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Evaluation via Supervised Machine Learning of the Broiler Pectoralis Major and Liver Transcriptome in Association with the Muscle Myopathy Wooden Breast

ABSTRACT: Evaluation via Supervised Machine Learning of the Broiler Pectoralis Major and Liver Transcriptome in Association with the Muscle Myopathy Wooden Breast

PROVIDER: PRJNA602475 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10919114.fastq.gz	Fastqsanger.gz
	SRR10919115.fastq.gz	Fastqsanger.gz
	SRR10919116.fastq.gz	Fastqsanger.gz
	SRR10919117.fastq.gz	Fastqsanger.gz
	SRR10919118.fastq.gz	Fastqsanger.gz

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Project description:The muscle myopathy wooden breast (WB) has recently appeared in broiler production and has a negative impact on meat quality. WB is described as hard/firm consistency found within the pectoralis major (PM). In the present study, we use machine learning from our PM and liver transcriptome dataset to capture the complex relationships that are not typically revealed by traditional statistical methods. Gene expression data was evaluated between the PM and liver of birds with WB and those that were normal. Two separate machine learning algorithms were performed to analyze the data set including the sequential minimal optimization (SMO) of support vector machines (SVMs) and Multilayer Perceptron (MLP) Artificial Neural Network (ANN). Machine learning algorithms were compared to identify genes within a gene expression data set of approximately 16,000 genes for both liver and PM, which can be correctly classified from birds with or without WB. The performance of both machine learning algorithms SMO and MLP was determined using percent correct classification during the cross-validations. By evaluating the WB transcriptome datasets by 5× cross-validation using ANNs, the expression of nine genes ranked based on Shannon Entropy (Information Gain) from PM were able to correctly classify if the individual bird was normal or exhibited WB 100% of the time. These top nine genes were all protein coding and potential biomarkers. When PM gene expression data were evaluated between normal birds and those with WB using SVMs they were correctly classified 95% of the time using 450 of the top genes sorted ranked based on Shannon Entropy (Information Gain) as a preprocessing step. When evaluating the 450 attributes that were 95% correctly classified using SVMs through Ingenuity Pathway Analysis (IPA) there was an overlap in top genes identified through MLP. This analysis allowed the identification of critical transcriptional responses for the first time in both liver and muscle during the onset of WB. The information provided has revealed many molecules and pathways making up a complex molecular mechanism involved with the progression of wooden breast and suggests that the etiology of the myopathy is not limited to activity in the muscle alone, but is an altered systemic pathology.

Project description:Introduction: Skeletal muscle satellite cells (MuSCs, or stem cells) play a crucial role in muscle development, maintenance, and regeneration, serving both hypertrophic support and regenerative myogenesis. Syndecans (SDCs) act as communication bridges within the muscle microenvironment, regulating interactions with extracellular matrix components, and contributing significantly to tissue repair and inflammation. Specifically, syndecan-4 (SDC4) is involved in muscle regeneration at multiple stages. Methods: This study delves into the emerging challenge of wooden breast (WB) myopathy and its connection to SDC4. Our hypothesis proposes that disruptions in MuSC dynamics through SDC4 contribute to the increased incidence of breast myopathies observed in growing broilers. To test our hypothesis, non-affected and affected broilers were systematically selected, and the characteristics of WB myopathy were studied both in vitro and in vivo. SDC4 overexpression in MuSCs and blocking peptides corresponding to the SDC4 ectodomain were used for investigation of the role of SDC4 in muscle development and its shedding levels. Results and Discussion: Examination in vivo of affected muscles revealed smaller fibers and changes in metabolic pathways. In vitro studies unveiled disrupted proliferation of MuSCs in WB myopathy, accompanied by downregulation of several muscle markers. Investigation of a potentially role of SDC4 in the pathogenesis of WB myopathy revealed a decreased tendency in SDC4 gene expression and increased shedding of its ectodomain. Moreover, we showed that SDC4 overexpression is linked to decreased proliferation in MuSCs and affected myogenesis. We detected the impairment proliferation of WB-affected MuSCs, revealing critical insights into the dysfunctional state of these cells in myopathy. Additionally, by treating MuSCs with blocking peptides derived from the SDC4 ectodomain, we identified altered proliferation. Taken together, this work contributes valuable knowledge on the molecular mechanisms underlying WB myopathy and role of SDC4 in this chicken myopathy.

Dataset Information

Evaluation via Supervised Machine Learning of the Broiler Pectoralis Major and Liver Transcriptome in Association with the Muscle Myopathy Wooden Breast

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