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Introduction
Markhoz goat is one of the most important native breeds in Iran, mainly raised in Kurdistan province, in west Iran (Rashidi et al., 2015). Markhoz goat is well known for mohair and meat production (Farshad et al., 2008), which is obviously different from other Iranian goat breeds, such as Mahabadi and Lori (Simaei-Soltani et al., 2016). Twinning rate in this breed is approximately 26%, and triplet births also occur (Rashidi et al., 2011). The Markhoz goat is an endangered breed and needs more attention for conservation. According to Bahmani et al. (2011), total and effective population sizes, and number of breeding Markhoz females and males in 2009 were 2,456, 266, 1,332 and 70 heads, respectively. That study revealed that the Markhoz goat is facing demographic and geographical risks, decreasing variation, and imminent danger of extinction. Breeding for productivity and profitability could stimulate farmers to keep a breed and, thus, could be considered as an efficient way to prevent breed extinction. A non-intensive breeding program has been planned for the whole Markhoz population, but irregular tandem selection programs including periodical phenotypic selections on different important traits -including mohair properties, body weight and reproduction efficiency- have been conducted at the Markhoz Goat Research Center for several generations during past years.
Litter size is one of the most important reproduction traits, especially in small ruminants with a high economic merit and a noticeable impact on profitability (Abdoli et al., 2016); hence a primary objective of breeding programs for sheep and goat should be maximizing genetic progress of litter size.
Estimation of genetic, phenotypic and environmental trends provides an evaluation perspective for previous selection strategies and facilitates designing a more suitable breeding program for the future. Therefore, the aim of this study was to estimate genetic parameters and trends for litter size as a prolificacy trait in Markhoz goats.
Materials and methods
Animal and data collection
Data and pedigree information were collected from 1992 to 2015 at the Markhoz Goat Research Center in Kurdistan province, west Iran (35°16’37.7”N 47°01’11.3”E). The goats were kept under semi- intensive management conditions with a controlled mating system. The mating season was from October to November and kidding was from February to March. The does were first exposed to the bucks at about 18 months of age and each buck was randomly mated with 10 to 15 does for two to three mating seasons. Newborn kids were weighed and ear-tagged at birth (Rashidi et al., 2011; Khani et al., 2017). Litter size (LS) was defined as the number of kids born alive per kidding and considered as a prolificacy trait of dams. The dataset included 3,064 LS records from 1,171 does. Minimum, maximum and average of LS records were 1, 3 and 1.3, respectively. The pedigree was traced back to all available ancestral information, consisting of 12 generations. The pedigree file included 5,137 animals, with 235 sires, 1,481 dams and 343 founders.
Statistical analysis
The fixed factors in the following model with significant effects on LS were determined based on a preliminary general linear model analysis using the GLM procedure of SAS® software, version 9.4 (SAS Institute Inc., Cary, NC, USA) (2013). Variance components and breeding values were estimated using a repeatability animal model as follow:
y = Xb + Zu + Wpe + e
Where:
y: is vector of observations.
b: is vector of fixed effects, determined from the general linear model analysis, including birth year (1992-2012), kidding age (2-7 years) and kidding year (1995-2015).
u, pe and e: are vectors of random direct additive genetic, permanent environmental and residual effects, respectively.
X, Z and W: are incidence matrices relating observations to the corresponding effects. This model was fitted with a logit link function using ASReml (Analysis of mixed models for S language environments, using Restricted Maximum Likelihood), version 2 (Gilmour et al., 2006). In this model, the LS was analyzed as a threshold trait (Mrode, 2014).
Environmental deviations (E) were estimated:
E= P - µ - BV
Where:
P: is the phenotypic value.
µ: is the overall mean. BV: are breeding values.
Genetic, phenotypic, and environmental trends were estimated by regression of breeding value, phenotypic value and environmental deviation averages on doe birth year, respectively, using REG procedure of SAS 9.4 (SAS Institute Inc., 2013).
Results
Fixed effects, variance components and genetic parameters
Birth year, kidding year and dam age at kidding had significant associations with LS (p<0.01) and, thus, were included as fixed effects in the animal mixed model used to estimate the variance components and breeding values. Estimates of variance components, heritability (h2), repeatability (r), and coefficient of permanent environmental effects (pe2), defined as the ratio of permanent environmental to total phenotypic variances, are presented in the Table 1. A very low and non-significant heritability (0.0016 ± 0.0068) was estimated for LS in the studied population. Low estimates were also obtained for r and pe2 (0.0536 ± 0.0111 and 0.0520 ± 0.0129, respectively).
Genetic, phenotypic and environmental trends
Estimates of genetic, environmental and phenotypic trends and their significance level (p values) are presented in Table 2. General trends of breeding values, phenotypes and environmental deviations are also illustrated in Figure 1. A non-significant, and actually zero, genetic trend (0.00004 ± 0.00002 heads/kidding/year) was estimated for LS in the study. Despite a relatively stable situation of the breeding values, negative and significant phenotypic and environmental trends (-0.01097 ± 0.00336 and -0.01100 ± 0.00337 heads/kidding/year, respectively) were estimated for LS in the studied period (Table 2). Phenotypic and environmental trends had similar patterns in different years (Figure 1).
Table 2: estimates of genetic, enviromental and phenotypic trends (heads/kidding/year) for litter size (LS) of Markhoz goats.
Discussion
Most reproduction traits, including litter size, have low heritability estimates. In other words, additive genetic effects have little effects on reproduction traits, while environmental and non-additive genetic effects considerably affect these traits. A low heritability indicates low possibility to achieve rapid genetic progress through phenotypic selection. Low -and close to zero- estimate of heritability for LS in the present study agrees with previous estimations in different goat breeds (Maghsoudi et al., 2009; Rashidi et al., 2011). In a previous study on genetic parameters of pre-weaning performance and reproduction traits in Markhoz goats, the LS was considered as a continuous trait and its h2 estimate was also low and close to 0.01 (Rashidi et al., 2011). This negligible difference with results of the present study is likely due to different considerations of the trait in the models (continuous vs. categorical), and inclusion of more data in the present study. Moreover, the LS phenotypic and environmental averages had considerable decreases in recent years (Figure 1), which could decrease the estimate of h2, as the result of an increase in phenotypic and environmental variances. Low heritability of LS in the present study supports previous concepts about the need of more studies on major genes, and finding genetic background of LS trait in different goat breeds (Simaei-Soltani et al., 2016). Low estimates were also obtained for repeatability and permanent environment coefficient; thus the LS repeatability is entirely due to permanent environmental effects. Low r and pe2 indicate considerable effect of temporary environment on LS, at least in the studied population.
Results of the current study show that genetic progress of LS in Markhoz goats was actually zero during the past two decades. Similar estimate of genetic trend has been reported in Saanen goats in Croatia (Kasap et al., 2013). This observation is due to low heritability of LS and thus, unfeasibility of genetic progress by common phenotypic selection methods. Negligible genetic trend along with significant and similar estimates of phenotypic and environmental trends (-0.01097 and -0.01100 heads/ year, respectively) emphasize the noticeable effects of environmental factors on LS. Based on negative estimates of phenotypic and environmental trends, it could be concluded that the environmental factors and as a result, phenotypic situation of LS in Markhoz goats is worsening every year. A main source of the observed negative phenotypic and environmental trends was dramatic decline of litter size after 2009, which indicated poor management and feeding strategies of Markhoz goats in recent years. This situation considerably increases the extinction risk of this breed. Hence, preservation of this breed needs more precise strategies for breeding and management.
This study shows that the programs used have not been efficient to improve the reproduction ability of this breed. A way to protect the Markhoz breed from extinction risk is improving its reproduction efficiency to stimulate farmers to keep this breed. Low heritability of litter size means that traditional breeding methods based on phenotypic data, would be time consuming and an inefficient process, because they need several generations for a slight genetic progress. Improvement of environmental factors such as nutrition, management and health care strategies would be more efficient methods to enhance the reproduction ability traits. In addition to optimize environmental conditions, more attempts to find genetic background of LS trait in Markhoz breed, and application of molecular genetics and high-throughput technologies, such as single nucleotide polymorphism (SNP) chips, whole genome sequencing, and whole transcriptome analysis for marker assisted selection (MAS) or prediction of genomic breeding values could improve the genetic situation of reproduction traits and reduce the extinction risk for this breed.
