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.
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 1993, the Houbara bustard has been bred in captivity by the Prince Sultan Bin Abdul Aziz Al Saud Foundation (IFCDW) in Agadir, Morocco, and several conservation methods were developed. Generally, maintaining and preserving genetic diversity is essential in this type of program, as the loss and deterioration of genetic diversity and increased inbreeding may lead to inbreeding depression, bottlenecks, non-adaptation to environmental change, and consequently extinction of species and populations [
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 [
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 [
Furthermore, among the causes of decline of genetic diversity, is the reduction of the effective size of a population ( N e ) 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.
A total of 799 birds belonging to 5 different populations were used for this study (
Genomic DNA was extracted from blood samples and genotyped by Polymerase Chain Reaction (PCR), using 4 pairs of polymorphic primers: A210, D117, D110 and A205 as described elsewhere [
Subpopulations | Number | Origin | Date of sampling |
---|---|---|---|
Subpopulation 1 | 25 | Wild from Erfoud | 1993-1994 |
Subpopulation 2 | 21 | Wild from Boudnib | 1993-1994 |
Subpopulation 3 | 89 | Wild from Errachidia | 1993-1994 |
Subpopulation 4 | 562 | Captive and issued from populations 1, 2 and 3 | 1995-2004 |
Subpopulation 5 (CO6) | 102 | Wild from the East of Morocco (Towards Algeria) | 2006 |
Total heterozygosity ( H T ) and allele frequencies were calculated using Arlequin v.3.5.1.2 [
H T = 2 n 2 ( n − 1 ) ( 1 − ∑ i = 1 n p i 2 ) , with the mean p i allele frequencies of the ith allele
in all populations or subpopulations studied. The effective number of alleles
( N e = 1 ∑ i = 1 n p i 2 ) [
( I = − ∑ i = 1 n p i ln ( p i ) were also estimated by GenAlex [
[
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 F S T and its probability value (P-value) between different pairs of populations.
According to Malécot [
The theories of Caballero and Toro [
In general, considering a metapopulation composed of n populations or subpopulations of N i individuals, the average coefficient of inbreeding of the subpopulation i is: ( F i = 2 s i − 1 ) with s i the average self coancestry of all the individuals. Also, the average distance between the individuals belonging to
subpopulations i and j is defined as D i j = [ ( s i + s j ) 2 ] − f i j . As for the minimum
distance of Nei (1987) it is calculated by applying the equation:
D i j ( N e i ) = D i j − [ ( D i i + D j j ) 2 ] = [ ( f i i + f j j ) 2 ] − f i j , with ( f i i ) and ( f j j ) the average
coancestries, ( D i i ) and ( D i j ) of subpopulations I and j, respectively.
Furthermore, at the within subpopulation level, the average coefficient of
coancestry is expressed as: f ˜ = ∑ i = 1 n f i i N i N T , the average of self-coancestry as: s ˜ = ∑ i = 1 n s i N i N T , the average inbreeding coefficient as: F ˜ = ∑ i = 1 n F i N i N T , and the average distance between individuals as: D ˜ = s ˜ − f ˜ = ∑ i = 1 n D i i N i N T with, N T = ∑ i = 1 n N i as the
overall size of the metapopulation. Consequently, the average coancestry and genetic distance over the entire metapopulation are:
f ¯ = f ˜ − D ¯ = ∑ i = 1 n f i i N i N T − D ¯ = ∑ i , j = 1 n f i j N i N j N T 2 = ∑ i = 1 n N i N T [ f i i − ∑ j = 1 n D i j N j N T ] and
D ¯ = ∑ i , j = 1 n D i j N i N j N T 2 , respectively. Total gene diversity ( D G T = 1 − f ¯ ) is thus, com-
posed of between subpopulation diversity ( D G B S = f ˜ − f ¯ ) and within subpopulation diversity ( D G W S = 1 − f ˜ ). The latter is the sum of within individual diversity ( D G W I = 1 − s ˜ ) and among individual diversity ( D G B I = 1 − s ˜ ). The contributions of subpopulations i and j to the next generation can be extracted from the total gene diversity by applying the following equation:
D G T = 1 − f ¯ = 1 − ∑ i , j = 1 n f i j c i c j = 1 − ∑ i = 1 n c i ( f i i − ∑ j = 1 n D i j c j ) . Finally, Wright’s coefficient
[
F S T = G D B S G D T = f ˜ − f ¯ 1 − f ¯ .
The aforementioned analyses were carried out using the METAPOP v.2.0.a3 software [
The allelic richness or the number of alleles per locus is estimated based on the classical rarefaction method proposed by El Mousadik and Petit [
given locus is: A i = ∑ k = 1 K ( 1 − P i k ) with, P i k = ( N i − N i k ) g ( N i ) g .
By analogy with the coefficient of genetic differentiation F S T , a coefficient of differentiation of allelic richness was also proposed by El Mousadik and Petit
[
richness, R T the total allelic richness, and a i 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 [
allelic diversity is calculated as: A S = R S − 1 = [ 1 n ∑ i = 1 n a i ] − 1 , while the mean allelic
distance between populations i is calculated as:
d A , i j = 1 2 ∑ k = 1 K [ ( 1 − P i k ) P j k + P i k ( 1 − P j k ) ] . The average distance between all the populations is thus equal to: D A = 1 n 2 ( ∑ i , j = 1 n d A , i j ) . Therefore, the total allelic diversity is given as: A T = A S + D A = [ 1 n ∑ i = 1 n ( a i + 1 n ∑ j = 1 n d i j ) ] − 1 = [ 1 n 2 ∑ k = 1 K ∑ i , j = 1 n ( 1 − P i k P j k ) ] − 1 .
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: A S T = D A A T = A T − A S A T .
The method of Kirkpatrick et al. [
The Fisher’s exact test revealed no linkage disequilibrium between the different loci. Micro-checker software also did not detect any signs of marginalization of large alleles, genotyping and profiling errors or the existence of null alleles. The amplification of the four microsatellites generated 28 alleles in total for the 799 individuals studied. No private or rare alleles were detected in the wild populations of Erfoud, Errachidia, Boudnib or the captive population of 1995-2004. On the other hand, among the 2006 wild population (CO6), 3 alleles (162) were revealed at the locus D117 (corresponding to an allelic frequency of 0.015) and 8 alleles (233) at the A205 locus (corresponding to an allelic frequency of 0.039) (
In
Loci | Erfoud | Boudnib | Errachidia | Captive | CO6 | Het. Total |
---|---|---|---|---|---|---|
A210 | 0.8057 | 0.8141 | 0.7915 | 0.7922 | 0.7769 | 0.7930 |
D117 | 0.6232 | 0.6538 | 0.6609 | 0.6217 | 0.6501 | 0.6322 |
D110 | 0.6114 | 0.6771 | 0.6738 | 0.6740 | 0.6265 | 0.6670 |
A205 | 0.6342 | 0.6190 | 0.6524 | 0.5399 | 0.6740 | 0.6533 |
Average | 0.6686 | 0.6910 | 0.6946 | 0.6569 | 0.6819 | 0.6864 |
Standard deviation | 0.0918 | 0.0854 | 0.0651 | 0.1057 | 0.0662 | 0.0725 |
decrease of ( H e ) could be explained by the moderate diversity in 205 locus (0.5399).
The genetic variability quantified by AMOVA showed a slight structuration between the populations of Houbara bustards, with 92.25% variation within the populations compared with only 7.75% between the populations. However, the coefficient of differentiation was not significant at 5% ( F S T = 0.077 , P-value < 0.05) (
From the indices of fixation F S T presented in (
The allelic richness varies between 5 and 9 for loci D117 and A205, respectively (
In parallel with the analysis carried out by the METAPOP software, the average coancestry over the entire metapopulation was calculated by MOLKIN v.3.0 and estimated at f ¯ = 0.313104 . As already mentioned, the captive population is issued from the crosses between individuals belonging to the founding populations of Erfoud, Errachidia and Boudnib. This can explain, on one hand, the high values of the coefficients f i j (0.3354, 0.3221 and 0.3232) and on the other hand, the small values of Nei’s distances among individuals corresponding to them (0.0070, 0.0042 and 0.0109) (
The wild population in 2006 (CO6) is the most distant of the other populations ( D i j ranging from 0.0794 to 0.0986). The mean minimum Nei distance of the entire meta-population is estimated at ( D i j = 0.0226 ). This is also equal to inter-population genetic diversity f ˜ − f ¯ = [ 1 − f ¯ ] − [ 1 − f ˜ ] . This result is in support with the result obtained by Harlequin in
Source of variation | Degree of freedom | Sum of squares | % of variation |
---|---|---|---|
Inter-populations | 4 | 64.693 | 7.75 |
Intra-populations | 1593 | 1520.577 | 92.25 |
Total | 1597 | 1585.270 | 100.00 |
Erfoud | Boudnib | Errachidia | Captive | CO6 | |
---|---|---|---|---|---|
Erfoud | * | 0.6666 | 0.5135 | 0.5945 | 0.0000 |
Boudnib | −0.0046 | * | 0.7297 | 0.2522 | 0.0000 |
Errachidia | −0.0001 | −0.0046 | * | 0.2703 | 0.0000 |
Captive | −0.0017 | 0.0042 | 0.0043 | * | 0.0000 |
CO6 | 0.1349 | 0.1301 | 0.1227 | 0.1554 | * |
Subpopulation | f i i | s i | F i | d i i |
---|---|---|---|---|
Erfoud | 0.3344 | 0.6667 | 0.3333 | 0.3223 |
Boudnib | 0.3254 | 0.6429 | 0.2857 | 0.3175 |
Errachidia | 0.3094 | 0.6676 | 0.3352 | 0.3582 |
Captive | 0.3430 | 0.7007 | 0.4014 | 0.3577 |
CO6 | 0.3216 | 0.6955 | 0.3910 | 0.3739 |
Average | f ˜ = 0.3361 | s ˜ = 0.6938 | F ¯ = 0.3875 | D ¯ = 0.3576 |
Subpopulations | f i j | D i j ( N e i ) |
---|---|---|
Erfoud & Boudnib | 0.3220 | 0.0105 |
Erfoud & Errachidia | 0.3171 | 0.0096 |
Erfoud & Captive | 0.3354 | 0.0070 |
Erfoud & CO6 | 0.2412 | 0.0912 |
Boudnib & Errachidia | 0.3101 | 0.0073 |
Boudnib & Captive | 0.3232 | 0.0109 |
Boudnib & CO6 | 0.2346 | 0.0886 |
Errachidia & Captive | 0.3221 | 0.0042 |
Errachidia & CO6 | 0.2360 | 0.0794 |
Captive & CO6 | 0.2337 | 0.0986 |
value of genetic structuring measured by the index F S T to 0.07752 (AMOVA).
If the different populations are forced to contribute to the next generation, the components of the overall metapopulation genetic diversity D G T could be partitioned as mentioned in (
With
D G T = 1 − f ¯ = [ ( 1 − s ˜ ) + ( s ˜ − f ˜ ) ] + [ f ˜ − f ¯ ] = [ 1 − f ˜ ] + [ f ˜ − f ¯ ] = 0.3062 + 0.3576 + 0.0226 = 0.6639 + 0.0226 = 0.6865 .
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 [
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) (
Subpopulation | Contribution to the D G W I | Contribution to the D G B I | Contribution to the D G W S | Contribution to the D G B S | Contribution to the D G T |
---|---|---|---|---|---|
Erfoud | 0.0104 | 0.0101 | 0.0205 | 0.0007 | 0.0213 |
Boudnib | 0.0094 | 0.0083 | 0.0177 | 0.0006 | 0.0183 |
Errachidia | 0.0370 | 0.0399 | 0.0769 | 0.0022 | 0.0792 |
Captive | 0.2105 | 0.2516 | 0.4621 | 0.0175 | 0.4796 |
CO6 | 0.0389 | 0.0477 | 0.0866 | 0.0089 | 0.0955 |
Total | 1 − s ˜ = 0.3062 | s ˜ − f ˜ = 0.3576 | 1 − f ˜ = 0.6639 | f ˜ − f ¯ = 0.0226 | 1 − f ¯ = 0.6865 |
Subpopulation removed | D G T | i | Within subpopulation (Intra-individuals) | Within subpopulation (Inter-individuals) | Among subpopulations | H T |
---|---|---|---|---|---|
Erfoud | 0.6870 | −0.1274 | 0.1662 | 0.0331 | 0.07 |
Boudnib | 0.6863 | −0.2002 | 0.1580 | 0.0160 | −0.02 |
Errachidia | 0.6853 | −0.4781 | −0.0098 | 0.3141 | −0.17 |
Captive | 0.7218 | 2.2777 | −0.0115 | 2.6324 | 4.89 |
CO6 | 0.6639 | 0.0381 | −0.3588 | −3.0796 | −3.40 |
by 4.89%, whereas, the one of the wild CO6 population will result in a 3.40% loss in overall gene diversity due to decreased diversity or between subpopulation distance (−3.07%).
The allelic richness with K (42) or without rarefaction K in all the subpopulations studied is presented in
The proportions of contribution of each population to the total allelic diversity obtained after rarefaction are summarized in (
The percentages of gain (−) and loss (+) of allelic diversity recalculated after elimination of each bustard subpopulation are shown in (
Subpopulation | No. of private alleles | No. of alleles/locus (K) | No. of alleles/locus after rarefaction K(42) |
---|---|---|---|
Efroud | 0 | 5.00 | 4.88 |
Boudnib | 0 | 5.25 | 5.25 |
Errachidia | 0 | 5.75 | 5.19 |
Captive | 0 | 6.50 | 4.82 |
CO6 | 11 | 6.50 | 5.23 |
Total | 11 | 7.00 | 5.29 |
Subpopulation | Within subpopulation level | Between subpopulation level | Total |
---|---|---|---|
Erfoud | 0.7766 | 0.0961 | 0.8727 |
Boudnib | 0.8500 | 0.1069 | 0.9569 |
Errachidia | 0.8387 | 0.1064 | 0.9450 |
Captive | 0.7620 | 0.1248 | 0.8868 |
CO6 | 0.8461 | 0.1649 | 1.0109 |
Total | AS = 4.0733 | DA = 0.5990 | AT = 4.6723 |
priorities, especially in the long term, unlike the Captive and Erfoud populations.
The optimal contributions of each population to an artificial germplasm are presented in (
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
Excluded subpopulation | Level (intra-population) | Level (inter-population) | Total |
---|---|---|---|
Erfoud | −1.0181 | −0.9190 | −1.9371 |
Boudnib | 0.9455 | −0.0617 | 0.8838 |
Errachidia | 0.6421 | −0.5114 | 0.1307 |
Captive | −1.4094 | 0.5196 | −0.8897 |
CO6 | 0.8399 | 3.1249 | 3.9648 |
Contribution (%) | ||||
---|---|---|---|---|
Subpopulation | λ = 0 | λ = 1 | λ = 2 | λ = 5 |
Erfoud | 3.10 | 0.00 | 0.00 | 0.00 |
Boudnib | 3.40 | 1.50 | 0.00 | 0.00 |
Errachidia | 0.00 | 52.3 | 57.7 | 69.3 |
Captive | 44.1 | 0.00 | 0.00 | 0.00 |
CO6 | 49.1 | 46.1 | 42.3 | 30.70 |
DGpool | 0.7167 | 0.7239 | 0.7237 | 0.7201 |
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. [
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 ( D i j = 0.986 ), and 2) the proportions of contribution to a synthetic population are considerable (49.1% and 44.1% for a value of λ = 0).
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 [
In conclusion, the partition of allelic richness proposed by Petit et al. [
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 [
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.) [
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.
The authors are very grateful to the Late Prince Sultan Bin Abdul Aziz Al Saud for sponsoring this study and for the research facilities.
Korrida, A., Benameur, B., Filali, K. and Jadallah, S.J. (2018) Genetic Diversity Management of Moroccan Captive-Bred Houbaras. Open Journal of Applied Sciences, 8, 47-61 https://doi.org/10.4236/ojapps.2018.82004