Tactile localization of acoustic stimuli with an earmold vibratrory aid

This study examines the tactile localization of sound sources utilizing an earmold vibratory hearing aid

Learning your ABCDs: Asset-Based Community Development through Education Abroad and Community Engaged Research in Rural Malawi

The project is a partnership with the Malawi Children’s Mission (MCM), a feeding center and primary school that provides health care and emotional support services to 150 children who have been orphaned and their families in the rural villages of M\u27bwana, Jamali, and Mwazama. Asset-based community development (ABCD; Kretzman & McKnight, 1996) was used in the context of community engaged research to establish a sustainable university-assisted component of MCM through education abroad. ABCD relies upon individual and collective strengths and resources of community members to address the problems they define as needing attention, and has been used successfully in sub-Saharan Africa (Yeneabat & Butterfield, 2012). This project demonstrates how small scale community development informed by ABCD is an ethical and empowering approach that aims to reduce dependency on formal systems by using the talents and resources of the people to build a sense of hope and promote wellbeing and social and economic health. Binghamton University students and faculty took initial steps in ABCD during an education abroad trip to Malawi in 2016.https://orb.binghamton.edu/research_days_posters/1001/thumbnail.jp

A Functional Selection Model Explains Evolutionary Robustness Despite Plasticity in Regulatory Networks

Evolutionary rewiring of regulatory networks is an important source of diversity among species. Previous evidence suggested substantial divergence of regulatory networks across species. However, systematically assessing the extent of this plasticity and its functional implications has been challenging due to limited experimental data and the noisy nature of computational predictions. Here, we introduce a novel approach to study cis-regulatory evolution, and use it to trace the regulatory history of 88 DNA motifs of transcription factors across 23 Ascomycota fungi. While motifs are conserved, we find a pervasive gain and loss in the regulation of their target genes. Despite this turnover, the biological processes associated with a motif are generally conserved. We explain these trends using a model with a strong selection to conserve the overall function of a transcription factor, and a much weaker selection over the specific genes it targets. The model also accounts for the turnover of bound targets measured experimentally across species in yeasts and mammals. Thus, selective pressures on regulatory networks mostly tolerate local rewiring, and may allow for subtle fine-tuning of gene regulation during evolution

The evolutionary dynamics of the Saccharomyces cerevisiae protein interaction network after duplication

Gene duplication is an important mechanism in the evolution of protein interaction networks. Duplications are followed by the gain and loss of interactions, rewiring the network at some unknown rate. Because rewiring is likely to change the distribution of network motifs within the duplicated interaction set, it should be possible to study network rewiring by tracking the evolution of these motifs. We have developed a mathematical framework that, together with duplication data from comparative genomic and proteomic studies, allows us to infer the connectivity of the preduplication network and the changes in connectivity over time. We focused on the whole-genome duplication (WGD) event in Saccharomyces cerevisiae. The model allowed us to predict the frequency of intergene interaction before WGD and the post duplication probabilities of interaction gain and loss. We find that the predicted frequency of self-interactions in the preduplication network is significantly higher than that observed in today's network. This could suggest a structural difference between the modern and ancestral networks, preferential addition or retention of interactions between ohnologs, or selective pressure to preserve duplicates of self-interacting proteins

MetaPhOrs: orthology and paralogy predictions from multiple phylogenetic evidence using a consistency-based confidence score

Reliable prediction of orthology is central to comparative genomics. Approaches based on phylogenetic analyses closely resemble the original definition of orthology and paralogy and are known to be highly accurate. However, the large computational cost associated to these analyses is a limiting factor that often prevents its use at genomic scales. Recently, several projects have addressed the reconstruction of large collections of high-quality phylogenetic trees from which orthology and paralogy relationships can be inferred. This provides us with the opportunity to infer the evolutionary relationships of genes from multiple, independent, phylogenetic trees. Using such strategy, we combine phylogenetic information derived from different databases, to predict orthology and paralogy relationships for 4.1 million proteins in 829 fully sequenced genomes. We show that the number of independent sources from which a prediction is made, as well as the level of consistency across predictions, can be used as reliable confidence scores. A webserver has been developed to easily access these data (http://orthology.phylomedb.org), which provides users with a global repository of phylogeny-based orthology and paralogy predictions

Arboretum: Reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules

Comparative functional genomics studies the evolution of biological processes by analyzing functional data, such as gene expression profiles, across species. A major challenge is to compare profiles collected in a complex phylogeny. Here, we present Arboretum, a novel scalable computational algorithm that integrates expression data from multiple species with species and gene phylogenies to infer modules of coexpressed genes in extant species and their evolutionary histories. We also develop new, generally applicable measures of conservation and divergence in gene regulatory modules to assess the impact of changes in gene content and expression on module evolution. We used Arboretum to study the evolution of the transcriptional response to heat shock in eight species of Ascomycota fungi and to reconstruct modules of the ancestral environmental stress response (ESR). We found substantial conservation in the stress response across species and in the reconstructed components of the ancestral ESR modules. The greatest divergence was in the most induced stress, primarily through module expansion. The divergence of the heat stress response exceeds that observed in the response to glucose depletion in the same species. Arboretum and its associated analyses provide a comprehensive framework to systematically study regulatory evolution of condition-specific responses.Howard Hughes Medical InstituteBroad Institute of MIT and HarvardNational Institutes of Health (U.S.) (Pioneer Award)National Institutes of Health (U.S.) (R01 2R01CA119176-01)Burroughs Wellcome Fund (Career Award at the Scientific Interface)Alfred P. Sloan Foundatio

Impact of Hydrodynamic Injection and phiC31 Integrase on Tumor Latency in a Mouse Model of MYC-Induced Hepatocellular Carcinoma

Hydrodynamic injection is an effective method for DNA delivery in mouse liver and is being translated to larger animals for possible clinical use. Similarly, phiC31 integrase has proven effective in mediating long-term gene therapy in mice when delivered by hydrodynamic injection and is being considered for clinical gene therapy applications. However, chromosomal aberrations have been associated with phiC31 integrase expression in tissue culture, leading to questions about safety.To study whether hydrodynamic delivery alone, or in conjunction with delivery of phiC31 integrase for long-term transgene expression, could facilitate tumor formation, we used a transgenic mouse model in which sustained induction of the human C-MYC oncogene in the liver was followed by hydrodynamic injection. Without injection, mice had a median tumor latency of 154 days. With hydrodynamic injection of saline alone, the median tumor latency was significantly reduced, to 105 days. The median tumor latency was similar, 106 days, when a luciferase donor plasmid and backbone plasmid without integrase were administered. In contrast, when active or inactive phiC31 integrase and donor plasmid were supplied to the mouse liver, the median tumor latency was 153 days, similar to mice receiving no injection.Our data suggest that phiC31 integrase does not facilitate tumor formation in this C-MYC transgenic mouse model. However, in groups lacking phiC31 integrase, hydrodynamic injection appeared to contribute to C-MYC-induced hepatocellular carcinoma in adult mice. Although it remains to be seen to what extent these findings may be extrapolated to catheter-mediated hydrodynamic delivery in larger species, they suggest that caution should be used during translation of hydrodynamic injection to clinical applications

The multiple gene duplication problem revisited

Motivation: Deciphering the location of gene duplications and multiple gene duplication episodes on the Tree of Life is fundamental to understanding the way gene families and genomes evolve. The multiple gene duplication problem provides a framework for placing gene duplication events onto nodes of a given species tree, and detecting episodes of multiple gene duplication. One version of the multiple gene duplication problem was defined by Guigó et al. in 1996. Several heuristic solutions have since been proposed for this problem, but no exact algorithms were known

Uncovering RNA Editing Sites in Long Non-Coding RNAs

RNA editing is an important co/post-transcriptional molecular process able to modify RNAs by nucleotide insertions/deletions or substitutions. In human, the most common RNA editing event involves the deamination of adenosine (A) into inosine (I) through the adenosine deaminase acting on RNA proteins. Although A-to-I editing can occur in both coding and non-coding RNAs, recent findings, based on RNA-seq experiments, have clearly demonstrated that a large fraction of RNA editing events alter non-coding RNAs sequences including untranslated regions of mRNAs, introns, long non-coding RNAs (lncRNAs), and low molecular weight RNAs (tRNA, miRNAs, and others). An accurate detection of A-to-I events occurring in non-coding RNAs is of utmost importance to clarify yet unknown functional roles of RNA editing in the context of gene expression regulation and maintenance of cell homeostasis. In the last few years, massive transcriptome sequencing has been employed to identify putative RNA editing changes at genome scale. Despite several efforts, the computational prediction of A-to-I sites in complete eukaryotic genomes is yet a challenging task. We have recently developed a software package, called REDItools, in order to simplify the detection of RNA editing events from deep sequencing data. In the present work, we show the potential of our tools in recovering A-to-I candidates from RNA-Seq experiments as well as guidelines to improve the RNA editing detection in non-coding RNAs, with specific attention to the lncRNAs

eggNOG: automated construction and annotation of orthologous groups of genes

The identification of orthologous genes forms the basis for most comparative genomics studies. Existing approaches either lack functional annotation of the identified orthologous groups, hampering the interpretation of subsequent results, or are manually annotated and thus lag behind the rapid sequencing of new genomes. Here we present the eggNOG database (‘evolutionary genealogy of genes: Non-supervised Orthologous Groups’), which contains orthologous groups constructed from Smith–Waterman alignments through identification of reciprocal best matches and triangular linkage clustering. Applying this procedure to 312 bacterial, 26 archaeal and 35 eukaryotic genomes yielded 43 582 course-grained orthologous groups of which 9724 are extended versions of those from the original COG/KOG database. We also constructed more fine-grained groups for selected subsets of organisms, such as the 19 914 mammalian orthologous groups. We automatically annotated our non-supervised orthologous groups with functional descriptions, which were derived by identifying common denominators for the genes based on their individual textual descriptions, annotated functional categories, and predicted protein domains. The orthologous groups in eggNOG contain 1 241 751 genes and provide at least a broad functional description for 77% of them. Users can query the resource for individual genes via a web interface or download the complete set of orthologous groups at http://eggnog.embl.de