The untranslated regions (UTRs) of genes play crucial roles in regulating gene expression at the post-transcriptional level such as affecting mRNA stabilization. In this study, 26 single nucleotide polymorphisms (SNPs) and one deletion located in UTR were genotyped from 186 Dazu black goats via SNaPshot, and the correlation between genotype and litter size was analyzed. The results indicated that two SNP loci, SNP_chr17-20182525 and SNP_chr7-65652612, which were located at the 3′ UTR of scavenger receptor class B member 1 and follistatin-like 4, were significantly (P < 0.05) correlated with the litter size of first parity goats. SNP_chr7-65652612 was also significantly associated with the total litter size of first and second parity offspring (P < 0.05). In conclusion, SNP_chr7-65652612 and SNP_chr17-20182525 have correlation with the litter size of Dazu black goat and they are potential genetic markers for litter size breeding.
Les séquences non traduites (UTR — « untranslated regions ») des gènes jouent un rôle primordial dans la régulation de l’expression de gènes du point de vu post transcriptionnel, comme celui de la stabilisation de l’ARNm. Dans cette étude, 26 polymorphismes mononucléotidiques (SNP — « single nucleotide polymorphism ») et une délétion localisés dans les UTR de 186 chèvres noires Dazu ont été génotypés par SNaPshot, et la corrélation entre le génotype et la taille de portée a été analysée. Les résultats indiquent qu’il y a une corrélation significative (P < 0,05) entre deux loci SNP, SNP_chr17-20182525 et SNP_chr7-65652612, qui se trouvent à l’extrémité 3′ UTR du récepteur scavenger de classe B, type 1 et apparenté à la follistatine 4, et la taille de portée des chèvres à la première parité. SNP_chr7-65652612 est aussi associé de façon significative à la taille totale de la portée de la progéniture aux premières et deuxièmes parités (P < 0,05). En conclusion, il y a corrélation entre SNP_chr7-65652612 et SNP_chr17-20182525 et la taille de portée des chèvres noires Dazu et les SNPs sont des marqueurs génétiques potentiels de taille de portée en reproduction. [Traduit par la Rédaction]
Introduction
Rapid development in economy and living standards has remarkably changed the human dietary structure. The current demand for mutton has been gradually increasing due to its low cholesterol and high contents of protein, amino acid, and trace elements.
Dazu black goat, originated in Dazu County, Chongqing, China, is formed by breeding and selection with excellent meat quality. In addition, Dazu black goats are also well known for reproduction traits with high fecundity, big litter size, and precocious sexual maturity. Thus, it can be used as a valuable material to search for genetic markers related to economic traits. Litter size is widely recognized as one of the most important economic parameters for mutton sheep farming. Fortunately, some major genes and genetic variations associated with litter size, including growth differentiation factor 9 (Wang et al. 2019), bone morphogenetic protein receptor, type IB (Shokrollahi and Morammazi 2018), and gonadotropin-releasing hormone receptor (Bemji et al. 2018), have been identified. The development of the whole-genome resequencing technique provided a useful tool to elaborate on genetic factors underlying the formation of economic traits at the whole-genome level. Several studies have been carried out on goat litter size with the whole-genome resequencing (E et al. 2019; Zhang et al. 2019). However, studies on the polymorphisms in untranslated regions (UTRs) are limited (Zhang et al. 2018; Kang et al. 2019; Quan et al. 2019; Yang et al. 2019), and the associations with litter size remain unclear.
UTRs, including 5′ and 3′ UTRs, play crucial roles in regulating gene expression at multiple levels including transcriptional regulation, pre-mRNA processing, mature mRNA transportation, mRNA stability, and translational control. Variations in UTR sequences can affect gene expression and thus phenotypic expression. The association between the polymorphisms in the UTR and goat litter size should be evaluated to further understand the relevant molecular mechanisms. Follistatin-like 4 (FSTL4) is a member of the follistatin gene family and it belongs to transforming growth factor (TGF)-β superfamily inhibitors. FSTL4, ubiquitously expressed in tissues including heart, lung, kidney, testis, neurons, muscle, and intestine, plays multiple roles in biological processes (Tsuchida et al. 2000). Recent studies showed that FSTL4 was a candidate gene for the reproduction ability in dairy cows (Lu et al. 2021). Scavenger receptor class B member 1 (SCARB1), also known as SR-BI, plays an important role in reproduction activity. SCRAB1 is expressed in cells of developing follicles such as theca, granulosa, and cumulus cells. Mice carrying null mutation of the SCARB1 gene (SCARB1−/−) had ovaries with small corpora lutea (Jiménez et al. 2010).
In this study, based on the data of the published article (E et al. 2019) and expanded the sample size, we explore the association of 26 single nucleotide polymorphisms (SNPs) and one deletion in the UTRs with litter size in Dazu black goats and determine the potential for these polymorphisms as genetic markers in the marker-assisted selection of goat.
Materials and methods
Ethical statement
The experimental conditions in this study were approved by the Committee on the Ethics of Animal Experiments of Southwest University and the Animal Protection Law of China (this study did not directly carry out any relevant experiments on animals).
Animals and genomic DNA extraction
A total of 186 individual goats were sampled from the Dazu black goat breeding farm of Southwest University (Chongqing, China). No close kinship did exist between individuals within 2–3 generations. The animals were bred under the same feeding conditions and environment. The lambing records of all animals and the litter size of first and second parity animals were collected. Exactly 1 mL of venous blood was collected, and whole blood genomic DNA was extracted using the TIANamp Blood DNA kit (Tiangen, Beijing, China). Optical density was detected using a NanoDrop2000 instrument, and DNA quality was tested by 1.25% agarose gel electrophoresis. The DNA samples were stored at −20 °C for further analysis.
Primer design and genotyping
The detailed primer information is described in Table S1 and SNaPshot was used to analyze genotype. The polymerase chain reaction (PCR) was performed and the reaction volume and thermal profile were given in Table S2. The PCR product was treated with alkaline phosphatase remove free dNTPs (Table S3). Single base extension reaction was conducted and the detailed information was given in Table S4. Finally, SNaPshot reaction product was purified as described in Table S5. The 27 variant loci of all individuals were genotyped using SNaPshot and the ABI3730XL sequencing platform (AB, Waltham, USA). The expected and observed heterozygosities (HE and HO, respectively) and polymorphic information content (PIC) of each SNP were estimated using GenePop ( http://www.genepop.curtin.edu.au/).
Statistical analyses
Although the limitations of using a small sample size for case-control studies were reported (Clarke et al. 2011), the goat litter size is a strong associated trait with high heritability. Many studies have been proved that relative small sample size could be used to detect key candidate markers (Lai et al. 2016; Islam et al. 2020; Tao et al. 2020; Smołucha et al. 2021). In accordance with the Genome Variant Map data (GVM000039) and litter size record of Dazu goats (E et al. 2019), the genotype frequencies of 27 variants located at the 5′ and 3′ UTRs were measured by Fisher’s test with R script. The genetic effects (GEs) of minimum allele frequency (MAF) were measured via a general linear model with efficient mixed-model association eXpedited (EMMAX, Kang et al. 2010; Legarra et al. 2018). On the basis of the limited number of markers in this study, P < 0.05 was used to filter significant markers. All markers were placed into fixed effect estimated matrix to explain the phenotype variances:
where Y is a vector of phenotype values; μ is the average vector; the length is the same as the number of individuals (n); α is a vector of the markers’ estimated effect; X is a designed matrix in which the dimension is n × m, where m is the number of markers; and e is the residual matrix.
Deviations of SNPs from the Hardy–Weinberg equilibrium (HWE) within populations were identified using Arlequin software version 3.5.1.3 (Excoffier and Lischer 2010).
Results and discussion
In this study, the genotype frequencies of 27 variants located at the 5′ and 3′ UTRs were significantly different between high and low yields of litter size by Fisher's test according to previously published wide-genome data set (Table 1, Genome Variant Map data: GVM000039). This finding suggests that the series of SNPs have a strong correlation with goat litter size. In addition, the genotype data of 27 variants of all individuals were uploaded to European Variation Archive (Project_PRJEB35784, Analyses_ERP118896). Based on the data analysis, we further explore the correlation between 27 variant loci and litter size by expanding the sample size of Dazu goat. Analysis of all 27 variant loci showed that the majority of variants carry high levels of polymorphism, as revealed by HE, HO, and PIC. Among these variants, SNP_chr11-70706856 and SNP_chr12-74985766 were homozygous and excluded from the further study (Table 2). According to HWE, seven SNPs within the population deviated from equilibrium, thus suggesting that these SNPs may be subject to artificial selection. The dominant genotype frequencies of the relevant trait-determining sites were fixed due to artificial selection within the population during long-term breeding.
Table 1.
Twenty-seven variants with significant divergence between high and low yields of litter size in Dazu black goats based on a genome-wide selection data set.
Table 2.
Polymorphisms of 27 variants within the Dazu black goat population.
Correlation analysis showed that two SNP loci, namely, SNP_chr17-20182525 (P = 0.0472, GE [MAF] = −0.1908) and SNP_chr7-65652612 (P = 0.0493, GE [MAF] = −0.2860), which were located at the 3′ UTR of SCARB1 (XM_018061401.1: c.*403G > A) and FSTL4 (XM_018050393.1: c.*741C > G), respectively (Table 3), were significantly correlated with the litter size of first parity goats (LF). No SNP was significantly associated with the litter size of second-born animals (LS). The sum litter size of first and second parity animals (SL) was evaluated, and correlation analysis of all SNPs with the first and second parity litter size was performed. The results showed that SNP_chr7-65652612 was significantly associated with SL (P = 0.0118, GE (MAF) = −0.6357, Table 3).
Table 3.
Correlation analysis of 24 SNP variations with litter size in Dazu black goats.
SCARB mediates the liver uptake and bile secretion of high-density lipoprotein cholesterol, thereby promoting reverse cholesterol transport and slow lipoprotein aggregation; thus, SCARB has antiatherosclerotic effects (Takiguchi et al. 2018; Lee et al. 2019). Previous studies have shown that the SNP rs5888 in the SCARB1 gene is associated with serum lipid levels in a sex-specific manner (Morabia et al. 2004). SCARB1 has been involved in osteoblast differentiation (Tourkova et al. 2019), the molecular immune mechanism of allicin (Toma et al. 2019), and reproduction performance (Jiménez et al. 2010). However, no direct evidence supports the involvement of SCARB1 in goat litter size.
SNP_chr7-65652612 in the 3′ UTR of FSTL4 was not only significantly associated with the litter size of first parity goats and the total litter size of first and second parity goats but it was also a factor promoting significant differences in litter size between different genotypes (Table 4). FST is a mono-affinity glycoprotein that binds to many members of the TGF-β superfamily via paracrine and autocrine signaling, hence critical to female animal reproduction activity (Passos et al. 2013; Cannarella et al. 2019). A series member of FSTL has been found to play a role in reproduction. FSTL3 levels could be attributed to pre-eclampsia, and they are associated with an increased likelihood of developing pre-eclampsia (Founds et al. 2015). Moreover, FSTL3 could limit the age-related degeneration and size of testicles (Oldknow et al. 2013). FSTL4 was recently shown to be a candidate for the reproduction performance in dairy cows (Lu et al. 2021).
Table 4.
Genotype frequency and litter size differences between genotypes of candidate SNPs.
Natural selection is the main cause of genetic polymorphism. The diversity of genetic variation in population is the basis for phenotype difference. In this study, 27 gene polymorphisms may lead to changes in protein function, resulting in differences in litter size of Dazu black goat. At present, many studies have concluded that genetic variation is related to economic traits of animals. IGF1R c.654g > a variation had significant effects on many economic traits of Polish colored Merino sheep (Grochowska et al. 2020). The variation of FABP4 is related to the milk production traits of Greek Sfakia sheep (Ibrahim et al. 2019). The sample size in the study is a key parameter for detection of candidate marker. Although the sample size in this study is much larger than other reported studies (Lai et al. 2016; Islam et al. 2020; Tao et al. 2020; Smołucha et al. 2021), expansion of sample size will surely enhance detection power and reduce false positive rate.
In conclusion, this study explored 26 SNPs and one deletion variation in the UTR and found that two SNPs were associated with high fecundity of Dazu black goats. The results could contribute to revealing the genetic mechanism underlying the high reproduction performance of Dazu goats.
Acknowledgements
This work was supported by the National Key R&D Program of China (No. 2018YFD0502000), the National Natural Science Foundation of China (No. 31172195), the Fundamental Research Funds for the Central Universities (No. XDJK2018B014; support for experimental animal costs), and Chongqing Research Program of Basic Research and Frontier Technology (cstc2018jcyjAX0153).
Supplementary material
Supplementary data are available with the article at https://doi.org/10.1139/cjas-2020-0170.