Women\u27s Experiences in the Transition from Capstone Design Courses to Engineering Workplaces

Substantial research over the past few decades has documented the challenges women experience both as students in engineering programs and as professionals in engineering workplaces. Few studies, however, have followed women from one context to the other to explore the ways in which school experiences, and particularly capstone experiences designed to facilitate this transition, do and do not prepare women for their work as practicing engineers. To address this gap, we draw on data from a larger multi-institution study to address the question, “How do women experience the transition from engineering school to engineering work?” Participants for this study are drawn from a larger study across four universities (three mechanical engineering programs and one engineering science program). All participants identified as “female” on a screening questionnaire that included options for transgender and gender-nonconforming, as well as an option to skip the question. The full data set includes interviews with the participants conducted at the end of their capstone design course, responses to open-ended questions sent each week during their first 12 weeks of work, and interviews conducted after three, six, and 12 months of work. To answer the research question, we used purposeful sampling to identify four women whose interviews represented different trajectories across this school-to-work transition; we then used constructed narrative analysis to present their individual stories and identify salient points of similarity and difference for discussion. We also present implications for engineering educators, including that life-long learning should be expected, communication and collaboration are as essential workplace skills as technical competencies, and that gender is not necessarily a homogenizing force. Above all, we emphasize the power of the individual voice in better understanding the experiences of our students

TranspoGene and microTranspoGene: transposed elements influence on the transcriptome of seven vertebrates and invertebrates

Transposed elements (TEs) are mobile genetic sequences. During the evolution of eukaryotes TEs were inserted into active protein-coding genes, affecting gene structure, expression and splicing patterns, and protein sequences. Genomic insertions of TEs also led to creation and expression of new functional non-coding RNAs such as micro- RNAs. We have constructed the TranspoGene database, which covers TEs located inside proteincoding genes of seven species: human, mouse, chicken, zebrafish, fruit fly, nematode and sea squirt. TEs were classified according to location within the gene: proximal promoter TEs, exonized TEs (insertion within an intron that led to exon creation), exonic TEs (insertion into an existing exon) or intronic TEs. TranspoGene contains information regarding specific type and family of the TEs, genomic and mRNA location, sequence, supporting transcript accession and alignment to the TE consensus sequence. The database also contains host gene specific data: gene name, genomic location, Swiss-Prot and RefSeq accessions, diseases associated with the gene and splicing pattern. In addition, we created microTranspoGene: a database of human, mouse, zebrafish and nematode TEderived microRNAs. The TranspoGene and micro- TranspoGene databases can be used by researchers interested in the effect of TE insertion on the eukaryotic transcriptome

Resistance gene enrichment sequencing (RenSeq) enables reannotation of the NB-LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations

RenSeq is a NB-LRR (nucleotide binding-site leucine-rich repeat) gene-targeted, Resistance gene enrichment and sequencing method that enables discovery and annotation of pathogen resistance gene family members in plant genome sequences. We successfully applied RenSeq to the sequenced potato Solanum tuberosum clone DM, and increased the number of identified NB-LRRs from 438 to 755. The majority of these identified R gene loci reside in poorly or previously unannotated regions of the genome. Sequence and positional details on the 12 chromosomes have been established for 704 NB-LRRs and can be accessed through a genome browser that we provide. We compared these NB-LRR genes and the corresponding oligonucleotide baits with the highest sequence similarity and demonstrated that ~80% sequence identity is sufficient for enrichment. Analysis of the sequenced tomato S. lycopersicum ‘Heinz 1706’ extended the NB-LRR complement to 394 loci. We further describe a methodology that applies RenSeq to rapidly identify molecular markers that co-segregate with a pathogen resistance trait of interest. In two independent segregating populations involving the wild Solanum species S. berthaultii (Rpi-ber2) and S. ruiz-ceballosii (Rpi-rzc1), we were able to apply RenSeq successfully to identify markers that co-segregate with resistance towards the late blight pathogen Phytophthora infestans. These SNP identification workflows were designed as easy-to-adapt Galaxy pipelines

miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments

Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/

FINDbase: a relational database recording frequencies of genetic defects leading to inherited disorders worldwide

Frequency of INherited Disorders database (FINDbase) () is a relational database, derived from the ETHNOS software, recording frequencies of causative mutations leading to inherited disorders worldwide. Database records include the population and ethnic group, the disorder name and the related gene, accompanied by links to any corresponding locus-specific mutation database, to the respective Online Mendelian Inheritance in Man entries and the mutation together with its frequency in that population. The initial information is derived from the published literature, locus-specific databases and genetic disease consortia. FINDbase offers a user-friendly query interface, providing instant access to the list and frequencies of the different mutations. Query outputs can be either in a table or graphical format, accompanied by reference(s) on the data source. Registered users from three different groups, namely administrator, national coordinator and curator, are responsible for database curation and/or data entry/correction online via a password-protected interface. Databaseaccess is free of charge and there are no registration requirements for data querying. FINDbase provides a simple, web-based system for population-based mutation data collection and retrieval and can serve not only as a valuable online tool for molecular genetic testing of inherited disorders but also as a non-profit model for sustainable database funding, in the form of a ‘database-journal’

5-Hydroxymethylation marks a class of neuronal gene regulated by intragenic methylcytosine levels.

AbstractWe recently identified a class of neuronal gene inheriting high levels of intragenic methylation from the mother and maintaining this through later development. We show here that these genes are implicated in basic neuronal functions such as post-synaptic signalling, rather than neuronal development and inherit high levels of 5mC, but not 5hmC, from the mother. 5mC is distributed across the gene body and appears to facilitate transcription, as transcription is reduced in DNA methyltransferase I (Dnmt1) knockout embryonic stem cells as well as in fibroblasts treated with a methyltransferase inhibitor. However in adult brain, transcription is more closely associated with a gain in 5hmC, which occurs without a measurable loss of 5mC. These findings add to growing evidence that there may be a role for 5mC in promoting transcription as well as its classical role in gene silencing