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Related Concept Videos

General Transcription Factors01:30

General Transcription Factors

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Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
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Pleiotropy01:33

Pleiotropy

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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,...
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Transcription Factors02:16

Transcription Factors

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Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
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Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

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Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
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Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Partitioning genetic pleiotropy within tissue-specific regulatory patterns.

Prasun Panja1, Diptanil Biswas1, Samsiddhi Bhattacharjee1

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This study introduces J-PEP, a novel framework for understanding complex trait genetics by identifying pleiotropic SNP clusters. It links genetic architecture to tissue-specific epigenomic patterns for improved interpretation.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-Wide Association Studies (GWAS) reveal pleiotropic SNP clusters linked to complex traits.
  • Tissue-specific epigenomic profiles are crucial for understanding these pleiotropic effects.
  • Current methods lack efficient tissue-aware interpretation of genetic architecture.

Purpose of the Study:

  • To introduce J-PEP, a novel framework for tissue-aware interpretation of complex trait genetic architecture.
  • To develop PEPA, a cross-modal validation metric for assessing results.
  • To improve the clustering efficiency and mechanistic interpretation of pleiotropic and epigenomic patterns.

Main Methods:

  • J-PEP jointly factorizes trait and tissue data matrices.
  • Identifies soft clusters of Single Nucleotide Polymorphisms (SNPs).
  • Captures both pleiotropic and shared epigenomic patterns across tissues.

Main Results:

  • J-PEP enhances the identification of SNP clusters with shared epigenomic patterns.
  • The framework improves clustering efficiency compared to existing methods.
  • Provides better mechanistic insights into the genetic architecture of complex traits.

Conclusions:

  • J-PEP offers a powerful approach for tissue-aware genetic interpretation.
  • The framework facilitates understanding of pleiotropy and epigenomic regulation in complex traits.
  • PEPA serves as a valuable metric for cross-modal validation in genetic studies.