Abstract
Identifying the genetic architecture of complex traits is important to many geneticists, including those interested in human disease, plant and animal breeding, and evolutionary genetics. ...Advances in sequencing technology and statistical methods for genome-wide association studies have allowed for the identification of more variants with smaller effect sizes, however, many of these identified polymorphisms fail to be replicated in subsequent studies. In addition to sampling variation, this failure to replicate reflects the complexities introduced by factors including environmental variation, genetic background, and differences in allele frequencies among populations. Using Drosophila melanogaster wing shape, we ask if we can replicate allelic effects of polymorphisms first identified in a genome-wide association studies in three genes: dachsous, extra-macrochaete, and neuralized, using artificial selection in the lab, and bulk segregant mapping in natural populations. We demonstrate that multivariate wing shape changes associated with these genes are aligned with major axes of phenotypic and genetic variation in natural populations. Following seven generations of artificial selection along the dachsous shape change vector, we observe genetic differentiation of variants in dachsous and genomic regions containing other genes in the hippo signaling pathway. This suggests a shared direction of effects within a developmental network. We also performed artificial selection with the extra-macrochaete shape change vector, which is not a part of the hippo signaling network, but showed a largely shared direction of effects. The response to selection along the emc vector was similar to that of dachsous, suggesting that the available genetic diversity of a population, summarized by the genetic (co)variance matrix (G), influenced alleles captured by selection. Despite the success with artificial selection, bulk segregant analysis using natural populations did not detect these same variants, likely due to the contribution of environmental variation and low minor allele frequencies, coupled with small effect sizes of the contributing variants.
Assessing student knowledge based on their writing using traditional qualitative methods is time-consuming. To improve speed and consistency of text analysis, we present our mixed methods development ...of a machine learning predictive model to analyze student writing. Our approach involves two stages: first an exploratory sequential design, and second an iterative complex design. We first trained our predictive model using qualitative coding of categories (ideas) in student writing. We next revised our model based on feedback from instructor-users. The model itself highlighted categories in need of revision. The contribution to mixed methods research lies in our innovative use of the machine learning tool as a rapid, consistent additional coder, and a resource that can predict codes for new student writing.
Students' writing can provide better insight into their thinking than can multiple-choice questions. However, resource constraints often prevent faculty from using writing assessments in large ...undergraduate science courses. We investigated the use of computer software to analyze student writing and to uncover student ideas about chemistry in an introductory biology course. Students were asked to predict acid-base behavior of biological functional groups and to explain their answers. Student explanations were rated by two independent raters. Responses were also analyzed using SPSS Text Analysis for Surveys and a custom library of science-related terms and lexical categories relevant to the assessment item. These analyses revealed conceptual connections made by students, student difficulties explaining these topics, and the heterogeneity of student ideas. We validated the lexical analysis by correlating student interviews with the lexical analysis. We used discriminant analysis to create classification functions that identified seven key lexical categories that predict expert scoring (interrater reliability with experts = 0.899). This study suggests that computerized lexical analysis may be useful for automatically categorizing large numbers of student open-ended responses. Lexical analysis provides instructors unique insights into student thinking and a whole-class perspective that are difficult to obtain from multiple-choice questions or reading individual responses. (Contains 6 tables and 2 figures.)
Recent calls for college biology education reform have identified "pathways and transformations of matter and energy" as a big idea in biology crucial for students to learn. Previous work has been ...conducted on how college students think about such matter-transforming processes; however, little research has investigated how students connect these ideas. Here, we probe student thinking about matter transformations in the familiar context of human weight loss. Our analysis of 1192 student constructed responses revealed three scientific (which we label "Normative") and five less scientific (which we label "Developing") ideas that students use to explain weight loss. Additionally, students combine these ideas in their responses, with an average number of 2.19 plus or minus 1.07 ideas per response, and 74.4% of responses containing two or more ideas. These results highlight the extent to which students hold multiple (both correct and incorrect) ideas about complex biological processes. We described student responses as conforming to either Scientific, Mixed, or Developing descriptive models, which had an average of 1.9 plus or minus 0.6, 3.1 plus or minus 0.9, and 1.7 plus or minus 0.8 ideas per response, respectively. Such heterogeneous student thinking is characteristic of difficulties in both conceptual change and early expertise development and will require careful instructional intervention for lasting learning gains.
Many organisms worldwide are responding to rapid climate change by shifting their geographic ranges. The white-footed mouse, Peromyscus leucopus, has expanded its range northward in Michigan and ...Wisconsin since 1980 and is now common in localities where it was previously unknown. To investigate the origin and history of the newly established populations, complete D-loop sequences were analyzed from 595 white-footed mice collected throughout the northern Great Lakes region. Mice from Wisconsin and the western Upper Peninsula (UP) of Michigan make up a well-differentiated lineage, while the eastern UP and the Lower Peninsula (LP) of Michigan form a second lineage. The two lineages diverged about 34,000 BP, well before they migrated to the Great Lakes region. The close genetic relationship between mice in the LP and those in the eastern UP is probably due primarily to accidental transport by humans and may have implications for the spread of Lyme disease in the Upper Midwest.
The core concept of genetic information flow was identified in recent calls to improve undergraduate biology education. Previous work shows that students have difficulty differentiating between the ...three processes of the Central Dogma (CD; replication, transcription, and translation). We built upon this work by developing and applying an analytic coding rubric to 1050 student written responses to a three‐question item about the CD. Each response was previously coded only for correctness using a holistic rubric. Our rubric captures subtleties of student conceptual understanding of each process that previous work has not yet captured at a large scale. Regardless of holistic correctness scores, student responses included five or six distinct ideas. By analyzing common co‐occurring rubric categories in student responses, we found a common pair representing two normative ideas about the molecules produced by each CD process. By applying analytic coding to student responses preinstruction and postinstruction, we found student thinking about the processes involved was most prone to change. The combined strengths of analytic and holistic rubrics allow us to reveal mixed ideas about the CD processes and provide a detailed picture of which conceptual ideas students draw upon when explaining each CD process.
White-tailed deer, Odocoileus virginianus, is the most important game species in Venezuela. Some populations are currently threatened by overhunting and habitat loss, making it necessary for ...implementation of conservation programs. In this study, we employed molecular phylogenetics and population genetics principles to identify conservation units of Venezuelan populations of this species and to provide recommendations for its management. We analyzed DNA sequences—730 base pairs of the mitochondrial control region—in 26 individuals sampled from the 3 subspecies present in Venezuela. Results revealed moderate levels of genetic polymorphism. In addition, evidence of significant population structure was found. Phylogeographic analyses showed 4 lineages with the nominal subspecies O. v. gymnotis appearing to be polyphyletic. A remarkable divergence among haplotypes from Venezuela and North America was revealed in phylogenetic analyses, the former comprising a monophyletic group. The observed divergence among haplotypes from Venezuelan and North American populations was, in most cases, higher than that observed among the latter and haplotypes of O. hemionus (black-tailed deer). This result suggests that Venezuelan white-tailed deer could be considered an evolutionarily significant unit. We interpreted the results obtained within the context of climatic changes since Late Pleistocene. In addition to ecological and morphological evidence, our data suggest that O. v. margaritae and O. v. goudotii populations, the 2 subspecies considered endangered, are clearly differentiated and should be recognized as geminate evolutionary units and protected as distinct groups, even though there is no clear support for elevating these subspecies to species rank, as proposed recently.
We analyzed growth of the sigmodontine rodent Oryzomys albigularis under laboratory conditions, fitting data to growth models, to test the null hypothesis that no differences exist between sexes. We ...propose a biologic criterion for growth-model selection, under the assumption that the curve should show critical stages of the organism's postnatal development and growth. Following this approach, growth of O. albigularis best fits a logistic curve. Our results show that, although males and females grow at the same rate, the final size is significantly different, being slightly dimorphic. These results, together with behavioral observations of the animals in the laboratory, support the hypothesis of a monogamic mating system for this species.
We analyzed growth of the sigmodontine rodent Oryzomys albigularis under laboratory conditions, fitting data to growth models, to test the null hypothesis that no differences exist between sexes. We ...propose a biologic criterion for growth-model selection, under the assumption that the curve should show critical stages of the organism's postnatal development and growth. Following this approach, growth of O. albigularis best fits a logistic curve. Our results show that, although males and females grow at the same rate, the final size is significantly different, being slightly dimorphic. These results, together with behavioral observations of the animals in the laboratory, support the hypothesis of a monogamic mating system for this species.
Constructed response questions - in which students must use their own language in order to explain a phenomenon - create more meaningful opportunities for instructors to identify their students' ...learning obstacles than multiple choice questions. However, the realities of typical large-enrollment undergraduate classes restrict the options faculty have for moving towards more learner-focused instruction. We are exploring the use of computerized lexical analysis of students' writing in large enrollment undergraduate biology and geology courses. We have created libraries that categorize student responses with > 90% accuracy. These categories can be used to predict expert ratings of student responses with accuracy approaching inter-rater reliability among expert raters. These techniques also provide insight into students' use of analogical thinking, a fundamental part of scientific modeling. These techniques have potential for improving assessment practices across STEM disciplines.
PDF
