Domestication of goats first began 10,000 years ago
(Zeder and Hesse, 2000;
Kumar et al., 2018; Bertolini et al., 2018). After goats spread worldwide from domestication centers, the phenotypic characteristics of different local population and population have huge differences because of the differences in the ecological environment, culture in habitat regions and artificial breeding of human with breeding requirements
(Guang-Xin et al., 2018;
Wang et al., 2017).
More than 90% of goats are distributed in Asia and Africa
(Yang et al., 2018). However, the large number of high-productivity introduced breeds has led to a decline in the population size of native populations and extensive gene flow between commercial breeds and local populations has affected the conversion of local goat populations
(Guang-Xin et al., 2018;
Yang et al., 2021). Microsatellite markers in eukaryotes
(Yadav et al., 2015) have been widely used to investigate the genetic diversity of a variety of domestic animals, such as deer
(Yang et al., 2018), pig
(Kharzinova and Zinovieva, 2020) and chicken
(Habimana et al., 2020).
This study aimed to explore the genetic diversity and population genetic structure relationships of six goat populations (five local populations and one introduced breed) in Chongqing, China using 18 autosomal microsatellite markers to provide a data reference for their conservation.
Six goat populations, including five indigenous populations (Table 1), namely, Banjiao (BJG, 21), Dazu black (DZG, 24), Hechuan white (HCG, 24), Jianzhou big-ear (JZG, 30) and Youzhou Wu (UZG, 25) goats and an introduced breed called Nubian goat (NBG, 21). A total of 145 samples with unrelated kinship were randomly collected. Venous blood (5 mL) was collected from each goat and genomic DNA was extracted using the Steypure Universal Genomic DNA Extraction Kit (Chongqing, China). Eighteen microsatellite markers (INRA023, ILSTS005, INRABERN185, MAF065, INRA063, ILSTS011, OarFCB20, SRCRSP7, ILSTS029, SPS113, CSRD247, SRCRSP5, SRCRSP8, SRCRSP9, TCRVB6, MAF70, OarFCB48 and TGLA53) were used for genotyping of samples and genetic diversity analysis similar to a previous study
(Guang-Xin et al., 2020). Primers of microsatellite markers were synthesized by Wuhan Tianyi Huiyuan Biological Co., Ltd.
A 15 μL system, including 0.35 μL of upstream and downstream primers (10 μmol/L), 1 μL of DNA (~100 ng/μL), 7.5 μL of 2×Accurate Taq master mix (Accurate Biology, Chongqing) and 5.8 μL of ddH2O, was used for PCR amplification. The following program of the PCR amplification system was applied: predenaturation at 94°C for 5 min, denaturation at 94°C for 30 s, annealing at 51°C-61°C for 30 s, extension at 72°C for 30 s and 30 cycles. Finally, amplification was extended at 72°C for 5 min and products were stored at 4°C. PCR products were genotyped using the ABI3730 platform (AB, US).
Observed heterozygosity (HO), expected heterozygosity (HE), polymorphic information content (PIC) and mean number of alleles (NA) were analyzed using the microsatellite toolkit
(Freeman et al., 2004). Hardy–Weinberg equilibrium (HWE) and genetic differentiation coefficient (FST) were calculated using Arlequin
(Excoffier et al., 2007). Inbreeding coefficients within population (FIS) were analyzed using FSTAT software
(Goudet, 1995). PHYLIP software package
(Felsenstein, 1989) was used to construct a phylogenetic tree on the basis of Nei’s genetic distance and iTOL (https://itol.embl.de/) online website was utilized for visualization. STRUCTURE 2.3.3
(Pritchard et al., 2000) was applied to perform Bayesian population structure clustering analysis with 100 repetitions and STRUCTURE_harvester (http://taylor0.biology.ucla.edu/struct_harvest/) online tool was used to assess the optimal K value. Furthermore, the structural result was visualized using CLUMP
(Jakobsson and Rosenberg, 2007) and DISSTRUCT 1.1
(Rosenberg, 2004).
A total of 271 alleles were detected in all samples (Table 1) and NA of each microsatellite marker ranged from 8 (MAF70) to 28 (INRA023). HE ranged from 0.58 (SRCRSP7 and ILSTS029) to 0.92 (CSRD247) and HO ranged from 0.22 (ILSTS005) to 0.81 (MAF065), with an average value of 0.58. PIC of each marker ranged from 0.56 (SRCRSP7 and ILSTS029) to 0.91 (CSRD247), with an average value of 0.74.
The results were higher than those of Indian
(Yadav et al., 2015), Brazilian
(Menezes et al., 2020) and Chinese goat breed populations along the Yangtze River
(Guang-Xin et al., 2018) despite their similarity with Chinese dairy
(Wang et al., 2017) and endangered Spanish
(Serrano et al., 2009) goat breeds. Therefore, the six goat populations in Chongqing demonstrated rich genetic diversity.
The HWE analysis results of all markers (Table 2) showed that 11 markers deviate from HWD in the JZG population while BJG deviates from HWE with the minimum number of markers (4). Notably, ILSTS005 deviated from HWE within all six populations while INRA063, OutFCB20 and OutFCB48 did not deviate from HWE among the populations.
The genetic diversity of population demonstrated that NA of the six goat populations ranges from 5.83±1.98 (UZG) to 8.22±2.44 (JZG), PIC ranges from 0.56 (UZG) to 0.67 (JZG), HE ranges from 0.62±0.042 (UZG) to 0.72±0.029 (JZG) and HO ranges from 0.52±0.024 (JZG) to 0.64±0.024 (NBG). Notably, FIS of each population ranged from 0.043 (NBG) to 0.284 (JZG) and FIS of all populations was statistically insignificant (P>0.00046, Table 3). Although the above-mentioned populations were not yet under inbred, the results of HWE analysis indicated that the conservative status of their genetic diversity should be monitored.
In particular, HE of the six goat populations was higher than their HO in this study, thereby indicating that decreased heterozygosis is common in these goat populations. Notably, the small population size and unbalanced mating ratio, particularly when a few satisfactory breeding males provided the group a high proportion of spouse rights, will cause the population to deviate from the balance and lead to increased risks in the population
(Yang et al., 2021; Guang-Xin et al., 2019;
Basang et al., 2021). Therefore, some of these populations, especially JZG and BJG, still showed potential risks of inbreeding.
Subsequently, the result of FST analysis showed that the FST pair among populations is significant (P<0.05), thereby indicating a large and significant genetic divergence among populations (Table 4). The smallest difference pair (FST=0.0479, P<0.05) was identified between DZG and HCG, whereas the largest difference pair (FST=0.23306, P<0.05) was identified between HCG and JZG.
The phylogenetic results (Fig 1) showed that the three populations, namely, NBG, UZG and BJG, cluster into one; HCG and DZG cluster together and JZG clusters individually. Except for the introduced breed (NBG), population phylogenetic relationships of other local populations were consistent with their geographical distribution of habitats.
The results of population structure (Fig 2) analysis in this study showed that DZG and HCG are initially separated from all populations when K=2, JZG populations are separated from the remaining four populations to form a cluster when K=3 and the BJG population is separated into another cluster when K=4. In addition, K=3 obtained the optimal K value (Table 5) and the population structure pattern was consistent with previous reports
(Guang-Xin et al., 2015).
The geographical environment of Chongqing is complex because several criss-crossing mountains and rivers that serve as a natural geographical barrier for wild and domestic animal populations affect the exchange of genetic material among them
(Yang et al., 2021; Yuan et al., 2012). The phylogenetic relationship and population clustering of populations, especially HCG and DZG, were in accordance with their sampling locations.
Notably, Youyang (the UZG sample location) is far from Kaizhou; however, UZG and the two goat populations from Kaizhou (NBG and BJG) are grouped together. Hence, the phylogenetic relationship of Chongqing indigenous populations fails to match completely with their geographical distribution. This phenomenon is widely observed in domestic animals
(Guang-Xin et al., 2018). Therefore, extensive historical exchanges of genetic material are observed among original goat populations after introducing NBG. In particular, human migration and trade activities cause genes to flow easily among adjacent animal population habitats.
