Polymorphism of four microsatellites and their polymerisation effect on litter size in Boer goats

Jian Gang Wang¹ · Jin-Xing Hou¹ · Guang Li¹ · Guang Qin Zhu¹ · Bin Yun Cao*¹

¹Northwest A&F University, College of Animal Science and Technology, Yangling, Shaanxi, P.R. China

*Corresponding author: caobinyun@126.com

Financial support: This study was supported by the National Support Program of China (2011BAD28B05-3) and Technology Innovation Project of Shaanxi Province (2011KTCL02-09).

Keywords: microsatellite marker, pedigrees, polymerisation effect, polymorphism.

Background: Finding molecular markers linked to quantitative trait loci is the first step in marker-assisted selection (MAS). Microsatellites are excellent molecular markers because of their large numbers, even distribution in the genome, and high polymorphism. In this study, the polymerisation effect of four microsatellites (OarAE101, BM1329, BM143, and LSCV043) on litter size was analysed using microsatellite markers and pedigrees.

Results: The results indicate that the polymerisation effect of four microsatellite loci significantly affected the litter size. E₅E₁₀F₂F₆G₁G₅H₆H₁₁ and E₃E₈F₅F₇G₁G₅H₃H₉ had the highest and lowest litter sizes in the F2 generation, respectively. The polymerisation effect value (v) of the E₅E₁₀ genotype was 3.18% higher than that of the E₂E₇ genotype. The v of genotype F₂F₆ was 14.47% higher than that of the F₅F₇ genotype. The v of genotype G₁G₅ was 58.99% higher than that of the G₂G₇ genotype. The v of the H₆H₁₁ genotype was 5.60% to 49.74% higher than those of the H₄H₁₀ and H₁H₇ genotypes. The v of the H₃H₉ genotype was 17.22% higher than that of the H₁H₇ genotype.

Conclusions: The results of the present study are vital to improving the reproductive performance in goat breeds MAS.

Selective breeding in goats is relatively effective because of the low heritability of the litter sizes. Marker-assisted selection (MAS) can improve the efficiency of selective breeding for traits with low heritability by controlling the selection time, selection strength, and accuracy. The search for molecular markers linked to quantitative trait loci is the first step in MAS (Dekkers, 2004; Williams, 2005). Microsatellites are excellent molecular markers because of their large numbers, even distribution in the genome, and high polymorphism (Scali et al. 2012).

Polymerisation is a breeding method for developing new breeds or lines. In this technique, favourable genes from several different breeds or lines are integrated into a breed or line through genetic engineering and hybridisation, backcrossing, and multiple cross (Yadav et al. 1990; Servin et al. 2003). Polymerisation affects the contribution rates of different genotypes to the performance in genotype combinations (Li et al. 2011). Marker-assisted gene pyramiding provides a way for animal and plant breeders to integrate the favourable genes identified in different breeds (lines) and to build an ideal genotype or genotype combination through optimal mating of individuals based on their genotypes at the target loci. Gene pyramiding has been successfully applied in several crop breeding programs to improve the disease and insect pest resistance of crops, consequently producing a number of varieties and lines (Huang et al. 1997; Hittalmani et al. 2000; Barloy et al. 2007). However, gene pyramiding in animals has not been practiced to date because of low fertility, long generation intervals, inability to perform self-fertilisation, and inbreeding depression in animals.

One copy of the FecB gene increases the ovulation rate by 1.3 to 1.6, while two copies increase the rate by 2.7 to 3.0. The litter size is increased by 0.9 to 1.2 in ewes that carry a single copy and by 1.1 to 1.7 in ewes with two copies of the FecB gene (Davis et al. 1982; Piper et al. 1985). Four microsatellite loci (OarAE101, LSCV043, BM1329, and BM143) are linked to the FecB gene on ovine chromosome 6 (Montgomery et al. 1993; Lord et al. 1996; Zhang et al. 2009). Montgomery et al. (1993) found that microsatellite marker OarAE101 is linked to the FecB gene, with a maximum likelihood-of-the-odds (lod) score of 17.33 at a distance of 13 centimorgans (cM). Lord et al. (1998) mapped the FecB gene to a 10 cM region between microsatellites BM1329 and OarAE101. Mulsant et al. (1998) reported that the closest flanking markers of the FecB gene are caprine microsatellite LSCV043, which are situated approximately 2 cM on either side of the gene.

Based on the above considerations, we detected the polymorphisms of caprine OarAE101, LSCV043, BM1329, and BM143 in the present study and investigated the relationship between these genetic markers and litter size. This study would provide a number of useful information on goat genetic resources and breeding.

DNA samples

All animals were maintained according to the No. 5 proclamation of the Ministry of Agriculture (P.R. China). Sample collection was approved by the Institutional Animal Care and Use Ethics Committee of Northwest A&F University and was performed in accordance with the ‘‘Guidelines for Experimental Animals’’ of the Ministry of Science and Technology (Beijing, China). Blood samples were obtained from 279 Boer goats, which were reared in Liuyou County of Shaanxi Province (P.R. China). The litter size and pedigree records of each female goat were collected for statistical analysis. DNA samples were extracted from leucocytes (Mullenbach et al. 1989).

PCR conditions and microsatellite marker

According to sheep and bovine microsatellites: OarAE101, BM1329, LSCV043, and BM143 (GenBank accession nos. L13692, G18422, and G18387 and NCBI accession no. 279530, respectively), four primer pairs (P1 to P4) were designed to amplify goat microsatellites OarAE101, BM1329, LSCV043, and BM143 (Table 1), respectively. The 12 µL volume contained 6.0 µL dH₂O, 2.0 µL 10 x buffer, 1.0 µL genomic DNA template, 0.5 µL of each primer (10 pmol/µL), 1.0 µL dNTPs (dATP, dTTP, dCTP, and dGTP), 1.0 µL Taq DNA polymerase (MBI), and 1.5 mM MgCl₂. The cycling protocol was 4 min at 95ºC, 35 cycles of denaturation at 94ºC for 30 sec, annealing at XºC (Table 1) for 30 sec, extension at 72ºC for 40 sec, and a final extension at 72ºC for 10 min. Aliquots (5 μL) of the PCR products were mixed with 2 μL bromophenol blue, and the mixed PCR products were subjected to PAGE (80 mm x 73 mm x 0.75 mm) in a 1 x TBE buffer at constant voltage (200 V) for 3.5 hrs. The gel (29:1 acrylamide:bis) was stained with 0.1% silver nitrate (Ji et al. 2007).

Statistical analysis

Genotypic frequencies were directly calculated. Statistical analysis was performed using the general linear model in the analysis menu of the SPSS 16 statistical software. Multiple comparisons of the means were performed using the least-significant difference method. The model applied was as follows:

Y_ilm = µ + G_i+ S_l + E_ilm

[Model 1]

where Y_ilm is the trait measured on each of the ilm^th animal, µ is the overall population mean, G_i is the fixed effect associated with the i^th genotype, S_l is the random effect associated with the l^th sire, and E_ilm is the random error. The combination effects of the four microsatellites on litter size were analysed using the following model:

Y_ilm = µ + C_i + S_l + E_ilm

[Model 2]

where Y_ilm, µ, and S_l are the same as those in Model 1 and C_i is the fixed effect associated with the i^th combined genotype. Effects associated with farm, birth year, and season of birth were not matched in the linear model because preliminary statistical analyses indicated that these factors do not have a significant effect on the variability of traits in the analysed populations. 

The polymerisation effect values (v) of the genotypic combinations of four microsatellites were calculated using Equation 1.

[Equation 1]

where c and d are the least-square means of different genotypic combinations at average parity, respectively.

Polymorphism of microsatellite loci

Eleven alleles were found at the microsatellite OarAE101 locus (135, 132, 129, 126, 124, 120 bp, 116, 114, 111, 109, and 106 bp) and were subsequently labelled as E₁, E₂, E₃, E₄, E₅, E₆, E₇, E₈, E₉, E₁₀, and E₁₁, respectively (Figure 1, Table 2). Seven alleles were detected at the microsatellite BM1329 locus (220, 217, 215, 210, 207, 190, and 187 bp) and were labelled as F₁, F₂, F₃, F₄, F₅, F₆, and F₇, respectively (Figure 2, Table 2). Meanwhile, nine alleles were found at the microsatellite LSCV043 locus (167, 162, 155, 150, 145, 140, 135, 130, and 120 bp) and were subsequently labelled as G₁, G₂, G₃, G₄, G₅, G₆, G₇, G₈, and G₉, respectively (Figure 3, Table 2). Eleven alleles were found at the microsatellite BM143 locus (137, 135, 132, 129, 127, 124, 120, 119, 115, 114, and 110 bp) and were labelled as H₁, H₂, H₃, H₄, H₅, H₆, H₇, H₈, H₉, H₁₀, and H₁₁ respectively (Figure 4, Table 2). The different genotypes of the four microsatellite loci are shown in Table 3.

Association of the four microsatellite polymorphisms with litter size

The different genotypes of the four microsatellite loci exhibited significant effects on the litter size. The results indicate that individuals with E₅E₁₀ and E₂E₇ genotypes had the largest and smallest litter sizes, respectively, compared with those of other genotypes in the OarAE101 locus (P < 0.05). In the BM1329 locus, individuals with the F₂F₆ genotype had larger litter sizes than those with the F₄F₇ and F₅F₇ genotypes (P < 0.05). In the LSCV043 locus, individuals with the G₁G₅ genotype had the largest litter size compared with those of other genotypes (P < 0.05). In the BM143 locus, individuals with the H₆H₁₁ genotype had larger litter sizes than those with the H₂H₈ genotype (P < 0.05).

Individuals with E₅E₁₀F₂F₆G₁G₅H₆H₁₁ had larger litter sizes than those with E₅E₁₀F₂F₆G₁G₅H₄H₁₀, E₅E₁₀F₅F₇G₂G₆H₆H₁₁, and E₅E₁₀F₂F₆G₂G₆H₆H₁₁ at average parity (P < 0.05) (Table 4). Compared with E₅E₁₀F₂F₆G₁G₅H₄H₁₀, the polymerisation effect value (v) of the H₆H₁₁ genotype of E₅E₁₀F₂F₆G₁G₅H₆H₁₁ was 16.80% higher than that of the H₄H₁₀ genotype. A comparison of E₅E₁₀F₂F₆G₂G₆H₆H₁₁ and E₅E₁₀F₅F₇G₂G₆H₆H₁₁ showed that the v of the F₂F₆ genotype was 14.47% higher than that of the F₅F₇ genotype. Meanwhile, a comparison of E₅E₁₀F₂F₆G₁G₅H₆H₁₁ and E₅E₁₀F₂F₆G₂G₆H₆H₁₁ indicated that the v of the G₁G₅ genotype was 8.55% higher than that of the G₂G₆ genotype (Table 4).

Individuals with E₅E₁₀F₂F₆G₁G₅H₁H₇ had larger litter sizes than those with E₅E₁₀F₂F₆G₂G₆H₄H₁₀, E₂E₇ F₂F₆G₂G₇H₆H₁₁, and E₂E₇F₅F₇G₁G₅H₆H₁₁ at average parity (P < 0.05) (Table 5). A comparison of E₅E₁₀F₂F₆G₁G₅H₆H₁₁ of the F₁ generation and E₅E₁₀F₂F₆G₂G₆H₄H₁₀ of the F₀ generation showed that the v of the H₆H₁₁ genotype was 49.74% higher than that of the H₄H₁₀ genotype. A comparison of E₂E₇F₂F₆G₁G₅H₆H₁₁ of the F₁ generation and E₂E₇F₂F₆G₂G₇H₆H₁₁ of the F₀ generation indicated that the v of the G₁G₅ genotype was 58.99% higher than that of the G₂G₇ genotype. A comparison of E₂E₇F₂F₆G₁G₅H₆H₁₁ of the F₁ generation and E₅E₁₀F₂F₆G₁G₅H₁H₇ of the F₀ generation showed that the v of the H₆H₁₁ genotype was 13.20% higher than that of the H₁H₇ genotype (Table 5).

Individuals with E₅E₁₀F₂F₆G₁G₅H₆H₁₁ had larger litter sizes than those with E₂E₇F₂F₆G₁G₅H₁H₇ and E₃E₈F₅F₇G₁G₅H₃H₉ at average parity (P < 0.05) (Table 6). In the F₂ generation, the v of H₃H₉ of the E₅E₁₀F₅F₇G₁G₅H₃H₉ genotype was 21.53% higher than that of the H₁H₇ genotype compared with E₅E₁₀F₅F₇G₁G₅H₁H₇. A comparison of E₅E₁₀F₂F₆G₁G₅H₆H₁₁ and E₅E₁₀F₂F₆G₂G₆H₆H₁₁ showed that the v of the G₁G₅ genotype was 19.18% higher than that of the G₂G₆ genotype. A comparison of E₂E₇F₂F₆G₁G₅H₆H₁₁ of the F₁ generation and E₂E₇F₂F₆G₁G₅H₁H₇ of F₂ generation indicated that the v value of the H₆H₁₁ genotype was 70.48% higher than that of the H₁H₇ genotype. A comparison of E₅E₁₀F₅F₇G₂G₆H₆H₁₁ of the F₁ generation and E₅E₁₀F₅F₇G₃G₈H₆H₁₁ of the F₂ generation showed that the v of the G₂G₆ genotype was 6.82% higher than that of the G₃G₈ genotype.

The 107 bp/113 bp genotype of OarAE101 and 146 bp/158 bp genotype of BM1329 exhibited significant positive correlations with the litter size in Small Tail Han sheep (Chu et al. 2001). Ouyang et al. (2006) reported that individuals with the 107 bp/111 bp genotype had the largest litter size compared with those of other genotypes in microsatellite OarAE101. In addition, individuals with the 100 bp/106 bp and 106 bp/112 bp genotypes had larger litter sizes than those of other genotypes in microsatellite BM143. In the present study, the results indicate that individuals with the E₅E₁₀ and E₂E₇ genotypes had the highest and lowest litter sizes, respectively, in the OarAE101 locus (P < 0.05). Individuals with the F₂F₆ genotype had larger litter sizes than those with the F₄F₇ and F₅F₇ genotypes in the BM1329 locus (P < 0.05). Individuals with the G₁G₅ genotype had the largest litter size in the LSCV043 locus (P < 0.05). Individuals with the H₆H₁₁ genotype had larger litter sizes than those with the H₂H₈ genotype in the BM143 locus (P < 0.05).

Reproductive traits are complex quantitative traits that involve multiple genes, loci, and interactions. Therefore, investigations on the combined effects of multiple genes or loci on reproductive traits are important (An et al. 2013). In the present study, the association between multiple loci and litter size from the first to the fourth parity was analysed. The results show that the polymerisation effects of E₅E₁₀F₂F₆G₁G₅H₆H₁₁ and E₅E₁₀F₂F₆G₁G₅H₁H₇ on litter size were greater than those of other combination genotypes. Compared with E₅E₁₀F₂F₆G₁G₅H₄H₁₀, the polymerisation effect value (v) of the H₆H₁₁ genotype of E₅E₁₀F₂F₆G₁G₅H₆H₁₁ was 16.80% higher than that of the H₄H₁₀ genotype. A comparison of E₅E₁₀F₂F₆G₂G₆H₆H₁₁ and E₅E₁₀F₅F₇G₂G₆H₆H₁₁ showed that the v of the F₂F₆ genotype was 14.47% higher than that of the F₅F₇ genotype. A comparison of E₅E₁₀F₂F₆G₁G₅H₆H₁₁ of the F₁ generation and E₅E₁₀F₂F₆G₂G₆H₄H₁₀ of the F₀ generation indicated that the v of the H₆H₁₁ genotype was 49.74% higher than that of the H₄H₁₀ genotype. A comparison of E₂E₇F₂F₆G₁G₅H₆H₁₁ of the F₁ generation and E₂E₇F₂F₆G₂G₇H₆H₁₁ of the F₀ generation showed that the v of the G₁G₅ genotype was 58.99% higher than that of the G₂G₇ genotype. Compared with E₅E₁₀F₅F₇G₁G₅H₁H₇, the v of H₃H₉ of the E₅E₁₀F₅F₇G₁G₅H₃H₉ genotype was 21.53% higher than that of the H₁H₇ genotype. A comparison of E₂E₇F₂F₆G₁G₅H₆H₁₁ of the F₁ generation and E₂E₇F₂F₆G₁G₅H₁H₇ of the F₂ generation showed that the v value of the H₆H₁₁ genotype was 70.48% higher than that of the H₁H₇ genotype. The results of the previous studies, together with the results obtained in the present study, indicate that the four microsatellite polymorphisms associated with litter size have potential applications in MAS programs for goat breeding.

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