Related Experiment Video

Updated: Aug 22, 2026

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis
08:46

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis

Published on: August 26, 2020

RhD variants in Caucasians: consequences for checking clinically relevant alleles

Hélène Ansart-Pirenne1, Marianne Asso-Bonnet, Pierre-Yves Le Pennec

  • 1National Blood Group Reference Center and the French Establishment of Transfusion of Ile de France, Hôpital Henri Mondor, Créteil, France.

Transfusion
|August 21, 2004
PubMed

Insights

This study identified five new weak D variants, improving understanding of D antigen variations. Genotyping weak D Type 1 and 2 can optimize blood transfusions for carriers.

Area of Science:

  • Hematology
  • Immunogenetics
  • Blood group serology

Background:

  • Weak D type carriers have limited immunization risk unless antigen density is below 400 antigens per red blood cell (RBC).
  • Partial D carriers, however, can produce anti-D antibodies.

Purpose of the Study:

  • To characterize new variants of the D antigen.
  • To investigate the molecular basis of weak D expression and anti-D production.

Main Methods:

  • Serologic and molecular analyses were performed on 168 blood samples from Caucasian individuals.
  • Focus on samples exhibiting weak D expression and/or anti-D production.

Main Results:

  • Identified 70 partial D and 62 weak D cases.
  • Characterized five novel weak D alleles (399G>T, 680T>C, 833G>A, 851C>T, 1015G>A).
  • Weak D Type 1 and 2 alleles showed antigen density up to 500, while new variants and most other weak D variants had densities below 400 antigens/RBC.

Conclusions:

  • Provided molecular characterization of five new D variants.
  • Recommended routine genotyping for weak D Type 1 and 2 in laboratories for serologically weak D antigens.
  • Genotyping can prevent wastage of D- RBC units by enabling safe transfusion of D+ units to carriers.
Abstract

More Related Videos

High-resolution Melting PCR for Complement Receptor 1 Length Polymorphism Genotyping: An Innovative Tool for Alzheimer's Disease Gene Susceptibility Assessment07:26

High-resolution Melting PCR for Complement Receptor 1 Length Polymorphism Genotyping: An Innovative Tool for Alzheimer's Disease Gene Susceptibility Assessment

Published on: July 18, 2017

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

Related Concept Videos

Genetic Lingo01:11

Genetic Lingo

Overview
Pedigree Analysis01:35

Pedigree Analysis

Overview
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Comparing Copy Number Variations and SNPs02:26

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%...
Lethal Alleles02:41

Lethal Alleles

Agouti: A Lethal Allele
Lucien Cuénot discovered lethal alleles in 1905 while studying the inheritance of coat color in mice. The agouti gene is responsible for the color of the coat in mice. This gene codes for an agouti-signaling protein, which is responsible for melanin distribution in mammals. The wild-type allele gives rise to gray-brown coat color in mice, while the mutant allele gives rise to yellow coat color. In addition to coat color, the agouti gene is associated with the yellow...
Genome-wide Association Studies-GWAS01:11

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...