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19 December 2024

Multiplex Detection of SNPs for Genetic Monitoring in Laboratory Mice by Luminex xTAG Assay

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1
Division of Laboratory Animal Monitoring, National Institutes for Food and Drug Control, Beijing 102629, China
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R&D Center, Beijing Minhai Biotechnology Co., Ltd., Beijing 102629, China
3
China National Rodent Laboratory Animal Resources Center, Beijing 102629, China
*
Authors to whom correspondence should be addressed.
Genes2024, 15(12), 1622;https://doi.org/10.3390/genes15121622
This article belongs to the Section Animal Genetics and Genomics
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Abstract

Background: The genetic quality of laboratory mice may have a direct impact on the results of research. Therefore, it is essential to improve genetic monitoring methods to guarantee research quality. However, few current methods boast high efficiency, high throughput, low cost, and general applicability at the same time. Methods: First, we got 34 SNP loci from previous studies for inbred strains and screened out 15 loci with good polymorphism for outbred groups from these 34 loci. Then, by using the Luminex xTAG assay, we tested inbred strains and outbred groups. Results: We tested commonly used inbred strains and five DNA samples from the International Council for Laboratory Animal Science, obtaining correct genotyping results. Additionally, some loci were potentially confirmed to be useful for distinguishing C57BL/6 and BALB/c mouse substrains. Furthermore, we tested three outbred groups and analyzed the genetic structure, and we compared the results of the SNP markers by xTAG assay to the STR markers by PCR, the trends of the three groups are the same. Conclusions: In our studies, the panels could meet the requirements for method promotion and provide a good choice for the genetic monitoring of inbred and outbred mice.

1. Introduction

Laboratory mice are commonly used in biomedical and behavioral research due to their significant benefits to human health [1,2]. Due to their low cost, small size, and availability, laboratory mice play an irreplaceable role in the field of biomedicine [3]. Many studies have attached great importance to genetic structural analysis and quality control to ensure the continued genetic diversity of a population [4,5,6].
The regular genetic quality monitoring of laboratory mice can provide reliable information and guidance for breeding and reproduction. Compared with outbred stocks, inbred strains are more stable, have less phenotypic variation, are better defined, are more uniform, have more extensive background data, and have a wider international distribution than outbred stocks [7,8]. The methods for breeding inbred strains and outbred stocks are completely different. Maintaining homogeneity of the genetic background is critical for breeding inbred strains, whereas heterozygosity is the principal emphasis in breeding outbred mice [9,10]. With the progress of molecular biology technology, DNA molecular markers have become the primary method of monitoring the genetic quality of laboratory mice. Most researchers have used microsatellite markers and single-nucleotide polymorphism (SNP) markers to detect genetic quality [4,11,12,13].
Various SNP genotyping techniques have been developed to improve detection accuracy, time, and price [14]. However, current SNP genotyping methods are characterized by high failure rates and low applicability [13,15,16]. Therefore, in the current study, we aimed to develop novel panels of SNP markers based on allele-specific primer extension (ASPE) and MagPlex-TAG microspheres. This could be used for genetic monitoring in inbred and outbred laboratory mice, which will lay the foundation for the genetic quality control of laboratory mice.

2. Materials and Methods

2.1. Animal Sample

Inbred mice were selected from Beijing and Shanghai for this study.
We collected 8 inbred strains from Beijing—C57BL/6JNifdc, C57BL/6JNifdc-bg, BALB/cJNifdc, BALB/cCrSlcNifdc, SCID/Nifdc, Nu/JNifdc, C3H/HeJNifdc, and DBA/2Nifdc—which were from the National Rodent Laboratory Animal Resources Center. The production license was SCXK (Jing)2022-0002.
We purchased C57BL/6, BALB/c, and NOD-SCID from Beijing HFK Bioscience Co., Ltd., Beijing, China, the production license was SCXK (Jing) 2019-0008.
We bought C57BL/6 and BALB/c from SPF (Beijing) Biotechnology Co., Ltd., Beijing, China, whose production license was SCXK (Jing) 2019-0010.
We procured the BALB/c from Beijing Vital River Laboratory Animal Technology Co., Ltd., Beijing, China, and the C57BL/6 from Peking University Health Science Center Department of Laboratory Animal Science. The production licenses were SCXK (Jing) 2021-0006 and SCXK (Jing) 2021-0013, respectively.
Three inbred strains, C57BL/6, BALB/c, and C3H/HeJ, were selected from National Rodent Laboratory Animal Resources, Shanghai Branch. The production license was SCXK (Hu)2017-0005.
Also, we obtained five DNA samples from the International Council for Laboratory Animal Science (ICLAS): C57BL/6J, C57BL/6NTac, BALB/cAnNTac, BALB/cJ, and C3H/HeNTac.
We obtained the KM/Nifdc, ICR/Nifdc, and NIH/Nifdc outbred groups from the National Rodent Laboratory Animal Resources Center were used, with 30 samples and half-sex from each strain.
All experiments followed the 3R principle and were approved by the Institutional Animal Care and the Committee of the National Institutes for Food and Drug Control 2022 (B)025.

2.2. SNP Locus Selection and Primer Design

We developed our approach based on previous reports [4] and information from the Central Institute for Experimental Animals (https://www.ciea.or.jp/en/, accessed on 1 March 2022). Using Primer Premier 6.0 software, we designed multiplex PCR primers and ASPE primers. An 801-base-pair (bp) template sequence, which included the SNP base and 400 bp of flanking regions, was input into the program. The 50 bp upstream and downstream of the SNPs were excluded from primer selection. The amplifications were designed to be relatively small with similar melting temperatures to facilitate efficient amplification in multiplex PCR [17,18]. All ASPE primers targeted both wild-type and mutant alleles through allele-specific nucleotides at the 3′ end and incorporated unique TAGs at the 5′ end, which were in reverse complement to the anti-TAGs on the xTAG beads.

2.3. DNA Extraction

The phenol–chloroform extraction method was used to extract DNA from tails [19]. All DNA concentrations were diluted to 50 ng/μL and stored at −20 °C.

2.4. Multiplex PCR Procedure and Agarose Gel Electrophoresis

The multiplex PCR was performed in a 30 μL reaction volume containing 15 μL of 2× Hotstart PCR Master Mix without dye by Sangon Biotech Co., Ltd., Shanghai, China, 10 μL of Sterilized ddH2O, 3 μL of a mixture of 10 pmol PCR primer, and 2 μL 50 ng of the extracted DNA template. The PCR protocol was as follows: a first extension at 96 °C for 30 s; a second at a suitable temperature for 1min; extensions at 72 °C for 30 s, 30 cycles; and a final extension at 72 °C for 8 min. All assays were run with positive and negative controls.
Amplified products were electrophoresed on a 2.5% agarose gel at 135 V for 35 min and stored at −20 °C for further analysis.

2.5. Exonuclease I-Shrimp Alkaline Phosphatase Treatment

After the multiplex PCR reaction, there are remaining amplified dNTPs, primers, single-stranded products, etc., which affect the subsequent reaction. Exonuclease I (Exo) was used to remove the remaining amplified primers and single-stranded products, and shrimp alkaline phosphatase (SAP) was used to remove the remaining primers, single-stranded DNA, and remaining dNTPs, especially dCTP, from the PCR products. Finally, 1 μL of Exo-SAP mixture was used to inactivate the enzyme, followed by a 30 min reaction at 37 °C and a 15 min reaction at 80 °C.

2.6. Allele-Specific Primer Extension (ASPE) Reaction

The total reaction system comprised 20 μL, containing 5 μL of purified multiplex PCR product, 1 μL of 10×TaqTM Hot Start DNA polymerase buffer (Sangon Biotech Co., Ltd., Shanghai, China), 0.25 μL of 400 μmol/L Biotin-dCTP (Thermo Fisher Scientific, Waltham, MA, USA), 1 μL of 100 μmol/L dATP/ dGTP/dTTP mix(Thermo Fisher Scientific, Waltham, MA, USA), 0.15 μL of 5 U/μL TaqTM Hot Start DNA polymerase (Sangon Biotech Co., Ltd., Shanghai, China), 1 μL of TAG-ASPE primer mix (containing 500 nmol/L of each TAG-ASPE primer), and 10.01 μL of dd H2O. This was mixed and centrifuged at a low speed (3000× g, 10 s), and the ASPE conditions was as follows: 94 °C for 30 s, 54 °C for 1 min, and 74 °C 2 min, 30 cycles.

2.7. Hybridization and Data Analysis

MagPlex-TAG microspheres were purchased from Luminex(Austin, TX, USA). Nucleic acid hybridization was performed in a 25 μL reaction volume containing 2.5 μL of ASPE reaction product and 22.5 μL of a working microsphere mixture, which included 2500 beads of each target-specific microsphere. The hybridization conditions were set at 96 °C for 90 s, 37 °C for 40 min. Subsequently, 100 μL of 1× SAPE buffer containing 8 μg/mL SAPE (Thermo Fisher Scientific, Waltham, MA, USA) was added, and the mixture was incubated at 37 °C for 20 min. The products were analyzed using the Luminex 200 detection system immediately after hybridization.
The Luminex 200 detection system (xPONENT3.1 software) provided median fluorescence intensity (MFI) values for all tested samples. Allelic MFI ratio = MFIcalled allele/(MFIwild allele + MFImutant allele). The result was performed according to the genotyping criteria provided by Luminex: MFI ratios above 0.75 or below 0.25 for wild-type or pure mutant type and between 0.25 and 0.75 for heterozygous mutant type.
For outbred groups, after we obtained the SNP genotyping results of 3 outbred groups, we used POPGENE 32 software version 1.0.0.0 [20] to calculate the observed number of alleles (Na), effective number of alleles (Ne), observed heterozygosity (Obs het), expected heterozygosity (Exp Het), average heterozygosity (Ave Het), and Shannon′s information index (SI); SNP loci were tested for polymorphism information content (PIC) by PIC-Calc 0.6 [21].

3. Results

3.1. SNP Locus Selection

We obtained 34 loci that could be stably amplified in inbred strains. We screened out 15 loci with good polymorphism for outbred groups from these 34 loci. Loci in these panels would be candidates for the final SNP marker evaluation systems. All SNP locus information is shown in Table 1.
Table 1. Number of alleles, location, and amplification primer sequences.
Then, we randomly divided 34 loci into four panels [22]; the multiplex PCR primers are shown in Table 2(1)–(4), and the ASPE primers are shown in Table 3(1)–(4).
Table 2. (1) Panel A PCR primer sequences and amplification conditions; (2) Panel B PCR primer sequences and amplification conditions; (3) Panel C PCR primer sequences and amplification conditions; (4) Panel D PCR primer sequences and amplification conditions.
Table 3. (1) Panel A TAG-ASPE primer sequences; (2) Panel B TAG-ASPE primer sequences; (3) Panel C TAG-ASPE primer sequences; (4) Panel D TAG-ASPE primer sequences.

3.2. Result of Luminex xTAG Assay

Examples of the corrected data for the two inbred strains, BALB/c and C57BL/6J, used to develop this assay are shown in Table 4. SNPs were called when the corrected MFI was three times higher than the negative samples. In Table 4, the MFI values of the called alleles ranged from 1198.5 to 9184.5, while the MFI values of uncalled alleles ranged from 0 to 449.5. These results demonstrate that the Luminex xTAG Assay is a reliable tool for accurately identifying all targeted SNPs.
Table 4. MFI values of each microsphere set corresponding to each allele of C57BL/6JNifdc and BALB/cJNifdc.

3.3. Analysis of Inbred Strains SNP Loci

We calculated the allele frequency for each strain based on the MFI detection results and determined the genotypes of each strain at 34 loci. The genotyping results showed that all strains were homozygous at all 34 loci, with no heterozygotes present. The specific genotyping results are shown in Table 5.
Table 5. (1) The genotyping results of all samples; (2) The genotyping results of BALB/c samples; (3) The genotyping results of C57BL/6 samples.
The genotyping results at the 34 SNP loci were used to compare the same strains from different rodent laboratory animal centers, and the comparison results are shown in Table 5(1).
Since C57BL/6 and BALB/c are the most widely used inbred mouse strains [23,24,25,26,27], we compared various sources of these strains, with the results shown in Table 5(2) and (3). From Table 5(2), it can be seen that the BALB/cJNifdc strain from BJ1 had different genotyping results at rs3712692, rs3706082, and rs3656801 compared to others.
Meanwhile, Table 5(3) reveals that the C57BL/6NTac strain exhibited differences at the loci rs3709624, rs3659787, rs3722313, rs3702158, and rs3724876 compared to C57BL/6 mice from other institutes. This suggests that C57BL/6NTac has diverged into substrains of C57BL/6, and these five loci can be used to differentiate between the substrains.

3.4. Population Genetic Structure Analysis

We obtained genetic data of three outbred groups at 15 loci. In KM mice, the observed number of alleles was 1.7333, the effective number of alleles was 1.4246, and the Shannon′s information index was 0.3749. Furthermore, the average heterozygosity was 0.2503. The average polymorphism information content (PIC) was 0.2006. The results are shown in Table 6(1).
Table 6. (1) The Na, Ne, Obs Het, Exp Het, Ave Het, SI, and PIC of the KM group; (2) The Na, Ne, Obs Het, Exp Het, Ave Het, SI, and PIC of the NIH group; (3) The Na, Ne, Obs Het, Exp Het, Ave Het, SI, and PIC of the ICR group.
In NIH mice, the observed number of alleles was 1.6667, the effective number of alleles was 1.2954, and the Shannon′s information index was 0.2829. Furthermore, the average heterozygosity was 0.1831 and the PIC was 0.1495. The specific data of the NIH group are shown in Table 6(2).
In ICR mice, the observed number of alleles, the effective number of alleles, the Shannon′s information index, the average heterozygosity, and the PIC were 1.7333, 1.3399, 0.3203, 0.2068, and 0.1688, respectively. The specific results are shown in Table 6(3).

3.5. Comparison of Sanger Sequencing and Luminex xTAG Assay

Currently, the most widely used SNP detection method is Sanger Sequencing (SS) [28]. Based on this, a comparison between SS and Luminex xTAG Assay is presented in Table 7.
Table 7. The comparison of Sanger Sequencing and Luminex xTAG Assay.

4. Discussion

Laboratory mice play an irreplaceable role in the field of biomedicine. For their contributions to scientific and technological development, they are perceived as the touchstone and living precision instruments in research.
The stability of mouse quality is directly related to the repeatability of research results [29,30]. However, this is often overlooked, despite being a very important factor. Therefore, the genetic quality control of mice is the basic guarantee of scientific research quality.
Traditional methods such as biochemical markers include large sample consumption, time-consuming experimental procedures, and complex outcome discrimination. With the progress of molecular biology technology, one of the greatest improvements of molecular markers over biochemical markers is that laboratory animals no longer must be euthanized [9], and compared with Short Tandem Repeats (STRs), SNPs are more stable; the mutation rate is only 10−9. Furthermore, SNP detection requires lower sample quality than STRs. Since SNPs are biallelic markers, they can be detected automatically based on signals such as “+/−” or “1/0” [14,31]. This feature makes the SNP marker a better tool for achieving an automated and high-throughput analysis [14,32,33,34]. Based on the above advantages, the SNP marker-based assay was chosen in this study for laboratory mice.
Some platforms and methods exist for SNP-based genotyping, including ultra-high-throughput technologies like Illumina and Affymetrix. However, only a few of them are simultaneously flexible, fast (<1 day), cost-effective, and capable of simultaneously detecting multiplexed signals at medium-to high-throughput [35,36].
Luminex is a new type of biomolecular detection technology that can simultaneously detect multiple biomolecules such as antigens [37], antibodies [38], and nucleic acid [13] by flow cytometry [39]. It has emerged that Luminex not only offers the benefits of high throughput but also affords the advantages of high sensitivity, smaller sample volumes, and lower costs [40,41,42], which are suitable for multiple-sample analysis. The inside of the microsphere is stained with a precise number of two fluorescent agents of different spectra. This method allows for the simultaneous measurement of up to 100 different microspheres, each with a unique spectral address, in a reaction vessel. [17,38,43,44,45]. A fourth fluorescent pigment binds to the reporter molecule to detect ionic molecular interactions occurring on the surface of the microsphere. Each set of microspheres has multiple readings, providing valid and reliable statistics [46].
In this study, the method we established not only detected the international reference standards of ICLAS but also detected the commonly used strains of domestic rodent laboratory animal centers. The consistent genotyping results showed that the laboratory mice in various centers now have good genetic quality. Some strains have different genotyping results at individual loci; not only does this hint that these loci could indeed distinguish the substrains of BALB/c mice and C57BL/6 mice but it also suggests that we should pay more attention to and regularly monitor the genetic background of laboratory mice in different regions to ensure the reliability of our experimental results.
We calculated the average effective allele number, average effective heterozygosity, average Shannon′s index, PIC and others to evaluate genetic variation in three outbred groups. In addition, we compared the results of the SNP markers by xTAG assay to the STR markers by PCR, and it was found that whether using SNP markers or STR markers, the trends of the three groups are the same, namely KM > ICR > NIH. This result proves that our selected loci are very reliable for analysis in outbred groups. However, the number of SNP loci selected is small in this study, and the number of SNPs for screening outbred stocks should be expanded in subsequent studies to make the method more widely applicable to them.

5. Conclusions

In conclusion, the combination of SNP loci selected in this paper provides a good choice for the genetic monitoring of the quality and the population genetic structure of laboratory mice.

Author Contributions

Conceptualization, J.Z. and J.W.; data curation, J.Z. and H.L.; methodology, J.Z. and H.W.; project administration, J.W. and B.Y.; software, H.L. and L.Z.; writing—original draft preparation, J.Z. and J.W.; writing—review and editing, J.Z., J.W., R.F. and B.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by National Key R&D Program of China to Jie Wei (Grant No. 2021YFF0703200).

Institutional Review Board Statement

The animal study protocol was approved by the Institutional Animal Care and used Committee of the National Institutes For Food And Drug Control 2022 (B)025.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions.

Acknowledgments

The authors would like to thank the National Rodent Laboratory Animal Resources Center and National Rodent Laboratory Animal Resources, Shanghai Branch for providing the samples used for this study.

Conflicts of Interest

Author Jiaqi Zhou was employed by the company Beijing Minhai Biotechnology Co., Ltd., Beijing, China. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Ahangari Cohan, R.; Nouri Inanlou, D.; Samiee Aref, M.H.; Zeinali, S.; Farhoudi, R. Microsatellite Marker Analysis for Laboratory Mice Profiling. Adv. Biomed. Res. 2019, 8, 40. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  2. Wade, C.M.; Daly, M.J. Genetic variation in laboratory mice. Nat. Genet. 2005, 37, 1175–1180. [Google Scholar] [CrossRef]
  3. Gretebeck, L.M.; Subbarao, K. Animal models for SARS and MERS coronaviruses. Curr. Opin. Virol. 2015, 13, 123–129. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  4. Petkov, P.M.; Cassell, M.A.; Sargent, E.E.; Donnelly, C.J.; Robinson, P.; Crew, V.; Asquith, S.; Haar, R.V.; Wiles, M.V. Development of a SNP genotyping panel for genetic monitoring of the laboratory mouse. Genomics 2004, 83, 902–911. [Google Scholar] [CrossRef] [PubMed]
  5. Zhang, X.; He, Y.; Zhang, W.; Wang, Y.; Liu, X.; Cui, A.; Gong, Y.; Lu, J.; Liu, X.; Huo, X.; et al. Development of Microsatellite Marker System to Determine the Genetic Diversity of Experimental Chicken, Duck, Goose, and Pigeon Populations. Biomed. Res. Int. 2021, 2021, 8851888. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  6. Bryda, E.C.; Riley, L.K. Multiplex microsatellite marker panels for genetic monitoring of common rat strains. J. Am. Assoc. Lab. Anim. Sci. 2008, 47, 37–41. [Google Scholar] [PubMed]
  7. Tuttle, A.H.; Philip, V.M.; Chesler, E.J.; Mogil, J.S. Comparing phenotypic variation between inbred and outbred mice. Nat. Methods 2018, 15, 994–996. [Google Scholar] [CrossRef] [PubMed]
  8. Festing, M.F. Inbred strains should replace outbred stocks in toxicology, safety testing, and drug development. Toxicol. Pathol. 2010, 38, 681–690. [Google Scholar] [CrossRef]
  9. Fahey, J.R.; Katoh, H.; Malcolm, R.; Perez, A.V. The case for genetic monitoring of mice and rats used in biomedical research. Mamm. Genome 2013, 24, 89–94. [Google Scholar] [CrossRef] [PubMed]
  10. Shang, H.; Wei, H.; Yue, B.; Xu, P.; Huang, H. Microsatellite analysis in two populations of Kunming mice. Lab. Anim. 2009, 43, 34–40. [Google Scholar] [CrossRef] [PubMed]
  11. Mekada, K.; Hirose, M.; Murakami, A.; Yoshiki, A. Development of SNP markers for C57BL/6N-derived mouse inbred strains. Exp. Anim. 2014, 64, 91–100. [Google Scholar] [CrossRef] [PubMed]
  12. Abe, K.; Murakami, A.; Nakamura, S.; Nakata, H.; Moriwaki, K.; Obata, Y.; Yoshiki, A. Genetic differences among C57BL/6 substrains. Exp. Anim. 2009, 58, 141–149. [Google Scholar]
  13. Huang, C.W.; Lin, Y.T.; Ding, S.T.; Lo, L.L.; Wang, P.H.; Lin, E.C.; Liu, F.W.; Lu, Y.W. Efficient SNP Discovery by Combining Microarray and Lab-on-a-Chip Data for Animal Breeding and Selection. Microarrays 2015, 4, 570–595. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  14. Kim, S.; Misra, A. SNP genotyping: Technologies and biomedical applications. Annu. Rev. Biomed. Eng. 2007, 9, 289–320. [Google Scholar] [CrossRef] [PubMed]
  15. Tsuchihashi, Z.; Dracopoli, N. Progress in high throughput SNP genotyping methods. Pharmacogenomics J. 2002, 2, 103–110. [Google Scholar] [CrossRef]
  16. Syvänen, A.-C. Accessing genetic variation: Genotyping single nucleotide polymorphisms. Nat. Rev. Genet. 2001, 2, 930–942. [Google Scholar] [CrossRef]
  17. Holmes, A.; McAllister, G.; McAdam, P.R.; Hsien Choi, S.; Girvan, K.; Robb, A.; Edwards, G.; Templeton, K.; Fitzgerald, J.R. Genome-wide single nucleotide polymorphism-based assay for high-resolution epidemiological analysis of the methicillin-resistant Staphylococcus aureus hospital clone EMRSA-15. Clin. Microbiol. Infect. 2014, 20, O124–O131. [Google Scholar] [CrossRef] [PubMed]
  18. Schoske, R.; Vallone, P.M.; Ruitberg, C.M.; Butler, J.M. Multiplex PCR design strategy used for the simultaneous amplification of 10 Y chromosome short tandem repeat (STR) loci. Anal. Bioanal. Chem. 2003, 375, 333–343. [Google Scholar] [CrossRef] [PubMed]
  19. Barnett, R.; Larson, G. A phenol–chloroform protocol for extracting DNA from ancient samples. In Ancient DNA: Methods and Protocols; Shapiro, B., Hofreiter, M., Eds.; Humana Press: Totowa, NJ, USA, 2012; pp. 13–19. [Google Scholar]
  20. Nei, M. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. USA 1973, 70, 3321–3323. [Google Scholar] [CrossRef]
  21. Nagy, S.; Poczai, P.; Cernák, I.; Gorji, A.M.; Hegedűs, G.; Taller, J. PICcalc: An online program to calculate polymorphic information content for molecular genetic studies. Biochem. Genet. 2012, 50, 670–672. [Google Scholar] [CrossRef]
  22. Henegariu, O.; Heerema, N.; Dlouhy, S.; Vance, G.; Vogt, P. Multiplex PCR: Critical parameters and step-by-step protocol. Biotechniques 1997, 23, 504–511. [Google Scholar] [CrossRef]
  23. Soudi, S.; Zavaran-Hosseini, A.; Hassan, Z.M.; Soleimani, M.; Adegani, F.J.; Hashemi, S.M. Comparative study of the effect of LPS on the function of BALB/c and C57BL/6 peritoneal macrophages. Cell J. 2013, 15, 45. [Google Scholar] [PubMed]
  24. Santos, E.W.; de Oliveira, D.C.; Hastreiter, A.; da SILVA, G.B.; de Oliveira Beltran, J.S.; Tsujita, M.; Crisma, A.R.; Neves, S.M.P.; Fock, R.A.; Borelli, P. Hematological and biochemical reference values for C57BL/6, Swiss Webster and BALB/c mice. Braz. J. Vet. Res. Anim. Sci. 2016, 53, 138–145. [Google Scholar] [CrossRef]
  25. de Oliveira Beltran, J.S.; Tsujita, M.; Crisma, A.R.; Peris, S.M. Hematological and biochemical reference values for C57BL/6. Braz. J. Vet. Res. Anim. Sci 2016, 53, 138–145. [Google Scholar]
  26. Liu, T.; Matsuguchi, T.; Tsuboi, N.; Yajima, T.; Yoshikai, Y. Differences in expression of toll-like receptors and their reactivities in dendritic cells in BALB/c and C57BL/6 mice. Infect. Immun. 2002, 70, 6638–6645. [Google Scholar] [CrossRef]
  27. Trunova, G.; Makarova, O.; Diatroptov, M.; Bogdanova, I.; Mikchailova, L.; Abdulaeva, S. Morphofunctional characteristic of the immune system in BALB/c and C57BL/6 mice. Bull. Exp. Biol. Med. 2011, 151, 99–102. [Google Scholar] [CrossRef]
  28. Mouse Genome Sequencing Consortium. Initial sequencing and comparative analysis of the mouse genome. Nature 2002, 420, 520–562. [Google Scholar] [CrossRef]
  29. Burden, N.; Sewell, F.; Chapman, K. Testing chemical safety: What is needed to ensure the widespread application of non-animal approaches? PLoS Biol. 2015, 13, e1002156. [Google Scholar] [CrossRef] [PubMed]
  30. Gasper, D.J.; Suresh, M.; Kawaoka, Y. C57BL/6J and C57BL/6NJ mice are differentially susceptible to inflammation-associated disease caused by influenza A virus. Front. Microbiol. 2019, 9, 3307. [Google Scholar]
  31. Benavides, F.; Rulicke, T.; Prins, J.B.; Bussell, J.; Scavizzi, F.; Cinelli, P.; Herault, Y.; Wedekind, D. Genetic quality assurance and genetic monitoring of laboratory mice and rats: FELASA Working Group Report. Lab. Anim. 2020, 54, 135–148. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  32. Tsang, S.; Sun, Z.; Luke, B.; Stewart, C.; Lum, N.; Gregory, M.; Wu, X.; Subleski, M.; Jenkins, N.A.; Copeland, N.G.; et al. A comprehensive SNP-based genetic analysis of inbred mouse strains. Mamm. Genome 2005, 16, 476–480. [Google Scholar] [CrossRef] [PubMed]
  33. Vignal, A.; Milan, D.; SanCristobal, M.; Eggen, A. A review on SNP and other types of molecular markers and their use in animal genetics. Genet. Sel. Evol. 2002, 34, 275–305. [Google Scholar] [CrossRef] [PubMed]
  34. Syvänen, A.-C. Toward genome-wide SNP genotyping. Nat. Genet. 2005, 37, S5–S10. [Google Scholar] [CrossRef] [PubMed]
  35. Thierry, S.; Derzelle, S. Multiplexed genotyping of Bacillus anthracis by Luminex xMap suspension array. Methods Mol. Biol. 2015, 1247, 401–412. [Google Scholar] [CrossRef] [PubMed]
  36. Matsuda, K. PCR-based detection methods for single-nucleotide polymorphism or mutation: Real-time PCR and its substantial contribution toward technological refinement. Adv. Clin. Chem. 2017, 80, 45–72. [Google Scholar] [PubMed]
  37. Navidad, J.F.; Griswold, D.J.; Gradus, M.S.; Bhattacharyya, S. Evaluation of Luminex xTAG gastrointestinal pathogen analyte-specific reagents for high-throughput, simultaneous detection of bacteria, viruses, and parasites of clinical and public health importance. J. Clin. Microbiol. 2013, 51, 3018–3024. [Google Scholar] [CrossRef] [PubMed]
  38. Wu, W.; Zhang, S.; Qu, J.; Zhang, Q.; Li, C.; Li, J.; Jin, C.; Liang, M.; Li, D. Simultaneous detection of IgG antibodies associated with viral hemorrhagic fever by a multiplexed Luminex-based immunoassay. Virus Res. 2014, 187, 84–90. [Google Scholar] [CrossRef] [PubMed]
  39. Kofoed, K.; Schneider, U.V.; Scheel, T.; Andersen, O.; Eugen-Olsen, J. Development and validation of a multiplex add-on assay for sepsis biomarkers using xMAP technology. Clin. Chem. 2006, 52, 1284–1293. [Google Scholar] [CrossRef]
  40. Bourgey, M.; Lariviere, M.; Richer, C.; Sinnett, D. ALG: Automated genotype calling of Luminex assays. PLoS ONE 2011, 6, e19368. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  41. Zhang, G.; Cai, F.; Zhou, Z.; DeVos, J.; Wagar, N.; Diallo, K.; Zulu, I.; Wadonda-Kabondo, N.; Stringer, J.S.; Weidle, P.J.; et al. Simultaneous detection of major drug resistance mutations in the protease and reverse transcriptase genes for HIV-1 subtype C by use of a multiplex allele-specific assay. J. Clin. Microbiol. 2013, 51, 3666–3674. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  42. Reslova, N.; Michna, V.; Kasny, M.; Mikel, P.; Kralik, P. xMAP technology: Applications in detection of pathogens. Front. Microbiol. 2017, 8, 55. [Google Scholar] [CrossRef]
  43. Pickering, J.W.; McMillin, G.A.; Gedge, F.; Hill, H.R.; Lyon, E. Flow cytometric assay for genotyping cytochrome P450 2C9 and 2C19. Am. J. Pharmacogenom. 2004, 4, 199–207. [Google Scholar] [CrossRef] [PubMed]
  44. Lee, S.H.; Choi, H.B.; Yu, S.Y.; Chang, U.J.; Kim, C.K.; Kim, H.J. Detection of first-line anti-tuberculosis drug resistance mutations by allele-specific primer extension on a microsphere-based platform. Ann. Lab. Med. 2015, 35, 487–493. [Google Scholar] [CrossRef] [PubMed] [PubMed Central]
  45. Chen, J.; Iannone, M.A.; Li, M.-S.; Taylor, J.D.; Rivers, P.; Nelsen, A.J.; Slentz-Kesler, K.A.; Roses, A.; Weiner, M.P. A microsphere-based assay for multiplexed single nucleotide polymorphism analysis using single base chain extension. Genome Res. 2000, 10, 549–557. [Google Scholar] [CrossRef]
  46. Spierings, G.; Dunbar, S.A. Pharmacogenetics using Luminex(R) xMAP(R) technology: A method for developing a custom multiplex single nucleotide polymorphism mutation assay. Methods Mol. Biol. 2013, 1015, 115–126. [Google Scholar] [CrossRef] [PubMed]
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The Complete Mitochondrial Genome of the Luciocyprinus langsoni (Cypriniformes: Cyprinidae): Characterization, Phylogeny, and Genetic Diversity Analysis
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