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Related Concept Videos

Human Genetics01:28

Human Genetics

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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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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.
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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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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...
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Updated: Sep 18, 2025

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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Mapping MAVE data for use in human genomics applications.

Jeremy A Arbesfeld1, Estelle Y Da2, James S Stevenson1

  • 1The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA.

Genome Biology
|June 25, 2025
PubMed
Summary
This summary is machine-generated.

Researchers mapped millions of genetic variants from multiplexed assays of variant effect (MAVE) to human reference sequences. This integration enhances variant interpretation and accelerates biomedical discovery by making functional data more accessible.

Keywords:
Deep mutational scanningFunctional assayGenomic medicineGenomicsGlobal Alliance for Genomics and HealthMassively parallel reporter assaysMultiplexed assays of variant effectVariation representation specification

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Functional assay data is crucial for understanding genetic variant impact.
  • Assay data often uses non-standard sequences, hindering integration with reference genomes.
  • Multiplexed Assays of Variant Effect (MAVE) data requires mapping to human reference sequences for broader accessibility.

Purpose of the Study:

  • To map MAVE data to human reference sequences for improved accessibility and usability.
  • To integrate MAVE variant information into major genomic resources.
  • To facilitate the use of functional variant data in research and clinical settings.

Main Methods:

  • Mapped approximately 9.0 million MAVE variants from MaveDB to human reference sequences.
  • Preserved data provenance by referencing original MAVE sequences.
  • Disseminated mapped data to key genomic resources like UCSC Genome Browser and Ensembl.

Main Results:

  • Successfully mapped millions of MAVE variants to human reference genomes.
  • Integrated MAVE data into widely used genomic applications, including the Genomics 2 Proteins Portal, UCSC Genome Browser, Ensembl Variant Effect Predictor, and DECIPHER.
  • Enabled visualization and integration of MAVE variants with other biological and clinical data.

Conclusions:

  • Mapping MAVE variants to human reference sequences unlocks new applications for functional data.
  • Increased access to MAVE data supports clinical variant interpretation and biomedical research.
  • This work enhances the utility of MAVE data for scientific discovery and diagnostics.