Measuring and Managing Genetic Variability in Small Populations Hubert De Rochambeau, Florence Fournet-Hanocq, Jacqueline Vu Tien Khang

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Measuring and Managing Genetic Variability in Small Populations Hubert De Rochambeau, Florence Fournet-Hanocq, Jacqueline Vu Tien Khang Measuring and managing genetic variability in small populations Hubert de Rochambeau, Florence Fournet-Hanocq, Jacqueline Vu Tien Khang To cite this version: Hubert de Rochambeau, Florence Fournet-Hanocq, Jacqueline Vu Tien Khang. Measuring and man- aging genetic variability in small populations. Annales de zootechnie, INRA/EDP Sciences, 2000, 49 (2), pp.77-93. 10.1051/animres:2000109. hal-00889883 HAL Id: hal-00889883 https://hal.archives-ouvertes.fr/hal-00889883 Submitted on 1 Jan 2000 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Ann. Zootech. 49 (2000) 77–93 77 © INRA, EDP Sciences Review article Measuring and managing genetic variability in small populations Hubert DE ROCHAMBEAU*, Florence FOURNET-HANOCQ, Jacqueline VU TIEN KHANG Station d’Amélioration Génétique des Animaux, BP 27, 31326 Auzeville Cedex, France (Received 2 July 1999; accepted 14 January 2000) Abstract — Genetic variability in small populations is affected by specific phenomena. The joint effects of genetic drift and selection, in addition to the decrease in genetic variance due to the mere selection (Bulmer effect), enhance the risk of losing alleles at selected or unselected genes and increase the inbreeding in the population by changing the family structure. Criteria for measuring this change in genetic variability are derived from the three approaches to describe the genetic variabil- ity. At the genealogical level, the kinship and inbreeding coefficients, or the effective population size, can be used. At the trait level, the estimation of its heritability is a good measure of remaining genetic variance. At the genome level, studying the polymorphism of known genetic markers can inform on the degree of genetic diversity. These criteria are to be integrated in specific tools for the management of the genetic variability. After a short introduction on the basic concepts needed for the study of genetic variability in small populations, the main criteria available to measure its change in populations is exposed and their relative efficiencies discussed. The strategies for monitoring genetic variability, deriving from the previous criteria, are illustrated through different examples. small population / genetic variability / genetic drift / genetic management / conservation programme Résumé — Mesure et gestion de la variabilité génétique dans les petites populations. Plusieurs phénomènes spécifiques modifient la variabilité génétique dans les petites populations. Les effets com- binés de la dérive génétique et de la sélection, auxquels s’ajoutent la réduction de la variance géné- tique due spécifiquement à la sélection (Effet Bulmer), renforcent le risque de perdre des allèles à des loci sélectionnés et non sélectionnés et augmentent la consanguinité de la population du fait de la modi- fication de la structure familiale. Les critères de mesure de la variabilité génétique dérivent des 3 approches utilisées pour la décrire. Les coefficients de consanguinité et de parenté ou l’effectif génétique résument l’information généalogique. L’estimation de l’héritabilité d’un caractère syn- thétise la variabilité génétique restante. L’étude du polymorphisme pour des marqueurs génétiques * Correspondence and reprints Tel.: 33 (0)5 61 28 51 88; fax: 33 (0)5 61 28 53 53; e-mail: [email protected] 78 H. de Rochambeau et al. décrit la variabilité existante au niveau du génome. Ces critères servent à construire des outils de ges- tion de la variabilité. Après une brève introduction qui présente les concepts utiles à l’étude de la varia- bilité génétique, les principaux critères utilisés pour suivre son évolution sont décrits, et leur effica- cité est comparée. Les stratégies de gestion qui dérivent de ces critères sont ensuite illustrées à partir de l’étude de quelques exemples. petites populations / variabilité génétique / dérive génétique / gestion génétique / programme de conservation 1. INTRODUCTION tions of genetic variability used to measure its evolution will be compared. A presen- Genetic variability may be defined as the tation of more or less complex rules for “genetic ability to vary”, and therefore the monitoring small populations will conclude capacity to respond to environmental vari- this paper. The concepts developed in the ations or changes in the selection objectives. first part will concern any kind of small pop- Genetic variability is also the basis of any ulation, but the last part of the paper will genetic progress, when a population is focus on populations under conservation undergoing selection. Its maintenance at a programmes. consistent level is then of great concern in any population, selected or not, and what- ever its size. However, the smaller the pop- 2. BASIC PHENOMENA ulation, the higher the need for conserva- AND CONCEPTS tion, as there are less individuals so less “containers” for genetic variability. 2.1. Genetic drift and inbreeding But how can we decide that a population is “small”? What may be called “small pop- A restricted number of individuals con- ulation” is a population where the number of tributing to the next generation in a small individuals really contributing to the next population will have two consequences: generation is restricted, whether the total genetic drift and inbreeding. population size is really small (up to sev- Genetic drift has been defined by Wright eral hundreds of individuals) or the use of [51] for a neutral, (i.e. non selected) bi-allelic techniques allowing a large diffusion of locus, as random fluctuations of allelic fre- progress (artificial insemination, multiple quencies around their initial value, due to ovulation and embryo transfer) reduces the the sampling of alleles from one generation number of reproducers in one sex or both, or to the next, finally leading to the fixation of provokes a disequilibrium in the reproduc- one of the alleles (and the loss of the other). ers’ contributions to subsequent generations. The higher the number of generations con- Some domestic populations may then be sidered and the smaller the population, the considered as “small populations” and be greater the fluctuations. This can be concerned by the following. extended to more than one locus, providing This paper aims to present the basic con- a progressive increase of homozygosity over cepts and the main tools for the manage- all the genes in the population, due to the ment of genetic variability in a small popu- successive samplings of alleles over time lation, with or without selection. After a and the consecutive random fixations of description of the phenomena acting on some alleles and losses of others. genetic variability in such a population, the The probabilistic approach of inbreed- criteria derived from the different defini- ing was derived by Malecot [29]. In small Genetic management of small populations 79 populations, the number of founder ances- – a dominance effect D, resulting from tors is restricted (“founder” means an indi- interactions between the paternal and mater- vidual whose parents are unknown). Over nal alleles at a given locus; successive generations, even if matings are – an epistatic effect I, concerning inter- panmictic, individuals are more likely to be actions between alleles at different loci. related, due to one or more common ances- In most cases, only the additive genetic tors, and thereafter, matings between rela- part of the performance is considered and tives produce inbred individuals. As a con- the genetic variability of a quantitative trait sequence, two homologous genes could be is approached by its additive genetic vari- “identical by descent”, i.e. they are both ance. Several models, either analytic [6, 49] deriving by copy from the same gene in a or stochastic [15], differing by the hypothe- common ancestor. ses they rely on, are available to describe and predict the evolution of additive genetic 2.2. Consequences on genetic variability variance over generations. The more com- plex the model, the more accurate the pre- Genetic drift and inbreeding were two diction of genetic variance over time. This is aspects of a phenomenon which increases illustrated in Figure 1, where the predictions the rate of homozygous genes in the popu- provided by three analytical models based lation. As the genetic variability of the trait on Gaussian theory are compared. Wright model [51] and Bulmer model [3] consider under study can be characterised by the only one effect at a time on genetic vari- number of different alleles available at the ance, either genetic drift (Wright model) or loci controlling the trait in the whole popu- selection (Bulmer model). The Verrier et al. lation, the loss of alleles due to genetic drift model [49] accounts for genetic drift, selec- or inbreeding consecutively decreases the tion and interactions between the two fac- genetic variability. tors. The Wright model highlights the effect The previous concepts were developed of genetic drift on genetic variance: the for one single neutral locus. Most of the remaining variance after 30 generations
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