Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits

Jinghui Li; Tianjing Zhao; Dailu Guan; Zhangyuan Pan; Zhonghao Bai; Jinyan Teng; Zhe Zhang; Zhili Zheng; Jian Zeng; Huaijun Zhou; Lingzhao Fang; Hao Cheng

doi:10.1016/j.xgen.2023.100390

Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits

Jinghui Li, Tianjing Zhao, Dailu Guan, Zhangyuan Pan, Zhonghao Bai, Jinyan Teng, Zhe Zhang, Zhili Zheng, Jian Zeng, Huaijun Zhou, Lingzhao Fang^*, Hao Cheng^*

^*Corresponding author for this work

Center for Quantitative Genetics and Genomics

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

5 Citations (Scopus)

Abstract

Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.

Original language	English
Article number	100390
Journal	Cell Genomics
Volume	3
Issue	10
Number of pages	16
ISSN	2666-979X
DOIs	https://doi.org/10.1016/j.xgen.2023.100390
Publication status	Published - Oct 2023

Keywords

complex trait
deep learning
functional conservation
gene expression
human
pig

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title = "Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits",

abstract = "Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.",

keywords = "complex trait, deep learning, functional conservation, gene expression, human, pig",

author = "Jinghui Li and Tianjing Zhao and Dailu Guan and Zhangyuan Pan and Zhonghao Bai and Jinyan Teng and Zhe Zhang and Zhili Zheng and Jian Zeng and Huaijun Zhou and Lingzhao Fang and Hao Cheng",

year = "2023",

month = oct,

doi = "10.1016/j.xgen.2023.100390",

language = "English",

volume = "3",

journal = "Cell Genomics",

issn = "2666-979X",

publisher = "Cell Press",

number = "10",

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Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits. / Li, Jinghui; Zhao, Tianjing; Guan, Dailu et al.
In: Cell Genomics, Vol. 3, No. 10, 100390, 10.2023.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

TY - JOUR

T1 - Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits

AU - Li, Jinghui

AU - Zhao, Tianjing

AU - Guan, Dailu

AU - Pan, Zhangyuan

AU - Bai, Zhonghao

AU - Teng, Jinyan

AU - Zhang, Zhe

AU - Zheng, Zhili

AU - Zeng, Jian

AU - Zhou, Huaijun

AU - Fang, Lingzhao

AU - Cheng, Hao

PY - 2023/10

Y1 - 2023/10

N2 - Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.

AB - Assessment of genomic conservation between humans and pigs at the functional level can improve the potential of pigs as a human biomedical model. To address this, we developed a deep learning-based approach to learn the genomic conservation at the functional level (DeepGCF) between species by integrating 386 and 374 functional profiles from humans and pigs, respectively. DeepGCF demonstrated better prediction performance compared with the previous method. In addition, the resulting DeepGCF score captures the functional conservation between humans and pigs by examining chromatin states, sequence ontologies, and regulatory variants. We identified a core set of genomic regions as functionally conserved that plays key roles in gene regulation and is enriched for the heritability of complex traits and diseases in humans. Our results highlight the importance of cross-species functional comparison in illustrating the genetic and evolutionary basis of complex phenotypes.

KW - complex trait

KW - deep learning

KW - functional conservation

KW - gene expression

KW - human

KW - pig

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U2 - 10.1016/j.xgen.2023.100390

DO - 10.1016/j.xgen.2023.100390

M3 - Journal article

C2 - 37868039

AN - SCOPUS:85173430072

SN - 2666-979X

VL - 3

JO - Cell Genomics

JF - Cell Genomics

IS - 10

M1 - 100390

ER -

Learning functional conservation between human and pig to decipher evolutionary mechanisms underlying gene expression and complex traits

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Keywords

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