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RNA Splicing

RNA Splicing

Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...

Pre-mRNA Processing: RNA Splicing

Pre-mRNA Processing: RNA Splicing

Alternative RNA Splicing

Alternative RNA Splicing

Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...

Alternative RNA Splicing

Alternative RNA Splicing

Single Nucleotide Polymorphisms-SNPs

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

Comparing Copy Number Variations and SNPs

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

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Related Experiment Video

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Merging Absolute and Relative Quantitative PCR Data to Quantify STAT3 Splice Variant Transcripts

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Identification and Quantification of Splicing Quantitative Trait Loci.

Ankeeta Shah¹, Yang I Li^2,3

¹Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL, USA.

Methods in Molecular Biology (Clifton, N.J.)

|December 19, 2019

Summary

Identifying genetic variants that influence complex traits is crucial. This study focuses on noncoding variants, specifically mapping splicing quantitative trait loci (sQTL), to understand their impact on gene regulation and complex diseases.

Keywords:

Complex traits Gene expression Genetic variation Quantitative trait loci (QTL)Splicing Splicing QTL (sQTL)

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Area of Science:

Genetics and Genomics
Complex Trait Variation
Gene Regulation

Background:

Complex traits and diseases possess a significant genetic basis, necessitating identification of underlying genetic variants.
Noncoding variants, unlike coding mutations in Mendelian diseases, are presumed to significantly contribute to complex traits by influencing gene regulation.

Purpose of the Study:

To review recent advancements and methodologies for discovering regulatory regions linked to complex traits.
To specifically detail the process of mapping splicing quantitative trait loci (sQTL) as a key approach.

Main Methods:

Focus on methods for identifying noncoding variants associated with phenotypic variation.
Detailed explanation of mapping splicing quantitative trait loci (sQTL).
Utilizing the Yoruba samples from the GEUVADIS dataset as a case study for sQTL analysis.

Main Results:

Demonstration of sQTL mapping as a viable method to uncover regulatory variants.
Highlighting the importance of noncoding variation in understanding complex trait genetics.
Provides a framework for future research into genetic underpinnings of complex diseases.

Conclusions:

Understanding noncoding variation is essential for deciphering the genetic architecture of complex traits.
sQTL mapping offers a powerful approach to identify regulatory variants impacting gene expression and splicing.
The study underscores the need for comprehensive analysis of noncoding regions in genetic research.