Population genetic structure analysis and effect of inbreeding on body weights at different ages in Iranian Mehraban sheep
© Yavarifard et al.; licensee BioMed Central Ltd. 2014
Received: 21 August 2014
Accepted: 17 November 2014
Published: 10 December 2014
The objective of this study was to describe the population structure and inbreeding, and to quantify their effects on weights at different ages of Mehraban sheep in Iran. The analysis was based on the pedigree information of 26990 animals and 10278 body weight records from birth to yearling age. Data and pedigree information were collected during 1994 to 2011 by the breeding station of Mehraban sheep. The population structure was analyzed using the CFC program. Inbreeding of all animals was calculated by INBUPGF90 program. All animals were grouped into three classes according to their inbreeding coefficients: the first class included non-inbred animals (F=0); and the second and third classes included inbred animals (0<F<0.05 and F≥0.05, respectively). The average inbreeding in Mehraban sheep was 1.69%. Founder equivalent (fe) values were estimated to be 4244, 3116 and 2965 during 1994-1999, 2000-2005 and 2006-2011, respectively. The effective population sizes (Ne) were 363, 5080 and 5740 during 1994-1999, 2000-2005 and 2006-2011, respectively. Generation interval was 2.15 years for this breed of sheep. Regression coefficients of birth weight, 3-month weight, 6-month weight and yearling weight on lamb inbreeding were estimated to be -6.34±0.69, -14.68±5.33, 48.00±9.43 and 98.65±15.65, respectively. Both positive and negative inbreeding effects were found in the current study. The utilization of a program for designed mating system, in the present flock, could be a suitable approach to keep the level of inbreeding under control.
KeywordsFat-tailed sheep Growth traits Inbreeding depression Mating program Pedigree analysis
During the past 50 years, the indigenous genetic reserves are in a critical stage all over the world due to large changes in production systems, change of market demand and intercourse of domestic animals with other breeds. Along with increase in genetic progress, maintaining genetic diversity in the population is very important to adapt with the economic and environmental changes in the future and ensure long-term response to selection for traits that are very important . Effective population size (Ne) is a criterion for determining similarity between alleles of the loci so that there was a common ancestor and determines the level of inbreeding and reduced rate of genetic variation due to gene random drift . Intensive use of a few breeding animals, where the selection intensity is high, could result in greater rates of inbreeding in the population. Therefore, a small number of seedstock, with a strong family relationship, is responsible for the maintenance of almost the whole genetic pool in the population. This is an aspect of great influence in the genealogical analysis of a population structure, because of its effect on the probability of genes lost between generations and the consequent reduction in genetic variability .
Discrepancies in ancestral origins and migration events are important causative factors explaining genetic differences between current populations -. Hence, the optimal management of population is essential in order to prevent from decrease in diversity. Estimation of parameters such as effective population size, inbreeding and coancestry are depended significantly on the genealogy information. Measurement of the effect of inbreeding on economic traits is important in order to estimate the magnitude of change associated with increases in inbreeding. It is apparent that different breeds and populations, as well as different traits vary in their response to inbreeding. Some populations may show a very pronounced effect of increased inbreeding for a trait, whereas others may not display much of an effect ,. The rate of inbreeding needs to be limited to maintain diversity at an acceptable level, so that genetic variation will ensure that future animals can respond to changes in the environment and to selection. Without genetic variation, animals cannot adapt to these changes . Commonly, negative inbreeding effects, or inbreeding depression, are thought to most frequently occur because of an increase in frequencies of recessive alleles that adversely affect the traits of interest . The increased frequency of recessive alleles leads to a larger number of individuals that are homozygous for the recessive alleles, whereas in non-inbred populations, the recessive allele would more frequently be masked by an advantageous dominant allele .
One of the most important breeds of Iranian sheep is Mehraban sheep which is reared in Hamedan province. This breed is adapted to harsh climate and rocky environments in the western regions of Iran. The Mehraban is a fat-tailed carpet wool sheep with light brown, cream or grey color, dark face and neck and primarily used for meat production . The objective of this study was to describe the population structure and inbreeding, and to quantify their effects on weights at different ages of Mehraban sheep in Iran from 1994 to 2011.
Experimental design and animals
Summary of pedigree information for Mehraban sheep
Individuals in total
Individuals with known sire
Individuals with known dam
Individuals with known sire and dam
Individuals with progeny
Characteristics of data set for Mehraban sheep
Number of records
Standard deviation (kg)
Coefficient of variation (%)
Statistical and genetic analyses
The CFC program  was used to calculate pedigree statistics and genetic structure analysis of the population. To characterize the population structure, variation changes in inbreeding (ΔF), average coancestry (AC), effective population size (Ne), generation interval (L) and parameters derived from the method of analysis of gene origin probability were calculated. The parameters related to the method of analysis of gene origin probability were: founder equivalent (fe), founder genome equivalent (fg), effective number of non-founder (Nenf), average number of discrete generation equivalents (Ge), maximum number of discrete generation equivalents (MaxGe) and minimum number of discrete generation equivalents (MinGe). Animals were grouped based on their birth years into three classes (1994–1999, 2000–2005, and 2006–2011). This classification was necessary for the CFC program to compute the genetic structure parameters of the population.
Where p i is the expected proportional genetic contribution of founder i, calculated by the average relationship of the founder to each animal in the current population, and f is the total number of founders. The parameter fe indicates the number of equally contributing founders that would produce the same level of genetic diversity as that observed in the current population .
Where r i is the expected proportion of founder i’s alleles that remain in the current population and can take on a value of 0.5 if one allele is present or 1.0 if two alleles are present, p i is the expected proportional genetic contribution of founder i, and f is the number of contributing founders .
In this equation, n j is the number of known ancestors for animal j and g ij is the number of generations between animal i (ancestor) and animal j. The depth of the pedigree in each reference population was examined by computing Ge which is the expected number of generations from the base population, to the reference population if generation proceeded discretely .
Where N enf is the effective number of non-founders. Also, f g and f e are founder genome equivalents and founder equivalents, respectively.
Where F i is the individual coefficient of inbreeding and t is the equivalent complete generations .
This way of computing effective population number is not dependent on the whole reference population mating policy, but on the matings carried out throughout the pedigree of each individual .
Generation interval (L) was calculated as the average age of the parents at the birth of their lambs. All the animals were grouped into three classes according to the inbreeding coefficients obtained by their pedigrees: the first class included non-inbred animals (F= 0); and the second and third classes included inbred animals (0< F< 0.05 and F ≥ 0.05, respectively). Moreover, the birth type (single, twin) and lamb sex (male, female) was considered for each of the lambs. Due to the low frequency of triple births, triple lambs were not included in this study.
Trend of inbreeding over time was estimated using the linear regression of individual inbreeding on the birth year using the Reg procedure of SAS . The GLM procedure of SAS was used for determining the fixed factors which had significant effect on the traits investigated. After data verification, defective and doubtful records were deleted (e.g., lambs without weight records or with incomplete records of parentage or with registration numbers lower than the numbers of their parents were left out). The least-squares means were estimated for each trait using the Average Information Restricted Maximum Likelihood (AIREML) algorithm of the Wombat program  by fitting six single trait animal models which ignore or include additive direct and maternal genetic and permanent environmental effects. The statistical models included herd-year-season of lambing, lamb sex in 2 classes (male and female), age of dam at lambing in 6 classes (2–7 years old), birth type in 2 classes (single, twin), inbreeding in 3 groups (F= 0, 0< F< 0.05, F ≥ 0.05) and interaction between them. The most appropriate model for BW, 9 MW and YW included direct additive genetic and maternal permanent environmental effects and for WW included direct additive genetic effects as well as maternal additive genetic effects and for 6 MW included maternal and direct additive genetic effects as well as covariance between direct additive and maternal additive genetic effects.
Analysis of pedigree
Distribution of records for body weight traits in different inbreeding classes of animals born between 1994 and 2011
Mean ± SE
Mean ± SE
Mean ± SE
Mean ± SE
Mean ± SE
3.88 ± 0.01a
22.46 ± 0.06a
34.62 ± 0.06b
39.06 ± 0.93c
50.20 ± 0.01a
3.65 ± 0.01b
22.12 ± 0.06ab
36.23 ± 0.06ab
45.51 ± 0.11b
52.68 ± 0.15a
F ≥ 0.05
3.32 ± 0.23c
21.01 ± 0.06b
37.48 ± 0.06a
47.66 ± 0.88a
55.35 ± 1.32a
The results of the pedigree analysis for the reference population of Mehraban sheep in year groups
Number of animals
Founder equivalent (fe)
Founder genome equivalent (fg)
Effective number of non-founders (Nenf)
Effective population size (Ne)
Average number of discrete generation equivalents (Ge)
Maximum number of discrete generation equivalents (MaxGe)
Minimum number of discrete generation equivalents (MinGe)
Generation interval (L), years
Average coancestry (AC)
Changes in inbreeding (ΔF)
Distribution of records for body weight traits in different inbreeding classes of animals grouped by the type of birth and born between 1994 and 2011
Mean ± SE
Mean ± SE
Mean ± SE
Mean ± SE
Mean ± SE
3.96 ± 0.47a
22.44 ± 4.92a
34.66 ± 8.13a
39.07 ± 8.29b
50.20 ± 0.01a
3.87 ± 0.68a
21.98 ± 4.59a
36.73 ± 7.47a
45.78 ± 6.66a
52.35 ± 8.73a
F ≥ 0.05
3.85 ± 0.65a
22.37 ± 3.36a
36.22 ± 5.51a
46.57 ± 3.36a
52.60 ± 3.99a
3.33 ± 0.46a
22.61 ± 4.19a
34.41 ± 5.83b
2.96 ± 0.77b
22.55 ± 3.92a
36.71 ± 6.24ab
44.76 ± 5.77b
53.65 ± 5.28b
F ≥ 0.05
2.59 ± 0.83c
18.98 ± 1.69b
39.00 ± 2.53a
48.98 ± 0.67a
57.56 ± 1.28a
Distribution of records for body weight traits in different inbreeding classes of animals grouped by the sex of lamb and born between 1994 and 2011
Mean ± SE
Mean ± SE
Mean ± SE
Mean ± SE
Mean ± SE
3.96 ± 0.51a
22.48 ± 4.69a
35.30 ± 8.37a
40.64 ± 9.72b
50.20 ± 0.01a
3.77 ± 0.82a
22.28 ± 4.16a
36.81 ± 6.12a
46.05 ± 6.43a
53.16 ± 6.48a
F ≥ 0.05
3.43 ± 1.05b
22.77 ± 2.30a
36.90 ± 5.67a
46.80 ± 3.14a
53.77 ± 3.66a
3.81 ± 0.46a
22.45 ± 4.63a
34.09 ± 7.26b
36.80 ± 0.83c
3.54 ± 0.76a
21.95 ± 4.26a
35.66 ± 5.69b
44.97 ± 6.32b
52.17 ± 6.99b
F ≥ 0.05
3.13 ± 0.76b
18.38 ± 2.68b
38.50 ± 1.00a
49.98 ± 0.82a
58.53 ± 0.47a
Female lambs showed significant differences in their body weights based on their inbreeding coefficient. The BW and WW of female lambs within third class of inbreeding were significantly (P< 0.05) lower than those of lambs in the first and second classes. The 6 MW of female lambs showed a significant difference (P< 0.05) between third class of inbreeding and first and second classes (38.50 ± 1.00 kg vs. 34.09 ± 7.26 kg and 35.66 ± 5.69 kg; respectively). The 9 MW of female lambs showed a significant difference between all three classes of inbreeding (P< 0.05). On the other hand, the YW of female lambs showed significant difference between second and third classes of inbreeding (52.17 ± 6.99 kg vs. 58.53 ± 0.47 kg; P< 0.05).
Regression coefficients of body weights
Regression coefficients (±SE) of body weight traits (in grams) on inbreeding of lambs for a change of 1% in inbreeding
−1.84 ± 0.67**
−11.45 ± 6.45**
54.50 ± 12.35**
−22.00 ± 19.58
232.65 ± 27.96**
−7.22 ± 1.33**
−28.63 ± 9.16**
30.26 ± 13.68*
17.81 ± 16.52
19.59 ± 15.30
−5.74 ± 0.99**
−9.23 ± 7.24
32.18 ± 12.87*
−10.72 ± 16.11
68.47 ± 17.83**
−7.23 ± 0.94**
−21.66 ± 7.85**
65.23 ± 13.81**
7.23 ± 22.62
171.28 ± 29.97**
−6.34 ± 0.69**
−14.68 ± 5.33**
48.00 ± 9.43**
−4.09 ± 13.12
98.65 ± 15.65**
Reported estimates of lamb inbreeding effects on growth performance traits showed the same trend by other authors. Similar to the current results, some reported a lower regression coefficient for BW due to increase in inbreeding, e.g. Ghavi Hossein-Zadeh  observed a reduction of 0.009 kg for 1% increase of inbreeding in Iranian Moghani sheep; Selvaggi et al.  found a mean value of 0.019 kg in Leccese sheep; MacKinnon et al. , Analla et al. , Van Wyk et al. , Ercanbrack and Knight , Khan et al.  and Mirza et al.  reported regression coefficients of −0.027, −0.013, −0.008, −0.010, −0.008 and −0.007 kg, respectively. Reasons of variation in inbreeding effects could be due to differences between the breeds in allele separation, amount of genetic variation in the base population, management, and diversity of the founders of the flocks examined .
Similar to the current results, Van Wyk et al.  and Selvaggi et al.  reported significant reduction in WW of lambs due to 1% increase in inbreeding in different breeds of sheep and inconsistent with the current result, Ghavi Hossein-Zadeh  and Lamberson and Thomas  reported no significant reduction in WW due to inbreeding. Sex of lambs was a significant effect in the current analysis of inbreeding; but Barczak et al.  and Ghavi Hossein-Zadeh  observed non-significant differences between males and females. Barczak et al.  reported positive inbreeding effects on fourth week weight in a multi-breed sheep population and Ghavi Hossein-Zadeh  reported positive inbreeding effects on 6 MW and YW in Moghani sheep population. There are several methodological and biological factors which determine the estimated inbreeding impact on the performance traits. It is well known that both negative and positive effects exist. Therefore, in a population, bad and good inbreeding effects are mixed .
The results of this study indicated a significant increase in 6WW and YW of lambs due to 1% increase in inbreeding, but Ghavi Hossein-Zadeh  reported a significant reduction in YW of male lambs (0.357 kg). The possible explanation for the strong inbreeding depression observed for 6 MW and YW in this study was the higher heritability of this trait compared to other weight traits in Mehraban sheep .
The inbreeding level estimates are strongly determined by the two main factors: depth and completeness of pedigree and selection intensity. Selection intensity is often increased by the reproductive technologies being focused on a few superior animals (especially sires) and the application of advanced methods of genetic evaluation. Embryo transfer and artificial insemination technology currently allow the intensive use of the same sires, leading to increase in the relationship coefficient between animals, which help to the increase in inbreeding in this population. A high inbreeding level is observed for populations rebuilt from small number of founders , but on the other hand in this case the accuracy is strongly determined by the incompleteness of pedigrees . Animal breeding emphasis on the genetic breeding values of the traits, used as criteria of sires and dams selection, can also raise the inbreeding coefficient, since relationship between animals tend to present similar genetic values, having as a consequence the selection of the most frequent relatives . Average inbreeding estimates reported in this study were lower than reported estimates of Ghavi Hossein-Zadeh  in Moghani sheep (2.93%), Dorostkar et al.  in Moghani sheep (2.069%), Pedrosa et al.  in Santa Inês sheep in Brazil (2.33%). Van Wyk et al.  and Selvaggi et al.  reported high rates of inbreeding in Dormer sheep (16%) and Leccese sheep (8.1%), respectively. On the other hand, Eteqadi et al.  reported lower inbreeding (0.15%) in Guilan sheep. The lower inbreeding coefficient in the current sheep population compared with other studies could be due to the lack of designed mating programs and absence of selection, especially before 1999. The rapid increase in the rate of inbreeding in 1999–2000 could be resulted from the reduction in the number of sires. Similar to the current results, Eteqadi et al. , Ghavi Hossein-Zadeh , Dorostkar et al. , Pedrosa et al.  and Barczak et al.  reported positive trend for inbreeding over the years.
The generation interval was 2.15 years in the current population, and MacKinnon  reported the generation intervals of 2.65 and 4.28 years for different crossbred sheep. Van Wyk et al. , Pedrosa et al. , Ghavi Hossein-Zadeh  and Eteqadi et al.  reported generation intervals of 3.27, 3.70, 3.34 and 2.385 years for Elsenburg Dormer sheep, Santa Inês sheep, Moghani sheep and Guilan sheep, respectively. Lower estimates of generation interval would cause larger responses .
The fe and fg values are important parameters which can be used for management and control of small populations. Also, these parameters can increase the accuracy of changes in some parameters such as effective population size and inbreeding rate . In a population, abundance of some forms of founder animals may be more than the others, in creating the next generation. This makes these animals have greater contributions than others in the population gene pool. The fe parameter was calculated for correcting this item. The fe value was 2965 in 2011 which was proportional to the increased number of animals (9905) in this year. This indicated the unequal contribution of founder animals in creating offspring. The most important limitation of fe is converging genetic contribution of founder animals after several generations which will lead to remain fe in a constant value.
The fg parameter is an indicator for showing the unequal participation of founder animals and accidental loss of genes during transmission from parents to offspring. For this reason, the value of fg is always lower than the fe value and decreases rapidly over the time. As expected, the value of fg was reduced over the studied years.
The Ge parameter is a factor to indicate the depth and quality of the pedigree. The Ge value was increased over the studied years. Therefore, this indicated the increase in pedigree information and its evolution over the years. The AC values were increased over the years. Animals’ AC predicts average inbreeding of future generation in a population. For this reason, this parameter can be used to calculate the effective population size in the future. High relative population size, meaning low variation in a population due to the reduction of variance between individuals, will lead to a decrease in the response to selection.
The effective size of population is described by the number of animals that mate in an ideal population and produce the same inbreeding increment of the population under study . Evolutionary biologists have suggested that an effective population size in the range of 500–5000 is mandatory to secure evolutionary potential of natural populations . The reduction in effective population size, as a direct outcome of reduction in genetic diversity, associates with various unfavorable phenomena such as inbreeding depression in fitness-related traits and an increased change in response to selection . One problem with the Ne value is that the value indicates the number of breeding animals needed to produce the average ΔF and does not quantify the cumulative decrease in allelic diversity or changes in breeding structure from year to year (10). Hence, the value obtained for Ne is not comparable to measures of fe and fg . Most breeding programs may try to minimize accumulation of inbreeding and quantify the increase by calculating the change in inbreeding per generation (∆F)  in order to decrease the possible negative effect of inbreeding on productive traits.
In conclusion, average inbreeding was 1.69% in Iranian Mehraban sheep and an increasing trend for inbreeding was observed over the years. Both positive and negative inbreeding effects were found in the current study. Different methods are proposed to maximize response to selection in an acceptable level of inbreeding such as balanced use of animals as parents of the next generation, limiting the size of families and creating sub-lines. Implementation of these methods and use of designed mating system can help to obtain the optimal response to the selection by least accumulation of inbreeding in Mehraban sheep flock in the future. Overall, avoidance from inbreeding is a main objective on the management of vulnerable species and breeds and this is especially true with respect to these new findings in Mehraban sheep.
- Barker JSF: Conservation and management of genetic diversity: a domestic animal perspective. Can J Forest Res. 2001, 31: 588-595. 10.1139/x00-180.View ArticleGoogle Scholar
- Norberg E, Sørensen AC: Inbreeding trend and inbreeding depression in the Danish populations of Texel, Shropshire, and Oxford down. J Anim Sci. 2007, 85: 299-304. 10.2527/jas.2006-257.View ArticlePubMedGoogle Scholar
- Pedrosa VB, Santana ML, Oliveira J, Eler JP, Ferraz JBS: Population structure and inbreeding effects on growth traits of Santa Inês sheep in Brazil. Small Rumin Res. 2010, 93: 135-139. 10.1016/j.smallrumres.2010.05.012.View ArticleGoogle Scholar
- Alvarez I, Royo LJ, Fernandez I, Gutierrez JP, Gomez E, Goyache F: Genetic relationships and admixture among sheep breeds from Northern Spain assessed using microsatellites. J Anim Sci. 2004, 82: 2246-52.PubMedGoogle Scholar
- Canon J, Alexanderino P, Bessa I, Carleos C, Carretero Y, Dunner S, Ferran N, Garcia D, Jordana J, Laloë D, Pereira A, Sanchez A, Moazami-Goudarzi K: Genetic diversity measures of local European cattle breeds for conservation purposes. Genet Sel Evol. 2001, 33: 311-32. 10.1186/1297-9686-33-3-311.View ArticlePubMedPubMed CentralGoogle Scholar
- Rendo F, Iriondo M, Jugo BM, Mazon LI, Aguirre A, Vicario A, Estonba A: Tracking diversity and differentiation in six sheep breeds from the North Iberian Peninsula through DNA variation. Small Rumin Res. 2004, 52: 195-202. 10.1016/j.smallrumres.2003.07.004.View ArticleGoogle Scholar
- Barczak E, Wolc A, Wójtowski J, Ślósarz P, Szwaczkowski T: Inbreeding and inbreeding depression on body weight in sheep. J Anim Feed Sci. 2009, 18: 42-50.Google Scholar
- Negussie E, Abegaz S, Rege JOE: Genetic trend and effects of inbreeding on growth performance of tropical fat-tailed sheep. Proc 7th World Congress Genet Appl Livestock Prod Montpellier, France. 2002, 25: 1-4.Google Scholar
- Van Wyk JB, Fair MD, Cloete SWP: The effect of inbreeding on the production and reproduction traits in the elsenburg dormer sheep stud. Livest Sci. 2009, 120 (3): 218-224. 10.1016/j.livsci.2006.10.005.View ArticleGoogle Scholar
- MacKinnon KM: Analysis of Inbreeding in a Closed Population of Crossbred Sheep. 2003, MSc Thesis, Virginia Polytechnic Institute and State University Blacksburg, Virginia, USAGoogle Scholar
- Lamberson WR, Thomas DL: Effects of inbreeding in sheep: A review. Anim Breed Abstr. 1984, 52: 287-297.Google Scholar
- Zamani P, Mohammadi H: Comparison of different models for estimation of genetic parameters of early growth traits in the Mehraban sheep. J Anim Breed Genet. 2008, 125: 29-34. 10.1111/j.1439-0388.2007.00676.x.View ArticlePubMedGoogle Scholar
- Sargolzaei M, Iwaisaki HJ, Colleau J. CFC: A tool for monitoring genetic diversity. In Proceedings of 8th World Congress on Genetics Applied to Livestock Production. CD-ROM Communication 27-28. Belo Horizonte, Brazil. 13-18 August 2006.
- Lacy RC: Analysis of founder representation in pedigrees: founder equivalents and founder genome equivalents. Zoo Biol. 1989, 8: 111-123. 10.1002/zoo.1430080203.View ArticleGoogle Scholar
- Caballero A, Toro MA: Interrelations between effective population size and other pedigree tools for the management of conserved populations. Genet Res. 2000, 75: 331-343. 10.1017/S0016672399004449.View ArticlePubMedGoogle Scholar
- Woolliams JA, Mantysaari EA: Genetic contributions of Finnish Ayshire bulls over four generations. Anim Sci. 1995, 61: 177-187. 10.1017/S1357729800013709.View ArticleGoogle Scholar
- Aguilar I, Misztal I: Technical note: recursive algorithm for inbreeding coefficients assuming nonzero inbreeding of unknown parents. J Dairy Sci. 2008, 91: 1669-1672. 10.3168/jds.2007-0575.View ArticlePubMedGoogle Scholar
- Falconer DS, Mackay TFC: Introduction to Quantitative Genetics. 1996, Longman Group LTD, Harlow, Essex, UK, 4Google Scholar
- González-Recio O, López de Maturana E, Gutiérrez JPJ: Inbreeding depression on female fertility and calving ease in Spanish dairy cattle. J Dairy Sci. 2007, 90: 5744-5752. 10.3168/jds.2007-0203.View ArticlePubMedGoogle Scholar
- Maignel L, Boichard D, Verrier E: Genetic variability of French dairy breeds estimated from pedigree information. Interbull Bull. 1996, 14: 49-54.Google Scholar
- Gutiérrez JP, Cervantes I, Molina A, Valera M, Goyache F: Individual increase in inbreeding allows estimating realised effective sizes from pedigrees. Genet Sel Evol. 2008, 40: 359-378. 10.1186/1297-9686-40-4-359.View ArticlePubMedPubMed CentralGoogle Scholar
- Ghavi Hossein-Zadeh N: Inbreeding effects on body weight traits of Iranian Moghani sheep. Arch Tierz. 2012, 55 (2): 171-178.Google Scholar
- Selvaggi M, Dario C, Peretti V, Ciotola F, Carnicella D, Dario M: Inbreeding depression in Leccese sheep. Small Rumin Res. 2010, 89: 42-46. 10.1016/j.smallrumres.2009.12.005.View ArticleGoogle Scholar
- Analla M, Montilla JM, Serradilla JM: Study of the variability of the response to inbreeding for meat production in merino sheep. J Anim Breed Genet. 1999, 116 (6): 481-488. 10.1046/j.1439-0388.1999.00199.x.View ArticleGoogle Scholar
- Ercanbrack SK, Knight A: Effects of inbreeding on reproduction and wool production of Rambouillet, Targhee, and Columbia ewes. J Anim Sci. 1991, 69: 4734-4744.PubMedGoogle Scholar
- Khan MS, Ahmad MD, Ahmad Z, Jadoon JK: Effect of inbreeding on performance traits of Rambouillet sheep. J Anim Plant Sci. 1995, 5: 299-304.Google Scholar
- Gamasaee VA, Hafezian SH, Ahmadi A, Baneh H, Farhadi A, Mohamadi A: Estimation of genetic parameters for body weight at different ages in Mehraban sheep. Afri J Biotech. 2010, 9: 5218-5223.Google Scholar
- Dorostkar M, Faraji Arough H, Shodja J, Rafat SA, Rokouei M, Esfandyari H: Inbreeding and inbreeding depression in Iranian Moghani sheep breed. J Agric Sci Technol. 2012, 14: 549-556.Google Scholar
- Eteqadi B, Ghavi Hossein-Zadeh N, Shadparvar AA: Population structure and inbreeding effects on body weight traits of Guilan sheep in Iran. Small Rumin Res. 2014, 3: 45-51. 10.1016/j.smallrumres.2014.03.003.View ArticleGoogle Scholar
- Ghavi Hossein-Zadeh N: Bayesian estimates of genetic changes for body weight traits of Moghani sheep using Gibbs sampling. Trop Anim Health Prod. 2012, 44: 531-536. 10.1007/s11250-011-9930-1.View ArticlePubMedGoogle Scholar
- Martínez AT, Rencoret J, Marques G, Gutiérrez A, Ibarra D, Jiménez-Barbero J, del Río JC: Monolignol acylation and lignin structure in some nonwoody plants. J Phytochem. 2008, 69: 2831-2843. 10.1016/j.phytochem.2008.09.005.View ArticleGoogle Scholar
- Hill R: Math. Proc. Cambridoe Phil.Soc 1979, 85:179.
- Frankham R, Ballou JD, Briscoe DA: Introduction to Conservation Genetics. 2002, Cambridge University Press, Cambridge, EnglandView ArticleGoogle Scholar
- Boichard D, Maignel L, Verrier É: The value of using probabilities of gene origin to measure genetic variability in a population. Genet Sel Evol. 1997, 29: 5-23. 10.1186/1297-9686-29-1-5.View ArticlePubMed CentralGoogle Scholar
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