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Related Concept Videos

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%...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
Position-effect Variegation02:32

Position-effect Variegation

In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
Pleiotropy01:33

Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...

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In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
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In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

Decoding common and rare noncoding variant effects across cellular and developmental contexts.

Andrew R Marderstein1,2, Soumya Kundu3,4, Evin M Padhi5

  • 1Department of Pathology, Stanford University, Stanford, CA, USA. mardera1@mskcc.org.

Nature Genetics
|June 15, 2026
PubMed
Summary
This summary is machine-generated.

This study uses deep learning to predict how noncoding genetic variants affect cell-specific gene regulation during human development. It identifies distinct roles for common versus rare variants in development and disease.

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
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In Vivo Modeling of the Morbid Human Genome using Danio rerio
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In Vivo Modeling of the Morbid Human Genome using Danio rerio

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Last Updated: Jun 17, 2026

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila
06:41

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Published on: August 20, 2019

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

In Vivo Modeling of the Morbid Human Genome using Danio rerio
12:31

In Vivo Modeling of the Morbid Human Genome using Danio rerio

Published on: August 24, 2013

Area of Science:

  • Genomics
  • Developmental Biology
  • Computational Biology

Background:

  • Understanding noncoding genetic variants' roles in cell-specific gene regulation across human development is challenging.
  • Noncoding variants contribute significantly to human traits and diseases, but their functional interpretation remains difficult.

Purpose of the Study:

  • To develop a computational framework for predicting the functional impact of noncoding variants in diverse cell types during human development.
  • To differentiate the regulatory effects of common and ultra-rare noncoding variants.
  • To identify noncoding variants associated with human diseases.

Main Methods:

  • Generated over 3 billion predictions of chromatin accessibility using deep learning sequence models across fetal and adult cell types.
  • Integrated population genetics data and evolutionary constraint to prioritize functional noncoding variants.
  • Developed FLARE (Functional Lasso Analysis of Regulatory Evolution) to identify variants with extreme regulatory effects.

Main Results:

  • Common variants exhibit more cell-type-specific regulatory effects, while ultra-rare variants show broader impacts.
  • Strongest evidence of purifying selection on variants was observed in fetal neurons.
  • FLARE successfully prioritized noncoding variants implicated in childhood disorders, adult brain expression outliers, and schizophrenia heritability.

Conclusions:

  • Integrating single-cell chromatin accessibility, population genetics, and deep learning provides a powerful framework for identifying regulatory variants.
  • This approach can elucidate the role of noncoding variation in human development and complex diseases.
  • The findings highlight the distinct contributions of common and rare variants to regulatory evolution and disease risk.