Next Article in Journal
Relationship among Sex, Skin Color, and Production Parameters of Broiler in Pectoral Myopathies
Previous Article in Journal
A Preliminary Investigation of Myostatin Gene (MSTN) Variation in Red Deer (Cervus elaphus) and Its Implications for Venison Production in New Zealand
Previous Article in Special Issue
Runs of Homozygosity and Quantitative Trait Locus/Association for Semen Parameters in Selected Chinese and South African Beef Cattle
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genetic Variations within the Bovine CRY2 Gene Are Significantly Associated with Carcass Traits

1
Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Xianyang 712100, China
2
Institute of Animal Science and Veterinary, Shandong Academy of Agriculture Science, Jinan 250100, China
3
College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin 300380, China
*
Authors to whom correspondence should be addressed.
Animals 2022, 12(13), 1616; https://doi.org/10.3390/ani12131616
Submission received: 19 May 2022 / Revised: 16 June 2022 / Accepted: 21 June 2022 / Published: 23 June 2022

Abstract

:

Simple Summary

Carcass traits are crucial for beef cattle breeding. CRY2, as a clock gene, affects the body’s metabolism and regulates the physiological function of skeletal muscles, including muscle growth and development. In order to investigate the relationship between the CRY2 gene and cattle carcass traits, a total of 705 individuals from the Shandong Black Cattle Genetic Resource (SDBCGR) population were randomly collected. Eight potential insertion/deletion sites within the CRY2 gene were analyzed, and two of them were polymorphic. Population genetic parameters including genotype frequencies and allele frequencies of the two loci in the tested population were calculated. Importantly, the two loci were significantly related to carcass traits such as gross weight, ribeye, and high rib, suggesting that CRY2 shows the potential for bovine growth and development. The two loci can be used as effective molecular markers affecting carcass traits of beef cattle and provide certain scientific and theoretical bases for practical breeding.

Abstract

As an important part of the circadian rhythm, the circadian regulation factor 2 of cryptochrome (CRY2), regulates many physiological functions. Previous studies have reported that CRY2 is involved in growth and development. However, the relationship between CRY2 gene polymorphism and cattle carcass traits remains unclear. The aim of this study was to detect the possible variations of the CRY2 gene and elucidate the association between the CRY2 gene and carcass traits in the Shandong Black Cattle Genetic Resource (SDBCGR) population (n = 705). We identified a 24-bp deletion variation (CRY2-P6) and a 6-bp insertion variation (CRY2-P7) in the bovine CRY2 gene. The frequency of the homozygous II genotype is higher than the heterozygous ID genotype in both two loci. In addition, CRY2-P6 was consistent with HWE (p > 0.05). Importantly, the CRY2-P6 variant was significantly associated with 12 carcass traits, including gross weight, ribeye, high rib, thick flank, etc. and the II was the dominant genotype. The CRY2-P7 site was also significantly correlated with five traits (gross weight, beef-tongue, etc.). Collectively, these outcomes indicated that the two Indel loci in the CRY2 gene could be used for marker-assisted selection of cattle carcass traits.

1. Introduction

Beef quality is influenced by a combination of various factors, including breed, age, sex and gene genotype, as well as environmental factors such as feeding management and slaughter processes [1]. The Shandong Black Cattle Genetic Resource (SDBCGR) population is a new high-grade beef cattle breed in China, which is a hybrid of Bohai Black Cattle, Luxi Cattle and Japanese Black Cattle [2]. Its growth performance and meat quality traits are comparable to those of Japanese Kobe beef, and its meat quality meets the international A3 standard, which can fill the shortage of domestic high-grade beef.
Carcass traits controlled by micro-effective polygenes are not only a comprehensive reflection of growth and development of different bodies but also an important economic and breeding index for beef cattle [3,4]. Currently, the main genetic variations are divided into three types: single nucleotide polymorphism (SNP), insertion or deletion (Indel) and copy number variation (CNV). Indel, as a high-throughput genetic marker, is widely utilized in molecular marker assisted selection, animal population genetic analysis, medical diagnosis, etc. [5], and many studies have also provided evidence that Indel polymorphisms are related to characteristic traits among livestock [6]. With the continuous improvement of molecular marker technology, the shortcomings of traditional breeding methods, such as long cycles and unstable inheritance of excellent traits, have been eliminated, and the breeding program for cattle improvement can be better fulfilled. Marker-assisted selection (MAS), is an alternative selection for DNA mutations, which is independent of the microenvironment [7]. Among the three main genetic variations, Indel is the most convenient for detection that does not require special conditions for equipment and technology, and is widely applied in the screening of key economic traits in animals [8]. Therefore, we can continue to improve carcass traits in the SDBCGR population using the MAS method.
The circadian clock is a global regulatory system that produces 24-h cycle rhythm changes in many cellular and body functions [9]. CRY2, a circadian regulation factor 2 of cryptochrome, which is a critical component of the circadian core oscillator complex, is necessary for the generation and maintenance of the circadian rhythm [10]. Mutations in clock genes such as CRY2 can alter circadian rhythms and produce long, short, or irregular phenotypes [11]. As a transcriptional inhibitor, CRY2 negatively regulates gene transcription and is related to many physiological processes [12]. The circadian rhythm regulates multiple physiological functions, including sleep, body temperature, appetite during exercise and hormone secretion [13]. Interestingly, clock genes can also regulate the physiological functions of skeletal muscle, including muscle growth and maintenance as well as energy metabolism. Numerous rhythm genes in muscle show expression of neurotransmitters at midnight, which corresponds to the peak of physical activity [14]. In addition to shifts in activity, it has been found that disrupted changes in normal circadian gene function may lead to the impairment of metabolic health. The circadian rhythm variations can be associated with the peripheral metabolic effects of the biological clock [15,16]. Moreover, disruptions in circadian rhythm behavior such as shift workers or animal models are more susceptible to metabolic diseases [17]. Meanwhile, the clock mechanism regulates the expression of many metabolic genes in peripheral tissues [18,19]. Circadian clock dysregulation has been associated with many diseases, such as sleep disorders, cancer and metabolic diseases [20,21,22]. Additionally, genetic and epidemiological studies have reported that clock dysbiosis is associated with various adverse metabolic phenotypes [23]. CRY2, as an important part of the circadian rhythm, plays a key role in proliferation, DNA repair and DNA damage checkpoint control, regulating important cell cycle progression genes [24,25]. In addition to its effect on metabolism, CRY2 also affects the growth of the body and alters the generation of muscle cells. To date, there is little research on the CRY2 gene in relation to carcass traits in cattle.
The final growth performance of animals depends on the interaction of environmental, nutritional and genetic factors [26]. Thus, in terms of genetics, in order to further improve carcass traits in the SDBCGR population, it is necessary to analyze the relationship between gene variations and recorded carcass traits. Hence, the purpose of this study was to detect Indel variations within the CRY2 gene in the SDBCGR population and further test the correlation between the CRY2 gene and carcass traits. The results of the current study will provide valuable information for the application of the CRY2 gene in molecular breeding programs in the SDBCGR population.

2. Materials and Methods

2.1. Sample Collection and Data Recording

All samples (n = 705) from the SDBCGR population come from two similar farms (Shandong, China) and all individuals are similar in body condition, age and feeding conditions (including feed allocation, environment and disease control). In addition, this study used carcass traits such as gross weight, carcass weight (left limb weight and right limb weight), chuck tender, etc. (Figure 1).
Furthermore, after slaughter, farm technicians randomly selected and recorded carcass trait data of males and females, respectively, according to the same standard. Sterile electronic scales were used to weigh the carcass traits such as sirloin and thick flank, and vernier calipers or double calipers were used to measure ribeye morphology and phenotypic characteristics.

2.2. Genomic DNA Isolation

Genomic DNA was extracted from the neck muscle tissue samples in accordance with the phenol-chloroform method [27,28]. Firstly, fragmented muscle tissue was lysed with protease K and sodium dodecyl sulfate, and then an equal amount of water-saturated phenol was added to the test tube to be centrifuged to achieve phase separation. The upper aqueous phase was transferred to a new centrifuge tube and then chloroform was added to extract residual phenol from the aqueous phase. DNA was concentrated with anhydrous ethanol. Finally, DNA was washed with 70% ethanol and diluted with water after drying. In addition, the concentration of the DNA samples was tested by Nanodrop 2000 (Thermo Scientific, Waltham, MA, USA). Subsequently, DNA samples were diluted to 20 ng/µL and frozen at −40 °C for further experiments.

2.3. PCR Amplification and Genotyping

Eight genetic variation loci were retrieved from the Ensembl database. Then, based on the genetic sequence of the bovine CRY2 gene, eight pairs of primers (Table 1) were designed using Primer Premier 5 software and synthesized by the Sangon Biotech company (Xi’an, China). Polymorphic fragments were amplified by the polymerase chain reaction (PCR) method using a touch-down program and the PCR amplification procedure was consistent with previous studies [29] (Figure 2). Subsequently, PCR products were detected by 3.0% agarose gels electrophoresis to identify the genotypes of all individuals (n = 705). PCR products were then sequenced using Sanger sequencing technology by the Tsingke Biotechnology Company (Xi’an, China).

2.4. Statistical Analyses

Genotypic and allelic frequencies were calculated directly based on the different genotypic numbers. Population genetic parameters including heterozygosity (He), homozygosity (Ho), effective allele number (Ne) and polymorphism information content (PIC) were calculated by Nei’s method [30] (Table 2). The correlation between different genotype and carcass traits was analyzed by an independent samples t-test with SPSS (Version 25.0, IBM Corporation, New York, NY, USA), and data was presented as the mean ± standard error. p-Value < 0.05 was considered to indicate statistical significance. Additionally, Hardy–Weinberg equilibrium (HWE) was measured using the SHEsis online website. The general linear model was as follows: Yijk = μ +Si + Gj + Eijk, where Yijk is the phenotypic value, μ is the overall population mean, Si is the effect of sex, Gj is the genotype, and Eijk is the random error [31].

3. Results

3.1. Identification of Indel Variations within the CRY2 Gene

The bovine CRY2 gene is located on chromosome 15 and consists of 12 exons with a length of 34,781 bp (NCBI https://www.ncbi.nlm.nih.gov/, accessed on 10 December 2020), and based on the eight loci, the bovine CRY2 gene map was plotted (Figure 3a). The electrophoresis pattern and sequencing map showed that only the CRY2-P6 and CRY2-P7 loci are polymorphic in the SDBCGR population (Figure 3b–e), and they are deletion and insertion variations, respectively. The CRY2-P6 locus had the homozygous insertion (II) genotype and heterozygous (ID) genotype (Figure 3b,c), while the CRY2-P7 locus also contained two genotypes: the heterozygous (ID) genotype and (II) homozygous insertion genotype (Figure 3d,e).

3.2. Genotypic Frequencies and Population Genetic Parameters Analysis

Based on genetic polymorphisms of the CRY2-P6 and CRY2-P7 loci, the genotypic frequencies, allelic frequencies and population genetic parameters were calculated. The frequency of the II genotype (0.933) was higher than ID (0.067) within the CRY2-P6 locus (Table 3). Similarly, for the CRY2-P7 locus, the II genotype had a higher frequency (0.622) (Table 3). In addition, the CRY2-P6 locus is consistent with HWE (p > 0.05), while CRY2-P7 locus deviated from the HWE. PIC value indicated that the CRY2-P6 locus had low genetic polymorphism (PIC < 0.25), while the CRY2-P7 locus represented medium genetic diversity (0.25 < PIC < 0.5).

3.3. Associations between Different Genotypes and Carcass Traits

The correlations between the CRY2-P6 locus in the cattle CRY2 gene and carcass traits of the SDBCGR population were evaluated by an independent samples t-test (Table 4). The results of the association analysis reflected that the CRY2-P6 locus within the cattle CRY2 gene was significantly associated with gross weight, back tendon, chuck tender, money tendon, flank steak, triangle flank, ribeye, high rib, beef tenderloin, thick flank, right limbs weight and boneless short ribs in the SDBCGR. Furthermore, individuals with the homozygous genotype displayed a superior phenotype compared to those with heterozygous genotype at the CRY2-P6 locus (p < 0.05) (Figure 4a,b).
The independent samples t-test was also conducted to validate the relationship between the CRY2-P7 locus and carcass traits (Table 5). The results showed that there was a significant correlation between the CRY2-P7 locus and beef tongue, the length of ribeye, brisket, meat tendon and shoulder clod in male and female SDBCGR. Meanwhile, in males, the II genotype was the dominant genotype (Figure 4c).

3.4. Linkage Disequilibrium Analysis of Different Genotypes in the Bovine CRY2 Gene

We performed linkage disequilibrium analysis between the two Indel loci in the intron region of the CRY2 gene (SHEsis online website, http://analysis.bio-x.cn/, accessed on 10 June 2021). The results exhibited that D’ test value was 0.952 and r2 test value was 0.007 (Figure 5). Therefore, according to the D’ test results, there was a strong linkage between the CRY2-P6 and CRY2-P7 loci; however, r2 displayed adverse result. The results of haplotype analysis for CRY2 generated four haplotypes, and Ip6-Ip7 had the highest frequency (Figure 6).

3.5. Analysis of the Combined Effect of the CRY2-P6 and CRY2-P67 Loci on Carcass Traits

Furthermore, the combinatorial genotype analysis between the CRY2-P6 and CRY2-P7 loci in the SDBCGR population and carcass traits was performed. The genotype with lower frequency (n < 3) was excluded from the correlation analysis. In males, the association analysis of three combined genotypes with carcass traits in SDBCGR showed that the three combined genotypes were all significantly associated with several traits (such as money tendon, chuck tender, flank steak, triangle flank and high rib etc.), and combined genotype II-II had a dominant phenotype with significant (p < 0.05) differences (Table 6 and Table 7). In females, there were four combined genotypes available for association analysis. Moreover, the combined genotypes were significantly associated with the traits such as chuck tender, thick flank and flank steak, and the combined genotypes II-II and ID-ID had superior (p < 0.05) phenotypes. These results further proved that the CRY2 gene plays an important role in carcass traits of the SDBCGR population (Table 6 and Table 8).

4. Discussion

Among the detected loci, the CRY2-P6 locus and CRY2-P7 locus exhibited polymorphism. Association analysis revealed that the CRY2-P6 and CRY2-P7 variants in the CRY2 gene were significantly correlated with SDBCGR population carcass traits (chuck tender, money tendon, flank steak, ribeye, high rib, thick flank, boneless short ribs, beef tongue, etc.). Interestingly, at the CRY2-P6 locus, the II genotype was more phenotypically advantageous, and the frequency of the “I” allele was higher compared to the “D” allele. In addition, at the CRY2-P7 locus, the II phenotype was more favorable in males. In females, however, it shows a different phenotypic advantage. Previous studies have shown that many physiological processes regulated by circadian rhythm are different between genders [32]. In mammals, females and males have differences in hormones, anatomy and metabolism; in addition, in CRY2 deficiency, the growth of mice is impaired in a gender-dependent manner, which is due to a change in growth hormone circulation patterns in mutant males [16]. Thus, we speculate that CRY2 affects body growth in a gender-biased manner. Moreover, we predicted transcription factors at the CRY2-P7 locus and found that the FOXA2 transcription factor can specifically bind to the II genotype sequence. FOXA2 contributes to homeostasis in skeletal muscle and is essential for both estrogen and androgen transmission [33]. The PIC value of a marker is equivalent to its ability to detect polymorphisms between individuals in a population and is an indicator of the marker quality in genetic studies; the higher this ability, the greater its value [34]. From the analysis of population parameters, the CRY2-P7 locus has a moderate polymorphism (0.25 < PIC < 0.5), which has a high potential genetic value. The CRY2-P6 locus is compatible with HWE, while the CRY2-P7 locus is not. Possible explanations could be non-random mating, genetic drift or the effects of artificial selection [6].
Our experiment involved many carcass quality traits such as ribeye, thick flank, high rib, beef tongue, chuck tender and boneless short ribs. The clock network is integrated into all major cellular signaling and metabolic pathways, and clock disruptions are expected to affect cell and organism behavior in various ways [23,35,36]. On the one hand, previous studies have shown that melatonin secreted by the pineal gland directly regulated pancreatic insulin secretion in a suprachiasmatic nucleus (SCN) clock-dependent manner [37,38]. It has been proven in studies that the genetic disruption of mouse clock components can induce metabolic diseases, including obesity, by attenuating rhythmic changes in hormone concentrations and expression of metabolic genes [18,19]. Furthermore, CRY2 deficiency impairs body growth, alters the pattern of circulating growth hormone, and the expression of adipogenic and steroid pathways [16]. Therefore, we hypothesize that deletion of the CRY2 gene alters hormone secretion and energy metabolism patterns in the organism, thereby affecting body growth. On the other hand, most of the carcass traits involved in this study were related to muscle or bone components. Clock genes can regulate the physiological functions of skeletal muscle, including muscle growth and maintenance as well as energy metabolism. Previous studies have revealed that CRY2, rather than CRY1, promotes the proliferation of myogenic cells and subsequent formation of myotubes on a circadian basis. Similar differences may occur in chondrocytes [39,40]. Therefore, we suggest that the CRY2 gene has a function in promoting muscle growth as well as promoting bone metabolism. However, the specific mechanism of how the CRY2 affects cattle carcass traits remains to be further explored.
Based on the result of the r2 value in the LD analysis, there was no linkage between the two loci. Although there was no linkage between the two loci, these variations might have a superposition effect. Considering the large sample size of the SDBCGR population (n = 705), the relationship between the combined genotype and carcass traits was analyzed. The results showed that the genotype II-II had better carcass traits. Taking into account the above results, we concluded that the Indel variations of CRY2 can effectively affect the carcass traits in cattle, which can be used as effective DNA molecular markers for cattle breeding.

5. Conclusions

Briefly, we analyzed eight Indel loci within the CRY2 gene in the SDBCGR population, among which the CRY2-P6 and CRY2-P7 polymorphisms were polymorphic and significantly associated with carcass traits, and II genotype had the greatest effect on carcass traits at the CRY2-P6 locus in SDBCGR population. The results suggest that the CRY2-P6 and CRY2-P7 variants of the CRY2 gene can be useful molecular markers for determining carcass traits in cattle. In this field, these molecular markers can be applied in actual production in the future to improve carcass traits in beef cattle and accelerate breeding improvement. However, the possible effect of CRY2 gene variant on carcass traits needs to be further investigated.

Author Contributions

Resources, E.S. and F.J.; Conducting experiment, X.L. (Xuelan Li), E.J. and K.Z.; Project administration, X.L. (Xianyong Lan) and P.G.; Data curation, X.L. (Xuelan Li) and S.Z.; Writing—original draft, X.L. (Xuelan Li); Writing—review & editing, X.L. (Xianyong Lan) and H.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Agricultural Improved Seed Project of Shandong Province (No.2020LZGC014), the National Natural Science Foundation of Tianjing (No.19JCYBJC24800), the National Project for Undergraduate of Northwest A&F University (No.S202010712004), and the Shandong Provincial Natural Science Foundation (ZR2019BC086).

Institutional Review Board Statement

All experimental procedures were approved by the Animal Policy and Welfare Committee of Northwest A&F University (protocol number: NWAFAC1008).

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available upon request from corresponding author.

Acknowledgments

We would like to thank Enliang Song and his team at Shandong Key Laboratory of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, Shandong, China for collection of Shandong Black Cattle Genetic Resource population samples.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wang, X.; Li, G.P. Meat quality traits of cattle and it influence factors. Chin. J. Anim. Nutr. 2019, 31, 4949–4958. (In Chinese) [Google Scholar]
  2. Liu, R.; Liu, X.; Bai, X.; Xiao, C.; Dong, Y. Different expression of lipid metabolism-related genes in Shandong black cattle and Luxi cattle based on transcriptome analysis. Sci. Rep. 2020, 10, 21915. [Google Scholar] [CrossRef] [PubMed]
  3. Al-Mamun, H.A.; Kwan, P.; Clark, S.A.; Ferdosi, M.H.; Tellam, R.; Gondro, C. Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight. Genet. Sel. Evol. 2015, 47, 66. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Macé, T.; González-García, E.; Pradel, J.; Parisot, S.; Carrière, F.; Douls, S.; Foulquié, D.; Hazard, D. Genetic analysis of robustness in meat sheep through body weight and body condition score changes over time. J. Anim. Sci. 2018, 96, 4501–4511. [Google Scholar] [CrossRef]
  5. Ren, F.; Yu, S.; Chen, R.; Lv, X.; Pan, C. Identification of a novel 12-bp insertion/deletion (indel) of iPS-related Oct4 gene and its association with reproductive traits in male piglets. Anim. Reprod. Sci. 2017, 178, 55–60. [Google Scholar] [CrossRef]
  6. Wang, S.; Liu, S.; Yuan, T.; Sun, X. Genetic effects of FTO gene insertion/deletion (InDel) on fat-tail measurements and growth traits in Tong sheep. Anim. Biotechnol. 2021, 32, 229–239. [Google Scholar] [CrossRef]
  7. Xin, D.; Bai, Y.; Bi, Y.; He, L.; Kang, Y.; Pan, C.; Zhu, H.; Chen, H.; Qu, L.; Lan, X. Insertion/deletion variants within the IGF2BP2 gene identified in reported genome-wide selective sweep analysis reveal a correlation with goat litter size. J. Zhejiang Univ.-Sci. B 2021, 22, 757–766. [Google Scholar] [CrossRef]
  8. Wang, P.; Li, Y.; Meng, T.; Zhang, J.; Wei, Y.; Meng, Z.; Lin, Y.; Liu, D.; Sui, L. KDM6A promotes, chondrogenic differentiation of periodontal ligament stem cells by deme-thylation of SOX9. Cell Prolif. 2018, 51, e12413. [Google Scholar] [CrossRef] [Green Version]
  9. Lee, J.H.; Sancar, A. Circadian clock disruption improves the efficacy of chemotherapy through p73-mediated apoptosis. Proc. Natl. Acad. Sci. USA 2011, 108, 10668–10672. [Google Scholar] [CrossRef] [Green Version]
  10. Fu, L.; Patel, M.S.; Bradley, A.; Wagner, E.F.; Karsenty, G. The molecular clock mediates leptin-regulated bone formation. Cell 2005, 122, 803–815. [Google Scholar] [CrossRef] [Green Version]
  11. Van der Horst, G.T.; Muijtjens, M.; Kobayashi, K.; Takano, R.; Kanno, S.; Takao, M.; de Wit, J.; Verkerk, A.; Eker, A.P.; van Leenen, D.; et al. Mammalian Cry1 and Cry2 are essential for maintenance of circadian rhythms. Nature 1999, 398, 627–630. [Google Scholar] [CrossRef]
  12. Lee, Y.; Lee, J.; Kwon, I.; Nakajima, Y.; Ohmiya, Y.; Son, G.H.; Lee, K.H.; Kim, K. Coactivation of the CLOCK-BMAL1 complex by CBP mediates resetting of the circadian clock. J. Cell Sci. 2010, 123, 3547–3557. [Google Scholar] [CrossRef] [Green Version]
  13. Sahar, S.; Sassone-Corsi, P. Regulation of metabolism: The circadian clock dictates the time. Trends Endocrinol. Metab. 2012, 23, 1–8. [Google Scholar] [CrossRef] [Green Version]
  14. McCarthy, J.J.; Andrews, J.L.; McDearmon, E.L.; Campbell, K.S.; Barber, B.K.; Miller, B.H.; Walker, J.R.; Hogenesch, J.B.; Takahashi, J.S.; Esser, K.A. Identification of the circadian transcriptome in adult mouse skeletal muscle. Physiol. Genom. 2007, 31, 86–95. [Google Scholar] [CrossRef] [Green Version]
  15. Vitaterna, M.H.; Selby, C.P.; Todo, T.; Niwa, H.; Thompson, C.; Fruechte, E.M.; Hitomi, K.; Thresher, R.J.; Ishikawa, T.; Miyazaki, J.; et al. Differential regulation of mammalian period genes and circadian rhythmicity by cryptochromes 1 and 2. Proc. Natl. Acad. Sci. USA 1999, 96, 12114–12119. [Google Scholar] [CrossRef] [Green Version]
  16. Bur, I.M.; Cohen-Solal, A.M.; Carmignac, D.; Abecassis, P.Y.; Chauvet, N.; Martin, A.O.; van der Horst, G.T.; Robinson, I.C.; Maurel, P.; Mollard, P.; et al. The circadian clock components CRY1 and CRY2 are necessary to sustain sex dimorphism in mouse liver metabolism. J. Biol. Chem. 2009, 284, 9066–9073.e4. [Google Scholar] [CrossRef] [Green Version]
  17. Chaix, A.; Lin, T.; Le, H.D.; Chang, M.W.; Panda, S. Time-Restricted Feeding Prevents Obesity and Metabolic Syndrome in Mice Lacking a Circadian Clock. Cell Metab. 2019, 29, 303–319. [Google Scholar] [CrossRef]
  18. Dibner, C.; Schibler, U.; Albrecht, U. The mammalian circadian timing system: Organization and coordination of central and peripheral clocks. Annu. Rev. Physiol. 2010, 72, 517–549. [Google Scholar] [CrossRef] [Green Version]
  19. Maury, E.; Ramsey, K.M.; Bass, J. Circadian rhythms and metabolic syndrome: From experimental genetics to human disease. Circ. Res. 2010, 106, 447–462. [Google Scholar] [CrossRef] [Green Version]
  20. Bass, J.; Lazar, M.A. Circadian time signatures of fitness and disease. Science 2016, 354, 994–999. [Google Scholar] [CrossRef] [Green Version]
  21. Panda, S. Circadian physiology of metabolism. Science 2016, 354, 1008–1015. [Google Scholar] [CrossRef] [Green Version]
  22. Takahashi, J.S. Transcriptional architecture of the mammalian circadian clock. Nat. Rev. Genet. 2017, 18, 164–179. [Google Scholar] [CrossRef] [Green Version]
  23. Sahar, S.; Sassone-Corsi, P. Metabolism and cancer: The circadian clock connection. Nat. Rev. Cancer 2009, 9, 886–896. [Google Scholar] [CrossRef]
  24. Gauger, M.A.; Sancar, A. Cryptochrome, circadian cycle, cell cycle checkpoints, and cancer. Cancer Res. 2005, 65, 6828–6834. [Google Scholar] [CrossRef] [Green Version]
  25. Lee, J.H.; Gaddameedhi, S.; Ozturk, N.; Ye, R.; Sancar, A. DNA damage-specific control of cell death by cryptochrome in p53-mutant ras-transformed cells. Cancer Res. 2013, 73, 785–791. [Google Scholar] [CrossRef] [Green Version]
  26. Li, Z.H.; Li, H.; Zhang, H.; Wang, S.Z.; Wang, Q.G.; Wang, Y.X. Identification of a single nucleotide polymorphism of the insulin-like growth factor binding protein 2 gene and its association with growth and body composition traits in the chicken. J. Anim. Sci. 2006, 84, 2902–2906. [Google Scholar] [CrossRef] [Green Version]
  27. Köchl, S.; Niederstätter, H.; Parson, W. DNA extraction and quantitation of forensic samples using the phenol-chloroform method and real-time PCR. Methods Mol. Biol. 2005, 297, 13–30. [Google Scholar] [CrossRef]
  28. Lan, X.Y.; Pan, C.Y.; Chen, H.; Zhang, C.L.; Li, J.Y.; Zhao, M.; Lei, C.Z.; Zhang, A.L.; Zhang, L. An AluI PCR-RFLP detecting a silent allele at the goat POU1F1 locus and its association with production traits. Small Rumin. Res. 2007, 73, 8–12. [Google Scholar] [CrossRef]
  29. Li, J.; Zhu, X.; Ma, L.; Xu, H.; Cao, X.; Luo, R.; Chen, H.; Sun, X.; Cai, Y.; Lan, X. Detection of a new 20 bp insertion/deletion (indel) within sheep PRND gene using mathematical expectation (ME) method. Prion 2017, 11, 143–150. [Google Scholar] [CrossRef] [Green Version]
  30. Nei, M.; Roychoudhury, A.K. Sampling variances of heterozygosity and genetic distance. Genetics 1974, 76, 379–390. [Google Scholar] [CrossRef]
  31. Zhang, S.; Xu, H.; Kang, Z.; Cai, H.; Dang, R.; Lei, C.; Chen, H.; Guo, X.; Lan, X. Bovine pituitary homeobox 2 (PITX2): mRNA expression profiles of different alternatively spliced variants and association analyses with growth traits. Gene 2018, 669, 1–7. [Google Scholar] [CrossRef] [PubMed]
  32. Škrlec, I.; Talapko, J.; Juzbašić, M.; Steiner, R. Sex Differences in Circadian Clock Genes and Myocardial Infarction Susceptibility. J. Cardiovasc. Dev. Dis. 2021, 8, 53. [Google Scholar] [CrossRef] [PubMed]
  33. Phua, W.W.T.; Tan, W.R.; Yip, Y.S.; Hew, I.D.; Wee, J.W.K.; Cheng, H.; Leow, M.K.S.; Wahli, W.; Tan, N.S. PPARβ/δ Agonism Upregulates Forkhead Box A2 to Reduce Inflammation in C2C12 Myoblasts and in Skeletal Muscle. Int. J. Mol. Sci. 2020, 21, 1747. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Serrote, C.M.L.; Reiniger, L.R.S.; Silva, K.B.; Rabaiolli, S.M.D.S.; Stefanel, C.M. Determining the Polymorphism Information Content of a molecular marker. Gene 2020, 726, 144175. [Google Scholar] [CrossRef]
  35. Hastings, M.H.; Reddy, A.B.; Maywood, E.S. A clockwork web: Circadian timing in brain and periphery, in health and disease. Nat. Rev. Neurosci. 2003, 4, 649–661. [Google Scholar] [CrossRef]
  36. Takahashi, J.S.; Hong, H.K.; Ko, C.H.; McDearmon, E.L. The genetics of mammalian circadian order and disorder: Implications for physiology and disease. Nat. Rev. Genet. 2008, 9, 764–775. [Google Scholar] [CrossRef]
  37. Peschke, E.; Peschke, D.; Hammer, T.; Csernus, V. Influence of melatonin and serotonin on glucose-stimulated insulin release from perifused rat pancreatic islets in vitro. J. Pineal Res. 1997, 23, 156–163. [Google Scholar] [CrossRef]
  38. Picinato, M.C.; Haber, E.P.; Cipolla-Neto, J.; Curi, R.; de Oliveira Carvalho, C.R.; Carpinelli, A.R. Melatonin inhibits insulin secretion and decreases PKA levels without interfering with glucose metabolism in rat pancreatic islets. J. Pineal Res. 2002, 33, 156–160. [Google Scholar] [CrossRef] [Green Version]
  39. Lowe, M.; Lage, J.; Paatela, E.; Munson, D.; Hostager, R.; Yuan, C.; Katoku-Kikyo, N.; Ruiz-Estevez, M.; Asakura, Y.; Staats, J.; et al. CRY2 Is Critical for Circadian Regulation of Myogenic Differentiation by Bclaf1-Mediated mRNA Stabilization of Cyclin D1 and Tmem176b. Cell Rep. 2018, 22, 2118–2132. [Google Scholar] [CrossRef] [Green Version]
  40. Bekki, H.; Duffy, T.; Okubo, N.; Olmer, M.; Alvarez-Garcia, O.; Lamia, K.; Kay, S.; Lotz, M. Suppression of circadian clock protein cryptochrome 2 promotes osteoarthritis. Osteoarthr. Cartil. 2020, 28, 966–976. [Google Scholar] [CrossRef]
Figure 1. The distribution map of cattle carcass traits involved in this study.
Figure 1. The distribution map of cattle carcass traits involved in this study.
Animals 12 01616 g001
Figure 2. The PCR amplification procedure.
Figure 2. The PCR amplification procedure.
Animals 12 01616 g002
Figure 3. Genotyping of CRY2-P6 and CRY2-P7. (a) The position and gene structure map of CRY2; (be) The electrophoresis pattern and sequence chromatograms of the CRY2-P6 and CRY2-P7 loci in the cattle CRY2 gene.
Figure 3. Genotyping of CRY2-P6 and CRY2-P7. (a) The position and gene structure map of CRY2; (be) The electrophoresis pattern and sequence chromatograms of the CRY2-P6 and CRY2-P7 loci in the cattle CRY2 gene.
Animals 12 01616 g003
Figure 4. Correlation analysis diagram of carcass traits. (ac) Relationship between the CRY2-P6 and CRY2-P7 loci in the CRY2 gene and carcass traits in the SDBCGR population. (a) CRY2-P6, male; (b) CRY2-P6, female; (c) CRY2-P7, male.
Figure 4. Correlation analysis diagram of carcass traits. (ac) Relationship between the CRY2-P6 and CRY2-P7 loci in the CRY2 gene and carcass traits in the SDBCGR population. (a) CRY2-P6, male; (b) CRY2-P6, female; (c) CRY2-P7, male.
Animals 12 01616 g004aAnimals 12 01616 g004b
Figure 5. Linkage disequilibrium plot of the two indel loci in the CRY2 gene.
Figure 5. Linkage disequilibrium plot of the two indel loci in the CRY2 gene.
Animals 12 01616 g005
Figure 6. Haplotype frequencies of the CRY2 gene in the SDBCGR population (IP6-IP7: 0.779; IP6-DP7: 0.186; DP6-IP7: 0.034; DP6-DP7: 0.001).
Figure 6. Haplotype frequencies of the CRY2 gene in the SDBCGR population (IP6-IP7: 0.779; IP6-DP7: 0.186; DP6-IP7: 0.034; DP6-DP7: 0.001).
Animals 12 01616 g006
Table 1. PCR primer sequences of the cattle CRY2 gene.
Table 1. PCR primer sequences of the cattle CRY2 gene.
NamesPrimer Sequences (5′ to 3′)Product Sizes (bp)Location
P1-5-bp delF:CCCCACCACCAAAAAAAG
R:TGGATGGATGGCATCACC
197/192intron 1
P2-20-bp insF:GCCAGGAGGCCACAATCTG
R:ACCATGAGCCATAAACTTCCCA
227/247intron 1
P3-5-bp delF:TCCTTCTCCAACGTATGAAAGT
R:GAGACACAAGAGATGAGGGTTC
199/194intron 1
P4-15-bp delF:CTGGAGTCGTCCCTCATTGG
R:AGGTCTCACGATGACCTCCA
245/230intron 1
P5-8-bp insF: TTTCCTCCTGAGAGGACGGT
R: CATTCTGGCACGAGCTGAGT
250/258intron 1
P6-24-bp delF:AACTGAGAAGGTAAAGCCCTCC
R:AGGCAAATACCTCTGCAACC
244/220intron 5
P7-6-bp insF:GGGTTCGAGGAAATAGAGTGAGG
R:GCCATCAGGTAGGAAACACCT
306/312intron 5
P8-13-bp delF:GACACGGGCCGTCCTAAC
R:TCCGGGAAATCAAACGAGGC
227/214intron 11
Table 2. Analysis of population genetic parameters.
Table 2. Analysis of population genetic parameters.
Population Genetic ParametersFormulaPurpose
Ho H o = i = 1 n P i 2 Estimation of allele homozygosity
He H e = 1 i = 1 n P i 2 Estimation of allele heterozygosity
Ne N e = 1 / i = 1 n P i 2 Reflecting the interaction between alleles
PIC P I C = 1 i = 1 m P i 2 i = 1 m 1 j = i + 1 m 2 P i 2 P j 2 Estimation of marker gene polymorphism
Note: The above parameters are calculated using the SHEsis platform (http://analysis.biox.cn, accessed on 8 June 2021).
Table 3. Genetic diversities of the P6-24-bp deletion and the P7-6-bp insertion of the CRY2 gene.
Table 3. Genetic diversities of the P6-24-bp deletion and the P7-6-bp insertion of the CRY2 gene.
LociSizesGenotypic FrequenciesAllelic FrequenciesHWEPopulation Parameters
IIIDIDp-ValuesHoHeNePIC
CRY2-P67050.933
(n = 658)
0.067
(n = 47)
0.9670.033p > 0.050.9360.0641.0690.062
CRY2-P77020.622
(n = 437)
0.378
(n = 265)
0.8110.189p < 0.050.6940.3061.4410.259
Table 4. Relationship between the CRY2-P6 locus and carcass traits in SDBCGR.
Table 4. Relationship between the CRY2-P6 locus and carcass traits in SDBCGR.
Carcass TraitsObserved Genotypes (MEAN ± SE)p-Value
IIID
Male (n = 195)
Gross weight (kg)765.36 ± 7.93 (n = 181)669.73 ± 24.90 (n = 11)0.004
Back tendon (kg)0.85 ± 0.02 (n = 91)0.72 ± 0.05 (n = 6)0.041
Chuck tender (kg)3.60 ± 0.07 (n = 91)2.71 ± 0.21 (n = 6)0.002
Right limbs weight (kg)230.41 ± 3.14 (n = 91)201.00 ± 15.02 (n = 5)0.036
Money tendon (kg)1.49 ± 0.03 (n = 91)1.15 ± 0.13 (n = 6)0.002
Flank steak (kg)7.69 ± 0.13 (n = 90)6.13 ± 0.48 (n = 6)0.004
Triangle flank (kg)7.13 ± 0.13 (n = 106)6.08 ± 0.35 (n = 9)0.020
Ribeye (kg)12.38 ± 0.19 (n = 105)11.09 ± 0.32 (n = 10)0.044
High rib (kg)18.72 ± 0.48 (n = 106)13.25 ± 1.56 (n = 10)0.001
Beef tenderloin (kg)6.10 ± 0.09 (n = 103)5.69 ± 0.12 (n = 10)0.012
Female (n = 512)
Chuck tender (kg)3.01 ± 0.03 (n = 376)2.79 ± 0.11 (n = 33)0.034
Thick flank (kg)11.41 ± 0.12 (n = 376)10.38 ± 0.38 (n = 33)0.017
Right limbs weight (kg)209.08 ± 1.75 (n = 377)196.60 ± 5.38 (n = 33)0.042
Boneless short ribs (kg)1.24 ± 0.02 (n = 372)1.10 ± 0.06 (n = 32)0.033
Note: (p < 0.05) refers to significant differences among the genotypes.
Table 5. Relationship between the CRY2-P7 locus and carcass traits in SDBCGR.
Table 5. Relationship between the CRY2-P7 locus and carcass traits in SDBCGR.
Carcass TraitsObserved Genotypes (MEAN ± SE)p-Value
IIID
Male (n = 195)
Beef tongue (kg)1.44 ± 0.07 (n = 59)1.28 ± 0.04 (n = 33)0.040
The length of ribeye (cm)9.54 ± 0.53 (n = 8)7.38 ± 0.46 (n = 5)0.017
Brisket (kg)9.24 ± 0.34 (n = 68)7.69 ± 0.43 (n = 46)0.005
Female (n = 512)
Meat tendon (kg)4.74 ± 0.40 (n = 186)6.00 ± 0.47 (n = 117)0.045
Shoulder clod (kg)1.18 ± 0.03 (n = 255)1.28 ± 0.04 (n = 150)0.021
Note: (p < 0.05) refers to significant differences among the genotypes.
Table 6. Combined genotype frequency of CRY2 in SDBCGR.
Table 6. Combined genotype frequency of CRY2 in SDBCGR.
GenderCombined Genotype NameCombined Genotype TypeGenotype Frequency
MaleCombined-1II-II0.566
Combined-2II-ID0.377
Combined-3ID-II0.047
Combined-4ID-ID0.010
FemaleCombined-1II-II0.571
Combined-2II-ID0.360
Combined-3ID-II0.055
Combined-4ID-ID0.014
Table 7. Combined genotype analysis of the CRY2-P6 deletion and CRY2-P7 insertion loci in SDBCGR (male).
Table 7. Combined genotype analysis of the CRY2-P6 deletion and CRY2-P7 insertion loci in SDBCGR (male).
Weight of Carcass TraitsCombined Genotype (MEAN ± SE)p-Value
II-IIII-IDID-II
Male (n = 195)
Gross weight (kg)769.97 a ± 10.18
(n = 108)
760.32 a ± 12.86
(n = 72)
671.67 b ± 30.48
(n = 9)
0.033
Money tendon (kg)1.49 a ± 0.04
(n = 57)
1.48 a ± 0.39
(n = 33)
1.14 b ± 0.16
(n = 5)
0.025
Chuck tender (kg)3.61 a ± 0.09
(n = 57)
3.52 b ± 0.10
(n = 33)
2.93 b ± 0.12
(n = 5)
0.019
Flank steak (kg)7.77 a ± 0.16
(n = 57)
7.56 a ± 0.23
(n = 32)
6.39 b ± 0.49
(n = 5)
0.018
Brisket (kg)9.66 a ± 0.32
(n = 59)
7.69 ab ± 0.43
(n = 45)
7.31 b ± 1.38
(n = 7)
0.001
Triangle flank (kg)7.42 a ± 0.16
(n = 60)
6.72 ab ± 0.19
(n = 45)
6.10 b ± 0.40
(n = 8)
0.004
High rib (kg)19.32 a ± 0.63
(n = 61)
17.71 a ± 0.75
(n = 44)
13.79 b ± 1.71
(n = 8)
0.004
Note: Different superscript letters (lower-case letters: p < 0.05) refer to significant differences among the genotypes.
Table 8. Combined genotype analysis of the CRY2-P6 deletion and CRY2-P7 insertion loci in SDBCGR (female).
Table 8. Combined genotype analysis of the CRY2-P6 deletion and CRY2-P7 insertion loci in SDBCGR (female).
Weight of Carcass TraitsCombined Genotype (LSMa ± SE)p-Value
II-IIII-IDID-IIID-ID
Female (n = 506)
Gross weight (kg)688.74 a ± 4.81
(n = 287)
672.02 b ± 6.13
(n = 182)
650.50 b ± 11.77
(n = 28)
679.43 ab ± 41.60 (n = 7)0.034
Left limbs weight (kg)210.15 a ± 2.09
(n = 231)
205.75 a ± 2.92
(n = 144)
191.37 b ± 4.91
(n = 26)
211.33 ab ± 16.61 (n = 6)0.041
Right limbs weight (kg)210.66 ab ± 2.16
(n = 231)
206.42 ab ± 2.99
(n = 144)
190.73 ac± 5.05
(n = 26)
210.92 a ± 15.80 (n = 6)0.035
Chuck tender (kg)3.00 ab ± 0.04
(n = 231)
3.02 ab ± 0.05
(n = 143)
2.67 ac ± 0.11
(n = 26)
3.14 a ± 0.33
(n = 6)
0.034
Thick flank (kg)11.37 a ± 0.16
(n = 231)
11.47 a ± 0.19
(n = 143)
10.02 b ± 0.38
(n = 26)
11.06 ab ± 0.93
(n = 6)
0.037
Shoulder clod (kg)1.17 b ± 0.03
(n = 230)
1.20 b ± 0.0
4 (n = 144)
1.20 b ± 0.11
(n = 25)
1.99 a± 0.22
(n = 6)
3.9 × 105
Flank steak (kg)6.82 a ± 0.09
(n = 230)
6.75 a ± 0.11
(n = 140)
6.10 b ± 0.25
(n = 26)
7.52 a ± 0.54
(n = 6)
0.029
Outside flat (kg)18.16 ab ± 0.49
(n = 224)
18.00 ab ± 0.66
(n = 139)
13.75 ac ± 1.44
(n = 26)
17.17 a ± 1.42
(n = 6)
0.041
Note: Different superscript letters (lower-case letters: p < 0.05) refer to significant differences among the genotypes.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Li, X.; Jiang, E.; Zhang, K.; Zhang, S.; Jiang, F.; Song, E.; Chen, H.; Guo, P.; Lan, X. Genetic Variations within the Bovine CRY2 Gene Are Significantly Associated with Carcass Traits. Animals 2022, 12, 1616. https://doi.org/10.3390/ani12131616

AMA Style

Li X, Jiang E, Zhang K, Zhang S, Jiang F, Song E, Chen H, Guo P, Lan X. Genetic Variations within the Bovine CRY2 Gene Are Significantly Associated with Carcass Traits. Animals. 2022; 12(13):1616. https://doi.org/10.3390/ani12131616

Chicago/Turabian Style

Li, Xuelan, Enhui Jiang, Kejing Zhang, Sihuan Zhang, Fugui Jiang, Enliang Song, Hong Chen, Peng Guo, and Xianyong Lan. 2022. "Genetic Variations within the Bovine CRY2 Gene Are Significantly Associated with Carcass Traits" Animals 12, no. 13: 1616. https://doi.org/10.3390/ani12131616

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop