scholarly journals Glue genes are subjected to diverse selective forces during Drosophila development

2021 ◽  
Author(s):  
Flora Borne ◽  
Rob J Kulathinal ◽  
Virginie Courtier-Orgogozo
Keyword(s):  
Codon Bias ◽  
Evolutionary Dynamics ◽  
Multiple Time ◽  
Selective Sweeps ◽  
Closely Related Species ◽  
Evolutionary Forces ◽  
Adult Fitness ◽  
Highly Expressed Genes ◽  
Selective Forces ◽  
Multiple Time Points

Molecular evolutionary studies usually focus on genes with clear roles in adult fitness or on developmental genes expressed at multiple time points during the life of the organism. Here, we examine the evolutionary dynamics of Drosophila glue genes, a set of eight genes tasked with a singular primary function during a specific developmental stage: the production of glue that allows animal pupa to attach to a substrate for several days during metamorphosis. Using phenotypic assays and integrating data from transcriptomics, PacBio genomes, and genetic variation from global populations, we explore the selective forces acting on the glue genes within the cosmopolitan D. melanogaster species and its five closely related species, D. simulans, D. sechellia, D. mauritiana, D. yakuba, and D. teissieri. We observe a three-fold difference in glue adhesion between the least and the most adhesive D. melanogaster strain, indicating a strong genetic component to phenotypic variation. These eight glue genes are among the most highly expressed genes in salivary glands yet they display no notable codon bias. New copies of Sgs3 and Sgs7 are found in D. yakuba and D. teissieri with the Sgs3 coding sequence evolving rapidly after duplication in the D. yakuba branch. Multiple sites along the various glue genes appear to be constrained. Our population genetics analysis in D. melanogaster suggests signs of local adaptive evolution for Sgs5 and Sgs5bis and traces of selective sweeps for Sgs1, Sgs3, Sgs7 and Sgs8. Our work shows that stage-specific genes can be subjected to various dynamic evolutionary forces.

scholarly journals A novel bioinformatics approach to reveal the role of circadian oscillations in AD development

2020 ◽  
Author(s):  
Zhiwei Ji ◽  
Dazhi Shang ◽  
Pora Kim ◽  
Mengyuan Yang ◽  
Sijia Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Evolutionary Dynamics ◽  
Expression Profiles ◽  
Circadian Variation ◽  
Gene Expression Profiles ◽  
Brain Regions ◽  
Multiple Time ◽  
Circadian Genes ◽  
Gene Expression Correlation ◽  
Multiple Time Points

AbstractAltered circadian gene expression may contribute to Alzheimer’s disease (AD) progression. Unfortunately, sampling the central nervous system (CNS) at multiple time points is not feasible. Moreover, there are no AD-related time-series transcriptome datasets available for studying these circadian patterns and their impacts on AD development. In this study, we introduce a novel computational platform, Event-driven Sample Ordering for Circadian Variation Detection (ESOCVD), to reveal rhythmic patterns of gene expression of AD using untimed transcriptome datasets. ESOCVD was applied to 20 untimed gene expression profiles of 16 brain regions from approximately 3000 AD patients in public transcriptome databases. Our analysis revealed five types of circadian alteration patterns in ~2,000 circadian genes in different brain regions of AD patients. Further analyses of additional databases confirmed that our analytical platform can be applied to identify the evolutionary dynamics of circadian variation during the process of AD development. Through the gene expression correlation analysis for our 8 circadian genes identified from AMP-AD MSBB cohorts, we identified stage-specifically enriched biological processes with anticipated context. Gene expression analysis of AD mouse brain tissues further substantiated the predictions of the ESOCVD model. In summary, ESOCVD is highly versatile in bridging circadian research and precision medicine.

scholarly journals Drug Resistance Evolution in HIV in the Late 1990s: Hard Sweeps, Soft Sweeps, Clonal Interference and the Accumulation of Drug Resistance Mutations

2020 ◽  
Vol 10 (4) ◽  
pp. 1213-1223
Author(s):  
Kadie-Ann Williams ◽  
Pleuni Pennings
Keyword(s):  
Drug Resistance ◽  
Evolutionary Dynamics ◽  
Evolutionary Medicine ◽  
Multiple Time ◽  
Resistance Mutations ◽  
Clonal Interference ◽  
Data Set ◽  
Resistance Evolution ◽  
Multiple Time Points ◽  
Viral Sequences

The evolution of drug resistance in pathogens such as HIV is an important and widely known example in the field of evolutionary medicine. Here, we focus on a unique data set from the late 1990s with multiple viral sequences from multiple time points in 118 patients. We study patterns of evolutionary dynamics in the viral populations in these patients who were treated with Reverse Transcriptase Inhibitors and Protease Inhibitors in the late 1990s. Specifically, we aim to visualize and analyze examples of population genetic processes such as selective sweeps and clonal interference. The figures and descriptions in this paper can be used in evolution and population genetics classes. We show and analyze a wide variety of patterns, specifically: soft sweeps, hard sweeps, softening sweeps and hardening sweeps, simultaneous sweeps, accumulation of mutations and clonal interference.

scholarly journals Physical activity levels among ovarian cancer survivors: a prospective longitudinal cohort study

2021 ◽  
pp. ijgc-2020-002107
Author(s):  
Tamara Jones ◽  
Carolina Sandler ◽  
Dimitrios Vagenas ◽  
Monika Janda ◽  
Andreas Obermair ◽  
...  
Keyword(s):  
Physical Activity ◽  
Ovarian Cancer ◽  
Stage Iv ◽  
Multiple Time ◽  
Activity Levels ◽  
Prospective Longitudinal Study ◽  
Physical Activity Advice ◽  
Physical Activity Levels ◽  
Multiple Time Points ◽  
Prospective Longitudinal

ObjectivePhysical activity following cancer diagnosis is associated with improved outcomes, including potential survival benefits, yet physical activity levels among common cancer types tend to decrease following diagnosis and remain low. Physical activity levels following diagnosis of less common cancers, such as ovarian cancer, are less known. The objectives of this study were to describe physical activity levels and to explore characteristics associated with physical activity levels in women with ovarian cancer from pre-diagnosis to 2 years post-diagnosis.MethodsAs part of a prospective longitudinal study, physical activity levels of women with ovarian cancer were assessed at multiple time points between pre-diagnosis and 2 years post-diagnosis. Physical activity levels and change in physical activity were described using metabolic equivalent task hours and minutes per week, and categorically (sedentary, insufficiently, or sufficiently active). Generalized Estimating Equations were used to explore whether participant characteristics were related to physical activity levels.ResultsA total of 110 women with ovarian cancer with a median age of 62 years (range 33–88) at diagnosis were included. 53–57% of the women were sufficiently active post-diagnosis, although average physical activity levels for the cohort were below recommended levels throughout the 2-year follow-up period (120–142.5min/week). A decrease or no change in post-diagnosis physical activity was reported by 44–60% of women compared with pre-diagnosis physical activity levels. Women diagnosed with stage IV disease, those earning a lower income, those receiving chemotherapy, and those currently smoking or working were more likely to report lower physical activity levels and had increased odds of being insufficiently active or sedentary.ConclusionsInterventions providing patients with appropriate physical activity advice and support for behavior change could potentially improve physical activity levels and health outcomes.

scholarly journals The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eileen M. Boyle ◽  
Shayu Deshpande ◽  
Ruslana Tytarenko ◽  
Cody Ashby ◽  
Yan Wang ◽  
...  
Keyword(s):  
Tumour Suppressor Genes ◽  
Multiple Time ◽  
Clonal Structure ◽  
Time To Progression ◽  
Novel Mutations ◽  
Evolutionary Patterns ◽  
Risk Of Progression ◽  
Multiple Time Points ◽  
Smoldering Myeloma ◽  
Copy Number Changes

AbstractSmoldering myeloma (SMM) is associated with a high-risk of progression to myeloma (MM). We report the results of a study of 82 patients with both targeted sequencing that included a capture of the immunoglobulin and MYC regions. By comparing these results to newly diagnosed myeloma (MM) we show fewer NRAS and FAM46C mutations together with fewer adverse translocations, del(1p), del(14q), del(16q), and del(17p) in SMM consistent with their role as drivers of the transition to MM. KRAS mutations are associated with a shorter time to progression (HR 3.5 (1.5–8.1), p = 0.001). In an analysis of change in clonal structure over time we studied 53 samples from nine patients at multiple time points. Branching evolutionary patterns, novel mutations, biallelic hits in crucial tumour suppressor genes, and segmental copy number changes are key mechanisms underlying the transition to MM, which can precede progression and be used to guide early intervention strategies.

scholarly journals Use of TanDEM-X and SRTM-C Data for Detection of Deforestation Caused by Bark Beetle in Central European Mountains

2021 ◽  
Vol 13 (15) ◽  
pp. 3042
Author(s):  
Kateřina Gdulová ◽  
Jana Marešová ◽  
Vojtěch Barták ◽  
Marta Szostak ◽  
Jaroslav Červenka ◽  
...  
Keyword(s):  
Bark Beetle ◽  
Synergistic Effects ◽  
Canopy Height ◽  
Surface Model ◽  
Multiple Time ◽  
Central European ◽  
Time Points ◽  
Bohemian Forest ◽  
Multiple Time Points ◽  
Surrounding Areas

The availability of global digital elevation models (DEMs) from multiple time points allows their combination for analysing vegetation changes. The combination of models (e.g., SRTM and TanDEM-X) can contain errors, which can, due to their synergistic effects, yield incorrect results. We used a high-resolution LiDAR-derived digital surface model (DSM) to evaluate the accuracy of canopy height estimates of the aforementioned global DEMs. In addition, we subtracted SRTM and TanDEM-X data at 90 and 30 m resolutions, respectively, to detect deforestation caused by bark beetle disturbance and evaluated the associations of their difference with terrain characteristics. The study areas covered three Central European mountain ranges and their surrounding areas: Bohemian Forest, Erzgebirge, and Giant Mountains. We found that vertical bias of SRTM and TanDEM-X, relative to the canopy height, is similar with negative values of up to −2.5 m and LE90s below 7.8 m in non-forest areas. In forests, the vertical bias of SRTM and TanDEM-X ranged from −0.5 to 4.1 m and LE90s from 7.2 to 11.0 m, respectively. The height differences between SRTM and TanDEM-X show moderate dependence on the slope and its orientation. LE90s for TDX-SRTM differences tended to be smaller for east-facing than for west-facing slopes, and varied, with aspect, by up to 1.5 m in non-forest areas and 3 m in forests, respectively. Finally, subtracting SRTM and NASA DEMs from TanDEM-X and Copernicus DEMs, respectively, successfully identified large areas of deforestation caused by hurricane Kyril in 2007 and a subsequent bark beetle disturbance in the Bohemian Forest. However, local errors in TanDEM-X, associated mainly with forest-covered west-facing slopes, resulted in erroneous identification of deforestation. Therefore, caution is needed when combining SRTM and TanDEM-X data in multitemporal studies in a mountain environment. Still, we can conclude that SRTM and TanDEM-X data represent suitable near global sources for the identification of deforestation in the period between the time points of their acquisition.

scholarly journals Associations of Binge Drinking With Vascular Brain Injury and Atrophy in Older American Indians: The Strong Heart Study

2021 ◽  
Vol 33 (7-8_suppl) ◽  
pp. 51S-59S
Author(s):  
Jordan P. Lewis ◽  
Astrid M. Suchy-Dicey ◽  
Carolyn Noonan ◽  
Valarie Blue Bird Jernigan ◽  
Jason G. Umans ◽  
...  
Keyword(s):  
Brain Injury ◽  
Binge Drinking ◽  
American Indians ◽  
Multiple Time ◽  
Heart Study ◽  
Neurological Risk ◽  
The Us ◽  
Large Cohort Study ◽  
Magnetic Resonance Imaging Mri ◽  
Multiple Time Points

Objectives: American Indians (AIs) generally consume less alcohol than the US general population; however, the prevalence of alcohol use disorder is higher. This is the first large cohort study to examine binge drinking as a risk factor for vascular brain injury (VBI). Methods: We used linear and Poisson regression to examine the association of self-reported binge drinking with VBI, measured via magnetic resonance imaging (MRI), in 817 older AIs who participated in the Strong Heart and Cerebrovascular Disease and Its Consequences in American Indians studies. Results: Any binge drinking at multiple time-points was associated with increased sulcal (β = 0.360, 95% CI [0.079, 0.641]) and ventricle dilatation (β = 0.512, 95% CI [0.174, 0.850]) compared to no binge drinking. Discussion: These observed associations are consistent with previous findings. Identifying how binge drinking may contribute to VBI in older AIs may suggest modifiable health behaviors for neurological risk reduction and disease prevention.

Chromosomal Patterns of Microsatellite Variability Contrast Sharply in African and Non-African Populations of Drosophila melanogaster

Genetics ◽  
2002 ◽  
Vol 160 (1) ◽  
pp. 247-256
Author(s):  
M Kauer ◽  
B Zangerl ◽  
D Dieringer ◽  
C Schlötterer
Keyword(s):  
Chromosomal Polymorphism ◽  
Background Selection ◽  
Selective Sweeps ◽  
X Chromosomes ◽  
Evolutionary Forces ◽  
Relative Contribution ◽  
African Populations ◽  
Neutral Variation ◽  
Colonization Process ◽  
The Subject

Abstract Levels of neutral variation are influenced by background selection and hitchhiking. The relative contribution of these evolutionary forces to the distribution of neutral variation is still the subject of ongoing debates. Using 133 microsatellites, we determined levels of variability on X chromosomes and autosomes in African and non-African D. melanogaster populations. In the ancestral African populations microsatellite variability was higher on X chromosomes than on autosomes. In non-African populations X-linked polymorphism is significantly more reduced than autosomal variation. In non-African populations we observed a significant positive correlation between X chromosomal polymorphism and recombination rate. These results are consistent with the interpretation that background selection shapes levels of neutral variability in the ancestral populations, while the pattern in derived populations is determined by multiple selective sweeps during the colonization process. Further research, however, is required to investigate the influence of inversion polymorphisms and unequal sex ratios.

scholarly journals Effect of genome composition and codon bias on infectious bronchitis virus evolution and adaptation to target tissues

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Giovanni Franzo ◽  
Claudia Maria Tucciarone ◽  
Matteo Legnardi ◽  
Mattia Cecchinato
Keyword(s):  
Codon Usage ◽  
Codon Bias ◽  
Synonymous Codon ◽  
Synonymous Codon Usage ◽  
Accessory Proteins ◽  
Effective Number ◽  
Genome Composition ◽  
Infectious Bronchitis ◽  
Selective Forces ◽  
Effective Number Of Codons

Abstract Background Infectious bronchitis virus (IBV) is one of the most relevant viruses affecting the poultry industry, and several studies have investigated the factors involved in its biological cycle and evolution. However, very few of those studies focused on the effect of genome composition and the codon bias of different IBV proteins, despite the remarkable increase in available complete genomes. In the present study, all IBV complete genomes were downloaded (n = 383), and several statistics representative of genome composition and codon bias were calculated for each protein-coding sequence, including but not limited to, the nucleotide odds ratio, relative synonymous codon usage and effective number of codons. Additionally, viral codon usage was compared to host codon usage based on a collection of highly expressed genes in IBV target and nontarget tissues. Results The results obtained demonstrated a significant difference among structural, non-structural and accessory proteins, especially regarding dinucleotide composition, which appears under strong selective forces. In particular, some dinucleotide pairs, such as CpG, a probable target of the host innate immune response, are underrepresented in genes coding for pp1a, pp1ab, S and N. Although genome composition and dinucleotide bias appear to affect codon usage, additional selective forces may act directly on codon bias. Variability in relative synonymous codon usage and effective number of codons was found for different proteins, with structural proteins and polyproteins being more adapted to the codon bias of host target tissues. In contrast, accessory proteins had a more biased codon usage (i.e., lower number of preferred codons), which might contribute to the regulation of their expression level and timing throughout the cell cycle. Conclusions The present study confirms the existence of selective forces acting directly on the genome and not only indirectly through phenotype selection. This evidence might help understanding IBV biology and in developing attenuated strains without affecting the protein phenotype and therefore immunogenicity.

scholarly journals Inferring time series chromatin states for promoter-enhancer pairs based on Hi-C data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Henriette Miko ◽  
Yunjiang Qiu ◽  
Bjoern Gaertner ◽  
Maike Sander ◽  
Uwe Ohler
Keyword(s):  
Time Series ◽  
Histone Modifications ◽  
Gene Activation ◽  
Expectation Maximization Algorithm ◽  
Chromatin State ◽  
Open Chromatin ◽  
Multiple Time ◽  
Enhancer Activity ◽  
Chromatin States ◽  
Multiple Time Points

Abstract Background Co-localized combinations of histone modifications (“chromatin states”) have been shown to correlate with promoter and enhancer activity. Changes in chromatin states over multiple time points (“chromatin state trajectories”) have previously been analyzed at promoter and enhancers separately. With the advent of time series Hi-C data it is now possible to connect promoters and enhancers and to analyze chromatin state trajectories at promoter-enhancer pairs. Results We present TimelessFlex, a framework for investigating chromatin state trajectories at promoters and enhancers and at promoter-enhancer pairs based on Hi-C information. TimelessFlex extends our previous approach Timeless, a Bayesian network for clustering multiple histone modification data sets at promoter and enhancer feature regions. We utilize time series ATAC-seq data measuring open chromatin to define promoters and enhancer candidates. We developed an expectation-maximization algorithm to assign promoters and enhancers to each other based on Hi-C interactions and jointly cluster their feature regions into paired chromatin state trajectories. We find jointly clustered promoter-enhancer pairs showing the same activation patterns on both sides but with a stronger trend at the enhancer side. While the promoter side remains accessible across the time series, the enhancer side becomes dynamically more open towards the gene activation time point. Promoter cluster patterns show strong correlations with gene expression signals, whereas Hi-C signals get only slightly stronger towards activation. The code of the framework is available at https://github.com/henriettemiko/TimelessFlex. Conclusions TimelessFlex clusters time series histone modifications at promoter-enhancer pairs based on Hi-C and it can identify distinct chromatin states at promoter and enhancer feature regions and their changes over time.

scholarly journals Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidates for targeted treatment

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hua Sun ◽  
Song Cao ◽  
R. Jay Mashl ◽  
Chia-Kuei Mo ◽  
Simone Zaccaria ◽  
...  
Keyword(s):  
Human Tumors ◽  
Multiple Time ◽  
Cancer Treatments ◽  
Whole Genome Duplications ◽  
Patient Derived Xenograft ◽  
Genome Duplications ◽  
Genomic Characterization ◽  
Cancer Types ◽  
Multiple Time Points ◽  
Pdx Models

AbstractDevelopment of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs’ recapitulation of human tumors.

Sign in / Sign up

Export Citation Format

Share Document