DNA Polymorphisms in 3ʹUTR and Intron-9 Region of PPARGC1A Gene and its Association with Milk Production Traits in Gaolao Cattle

Traditional and advanced principles and tools in animal genetics and breeding will revolutionize future dairy cattle breeding for productivity enhancement. Molecular marker technology has paved the way for identifying the candidate gene regions underlying economic traits like milk production in dairy animals. The imputation of these identified variants information in genetic evaluation increases selection accuracy and improves genetically essential traits like milk yield and milk composition. Various researchers are currently working on genomic research to enhance milk productivity by conducting candidate gene polymorphism and association studies (Rahayu et al., 2019; Liu et al., 2020; Korkuc et al., 2021).  

Peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PPARGC1A) gene mediates the expression of genes involved in gluconeogenesis. It is a prominent functional and positional candidate governing the potential quantitative trait locus effect for milk fat in dairy bovines. PPARGC1A gene is located on the 6th bovine autosome and to date, many SNPs related to milk production traits have been identified. Various studies have reported that SNPs like PPARGC1Ac.1892T>C and PPARGC1A- c.3359 A>C affect milk yield traits (Weikard et al., 2005; Khatib et al., 2007; Komisarek et al., 2009; Viale et al., 2017).

Gaolao cattle is a relatively fair milk yielder indigenous cattle breed well adapted to harsh, adverse and tropical climatic conditions of the Vidarbha region of Maharashtra state of India. Gaolao Breed is known by her prominent frontal bone and short stumpy horns. Candidate genes have been consistently reported from different studies for their association with the milk production traits (Strucken et al., 2015). PPARGC1A was analyzed using a genome-wide association study approach to identify significant SNPs strongly linked with milk traits. Because of this, it is needed to study PPARGC1A gene to develop a database of variations linked with milk traits for their possible further use in improving productive and healthy Gaolao population.

Experimental animals and data collection
 
The adult milking Gaolao cows were selected for the current study from Gaolao farmers of the breeding tract. Around 05 ml blood was collected from 224 purebred adults milking Gaolao cattle using sterile needle and anticoagulant. The collected blood was stored at 4^oC temperature until DNA isolation. Milk in the quantity of around 20 ml was collected from 135 adult milking cows to estimate milk components like fat%, protein%, SNF% and Lactose%, etc.
 
Nucleic acid extraction, quality and quantity estimation
 
The nucleic acid extraction was carried out using phenol, chloroform-isoamyl alcohol extraction protocol (Sambrook and Russel, 2001) with minor modifications and also using Kits. The quality and quantity were checked using a spectrophotometer and agarose gel electrophoresis. The genomic DNA was stored at -20^oC in a freezer which was later used to prepare a working solution for PCR reactions.
 
Polymerase chain reaction
 
The primers were custom synthesized from a company for their use in amplification of 3'UTR and Intron-9 regions of PPARGC1A gene. The information about the gene region, amplicon product size, annealing temperature, primer sequence is given in Table 1. The PCR amplification of 3'UTR and intron-9 regions of PPARGC1A gene was carried out using PPARGC1AG1 and PPARGC1AG4 primers. The PCR amplification conditions for PCR components and thermal cycling conditions were optimized in the laboratory. PCR amplification was performed in a volume of 25 μl containing 12.5 μl 1X PCR buffer, 10 pM of each primer, 4% DMSO and 50-100 ng genomic DNA. The cycling protocol was as follows: 5 min at 95^oC, 32 cycles of denaturing at 94^oC for 45 seconds, annealing at Tm ^oC for 45 seconds (Table 1) and extension at 72^oC for 45 seconds, with a final extension at 72^oC for 7 min. The PCR amplifications were assessed in 1.5% agarose gel electrophoresis by loading 4 μl of PCR product mixed with ethidium bromide (10 mg/ml). The stained PCR gels were visualized using UV fluorescence and documented in a gel documentation system (BR Biochem).


 
PCR-RFLP analysis
 
The quality PCR amplicons were used for PPARGC1AG1-NheI PCR-RFLP analysis in 224 animals of Gaolao cattle. The restriction digestion of the regions of the PPARGC1A gene was carried out using 5U/µl of NheI restriction enzyme and  0.1- 0.5 μg PCR product of each primer and incubated at 37^oC temperature for 14 hours. Later restriction enzyme digested PCR products were resolved in 3.5% agarose gel electrophoresis using ethidium bromide staining and later documented under GelDoc system.
 
PCR-SSCP analysis
 
SSCP analysis was carried out in 43 animals with the vertical electrophoresis apparatus (Bio-rad). The 8% polyacrylamide gel was prepared using acrylamide: bisacrylamide (49:1), 10X TBE buffer, glycerol and autoclaved distilled water and electrophoresis was run at 150 volts for 5-6 hrs at 25°C temperature. After completing the electrophoresis run, the SSCP gel was stained using the standard 0.01% silver nitrate staining procedure with some modifications in the laboratory.
 
SNP analysis using bioinformatics tools
 
The obtained DNA sequences were analyzed using various bioinformatics tools (BioEdit BLAST, Clustal Omega) to detect nucleotide substitutions.
 
Statistical analysis
 
Genotype and allele frequencies were estimated using POPGENE Ver­sion 1.31 (Yeh and Boyle, 1997). The obtained gene and genotype frequencies were tested for deviation from Hardy-Weinberg equilibrium using a Chi-square test (Devlin and Risch, 1995). The relationship between the milk component and genotype was tested using one-way ANOVA. The mathematical model is as below,

GT_ijklm = μ + MY_i+ F_j + S_k + L_l + P_m +  + e_ijklm
 

Where,
GT_ijklm= is the observed genotype.
μ = Overall mean.
MY_i= Fixed effect of Milk Yield.
F_j = Fixed effect of Fat %.
S_k = Fixed effect of the SNF %.
L_l = Fixed effect of Lactose %.
P_m = Fixed effect of the Protein %.
e_ijklm = Residual(error) effect of each observation.

All the analysis was done by SPSS Version 20 (IBM, USA).

Information about particular candidate genes like PPARGC1A due to their relevant biological functions, the polymorphism details and their effects on economic traits will help understand a molecular pathway that leads to productivity variation between different individuals of the established breed.
 
PPARGC1AG1- NheI PCR-RFLP results
 
The 357 bp  fragment of 3'UTR region of PPARGC1A gene was amplified using PPARGC1AG1 primer (Fig 1) and digested using NheI enzyme (Khatib et al., 2007). The PPARGC1AG1- NheI PCR-RFLP analysis in 224 animals revealed three different genotypes, i.e., AA with 357 bp band size, AB with 357 bp, 317 bp and 40 bp band sizes and BB with 317 bp and 40 bp band sizes (Fig 2). PPARGC1AG1- NheI locus was found polymorphic for SNP (C.3359 A>C) with genotype frequency for AA genotype as 0.69, AB =0.30 and BB= 0.01. The allele frequency for the A alleles was found at 0.84 and for the allele, B was 0.16 at the PPARGC1AG1- NheI locus (Table 2). The non-significant chi-square value indicated that all the genotypic frequencies in the population were not in Hardy-Weinberg equilibrium (P>0.01). The current study’s findings are in line with the results reported by Basak et al., (2019) in 146 Deoni breeds of cattle for AA, AC and CC genotypes with frequencies as 0.75, 0.21 and 0.04, respectively. For this locus, (Kowalewska-Luczak et al., 2010) also found two genotypes i.e. AA and AC as 0.76 and 0.24 respectively in 181 Jersey cows. 



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However, for the University of Wisconsin (UW) dairy cattle population at this SNP (C.3359 A>C), Khatib et al., (2007) reported genotype frequencies as 0.163, 0.506 and 0.331 for AA, AC and CC, respectively and as 0.123, 0.430 and 0.447, for the Cooperative Dairy DNA Repository (CDDR) population respectively. Weikard et al.  (2005) identified genotype frequencies of AA, AC and CC genotype as 0.15, 0.58 and 0.27, respectively in German Holstein cattle. Similarly, in South Anatolian Red (SAR) indigenous cattle breeds of Turkey, Atila et al., (2014) reported two genotypes, i.e., AA and AC, with 0.23 and 0.77 frequencies, respectively. In East Anatolian Red (EAR) breeds, they found two genotypes, i.e., AA and AC, with frequencies as 0.40 and 0.60, respectively. However, Pasandideh et al., (2015) identified AA, AC and CC genotypes with frequency as 0.38, 0.52 and 0.10, respectively, in 398 Iranian Holstein cows. In the current study, no significant differences were found in milk production traits between all genotypes (Table 3) in 135 experimental animals. However, Khatib et al., (2007) found that A allele was associated with protein percentage in both populations for SNP A/C at position 3359 in the 3'UTR and milk traits in UW and CDDR populations. Similarly, in other studies (Weikard et al., 2005), the PPARGC1A- c.3359A>C SNP, have been reported to affect milk yield traits.

 
SNP detection at polymorphic PPARGC1AG1- NheI PCR-RFLP Locus
 
Three polymorphic genotypes were sequenced which revealed T-C SNP at 263^rd position in the PPARGC1A gene sequence (Fig 3). The alignment of 279 bp PPARGC1AG1 sequence with Bos taurus reference sequence (KM111251.1) revealed 02 computational SNPs viz; C-T at 263^rd position and A-T at 268^th position. BLAST analysis of 279 bp sequence revealed sequence identity of 98.93% with cattle, buffalo and 98.21% with sheep and 97.96% with goat respectively. Distance tree was generated using pairwise alignments between obtained 279 bp sequence in Gaolao cattle with related database sequences (Fig 4). Researchers have performed the alignment analysis of bovine PPARGC1A which exhibited a similarity of 94% for humans and 91.1% for mice and rats (Weikard et al., 2005).




 
PPARGC1AG4-SSCP and SNP detection
 
The PCR-SSCP analysis of 195 bp amplified fragment of PPARGC1A gene (Fig 5) was carried out in 43 samples using 8% PAGE. The silver staining of PPARGC1AG4 gene fragments revealed polymorphism with two SSCP patterns (A and B) at PPARGC1AG4-SSCP locus (Fig 6). The frequency of pattern A was 0.35 and of pattern B was 0.65  in 43 Gaolao animals. The analysis of SSCP Patterns revealed no significant differences in milk production traits (Table 4). However, it was found that individuals with SSCP patterns B exhibited relatively more fat%, SNF%, lactose%, protein % and milk yield than patterns  A. Two SSCP patterns A and B were sequenced which revealed nucleotide substitution indel SNP N-T at 116^th position in Gaolao Cattle.







However, Weikard et al. (2005) revealed SNP c.1892+19T>C in intron 9 of PPARGC1A gene exhibiting three genotypes TT, TC and CC with frequencies as 0.01,0.30 and 0.68 respectively in German Holstein. Khatib et al., (2007) reported three genotypes TT, TC and CC with frequencies as 0.019,0.65 and 0.331 respectively and a significant association between milk yield and milk fat traits. Schennink et al., (2009) screened Holstein Friesian Cattle for SNP c.1892+19T>C and reported frequency of C allele as 0.75 and T allele as 0.25, respectively. Boleckova et al., (2012) also reported the frequency of C allele as 0.80 and T allele as 0.20, respectively, in Czech Fleckvieh cattle. (Kowalewska-Luczak et al., 2010) also reported frequency of C allele as 0.37 and T allele as 0.63 respectively in 181 Jersey cows and revealed no significant association. Komisarek et al., (2009) also reported the frequency of C allele as 0.73 and T allele as 0.27 respectively in Polish HF cows and revealed no relation of T allele and milk yield traits. Alim et al., (2012) also reported the frequency of C allele as 0.69 and T allele as 0.31 respectively in Chinese HF cows and revealed the relation of TT genotype with milk higher protein level. Basak et al., (2019) also reported the frequency of the C allele as 0.635 and T allele as 0.365, respectively, in Deoni cattle. Atila et al., (2014) also reported the frequency of C allele as 0.65 and T allele as 0.35 respectively in South Anatolian Red cattle. Atila et al., (2014) also reported the frequency of C allele as 0.80 and T allele as 0.20, respectively, in East Anatolian Red cattle. They revealed the relation of CC genotype with high milk fat%. Pasandideh et al., (2015) also reported the frequency of C alleles as 0.56 and T alleles as 0.44 respectively in Iranian Holstein cows. They revealed the relation of TT genotype with high-fat percentage and TC genotype was associated with milk protein.

PPARGC1AG1- NheI locus PCR-RFLP locus at 3'UTR region of PPARGC1A gene was polymorphic for SNP (C.3359 A>C) with frequency for the A alleles as 0.84 and allele B allele as 0.16 in 224 Gaolao cattle population; however, no significant differences were observed in milk traits between in all genotypes at PPARGC1A-NheI polymorphism. The comparison in PPARGC1AG4-SSCP Patterns revealed no significant differences in milk production traits. PPARGC1AG1- NheI PCR-RFLP genotype and PPARGC1AG4-SSCP pattern-based sequencing revealed SNPs in the PPARGC1A gene sequence in Gaolao cattle population. The identified genetic variation information at these loci in the PPARGC1A candidate gene of Gaolao cattle will aid in future studies for identification of significant associations for the development of markers for selection and improvement in milk production traits.

The authors duly acknowledge the financial support to the present work by the funding agency SERB-DST, New Delhi, under Core Research Grant Scheme (File No. EMR/2017/000323), to Dr. D.S. Kale, PI and Asstt. Professor at Deptt. of AGB, NVC, MAFSU, Nagpur. The help rendered from members of Gaolao Breeder’s Association and from State A.H. Deptt.; Dr. Pradnya Gulhane, Dr. Madhavi and Mr. Kheche, Mr. Lahulkar, Mr. Baghel, Mr. Chandankhede, Mr. Pravin Galhat and Mr. Prasanna Bamb in the survey, phenotyping and collection of blood and milk samples of Gaolao cattle from the breeding tract is duly acknowledged.