Monitoring of genetic diversity in Taiwan conserved chickens assessed by pedigree and molecular data

Livestock Science 184 (2016) 85–91

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Monitoring of genetic diversity in Taiwan conserved chickens assessed by pedigree and molecular data Manh-Hung Pham a,b,n, Xuan-Hoan Tran c, Cécile Berthouly-Salazar d, Michèle Tixier-Boichard e, Chih-Feng Chen a,f, Yen-Pai Lee a a

Department of Animal Science, National Chung-Hsing University, Taichung 40227, Taiwan Faculty of Animal Science, Vietnam National University of Agriculture, Trau Quy Town, Gia Lam District, Ha Noi City, VietNam c Key Laboratory of Animal Cell Technology, National Institute of Animal Sciences, Tu Liem, Hanoi, VietNam d Institut de Recherche pour le Développement, UMR Diversité, Adaptation et Développement des Plantes (DIADE), Avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France e INRA/AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, Jouy-en-Josas, France f Research Center for Integrative and Evolutionary Galliformes Genomics (iEGG), National Chung-Hsing University, Taichung 40227, Taiwan b

art ic l e i nf o

a b s t r a c t

Article history: Received 9 August 2015 Received in revised form 27 December 2015 Accepted 29 December 2015

Local chicken breeds face high risks of extinction. A conservation program has been set up for eight Taiwan conserved chicken populations (TCP). The research presented here aims at estimating effective population size (Ne) and conservation priorities of TCP populations using pedigree and molecular data. Genome diversity was assessed by genotyping 22 microsatellite markers in 45–50 animals per breed. Results from the pedigree-based analysis showed that most Ne values ranged between 50 and 100 except the Shek-Ki breed which exhibited the smallest value (46) so that most breeds could be considered as safe from a conservation point of view. The change in inbreeding per generation varied between 0.7% to 1.9% depending on breeds. Ne values estimated from molecular-based analysis were generally lower than those estimated from pedigree-based analysis, suggesting a loss of diversity between the onset of the conservation program (from 1983 to 1995) and the start of pedigree recording in 2002. According to Ne values, the TCP populations do not appear to be at a high risk, but mating plans by a rotation mating system should be designed in order to limit the increase in inbreeding. Regarding the conservation strategy within the TCP, the Shek-Ki and Hua-Tung breeds showed the highest priority for conservation in terms of genetic risk status and contributions to total diversity across pedigree- and molecular-based approaches. In conclusion, this study of TCP populations shows how different types of data can be combined to define conservation priorities considering risk, diversity, or utility of local chicken breeds. & 2016 Published by Elsevier B.V.

Keywords: Conservation priorities Effective population sizes Inbreeding Molecular data Pedigree information

1. Introduction Local chicken breeds play an important role in Taiwan due to the traditional cuisine and culture. Local chicken breeds may carry disease-resistant genes and show high abilities to adapt to alternative farming systems, such as organic, which will particularly improve animal welfare and food safety (Fanatico et al., 2009; Pham et al., 2012) as well as adaptation to harsh environmental conditions (Tixier-Boichard et al., 2009). Phenotypic data and pedigree

n Corresponding author at: Faculty of Animal Science, Vietnam National University of Agriculture, Trau Quy Town, Gia Lam District, Ha Noi City, VietNam. E-mail addresses: [email protected] (M.-H. Pham), [email protected] (X.-H. Tran), [email protected] (C. Berthouly-Salazar), [email protected] (M. Tixier-Boichard), [email protected] (C.-F. Chen), [email protected] (Y.-P. Lee).

http://dx.doi.org/10.1016/j.livsci.2015.12.013 1871-1413/& 2016 Published by Elsevier B.V.

information have proven to be useful for characterization and management of genetic diversity (Boichard et al., 1997; Tixier-Boichard et al., 2009; Lenstra et al., 2012). Unfortunately, phenotypic data and pedigree records of local chickens are rarely documented in reality (Tixier-Boichard et al., 2009). Therefore, molecular markers are used to monitor the loss of genetic diversity of populations and set priorities for conservation (Boettcher et al., 2010). FAO (2014) reported that 21.3 percent of chicken breeds in the world were classified as being at risk of extinction, highlighting the importance to assess genetic diversity and the current population status. This percentage might be higher than that because of a large number of populations with an unknown status in developing countries. Basically, there are three strategies for setting priorities in conservation such as the maximum-risk strategy, the maximum-diversity strategy as well as the maximum-utility strategy (Bennewitz et al., 2007). The maximum-risk strategy is based on the numbers of

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breeding animals (FAO, 2000), inbreeding rate (EAAP, 1998; Meuwissen, 2009) and recommended effective population size (Ne) (Meuwissen, 2009). The Ne measures the number of breeding individuals in an idealized population in equilibrium that would show a similar trend in inbreeding as the population under study, it is one of the most pivotal parameters in both evolutionary biology and conservation of genetic diversity (Waples and Do, 2010; Goyache et al., 2011; Leroy et al., 2013). This parameter is considered as one of the major criteria for monitoring risk status in livestock populations because it accounts for inbreeding and loss of genetic diversity through random genetic drift (Falconer and Mackay, 1996; Meuwissen, 2009). Leroy et al. (2013) showed that estimates of effective population size varied according to the within-breed genetic structure, for different species (i.e. cattle, dog, horse and sheep). The maximum-diversity strategy defines that a breed is selected for conservation when it contributes significantly to the overall genetic diversity weighted by both the between- and within-breed diversity. Breeds can be ranked according to their contribution either to the actual or to the predicted future diversity (Bennewitz et al., 2007). For instance, Zanetti et al. (2010) set up conservation priorities for five Italian local chicken breeds undergoing in situ conservation using 20 microsatellites. In the case of Vietnamese domestic chickens, Pham et al. (2013a) showed that black H’mong, Lien Minh and Luong Phuong were ranked with the highest priorities for conservation according to Caballero and Toro (2002), and Petit et al. (1998) approaches, taking into account within- and between-breeds components of diversity. When possible, pedigree information and molecular data should be combined for decision making of conservation priorities (Zanetti et al., 2010). Pedigree-based and molecular-based estimates of genetic diversity may be more or less correlated depending on the pedigree completeness and the number of markers (Toro et al., 2006) as illustrated in Iberian pigs with correlations between pedigree inbreeding and marker homozygosity ranging from 0.69 with 49 microsatellites (Toro et al., 2002) to 0.92 with 60 K SNPs (Silió et al., 2010). Furthermore, perfect correlations between approaches cannot be reached because pedigree-based estimates do not take into account Mendelian sampling, and it is known that full-sibs would share between 45% and 55% of their genes rather than exactly 50% in a traditional relationship matrix (VanRaden and Tooker, 2007). An additional difference between pedigree- and molecular-based analyses is the definition of the founder population, which depends on the depth of pedigree for pedigree-based analysis, the more complete the pedigree, the more ancient the founder population (Falconer and Mackay, 1996). Consequently, pedigree- and molecular-based analysis is using different information, as pedigree-based analysis reflects only diversity due to relatively recent ancestry, depending on the population history (Toro et al., 2006; Engelsma et al., 2012). The purposes of this study were (i) to assess genetic diversity with pedigree-based estimates and molecular-based estimates for eight populations kept under a conservation program in Taiwan since 1982, and (ii) to monitor trends in genetic diversity and to make recommendations for conservation strategy.

2. Material and methods 2.1. Data Conservation of native chickens in Taiwan started from 1982, when native chickens were collected around the islands and conserved at National Chung-Hsing University (NCHU) experimental farm. Eight Taiwan conserved chicken populations (TCP: B strain, L2 strain, Hsin-Yi, Hua-Tung, Ju-Chi, Nagoya, Quemoy and

Table 1 Pedigree information in the first generation of the eight populations when conservation program started. Population

First generation

B strain (BS) L2 strain (LS) Hsin-Yi (HY) Hua-Tung (HT) Ju-Chi (JC) Nagoya (NG) Quemoy (KM) Shek-Ki (KT)

Year

Sire

Dam

Nes

ΔF

1984 1984 1984 1990 1986 1989 1995 1989

6 5 7 2 12 9 1 6

20 28 15 4 38 22 4 19

18.5 17.0 19.1 5.3 36.5 25.5 3.2 18.2

2.71 2.95 2.62 9.38 1.37 1.96 15.63 2.74

Nes, effective population size based on number of sires and dams; and ΔF, rate of hypothetical inbreeding (in percentage) for a population with such an effective population size.

Shek-Ki) have been conserved at NCHU experimental farm since then (Lee, 2006). The L2 and B strains were selected by NCHU from the same Taiwan native chicken population (Lee, 2006). Both strains were closed populations since their establishment in 1983, while B strain was a male line and a L2 female line for crossing to produce commercial meat-type chicken. Since then, they have been selected for 24 and 26 generations, respectively, and have been extensively used in research as well as in production (Chao and Lee, 2001; Chen et al., 2007; Pham et al., 2013b). A small number of parents were used to set up the first generation for eight populations between 1984 and 1995 (Table 1). The management of conserved chicken populations followed a routine procedure (Chao and Lee, 2001). Chicks were raised in floor pens until 16 week of age, when they were transferred to individual wire floored cages. Artificial insemination was individually used for the female chickens with sire known and dam known. On the average, the generation interval of TCP populations was one generation per year (Table 2). For the present study, pedigree information recorded between 2002 (starting with ancestors in 2001) and 2008 were used to estimate the effective population size with different methods. The pedigree information included a total of 4283 individuals and the numbers of founders at the onset of pedigree recording are shown in Table 2. In addition, samples from 383 individuals (i.e. 288 individuals from six TCP born in 2003 and 95 individuals from B and L2 strains born in 2008) were genotyped and part of the data was previously published (Berthouly et al., 2008; Chang et al., 2012; Pham et al., 2013b). Briefly, an average of 48 individuals per population was genotyped for 22 microsatellites among FAO (2011) recommended markers. These Table 2 Number of founders at the onset of pedigree recording and average number of male and female in the 2002–2008 periods for the eight populations. Population

B strain L2 strain Hsin-Yi Hua-Tung Ju-Chi Nagoya Quemoy Shek-Ki

Founders in 2001

2002–2008 generations

Sire

Dam

Nes

ΔF

Nm

Nf

Nes

ΔF

g2008

5 16 22 19 19 21 25 16

35 328 30 40 36 39 44 35

17.5 61.0 50.8 51.5 49.7 54.6 63.8 43.9

2.86 0.82 0.98 0.97 1.01 0.92 0.78 1.14

11.2 20.8 17.6 17.7 20.1 17.7 16.7 13.6

76.8 194.2 34.1 37.4 40.4 43.4 43.1 32.6

39.1 75.2 46.4 48.1 53.8 50.3 48.2 38.3

1.28 0.67 1.08 1.04 0.93 0.99 1.04 1.30

6 5 6 6 6 6 6 6

Nes, effective population size based on number of founder animals; ΔF, rate of hypothetical inbreeding (in percentage) expected for a population with Nes; Nm, average number of male; Nf, average number of female; Nes, effective population size based on number of breeding animals; and ΔF, rate of hypothetical inbreeding (in percentage) expected for a population with Nes across the 2002–2008 generations; g2008, number of generations known for the last generations.

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samples were used to estimate the contemporary effective population size and contributions to diversity. 2.2. Demographic and Pedigree-based analysis 2.2.1. Effective number of founders The effective number of founders (fe) is the number of equally contributing founders, which would give the same amount of genetic diversity that is present in the current population. This was calculated as in Lacy (1989), and it is usually much smaller than the actual number of founders in pedigree (animals with both parents unknown) because of unequal contributions of founders to the current population. 2.2.2. Effective number of ancestors The effective number of ancestors (fa) was calculated as in Boichard et al. (1997), explaining the complete genetic diversity of a population. When compared with the effective number of founders, it provides evidence of bottlenecks that occurred in population in the past. 2.2.3. Effective number of founder genomes The loss of genetic diversity would occur due to genetic drift in a small population, even if founders would contribute equally to this population (Ballou and Lacy, 1995). Therefore, the effective number of founder genomes or founder genome equivalent (fge) is defined as the number of equally contributing founders with no loss of founder alleles that would give the same amount of genetic diversity as is present in the reference population. The fge was calculated as in Caballero and Toro (2000). It accounts for the loss of genetic diversity that occurred in the population due to genetic drift and bottlenecks. 2.2.4. Effective number of nonfounders The effective number of nonfounders (Nenf) was calculated as ⎛ 1 1 ⎞−1 Nenf = ⎜ f – f ⎟ , where Nenf accounts for the contributions of ⎝ ge e ⎠ nonfounders and for loss of genetic diversity due to drift accumulated over nonfounder generations (Caballero and Toro, 2000). 2.2.5. Measure of the loss of genetic diversity Measures of the loss of genetic diversity can be derived from fe, fge, and Nenf. The amount of genetic diversity (GD) in the reference population was computed according to Lacy (1995) as 1 GD = 1 − 2f . When expressed as 1
GD, it measures the genetic ge

diversity loss in the population since the founder generation, as a 1 result from both genetic drift and bottlenecks. GD* = 1 – 2f , e

*

1
GD measures the loss of genetic diversity that occurred in the population due to the unequal contributions of founders before their contributions converged (Caballero and Toro, 2000). The 1 difference between GD* and GD is GD* − GD = 2N , which meaenf

sures the loss of diversity by genetic drift accumulated over nonfounder generations (Caballero and Toro, 2000). 2.2.6. Effective population size based on the mating plan The estimation of effective population size based on number of sires and dams (Nes) follows Wright’s (1931) model. This method makes possible to predict Nes under several assumptions, including random mating, absence of selection and random variation of progeny size across parents (Leroy et al., 2013). Computation of Nes only requires the estimated numbers of breeding males (Nm) and females (Nf) in the reference population using the

equation: Nes =

4Nm Nf . Nm +Nf

87

The increment of hypothetical inbreeding

(ΔF) is inversely proportional to the number of Nes: ΔF =

1 . 2Nes

2.2.7. Effective population size based on individual inbreeding rate The effective population size based on the individual increase in inbreeding (Nei) was computed for each population (Gutiérrez et al., 2008). The individual increase in inbreeding is defined as g −1 ΔFi = 1– i 1– Fi , where Fi is the inbreeding coefficient for each individual i, and gi is the equivalent complete generations (Gutiérrez et al., 2009). The mean of the ΔFi values computed for the n individuals belonging to a given population of individuals (ΔF ) can be used to estimate Nei by the method of Cervantes et al. (2008) 1 for each of these reference populations as Nei = 2ΔF . 2.2.8. Effective population size based on individual coancestry rate The realised effective population size (Nec) was calculated for each population based on the individual increase in coancestry rates (Cervantes et al., 2011). The increase in coancestry between (gj + g k )

any pair of j and k can be computed as Δcjk = 1 − 2 1 − Cjk , where cjk is the inbreeding of an offspring from j and k, and gj and gk are the number of equivalent complete generations for individual j and k, respectively. By averaging the increase in coancestry for all pairs of individuals in a reference subpopulation, we can estimate an effective population size based on coancestries as 1 Nec = 2Δc . The confidence interval of the estimated values of Nei and Nec can be computed using the variance of ΔFi and Δcjk from the individuals in each population (Gutiérrez et al., 2008). The genealogical information was analyzed using the program Endog v4.8, a computer program for monitoring genetic variability of populations using pedigree information (Gutiérrez and Goyache, 2005). 2.3. Degree of nonrandom mating The degree of nonrandom mating (α) was measured by the correlation of genes within individuals relative to the correlation of genes taken at random from the population as in Caballero and Toro (2000). This coefficient gives an indication of the deviation from Hardy–Weinberg equilibrium expectations and it is related to inbreeding and coancestry coefficient by (1
F)¼(1
f)  (1
α), where F and f are the inbreeding and coancestry coefficients, respectively (Wright, 1969). 2.4. Molecular-based analysis 2.4.1. Microsatellites genotyping and polymorphism The presence of null alleles was tested using FreeNA software (Chapuis and Estoup, 2007) in which loci with estimated frequencies of null alleles above 0.2 are considered to be potentially problematic for calculations. The null allele frequency estimated for the 22 loci was lower than 0.2 (data not shown) so we assumed that null alleles were absent and used for our analyses. The matrix of Nei's DA genetic distances (Nei et al., 1983) was computed by Populations package 1.2.32 (Langella, 1999). 2.4.2. Contemporary effective population size Contemporary effective population size (NeLD) was computed from genotypic data by a point estimation method using linkage disequilibrium (Hill, 1981; Waples, 2006). This method was implemented in LDNe program (Waples and Do, 2008), which corrects for biases resulting from the presence of a wide range of sample sizes and rare alleles, and was developed by Waples

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(2006). The NeLD could be calculated for unlinked loci 1 as NeLD = , where r is correlation among alleles and S is 1 (3 × ( r 2 –

S

the following formula: D¼ FST  CB þ(1
FST)  CW.

))

sample size (Hill, 1981; Waples, 2006). All alleles with frequencies less than the critical values (Pcrit) of 0.05 were excluded (Waples and Do, 2008). A jackknife method was used to construct 95% CIs of the estimates. 2.5. Contributions to diversity The contribution of each breed to total genetic diversity was computed by three approaches: a method based on molecular coancestry (Caballero and Toro, 2002), a method based on allelic richness (Petit et al., 1998) and a Weitzman approach modified by Ollivier and Foulley (2005). The method described by Caballero and Toro (2002) uses as a criterion for the maintenance of the maximum overall Nei’s (1987) gene diversity (GD) minimizing the average of molecular kinship within subpopulations (fs), the average of molecular coancestry within metapopulation (fm) and the average of Nei's minimum genetic distance between subpopulations (Nei, 1987). Total gene diversity (GDT) is GDT ¼1
fm. Genetic diversity within subpopulations is GDW ¼1
fs. Genetic diversity between subpopulations is GDB ¼ fs
fm. This approach estimates the genetic diversity remaining when removing a breed. Therefore, a positive value will indicate that higher diversity is obtained when a breed is not included in the dataset. The method described by Petit et al. (1998), is using the rarefied number of alleles per locus, and was applied to assess the contribution of each subpopulation to total allelic richness (CT) in meta-population. The CT included the AR of within-subpopulation diversity (CS) and its divergence from other subpopulations (CD) and therefore taking into account private alleles. In contrast to the method of Caballero and Toro, this one estimates a contribution to genetic diversity. Therefore, positive value would indicate that when population is included into the dataset it would increase genetic diversity. Contributions of the breeds to diversity were computed using Molkin 3.0, a computer program for genetic analysis of populations using molecular coancestry information (Gutiérrez et al., 2005). The method described by Ollivier and Foulley (2005), contributions to between-breeds diversity (CB) were assessed by using marginal loss of genetic diversity, based on DA genetic distances (Nei et al., 1983), following Weitzman approach (Weitzman, 1993) implemented in WEITZPRO (Derban et al., 2002). Withinbreed contributions to diversity (CW) and aggregate diversity (D) were calculated as suggested by Ollivier and Foulley (2005). The D index was obtained after weighting CB by FST and CW by 1
FST as

3. Results and discussion 3.1. Pedigree-based analysis 3.1.1. Inbreeding and effective population size The estimates of hypothetical inbreeding increment per generation are given in Table 2. The highest ΔF was approximately 1.3% found in Shek-Ki and B strain that means that in average 1.3% of heterozygosity was lost per generation. Table 3 showed that the highest increase in inbreeding rates was found for Ju-Chi, HuaTung and Shek-Ki populations at the values of 1.34%, 1.76% and 1.88%, respectively, which exceeded the maximum level of one percent per generation as recommended by Meuwissen (2009). Additional management such as mating decisions (avoidance of mating between relatives by forming 20 mating pairs) and optimum contribution selection (Grundy et al., 1998) should be considered. Avoiding mating between close relatives can be easily performed by a rotation mating system where each male ‘X’ is mated to a group of sisters/half-sisters, and the son of this male ‘X’ will be mated to the daughters of another male ‘Y’ which has no common parents with ‘X’. Another modern way is to calculate coancestry coefficients and to design the mating plan in a way to minimize the average coancestry of parents by the software. Family sizes should be kept homogenous, with always one son kept per sire family and at least one daughter kept per dam. An increase of generation interval for these breeds could also minimize inbreeding and thus a better conservation of their genetic diversity. The estimation of Ne values highly varied between breeds and according to methods. Averaged Nes between 2002–2008 values ranged from 38.3 in Shek-Ki to 75.2 in L2 strain, and were always lower than those estimated for 2001, except for B and L2 strains (Table 2). All but the Shek-Ki breed (Nei: 45.9) showed Nei values within the recommended minimum levels between 50 and 100 to maintain genetic variation for a population in a long term according to Meuwissen (2009). The average coancestry rates, corresponding to the expected inbreeding rates in the next generation, varied from 0.77 in L2 strain to 3.14% in Shek-Ki (Table 3). The Nec values were approximately equal to one-third of the Nei values, as indicated by the Nec/Nei ratio, and ranged from 21.0 in Shek-Ki to 35.9 in L2 strain (Table 3; Fig. 1). The ratio between Nec and Nei values was lower than one, which reflected that no substructure (Wahlund effect) is found within eight populations (Cervantes et al., 2011). Correlations between Nes and other Ne measures (Nei, Nec) were positive but not significant (Spearman's rank correlation ¼0.51,

Table 3 Estimates of effective population sizes for each population obtained by the pedigree and molecular data. Population

B strain L2 strain Hsin-Yi Hua-Tung Ju-Chi Nagoya Quemoy Shek-Ki

Pedigree informationa

Linkage disequilibriumb

n

ΔF

Nei 7 SE

Δc

Nec 7 SE

Nec Nei

n

r

NeLD (95% CI)

595 1346 362 386 424 428 419 323

0.69 0.61 0.75 1.76 1.34 0.79 0.91 1.88

77.8 7 12.0 98.1 7 23.7 72.7 7 27.6 59.3 7 12.3 72.7 7 15.5 76.1 7 14.0 98.7 7 12.8 45.9 7 8.3

1.58 0.77 1.61 2.60 2.47 1.66 2.19 3.14

28.1 71.8 35.972.2 25.4 72.4 22.3 71.8 24.671.9 25.7 72.2 25.5 71.9 21.0 71.8

0.36 0.37 0.35 0.38 0.34 0.34 0.26 0.46

45 50 48 48 48 48 48 48

0.032 0.030 0.040 0.040 0.031 0.031 0.031 0.042

57.7 57.8 16.1 19.9 36.6 38.9 52.7 16.7

(27.4, 305.1) (34.1, 131.7) (12.2, 21.3) (15.0, 26.9) (23.1, 66.5) (23.8, 75.4) (34.4, 94.7) (12.0, 23.5)

a n, number of individuals; ΔF , the rates of inbreeding per generation (in percentage); Nei, effective population size based on individual increase in breeding; Δc , the rates of coancestry per generation (in percentage); Nec, effective population size based on increase in coancestry; and ratio Nec . Nei b n, number of individuals, r, the estimated correlation among alleles; and NeLD, contemporary effective population size for each population.

M.-H. Pham et al. / Livestock Science 184 (2016) 85–91

Fig. 1. Effective population sizes for each population obtained by the pedigree and molecular data. Nei, effective population size based on individual increase in breeding with its standard error bars; Nec, effective population size based on increase in coancestry with its standard error bars; and NeLD, contemporary effective population size for each population.

0.57, P4 0.05). 3.1.2. Genetic contributions For the period between 2002 and 2008, the estimated values of the fe, fa, fge, Nenf and Na50 in eight populations are given in Table 4. They were always higher than the real number of founders recorded in the early generations between 1983 and 1995. In ShekKi, the estimated values were consistently lower than in the remaining seven populations, except for Nenf, which was lower in Hua-Tung. The fe, fa and fge values for Shek-Ki were 21, 20 and 16, respectively. The numbers of ancestors needed to explain 50% of the gene pool ranged from 7 in Shek-Ki to 16 in L2 strain. These results indicate that Shek-Ki has a narrow genetic base and contributes less to the within-breed component of genetic diversity than the remaining populations. The effective number of nonfounders was greatly higher than effective number of founder genomes, which indicates that loss of genetic diversity due to drift was accumulated over nonfounder generations. The loss of overall genetic diversity observed in Hua-Tung and Shek-Ki was 5.2% and 6.3%, respectively. The first loss ranged from 2.6% in Hua-Tung to 3.1% in Shek-Ki due to bottlenecks and genetic drift (Fig. 2). The second loss accounted for unequal founder contribution and ranged from 1.7% in Hua-Tung to 2.4% in Shek-Ki. The remaining loss was due to genetic drift only. 3.2. Degree of nonrandom mating The average inbreeding coefficients were smaller than average Table 4 Genetic contributions of eight Taiwan conserved chicken populations. Population

n

fe

fa

fge

Nenf

Na50

F

f

F2008 7 SE

B strain L2 strain Hsin-Yi Hua-Tung Ju-Chi Nagoya Quemoy Shek-Ki

595 1346 362 386 424 428 419 323

44 87 41 29 28 38 31 21

21 45 38 27 27 31 26 20

31.6 65.5 31.1 19.3 20.3 30.1 22.8 16.0

112.1 265.0 128.8 57.7 73.8 144.8 86.2 67.2

8 16 14 10 10 11 10 7

0.011 0.006 0.010 0.019 0.013 0.008 0.009 0.020

0.017 0.007 0.017 0.026 0.025 0.018 0.022 0.031

0.0517 0.006 0.025 7 0.003 0.048 7 0.015 0.065 7 0.011 0.038 7 0.004 0.0217 0.003 0.0357 0.004 0.0727 0.013

n, number of individuals; fe, estimates of effective number of founders; fa, effective number of ancestors; fge, effective number of founder genomes; Nenf, effective number of nonfounders; Na50, number of ancestors explaining 50% of the gene pool; F, inbreeding coefficient for each population in the 2002–2008 periods; f, coancestry coefficient for each population in the 2002–2008 periods; and F2008, inbreeding coefficient of the last generation in 2008; SE, standard error.

89

Fig. 2. Genetic diversity (GD) loss in eight populations in the period between 2002 and 2008. GD loss due to bottlenecks and genetic drift (1
GD); due to unequal founder contribution (1
GD*); and genetic drift only (GD*
GD).

coancestries in all eight populations (Table 4). Therefore, the degree of nonrandom mating has been negative and mating of highly average-related individuals was successfully avoided. The average inbreeding rates were moderate and ranged from 2.1% in Nagoya to 7.2% in Shek-Ki for the last generation (Table 4). However, these values do not take into account the fact that the founders in 2001 could have been already inbred because each population was closed since several generations. In practice, chickens showing a low individual inbreeding should be chosen for mating in order to maintain the recommended effective population sizes and to prevent the risk of extinction in small populations. 3.3. Molecular-based analysis 3.3.1. Contemporary effective population size The estimates of NeLD were lower than the ones of Nei given by the pedigree-based analysis and that of Nes values (Tables 2 and 3; Fig. 1). The correlations between NeLD and Nes was very low (Spearman’s rank correlation ¼0.24); but it was significantly positive between NeLD, Nei and Nec (Spearman’s rank correlation ¼0.85, 0.83 and 0.83, respectively, P o0.05). The sample size used for genotyping was included in the CIs of NeLD. It is possible that this underestimation is due to the small number of molecular markers used (Waples, 2006; Engelsma et al., 2012). Engelsma et al. (2010) showed that marker density was important in order to assess genetic diversity with heterozygosity estimates but was not so much important when an IBD method was used to assess diversity. The difference between molecular-based estimate of Ne and pedigree-based estimates of Ne could also occur if a loss of diversity took place between the initial founder generation and the first generation included in the pedigree. Pedigree-based estimates are as good as the pedigree data, which, in the present case, represents a quite recent part of the history of populations. According to Toro et al. (2006), some important loci might be highly differentiated because selective forces are strong enough at such loci to overcome the effect of low effective size. In order to maintain genetic diversity in a gene bank of Holstein cattle, Engelsma et al. (2012) concluded that high density SNP-based diversity provided a more detailed knowledge of diversity at the scale of chromosomal regions than pedigree-based estimate of diversity, which remains global. 3.3.2. Contributions to diversity The conservation priorities were mostly consistent across three approaches we used. Contribution to global diversity (GDG) was significantly negatively correlated with total allelic diversity (CT, Spearman’s rank correlation¼
0.83, P o0.05) and with aggregate diversity (D, Spearman's rank correlation¼
0.93, P o0.001). The

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M.-H. Pham et al. / Livestock Science 184 (2016) 85–91

Table 5 Loss or gain of genetic diversity, contributions to allelic richness and aggregate diversity for each of the eight Taiwan conserved chicken breeds. Population

B strain L2 strain Hsin-Yi Hua-Tung Ju-Chi Nagoya Quemoy Shek-Ki

Loss/gain of diversity

Contribution to richness

Weitzman's diversity

GDW

GDB

GDG

CS

CD

CT

CW

CB

D

0.20 0.96
0.68
2.64 1.33 1.56
0.71 0.00


0.41
1.39 1.33 1.57
0.13
3.32 0.54
2.47


0.21
0.44 0.65
1.07 1.21
1.76
0.18
2.47

0.32 1.27 0.72 0.39
0.42
0.64
0.24
1.40

0.47 3.00 1.32 2.89
1.21 3.37 2.58 6.73

0.80 4.27 2.04 3.28
1.64 2.73 2.34 5.33


0.42
1.27 0.89 3.57
1.76
2.04 0.98 0.04

6.55 20.36 4.91 9.27 2.55 31.82 11.09 30.00

1.68 4.63 2.15 5.39
0.47 7.02 4.09 8.29

GDW, change in within-population genetic diversity after removing population i; GDB, change in between-population genetic diversity after removing population i; GDG, change in global diversity after removing population i; CS, a contribution to within-population genetic diversity; CD, a between-population genetic diversity; CT, Total diversity; CW, contribution to within-population diversity; CB, contribution to between-population diversity; and D, aggregate diversity (in percentage).

D index was positively correlated with the CT (Spearman's rank correlation¼0.91, P o0.01). Negative correlation is expected with GDG since it expresses a loss why other methods express a gain. The results showed that Shek-Ki had the highest contributions (GDG ¼
2.47%, CT ¼5.33% and D¼8.29%) to overall genetic diversity (Table 5). Nagoya ranked the second contributions to diversity (GDG ¼
1.76% and D¼7.02%), and the fourth of CT ¼ 2.73% for conservation. Hua-Tung contributed the third rank (GDG ¼
1.07%, CT ¼3.28% and D ¼5.39%), but exhibited the highest GDW for conservation, whereas the traditional Ju-Chi breed had the smallest values of diversity (GDG ¼1.21%, CT ¼
1.64% and D¼
0.47%) for conservation priorities. Overall, the Shek-Ki, HuaTung and Nagoya had high conservation priorities in terms of genetic diversity. However, Shek-Ki and Nagoya exhibited very low within-breed diversity and it was highly differentiated from other breeds and appeared as obvious conservation priorities. When analysed for six TCP (i.e. not including B and L2 strains), the HuaTung contributed the highest to the aggregate diversity (Berthouly et al., 2008). Thus, using a different set of breeds seems to change the relative contribution of each breed, as observed in 24 Vietnamese domestic chicken populations (Pham et al., 2013a). In fact, the main contribution of the Hua-Tung was based on its gene diversity and thus this breed had a high contribution to the gene pool. 3.4. Potential conservation We have analyzed genetic diversity for eight Taiwan conserved chicken breeds based on both pedigree and molecular data. The smallest values of effective population size based on pedigree information were observed in Shek-Ki and Hua-Tung breeds. Thus, the Shek-Ki and Hua-Tung breeds showed high priorities for conservation in terms of genetic risk status and contributions to diversity. In spite of a very small number of founders in the first generation, the Hua-Tung breed exhibited the highest contribution to within-breed diversity. It is likely that the initial founders were very diverse because of the breed history: farmers kept this breed together with others in the backyard, so that Hua-Tung might have been crossed with imported larger game birds from Southeast Asia (Lee, 2006; Berthouly et al., 2008), which have bright black feather and large body size. Quemoy exhibited also a relatively high NeLD and Nei in spite of a very narrow base population. Contrasting with the history of the Hua-Tung breed, the Quemoy breed is expected to be a true native since it was essentially isolated from outside the world between 1949 and around 1990. Although chickens were also kept in the backyard, the original owners intentionally kept them as pure as possible (Chia-Juing Won, personal communication). However, the Quemoy conservation program is the most recent of all populations, since it started in 1995. Thus, it is likely

that effects of genetic drift have been less important in this breed than in others. Therefore, the effective numbers of founder genomes of Hua-Tung and Quemoy showed high values, for different reasons. Considering the maximum-utility approach is also needed before making recommendations for conservation. Conservation priorities should include the market demand, survivability and productivity related to specific genes under existing management conditions, scocio-economics and the needs for research and development (Toro et al., 2006; Pham et al., 2013a). In this respect, Shek-Ki has been selected as a sire line to be distributed to farmers producing the Three Yellow breed for meat consumption in Hong Kong (Berthouly et al., 2008). This breed showed the highest body weight at 16 weeks of age (Chang et al., 2012). Selection for a specific trait has resulted in a reduction of genetic variation (Toro et al., 2011). Chang et al. (2012) showed that Hsin-Yi, Shek-Ki and Hua-Tung males exhibited a better heat tolerance due to a lower panting rate than observed in others. In addition, Hsin-Yi responded to the highest antibody levels from Infectious Bursal Disease (IBD) vaccine. The Quemoy exhibited high antibody response to low pathogenic avian influenza H6N1 virus, Newcastle Disease and IBD vaccines.

4. Conclusions The Shek-Ki breed is of high priority for conservation considering risk and utility, the Hua-Tung breed is of high priority considering risk and diversity, and the Quemoy breed is of high priority considering diversity and utility. Then, the Nagoya breed may be of high priority considering between-breeds diversity, and the Hsin-Yi, B and L2 lines could be considered for conservation on the basis of utility only. Thus, this study of TCP populations shows how different types of data can be combined to define conservation priorities considering risk, diversity, or utility of local breeds.

Conflict of interest statement No actual or potential conflict of interest in relation to this article exists.

Acknowledgments We sincerely appreciate the chicken caretaker at NCHU experimental farm and graduate students for their assistance in pedigree recording. We also would like to thank two anonymous

M.-H. Pham et al. / Livestock Science 184 (2016) 85–91

reviewers to revise the manuscript with several improvements.

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