A method for developing apodemus agrarius microsatellite loci based on apodemus agrarius genome sequence

Abstract

The application discloses a method for developing microsatellite loci of Apodemus agrarius based on a genome sequence of the Apodemus agrarius, which develops the microsatellite loci of the Apodemus agrarius through genome data, is used for genetic quality analysis of the Apodemus agrarius, and enriches genetic data of the Apodemus agrarius. Based on the genome sequence information of the Apodemus agrarius on NCBI, microsatellite markers are mined by using MISA software, primers are designed by using Primer 5.0 software according to site information, and finally 288 pairs of microsatellite primers are obtained, and 30 pairs of polymorphic primers are screened for population typing. After genome DNA extraction, PCR amplification and electrophoresis identification, STR scanning detection is carried out, and GenAlEx version 6.501 software is used to analyze the STR scanning results. In the 60 samples, 152 alleles are detected by using the 30 pairs of primers, the average number of alleles is 5.06667, the average observed heterozygosity is 0.59183, the average Shannon index is 1.2645, and the average polymorphic information content is 0.59797.

Description

Technical Field

[0001] This invention relates to a method for developing microsatellite loci of the Great Forest Mouse based on the genome sequence of the Great Forest Mouse, belonging to the field of biogenetics technology. Background Technology

[0002] Microsatellites, also known as simple repeat sequences (SSRs) or short tandem repeat sequences (STRs), are distributed throughout the genome of an organism. They are characterized by high polymorphism, conservation, codominance, and good repetition. They play an important role in the identification of strains and varieties of animals, plants, microorganisms, and cells. Feng Dandan et al. used genomic data to screen microsatellite loci in long-clawed gerbils for genetic quality analysis of inbred lines and closed populations. Liu Chengxiu et al. assessed the genetic polymorphism of tree shrew populations using microsatellite loci, and then performed genetic quality testing on tree shrews of each generation.

[0003] The Great Forest Field Mouse (Apodemus peninsulae), belonging to the genus Apodemus in the family Muridae of the order Rodentia, is a slender rodent that primarily feeds on the seeds and fruits of broad-leaved trees and is a common rodent species in Northeast China. When classifying species within the genus Apodemus, the Great Forest Field Mouse is classified as a member of the Apodemus group, with the Striped Field Mouse and the Great Forest Field Mouse being the most genetically distant. Due to maternal inheritance of mitochondrial DNA and intraspecific hybridization between individuals of two adjacent subspecies, subspecies classification of the Great Forest Field Mouse cannot rely solely on cytochrome b data; further analysis combining morphological and nuclear DNA characteristics is necessary.

[0004] Research on the use of wild animals as laboratory animals is an effective way to address the insufficiency and unsuitability of existing laboratory animal species. This research typically involves introducing individuals from wild animal populations into a laboratory environment, where they are acclimated and developed to the characteristics and traits required for laboratory experiments through long-term rearing and selection. To develop new laboratory animal species using the Great Field Mouse for scientific research, it is necessary to conduct studies on its basic biological and molecular biological indicators. As a special type of experimental material, the standardization of laboratory animals has always been highly valued within the industry. Currently, research on the Great Field Mouse is limited to ecological and physiological-biochemical aspects; research on its genetics is still insufficient. Summary of the Invention

[0005] The purpose of this invention is to solve the above-mentioned problems by providing a method for developing microsatellite markers and analyzing genetic diversity in the Great Pleurotus ostreatus.

[0006] This invention achieves the above objective through the following technical solution: a method for developing microsatellite loci of *Apodemus davidii* based on the genome sequence of *Apodemus davidii*, comprising the following steps:

[0007] DNA extraction from SA and Great Forest Mouse DNA samples

[0008] Sixty SPF-grade field mice of any sex, age, and weight were randomly selected from the Experimental Animal Center of Jilin University. DNA samples were extracted from the tail and liver tissues of the mice, and the genomic DNA quality of the extracted DNA samples was tested.

[0009] Development of SB and SSR sites and design of primers

[0010] Based on the genome sequence information of *Apoda dalinensis* from NCBI, microsatellite markers were mined using MISA software. Primers were designed using Primer 5.0 software based on the site information. The primer design principles were as follows: primer length 18–27 bp, Tm set to 50℃–65℃, GC content 50%–60%, and product length 100–500 bp, resulting in 288 pairs of primers.

[0011] SC, PCR amplification and SSR detection

[0012] Primers were screened using DNA samples from 60 Giant Pleurotus eryngii mice. Primers with clear bands and good polymorphism were selected for population typing, and 30 pairs of polymorphic primers were finally selected.

[0013] The PCR amplification reaction system and conditions are as follows:

[0014] 10μL PCR reaction system: 5μL 2×Taq PCR Master Mix, 1μL DNA, 0.5μL each of forward and reverse primers, and 3μL ddH2O;

[0015] PCR amplification conditions: 95℃ for 5 min, 95℃ for 30 sec, annealing temperature 62℃-52℃ for 30 sec, 72℃ for 30 sec, 10 cycles, decreasing by 1℃ per cycle; 72℃ for 20 min.

[0016] The information for the 30 polymorphic primer pairs is as follows:

[0017]

[0018]

[0019] SD and fluorescent capillary electrophoresis detection

[0020] The PCR product from step SC was diluted to 1 ng / μL with ultrapure water. 1 μL of the diluted PCR product was denatured with 9 μL of a 1% internal standard formamide solution and then analyzed by capillary fluorescence electrophoresis on an ABI 3730xl DNA sequencer. The microsatellite PCR amplification data were interpreted using GeneMarker 2.2.0 software, and genetic diversity was analyzed using software such as GenAlEx version 6.501, specifically including:

[0021] ① Genetic diversity analysis

[0022] In GenAlEx version 6.501 software, various genetic diversity indicators of SSR loci and populations were calculated, including observed allele Na, effective allele Ne, Shannon index I, polymorphism information index PIC, observed heterozygosity Ho, and expected heterozygosity He.

[0023] ② Population genetic structure analysis

[0024] Genetic distances between populations were calculated using PowerMarker software. Cluster analysis was performed using the UPGMA method, and circular cluster diagrams were plotted. Population structure analysis of 60 samples was conducted using STRUCTURE 2.3.4, with K values ​​ranging from 1 to 20, a burn-in period of 10,000, and MCMC (Markov Chain Monte Carlo) set to 100,000. The analysis was performed 20 times for each K value, and the optimal ΔK value was calculated using the online tool STRUCTURE HARVESTER. Plots were created based on the optimal K values, and the structural analysis results were plotted using CLUMMP and DISTRUCT software.

[0025] ③ Analysis of molecular variance (AMOVA) and gene flow estimation

[0026] Based on the population genetic structure analysis results, the variation and differentiation between and within each population were calculated and significance tests were performed using GenAlEx version 6.501 software; the genetic differentiation coefficient Fst and gene flow Nm were calculated, with gene flow Nm calculated according to Wright's (1931) formula:

[0027] Nm = 0.25(1-Fst) / Fst.

[0028] Preferably, the genomic DNA quality detection in step SA includes DNA concentration and purity detection and DNA integrity detection, specifically the following steps:

[0029] ① DNA concentration and purity detection: Absorb 1 μL of DNA solution and use a Nanodrop ND-2000 micro-spectrophotometer to determine the concentration and purity of the extracted DNA. Record the concentration of the DNA sample, and the OD260 / OD230 and OD260 / OD280 ratios should be 1.8-2.0.

[0030] ② Integrity detection: The integrity of tissue genomic DNA was detected using 1.0% agarose gel electrophoresis.

[0031] The beneficial effects of this invention are as follows: The microsatellite marker development and genetic diversity analysis of the Great Forest Mouse disclosed in this invention have the following advantages:

[0032] 1. This invention provides genetic markers for genetic analysis of *Anacarya paliurus* by developing and screening microsatellite loci, and provides a basis for establishing genetic quality standards and detection technology systems for *Anacarya paliurus*.

[0033] 2. This invention provides efficient molecular markers and scientific references for promoting research such as the evaluation of germplasm resources and the construction of genetic maps of the Great Forest Mouse.

[0034] 3. This invention provides a comprehensive, objective, and fair evaluation of the genetic structure of the Great Forest Field Mouse, which helps to clarify the genetic background of the Great Forest Field Mouse and lays the foundation for its experimental animalization and production application. Attached Figure Description

[0035] Figure 1 This is an electrophoresis gel image of PCR amplification in this invention.

[0036] Figure 2 The graph shows the variation of K values ​​for the ΔK method used in the structure analysis of this invention, specifically the structure results of 60 samples when K = 2.

[0037] Figure 3 This is a clustering analysis diagram of the structure in this invention.

[0038] Figure 4 This is a diagram showing the UPGMA clustering results of the two populations in this invention.

[0039] Figure 5 This is a principal coordinate analysis diagram of 60 samples from this invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] This invention discloses a method for developing microsatellite loci of the Great Field Mouse (Ana spp.) based on the genome sequence. By developing and screening these microsatellite loci, genetic markers are provided for genetic analysis of the Great Field Mouse, and a basis is provided for establishing genetic quality standards and detection technology systems for the Great Field Mouse. The specific method is as follows:

[0042] Example: A method for developing microsatellite loci of the Great Forest Mouse based on the genome sequence of the Great Forest Mouse.

[0043] The reagent kits and reagents used in this experiment are shown in Table 1, and the instruments and equipment used in this experiment are shown in Table 2.

[0044] Table 1. Reagent Kits and Main Reagents

[0045]

[0046] Table 2. Instruments and equipment used in the experiment

[0047]

[0048] 1.1 Laboratory Animals

[0049] Sixty SPF-grade field mice of the Great Forest Rat were randomly selected from the Experimental Animal Center of Jilin University. The sex, age, and weight were not limited. The tail and liver tissues of the mice were collected and preserved in anhydrous ethanol at -20°C for subsequent molecular experiments.

[0050] 1.2 DNA extraction from Giant Apocynidae mice

[0051] DNA samples were extracted from rat tail and liver tissues, and the genomic DNA quality of the extracted DNA samples was analyzed. The DNA sample extraction method is as follows:

[0052] 1.2.1 Extraction of tissue genomic DNA

[0053] ① Take 30-50 mg of sample, cut it into small pieces and place it in a centrifuge tube. Add 400 μL of tissue lysis buffer and 5 μL of proteinase K to the centrifuge tube, shake to mix, and place in a 65℃ incubator for overnight digestion.

[0054] ② Add 200 μL of buffer GB to the mixture in step ①, mix thoroughly by inverting, place in a 70℃ water bath for 10 min, and then centrifuge at 12000 rpm for 30 sec to remove water droplets from the inner wall of the tube cap.

[0055] ③ Add 200 μL of anhydrous ethanol to the mixture in step ②, shake thoroughly for 15 seconds, and then centrifuge at 12000 rpm for 30 seconds to remove water droplets from the inner wall of the tube cap.

[0056] ④ Place the adsorption column CB3 in the collection tube, then transfer all the solution obtained in step ③ to the adsorption column, centrifuge at 12000 rpm for 30 seconds, discard the waste liquid, and put the adsorption column CB3 back into the collection tube.

[0057] ⑤ Add 500 μL of buffer GD to the adsorption column CB3, centrifuge at 12000 rpm for 30 seconds, discard the waste liquid, and put the adsorption column CB3 into the collection tube;

[0058] ⑥ Add 600 μL of washing solution PW to the adsorption column CB3, centrifuge at 12000 rpm for 30 seconds, discard the waste liquid, and put the adsorption column CB3 into the collection tube.

[0059] ⑦ Repeat step 6;

[0060] ⑧ Place the adsorption column CB3 back into the collection tube, centrifuge at 12000 rpm for 2 min, discard the waste liquid, and place the adsorption column CB3 at room temperature for 5 min;

[0061] ⑨ Transfer the adsorption column CB3 into a clean 1.5 mL centrifuge tube, add 100 μL of elution buffer TE, incubate at room temperature for 10 min, centrifuge at 12000 rpm for 2 min, and collect the elution buffer obtained after centrifugation into the centrifuge tube.

[0062] ⑩ Store the obtained DNA solution in a -20°C refrigerator for later use.

[0063] 1.2.2 The extracted genomic DNA was subjected to quality testing, and the specific methods are as follows:

[0064] ① DNA concentration and purity detection: Absorb 1 μL of DNA solution and use a Nanodrop ND-2000 micro-spectrophotometer to determine the concentration and purity of the extracted DNA from the sample. Record the concentration of the DNA sample, the OD260 / OD230 and OD260 / OD280 ratios, which should be 1.8-2.0.

[0065] ② Integrity detection: The integrity of the extracted tissue genomic DNA was detected using 1.0% agarose gel electrophoresis.

[0066] 1.3 Development of SSR loci and design of primers

[0067] Based on the genome sequence information of *Apoda dalinensis* from NCBI, microsatellite markers were mined using MISA software. Primers were designed using Primer 5.0 software based on the site information. The primer design principles were as follows: primer length 18–27 bp, temperature set at 50℃–65℃, GC content 50%–60%, and product length 100–500 bp. A total of 288 primer pairs were finally obtained.

[0068] 1.4 PCR amplification and SSR detection

[0069] Primers were screened using DNA samples from 60 Giant Pleurotus eryngii mice. Primers with clear bands and good polymorphism were selected for population typing, and 30 pairs of polymorphic primers were finally selected.

[0070] The PCR amplification reaction system and conditions are as follows:

[0071] 10μL PCR reaction system: 5μL 2×Taq PCR Master Mix, 1μL DNA, 0.5μL each of forward and reverse primers, and 3μL ddH2O;

[0072] PCR amplification conditions: 95℃ for 5 min, 95℃ for 30 sec, annealing temperature 62℃-52℃ for 30 sec, 72℃ for 30 sec, 10 cycles, decreasing by 1℃ per cycle; 72℃ for 20 min.

[0073] The information for the 30 polymorphic primer pairs is as follows:

[0074]

[0075]

[0076] To ensure the specificity of fluorescent PCR amplification and the uniformity of sample concentration, after fluorescent PCR amplification, 2 μL of PCR amplification product was analyzed on a 1% agarose gel electrophoresis. The band pattern of the PCR product was used to determine the amplification specificity of each SSR primer, and the brightness of the PCR product bands was used to determine the amplification efficiency of each SSR primer. Figure 1 It can be seen that the PCR amplification products showed clear bands when detected by agarose gel electrophoresis and the amplification results had good reproducibility.

[0077] 1.5 Fluorescent capillary electrophoresis detection

[0078] The PCR product from step SC was diluted to 1 ng / μL with ultrapure water. 1 μL of the diluted PCR product was denatured with 9 μL of a 1% internal standard formamide solution and then analyzed by capillary fluorescence electrophoresis on an ABI 3730xl DNA sequencer. The microsatellite PCR amplification data were interpreted using GeneMarker 2.2.0 software, and genetic diversity was analyzed using GenAlEx version 6.501 and other software.

[0079] 1.6 Diversity Analysis

[0080] 1.6.1 Genetic diversity analysis

[0081] In software such as GenAlEx version 6.501, various genetic diversity indicators of SSR loci and populations are calculated, including observed alleles (Na), effective alleles (Ne), Shannon index (I), polymorphism information index (PIC), observed heterozygosity (Ho), and expected heterozygosity (He).

[0082] The results of the genetic diversity analysis are as follows:

[0083] A total of 152 alleles (Na) were detected in 60 samples using 30 primer pairs. The minimum number of alleles was 3, the maximum number of alleles was 9, and the average number of alleles per locus was 5.06667. The total number of effective alleles (Ne, the more evenly distributed the alleles in the population, the closer Ne is to the actual number of alleles detected) was 97.983, ranging from 1.571 (AP049) to 6.139 (AP206), with an average of 3.2661 effective alleles per locus. The Shannon index (I) ranged from 0.672 (AP049) to 1.965 (AP206), with an average of 1.2645. The observed heterozygosity (Ho) ranged from 0.35 (AP223) to 0.917 (AP206), with an average of 0.59183. The expected heterozygosity (He) ranges from 0.364 (AP049) to 0.837 (AP206), with an average of 0.64617. The polymorphic information content (PIC) ranges from 0.335 (AP049) to 0.818 (AP206), with an average of 0.59797.

[0084] The polymorphisms of the 30 SSR primer pairs are shown in Table 3.

[0085] Table 3 Polymorphism of 30 SSR primer pairs

[0086]

[0087]

[0088] Note: Na: observed alleles; Ne: effective alleles; I: Shannon index; Ho: observed heterozygosity; He: expected heterozygosity; F: fixation index, an indicator to assess the deviation of actual observed values ​​from theoretical values; PIC: polymorphism information index; Prob: P-value; Signif: significance (ns indicates no significance, i.e., the population conforms to HWE; * indicates significant difference P<0.05, ** indicates significant difference P<0.01, *** indicates significant difference P<0.001).

[0089] 1.6.2 Population genetic structure analysis

[0090] Genetic distances between populations were calculated using PowerMarker software. Cluster analysis was performed using the UPGMA method, and circular clustering diagrams were plotted. Population structure analysis was conducted on 60 samples using STRUCTURE 2.3.4, with K values ​​ranging from 1 to 20, a burn-in period of 10,000, and MCMC (Markov Chain Monte Carlo) set to 100,000. The analysis was run 20 times for each K value, and the optimal ΔK value (representing the optimal population stratification) was calculated using the online tool STRUCTURE HARVESTER. Plots were created based on the optimal K values. The structural analysis results were plotted using CLUMMP and DISTRUCT software.

[0091] 1.6.2.1 STRUCTURE Analysis

[0092] The population structure of 60 samples was evaluated using 30 molecular markers. Based on the principle of maximizing likelihood, the optimal K value was determined to be 2, which allowed the 60 samples to be divided into two subpopulations. The results are as follows: Figure 2 As shown.

[0093] 1.6.2.2 Genetic Distance and Cluster Analysis

[0094] Genetic distance between populations (Nei, 1983) was calculated in PowerMarker. The genetic distance between the two populations was 0.16205014. Cluster analysis was performed using the unweighted group average method (UPGMA) based on Nei genetic distance. Table 4 shows that the genetic distance between populations was 0.16205014. Figure 3 The cluster analysis of the 60 *Apoda chinensis* samples shows the results of the structural analysis. Figure 4 The UPGMA clustering results for the two populations can be obtained.

[0095] Table 4 Genetic distance between populations

[0096]

[0097] The genetic diversity among populations is shown in Table 5;

[0098] Table 5 Genetic diversity among populations

[0099]

[0100]

[0101] Na: observed alleles; Ne: effective alleles; I: Shannon information index; Ho: observed heterozygosity; He: expected heterozygosity; F: fixed index. The genetic diversity of the population loci is shown in Table 6.

[0102] Table 6. Genetic diversity of population loci

[0103]

[0104]

[0105]

[0106] Pop: Population name; Locus: Locus name; Na: Observed alleles; Ne: Effective alleles; I: Shannon information index; Ho: Observed heterozygosity; He: Expected heterozygosity; F: Fixation index.

[0107] 1.6.3 Gene Flow Estimation

[0108] Based on the population genetic structure analysis results, the variation and differentiation among each population were calculated and significance tests were performed in GenAlEx version 6.501 software; the genetic differentiation coefficient (Fst) and gene flow (Nm) were calculated, and the gene flow (Nm) was calculated according to the formula of Wright (1931):

[0109] Nm = 0.25(1-Fst) / Fst.

[0110] Table 7. Gene flow (upper triangle) and genetic differentiation coefficient (lower triangle) among populations.

[0111]

[0112] 1.6.4 Analysis of molecular variance (AMOVA)

[0113] Analysis of molecular variance (ANOVA) is a method for measuring and calculating genetic variation among haplotypes (or genotypes) by using evolutionary distance. ANOVA showed that 13% of the genetic variation exists in the population, and 87% exists in individuals. Individual variation is the main source of total variation in the Great African Pleurotus ostreatus, as shown in Table 8.

[0114] Table 8. Analysis of molecular variance (AMOVA) of the populations.

[0115]

[0116] Source: Source of variation; df: Degrees of freedom; SS: Total variance; MS: Mean squared variance; Est.Var.: Estimated variance; %: Percentage of variation; Among Pops: Among populations; Among Indiv: Among individuals; Within Indiv: Within an individual. Intra-individual variation refers to the genetic differences caused by heterozygous alleles, and its magnitude is related to the number of heterozygous loci in an individual, i.e., the genetic diversity of an individual.

[0117] 1.6.5 Principal Coordinate Analysis

[0118] Principal Coordinate Analysis (PCoA) presents a visual coordinate representation of the similarity or difference between research data. It is a non-constrained dimensionality reduction analysis method and can also be used to study the similarity or dissimilarity of sample group composition. PCoA analysis reflects the differences between two or more samples by intuitively comparing the linear distances between samples on the coordinate axes. Closer linear distances between two samples or groups indicate smaller differences; conversely, larger linear distances indicate greater differences. PCoA analysis was performed using GenAIex software, and the results are as follows: Figure 5 As shown.

[0119] In summary, this invention provides genetic markers for the genetic analysis of *Anacarya paliurus* by developing and screening microsatellite loci, and provides a basis for establishing genetic quality standards and detection technology systems for *Anacarya paliurus*. This invention provides efficient molecular markers and scientific references for promoting research such as *Anacarya paliurus* germplasm resource evaluation and genetic map construction. This invention provides a comprehensive, objective, and impartial evaluation of the genetic structure of *Anacarya paliurus*, which helps to clarify the genetic background of *Anacarya paliurus* and lays the foundation for the experimental animalization and production application of *Anacarya paliurus*.

[0120] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0121] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A primer set for amplifying microsatellite loci of Apodemus 5 pallipes developed based on the genomic sequence of Apodemus pallipes, characterized in that: The primer set consists of 30 pairs of polymorphic primers, The information of 30 pairs of polymorphic primers is as follows: 。

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