通过转录组分析确定猪肌肉内脂肪酸组成的候选调控基因

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Genetics Selection Evolution Pub Date : 2024-02-12 DOI:10.1186/s12711-024-00882-x
Jesús Valdés-Hernández, Josep M. Folch, Daniel Crespo-Piazuelo, Magí Passols, Cristina Sebastià, Lourdes Criado-Mesas, Anna Castelló, Armand Sánchez, Yuliaxis Ramayo-Caldas
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引用次数: 0

摘要

肌内脂肪(IMF)含量及其脂肪酸(FA)组成通常由多个基因控制,每个基因的影响很小。在本研究中,为了确定参与脂肪酸组成的候选基因和潜在调控因子,我们对猪背阔肌(LD)肌肉的肌内脂肪酸和转录组图谱进行了多变量综合分析。我们还结合网络、调控影响因子(RIF)、假定靶基因的硅学预测和功能分析,以更好地支持我们研究结果的生物学相关性。为此,我们使用了 129 头伊比利亚×杜洛克回交猪的 LD RNA-Seq 和肌肉内 FA 组成图谱。我们发现了 378 个相关变量(13 个 FA 和 365 个基因),其中 6 个 FA(C20:4n-6、C18:2n-6、C20:3n-6、C18:1n-9、C18:0 和 C16:1n-7)是预测网络中相互关联度最高的变量。检测到的 FA 相关基因包括参与脂质和/或碳水化合物代谢或调控 IMF 沉积的基因(例如,adipoq、chukoq、chukoq、adipoq、adipoq、adipoq、adipoq)、adipoq, chuk, cycs, cyp4b1, dld, elovl6, fbp1, g0s2, gclc, hmgcr, idh3a, lep, lgals12, lpin1, plin1, pnpla8, ppp1r1b、SDR16C5、SFRP5、SOD3、SNW1 和 TFRC)、肉质(GALNT15、GOT1、MDH1、NEU3、PDHA1、SDHD 和 UNC93A)和运输(例如,GALNT15、GOT1、MDH1、NEU3、PDHA1、SDHD 和 UNC93A)。g.,EXOC7 和 SLC44A2)。功能分析突出显示了 54 个代表性过高的基因本体术语,包括众所周知的调控脂质和碳水化合物代谢的生物过程和途径。RIF分析表明,六种转录因子(CARHSP1、LBX1、MAFA、PAX7、SIX5和TADA2A)在基因表达和肌内FA组成中起着关键作用。根据硅学预测,我们确定了这六个调控因子的假定靶基因。其中,TADA2A 和 CARHSP1 的 RIF 评分极高,是猪体内的新型调控因子。此外,TADA2A 的表达与 C20:4n-6、C18:2n-6、C20:3n-6 和 C18:1n-9 相关(正相关或负相关),而 CARHSP1 的表达与 C16:1n-7 脂肪因子相关(正相关)。我们还发现,这两个转录因子共享参与脂质代谢的靶基因(如 GOT1、PLIN1 和 TFRC)。对肌肉转录组和肌肉内FA谱的综合分析揭示了猪体内FA和脂质代谢的关键候选基因和潜在调控因子的宝贵信息,其中一些转录因子被认为可控制基因表达并调节FA组成差异。
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Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis
Intramuscular fat (IMF) content and its fatty acid (FA) composition are typically controlled by several genes, each with a small effect. In the current study, to pinpoint candidate genes and putative regulators involved in FA composition, we performed a multivariate integrative analysis between intramuscular FA and transcriptome profiles of porcine longissimus dorsi (LD) muscle. We also carried out a combination of network, regulatory impact factor (RIF), in silico prediction of putative target genes, and functional analyses to better support the biological relevance of our findings. For this purpose, we used LD RNA-Seq and intramuscular FA composition profiles of 129 Iberian × Duroc backcrossed pigs. We identified 378 correlated variables (13 FA and 365 genes), including six FA (C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, C18:0, and C16:1n-7) that were among the most interconnected variables in the predicted network. The detected FA-correlated genes include genes involved in lipid and/or carbohydrate metabolism or in regulation of IMF deposition (e.g., ADIPOQ, CHUK, CYCS, CYP4B1, DLD, ELOVL6, FBP1, G0S2, GCLC, HMGCR, IDH3A, LEP, LGALS12, LPIN1, PLIN1, PNPLA8, PPP1R1B, SDR16C5, SFRP5, SOD3, SNW1, and TFRC), meat quality (GALNT15, GOT1, MDH1, NEU3, PDHA1, SDHD, and UNC93A), and transport (e.g., EXOC7 and SLC44A2). Functional analysis highlighted 54 over-represented gene ontology terms, including well-known biological processes and pathways that regulate lipid and carbohydrate metabolism. RIF analysis suggested a pivotal role for six transcription factors (CARHSP1, LBX1, MAFA, PAX7, SIX5, and TADA2A) as putative regulators of gene expression and intramuscular FA composition. Based on in silico prediction, we identified putative target genes for these six regulators. Among these, TADA2A and CARHSP1 had extreme RIF scores and present novel regulators in pigs. In addition, the expression of TADA2A correlated (either positively or negatively) with C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, and that of CARHSP1 correlated (positively) with the C16:1n-7 lipokine. We also found that these two transcription factors share target genes that are involved in lipid metabolism (e.g., GOT1, PLIN1, and TFRC). This integrative analysis of muscle transcriptome and intramuscular FA profile revealed valuable information about key candidate genes and potential regulators for FA and lipid metabolism in pigs, among which some transcription factors are proposed to control gene expression and modulate FA composition differences.
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
审稿时长
1 months
期刊介绍: Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.
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