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BioData Min. 2019 Nov 9;12:20. doi: 10.1186/s13040-019-0208-x. eCollection 2019.

Screening for mouse genes lost in mammals with long lifespans.

Author information

1
1Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute) IITP RAS, 19 build. 1 Bolshoy Karetny per., Moscow, 127051 Russia.
2
2Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences (IBCH RAS) 16/10, Miklukho-Maklaya str., Moscow, 117997 Russia.

Abstract

Background:

Gerontogenes include those that modulate life expectancy in various species and may be the actual longevity genes. We believe that a long (relative to body weight) lifespan in individual rodent and primate species can be due, among other things, to the loss of particular genes that are present in short-lived species of the same orders. These genes can also explain the widely different rates of aging among diverse species as well as why similarly sized rodents or primates sometimes have anomalous life expectancies (e.g., naked mole-rats and humans). Here, we consider the gene loss in the context of the prediction of Williams' theory that concerns the reallocation of physiological resources of an organism between active reproduction (r-strategy) and self-maintenance (K-strategy). We have identified such lost genes using an original computer-aided approach; the software considers the loss of a gene as disruptions in gene orthology, local gene synteny or both.

Results:

A method and software identifying the genes that are absent from a predefined set of species but present in another predefined set of species are suggested. Examples of such pairs of sets include long-lived vs short-lived, homeothermic vs poikilothermic, amniotic vs anamniotic, aquatic vs terrestrial, and neotenic vs nonneotenic species, among others. Species are included in one of two sets according to the property of interest, such as longevity or homeothermy. The program is universal towards these pairs, i.e., towards the underlying property, although the sets should include species with quality genome assemblies. Here, the proposed method was applied to study the longevity of Euarchontoglires species. It largely predicted genes that are highly expressed in the testis, epididymis, uterus, mammary glands, and the vomeronasal and other reproduction-related organs. This agrees with Williams' theory that hypothesizes a species transition from r-strategy to K-strategy. For instance, the method predicts the mouse gene Smpd5, which has an expression level 20 times greater in the testis than in organs unrelated to reproduction as experimentally demonstrated elsewhere. At the same time, its paralog Smpd3 is not predicted by the program and is widely expressed in many organs not specifically related to reproduction.

Conclusions:

The method and program, which were applied here to screen for gene losses that can accompany increased lifespan, were also applied to study reduced regenerative capacity and development of the telencephalon, neoteny, etc. Some of these results have been carefully tested experimentally. Therefore, we assume that the method is widely applicable.

KEYWORDS:

Aging; Gene loss; Gerontology; In silico analysis; Lifespan; Longevity; Synteny

Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

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