Genetic Diversity Management of Moroccan Captive-Bred Houbaras

With regards to an ex-situ conservation plan and program of Moroccan houbara bustards, the genetic diversity of a captive breeding stock of (Chamydotis undulata undulata) was studied and assessed using metapopulational approaches. The present study aims thus, the description and comparison of various strategies implemented in the species conservation that would conduct to: 1) a better quantification of the gain and loss of genetic diversity of the houbara herd made up of wild and captive populations, and consequently, to 2) a pertinent tracing of conservation and management priorities of the Moroccan avian subspecies.


Introduction
Bustard Houbara is an avian species classified as vulnerable by the International Union for Conservation of Nature (IUCN) in 2016. It belongs to the Otididae family and is banned from international trade by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Since genetic diversity and increased inbreeding may lead to inbreeding depression, bottlenecks, non-adaptation to environmental change, and consequently extinction of species and populations [1].
In addition to the technological advances in molecular biology and bioinformatics, a wide variety of genetic and statistical recommendations and approaches have been proposed for the study of genetic diversity in the conservation context [2] [3]. These techniques are generally based on the measurement of gene diversity, also known as "heterozygosity" [4] and/or allelic richness [5] [6]. In 1992, Weitzman [7] used phylogenetic methods based on genetic distances in the analysis of global genetic diversity to determine conservation priorities.
However, this approach has been criticized because it did not take into account within (sub)population diversity in its estimation [8].
More recently, to study genetic diversity extracted either from genealogies (pedigrees) or neutral molecular markers such as microsatellites, the most plausible and accepted strategy could be the one aimed at minimizing the kinship or coancestry in a metapopulation, by optimizing and maximizing the contribution of parents to subsequent generations [3]. In the case of subdivided or poorly structured populations, it was shown that this practice works in favor of genetic diversity by increasing the expected heterozygosity and the effective size of a population [9].
Furthermore, among the causes of decline of genetic diversity, is the reduction of the effective size of a population ( e N ) which is characterized by a decline in the number of alleles, and can in the long term, influence the species survival.
The aim of this research is to describe and compare different approaches that measure genetic diversity in terms of expected heterozygosity, mean coancestry and allelic richness with rarefaction, as well as to better assess the gain and loss of genetic diversity of a Moroccan Houbara bustard herd of recent pedigree, which is made up of wild founder and captive populations. Such study is believed to enable setting priorities for the conservation and management of the Moroccan avian subspecies.
. It is also equal to the expected total heterozygosity defined as: were also estimated by GenAlex [13]. Micro-Checker 2.2.3 [16] was used to identify genotyping errors. The deviation from Hardy-Weinberg equilibrium for each population was investigated by Fisher's exact test, using GENEPOP software [17] and considering 50,000 iterations and 20 batches.
The analysis of molecular variance (AMOVA) performed by Arlequin facilitated the quantification of the hierarchical structuring of genetic variance at within and between populations (or subpopulation) levels. The same program estimated genetic differentiation ST F and its probability value (P-value) between different pairs of populations.

Measurement of Genetic Diversity in Terms of Mean Coancestry fij
According to Malécot [18], the coancestry coefficient ( ij f ) between two individuals i and j, is the probability that two alleles at a locus taken at random are identical. Furthermore, the total genetic diversity ( T DG ) in a particular subdivided population or metapopulation, corresponds to the complement of the global coencestry coefficient ( 1 Open Journal of Applied Sciences between the two approaches is that the coefficient ( ij f ) between all pairs of individuals should be calculated by considering "identity by descent" in the case of pedigrees [18], and considering "identity in state" in the case of neutral markers.
In general, considering a metapopulation composed of n populations or subpopulations of i N individuals, the average coefficient of inbreeding of the subpopulation i is: − ) with i s the average self coancestry of all the individuals. Also, the average distance between the individuals belonging to subpopulations i and j is defined as As for the minimum distance of Nei (1987) it is calculated by applying the equation: . Finally, Wright's coefficient [19] of differentiation is calculated using the following formula: The aforementioned analyses were carried out using the METAPOP v.2.0.a3

A. Korrida et al. Open Journal of Applied Sciences
software [20], while the calculation of the mean meta-population matching was made using the MOLKIN v.3.0 program [21].

Measurement of Genetic Diversity in Terms of Allelic Richness with Rarefaction
The allelic richness or the number of alleles per locus is estimated based on the classical rarefaction method proposed by El Mousadik and Petit [22] and Petit et al. [5]. This method makes it possible to correct the bias resulting from the differences in sample sizes by considering the number of expected alleles of a sample whose size (g) is smaller than that of a larger size ( i N ). i N represents the total number of genes in a population (i) and ik N is the number of copies of the k th allele of a sample belonging to a given population. The allelic richness in a given locus is: By analogy with the coefficient of genetic differentiation ST F , a coefficient of differentiation of allelic richness was also proposed by El Mousadik and Petit [22]: 1 = ∑ ) the mean within population allelic richness, T R the total allelic richness, and i a the number of alleles.
The new methodology based on the principle of rarefaction and the partition of allelic richness into within and between population diversity and proposed by Caballero and Rodríguez-Ramilo [23], was applied in this work in order to compare the two approaches with rarefaction. In this case, within population allelic diversity is calculated as: , while the mean allelic distance between populations i is calculated as: The average distance between all the populations is thus equal to: . Therefore, the total allelic diversity is given as: The contribution of each population to total genetic diversity can also be deduced from this equation as well as the coefficient of allelic differentiation which is equal to:

Contribution of Each (Sub)population to the Total Genetic Diversity
The method of Kirkpatrick et al. [24] based on the simulated annealing logarithm, was used to rank the different populations according to their optimal contributions to an artificial gene pool (germplasm) possessing maximum genetic diversity. According to this approach, optimal contributions can be applied

Gene Diversity and Genetic Differentiation
The In Table 2, the global genetic diversity

Measurement of Genetic Diversity in Terms of Mean Coancestry
The allelic richness varies between 5 and 9 for loci D117 and A205, respectively ( Figure 1). According to (Table 5) ). This is also equal to inter-population genetic diversity  . This result is in support with the result obtained by Harlequin in Table 3 The population born in captivity contributed the most to total diversity with a value of 70% (0.4796). This may be due to the high number of individuals but especially to its within subpopulation genetic diversity which is equal to 0.4621.
The total inferred genetic diversity is similar to that estimated by Nei's method [26] ( Table 2).
Estimating the loss and gain of genetic diversity allows better management of stocks and varieties to be retained. This estimate is done by retrieving one or more populations from the gene pool and recalculating the total gene diversity (or its counterpart, i.e.: average coancestry) ( Table 8). The removal of the Captive population will increase the overall genetic diversity of the meta-population

Measurement of Allelic Richness with Rarefaction
The allelic richness with K (42) or without rarefaction K in all the subpopulations studied is presented in Table 9.
The proportions of contribution of each population to the total allelic diversity obtained after rarefaction are summarized in (Table 10). The total allelic diversity is estimated to 4.6723  (Table 11). The results obtained are in agreement with those mentioned in (Table 10), which show that the CO6 population is the most favorable for the program and conservation Table 9. Number of rare alleles and allelic richness K obtained after rarefaction on a common number of 42 genes.

Subpopulation Contribution to the Total Genetic Diversity
The optimal contributions of each population to an artificial germplasm are presented in (Table 12)  If the interest is to minimize total coancestry and thus maximizing total diversity, λ must take a value equal to 1. Finally, if much importance is given to the within subpopulation component, the value of λ must be greater than 1.

Discussion
Management of genetic variation is critical for vulnerable species raised in captivity in reserves (ex situ), and for wild animal species living in their original and natural habitats (in situ). In captive breeding systems, the regular recruitment of new wild populations is often beneficial for stable and sustainable maintenance of genetic variability. However, wild founder populations may be spatially structured and fragmented, and this differentiation in finite and isolated populations may lead to the appearance of consanguinity and genetic homogeneity, and Table 11. Gain (−) or loss (+) of allelic diversity (in %) after retrieving each population. consequently to the deterioration of overall genetic variability. For Houbara bustards bred in captivity, the use of selectively neutral molecular markers allowed a better assessment and quantification of genetic diversity (i.e.: gene and allelic diversity) at both within and between subpopulation levels.
Consequently, several findings have emerged and have been shown to be effective for ex situ conservation priorities and policies.
Calculations of genetic diversity of each subpopulation, as well as of the overall metapopulation showed that the wild populations of Errachidia, Boudnib and CO6 possess the most diversity compared to the wild population of Erfoud and Captive of 1995-2004. The average inbreeding and coancestry coefficients confirmed the origin of the Captive population from the wild populations of Erfoud-Errachidia-Boudnib area. The partitioning of total genetic diversity has also made it easy to optimize the contribution of each population to an artificial gene pool with the maximum genetic diversity. According to Eding et al. [27] and Fabuel et al. [28], the choice of the value of the population factor λ will depend on the objective and the final goal to be achieved in this optimization. Indeed, if a short-term selection response is aimed, the most frequent and common alleles should be favored, in which case the parameter λ will take small values. On the contrary, if the private alleles are to be maintained and preserved in the artificial population, the λ factor must take on larger values.
From a more general perspective of conservation and management of the Houbara breeding flock, if the ultimate objective of conservation is to maintain among subpopulation diversity, the wild population CO6 and the Captive population will be the most favored for two reasons: 1) they are the most distant However, more attention is needed during cross-breeding operations to avoid the risk of depression of exogamy. If the conservation strategy and priorities are to preserve intra-population diversity, the Errachidia population and the CO6 wild population should be favored given their large contribution proportions for λ = 2 and λ = 5.
In practice, the most widely adopted approach for maintaining genetic diversity, restricting and limiting inbreeding depression is to optimize parental contributions to the next generation through minimization of the overall coancestry of a particular metapopulation [29]. This strategy leads to a maximization of the global genetic diversity in terms of expected heterozygosity and effective population size [30].
In conclusion, the partition of allelic richness proposed by Petit et al. [5] is dependent only on the number of private alleles present in a population, so that the population can contribute to total allelic richness only if it has rare and unique alleles, otherwise its contribution will be zero. In contrast to El Mousadik and Petit [22] and Petit et al. [5], the procedure proposed by Caballero and Rodríguez-Ramilo [23] takes into account rare alleles and common alleles in the estimation of between subpopulation allelic differences. Open Journal of Applied Sciences From a long-term perspective, allelic richness is more advantageous than gene diversity for two reasons. First, it is the most sensitive to bottleneck events and therefore better reflects the old fluctuations of the effective population size [31].
Second, the limit of response to selection is often determined by the initial number alleles in a population [32]. However, short-term responses to inbreeding selection and depression are directly related to gene diversity.
In fact, in the selection of parents, the system of captive crosses must be added, since structuring and genetic differentiation in a meta-population is directly related to the type of coupling regime applied (circular, rotational, etc.) [33].
However, the impact of genetic diversity on maximizing genetic diversity is generally less important than the contribution of parents.
At the end of this comparative study, allele and gene diversities are two important criteria, which are not necessarily equivalent but are complementary, especially when it comes to preserving genetic diversity and identification of conservation units.