African trypanosomes of the sub-genus Trypanozoon) are eukaryotic parasitesthat cause disease in either humans or livestock. The development of genomic resources can be of great use to those interested in studying and controlling the spread of these trypanosomes. Here we present a large comparative analysis of Trypanozoon whole genomes, 83 in total, including human and animal infective African trypanosomes: 21 T. brucei brucei, 22 T. b. gambiense, 35 T. b. rhodesiense and 4 T. evansi strains, of which 21 were from Uganda. We constructed a maximum likelihood phylogeny based on 162,210 single nucleotide polymorphisms (SNPs.) The three Trypanosoma brucei sub-species and Trypanosoma evansi are not monophyletic, confirming earlier studies that indicated high similarity among Trypanosoma "sub-species". We also used discriminant analysis of principal components (DAPC) on the same set of SNPs, identifying seven genetic clusters. These clusters do not correspond well with existing taxonomic classifications, in agreement with the phylogenetic analysis. Geographic origin is reflected in both the phylogeny and clustering analysis. Finally, we used sparse linear discriminant analysis to rank SNPs by their informativeness in differentiating the strains in our data set. As few as 84 SNPs can completely distinguish the strains used in our study, and discriminant analysis was still able to detect genetic structure using as few as 10 SNPs. Our results reinforce earlier results of high genetic similarity between the African Trypanozoon. Despite this, a small subset of SNPs can be used to identify genetic markers that can be used for strain identification or other epidemiological investigations.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5636163PMC
http://dx.doi.org/10.1371/journal.pntd.0005949DOI Listing

Publication Analysis

Top Keywords

discriminant analysis
12
african trypanozoon
8
markers strain
8
strain identification
8
african trypanosomes
8
set snps
8
analysis
6
snps
6
genomic analyses
4
african
4

Similar Publications

Background/purpose: In this study, we utilized magnetic resonance imaging data of the temporomandibular joint, collected from the Division of Oral and Maxillofacial Surgery at Taipei Veterans General Hospital. Our research focuses on the classification and severity analysis of temporomandibular joint disease using convolutional neural networks.

Materials And Methods: In gray-scale image series, the most critical features often lie within the articular disc cartilage, situated at the junction of the temporal bone and the condyles.

View Article and Find Full Text PDF

Objective: To investigate the roles of fecal short-chain fatty acids (SCFAs) in polycystic ovary syndrome (PCOS).

Methods: The levels of SCFAs (acetate, propionate, and butyrate) in 83 patients with PCOS and 63 controls were measured, and their relationships with various metabolic parameters were analyzed. Intestinal microbiome analysis was conducted to identify relevant bacteria.

View Article and Find Full Text PDF

Introduction: This research is focused on early detection of Alzheimer's disease (AD) using a multiscale feature fusion framework, combining biomarkers from memory, vision, and speech regions extracted from magnetic resonance imaging and positron emission tomography images.

Methods: Using 2D gray level co-occurrence matrix (2D-GLCM) texture features, volume, standardized uptake value ratios (SUVR), and obesity from different neuroimaging modalities, the study applies various classifiers, demonstrating a feature importance analysis in each region of interest. The research employs four classifiers, namely linear support vector machine, linear discriminant analysis, logistic regression (LR), and logistic regression with stochastic gradient descent (LRSGD) classifiers, to determine feature importance, leading to subsequent validation using a probabilistic neural network classifier.

View Article and Find Full Text PDF

Background: Nurses' competency in pain management is essential for effectively alleviating patients' acute pain, controlling chronic pain, and promoting patient recovery. However, reliable tools for evaluating these competencies across different clinical specialties and healthcare settings are lacking. This study aimed to develop and validate a Pain Management Competency Scale for Nurses (PMCSN) and to assess the pain management competencies of nurses in China through a nationwide survey.

View Article and Find Full Text PDF

Background: With the rapid spread of Corona Virus Disease 2019 (COVID-19) in China, police officers were undergoing higher job stress, which made them physically and mentally exhausted, eventually leading to job burnout. The research aims to explore the mediating role of social support, psychological resilience, and sleep quality in the relationship between perceived stress and burnout.

Methods: Data collection was based on multistage cluster random sampling of police in Wuhan, China, from June 2021 to October 2022.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!