Pig genome functional annotation enhances biological interpretations of complex traits and comparative epigenomics

Abstract

The functional annotation of livestock genomes is crucial for understanding the molecular mechanisms that underpin complex traits of economic importance, adaptive evolution and comparative genomics. Here, we provide the most comprehensive catalogue to date of regulatory elements in the pig (Sus scrofa) by integrating 223 epigenomic and transcriptomic data sets, representing 14 biologically important tissues. We systematically describe the dynamic epigenetic landscape across tissues by functionally annotating 15 different chromatin states and defining their tissue-specific regulatory activities. We demonstrate that genomic variants associated with complex traits and adaptive evolution in pig are significantly enriched in active promoters and enhancers. Furthermore, we reveal distinct tissue-specific regulatory selection between Asian and European pig domestication processes. Compared with human and mouse epigenomes, we show that porcine regulatory elements are more conserved in DNA sequence, under both rapid and slow evolution, than those under neutral evolution across pig, mouse, and human. Finally, we provide novel biological insights on tissue-specific regulatory conservation and demonstrate that, depending on the traits, mouse or pig might be more appropriate biomedical models for different complex traits and diseases in humans through integrating comparative epigenomes with 47 human genome-wide association studies.

PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks

“…However, the dataset used in this study was constructed by integrating enhancer sequence information from various sources [ 59 , 64 , 65 ], including transfer learning methods, publicly available ChIP-seq data, and comprehensive regulatory catalogs. While we made efforts to ensure the reliability and quality of the data, potential biases and inconsistencies may still exist, particularly in the case of non-enhancer sequences where the random sampling approach we employed may have limitations.…”

“…The project employs a variety of high-throughput techniques and bioinformatics methods to comprehensively annotate the genomes of various animal species, revealing their functions and regulatory mechanisms. Recently, Pan et al [ 64 ] integrated 223 epigenomic and transcriptomic datasets to create a comprehensive catalog of regulatory elements in pigs (Sus scrofa). We extracted enhancer information from this catalog for all tissues and merged it.…”

“…To construct an effective and robust model, we followed strict criteria to establish the dataset. To obtain high-quality and reliable enhancer sequences, we combined enhancer sequences obtained from MacPhillamy et al [ 59 ] and Pan et al [ 64 ]. We processed the BED files from these two datasets to obtain the overlapping fragments, which served as the initial enhancer sequences.…”

“…Each circle representing a specific source, the overlapping regions indicate the common enhancers shared between the sources, while the non-overlapping regions represent the unique enhancers specific to each source. MacPhillamy et al [ 59 ] and Pan et al [ 64 ].…”