G.640T>C Polymorphism of the TGF-β2 Gene is Associated with Salmonella Pullorum Resistance in Indonesian Chickens

The objectives of this study were to identify polymorphism of transforming growth factor β2 (TGF-β2) gene associated with Salmonella pullorum resistance in Indonesian chickens. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assays were used to genotype Indonesian chickens. Analysis of polymorphism was conducted by using PopGen 3.2 software. The effect of genotype on S. pullorum resistance was analyzed using the SAS General Linear Model (GLM) procedure. Genotyping was performed on 278 chickens from 7 Indonesian chicken populations (Sentul, Merawang, Pelung, Kampung, Parent Cobb broiler, The F1 crossbreed of Kampung x Parent Cobb broiler (KB) and F2 KB x KB. The product of amplification was 284 bp. The TGF-β2| RsaI locus was polymorphic in all populations, producing two alleles (T and C) and three genotypes (TT, CT, and CC). The result from the analysis of the allele and genotype frequency showed that the T allele had a higher frequency than the C allele in all populations. The χ2 analysis showed that the 6 chicken populations were deviated from Hardy-Weinberg equilibrium, with the exception of the Parent Cobb broiler chicken. The association result showed that TT genotype was significantly associated with S. pullorum resistance in Sentul chicken. Although the leukocyte concentration, leukocyte differentiation and H/L ratio in Sentul chicken with three of TGF-β2 genotypes (TT, TC, and CC) were not statistically different. In conclusion, polymorphism in the TGF-β2 chicken gene can be used as a candidate marker to increase S. pullorum immune response.


Introduction
The pullorum disease also called bacillary white diarrhea (BWD), is caused by Salmonella pullorum bacteria. This disease is a severe septicemia disease that causes high morbidity and mortality in young birds, especially newly hatched chicks (Xie et al. 2017). In many developing countries, S. pullorum infection in poultry is common and pullorum disease remains a major disease threat in the poultry industry, causes severe economic losses (Guo et al. 2016). Therefore, there is a need for a method that protects poultry against S. pullorum infections such as molecular approach.
The molecular approach has provided a tool for studying the genetic composition of individuals. In the selection program, using molecular data can improve the accuracy of selection. (Dekkers and Hospital, 2002). This approach offers a substantial way to detect molecular markers using only candidate genes. One of the candidate genes that play an important role in increasing the immune response is transforming growth factor β gene (TGF-β). The TGF-β gene superfamily is composed of multifunctional cytokines that promote cell growth and extracellular matrix synthesis and mediate the immune response (Massague, 2012). The TGF-β gene is recognized not only as a growth factor but also immune modulation cytokines (Li et al. 2006) also affect the function and phenotype of lymphocytes, dendritic cells, and macrophages (Li et al. 2006;Tran, 2012;Chistiakov et al. 2015). From differentiation to activation and proliferation, T lymphocytes are affected by the TGFβ gene (Han et al. 2009).
The TGF-β gene superfamily contains four different isoforms (TGF-β1, TGF-β2, TGF-β3, and TGF-β4) and many other signaling proteins produced by all white blood cell lineages (Johnson and Newfeld, 2002;Huminiecki et al. 2009). The chicken TGF-β2 gene is located on chromosome 3 and is approximately 70 kb long with seven exons (Burt and Paton, 1991). Recently, a new single nucleotide polymorphism (SNP) has been identified in the TGF-β2 promoter region which has a positive effect on chicken growth (Tang et al. 2011). However, a few studies have also reported an association between this chicken TGF-β2 polymorphism and resistance to bacteria such as S. enteritidis (Kramer et al. 2003;Malek and Lamont 2003;Tohidi et al. 2012) and chicken antibody response (Zhou et al. 2002).
Therefore, based on these biological functions, the objective of the current experiment was to study associations of TGF-β2 gene polymorphisms with the resistance of Indonesian chickens to S. pullorum. This information can be used to recommend Single Nucleotide Polymorphisms (SNPs) as candidates for Marker Assisted Selection (MAS). These findings can be applied not only in the chicken selection strategy to obtain better performance but can relatively be used in related studies in other poultry.

Experimental animal
Samples collected from wing veins into EDTA tubes, blood samples were obtained from 278 chickens from 7 different populations: Sentul (n = 96), Merawang (n = 23), Pelung (n = 10), Kampung (n = 57), Parent Cobb broiler (n = 10), F1 crossbreed of Kampung x Parent Cobb broiler (KB; n = 30) and F2 KB x KB (n = 52). All chickens bred in the Animal Breeding and Genetics Division, Department of Animal Production and Technology, Faculty of Animal Science, Bogor Agricultural University (IPB), Indonesia. All chickens used in the current study were maintained according to the principle of animal welfare. The chicken was maintained and fed under the same conditions to minimize the effect of environment. For association analysis, in this study was associated with Sentul chicken.

DNA extraction
The DNA extraction protocol was modified from Sambrook and Russel (2001) with the following procedures: each 20 µL of chicken blood was added to 1000 µL of 0.2% NaCl and then homogenized and centrifuged (8000 rpm) for 5 min and the supernatant part was removed. The precipitate was added to 40 µL of 10% SDS, 10 µL proteinase-K (5 mg/mL) and 1 x STE up to 400 µL. Then, the mixture was slowly shaken in the incubator at 55 ° C for 2 h. Phenol solution (400 µL), CIAA (400 µL) and NaCl 5M (40 µL) were added to the mixture and slowly shaken at room temperature for 1 h. DNA molecules were separated from phenol using a centrifuge (12000 rpm) for 5 min. DNA phases were moved and added to 800 µL EtOH absolute and 40 µL NaCl 5M. Then, samples were frozen overnight. DNA molecules were centrifuged (12000 rpm) for 5 min and supernatant part was removed. DNA precipitate was air dried and dissolved in 100 µL 80% TE.

Amplification and genotyping of TGF-β2 gene
Polymerase chain reaction (PCR) was carried out using primers specific for a part of exon 1 (284 bp) of TGF-β2 gene (GenBank Accession No. X58071.1): forward 5'-GCC ATA GGT TCA GTG CAA G -3'; reverse 5' TGA CAG AAG CTC TCA AGC C -3'. PCR was carried out in a total reaction volume of 15 μL containing 0.5 μL of the genomic DNA template, 0.3 μL of each primer, 0.3 μL dNTPs, 1 μL MgCl2, 0.05 μL of Taq polymerase, 1.5 μL 10X reaction buffer, and 10.85 μL of distilled water. Amplification was performed with a GeneAmp® PCR 9700 System (Applied Biosystems, USA). The thermal cycling conditions consisted of predenaturation at 95 o C for 5 min, followed by 35 cycles of denaturation at 95 o C for 10 s, annealing at 60 o C for 20 s, and extension at 72 o C for 30 s; the final extension step was at 72 o C for 5 min. DNA amplification products and standard DNA ladder were separated on 1.5% agarose gels on 0.5X TBE buffer.
Genetic polymorphism of TGF-β2 gene was conducted by Restriction Fragment Length Polymorphism (RFLP) using a RsaI restriction enzyme, which recognizes and cleaves GT|AC sites. Primer annealing position and RsaI restriction site are shown in Figure 1.
Amplification products were visualized on a 2% agarose gel containing 2.5 μL ethidium bromide and 0.5X TBE buffer (1 M Tris-base, 0.9 M boric acid, 0.01 M EDTA pH 8.0) with a DNA ladder as a standard size comparison. For enzymatic digestion and determination of RFLPs, PCR products (5 μL) were mixed with 0.3 μL of RsaI, 1 μL distilled water, and 0.7 μL Tango buffer and then incubated at 37 oC for 16 h. The digestion products were separated by horizontal electrophoresis (100 V, 40 min) in 2.5 % agarose gel in 0.5X TBE and 2.5 μL ethidium bromide visualized on an ultraviolet transilluminator.

DNA Sequencing
Sequencing was performed for a different genotype of TGF-β2 gene in exon 1. Forward and reverse primer fragments were sequenced using sequencer machine (ABI Prims 3100-Avant Genetic Analyzer) in 1 st Base Selangor, Malaysia.

Heterozygosity
Polymorphism of population can be analyzed by using heterozygosity number. Observed heterozygosity (Ho) (Weir, 1996) and expected heterozygosity (He) (Nei and Kumar, 2000) were computed by using PopGene software version 3.2 and were tested by the following formula: Description: Ho = Observed heterozygosity nij = Number of heterozygous animals N = Number of observed animal He = Expected heterozygosity xi = Frequency of allele q = Total alleles

Concentration of Leukocytes
The concentrations of leukocytes were measured using counting chamber method (Fischbach and Marshall, 2008) as follows: 20 μL of chicken blood was dissolved in 380 μL of Turk solution (1 mL of 1% gentian violet in water, 1 mL glacial acetic acid, and 100 mL distilled water) using a micropipette. The total number of leukocytes present was calculated by counting all viable cells present on four areas located in four corners of the room count under a light microscope (100x magnification) and then multiplying by 50 to determine the concentration of each mm 3 .

Leukocyte Differentiation
The value of leukocyte differentiation was calculated using the Rapid method (Fischbach and Marshall, 2008) as follows: 5 μL of chicken blood was dropped on the object glass with a horizontal position and another object glass placed with an angle of 45 o . Object glass was air dried and fixed with methanol for 5 min. After that, the object glass was placed into 10% Giemsa for 30 min. Then, the object glass was washed with running water and dried air. The leukocyte differentiation was calculated by counting under a microscope (100x magnification).

Phagocytosis assay
The phagocytosis assay was modified from Wang et al. (2009) with the following procedures: (1) Macrophage cell preparation. Macrophages were taken from peritoneal fluid of chicken. Collect peritoneal fluid of chicken by injecting 5 mL of NaCl in peritoneal cavity by following a gentle massage of the abdomen. The number of macrophages in peritoneal fluid was calculated using Neubauer hemocytometer.
(2) Bacteria (Staphylococcus aureus) preparation and Phagocytosis assay. Peritoneal exudate cell suspension (as a source of macrophages) used for in vitro phagocytosis assays (Ulupi et al. 2014). Calculate percent phagocytosis by counting the number of 50 macrophages. The activity and capacity of macrophages are calculated by the following formula (Wibawan and Laemmler, 1994

Clearance Test
Immune traits were detected in blood samples using the clearance test (Jackson et al. 1998). This method is used to identify the normal growth of bacterial populations (S. pullorum) as compared to the specially treated population. The effect of treatment on bacterial growth was measured after incubation for 24-48 h at 35 ± 1 °C. Preparation of bacterial culture begins with the rejuvenation of culture on nutrient media at 36 ± 1 °C for 18-24 h and subculture on Brain Heart Broth media at 36 ± 1 °C for 18-24 h.

Data analysis
Determination of SNP (single nucleotide polymorphism) and alignment sequence were performed with Molecular Evolutionary Genetics Analysis 5 (MEGA5) (Tamura et al. 2011). The sequencing results were analyzed by BioEdit (Hall, 2011). The BLAST (Basic Local Alignment Search Tool) program was used to search the NCBI GenBank databases for reference and homologous sequences. Genotype frequency, allele frequency, heterozygosity and the Hardy-Weinberg Equilibrium (HWE) were analyzed using PopGen version 3.2 (Raymond and Rousset, 2001). Test of HWE was conducted with chi-square test (χ 2 ) (Kaps and Lamberson, 2004). The number of degrees of freedom (df) is equal to the number of possible genotypes minus the number of alleles (Allendorf et al. 2013). The association of TGF-β2| RsaI genotype with S. pullorum disease resistance was analyzed using the GLM procedure of SAS 9.1.3 software (SAS Institute, Cary, NC, USA). Duncan's multiple range test was used to identify significant differences between means. The genetic effects were analyzed using the following model: Yij = μ + Gi + eij where Yij is the observation on immune traits, μ is the overall mean, Gi is the effect of the single nucleotide polymorphism genotypes, and eij is the random residual effect.

Polymorphism of TGF-β2 gene
A total of 278 samples were successfully amplified and resulted in a 284 bp fragment of the partial TGF-β2 gene exon 1 through PCR ( Figure 2). The 284 bp fragment of exon 1 of the TGF-β2 gene was digested with RsaI restriction enzyme. The allele designated by T shows the pattern of 2 fragments (184 and 100 bp), and C allele shows only 1 fragment (284 bp). The two alleles produce three genotypes, TT, TC and CC (Figure 3). This SNP characterized by PCR-RFLP method was compatible with previous reports (Kramer et al. 2003;Malek and Lamont 2003;Tohidi et al. 2012). The calculated genotype and allele frequencies of Indonesian chickens TGF-β2 gene are shown in Table 1. The homozygous TT genotype was present in the highest frequency across all the population. The distribution of the TGF-β2| RsaI alleles of the exon 1 is characterized by a higher frequency of the T allele compared to the C allele in all Indonesian chickens population studied.
Indonesian chickens populations were polymorphic with two alleles found (T and C). Nei and Kumar (2000) and Allendroft et al. (2013) proposes that populations may be classified as polymorphic if there are more than one allele at the locus and if the most common allele frequencies are less than 0.99. The observed heterozygosity (Ho) number in Indonesian chickens was lower than the expected heterozygosity (He) number (Table 2). According to Allendroft et al. (2013), this result indicated that the occurrence of inbreeding is a result of intensive selection of TGF-β2 gene in Indonesian chickens. The χ 2 analysis showed that all chicken populations were deviated from Hardy-Weinberg equilibrium, with the exception of the Parent Cobb broiler chicken. Allendroft et al. (2013) explained that χ 2 is in Hardy-Weinberg equilibrium if the genetic variation, allele and genotype frequencies in a population remain constant from one generation to the next in the absence of disturbing factors.

Sequence Analysis of TGF-β2 Gene
Sequence analysis using forward and reverse primer revealed that PCR product of TGF-β2 gene exon 1 in this study was similar with the 284 bp in length based on previously reported by Tohidi et al. (2012). The results of sequence alignment compared with Gallus gallus (chicken) GenBank (accession number X58071.1) showed that a mutation occurred in exon 1 of TGF-β2 gene (Figure 4) that caused a lack of RsaI restriction site (GT|AC). Malek and Lamont (2003) reported that there was a T-C transition mutation found at position 640 bp in the exon 1 of chicken TGF-β2.
Transition mutation between thymine (T) base with cytosine (C) base in the chickens with CC genotype causing an alteration in RsaI restriction site sequences GT|AC became GC|AC so that the RsaI enzyme couldn't recognize its restriction site. IUPAC single-letter codes were used to facilitate the definition of nucleotide sequences, which are Y symbol for pyrimidine (C or T/U), R symbol for purine (A or G), W symbol for weak (A or T) and K symbol for G or T. This sequence analysis results confirmed that TGF-β2| RsaI locus in all Indonesian chicken population studied was polymorphic.

Concentration of leukocytes, Leukocytes differentiation, and H/L ratio
The concentration of leukocytes, leukocytes differentiation and H/L ratio in Sentul chickens with TT, TC, and CC genotypes were not statistically different ( Table  3). The concentration of leukocytes in chickens with TT, TC, and CC genotype were within the normal range 17-32 x 10 3 mm -3 (Davis et al. 2008). These results indicate that the Sentul chicken with the third TGF-β2 genotype was not infected with the bacterium. Muhsinin et al. (2016) reported values of leukocyte differentiation are Sentul chicken is heterophile (45.80%), lymphocytes (51.55%) and monocytes (1.89%). Whereas Nurfaizin et al. (2014) have reported values for leukocyte differentiation in broiler chickens based on the density of the cage that is heterophile (27.57%), lymphocytes (56.44%) and monocytes (13.56%). The ratio of heterophils and lymphocytes (H/L) is used by ornithologists as a tool to monitor immune function in birds (Davis et al. 2008). In chicken, heterophils and monocytes are capable of phagocytosis. In acute inflammatory responses to infectious as well as non-infectious causes, heterophils are one of the first phagocytes to accumulate in the affected tissue (Potter et al. 2016).

Association of TGF-β2 gene polymorphisms with S. pullorum
The analysis of the association between the TGF-β2 gene genotype with S. aureus and S. pullorum in Sentul chicken is shown in Table 4 and Table 5. Chicken with TT genotype showed higher resistant to S. aureus and S. pullorum (p<0.05) compared to that of the TC and CC genotypes.  In the previous study, the use of SNP of innate immune genes, such as NRAMP1 (Beaumont et al. 2003;Muhsinin et al. 2016), TLR4 (Li et al. 2010), MyD88 (Liu et al. 2015), CD28, and MD-2 (Malek et al. 2004), leads to enhancement of S. pullorum resistance in chicken. Tohidi et al. (2012) reported that the single nucleotide polymorphism (SNP) within the same region in TGF-β2 gene maintained a significant association with resistant to salmonellosis in Malaysian indigenous chicken. The allele T in the study by Tohidi et al. (2012) showed a positive effect on immune traits.
Through the analysis, the polymorphisms of the TGF-β2 gene and the correlation with resistance to S. pullorum suggested that TGF-β2 gene may be one of the S. pullorum resistant genes in the innate immune system.

Conclusions
Indonesian chickens are polymorphic in the TGF-β2│ RsaI locus. The T allele frequency is higher in all populations. The TT genotypes in Sentul chicken having positive effects on the resistant to S. pullorum could be considered for selection strategies of the birds in the population.