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可量化稳态的遗传学:I. 一般问题。

The genetics of quantifiable homeostasis: I. The general issues.

作者信息

Murphy E A, Trojak J L

出版信息

Am J Med Genet. 1986 May;24(1):159-69. doi: 10.1002/ajmg.1320240120.

Abstract

Some fundamental issues in developing the quantitative genetics of heritable traits are addressed. Such a trait must be capable of being represented as a quantity. Choice of the metric can be satisfactorily made only in the light of some insight into the nature of the trait and what its revealing characteristics may be. This insight is likely to change as more is known about the process, so the form and detail of the analysis is not static but perhaps continually evolving. Much has been made out of sample means and, at a more sophisticated level, Galton-Fisher theory (the analysis of the first two moments of multivariate Gaussian variates). However, at least some processes seriously violate the assumptions underlying that theory. One such group comprises traits in which the means are unvarying and the genetic message lies in other aspects of the distribution; in these circumstances the standard summary statistics such as heritability, regression, and correlation may be totally uninformative, distracting, or even misleading. This paradox is illustrated by reference to homeostasis, where the Mendelian component lies, not in the mean, but in the degree of laxity of control. Since estimating higher moments is notoriously imprecise, the suggested remedy is the familial and commonsense one of exploring the genetics of the intermediate states and underlying mechanisms and not only that of the resultant ("bottom-line") phenotype. In our chosen problem, the task of relating the outcome to the basic mechanism of inheritance calls for a detailed understanding of the homeostasis involved.

摘要

本文探讨了可遗传性状数量遗传学发展中的一些基本问题。这样的性状必须能够用数量来表示。只有在对性状的本质及其可能揭示的特征有一定了解的基础上,才能令人满意地选择度量标准。随着对该过程了解的增多,这种认识可能会发生变化,因此分析的形式和细节并非一成不变,而是可能不断演变。样本均值以及更复杂层面的高尔顿 - 费舍尔理论(对多元高斯变量前两个矩的分析)已得到大量研究。然而,至少有一些过程严重违反了该理论所依据的假设。其中一类性状的均值不变,遗传信息存在于分布的其他方面;在这种情况下,诸如遗传力、回归和相关性等标准汇总统计量可能完全没有信息价值,具有误导性甚至会产生干扰。通过参考稳态说明了这一悖论,孟德尔成分不在于均值,而在于控制的宽松程度。由于估计高阶矩 notoriously 不精确,建议的补救方法是从家族角度和常识出发,探索中间状态和潜在机制的遗传学,而不仅仅是最终(“底线”)表型的遗传学。在我们所选择的问题中,将结果与基本遗传机制联系起来的任务需要对所涉及的稳态有详细的了解。 (注:“notoriously”在文中不太好直接准确翻译,这里保留英文,可能需要结合上下文调整更合适的表达)

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