Polymorphisms of ACACB Gene and Their Association with Milk Quality Traits in Yak

doi:10.21203/rs.3.rs-3893649/v1

Acetyl-CoA carboxylase beta (ACACB) is a rate-limiting enzyme involved in lipid syn-thesis and fatty acid oxidation. The results of our previous study showed that a total of seven SNPs were detected in the exon 37-intron 37, exon 46-intron 46, and intron 47 regions of the yak ACACB, and mutations in the ACACB were found to affect yak meat quality traits. However, the genetic effects of ACACB on yak milk quality traits have not been reported. Therefore, the aim of this study was to investigate the effects of ACACB polymorphisms on yak milk quality traits in Gannan yaks. In this study, A total of 202 Gannan yaks were included in the study. Analyze the different geno-types, diplotypes, and the presence or absence of haplotypes on milk quality. The seven SNPs were named as exon 37-intron 37 (exon 37: SNP1, intron 37: SNP2 and SNP3), exon 46-intron 46 (exon 46: SNP4, intron 46: SNP5), and intron 47 (SNP6 and SNP7). Apart from the SNP1, SNP2, SNP5, and SNP6 loci where the polymorphic information content (PIC) was low (PIC ≤ 0.25), the SNP3, SNP4, and SNP7 loci were all of intermediate polymorphic information status (0.25 < PIC < 0.5). The highest frequency of heterozygosity occurred at the SNP7 locus, and the two alleles were evenly distributed in the population compared to alleles at the other loci. There were no strong linkages between the SNPs (r²<0.33) except for a strong linkage disequilibrium observed between SNP1 and SNP2 (r²=0.89). Seven effective haplotypes and seven diplotypes were constructed for the Gannan yak ACACB gene. Correlation analysis showed that SNP1 and SNP7 were associated with lactose content (P<0.05), while SNP3 was significantly associated with the protein and monounsaturated fatty acid contents in the milk (P<0.05). SNP4 was significantly associated with both saturated and monounsaturated fatty acid contents (P<0.05 and P<0.01, respectively), while SNPs 5 and 7 were significantly correlated with the fat percentage (P<0.05) and SNP6 was significantly correlated with total solid content of the milk (P<0.05). Yaks with the H2H2 diplotype had significantly higher levels of milk fat than other diplotypes (P<0.05) while milk fat contents in animals carrying hap-lotype H2 were significantly higher than that in yaks carrying the deletion type (P<0.05). The findings of the present study suggest that polymorphisms in the yak ACACB affect milk quality and can be used as genetic markers for enhancing milk quality in yak populations. The findings provide a theoretical basis for the genetic characterization of milk quality traits in the Gannan yak.

Biological sciences/Biological techniques

Biological sciences/Genetics

Biological sciences/Molecular biology

The yak, Bos grunniens, is the largest ruminant unique to the Tibetan Plateau and its neighboring high-altitude regions, where it can survive in the harsh environmental conditions, including low oxygen levels¹. The yak provides products such as meat, milk, wool, and fleece, as well as animal power, fuel, and transportation, for local herders² and is thus an indispensable livestock species in the local economy. Yak milk is thick, sweet, and rich in nutrients, and is known as "natural concentrated milk". The milk also contains higher levels of dry matter, protein, fatty acids, minerals, and other nutrients than cow’s milk, and yak milk is also rich in vitamins A and C, has significant antioxidant properties, and is one of the best raw milks for the processing of cream products³. Yak milk is rich in protein, with a protein fraction of 5.32%⁴ and enhances the gastrointestinal immune function, absorption of calcium and phosphorus absorption, and has significant potential for the development of infant milk products⁵. It is known that milk production in mammals such as cows is affected by factors such as the genetics, breed, and nutritional level of the animal, as well as the calving litter size, calving age, and lactation season. Genetic studies of milk production have mainly focused on improving the yield and protein and fat contents of the mill. Milk fat is mainly composed of triglycerides and small amounts of cholesterol, diglycerides, monoglycerides, and free fatty acids, mostly short-chain saturated fatty acids (SFAs) together with phospholipids, sterols, pigments, and fat-soluble vitamins, all of which are easy for the body to digest and absorb. Furthermore, milk fat has an aromatic odor and is an important source of flavor in dairy products. Therefore, the percentage of milk represents a key indicator of the nutritional value of the milk, and reflects the production performance of dairy cows with economic consequences. In this study, we analyzed candidate genes associated with milk fat traits in the yak and investigated the effects of genetic mutation on milk quality.

Genes associated with milk fats are mostly associated with fatty acid and triglyceride synthesis. Lactation is regulated by multiple genes. For example, polymorphisms in exon 1 G>C and exon 34 A>G of the fatty acid synthase FASN gene are associated with milk fat content in Chinese Holstein cows⁶. While polymorphisms in signal transducer and activator of transcription 5A (STAT5A) influence both milk yield and fat percentage⁷ and polymorphisms in fatty acid-binding protein 3 (FABP3) were found to be significantly correlated with milk fat traits in Mehsana buffaloes⁸. Acetyl-coenzyme A carboxylase (ACC) was discovered in the late 1950s by Salih et al. It is a biotin-dependent carboxylase, belonging to the intermolecular carboxylation transfer family, which catalyzes the carboxylation of acetyl-coenzyme A to malonyl-monoacyl-coenzyme A during fatty acid synthesis and metabolism. ACC consists of two isomers, α and β, and plays a major regulatory role in the regulation of fatty acid metabolism^9,10. Acetyl-CoA carboxylase beta is encoded by the acetyl-CoA carboxylase beta gene (ACACB). The protein is localized outside the mitochondria and regulates the activity of carnitine palmitoyltransferase1 (CPT-1), preventing the transport of fatty acids into the mitochondria for fatty acid beta-oxidation¹¹. It is a rate-limiting enzyme that promotes lipid synthesis and plays a key regulatory role in lipid metabolism. Studies have shown that the ACACB gene is located in a quantitative trait locus (QTL) region known to significantly influence fat yield^12,13. Much of the current research on ACACB has focused on diseases such as cancer and obesity in humans and mice. The ACACB protein is abundantly expressed in skeletal and cardiac muscle^14-17, as well as in the liver, and is also found in mammalian brown adipose tissue, mammary glands, and pancreatic islets^11,17. Common polymorphisms in ACACB are associated with diseases such as obesity. Harwood et al. found that persistent fatty acid oxidation in adipocytes in ACACB -knockout mice protects against obesity and diabetes and is accompanied by reductions in abdominal fat stores^18,19. Han et al. showed that single nucleotide polymorphisms (SNPs) in ACACB in Chinese Holstein cows were significantly correlated with the overall yield, fat yield, fat percentage, protein yield, and protein percentage in the milk²⁰.

Currently, genetic breeding is an important initiative to improve milk production in yaks. However, most studies on ACACB have focused on its role in cancer and obesity-related diseases, with only a few studies focusing on animal production traits. In the present study, polymorphisms in the key ACACB gene were investigated in a population of Gannan yaks, with the aim of assessing the effects of ACACB genetic variation and its haplotypes on milk quality traits, and provide a theoretical basis for genetic breeding to enhance the butterfat content of the milk to improve the quality of milk-based products.

1. ACACB PCR Products

As shown by analysis of 1.5% agarose gels (Figure 1) it can be seen that the amplification products in the lanes are clear and bright with good specificity. Three bands at 455 bp, 362 bp, and 790 bp were observed.

2. Genetic Characterization of SNPs in ACACB

The results of our previous study showed that seven SNPs were detected in three regions of ACACB and each SNP had three genotypes²¹.

The results of the genotype frequency, allele frequency, and population genetic polymorphism analyses of the SNPs are shown in Table 1. The dominant genotypes of the SNP1, SNP2, SNP3, SNP4, SNP5, SNP6, and SNP7 loci were GG, CC, GC, CC, CC, GG, and GA, respectively; the PIC contents were all of moderate polymorphic information status (0.25<PIC<0.5), and the SNP1, SNP2, SNP5, and SNP6 loci showed low polymorphism (PIC≤0.25), indicating that the three SNP loci, SNP3, SNP4, and SNP7, had high genetic variance and strong selection potentials. The heterozygosity results showed the highest frequency at the SNP7 locus, and the number of effective alleles showed that the two alleles at the SNP7 locus were evenly distributed in the population compared with those at the other loci.

Table 1. Analysis of genetic polymorphism in yak ACACB.

SNPs	Genotype Frequency/%			Allele Frequency/%		PIC	He	Ho	Ne
SNP1	AA（6） 2.97	GA（30） 14.85	GG（166） 82.18	A 10.40	G 89.61	0.1690	0.1863	0.8137	1.2290
SNP2	AA（2） 0.99	CA（34）16.83	CC（166） 82.18	A 9.41	C 90.60	0.1559	0.1704	0.8296	1.2054
SNP3	CC（71） 35.15	GC（91） 45.05	GG（40） 19.80	C 57.68	G 42.32	0.3690	0.4882	0.5118	1.9540
SNP4	CC（129） 63.86	CT（63） 31.19	TT（10） 4.95	C 79.46	T 20.54	0.2732	0.3265	0.6735	1.4847
SNP5	CC（149） 73.76	CT（49） 24.26	TT（4） 1.98	C 85.89	T 24.11	0.2130	0.2424	0.7576	1.3199
SNP6	AA（6） 2.97	GA（57） 28.22	GG（139） 68.81	A 17.08	G 82.92	0.2431	0.2832	0.7168	1.3952
SNP7	AA（46） 22.77	GA（97） 48.02	GG（59） 29.21	A 46.78	G 53.22	0.3740	0.4979	0.5021	1.9918

3. Linkage Disequilibrium and Haplotype Analysis of SNPs

The results of the linkage disequilibrium analysis of the loci of the seven SNPs in ACACB are shown in Figure 2. Strong linkage disequilibrium was seen between SNP1 and SNP2 (r²=0.89), while no strong linkage was observed between the other SNPs (r²<0.33). The results of haplotype analysis are shown in Table 2; excluding haplotypes with frequencies lower than 3% in the Gannan yak population, a total of seven haplotypes with frequencies greater than 3% were detected, of which, haplotype H2 had the highest frequency of 29.20%, followed by 19.50% for H3, and 14.60% for H4, while H1, H5, H6, and H7 had lower frequencies of 7.10%, 9.40%, 3.40% and 3.90% respectively. A total of 28 diplotypes were found for the seven haplotypes. After exclusion of diplotypes with frequencies lower than 5%, seven were identified, namely, H1H2, H2H2, H2H3, H2H4, H2H5, H3H3, and H3H4, with the frequencies of 5.23, 14.38, 9.15, 11.76, 7.19, 6.54, and 9.15%, respectively.

The values of r²represent coefficient of LD between two sites, r² > 0.33 indicates a strong LD between sites.

Table 2. Haplotype analysis of ACACB mutation sites in yak.

Haplotype	Mutation site							Frequency/%	diplotypes	Frequency/%
Haplotype	SNP1	SNP2	SNP3	SNP4	SNP5	SNP6	SNP7	Frequency/%	diplotypes	Frequency/%
H1	G	C	G	C	T	G	A	7.10	H1H2	5.23
H2	G	C	C	C	C	G	G	29.20	H2H2	14.38
H3	G	C	C	T	C	G	A	19.50	H2H3	9.15
H4	G	C	G	C	C	A	G	14.60	H2H4	11.76
H5	A	A	G	C	C	G	A	9.40	H2H5	7.19
H6	G	C	G	C	C	G	G	3.40	H3H3	6.54
H7	G	C	G	C	C	G	A	3.90	H3H4	9.15

4. Analysis of the Correlation between ACACB Genotype and Milk Quality traits in Gannan Yak

The association analysis of ACACB genotypes with milk quality traits in Gannan yaks is shown in Table 3. The results indicate that the lactose contents of milk from individual yaks of the AA genotype at the SNP1 locus were significantly higher than those present in the GG genotype (P<0.05). The milk protein contents in yaks with the GC genotype at the SNP3 locus were significantly higher than those with the GG genotype (P<0.05), while the levels of milk fat associated with the CC genotype at the SNP5 locus were markedly greater than those of the TT genotype (P<0.05). The total solid contents in the milk from individual yaks of the GG genotype at the SNP6 locus were significantly greater than those of the GA genotype (P<0.05), while the milk fat levels in yaks of the GG genotype at the SNP7 locus were markedly increased in comparison with yaks of the GA genotype and lactose levels in yaks with the AA genotype were significantly higher than those with the and the GG genotype (P<0.05). There was no significant correlation between the genotypes of the SNP2 and SNP4 loci and milk quality traits (P>0.05).

The results indicated that the genotypes at the SNP loci in the ACACB gene were significantly associated with milk quality traits, suggesting their potential use as genetic markers for milk quality improvement in Gannan yaks.

Table 3. Correlations between ACACB genotypes and milk quality traits in Gannan yak.

SNPs	Genetypes	Milk quality
SNPs	Genetypes	No.	Protein rate/%	P-value	Fat rate/%	P-value	Lactose rate/%	P-value	Total solids/%	P-value	Non-fat solids/%	P-value
SNP1	AA	6	4.94±0.34	0.923	5.08±0.67	0.880	5.27±0.20^a	0.043	16.44±1.18	0.688	11.46±0.55	0.924
	GA	30	5.07±0.17		4.82±0.33		4.92±0.10^ab		16.44±0.59		11.37±0.27
	GG	166	5.02±0.10		4.97±0.20		4.82±0.06^b		16.00±0.35		11.29±0.16
SNP2	AA	2	4.80±0.58	0.896	5.86±1.12	0.612	5.18±0.33	0.213	17.16±2.00	0.641	11.22±0.93	0.921
	CA	34	5.06±0.16		4.81±0.32		4.93±0.09		16.40±0.56		11.39±0.26
	CC	166	5.02±0.10		4.97±0.20		4.81±0.06		16.00±0.35		11.29±0.16
SNP3	CC	71	4.98±0.13^ab	0.047	5.15±0.25	0.326	4.82±0.08	0.173	16.47±0.45	0.191	11.27±0.21	0.247
	GC	91	5.17±0.12^a		4.79±0.23		4.78±0.07		16.11±0.40		11.46±0.19
	GG	40	4.81±0.15^b		5.02±0.25		4.94±0.08		15.50±0.51		11.06±0.23
SNP4	CC	129	5.02±0.11	0.424	5.00±0.21	0.584	4.83±0.06	0.066	16.19±0.37	0.552	11.30±0.17	0.306
	CT	63	5.00±0.13		4.90±0.26		4.74±0.08		15.73±0.46		11.24±0.21
	TT	10	5.35±0.27		4.49±0.52		5.10±0.15		16.23±0.93		11.91±0.43
SNP5	CC	149	5.09±0.11	0.263	5.13±0.21^a	0.045	4.81±0.06	0.870	16.23±0.37	0.212	11.39±0.17	0.448
	CT	49	4.97±0.15		4.79±0.28^ab		4.79±0.09		16.21±0.51		11.19±0.23
	TT	4	4.48±0.41		3.36±0.78^b		4.91±0.23		13.67±1.40		10.76±0.65
SNP6	AA	6	5.00±0.11	0.212	5.71±0.67	0.492	4.78±0.20	0.353	16.19±0.38^ab	0.042	11.13±0.54	0.207
	GA	57	4.88±0.13		4.91±0.25		4.75±0.08		15.34±0.44^b		11.09±0.21
	GG	139	5.11±0.11		4.94±0.21		4.85±0.06		16.45±0.38^a		11.44±0.17
SNP7	AA	46	5.04±0.14	0.383	4.74±0.27^bc	0.040	4.93±0.08^a	0.040	16.08±0.49	0.792	11.43±0.23	0.433
	GA	97	4.95±0.12		4.81±0.22^b		4.82±0.07^ab		15.94±0.40		11.18±0.19
	GG	59	5.14±0.13		5.39±0.26^a		4.70±0.08^b		16.26±0.46		11.41±0.21

Data are shown as Mean ± SE; different lowercase letters in the same column indicate significant differences (P<0.05).

5. Effects of ACACB Genotype on Different Fatty acid Contents

The effects of ACACB genotypes of Gannan yak on the contents of different kinds of fatty acids are shown in Tables 4-8. The results showed that different genotypes at different SNP loci affected the levels of various types of fatty acids. Specifically, the C20:3n8C contents in individual yaks of the AA genotype at the SNP1 locus were significantly higher than that of the GG and GA genotypes (P<0.05), and the C11:0, C18:0, and C20:3n8C contents in yaks with the AA genotype at the SNP2 locus was significantly greater than those of the CC and CA genotypes (P<0.05 and P<0.01, respectively). C11:0, C18:0, and C20:3n8C were also markedly increased compared with the CC and CA genotypes (P<0.05 and P<0.01, respectively) while C14:0 and C16:0 were significantly higher in yaks with the GC genotype compared with the CC genotype at the SNP3 locus (P<0.05), and C23:0 was significantly higher than in the GG genotype in yak individuals of both GC and CC genotypes (P<0.05). In terms of monounsaturated fatty acids (MUFAs), the MUFA levels were significantly higher in the CC genotype compared with the GC and GG genotypes (P=0.05) while the C10:0, C14:0, C16:0, and SFA contents in SNP4 locus/CC and CT genotype yak individuals were significantly greater than those of the TT genotype (P<0.05, P<0.01) and the TT genotype was associated with markedly higher (P<0.05, P<0.01) levels of C17:1C, C18:1C, C18:3n6, and MUFA than the CC and CT genotypes. The SNP5 locus/CT genotype yak individuals had significantly (P<0.05) higher levels of C16:0 and C18:0 than those with the CC and TT genotypes, while genotypes associated with the SNP6 and SNP7 loci showed no significant associations with the levels of different types of fatty acids (P>0.05).

The results indicated that the genotypes at the SNP loci of the Gannan yak ACACB gene that were significantly or highly significantly associated with the contents of different types of fatty acids could be used as markers for the improvement of the fatty acid contents of Gannan yak milk.

Table 4. Correlations between ACACB genotypes and contents of different fatty acids in Gannan yak.

SNPs	Genetypes	Fatty acid (%)
SNPs	Genetypes	No.	C4:0	P	C6:0	P	C8:0	P	C10:0	P	C11:0	P	C12:0	P	C13:0	P	C14:0	P	C14:1C	P
SNP1	AA	6	1.24±0.22	0.611	1.86±0.34	0.390	1.08±0.22	0.529	2.02±0.33	0.623	0.39±0.18	0.606	1.48±0.26	0.870	0.28±0.07	0.682	7.31±0.76	0.709	0.67±0.17	0.443
	GA	30	1.41±0.11		2.34±0.17		1.33±0.11		2.36±0.17		0.21±0.09		1.63±0.13		0.23±0.04		7.96±0.38		0.60±0.09
	GG	166	1.32±0.07		2.20±0.10		1.27±0.06		2.29±0.10		0.21±0.05		1.62±0.08		0.22±0.02		7.88±0.23		0.52±0.05
SNP2	AA	2	0.99±0.37	0.433	1.22±0.57	0.157	0.64±0.36	0.168	1.11±0.56	0.083	1.03±0.30^a	0.026	1.05±0.44	0.432	0.12±0.12	0.535	5.35±1.27	0.122	0.53±0.29	0.451
	CA	34	1.41±0.10		2.32±0.16		1.33±0.10		2.37±0.16		0.20±0.09^b		1.63±0.13		0.24±0.03		7.99±0.36		0.62±0.08
	CC	166	1.32±0.07		2.20±0.10		1.27±0.06		2.29±0.10		0.22±0.05^b		1.61±0.08		0.22±0.02		7.87±0.22		0.52±0.05
SNP3	CC	71	1.29±0.08	0.686	2.06±0.13	0.125	1.22±0.08	0.193	2.18±0.13	0.323	0.28±0.07	0.147	1.64±0.10	0.906	0.20±0.03	0.249	7.41±0.28^b	0.010	0.48±0.07	0.059
	GC	91	1.36±0.08		2.32±0.12		1.35±0.07		2.37±0.11		0.15±0.06		1.61±0.09		0.22±0.02		8.25±0.25^a		0.61±0.06
	GG	40	1.33±0.10		2.21±0.15		1.22±0.09		2.29±0.14		0.26±0.08		1.58±0.11		0.26±0.03		7.73±0.32^ab		0.46±0.07
SNP4	CC	129	1.35±0.07	0.315	2.26±0.11	0.136	1.30±0.07	0.219	2.34±0.10^a	0.043	0.22±0.06	0.430	1.65±0.08	0.368	0.24±0.02	0.387	7.94±0.23^a	0.000	0.53±0.05	0.682
	CT	63	1.31±0.09		2.16±0.13		1.26±0.08		2.25±0.13^a		0.20±0.07		1.57±0.10		0.20±0.03		8.03±0.28^a		0.56±0.07
	TT	10	1.10±0.17		1.75±0.27		1.01±0.17		1.71±0.26^b		0.39±0.14		1.39±0.21		0.20±0.06		5.54±0.57^b		0.44±0.14
SNP5	CC	149	1.24±0.22	0.060	2.17±0.11	0.183	1.26±0.07	0.428	2.25±0.10	0.439	0.24±0.06	0.293	1.60±0.08	0.487	0.22±0.02	0.977	7.78±0.23	0.055	0.55±0.05	0.376
	CT	49	1.41±0.11		2.13±0.15		1.24±0.09		2.36±0.14		0.14±0.08		1.55±0.11		0.23±0.03		8.45±0.32		0.57±0.07
	TT	4	1.32±0.07		2.93±0.40		1.60±0.25		2.65±0.39		0.14±0.22		1.94±0.31		0.22±0.09		7.29±0.89		0.27±0.20
SNP6	AA	6	1.41±0.22	0.556	2.55±0.34	0.356	1.05±0.22	0.517	2.24±0.33	0.692	0.38±0.18	0.658	1.59±0.26	0.577	0.30±0.07	0.413	7.61±0.76	0.890	0.53±0.17	0.949
	GA	57	1.27±0.08		2.11±0.13		1.27±0.08		2.23±0.13		0.21±0.07		1.55±0.10		0.23±0.03		7.95±0.29		0.55±0.07
	GG	139	1.36±0.07		2.25±0.11		1.29±0.07		2.33±0.11		0.21±0.06		1.65±0.08		0.22±0.02		7.85±0.24		0.53±0.06
SNP7	AA	46	1.24±0.09	0.367	2.04±0.14	0.221	1.20±0.09	0.297	2.15±0.14	0.238	0.28±0.08	0.406	1.48±0.11	0.143	0.23±0.03	0.497	7.37±0.31	0.061	0.53±0.07	0.997
	GA	97	1.37±0.07		2.28±0.12		1.33±0.07		2.39±0.11		0.18±0.06		1.70±0.09		0.21±0.02		8.12±0.25		0.54±0.06
	GG	59	1.35±0.09		2.25±0.13		1.24±0.08		2.26±0.13		0.24±0.07		1.59±0.10		0.24±0.03		7.90±0.29		0.53±0.07

Data in shown as “Mean ± SE”; Data in the same column with different lowercase letters on the shoulders indicate significant differences (P<0.05).

Table 5. Correlations between ACACB genotypes and contents of different fatty acids in Gannan yak.

SNPs	Genetypes	Fatty acid (%)
SNPs	Genetypes	No.	C15:0	P	C15:1C	P	C16:0	P	C16:1C	P	C17:0	P	C17:1C	P	C18:0	P	C18:1T	P	C18:1C	P
SNP1	AA	6	0.90±0.26	0.667	0.33±0.13	0.683	28.85±2.92	0.731	0.62±0.23	0.206	0.89±0.18	0.316	0.28±0.51	0.793	24.82±2.55	0.308	1.75±0.59	0.584	17.50±3.12	0.321
	GA	30	1.03±0.13		0.21±0.07		31.01±1.46		0.87±0.12		0.99±0.09		0.46±0.25		23.72±1.27		1.11±0.29		15.79±1.55
	GG	166	1.09±0.08		1.09±0.08		30.18±0.87		0.98±0.07		0.86±0.05		0.56±0.15		22.27±0.76		1.20±0.18		17.99±0.93
SNP2	AA	2	0.11±0.44	0.080	0.37±0.22	0.779	23.26±4.92	0.277	0.30±0.40	0.130	0.92±0.30	0.356	0.18±0.86	0.800	38.40±4.17^a	0.001	0.69±1.00	0.864	15.39±5.28	0.364
	CA	34	1.06±0.12		0.22±0.06		31.06±1.39		0.86±0.11		0.97±0.08		0.46±0.24		23.11±1.18^b		1.24±0.28		16.10±1.49
	CC	166	1.09±0.08		0.21±0.04		30.16±0.87		0.98±0.07		0.86±0.05		0.56±0.15		22.32±0.74^b		1.19±0.18		17.98±0.93
SNP3	CC	71	1.07±0.10	0.868	0.22±0.05	0.998	28.25±1.10^b	0.018	0.94±0.09	0.192	0.87±0.07	0.845	0.83±0.19	0.070	23.36±0.97	0.400	1.26±0.23	0.887	19.11±1.19	0.180
	GC	91	1.07±0.09		0.22±0.05		30.89±0.98^a		1.03±0.08		0.87±0.06		0.45±0.17		22.28±0.87		1.15±0.20		17.03±1.07
	GG	40	1.13±0.11		0.21±0.06		31.54±1.24^a		0.84±0.10		0.91±0.07		0.36±0.22		21.92±1.10		1.20±0.26		17.22±1.34
SNP4	CC	129	1.12±0.08	0.518	0.21±0.04	0.674	30.50±0.89^a	0.025	0.97±0.07	0.822	0.88±0.05	0.093	0.46±0.16^b	0.024	22.40±0.80	0.630	1.21±0.18	0.988	17.28±0.93^b	0.000
	CT	63	1.02±0.10		0.23±0.05		30.43±1.11^a		0.95±0.09		0.85±0.07		0.63±0.19^b		22.95±0.99		1.18±0.23		17.44±1.16^b
	TT	10	0.98±0.21		0.29±0.11		24.46±2.27^b		0.85±0.19		1.15±0.14		1.49±0.39^a		21.11±2.02		1.22±0.47		27.53±2.36^a
SNP5	CC	149	1.05±0.08	0.565	0.22±0.04	0.938	29.58±0.90^b	0.038	0.99±0.07	0.445	0.87±0.06	0.242	0.61±0.16	0.244	23.13±0.79^a	0.046	1.08±0.18	0.175	17.89±0.98	0.794
	CT	49	1.11±0.11		0.20±0.06		32.44±1.24^a		0.90±0.10		0.81±0.08		0.28±0.22		20.76±1.09^b		1.26±0.25		17.74±1.35
	TT	4	1.36±0.31		0.24±0.16		31.44±3.42^ab		0.74±0.28		1.18±0.21		0.61±0.60		20.81±2.99^b		2.34±0.70		15.28±3.72
SNP6	AA	6	0.88±0.26	0.625	0.21±0.13	0.870	29.00±2.93	0.594	0.64±0.24	0.221	0.83±0.18	0.824	0.61±0.51	0.775	24.07±2.56	0.654	0.98±0.59	0.218	16.63±3.15	0.927
	GA	57	1.13±0.10		0.23±0.05		30.97±1.11		1.03±0.09		0.86±0.07		0.45±0.19		22.03±0.97		0.97±0.22		17.87±1.20
	GG	139	1.07±0.08		0.21±0.04		29.94±0.94		0.93±0.08		0.89±0.06		0.59±0.16		22.70±0.82		1.34±0.19		17.65±1.01
SNP7	AA	46	1.03±0.11	0.821	0.24±0.06	0.551	29.81±1.22	0.816	0.90±0.09	0.284	0.97±0.07	0.109	0.62±0.21	0.831	22.28±1.06	0.533	1.37±0.25	0.606	19.21±1.29	0.086
	GA	97	1.10±0.09		0.23±0.05		30.57±0.99		0.93±0.08		0.88±0.06		0.54±0.17		22.99±0.87		1.16±0.20		16.52±1.05
	GG	59	1.09±0.10		0.18±0.05		30.13±1.15		1.05±0.09		0.80±0.07		0.48±0.20		21.91±1.00		1.12±0.23		18.37±1.22

Data in shown as “Mean ± SE”; Data in the same column with different lowercase letters on the shoulders indicate significant differences (P<0.05).

Table 6. Correlations between ACACB genotypes and contents of different fatty acids in Gannan yak.

SNPs	Genetypes	Fatty acid (%)
SNPs	Genetypes	No.	C18:2T	P	C18:2C	P	C20:0	P	C18:3n6	P	C20:1C	P	C18:3n9	P	C21:0	P	C20:2C	P	C22:0	P
SNP1	AA	6	0.64±0.18	0.815	1.17±0.26	0.844	0.56±0.10	0.565	0.41±0.20	0.380	0.98±0.35	0.524	0.83±0.31	0.832	1.21±0.35	0.926	0.23±0.10	0.579	0.27±0.14	0.647
	GA	30	0.58±0.09		1.20±0.13		0.61±0.05		0.13±0.10		0.68±0.18		1.03±0.15		1.15±0.18		0.23±0.05		0.14±0.07
	GG	166	0.54±0.06		1.26±0.08		0.55±0.03		0.23±0.06		0.86±0.11		1.00±0.09		1.21±0.11		0.28±0.03		0.19±0.04
SNP2	AA	2	0.86±0.31	0.568	0.75±0.44	0.492	0.60±0.17	0.608	0.41±0.35	0.683	0.80±0.60	0.706	0.31±0.52	0.399	0.90±0.60	0.524	0.30±0.18	0.537	0.53±0.24	0.262
	CA	34	0.57±0.09		1.22±0.12		0.60±0.05		0.17±0.10		0.73±0.17		1.03±0.15		1.17±0.17		0.23±0.05		0.14±0.07
	CC	166	0.54±0.06		1.25±0.08		0.55±0.03		0.23±0.06		0.80±0.60		1.00±0.09		1.21±0.11		0.28±0.03		0.19±0.43
SNP3	CC	71	0.52±0.07	0.747	1.29±0.11	0.561	0.54±0.04	0.676	0.26±0.08	0.525	0.97±0.13	0.068	1.02±0.12	0.327	1.15±0.13	0.287	0.31±0.04	0.356	0.24±0.06	0.137
	GC	91	0.57±0.06		1.20±0.09		0.57±0.04		0.18±0.07		0.88±0.12		0.92±0.11		1.14±0.12		0.27±0.04		0.14±0.05
	GG	40	0.54±0.08		1.29±0.10		0.57±0.04		0.24±0.09		0.59±0.15		1.12±0.13		1.38±0.15		0.24±0.05		0.22±0.06
SNP4	CC	129	0.53±0.06	0.441	1.30±0.04	0.154	0.57±0.03	0.817	0.21±0.06^b	0.043	0.77±0.11	0.074	1.05±0.10	0.252	1.27±0.11	0.284	0.28±0.03	0.782	0.18±0.05	0.919
	CT	63	0.58±0.07		1.15±0.10		0.55±0.04		0.19±0.08^b		0.93±0.14		0.90±0.12		1.07±0.14		0.27±0.04		0.19±0.06
	TT	10	0.68±0.14		1.02±0.20		0.55±0.08		0.59±0.16^a		1.35±0.28		0.78±0.24		1.11±0.28		0.22±0.08		0.23±0.11
SNP5	CC	149	0.55±0.06	0.243	1.23±0.08	0.836	0.55±0.03	0.296	0.22±0.06	0.825	0.88±0.11	0.600	0.99±0.10	0.909	1.18±0.11	0.742	0.29±0.03	0.173	0.21±0.05	0.189
	CT	49	0.47±0.08		1.27±0.11		0.54±0.04		0.18±0.09		0.76±0.15		1.00±0.13		1.29±0.15		0.22±0.04		0.11±0.06
	TT	4	0.83±0.22		1.37±0.31		0.74±0.12		0.32±0.24		0.62±0.42		1.15±0.37		1.20±0.42		0.19±0.12		0.16±0.17
SNP6	AA	6	0.61±0.18	0.580	1.03±0.26	0.677	0.58±0.10	0.964	0.33±0.21	0.849	0.42±0.35	0.413	1.24±0.31	0.722	1.60±0.35	0.503	0.28±0.11	0.994	0.35±0.15	0.514
	GA	57	0.59±0.07		1.25±0.10		0.56±0.04		0.22±0.08		0.90±0.14		0.98±0.12		1.17±0.13		0.27±0.04		0.18±0.06
	GG	139	0.61±0.18		1.25±0.08		0.56±0.03		0.21±0.07		0.83±0.11		1.24±0.31		1.20±0.11		0.27±0.03		0.19±0.05
SNP7	AA	46	0.61±0.08	0.585	1.17±0.11	0.606	0.56±0.04	0.888	0.29±0.09	0.449	0.81±0.15	0.633	0.92±0.13	0.607	1.18±0.15	0.875	0.24±0.04	0.445	0.21±0.06	0.669
	GA	97	0.54±0.06		1.26±0.09		0.57±0.04		0.18±0.07		0.89±0.12		1.01±0.11		1.19±0.12		0.29±0.04		0.17±0.05
	GG	59	0.52±0.07		1.29±0.10		0.55±0.04		0.21±0.08		0.77±0.14		1.06±0.12		1.25±0.14		0.27±0.04		0.20±0.06

Data in shown as “Mean ± SE”; Data in the same column with different lowercase letters on the shoulders indicate significant differences (P<0.05).

Table 7. Correlations between ACACB genotypes and and contents of different fatty acids in Gannan yak.

SNPs	Genetypes	Fatty acid (%)
SNPs	Genetypes	No.	C20:3n8C	P	C22:1C	P	C20:4C	P	C23:0	P	C22:2C	P	C24:0	P	C20:5C	P	C24:1C	P
SNP1	AA	6	0.35±0.11^a	0.028	0.23±0.09	0.785	0.06±0.05	0.696	0.36±0.12	0.358	0.07±0.05	0.508	0.10±0.05	0.786	0.21±0.05	0.720	0.04±0.02	0.954
	GA	30	0.08±0.06^b		0.16±0.05		0.22±0.09		0.23±0.06		0.02±0.02		0.10±0.03		0.16±0.03		0.03±0.01
	GG	166	0.05±0.03^b		0.18±0.03		0.20±0.05		0.20±0.04		0.04±0.01		0.12±0.02		0.17±0.02		0.03±0.01
SNP2	AA	2	0.99±0.18^a	0.000	0.35±0.15	0.454	0.05±0.30	0.878	0.86±0.21	0.006	0.17±0.08	0.132	0.14±0.09	0.713	0.22±0.09	0.842	0.07±0.04	0.533
	CA	34	0.08±0.05^b		0.16±0.04		0.20±0.08		0.21±0.06		0.02±0.02		0.10±0.03		0.17±0.02		0.03±0.01
	CC	166	0.06±0.03^b		0.18±0.03		0.20±0.05		0.20±0.04		0.04±0.01		0.12±0.02		0.17±0.02		0.03±0.01
SNP3	CC	71	0.06±0.04	0.059	0.20±0.03	0.584	0.23±0.07	0.621	0.22±0.05^ab	0.014	0.04±0.02	0.713	0.12±0.02	0.847	0.17±0.02	0.777	0.03±0.01	0.942
	GC	91	0.02±0.04		0.16±0.03		0.22±0.06		0.14±0.04^b		0.04±0.02		0.11±0.02		0.18±0.02		0.03±0.01
	GG	40	0.14±0.05		0.19±0.03		0.15±0.08		0.30±0.05^a		0.03±0.02		0.13±0.02		0.16±0.02		0.03±0.01
SNP4	CC	129	0.08±0.04	0.650	0.20±0.04	0.284	0.19±0.06	0.704	0.23±0.04	0.090	0.05±0.04	0.295	0.12±0.02	0.472	0.16±0.02	0.409	0.03±0.01	0.623
	CT	63	0.04±0.04		0.09±0.07		0.23±0.07		0.13±0.05		0.06±0.02		0.10±0.02		0.18±0.02		0.03±0.01
	TT	10	0.03±0.09		1.02±0.20		0.14±0.14		0.22±0.10		0.03±0.04		0.09±0.04		0.21±0.04		0.02±0.02
SNP5	CC	149	0.08±0.04	0.343	0.19±0.03	0.230	0.07±0.21	0.696	0.23±0.04	0.146	0.04±0.01	0.433	0.12±0.02	0.823	0.18±0.02	0.072	0.03±0.01	0.867
	CT	49	0.02±0.05		0.13±0.04		0.18±0.08		0.13±0.05		0.02±0.02		0.11±0.02		0.14±0.02		0.03±0.01
	TT	4	0.04±0.14		0.18±0.11		0.22±0.06		0.14±0.15		0.02±0.05		0.09±0.07		0.12±0.06		0.02±0.03
SNP6	AA	6	0.30±0.11	0.095	0.37±0.09	0.083	0.39±0.18	0.504	0.46±0.12	0.092	0.06±0.05	0.476	0.22±0.05	0.151	0.24±0.05	0.225	0.04±0.02	0.453
	GA	57	0.05±0.04		0.17±0.03		0.18±0.07		0.21±0.05		0.05±0.02		0.12±0.02		0.18±0.02		0.02±0.01
	GG	139	0.06±0.04		0.18±0.03		0.21±0.06		0.19±0.04		0.03±0.02		0.11±0.02		0.16±0.02		0.03±0.01
SNP7	AA	46	0.08±0.05	0.806	0.17±0.04	0.757	0.26±0.07	0.251	0.19±0.05	0.251	0.04±0.02	0.989	0.12±0.02	0.178	0.17±0.02	0.955	0.03±0.01	0.892
	GA	97	0.05±0.04		0.18±0.03		0.15±0.06		0.18±0.04		0.04±0.02		0.10±0.02		0.17±0.02		0.03±0.01
	GG	59	0.07±0.05		0.20±0.04		0.24±0.07		0.26±0.05		0.04±0.02		0.14±0.02		0.17±0.02		0.03±0.01

Data in shown as “Mean ± SE”; Data in the same column with different lowercase letters on the shoulders indicate significant differences (P<0.05).

Table 8. Correlations between ACACB genotypes and contents of different fatty acids in Gannan yak.

SNPs	Genetypes	Fatty acid (%)
SNPs	Genetypes	No.	SFA	P-value	MUFA	P-value	PUFA	P-value	SCFA	P-value	MCFA	P-value
SNP1	AA	6	67.77±3.29	0.264	22.95±3.04	0.215	4.56±0.66	0.853	1.24±0.22	0.611	6.84±0.94	0.571
	GA	30	70.20±1.64		20.69±1.51		4.17±0.33		1.41±0.11		7.87±0.47
	GG	166	67.90±0.98		23.18±0.91		4.24±0.20		1.32±0.07		7.59±0.28
SNP2	AA	2	71.64±5.57	0.319	19.24±5.14	0.258	4.90±1.11	0.823	0.99±0.37	0.433	5.04±1.59	0.215
	CA	34	69.71±1.57		21.15±1.45		4.19±0.31		1.41±0.10		7.84±0.45
	CC	166	67.71±0.98		23.16±0.91		4.24±0.20		1.32±0.07		7.59±0.28
SNP3	CC	71	66.19±1.25	0.076	24.68±1.15^a	0.050	4.38±0.25	0.223	1.29±0.08	0.686	7.37±0.36	0.476
	GC	91	68.87±1.12		22.22±1.03^ab		4.03±0.22		1.36±0.08		7.80±0.32
	GG	40	68.66±1.41		21.81±1.30^b		4.46±0.28		1.33±0.10		7.56±0.41
SNP4	CC	129	68.40±0.98^a	0.000	22.29±0.89^b	0.000	4.30±0.20	0.619	1.35±0.07	0.315	7.76±0.29	0.093
	CT	63	68.49±1.22^a		22.75±1.11^b		4.07±0.25		1.31±0.09		7.44±0.36
	TT	10	57.27±2.48^b		34.15±2.26^a		4.27±0.52		1.10±0.17		6.25±0.74
SNP5	CC	149	67.76±1.03	0.661	23.08±0.96	0.792	4.27±0.20	0.357	1.20±0.09	0.060	7.52±0.29	0.307
	CT	49	68.93±1.42		22.49±1.32		3.95±0.28		1.79±0.26		7.42±0.40
	TT	4	68.27±3.93		21.22±3.63		4.77±0.78		0.14±0.15		9.25±1.12
SNP6	AA	6	68.00±3.32	0.967	21.03±3.07	0.815	5.12±0.66	0.357	1.41±0.22	0.556	7.81±0.95	0.575
	GA	57	68.23±1.26		22.81±1.17		4.24±0.25		1.27±0.08		7.37±0.36
	GG	139	67.91±1.07		22.96±0.98		4.19±0.21		1.36±0.07		7.74±0.30
SNP7	AA	46	66.43±1.36	0.090	24.61±1.26	0.058	4.31±0.27	0.643	1.24±0.09	0.367	7.15±0.39	0.190
	GA	97	69.25±1.11		21.66±1.02		4.13±0.22		1.37±0.07		7.87±0.32
	GG	59	67.32±1.28		23.34±1.18		4.35±0.26		1.35±0.09		7.58±0.37

Data in shown as “Mean ± SE”; Data in the same column with different lowercase letters on the shoulders indicate significant differences (P<0.05).

6. The Effects of ACACB Diplotypes on Milk Quality

The effects of different diplotypes of the ACACB gene in Gannan yaks on milk quality traits are shown in Table 9. It can be seen that the milk fat percentages in individuals with the H2H2 diplotype were significantly higher than in those with diplotypes H1H2, H2H3, H2H4, H2H5, H3H3, and H3H4 (P<0.05); although the other diplotypes showed associations with milk quality traits, the differences were not significant (P>0.05).

The results indicated that H2H2 was the dominant diplotype and could thus be used as a marker for improving milk quality traits in Gannan yaks.

Table 9. Effects of ACACB diplotypes on milk quality traits in Gannan yak.

Diplotypes	Meat quality
Diplotypes	No.	Protein rate/%	Fat rate/%	Lactose rate/%	Total solids/%	Non-fat solids/%
H1H2	8	5.53±0.35	4.29±0.62^c	4.94±0.18	16.96±1.18	11.75±0.58
H2H2	22	5.31±0.23	6.09±0.41^a	4.82±0.12	17.49±0.78	11.79±0.38
H2H3	14	4.60±0.28	5.66±0.49^ab	4.78±0.15	15.90±0.94	10.76±0.46
H2H4	18	5.08±0.24	5.20±0.42^abc	4.76±0.12	15.60±0.80	11.49±0.39
H2H5	11	4.98±0.30	5.30±0.53^abc	4.69±0.16	17.00±1.00	10.97±0.49
H3H3	10	5.34±0.31	4.72±0.55^bc	5.13±0.16	16.35±1.06	11.92±0.52
H3H4	14	4.82±0.27	4.32±0.47^c	4.65±0.14	14.50±0.91	10.87±0.44
P-value		0.145	0.018	0.251	0.119	0.206

Data in shown as “Mean ± SE”. Data in the same column with different lowercase letters on the shoulders indicate significant differences (P<0.05).

7. Effect of Presence/Absence of ACACB Haplotypes on Milk Quality

The effects of the presence and absence of ACACB haplotypes on milk quality traits are shown in Table 10. It can be seen that the percentage of milk fat in individuals carrying haplotype H2 was significantly greater than that in individuals with the deletion (P<0.05), while the total solid content in individuals carrying haplotypes H2 and H4 was significantly lower than that of individuals with the deletion (P<0.05). The results showed that the presence of haplotype H2 resulted in higher milk fat contents, while the presence of haplotypes H2 and H4 led to lower contents; differences in the presence or absence of the other haplotypes were not significant (P>0.05).

1. Genetic Characterization of ACACB in the Gannan Yak

The present study investigated, for the first time, the relationship between genetic variation in three different regions of ACACB in the Gannan yak and milk quality traits and fatty acid contents. Correlation analysis showed that the polymorphic loci SNP1, SNP3, SNP5, SNP6, and SNP7 genotypes of ACACB were significantly correlated with the fatty acid contents, milk fat percentages, lactose contents, milk protein percentages, total solid contents, and C11:0, C18:0, and C20:3n8C contents in the milk of Gannan yaks. SNP3 and SNP4 were significantly associated with the fatty acid contents of milk fat, including SFA and MUFA. Han et al. observed the variant locus g.66218726 T>C in ACACB of Chinese Holstein cows to be significantly associated with both milk yield and fat content²⁰. Genetic variation in intron 18 of ACACB has been found to be associated with obesity and kidney disease in humans^22,23. These findings indicate that there is considerable polymorphism in the ACACB gene in both humans and livestock species, and it is hypothesized that the SNP loci identified in the present study may be functional, although further confirmation is needed.

PIC and He are indicators of the degree of genetic variation within a population, with the magnitude of their values reflecting the overall level of genetic variation in the population; the larger the value, the richer the genetic diversity and the greater the potential for selection²⁴. Among the seven SNP loci investigated in this study, the SNP 1, 2, 5, and 6 loci showed low polymorphism (PIC≤0.25), SNP3, while the SNP4 and SNP7 loci were moderately polymorphic (0.25<PIC<0.5), suggesting that these seven SNP loci may be suitable for analyzing linkages between traits and genetic markers.

2. ACACB Gene Polymorphisms Affect Milk Quality Traits and Fatty Acid Contents in the Gannan Yak

The findings showed that genetic variation at the SNP 1, 2, 3, 5, and 7 loci in the ACACB gene was significantly correlated with milk quality traits in Gannan yaks. The ACACB gene, as a new candidate gene for genetic markers of milk improvement, encodes an enzyme involved in lipid metabolism, that is mainly expressed in tissues associated with high energy production, such as skeletal muscle, the myocardium, and liver. The enzyme is expressed on the outer mitochondrial membrane close to CTP1, where it functions as a negative regulator of fatty acid oxidation^25,26. ACACA (acetyl coenzyme A carboxylase alpha), an isoform of ACACB, is an enzyme that regulates fatty acid synthesis and is traditionally regarded as a major regulator of the rate-limiting step in de novo lipogenesis²⁷. It has been shown that ACACA var-iants significantly affect milk production traits in both dairy goats and cows^27-29. The ACACB gene is located in a region known to significantly influence both milk yield and milk composition³⁰. The ACACB gene SNP g.66218726 T>C significantly affects several milk production traits such as milk yield and fat content²⁰. It was thus hy-pothesized that ACACB genetic variants may affect quality traits in yak milk.

Although a literature search did not find publications on polymorphisms in ACACB in yaks, several studies have suggested that the gene is associated with traits related to fat metabolism in cattle. In human studies, ACACB genetic variants have been associated with metabolic syndrome, the onset of type II diabetes, kidney disease, and obesity in postmenopausal women^23,31,32. In pigs, ACACB was shown to be associated with lipid metabolic processes and obesity in Meishan pigs³³. The fatty acid contents of milk have been found to be heritable and have heritability estimates of 0.22 to 0.71³⁴. In the present study, it was found that genetic variants at SNPs 1, 2, 3, and 4 in ACACB were significantly associated with the contents of fat and different types of fatty acids in the milk of Gannan yaks. It was, therefore, hypothesized that variations in ACACB may affect the compositions of milk fat and fatty acids through the regulation of fat mobilization.

SNPs are defined as substitutions, insertions, or deletions of single nucleotides and are important in animal breeding³⁵. Determining the correlation between the loci of candidate SNPs and the economic traits of animals is an effective method for identifying new genetic markers, facilitating the accurate and efficient analysis of genetic diversity in breeding programs^36,37. Protein function and gene expression are associated with the location of the SNP, whether in regulatory sequences or coding regions³⁸. Exons, as protein-coding regions, make up only 1-2% of the genome, and the mutation rate of exons is about one-fifth that of non-coding regions³⁹. Studies have shown that a SNP in exon 2 of the growth hormone (GH) gene (SNP: c.100A>G) can be a useful marker in the selection of dairy goat breeds for growth and milk characteristics⁴⁰. Polymorphisms in exons 7 and 12 of the lactoferrin gene have been associated with the incidence of mastitis in Mora buffaloes⁴¹ while polymorphisms in exon 3 of leptin (LEP) affect milk production traits in New Zealand Holstein-Friesian × Jersey-cross dairy cows⁴² and polymorphisms in exons 2 and 5 and introns 1 and 2 of prolactin (PRL) affect milk production traits in Italian Mediterranean river buffalo⁴³. In the present study, two SNPs (SNP1 and SNP4) were detected in exons 37 and 46, respectively, of the ACACB gene in Gannan yaks, and were significantly correlated with the protein, lactose, and fatty acid contents of yak milk. These results were essentially consistent with those of previous studies but since there are fewer studies on ACACB genetic mutations and milk quality traits, the effects of these mutations on milk quality traits in the yak require further verification.

There is increasing evidence showing that introns are important for the normal expression of many eukaryotic genes. Introns have a wide range of functions and are involved in almost every step of the mRNA process. Although intronic variation may not directly affect the structure of a gene, it can influence transcription efficiency by affecting regulatory elements such as enhancers or other DNA structures⁴⁴. SNPs located in introns are also highly functional compared to those located in exons. Although introns lack coding ability, they can regulate gene expression⁴⁵ and introns in several genes have been shown to have normal transcription rates⁴⁶. While it is well known that intronic mutations do not alter the amino acid sequence, it has been found that mutations located in introns may have similar effects to those of synonymous mutations, and that the occurrence of intronic mutations affects a number of economically important traits in animals. For example, the intronic region of the GTPase-activating protein-encoding RAP1GAP gene in lake sheep, g.13561 G>A, and the intronic region of the amino acid-transporting protein-encoding rBAT gene, g.1460 T>C, were significantly correlated with traits associated with caudal fat deposition in the sheep⁴⁷. Amills et al. showed that the T to C substitution in intron 16 of the goat diacylglycerol O-acyltransferase-encoding DGAT1 gene had a significant effect on milk traits in goats and could be used as a marker for research⁴⁸. In addition, in the pre-sent study, it was found that introns 37, 46, and 47 of ACACB were mutated and correlated with milk quality traits such as milk fat and lactose contents, as well as the content of different types of milk fat fatty acids in Gannan yaks. This is essentially consistent with the findings of other studies and it was hypothesized that intronic variants in ACACB had a regulatory effect on milk production in yaks. Therefore, it is hypothesized that intronic variants may affect economically important traits in yaks.

In conclusion, mutations in ACACB have an important effect on yak milk quality traits, milk fat percentages, and fatty acid contents, indicating that ACACB and its genetic variants may be involved in fatty acid metabolism pathways which, in turn, regulate lipid metabolism and lead to changes in milk fat traits. However, further verification is required.

3. ACACB Gene Haplotypes and Diplotypes Affect Milk Quality and Fatty Acid Contents in Gannan Yaks

To assess the effects of the SNPs on milk quality traits, this study applied a model for the association analysis of haplotypes and diplotypes and milk quality traits. Hap-lotypes are inherited more efficiently than individual SNPs⁴⁹. The effect of a gene on an organism's traits may be related to different diplotypes of SNP sites in that gene⁵⁰. Liu et al. found that the melanocortin-4 receptor gene Hap1/4 diplotypes (ACC-ATG) were more strongly associated with carcass quality traits than other diplotypes in a Chinese indigenous beef cattle breed⁵¹. Gui et al. reported the individuals carrying Hap5/5 diplotypes (CC-GG-GG-GG-CC) of the hormone-sensitive lipase (HSL) gene in Chinese cattle breeds had greater levels of intramuscular fat content compared with other diplotypes⁵². Genetic variation in the promoter region of LAP3 dairy cows with the diplotype H1H3 (CTACGCT/GCGTACG) is associated with higher levels of lactation relative to other diplotypes⁵³. Studies on genetic variation in the prolactin gene in Holstein dairy cattle showed that the H2H8 diplotype was significantly asso-ciated with milk production traits⁵⁴. Perna et al. found that β-κ-casein (CN) haplo-types A1A, A1B, A1E, A2A, and A2B were associated with milk yield and fat content in Ayrshire dairy cows in Finland⁵⁵. The results of the present study revealed that the highest milk fat rate was associated with the H2H2 diplotype of the ACACB gene in Gannan yaks, which was significantly higher than other diplotypes; the milk fat con-tents of the milk from individuals carrying haplotype H2 were significantly higher than that in individuals with the deletion, and the total solid contents in individuals carrying haplotypes H2 and H4 were significantly lower than those of individuals with the deletion. This may be due to the fact that the ACACB gene and its SNPs affect fat mobilization by influencing the fatty acid oxidation pathway to regulate both milk quality and milk fat fatty acid contents, although the specific regulatory mechanism requires further investigation to determine the link between genetic variation and milk quality.

1. Animals and Sample Collection

Blood samples (10 mL) were collected from the jugular veins of 202 female Gannan yaks with calves; all yaks had had three litters and were at the same stage of lactation. The blood was collected into anticoagulant citrate dextrose solution (Acid-Citrate-Dextrose, ACD) and was brought back to the laboratory and frozen at -70℃ before genomic DNA extraction.

The animal study was approved by the Animal Care Committee at Gansu Agricultural University (approval number GAU-LC-2020-056). All animals in this study were approved by the Animal Ethics Committee of Gansu Agricultural University (approval number 2006-398). All methods were performed in accordance with the relevant guidelines and regulations.

The age, group, and litter size of all yaks from which blood samples were collected were recorded, and milk samples (25 mL) were collected once in the morning and once in the evening for three consecutive days. The samples were transferred to the laboratory on ice for the evaluation of milk quality characteristics.

2. Methods

2.1. Determination of milk quality traits

The milk samples were sent to the Quality Supervision, Inspection and Testing Center for Animal Hides and Skins and Products of the Ministry of Agriculture (Lanzhou, China) for trait analysis using a FOSS Milk Composition Analyzer (FOSS, Hillerød, Denmark). The traits analyzed included the levels of lactose, milk protein, and milk fat, and the contents of total solids and non-fat solids.

2.2. Extraction of genomic DNA

Genomic DNA was extracted from the yak blood using a Whole-Genome Blood DNA Extraction Kit (Centrifugal Column Type), according to the manufacturer’s instructions, and the DNA integrity, purity and concentration were evaluated by 1.5% agarose gels and spectrophotometry, using a NanoDropTM Lite spectrophotometer (Thermo Fisher, Waltham, MA, USA), and stored at -20℃ until use.

2.3. Primer design and synthesis

Primers were designed according to the yak ACACB sequence provided in the Ensembl database (ENSBMUG00000022222) using Primer Premier 5.0 software and the primer information is referenced in that literature²¹. The primers were synthesized by Beijing Kengke Biological Company (Xi'an, China).

2.4. Detection of SNP loci by PCR amplification and hybrid pool sequencing

The total volume of the PCR reaction was 20 μL and included 0.8 μL of each of the upstream and downstream primers, 0.8 μL of genomic DNA, 10.0 μL of Taq DNA polymerase, and 7.6 µL of ddH₂O. The PCR reaction conditions were pre-denaturation at 94 ℃ for 5 min, denaturation at 94 ℃ for 30 s, annealing at 60 ℃ for 30 s, extension at 72 ℃ for 30 s (35 cycles), and extension at 72 ℃ for 10 min. The PCR products were preserved at 4 ℃. Two microliters of the PCR amplification products from each of the 20 blood samples of the unrelated yaks were removed, and the mixed products to form a mixed pool. And then sent to Beijing Kengke Biological Company for sequencing.

2.5. Determination of genotype

The genomic DNA samples were sent to King Peptide Biologicals (Wuhan, China) for typing and determination of their genotypes using the KASP method.

3. Statistics and Data Analysis

Microsoft Excel 2016 was used to collate the data, and the genotype frequency and allele frequency, observed homozygosity (Ho), number of effective alleles (Ne), heterozygosity (He), and polymorphic information content (PIC) were calculated. Linkage disequilibrium and haplotypes of the SNPs were analyzed using SHEsis software (http://analysis.biox.cn/myAnalysis.php). Genotypes, haplotypes, and diplotypes of SNPs were analyzed to determine associations with milk quality traits using a general linear model (GLM) with SPSS 26.0 software. The statistical model was as follows: Y_ijk=μ+Genotype_i/Haplotype_i+Parity_j+Group_k+e_ijk, where Y_ijk represents the phenotypic observation; µ represents the population mean; Genotype represents the fixed effect of genotype; Haplotype represents the fixed effect of haplotype; Parity_j represents the fixed effect of litter size; Group_k represents the fixed effect of population; e_ijk represents the random error.

In this study, the influence of genetic variants in the ACACB gene on yak milk quality traits was investigated for the first time. Potential functional mutations in ACACB were identified, which can be used as molecular markers for the selection and breeding of yaks yielding high-quality milk, and provide a reference for an in-depth investigation on the influence of the yak ACACB gene on yak milk quality traits.

Data Availability: Data are contained within the article. The sequences data in our study has been uploaded to the NCBI gene bank and GenBank accession number are as follows: BankIt2726640 Sequence_1 OR348640; BankIt2726640 Sequence_2 OR348641; BankIt2726640 Sequence_3 OR348642; BankIt2726640 Sequence_4 OR348643; BankIt2726640 Sequence_5 OR348644; BankIt2726640 Sequence_6 OR348645; BankIt2726640 Sequence_7 OR348646; BankIt2726640 Sequence_8 OR348647.

Statement: This study was reported in accordance with ARRIVE guidelines (https://arriveguidelines.org/).

Acknowledgements: We give thanks all participants for their advice and support of this study.

Author Contributions: Conceptualization, X.W. methodology, Y.Q.; software, B.M.; validation, C.C.; formal analysis, S.C.; investigation, Y.Q. and C.Z.; resources, Z.Z.; data curation, F.Z.; writing—original draft preparation, C.Z.; writing—review and editing, X.L.; visualization, J.W. and Z.H.; project administration, B.S.; funding acquisition, J.H. All authors have read and agreed to the published version of the manuscript.

Funding: This study was supported by the “Gansu Agricultural University Public Recruitment Doctoral Research Start-up Fund (GAU-KYQD-2020-20)”, “Gansu Provincial Department of Education: Industrial Support Plan Project (2022CYZC-43)”, “Discipline Team Project of Gansu Agricultural University (GAU-XKTD-2022-22)”.

Competing interests: The authors declare no competing interests.

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No competing interests reported.

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Polymorphisms of ACACB Gene and Their Association with Milk Quality Traits in Yak

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