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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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Genetic Screens02:46

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
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Comparing Copy Number Variations and SNPs02:26

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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.
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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Single Nucleotide Polymorphisms-SNPs01:05

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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,...
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Genome-wide Association Studies-GWAS01:11

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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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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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A computational reference for human genomics analysis in (poly)phenol research.

Mirko Treccani1, Lucia Ghiretti1, Nicole Tosi1

  • 1Human Nutrition Unit, Department of Food and Drug, University of Parma, 43125, Parma, Italy. mirko.treccani@unipr.it.

Food & Function
|November 19, 2025
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Summary
This summary is machine-generated.

This study proposes a standard genomics reference for (poly)phenol research, analyzing 121 human genes involved in their processing. This framework aids understanding polyphenol impacts on human health through genomics and personalized nutrition.

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Area of Science:

  • Nutritional Genomics
  • Bioactive Compounds Research
  • Computational Biology

Background:

  • (Poly)phenols from plant foods offer health benefits.
  • Omics techniques study (poly)phenol impact, but lack a human genomics standard.
  • Understanding (poly)phenol-gene interactions is crucial for personalized nutrition.

Purpose of the Study:

  • To develop a standard reference for human genomics analysis of (poly)phenols.
  • To computationally investigate 121 candidate genes related to (poly)phenol absorption, distribution, metabolism, and excretion (ADME).
  • To facilitate deeper insights into (poly)phenol's role in human health and disease via omics approaches.

Main Methods:

  • Computational functional investigation of 121 candidate human genes.
  • Genomics data analysis to identify key genes in (poly)phenol pathways.
  • Gene network construction to explore functional consequences and protein-protein interactions.

Main Results:

  • A computational framework and reference for (poly)phenol genomics was established.
  • Identified and analyzed 121 candidate genes involved in (poly)phenol ADME.
  • Gene networks were explored to understand functional implications and interactions.

Conclusions:

  • The proposed reference framework supports genomics analyses in personalized nutrition and health.
  • This work enhances the understanding of (poly)phenol's impact on human health.
  • It lays the groundwork for future multi-omics studies on (poly)phenols.