scholarly journals Quantitative comparison of the anterior-posterior patterning system in the embryos of five Drosophila species

2018 ◽  
Author(s):  
Zeba Wunderlich ◽  
Charless C. Fowlkes ◽  
Kelly B. Eckenrode ◽  
Meghan D. J. Bragdon ◽  
Arash Abiri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Expression Patterns ◽  
Evolutionary Developmental Biology ◽  
Drosophila Virilis ◽  
Gene Expression Patterns ◽  
Data Sets ◽  
Developmental Gene ◽  
Regulatory Dna ◽  
Anterior Posterior

AbstractComplex spatiotemporal gene expression patterns direct the development of the fertilized egg into an adult animal. Comparisons across species show that, in spite of changes in the underlying regulatory DNA sequence, developmental programs can be maintained across millions of years of evolution. Reciprocally, changes in gene expression can be used to generate morphological novelty. Distinguishing between changes in regulatory DNA that lead to changes in gene expression and those that do not is therefore a central goal of evolutionary developmental biology. Quantitative, spatially-resolved measurements of developmental gene expression patterns play a crucial role in this goal, enabling the detection of subtle phenotypic differences between species and the development of computations models that link the sequence of regulatory DNA to expression patterns. Here we report the generation of two atlases of cellular resolution gene expression measurements for the primary anterior-posterior patterning genes in Drosophila simulans and Drosophila virilis. By combining these data sets with existing atlases for three other Drosophila species, we detect subtle differences in the gene expression patterns and dynamics driving the highly conserved axis patterning system and delineate inter-species differences in the embryonic morphology. These data sets will be a resource for future modeling studies of the evolution of developmental gene regulatory networks.

scholarly journals Embryology of the lamprey and evolution of the vertebrate jaw: insights from molecular and developmental perspectives

2001 ◽  
Vol 356 (1414) ◽  
pp. 1615-1632 ◽  
Author(s):  
Shigeru Kuratani ◽  
Yoshiaki Nobusada ◽  
Naoto Horigome ◽  
Yasuyo Shigetani
Keyword(s):  
Gene Expression ◽  
Nasal Septum ◽  
Expression Patterns ◽  
Regulatory Gene ◽  
Evolutionary Developmental Biology ◽  
Gene Expression Patterns ◽  
Upper Lip ◽  
Jaw Apparatus ◽  
Equivalent Site ◽  
Embryonic Structure

Evolution of the vertebrate jaw has been reviewed and discussed based on the developmental pattern of the Japanese marine lamprey, Lampetra japonica . Though it never forms a jointed jaw apparatus, the L. japonica embryo exhibits the typical embryonic structure as well as the conserved regulatory gene expression patterns of vertebrates. The lamprey therefore shares the phylotype of vertebrates, the conserved embryonic pattern that appears at pharyngula stage, rather than representing an intermediate evolutionary state. Both gnathostomes and lampreys exhibit a tripartite configuration of the rostral–most crest–derived ectomesenchyme, each part occupying an anatomically equivalent site. Differentiated oral structure becomes apparent in post–pharyngula development. Due to the solid nasohypophyseal plate, the post–optic ectomesenchyme of the lamprey fails to grow rostromedially to form the medial nasal septum as in gnathostomes, but forms the upper lip instead. The gnathostome jaw may thus have arisen through a process of ontogenetic repatterning, in which a heterotopic shift of mesenchyme–epithelial relationships would have been involved. Further identification of shifts in tissue interaction and expression of regulatory genes are necessary to describe the evolution of the jaw fully from the standpoint of evolutionary developmental biology.

scholarly journals The Ontology of the Amphioxus Anatomy and Life Cycle (AMPHX)

2021 ◽  
Vol 9 ◽  
Author(s):  
Stephanie Bertrand ◽  
João E. Carvalho ◽  
Delphine Dauga ◽  
Nicolas Matentzoglu ◽  
Vladimir Daric ◽  
...  
Keyword(s):  
Gene Expression ◽  
Scientific Community ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Evolutionary Developmental Biology ◽  
Model Organisms ◽  
Gene Expression Patterns ◽  
Marine Animal ◽  
Computable Representation ◽  
Different Parts

An ontology is a computable representation of the different parts of an organism and its different developmental stages as well as the relationships between them. The ontology of model organisms is therefore a fundamental tool for a multitude of bioinformatics and comparative analyses. The cephalochordate amphioxus is a marine animal representing the earliest diverging evolutionary lineage of chordates. Furthermore, its morphology, its anatomy and its genome can be considered as prototypes of the chordate phylum. For these reasons, amphioxus is a very important animal model for evolutionary developmental biology studies aimed at understanding the origin and diversification of vertebrates. Here, we have constructed an amphioxus ontology (AMPHX) which combines anatomical and developmental terms and includes the relationships between these terms. AMPHX will be used to annotate amphioxus gene expression patterns as well as phenotypes. We encourage the scientific community to adopt this amphioxus ontology and send recommendations for future updates and improvements.

scholarly journals Similarities of developmental gene expression changes in the brain between human and experimental animals: rhesus monkey, mouse, Zebrafish, and Drosophila

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ryuichi Nakajima ◽  
Hideo Hagihara ◽  
Tsuyoshi Miyakawa
Keyword(s):  
Gene Expression ◽  
Animal Models ◽  
Rhesus Monkey ◽  
Rhesus Monkeys ◽  
Expression Patterns ◽  
Developmental Changes ◽  
Gene Expression Patterns ◽  
Developmental Gene ◽  
Developmental Gene Expression ◽  
The Brain

Abstract Aim Experimental animals, such as non-human primates (NHPs), mice, Zebrafish, and Drosophila, are frequently employed as models to gain insights into human physiology and pathology. In developmental neuroscience and related research fields, information about the similarities of developmental gene expression patterns between animal models and humans is vital to choose what animal models to employ. Here, we aimed to statistically compare the similarities of developmental changes of gene expression patterns in the brains of humans with those of animal models frequently used in the neuroscience field. Methods The developmental gene expression datasets that we analyzed consist of the fold-changes and P values of gene expression in the brains of animals of various ages compared with those of the youngest postnatal animals available in the dataset. By employing the running Fisher algorithm in a bioinformatics platform, BaseSpace, we assessed similarities between the developmental changes of gene expression patterns in the human (Homo sapiens) hippocampus with those in the dentate gyrus (DG) of the rhesus monkey (Macaca mulatta), the DG of the mouse (Mus musculus), the whole brain of Zebrafish (Danio rerio), and the whole brain of Drosophila (D. melanogaster). Results Among all possible comparisons of different ages and animals in developmental changes in gene expression patterns within the datasets, those between rhesus monkeys and mice were highly similar to those of humans with significant overlap P-value as assessed by the running Fisher algorithm. There was the highest degree of gene expression similarity between 40–59-year-old humans and 6–12-year-old rhesus monkeys (overlap P-value = 2.1 × 10− 72). The gene expression similarity between 20–39-year-old humans and 29-day-old mice was also significant (overlap P = 1.1 × 10− 44). Moreover, there was a similarity in developmental changes of gene expression patterns between 1–2-year-old Zebrafish and 40–59-year-old humans (Overlap P-value = 1.4 × 10− 6). The overlap P-value of developmental gene expression patterns between Drosophila and humans failed to reach significance (30 days Drosophila and 6–11-year-old humans; overlap P-value = 0.0614). Conclusions These results indicate that the developmental gene expression changes in the brains of the rhesus monkey, mouse, and Zebrafish recapitulate, to a certain degree, those in humans. Our findings support the idea that these animal models are a valid tool for investigating the development of the brain in neurophysiological and neuropsychiatric studies.

scholarly journals scSensitiveGeneDefine: sensitive gene detection in single-cell RNA sequencing data by Shannon entropy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zechuan Chen ◽  
Zeruo Yang ◽  
Xiaojun Yuan ◽  
Xiaoming Zhang ◽  
Pei Hao
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Shannon Entropy ◽  
Expression Patterns ◽  
Ground Truth ◽  
Unsupervised Clustering ◽  
Gene Expression Patterns ◽  
Data Sets ◽  
Single Cell Rna Sequencing

Abstract Background Single-cell RNA sequencing (scRNA-seq) is the most widely used technique to obtain gene expression profiles from complex tissues. Cell subsets and developmental states are often identified via differential gene expression patterns. Most of the single-cell tools utilized highly variable genes to annotate cell subsets and states. However, we have discovered that a group of genes, which sensitively respond to environmental stimuli with high coefficients of variation (CV), might impose overwhelming influences on the cell type annotation. Result In this research, we developed a method, based on the CV-rank and Shannon entropy, to identify these noise genes, and termed them as “sensitive genes”. To validate the reliability of our methods, we applied our tools in 11 single-cell data sets from different human tissues. The results showed that most of the sensitive genes were enriched pathways related to cellular stress response. Furthermore, we noticed that the unsupervised result was closer to the ground-truth cell labels, after removing the sensitive genes detected by our tools. Conclusion Our study revealed the prevalence of stochastic gene expression patterns in most types of cells, compared the differences among cell marker genes, housekeeping genes (HK genes), and sensitive genes, demonstrated the similarities of functions of sensitive genes in various scRNA-seq data sets, and improved the results of unsupervised clustering towards the ground-truth labels. We hope our method would provide new insights into the reduction of data noise in scRNA-seq data analysis and contribute to the development of better scRNA-seq unsupervised clustering algorithms in the future.

Gene expression patterns in blood predict future severe endpoints in community acquired pneumonia

Pneumologie ◽  
2018 ◽  
Vol 72 (S 01) ◽  
pp. S8-S9
Author(s):  
M Bauer ◽  
H Kirsten ◽  
E Grunow ◽  
P Ahnert ◽  
M Kiehntopf ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Community Acquired Pneumonia ◽  
Gene Expression Patterns
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