scholarly journals Transcriptome sequencing of black grouse ( Tetrao tetrix ) for immune gene discovery and microsatellite development

Open Biology ◽  
2012 ◽  
Vol 2 (4) ◽  
pp. 120054 ◽  
Author(s):  
Biao Wang ◽  
Robert Ekblom ◽  
Todd A. Castoe ◽  
Eleanor P. Jones ◽  
Radoslav Kozma ◽  
...  
Keyword(s):  
Large Scale ◽  
Expressed Sequence Tag ◽  
Gene Discovery ◽  
Bird Species ◽  
Preliminary Test ◽  
Immune Gene ◽  
Large Set ◽  
Black Grouse ◽  
Immune Genes ◽  
Tetrao Tetrix

The black grouse ( Tetrao tetrix ) is a galliform bird species that is important for both ecological studies and conservation genetics. Here, we report the sequencing of the spleen transcriptome of black grouse using 454 GS FLX Titanium sequencing. We performed a large-scale gene discovery analysis with a focus on genes that might be related to fitness in this species and also identified a large set of microsatellites. In total, we obtained 182 179 quality-filtered sequencing reads that we assembled into 9035 contigs. Using these contigs and 15 794 length-filtered (greater than 200 bp) singletons, we identified 7762 transcripts that appear to be homologues of chicken genes. A specific BLAST search with an emphasis on immune genes found 308 homologous chicken genes that have immune function, including ten major histocompatibility complex-related genes located on chicken chromosome 16. We also identified 1300 expressed sequence tag microsatellites and were able to design suitable flanking primers for 526 of these. A preliminary test of the polymorphism of the microsatellites found 10 polymorphic microsatellites of the 102 tested. Genomic resources generated in this study should greatly benefit future ecological, evolutionary and conservation genetic studies on this species.

scholarly journals Avian Immunome DB: an example of a user-friendly interface for extracting genetic information

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Ralf C. Mueller ◽  
Nicolai Mallig ◽  
Jacqueline Smith ◽  
Lél Eöery ◽  
Richard I. Kuo ◽  
...  
Keyword(s):  
Bird Species ◽  
Gene Symbol ◽  
Immune Gene ◽  
Command Line ◽  
Biological Processes ◽  
Command Line Interface ◽  
Target List ◽  
Immune Genes ◽  
Front End ◽  
Gene Symbols

Abstract Background Genomic and genetic studies often require a target list of genes before conducting any hypothesis testing or experimental verification. With the ever-growing number of sequenced genomes and a variety of different annotation strategies, comes the potential for ambiguous gene symbols, making it cumbersome to capture the “correct” set of genes. In this article, we present and describe the Avian Immunome DB (Avimm) for easy gene property extraction as exemplified by avian immune genes. The avian immune system is characterised by a cascade of complex biological processes underlaid by more than 1000 different genes. It is a vital trait to study particularly in birds considering that they are a significant driver in spreading zoonotic diseases. With the completion of phase II of the B10K (“Bird 10,000 Genomes”) consortium’s whole-genome sequencing effort, we have included 363 annotated bird genomes in addition to other publicly available bird genome data which serve as a valuable foundation for Avimm. Construction and content A relational database with avian immune gene evidence from Gene Ontology, Ensembl, UniProt and the B10K consortium has been designed and set up. The foundation stone or the “seed” for the initial set of avian immune genes is based on the well-studied model organism chicken (Gallus gallus). Gene annotations, different transcript isoforms, nucleotide sequences and protein information, including amino acid sequences, are included. Ambiguous gene names (symbols) are resolved within the database and linked to their canonical gene symbol. Avimm is supplemented by a command-line interface and a web front-end to query the database. Utility and discussion The internal mapping of unique gene symbol identifiers to canonical gene symbols allows for an ambiguous gene property search. The database is organised within core and feature tables, which makes it straightforward to extend for future purposes. The database design is ready to be applied to other taxa or biological processes. Currently, the database contains 1170 distinct avian immune genes with canonical gene symbols and 612 synonyms across 363 bird species. While the command-line interface readily integrates into bioinformatics pipelines, the intuitive web front-end with download functionality offers sophisticated search functionalities and tracks the origin for each record. Avimm is publicly accessible at https://avimm.ab.mpg.de.

Size and spacing of grouse leks: comparing capercaillie (Tetrao urogallus) and black grouse (Tetrao tetrix) in two contrasting Eurasian boreal forest landscapes

2009 ◽  
Vol 87 (11) ◽  
pp. 1032-1043 ◽  
Author(s):  
Jørund Rolstad ◽  
Per Wegge ◽  
Andrey V. Sivkov ◽  
Olav Hjeljord ◽  
Ken Olaf Storaunet
Keyword(s):  
Forest Dynamics ◽  
Large Scale ◽  
Landscape Scale ◽  
Tetrao Urogallus ◽  
Black Grouse ◽  
Surrounding Area ◽  
Social Attraction ◽  
Tetrao Tetrix ◽  
Habitat Affinities

Capercaillie ( Tetrao urogallus L., 1758) and black grouse ( Tetrao tetrix L., 1758 (= Lyrurus tetrix (L., 1758))) are two sympatric Eurasian lekking grouse species that differ markedly in habitat affinities and social organization. We examined how size and spacing of leks in pristine (Russia) and managed (Norway) forests were related to habitat and social behavior. Leks of both species were larger and spaced farther apart in the pristine landscape. Capercaillie leks were regularly spaced at 2–3 km distance, increasing with lek size, which in turn was positively related to the amount of middle-aged and older forests in the surrounding area. Black grouse leks were irregularly distributed at shorter distances of 1–2 km, with lek size explained by the size of the open bog arena and the amount of open habitat in the surroundings. At the landscape scale, spatial distribution of open bogs and social attraction among male black grouse caused leks to be more aggregated, whereas mutual avoidance in male capercaillie caused leks to be spaced out. In the pristine landscape, large-scale and long-term changes in forest dynamics owing to wildfires, combined with an aggregated pattern of huge bog complexes, presumably provide both grouse species with enough time and space to build up bigger lek populations than in the managed landscape.

Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model

2019 ◽  
Author(s):  
Ryther Anderson ◽  
Achay Biong ◽  
Diego Gómez-Gualdrón
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Molecular Simulation ◽  
Large Scale ◽  
Learning Model ◽  
Operating Conditions ◽  
Small Subset ◽  
Screening Methods ◽  
Large Set ◽  
Metal Organic

<div>Tailoring the structure and chemistry of metal-organic frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), molecular simulation, such as grand canonical Monte Carlo (GCMC), has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent experiments to focus only on a small subset of the most promising MOFs. In many instances, however, even molecular simulation becomes prohibitively time consuming, underscoring the need for alternative screening methods, such as machine learning, to precede molecular simulation efforts. In this study, as a proof of concept, we trained a neural network as the first example of a machine learning model capable of predicting full adsorption isotherms of different molecules not included in the training of the model. To achieve this, we trained our neural network only on alchemical species, represented only by their geometry and force field parameters, and used this neural network to predict the loadings of real adsorbates. We focused on predicting room temperature adsorption of small (one- and two-atom) molecules relevant to chemical separations. Namely, argon, krypton, xenon, methane, ethane, and nitrogen. However, we also observed surprisingly promising predictions for more complex molecules, whose properties are outside the range spanned by the alchemical adsorbates. Prediction accuracies suitable for large-scale screening were achieved using simple MOF (e.g. geometric properties and chemical moieties), and adsorbate (e.g. forcefield parameters and geometry) descriptors. Our results illustrate a new philosophy of training that opens the path towards development of machine learning models that can predict the adsorption loading of any new adsorbate at any new operating conditions in any new MOF.</div>

scholarly journals Identification and development of an independent immune-related genes prognostic model for breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lin Chen ◽  
Yuxiang Dong ◽  
Yitong Pan ◽  
Yuhan Zhang ◽  
Ping Liu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Validation Dataset ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Immune Related Genes

Abstract Background Breast cancer is one of the main malignant tumors that threaten the lives of women, which has received more and more clinical attention worldwide. There are increasing evidences showing that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients and construct an immune-related genes prognostic index. Methods The list of 2498 immune genes was obtained from ImmPort database. In addition, gene expression data and clinical characteristics data of BC patients were also obtained from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P < 0.05 was considered to be statistically significant. Results In total, 556 immune genes were differentially expressed between normal tissues and BC tissues (p < 0. 05). According to the univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P < 0.05). Finally, a 15 immune genes risk scores model was established. All patients were divided into high- and low-groups. KM survival analysis revealed that high immune risk scores represented worse survival (p < 0.001). ROC curve indicated that the immune genes risk scores model had a good reliability in predicting prognosis (5-year OS, AUC = 0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC = 0.685, 5-year OS AUC = 0.717, P = 0.00048). Moreover, the immune risk signature was proved to be an independent prognostic factor for BC patients. Finally, it was found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways. Conclusion In conclusion, our study provides a new perspective for the expression of immune genes in BC. The constructed model has potential value for the prognostic prediction of BC patients and may provide some references for the clinical precision immunotherapy of patients.

scholarly journals Prevalence and genetic diversity of avian haemosporidian parasites in wild bird species of the order Columbiformes

2021 ◽  
Author(s):  
Yvonne R. Schumm ◽  
Dimitris Bakaloudis ◽  
Christos Barboutis ◽  
Jacopo G. Cecere ◽  
Cyril Eraud ◽  
...  
Keyword(s):  
Host Species ◽  
Large Scale ◽  
Phylogenetic Reconstruction ◽  
Bird Species ◽  
Avian Species ◽  
Blood Parasites ◽  
Migration Strategy ◽  
Haemosporidian Parasites ◽  
Multiplex Pcr Assay ◽  
And Migration

AbstractDiseases can play a role in species decline. Among them, haemosporidian parasites, vector-transmitted protozoan parasites, are known to constitute a risk for different avian species. However, the magnitude of haemosporidian infection in wild columbiform birds, including strongly decreasing European turtle doves, is largely unknown. We examined the prevalence and diversity of haemosporidian parasites Plasmodium, Leucocytozoon and subgenera Haemoproteus and Parahaemoproteus in six species of the order Columbiformes during breeding season and migration by applying nested PCR, one-step multiplex PCR assay and microscopy. We detected infections in 109 of the 259 screened individuals (42%), including 15 distinct haemosporidian mitochondrial cytochrome b lineages, representing five H. (Haemoproteus), two H. (Parahaemoproteus), five Leucocytozoon and three Plasmodium lineages. Five of these lineages have never been described before. We discriminated between single and mixed infections and determined host species-specific prevalence for each parasite genus. Observed differences among sampled host species are discussed with reference to behavioural characteristics, including nesting and migration strategy. Our results support previous suggestions that migratory birds have a higher prevalence and diversity of blood parasites than resident or short-distance migratory species. A phylogenetic reconstruction provided evidence for H. (Haemoproteus) as well as H. (Parahaemoproteus) infections in columbiform birds. Based on microscopic examination, we quantified parasitemia, indicating the probability of negative effects on the host. This study provides a large-scale baseline description of haemosporidian infections of wild birds belonging to the order Columbiformes sampled in the northern hemisphere. The results enable the monitoring of future changes in parasite transmission areas, distribution and diversity associated with global change, posing a potential risk for declining avian species as the European turtle dove.

scholarly journals A SNP assay for assessing diversity in immune genes in the honey bee (Apis mellifera L.)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dora Henriques ◽  
Ana R. Lopes ◽  
Nor Chejanovsky ◽  
Anne Dalmon ◽  
Mariano Higes ◽  
...  
Keyword(s):  
Apis Mellifera ◽  
Honey Bee ◽  
Large Scale ◽  
Medium Density ◽  
Nucleotide Polymorphisms ◽  
Functional Variation ◽  
Immune Genes ◽  
Wide Range ◽  
Scale Range ◽  
Innate Immune Genes

AbstractWith a growing number of parasites and pathogens experiencing large-scale range expansions, monitoring diversity in immune genes of host populations has never been so important because it can inform on the adaptive potential to resist the invaders. Population surveys of immune genes are becoming common in many organisms, yet they are missing in the honey bee (Apis mellifera L.), a key managed pollinator species that has been severely affected by biological invasions. To fill the gap, here we identified single nucleotide polymorphisms (SNPs) in a wide range of honey bee immune genes and developed a medium-density assay targeting a subset of these genes. Using a discovery panel of 123 whole-genomes, representing seven A. mellifera subspecies and three evolutionary lineages, 180 immune genes were scanned for SNPs in exons, introns (< 4 bp from exons), 3’ and 5´UTR, and < 1 kb upstream of the transcription start site. After application of multiple filtering criteria and validation, the final medium-density assay combines 91 quality-proved functional SNPs marking 89 innate immune genes and these can be readily typed using the high-sample-throughput iPLEX MassARRAY system. This medium-density-SNP assay was applied to 156 samples from four countries and the admixture analysis clustered the samples according to their lineage and subspecies, suggesting that honey bee ancestry can be delineated from functional variation. In addition to allowing analysis of immunogenetic variation, this newly-developed SNP assay can be used for inferring genetic structure and admixture in the honey bee.

Sign in / Sign up

Export Citation Format

Share Document