgression at a natural C. jacchus and C. penicillata species border along the Sao Francisco River in NE Brazil and in an area of Rio de Janeiro state where humans introduced these species exotically. Additionally, we describe for the first time autosomal genetic diversity in wild C. penicillata and expand previous C. jacchus genetic data. We characterize admixture within the natural zone as bimodal where hybrid ancestry is biased toward one parental species or the other. We also show evidence that Sao Francisco River islands are gateways for bidirectional gene flow across the species border. In the anthropogenic zone, marmosets essentially form a hybrid swarm with intermediate levels of admixture, likely from the absence of strong physical barriers to interspecific breeding. Our data show that while hybridization can occur naturally, the presence of physical, even if leaky, barriers to hybridization is important for maintaining species genetic integrity. Thus, we suggest further study of hybridization under different contexts to set well informed conservation guidelines for hybrid populations that often fit somewhere between "natural" and "man-made."
ContributorsMalukiewicz, Joanna (Author) / Boere, Vanner (Author) / Fuzessy, Lisieux F. (Author) / Grativol, Adriana D. (Author) / de Oliveira e Silva, Ita (Author) / Pereira, Luiz C. M. (Author) / Ruiz-Miranda, Carlos R. (Author) / Valenca, Yuri M. (Author) / Stone, Anne (Author) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2015-06-10
Description
Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as “economic epidemiology” or “epidemiological economics,” the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
ContributorsPerrings, Charles (Author) / Castillo-Chavez, Carlos (Author) / Chowell-Puente, Gerardo (Author) / Daszak, Peter (Author) / Fenichel, Eli P. (Author) / Finnoff, David (Author) / Horan, Richard D. (Author) / Kilpatrick, A. Marm (Author) / Kinzig, Ann (Author) / Kuminoff, Nicolai (Author) / Levin, Simon (Author) / Morin, Benjamin (Author) / Smith, Katherine F. (Author) / Springborn, Michael (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / W.P. Carey School of Business (Contributor) / Economics (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-12-01
Description
Preserving a system’s viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter- or intraspecies, may increase population fragility, either decreasing its ability to adapt effectively to environmental changes or facilitating the survival and success of ordinarily rare phenotypes. The latter may result in over-representation of individuals who may participate in resource utilization patterns that can lead to over-exploitation, exhaustion, and, ultimately, collapse of both the resource and the population that depends on it. Here, we aim to identify regimes that can signal whether a consumer–resource system is capable of supporting viable degrees of heterogeneity. The framework used here is an expansion of a previously introduced consumer–resource type system of a population of individuals classified by their resource consumption. Application of the Reduction Theorem to the system enables us to evaluate the health of the system through tracking both the mean value of the parameter of resource (over)consumption, and the population variance, as both change over time. The article concludes with a discussion that highlights applicability of the proposed system to investigation of systems that are affected by particularly devastating overly adapted populations, namely cancerous cells. Potential intervention approaches for system management are discussed in the context of cancer therapies.
ContributorsKareva, Irina (Author) / Morin, Benjamin (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-02-01
Description
Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI) data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454) is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. The new approach allows for a more comprehensive and effective use of MI data when testing mediation models.
ContributorsPapa, Lesther A. (Author) / Litson, Kaylee (Author) / Lockhart, Ginger (Author) / Chassin, Laurie (Author) / Geiser, Christian (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor)
Created2015-11-13
Description
Zoonotic pathogens that cause leprosy (Mycobacterium leprae) and tuberculosis (Mycobacterium tuberculosis complex, MTBC) continue to impact modern human populations. Therefore, methods able to survey mycobacterial infection in potential animal hosts are necessary for proper evaluation of human exposure threats. Here we tested for mycobacterial-specific single- and multi-copy loci using qPCR. In a trial study in which armadillos were artificially infected with M. leprae, these techniques were specific and sensitive to pathogen detection, while more traditional ELISAs were only specific. These assays were then employed in a case study to detect M. leprae as well as MTBC in wild marmosets. All marmosets were negative for M. leprae DNA, but 14 were positive for the mycobacterial rpoB gene assay. Targeted capture and sequencing of rpoB and other MTBC genes validated the presence of mycobacterial DNA in these samples and revealed that qPCR is useful for identifying mycobacterial-infected animal hosts.
ContributorsHousman, Genevieve (Author) / Malukiewicz, Joanna (Author) / Boere, Vanner (Author) / Grativol, Adriana D. (Author) / Pereira, Luiz Cezar M. (Author) / de Oliveira e Silva, Ita (Author) / Ruiz-Miranda, Carlos R. (Author) / Truman, Richard (Author) / Stone, Anne (Author) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Biodesign Institute (Contributor) / Personalized Diagnostics (Contributor)
Created2015-11-16
Description
Background
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.
Methodology
We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.
Conclusions
We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.
ContributorsTowers, Sherry (Author) / Afzal, Shehzad (Author) / Bernal, Gilbert (Author) / Bliss, Nadya (Author) / Brown, Shala (Author) / Espinoza, Baltazar (Author) / Jackson, Jasmine (Author) / Judson-Garcia, Julia (Author) / Khan, Maryam (Author) / Lin, Michael (Author) / Mamada, Robert (Author) / Moreno, Victor (Author) / Nazari, Fereshteh (Author) / Okuneye, Kamaldeen (Author) / Ross, Mary (Author) / Rodriguez, Claudia (Author) / Medlock, Jan (Author) / Ebert, David (Author) / Castillo-Chavez, Carlos (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / Mary Lou Fulton Teachers College (Contributor) / Educational Leadership and Innovation (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Global Security Initiative (Contributor)
Created2015-06-11