Orthology confers intron position conservation

<p>Abstract</p> <p>Background</p> <p>With the wealth of genomic data available it has become increasingly important to assign putative protein function through functional transfer between orthologs. Therefore, correct elucidation of the evolutionary relationships among genes is a critical task, and attempts should be made to further improve the phylogenetic inference by adding relevant discriminating features. It has been shown that introns can maintain their position over long evolutionary timescales. For this reason, it could be possible to use conservation of intron positions as a discriminating factor when assigning orthology. Therefore, we wanted to investigate whether orthologs have a higher degree of intron position conservation (IPC) compared to non-orthologous sequences that are equally similar in sequence.</p> <p>Results</p> <p>To this end, we developed a new score for IPC and applied it to ortholog groups between human and six other species. For comparison, we also gathered the closest non-orthologs, meaning sequences close in sequence space, yet falling just outside the ortholog cluster. We found that ortholog-ortholog gene pairs on average have a significantly higher degree of IPC compared to ortholog-closest non-ortholog pairs. Also pairs of inparalogs were found to have a higher IPC score than inparalog-closest non-inparalog pairs. We verified that these differences can not simply be attributed to the generally higher sequence identity of the ortholog-ortholog and the inparalog-inparalog pairs.</p> <p>Furthermore, we analyzed the agreement between IPC score and the ortholog score assigned by the InParanoid algorithm, and found that it was consistently high for all species comparisons. In a minority of cases, the IPC and InParanoid score ranked inparalogs differently. These represent cases where sequence and intron position divergence are discordant. We further analyzed the discordant clusters to identify any possible preference for protein functions by looking for enriched GO terms and Pfam protein domains. They were enriched for functions important for multicellularity, which implies a connection between shifts in intronic structure and the origin of multicellularity.</p> <p>Conclusions</p> <p>We conclude that orthologous genes tend to have more conserved intron positions compared to non-orthologous genes. As a consequence, our IPC score is useful as an additional discriminating factor when assigning orthology.</p

Functional Characterization in Caenorhabditis Elegans of Transmembrane Worm-Human Orthologs

Background: The complete genome sequences for human and the nematode Caenorhabditiselegans offer an opportunity to learn more about human gene function through functionalcharacterization of orthologs in the worm. Based on a previous genome-wide analysis of wormhumanorthologous transmembrane proteins, we selected seventeen genes to exploreexperimentally in C. elegans. These genes were selected on the basis that they all have highconfidence candidate human orthologs and that their function is unknown. We first analyzed theirphylogeny, membrane topology and domain organization. Then gene functions were studiedexperimentally in the worm by using RNA interference and transcriptional gfp reporter genefusions.Results: The experiments gave functional insights for twelve of the genes studied. For example,C36B1.12, the worm ortholog of three presenilin-like genes, was almost exclusively expressed inhead neurons, suggesting an ancient conserved role important to neuronal function. We proposea new transmembrane topology for the presenilin-like protein family. sft-4, the worm ortholog ofsurfeit locus gene Surf-4, proved to be an essential gene required for development during the larvalstages of the worm. R155.1, whose human ortholog is entirely uncharacterized, was implicated inbody size control and other developmental processes.Conclusions: By combining bioinformatics and C. elegans experiments on orthologs, we providefunctional insights on twelve previously uncharacterized human genes

An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence

With the rapid development of the internet of things (IoT) and artificial intelligence (AI) technologies, human activity recognition (HAR) has been applied in a variety of domains such as security and surveillance, human-robot interaction, and entertainment. Even though a number of surveys and review papers have been published, there is a lack of HAR overview papers focusing on healthcare applications that use wearable sensors. Therefore, we fill in the gap by presenting this overview paper. In particular, we present our projects to illustrate the system design of HAR applications for healthcare. Our projects include early mobility identification of human activities for intensive care unit (ICU) patients and gait analysis of Duchenne muscular dystrophy (DMD) patients. We cover essential components of designing HAR systems including sensor factors (e.g., type, number, and placement location), AI model selection (e.g., classical machine learning models versus deep learning models), and feature engineering. In addition, we highlight the challenges of such healthcare-oriented HAR systems and propose several research opportunities for both the medical and the computer science community

Genetic modifiers of ambulation in the cooperative international Neuromuscular Research Group Duchenne natural history study

OBJECTIVE: We studied the effects of LTBP4 and SPP1 polymorphisms on age at loss of ambulation (LoA) in a multiethnic Duchenne muscular dystrophy (DMD) cohort. METHODS: We genotyped SPP1 rs28357094 and LTBP4 haplotype in 283 of 340 participants in the Cooperative International Neuromuscular Research Group Duchenne Natural History Study (CINRG-DNHS). Median ages at LoA were compared by Kaplan-Meier analysis and log-rank test. We controlled polymorphism analyses for concurrent effects of glucocorticoid corticosteroid (GC) treatment (time-varying Cox regression) and for population stratification (multidimensional scaling of genome-wide markers). RESULTS: Hispanic and South Asian participants (n=18, 41) lost ambulation 2.7 and 2 years earlier than Caucasian subjects (p=0.003, <0.001). The TG/GG genotype at SPP1 rs28357094 was associated to 1.2-year-earlier median LoA (p=0.048). This difference was greater (1.9 years, p=0.038) in GC-treated participants, whereas no difference was observed in untreated subjects. Cox regression confirmed a significant effect of SPP1 genotype in GC-treated participants (hazard ratio = 1.61, p=0.016). LTBP4 genotype showed a direction of association with age at LoA as previously reported, but it was not statistically significant. After controlling for population stratification, we confirmed a strong effect of LTBP4 genotype in Caucasians (2.4 years, p =0.024). Median age at LoA with the protective LTBP4 genotype in this cohort was 15.0 years, 16.0 for those who were treated with GC. INTERPRETATION: SPP1 rs28357094 acts as a pharmacodynamic biomarker of GC response, and LTBP4 haplotype modifies age at LoA in the CINRG-DNHS cohort. Adjustment for GC treatment and population stratification appears crucial in assessing genetic modifiers in DMDFil: Bello, Luca. Children's National Medical Center; Estados Unidos. Università di Padova; ItaliaFil: Kesari, Akanchha. Children's National Medical Center; Estados UnidosFil: Gordish Dressman, Heather. Children's National Medical Center; Estados UnidosFil: Cnaan, Avital. Children's National Medical Center; Estados Unidos. The George Washington University; Estados UnidosFil: Morgenroth, Lauren P.. Children's National Medical Center; Estados UnidosFil: Punetha, Jaya. Children's National Medical Center; Estados Unidos. The George Washington University; Estados UnidosFil: Duong, Tina. Children's National Medical Center; Estados UnidosFil: Henricson, Erik K.. University of California at Davis; Estados UnidosFil: Pegoraro, Elena. Università di Padova; ItaliaFil: McDonald, Craig M.. University of California at Davis; Estados UnidosFil: Hoffman, Eric P.. Children's National Medical Center; Estados Unidos. The George Washington University; Estados UnidosFil: Dubrovsky, Alberto. Cooperative International Neuromuscular Research Group Investigators; ArgentinaFil: Andreone, Luz. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Cooperative International Neuromuscular Research Group Investigators; Argentina. Fundación Favaloro; ArgentinaFil: Cooperative International Neuromuscular Research Group Investigators. No especifica

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically-developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3-16 years of age underwent eight walking/running activities, including five 25 meters walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-minute walk test (6MWT), a 100 meters fast-walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens

Large-scale serum protein biomarker discovery in Duchenne muscular dystrophy.

Serum biomarkers in Duchenne muscular dystrophy (DMD) may provide deeper insights into disease pathogenesis, suggest new therapeutic approaches, serve as acute read-outs of drug effects, and be useful as surrogate outcome measures to predict later clinical benefit. In this study a large-scale biomarker discovery was performed on serum samples from patients with DMD and age-matched healthy volunteers using a modified aptamer-based proteomics technology. Levels of 1,125 proteins were quantified in serum samples from two independent DMD cohorts: cohort 1 (The Parent Project Muscular Dystrophy-Cincinnati Children's Hospital Medical Center), 42 patients with DMD and 28 age-matched normal volunteers; and cohort 2 (The Cooperative International Neuromuscular Research Group, Duchenne Natural History Study), 51 patients with DMD and 17 age-matched normal volunteers. Forty-four proteins showed significant differences that were consistent in both cohorts when comparing DMD patients and healthy volunteers at a 1% false-discovery rate, a large number of significant protein changes for such a small study. These biomarkers can be classified by known cellular processes and by age-dependent changes in protein concentration. Our findings demonstrate both the utility of this unbiased biomarker discovery approach and suggest potential new diagnostic and therapeutic avenues for ameliorating the burden of DMD and, we hope, other rare and devastating diseases