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家畜研究中的表型组学:数字表型分析和其他量化技术在全球范围内的瓶颈和前景。

Phenomics in Livestock Research: Bottlenecks and Promises of Digital Phenotyping and Other Quantification Techniques on a Global Scale.

机构信息

ICAR-National Research Centre on Camel, Bikaner, Rajasthan, India.

ICAR-National Research Centre on Mithun, Medziphema, Nagaland, India.

出版信息

OMICS. 2024 Aug;28(8):380-393. doi: 10.1089/omi.2024.0109. Epub 2024 Jul 16.

DOI:10.1089/omi.2024.0109
PMID:39012961
Abstract

Bottlenecks in moving genomics to real-life applications also include phenomics. This is true not only for genomics medicine and public health genomics but also in ecology and livestock phenomics. This expert narrative review explores the intricate relationship between genetic makeup and observable phenotypic traits across various biological levels in the context of livestock research. We unpack and emphasize the significance of precise phenotypic data in selective breeding outcomes and examine the multifaceted applications of phenomics, ranging from improvement to assessing welfare, reproductive traits, and environmental adaptation in livestock. As phenotypic traits exhibit strong correlations, their measurement alongside specific biological outcomes provides insights into performance, overall health, and clinical endpoints like morbidity and disease. In addition, automated assessment of livestock holds potential for monitoring the dynamic phenotypic traits across various species, facilitating a deeper comprehension of how they adapt to their environment and attendant stressors. A key challenge in genetic improvement in livestock is predicting individuals with optimal fitness without direct measurement. Temporal predictions from unmanned aerial systems can surpass genomic predictions, offering in-depth data on livestock. In the near future, digital phenotyping and digital biomarkers may further unravel the genetic intricacies of stress tolerance, adaptation and welfare aspects of animals enabling the selection of climate-resilient and productive livestock. This expert review thus delves into challenges associated with phenotyping and discusses technological advancements shaping the future of biological research concerning livestock.

摘要

将基因组学应用于实际的瓶颈也包括表型组学。这不仅适用于基因组医学和公共卫生基因组学,也适用于生态学和家畜表型组学。本专家叙述性评论探讨了在牲畜研究背景下,遗传组成与各种生物水平上可观察到的表型特征之间错综复杂的关系。我们详细说明了精确的表型数据在选择性繁殖结果中的重要性,并研究了表型组学的多方面应用,从改善到评估牲畜的福利、生殖性状和环境适应性。由于表型特征表现出很强的相关性,因此测量它们以及特定的生物学结果可以深入了解性能、整体健康以及发病率和疾病等临床终点。此外,牲畜的自动评估具有监测各种物种动态表型特征的潜力,有助于更深入地了解它们如何适应环境和随之而来的压力源。在牲畜遗传改良方面的一个关键挑战是在没有直接测量的情况下预测具有最佳适应性的个体。来自无人机系统的时间预测可以超过基因组预测,提供关于牲畜的深入数据。在不久的将来,数字表型和数字生物标志物可能会进一步揭示动物对压力耐受、适应和福利方面的遗传复杂性,从而能够选择适应气候变化和具有生产力的牲畜。因此,本专家评论深入探讨了表型分析相关的挑战,并讨论了塑造未来与牲畜有关的生物学研究的技术进步。

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