From Correlation to Causation: Defining Gene and RNA Function in Poultry Muscle Biology Using In Vivo Genetic Tools

TL;DR

This paper reviews how in vivo genetic tools are helping to move from observing RNA expression patterns to understanding actual gene functions in poultry muscle biology.

Contribution

The paper highlights the use of viral vectors and CRISPR/Cas9 to establish causal gene functions in poultry muscle biology, contrasting with the descriptive state of myopathy research.

Findings

Viral vectors and CRISPR/Cas9 enable direct in vivo validation of RNA functions in muscle development.

Transcriptomic data on myopathies lacks functional validation for most candidates.

Applying functional genomics tools to disease models can reveal causal mechanisms in poultry muscle biology.

Abstract

A central challenge in functional genomics is understanding the difference between correlative transcriptomic observations and definitive causal understanding of gene function in vivo. Poultry skeletal muscle, a system of significant agricultural and biological importance, demonstrates this challenge. While transcriptomic studies have cataloged extensive RNA expression dynamics during muscle development and in growth-related myopathies like wooden breast, establishing causative roles for these molecules is lacking. This review synthesizes how advanced genetic tools are now enabling a shift from correlation to causation in avian muscle biology. We detail how viral vectors (e.g., adenovirus, lentivirus, and RCAS) and CRISPR/Cas9 systems have provided direct in vivo validation of the functional roles of specific mRNAs, miRNAs, lncRNAs, and circRNAs in regulating myogenesis, hypertrophy, and atrophy. We contrast this success in fundamental biology with the study of myopathies, which remains largely descriptive. Here, a wealth of transcriptomic data has identified dysregulated pathways, including ECM remodeling, metabolism, and inflammation, but functional validation for most candidates is absent. We argue that the critical next step is to apply this established functional genomics toolkit to disease models. By defining causal mechanisms, this research will not only address a major agricultural issue but also provide a model for using genetic tools to dissect complex traits in a post-genomic era.

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