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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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Genomics02:02

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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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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Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
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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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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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Related Experiment Video

Updated: Jun 21, 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.

Biorxiv : the Preprint Server for Biology
|July 9, 2024
PubMed
Summary

Variant effect data in MaveDB is crucial for understanding genetic variants. The Atlas of Variant Effects Alliance created homology mappings to improve data utility for variant significance assessment.

Keywords:
deep mutational scanningglobal 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:

  • Large-scale experimental measures of variant functional assays in MaveDB hold potential for resolving variants of uncertain significance.
  • However, the current reporting of assay results relative to assayed sequence limits their downstream application.

Purpose of the Study:

  • To improve the utility of variant effect data by mapping it to human reference sequences.
  • To create machine-readable homology mappings for millions of variants.

Main Methods:

  • The Atlas of Variant Effects Alliance developed a method to map multiplexed assay of variant effect (MAVE) data to human reference sequences.
  • This involved creating robust, machine-readable homology mappings.

Main Results:

  • The method successfully processed approximately 2.5 million protein and genomic variants from MaveDB.
  • A high success rate of 98.61% was achieved in mapping examined variants.
  • Dissemination of mapped data to major resources like the UCSC Genome Browser and Ensembl Variant Effect Predictor was accomplished.

Conclusions:

  • The developed homology mapping method significantly enhances the downstream utility of MAVE data.
  • This facilitates more effective variant significance assessment and data integration into genomic resources.