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Genetic Screens

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

Epistasis Analysis

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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 chromosome underwent...

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Related Experiment Video

Updated: Jul 9, 2026

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor

Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor

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Introduction to Genetic Analysis Workshop 15 summaries.

John S Witte¹, Audrey H Schnell, Heather J Cordell

¹Department of Epidemiology and Biostatistics, Institute for Human Genetics, University of California at San Francisco, 513 Parnassus Avenue, San Francisco, CA 94143, USA. jwitte@ucsf.edu

Genetic Epidemiology

|November 30, 2007

Summary

The 15th Genetic Analysis Workshop (GAW15) focused on analyzing large genetic datasets for linkage and association studies. Key findings from gene expression and rheumatoid arthritis data were presented by 350 participants.

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Area of Science:

Genetics and Genomics
Statistical Genetics
Bioinformatics

Background:

The 15th Genetic Analysis Workshop (GAW15) convened to address challenges in analyzing large-scale genetic datasets.
Focus on linkage, association, and other analytical methods for complex genetic research.

Framework:

Utilized two real datasets and one simulated dataset for analysis.
Real datasets included gene expression phenotypes with genome-wide markers and rheumatoid arthritis data.
Simulated dataset mirrored the rheumatoid arthritis study structure for methodological validation.

Implementation:

A record 350 participants contributed 252 papers.
Contributions were organized into 17 presentation groups, facilitating focused discussion.
Analysis involved linkage and association studies on diverse genetic data.

Implications:

Advanced methodologies for analyzing large genetic datasets.
Provided insights into genetic factors influencing gene expression and rheumatoid arthritis.
Facilitated collaboration and knowledge exchange in the genetic analysis community.