Livestock Research for Rural Development 24 (7) 2012 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
Goats play an important role for the Albanian farmer community of marginal area. Muzhake is one of local goat breeds distributed in Southeastern part of Albania. Genetic characterization of native breeds is very important in conservation strategy designing. The aim of the present study was to estimate the genetic variability of Muzhake goat breed using microsatellite markers. The genomic DNA from 30 unrelated individuals, was analyzed by typing 30 microsatellite markers. Allele diversity, observed and expected heterozygosities, inbreeding coefficient were calculated. A total of 240 alleles were distinguished. All the microsatellites were highly polymorphic, with mean allelic number of 8, ranging 4-18 per locus.
The observed heterozygosity ranged between 0.33 to 0.93, with mean value of 0.69. PIC values ranged from 0.39 to 0.88, with mean of 0.71. It was noticed a low rate of inbreeding within breed (FIS = 0.07). The effective number of alleles varied from 1.47 to 11.5 with a mean 4.69. The value of Shannon information index (I) ranges from 0.77 to 2.49. A bottleneck analysis indicated no bottleneck in Muzhake breed. The population was not in Hardy-Weinberg equilibrium (HWE) for 9 out 30 loci. The results of the study indicate very high level of gene diversity. Most of the loci showed significant deviation from HWE, probably due to Wahlund effect. The set of used markers was highly informative. The results provided here may be useful in developing a national plan and strategy for the conservation of this breed.
Keywords: bottleneck, genetic diversity, heterozygosity, local goat breed
Microsatellites are markers of choice since they are simple to analyze, highly abundant and highly distributed in the genome. They display a high level of heterozygosity, a greater degree of polymorphisms and Mendelian inheritance. Microsatellites have been widely used for the examining of population structure (Luikart et al 1999; Bozkaya et al 2007), genetic mapping (Dib et al 1996; Roder et al 1998). Microsatellites are also used for evaluation of genetic variability in different livestock species, like cattle (Pandey et al 2006a,b), goat (Aggarwal et al 2007; Ramamoorthi et al 2009; Sadeghi et al 2010, Zhu et al 2011), sheep (Arora and Bhatia, 2004) and horses (Amirinia et al 2007; Koringa et al 2008).
Genetic diversity of Albanian local goat breeds was estimated previously using microsatellite markers (Hoda et al 2011). Muzhake is an important local goat breed, located at south and south-east of Albania. The number of breeding females is 34000 and breeding males 1500. Body weight is 65 kg and 50 kg for males and females respectively. Assessment of genetic variability and genetic characterization of a breed is very important step for undertaking conservation measurements. The aim of the present study was the genetic characterization of Muzhake goat breed, using 30 microsatellite markers.
Blood samples were collected at random from 30 unrelated animals of Muzhake goats. DNA was isolated according to the standard phenol/chloroform protocol (Sambrook et al 1989). A panel of 30 microsatellite markers as suggested by FAOs MoDAD programme, was used for genetic characterization of Muzhake goat, according to the methodology explained in detail by Canon et al 2006).
Microsatellite allele frequencies, observed and expected number of alleles, effective number of alleles and Shanon’s Information Index were estimated using Genalex 6 program (Peakall and Smouse 2006). Observed heterozygosity (Ho), expected heterozygosity (He) were estimated for 30 microsatellite markers using the same software. Polymorphic information content (PIC) was estimated for all markers using the Cervus software (Marshall 1998). Bottleneck events were tested by three methods implemented in the program BOTTLENECK (Piry et al 1999). Factorial Correspondence Analysis (FCA) was carried out using GENETIX v4.02 (Belkhir et al 2001).
Ewens-Watterson test was performed to test the neutrality for microsatellite markers, using the algorithm by Manly (2007) using 1000 simulated samples and implemented in Popgene software package (Yeh et al 1999).
Number of alleles (Na), number of effective alleles (Ne), expected and unbiased average heterozygosity (He), FIS and PIC values at each locus are displayed in Table 1. Number of alleles varied from 4 (ETH10, ILSTS00, MAF209) to 18 (BM6444). There were identified 240 alleles in the whole population for 30 microsatellite markers. Number of effective alleles varied from 1.47 (MAF209) to 11.5 (BM6444). The PIC values ranged from 0.30 (MAF209) to 0.91 (BM6444) with a mean value of 0.71. Observed heterozygosity ranged from 0.33 (MAF209, DRBP1) to 0.93 (OarFCB48), with a mean value of 0.69. The value of Shannon information index (I) ranged from 0.77 to 2.49. The values of expected heterozygosity ranged from 0.32 (AF209) to 0.91 (BM6444) with a mean value of 0.75. FIS values for all markers ranged from -0.22 (InraBern185) to 0.589 (DRBP1) with an overall mean estimate of 0.07.
Table 1: Measures of genetic variation in Muzhake goat |
|||||||||
Locus |
N |
Na |
Ne |
I |
Ho |
He |
UHe |
FIS |
PIC |
BM6444 |
30 |
18.0 |
11.54 |
2.60 |
0.80 |
0.91 |
0.93 |
0.12 |
0.91 |
CSRD247 |
30 |
7.0 |
5.09 |
1.78 |
0.80 |
0.80 |
0.82 |
0.00 |
0.78 |
DRBP1 |
30 |
8.0 |
5.26 |
1.85 |
0.33 |
0.81 |
0.82 |
0.59 |
0.79 |
ETH10 |
30 |
4.0 |
2.94 |
1.17 |
0.80 |
0.66 |
0.67 |
-0.21 |
0.60 |
ILSTS005 |
27 |
4.0 |
2.63 |
1.15 |
0.67 |
0.62 |
0.63 |
-0.08 |
0.57 |
ILSTS011 |
30 |
7.0 |
3.67 |
1.53 |
0.60 |
0.73 |
0.74 |
0.18 |
0.69 |
ILSTS029 |
29 |
5.0 |
2.76 |
1.22 |
0.55 |
0.64 |
0.65 |
0.14 |
0.58 |
ILSTS087 |
30 |
9.0 |
4.55 |
1.76 |
0.50 |
0.78 |
0.79 |
0.36 |
0.75 |
INRA023 |
30 |
10.0 |
5.98 |
2.02 |
0.80 |
0.83 |
0.85 |
0.04 |
0.82 |
INRA063 |
30 |
5.0 |
3.30 |
1.36 |
0.77 |
0.70 |
0.71 |
-0.10 |
0.65 |
InraBern172 |
30 |
8.0 |
5.11 |
1.78 |
0.77 |
0.80 |
0.82 |
0.05 |
0.78 |
INRABERN185 |
30 |
7.0 |
2.51 |
1.31 |
0.73 |
0.60 |
0.61 |
-0.22 |
0.57 |
MAF209 |
30 |
4.0 |
1.47 |
0.64 |
0.33 |
0.32 |
0.32 |
-0.05 |
0.30 |
MAF65 |
30 |
10.0 |
7.06 |
2.10 |
0.83 |
0.86 |
0.87 |
0.03 |
0.84 |
MAF70 |
30 |
7.0 |
3.34 |
1.44 |
0.60 |
0.70 |
0.71 |
0.14 |
0.65 |
McM527 |
30 |
8.0 |
5.92 |
1.88 |
0.90 |
0.83 |
0.85 |
-0.08 |
0.81 |
OarAE54 |
30 |
9.0 |
4.51 |
1.69 |
0.70 |
0.78 |
0.79 |
0.10 |
0.75 |
OarFCB20 |
30 |
5.0 |
3.46 |
1.38 |
0.73 |
0.71 |
0.72 |
-0.03 |
0.67 |
OarFCB48 |
30 |
8.0 |
6.12 |
1.90 |
0.93 |
0.84 |
0.85 |
-0.12 |
0.82 |
P19 |
30 |
9.0 |
6.57 |
2.00 |
0.60 |
0.85 |
0.86 |
0.29 |
0.83 |
SPS113 |
30 |
9.0 |
5.14 |
1.84 |
0.73 |
0.81 |
0.82 |
0.09 |
0.78 |
SRCRSP09 |
30 |
9.0 |
4.12 |
1.76 |
0.83 |
0.76 |
0.77 |
-0.10 |
0.73 |
SRCRSP15 |
30 |
6.0 |
3.08 |
1.29 |
0.50 |
0.68 |
0.69 |
0.26 |
0.62 |
SRCRSP23 |
30 |
15.0 |
8.91 |
2.42 |
0.87 |
0.89 |
0.90 |
0.02 |
0.88 |
SRCRSP3 |
30 |
5.0 |
2.66 |
1.24 |
0.40 |
0.62 |
0.63 |
0.36 |
0.59 |
SRCRSP5 |
29 |
9.0 |
4.13 |
1.77 |
0.76 |
0.76 |
0.77 |
0.00 |
0.74 |
SRCRSP7 |
30 |
5.0 |
2.99 |
1.29 |
0.57 |
0.67 |
0.68 |
0.15 |
0.62 |
SRCRSP8 |
30 |
11.0 |
5.70 |
2.01 |
0.77 |
0.82 |
0.84 |
0.07 |
0.80 |
TCRVB6 |
28 |
11.0 |
6.22 |
2.05 |
0.82 |
0.84 |
0.86 |
0.02 |
0.82 |
TGLA53 |
30 |
8.0 |
3.98 |
1.64 |
0.77 |
0.75 |
0.76 |
-0.02 |
0.71 |
Mean |
29.767 |
8.0 |
4.69 |
1.66 |
0.69 |
0.75 |
0.76 |
0.07 |
0.71 |
SE |
0.124 |
0.569 |
0.38 |
0.08 |
0.03 |
0.02 |
0.02 |
0.03 |
|
Number of alleles (Na), Effective number of alleles (Ne), Information Index (I), Observed Heterozygosity (Ho), Expected (He) and Unbiased Expected Heterozygosity (UHe), and Fixation Index (F). |
Table 2: The Ewens-Watterson
test for Neutrality at 30 microsatellite loci in Muzhake goat breed
|
||||||
Locus |
Probability of χ2 |
Probability of G2 |
Obs. F |
SE* |
L95* |
U95* |
BM6444 |
0.09 |
1.00 |
0.09 |
0.00 |
0.08 |
0.20 |
CSRD247 |
0.20 |
0.21 |
0.20 |
0.01 |
0.20 |
0.63 |
DRBP1 |
0.00 |
0.00 |
0.19 |
0.01 |
0.17 |
0.55 |
ETH10 |
0.74 |
0.65 |
0.34 |
0.03 |
0.29 |
0.87 |
ILSTS005 |
0.42 |
0.24 |
0.38 |
0.03 |
0.29 |
0.86 |
ILSTS011 |
0.51 |
0.48 |
0.27 |
0.01 |
0.20 |
0.62 |
ILSTS029 |
0.00 |
0.03 |
0.36 |
0.02 |
0.26 |
0.78 |
ILSTS087 |
0.02 |
0.39 |
0.22 |
0.01 |
0.15 |
0.49 |
INRA023 |
0.71 |
0.88 |
0.17 |
0.01 |
0.14 |
0.44 |
INRA063 |
0.49 |
0.32 |
0.30 |
0.02 |
0.26 |
0.79 |
InraBern1 |
0.99 |
0.99 |
0.20 |
0.01 |
0.17 |
0.55 |
INRABERN1 |
0.96 |
0.94 |
0.40 |
0.01 |
0.19 |
0.62 |
MAF209 |
0.96 |
0.94 |
0.68 |
0.02 |
0.30 |
0.84 |
MAF65 |
0.49 |
0.72 |
0.14 |
0.01 |
0.14 |
0.42 |
MAF70 |
0.02 |
0.47 |
0.30 |
0.01 |
0.20 |
0.60 |
McM527 |
0.93 |
0.77 |
0.17 |
0.01 |
0.17 |
0.55 |
OarAE54 |
0.00 |
0.92 |
0.22 |
0.01 |
0.16 |
0.49 |
OarFCB20 |
0.18 |
0.08 |
0.29 |
0.02 |
0.26 |
0.78 |
OarFCB48 |
0.97 |
0.91 |
0.16 |
0.01 |
0.17 |
0.55 |
P19 |
0.00 |
0.21 |
0.15 |
0.01 |
0.16 |
0.53 |
SPS113 |
0.39 |
0.66 |
0.19 |
0.01 |
0.16 |
0.48 |
SRCRSP09 |
0.67 |
0.75 |
0.24 |
0.01 |
0.16 |
0.50 |
SRCRSP15 |
0.57 |
0.53 |
0.32 |
0.02 |
0.23 |
0.73 |
SRCRSP23 |
0.05 |
0.99 |
0.11 |
0.00 |
0.10 |
0.25 |
SRCRSP3 |
0.00 |
0.02 |
0.38 |
0.02 |
0.26 |
0.79 |
SRCRSP5 |
0.97 |
0.99 |
0.24 |
0.01 |
0.16 |
0.48 |
SRCRSP7 |
0.00 |
0.08 |
0.34 |
0.02 |
0.26 |
0.81 |
SRCRSP8 |
0.02 |
0.61 |
0.18 |
0.00 |
0.13 |
0.40 |
TCRVB6 |
0.85 |
0.99 |
0.16 |
0.00 |
0.13 |
0.38 |
TGLA53 |
0.01 |
0.73 |
0.25 |
0.01 |
0.18 |
0.56 |
The Chi-square and likelihood ratio tests were performed to examine Hardy Weinberg Equilibrium (HWE) at each locus (Table 2). At some loci were revealed significant deviation from HWE (P < 0.05).
The neutrality test of each marker tested by Ewens-Watterson test for neutrality suggested that most of the microsatellite loci (Table 2) were neutral and unlinked to any selected trait, because observed F values lie outside of the upper and lower limits of 95% confidence region of expected F value. F value (sum of square of allelic frequency) lay outside the lower and upper limit of 95% confidence region of expected F value at only BM6444 locus.
Table 3: Bottleneck analysis for Muzhake goat breed using three different tests under infinite allele, two phase model and stepwise mutation. |
|||
Models |
Sign test |
Standartized |
Wilcoxon test |
IAM |
Hee = 18.16 |
T2 = 4.140 |
P (one tail for H deficiency) = 1.000 |
|
Hd = 2 |
P = 0.00002 |
P (one tail for H excess) = 0. 000 |
|
He = 28 |
|
P (two tails for H excess and deficiency) = 0.000 |
|
P = 0.0006 |
|
|
TPM |
Hee = 18.06 |
T2 = 1.330 |
P (one tail for H deficiency) = 0.98689 |
|
Hd = 11 |
P = 0.09183 |
P (one tail for H excess) = 0. 01387000 |
|
He = 19 |
|
P (two tails for H excess and deficiency) = 0.02774 |
|
P = 0.44016 |
|
|
SMM |
Hee = 17.65 |
T2 = -3.555 |
P (one tail for H deficiency) = 0.00202 |
|
Hd = 21 |
P = 0.00002 |
P (one tail for H excess) = 0. 99813 |
|
He = 9 |
|
P (two tails for H excess and deficiency) = 0.00403 |
|
P = 0.00134 |
|
|
|
|
|
|
If a population has
experienced a recent bottleneck, rare alleles tend to be lost and the average
number of alleles per locus and gene diversity are reduced. Heterozygosity,
however, is reduced slowly, because rare alleles contribute little to
heterozygosity. Therefore, in a recently bottlenecked population, the observed
gene diversity is higher than the expected equilibrium gene diversity. The
results of three different tests under three microsatellite evolution models for
recent bottleneck are displayed in Table 3. Results of sign test show presence
of bottleneck under TPM, but show the absence of bottleneck under IAM and SMM
model. The sign test revealed significant differences between the number of loci
observed and expected with heterozygosity excess under IAM model (Table 3). 28
loci out of 30 had heterozygosity excess, under IAM and two of loci showed
significant (P <0.01) heterozygosity deficiency. The standardized
difference revealed probability values less than 0.05 for IAM and SMM models.
Therefore the hypothesis of mutation drift equilibrium was not rejected only
under TPM model (T2 = 1.330, P = 0.09183). Wilcoxon test revealed that the
population had undergone recent bottleneck assuming the IAM model. Finally,
mode-shift indicator test was used as a second method to detect potential recent
bottleneck. The microsatellite alleles were organized into 10 frequency classes.
Alleles with low frequencies (0.01 − 0.1) are the most numerous. The
distribution followed the normal L-shaped form (Figure 1) suggesting that the
breed did not encounter a recent genetic bottleneck.
Factorial correspondence analysis (FCA) suggests that first axis accounted for 5.99%; second 5.76% and third 5.54% of the total variance (Figure 2). The analysis shows a close genetic relationship between individuals.
Muzhake goat has a high genetic variation considering gene diversity and average number of alleles per locus. Gene diversity of Muzhake goat was lower than values found for Raeini goats (0.805; Sadeghi et al 2010) or Xinong Sanen dairy goat (0.74 – 0.90; Zhu et al 2011). Number of alleles for each locus was higher than 4.
A gene locus is highly informative if PIC value is higher than 0.5 (Botstein et al 1980). Therefore most of the loci are highly informative. Average PIC value for Muzhake breed was 0.71 and was lower than value found for Chinese goats (0.75 – 0.8, Yang et al 1999), Iranian goat (0.78; Sadeghi et al 2010), or in Lori goat (0.73, (Mahmoudi, 2010), Xinong Sanen dairy goat (Zhu et al 2011), but higher than values observed in Mehsani goats (0.65, (Aggarwal et al 2007), in Zalawadi, Gohilwadi and Surti populations, (0.56, 0.64 and 0.60 respectively; Fatima et al 2008). Average gene diversity was 0.745. This value was lower than provided for Iranian goats (0.81; Sadeghi et al 2010).
Average FIS value is 0.07, indicating a reduction of heterozygotes at 7%. The most probable reason for this heterozygosity deficiency might be Wahlund effect, since sampling is carried out in numerous small farms. Since there is lack of herd book for sampled individuals all information considering nonrelatedness is provided entirely by the farmers. Therefore sampling of related individuals is not excluded entirely. This might have contributed in the deficit of heterozygotes.
The FIS values obtained here are much lower than reported previously for Marwari (FIS = 0.26) (Kumar et al 2005) and Mehsani (FIS = 0.16) goat breeds (Aggarwal et al 2007), but are comparative with the values reported for Zalawadi, Gohilwadi and in Surti (−0.058, 0.057 and 0.070, respectively) by (Fatima et al 2008).
All microsatellite markers used in the present study were shown to be highly polymorphic and useful for the molecular characterization of Muzhake goat breed. The information provided through the present study would be useful for designing effective conservation strategies.
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Received 22 May 2012; Accepted 26 June 2012; Published 1 July 2012