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Cell Specific Gene Expression

Cell Specific Gene Expression

Gene Evolution - Fast or Slow?

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...

Synteny and Evolution

Synteny and Evolution

John H. Renwick first coined the term “synteny” in 1971, which refers to the genes present on the same chromosomes, even if they are not genetically linked. The species with common ancestry tend to show conserved syntenic regions. Therefore, the concept of synteny is nowadays used to describe the evolutionary relationship between species.
Around 80 million years ago, the human and mice lineages diverged from the common ancestor. During the course of evolution, the ancestral...

Reporter Genes

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Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.

Molecular Factors Affecting Cell Division

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Position-effect Variegation

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In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.

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Related Experiment Video

Updated: Sep 9, 2025

Cell Lineage Analyses and Gene Function Studies Using Twin-spot MARCM

Cell Lineage Analyses and Gene Function Studies Using Twin-spot MARCM

Published on: March 2, 2017

Marker genes reveal dynamic features of cell evolving processes.

Wenjie Cao¹, Bengong Zhang², Tianshou Zhou¹

¹School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China.

Bioinformatics Advances

|September 2, 2025

Summary

This study analyzes single-cell RNA sequencing data to reveal dynamic features of cell fate determination. Key gene expression patterns and regulatory strengths change significantly during cell evolution and developmental branching.

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Last Updated: Sep 9, 2025

Cell Lineage Analyses and Gene Function Studies Using Twin-spot MARCM

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Area of Science:

Developmental Biology
Computational Biology
Genomics

Background:

Cell fate determination is crucial for embryonic development, but its dynamic processes are not fully understood.
Single-cell RNA sequencing (scRNA-seq) provides a powerful tool to study cellular heterogeneity and dynamic changes.

Purpose of the Study:

To investigate the dynamic features of cell fate determination using scRNA-seq data.
To identify statistical and expression pattern changes in key genes during cell differentiation.
To understand the regulatory mechanisms underlying cell fate decisions.

Main Methods:

Analysis of four scRNA-seq datasets from mouse embryo cells, mouse embryonic fibroblasts, human bone marrow, and intestine organoids.
Examination of gene expression distributions (e.g., Gata3 mRNA) before, at, and after developmental branching points.
Application of machine learning to analyze gene regulatory strengths, burst size, and frequency along pseudo-time trajectories.

Main Results:

Key genes exhibit distinct statistical features and expression patterns across different cell types and developmental stages.
Specific mRNA distribution patterns (e.g., bimodal, unimodal, trimodal) were observed for genes like Gata3 during cell fate decisions.
Gene regulatory strength generally increases before branching and monotonically increases after branching.
Key gene burst size and frequency show complex patterns, decreasing before branching and varying after branching.

Conclusions:

The study unveils essential dynamic features of cell processes and cell fate determination.
Identified patterns can supplement existing methods for accurately screening marker genes in developmental studies.
Findings contribute to a deeper understanding of genetic information maintenance during complex cell evolution.