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Electronic Journal of Biotechnology

On-line version ISSN 0717-3458

Electron. J. Biotechnol. vol.16 no.4 Valparaíso July 2013

http://dx.doi.org/10.2225/vol16-issue4-fulltext-13 

  Animal Biotechnology
Electronic Journal of Biotechnology ISSN: 0717-3458 Vol. 16 No. 4, Issue of July 15, 2013
© 2013 by Pontificia Universidad Católica de Valparaíso -- Chile Received November 14, 2012 / Accepted June 5, 2013
DOI: 10.2225/vol16-issue4-fulltext-13  
RESEARCH ARTICLE

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.

Abstract

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.

Introduction

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.

Materials and Methods

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:

Yilm= µ + Gi+ Sl + Eilm

[Model 1]

where Yilm is the trait measured on each of the ilmth animal, µ is the overall population mean, Gi is the fixed effect associated with the ith genotype, Sl is the random effect associated with the lth sire, and Eilm is the random error. The combination effects of the four microsatellites on litter size were analysed using the following model:

Yilm= µ + Ci + Sl + Eilm

[Model 2]

where Yilm, µ, and Sl are the same as those in Model 1 and Ci is the fixed effect associated with the ith 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.

Results

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.

Discussion

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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