Myricaria laxiflora population genetic analysis method based on simplified genome sequencing

Abstract

According to the myricaria laxiflora population genetic analysis method based on simplified genome sequencing, the myricaria laxiflora genetic diversity and population genetic structure analysis is carried out through SNP molecular markers, high repeatability and operability are achieved, and the myricaria laxiflora population genetic analysis method has great significance in myricaria laxiflora genetic resource evaluation and utilization; the method also has reference significance for evaluation work of genetic resources of other endangered wild plants; according to the method, the myricaria laxiflora population with high genetic diversity can be screened out according to the obtained population genetic variation data, and the myricaria laxiflora population is used as a prioritized myricaria laxiflora population, so that the method has guiding significance on in-situ protection work of myricaria laxiflora and is beneficial to formulating a myricaria laxiflora species protection plan and a genetic management strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of molecular biology, and particularly to a method for population genetic analysis of Myricaria laxiflora based on reduced-representation genome sequencing. Background Art

[0002] Myricaria laxiflora (Franch.) P. Y. Zhang & Y. J. Zhang is an upright shrub of the family Tamaricaceae and the genus Myricaria, mainly distributed in the areas on both sides of the Yangtze River in Zigui, Badong, Hubei, China and the Three Gorges of Wushan, Sichuan. Myricaria laxiflora has a strong ability to resist flood impact and endure waterlogging, and is an excellent tree species for sand fixation and greening on river banks; its branches and leaves are peculiar, the tree shape is beautiful, and it is gorgeous when blooming, with high ornamental value, and is also a good ornamental tree species. In addition, Myricaria laxiflora is an endemic species in the Three Gorges Reservoir Area of China, which has certain significance for studying the characteristics of the flora in the subtropical region of China; its existence also has important scientific significance for studying the classification and phylogeny of the genus Myricaria and even the family Tamaricaceae; the phenomenon that it does not shed leaves in winter and sheds leaves after being waterlogged in summer is a special case in the genus Myricaria, which is the result of long-term adaptation to the waterlogging environment, and also has important significance for studying plant evolution, plant genetics and variation, and the relationship between plants and the environment. Therefore, in order to achieve the efficient protection, utilization and scientific management of Myricaria laxiflora, and in order to better enrich and improve the research data on Myricaria laxiflora, it is crucial to carry out population genetic analysis of Myricaria laxiflora.

[0003] Currently, the molecular markers used in the population genetic analysis of Myricaria laxiflora are generally allozyme markers, Inter-simple sequence repeat (ISSR) markers, and Amplified Fragment Length Polymorphism (AFLP) markers, which have the disadvantages of low throughput, poor accuracy and resolution, and limit the analysis of genetic diversity and genetic structure of Myricaria laxiflora within its distribution range. Summary of the Invention

[0004] The present invention provides a method for population genetic analysis of Myricaria laxiflora based on reduced-representation genome sequencing, the experimental steps of which are simple, the cost is low, the results are accurate, the repeatability is high, and it does not rely on a reference genome.

[0005] The present invention provides an application of the above method in the population genetics analysis of Myricaria laxiflora and the in-situ conservation of Myricaria laxiflora.

[0006] The present invention provides a method for population genetic analysis of Myricaria laxiflora based on reduced-representation genome sequencing, which includes the following steps:

[0007] Step 1: Obtain a number of plant samples of Myricaria laxiflora, extract genomic DNA from the number of plant samples of Myricaria laxiflora to obtain a DNA sample;

[0008] Step 2: Completely digest the DNA sample with MseI enzyme and SacI enzyme to obtain digested fragments; ligate the digested fragments with sequencing adapters to obtain ligation products; mix the ligation products corresponding to the same plant sample to obtain a mixed sample; amplify the mixed sample to obtain an amplification product; mix the amplification products corresponding to a number of plant samples, perform agarose gel electrophoresis, and select the region of 250 - 500 bp on the agarose gel after electrophoresis for recovery and purification to obtain a reduced-representation genomic library;

[0009] Step 3: Perform paired-end sequencing on the reduced-representation genomic library to obtain sequencing data, and identify SNP loci based on the sequencing data;

[0010] Step 4: Calculate the expected heterozygosity, observed heterozygosity, and nucleotide polymorphism of the Myricaria laxiflora population based on the SNP loci to analyze the genetic diversity of Myricaria laxiflora; perform ancestral component analysis and principal component analysis on the SNP loci to analyze the population genetic structure of Myricaria laxiflora.

[0011] The method as described above, wherein obtaining a number of plant samples of Myricaria laxiflora includes: collecting leaves of a number of Myricaria laxiflora, where the interval between each individual Myricaria laxiflora plant collected is ≥ 5 m, and placing the leaves in liquid nitrogen for ultra-low temperature preservation to obtain Myricaria laxiflora plant samples.

[0012] The method as described above, wherein Step 1 further includes: performing quality control on the DNA sample to obtain a qualified DNA sample;

[0013] Wherein, performing quality control on the DNA sample includes: detecting the fragment size and degradation degree of the DNA sample using agarose gel electrophoresis to make the DNA sample complete; detecting the OD260 / 280 ratio of the DNA sample using a micro-spectrophotometer to make the OD260 / 280 ratio of the DNA sample 1.8 - 2.2; detecting the concentration of the DNA sample using a fluorescence quantitative instrument to make the DNA concentration in the DNA sample ≥ 50 ng / μL and the total DNA amount ≥ 2 μg.

[0014] The method as described above, wherein Step 2 further includes: performing quality control on the reduced-representation genomic library to obtain a qualified reduced-representation genomic library;

[0015] Among them, quality control of the reduced-representation genomic library includes: preliminarily quantifying the DNA concentration in the reduced-representation genomic library using a fluorescence quantitative analyzer to make the DNA concentration in the reduced-representation genomic library > 2 nM; detecting the inserted fragments in the reduced-representation genomic library using a bioanalyzer to make the size of the inserted fragments 250 - 500 bp and free of adapter contamination; accurately quantifying the effective DNA concentration in the reduced-representation genomic library using a real-time fluorescence quantitative PCR instrument to make the effective DNA concentration in the reduced-representation genomic library > 2 nM.

[0016] The method as described above, wherein in step 3, the sequencing depth of paired-end sequencing is 8.92X - 107.28X, and the average sequencing depth is 23.30X.

[0017] The method as described above, wherein step 3 further includes quality control of the sequencing data to obtain qualified sequencing data;

[0018] Quality control of the sequencing data includes: removing polyG or polyX with a tail length ≥ 10 bp in the sequencing data, removing Reads with more than 5 Ns in the sequencing data, and removing Reads with a proportion of bases with a base quality < 15 exceeding 40% of the total number of bases in the Reads; detecting the remaining Reads and removing Reads with a length < 15 bp to obtain qualified sequencing data.

[0019] The method as described above, wherein step 3 further includes quality control of SNP sites to obtain qualified SNP sites;

[0020] Quality control of SNP sites includes: removing SNP sites with a genotype deletion ratio > 10% in the SNP sites, removing SNP sites with a minor allele frequency < 0.05 in the SNP sites, and only retaining biallelic SNP sites to obtain qualified SNP sites.

[0021] The method as described above, wherein step 4 further includes: performing molecular variance analysis, population evolution analysis, and environmental isolation analysis and geographical isolation analysis on the SNP sites.

[0022] The present invention provides an application of the above method in the population genetics analysis of Myricaria laxiflora.

[0023] The present invention provides an application of the above method in the in-situ conservation of Myricaria laxiflora.

[0024] The present invention provides a method for population genetic analysis of Myricaria laxiflora based on reduced-representation genomic sequencing, having the following beneficial effects:

[0025] (1) The method of the present invention uses reduced-representation genome sequencing technology for population genetic analysis of Myricaria laxiflora. The experimental steps are simple, the cost is low, the results are accurate, and the repeatability is high. It can be independent of a reference genome.

[0026] (2) Based on SNP loci, the present invention analyzes the genetic diversity and population genetic structure of Myricaria laxiflora, which is of great significance for the evaluation and utilization of Myricaria laxiflora genetic resources. It helps to achieve the efficient protection, utilization and scientific management of Myricaria laxiflora, and can also provide a reference for the evaluation of genetic resources of other endangered wild plants.

[0027] (3) The method provided by the present invention can effectively distinguish the population genetic structure of Myricaria laxiflora and determine the genetic diversity of different genetic groups, thus helping to screen out genetic groups with higher genetic diversity for priority protection, which is of great significance for guiding the in-situ conservation work of Myricaria laxiflora. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is an Admixture analysis diagram of the wild population of Myricaria laxiflora;

[0029] Figure 2 It is a principal component analysis diagram of the wild population of Myricaria laxiflora;

[0030] Figure 3 It is a historical gene flow analysis diagram of the wild population of Myricaria laxiflora;

[0031] Figure 4 It is a significance test result diagram of environmental distance and genetic distance;

[0032] Figure 5 It is a significance test result diagram of geographical distance and genetic distance. DETAILED DESCRIPTION OF THE INVENTION

[0033] To enable those skilled in the art to better understand the solution of the present invention, the present invention will be further described in detail below. The specific embodiments listed below only describe the principles and features of the present invention. The examples given are only used to explain the present invention and do not limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0034] Reduced-Representation Genome Sequencing (RRGS) refers to a sequencing strategy that uses restriction endonucleases to break genomic DNA, and performs high-throughput sequencing on specific fragments to obtain a large number of genetic polymorphism tag sequences to fully represent the whole-genome information of the target species. This method has simple experimental steps and low cost, and can obtain genetic polymorphisms across the whole genome without relying on a reference genome, so it is widely used in fields such as ecology, evolution, and genomics. Among them, the GBS (Genotyping-by-Sequencing) technology is a kind of reduced-representation genome sequencing method. It is a technology that uses sequencing for genotyping. By selecting appropriate restriction endonucleases and combining high-throughput population sequencing to construct single nucleotide polymorphism (SNP) molecular markers, it can be used for molecular marker development, ultra-high density genetic map construction, population genetic analysis, population GWAS analysis, etc. The GBS technology can be used for population genetic analysis of Myricaria laxiflora. In the present invention, the genetic diversity and genetic structure of Myricaria laxiflora were mainly analyzed. Genetic diversity is an index to measure the genetic variation among individuals in a single species, represented by the diversity of alleles present in the population; genetic structure is the distribution pattern of the genetic variation of a population in time and space; among them, genetic variation is crucial for the ecological adaptation ability (such as the potential and ability to adapt to the external environment) and evolutionary potential of Myricaria laxiflora.

[0035] The present invention provides a method for population genetic analysis of Myricaria laxiflora based on reduced-representation genome sequencing. By using SNP molecular markers to analyze the genetic diversity and population genetic structure of Myricaria laxiflora, it has high repeatability and operability, and is of great significance for the evaluation and utilization of the genetic resources of Myricaria laxiflora, and also has reference significance for the evaluation of the genetic resources of other endangered wild plants; according to the obtained population genetic variation data, the present invention can screen out Myricaria laxiflora populations with high genetic diversity and use them as the Myricaria laxiflora populations to be preferentially protected, which has guiding significance for the in-situ protection of Myricaria laxiflora and helps to formulate the species protection plan and genetic management strategy of Myricaria laxiflora.

[0036] Therefore, in the first aspect, the present invention provides a method for population genetic analysis of Myricaria laxiflora based on reduced-representation genome sequencing, including the following steps:

[0037] Step 1: Obtain a number of plant samples of Myricaria laxiflora, and extract genomic DNA from the number of plant samples of Myricaria laxiflora to obtain a DNA sample;

[0038] Step 2: Completely digest the DNA sample with MseI enzyme and SacI enzyme to obtain digested fragments; ligate the digested fragments with sequencing adapters to obtain ligation products; mix the ligation products corresponding to the same plant sample to obtain a mixed sample; amplify the mixed sample to obtain amplified products; mix the amplified products corresponding to several plant samples, perform agarose gel electrophoresis, and select the region of 250 - 500 bp on the agarose gel after electrophoresis for recovery and purification to obtain a reduced-representation genomic library;

[0039] Step 3: Perform paired-end sequencing on the reduced-representation genomic library to obtain sequencing data, and identify SNP sites based on the sequencing data;

[0040] Step 4: Calculate the expected heterozygosity, observed heterozygosity, and nucleotide polymorphism of the Myricaria laxiflora population based on the SNP sites to analyze the genetic diversity of Myricaria laxiflora; perform ancestral component analysis and principal component analysis on the SNP sites to analyze the population genetic structure of Myricaria laxiflora.

[0041] The above method uses reduced-representation genomic sequencing technology for population genetic analysis of Myricaria laxiflora, which has the advantages of simple experimental steps, low cost, accurate results, and high repeatability, and can be independent of a reference genome. Using this SNP-site-based method to analyze the genetic diversity and population genetic structure of Myricaria laxiflora is of great significance for the evaluation and utilization of Myricaria laxiflora genetic resources, helps to screen out genetic groups with higher genetic diversity for priority protection, is of great significance for guiding the in-situ conservation work of Myricaria laxiflora, and also helps to achieve the efficient protection, utilization, and scientific management of Myricaria laxiflora, and can also provide a reference for the evaluation of genetic resources of other endangered wild plants.

[0042] Specifically, first, several plant samples of Myricaria laxiflora can be obtained, and genomic DNA is extracted from the several plant samples of Myricaria laxiflora to obtain a DNA sample. The method for extracting genomic DNA in the present invention is not limited and can be carried out according to conventional technical means in the art. For example, the cetyltrimethylammonium bromide (CTAB) method can be used to extract genomic DNA.

[0043] It can be understood that the "several plant samples of Myricaria laxiflora" in the present invention refers to collecting one plant sample from each of several Myricaria laxiflora plants, thereby obtaining several plant samples; for example, collecting one plant sample from each of 10 Myricaria laxiflora plants, thereby obtaining 10 plant samples, and they can correspond one by one to the above 10 Myricaria laxiflora plants.

[0044] Secondly, the DNA sample can be completely digested with MseI enzyme and SacI enzyme to obtain digested fragments; the digested fragments are ligated with sequencing adapters to obtain ligation products; the ligation products are mixed to obtain a mixed sample; the mixed sample is amplified to obtain amplified products; the amplified products are mixed and subjected to agarose gel electrophoresis, and the region of 380 - 480 bp on the electrophoresed agarose gel is selected for recovery and purification to obtain a reduced-representation genomic library.

[0045] Specifically, the DNA sample can be completely digested with restriction endonucleases MseI enzyme and SacI enzyme to obtain digested fragments; then the 3' ends of the digested fragments are A-tailed and ligated with sequencing adapters to obtain ligation products.

[0046] Among them, the restriction endonuclease MseI enzyme is a common enzyme for reduced-representation genomic sequencing. Through long-term experiments, it has been found that SacI enzyme is suitable for the Myricaria laxiflora species, and it has a good matching effect with MseI enzyme. When the two are used together for digesting the genomic DNA of Myricaria laxiflora, an appropriate number of target fragments can be obtained, avoiding difficulties in subsequent experiments due to too low a number and also avoiding strong background noise and difficulty in resolution due to too high a number.

[0047] It can be understood that this sequencing adapter can use common sequencing adapters in the art, such as MID sequencing adapters; the sequence of this sequencing adapter can also be any known adapter sequence in the art.

[0048] Subsequently, different ligation products corresponding to the same plant sample are mixed (Pooling), and purified using the AMPureXP Beads nucleic acid purification kit to obtain a mixed sample; the mixed sample is amplified using the high-fidelity polymerase KOD-Plus-Neo to obtain amplified products.

[0049] Among them, the amplification can adopt any known method for DNA fragment amplification in the art, such as polymerase chain reaction (PCR) amplification or non-PCR amplification.

[0050] Furthermore, for the PCR amplification method, the primers in the PCR amplification can be universal primers designed according to the specific adapter sequence; the PCR amplification program can include: initial denaturation at 94°C for 2 - 3 min, denaturation at 98°C for 10 s, annealing at 55 - 65°C for 30 s, extension at 68°C for 30 s, cycling 35 - 45 times; final extension at 72°C for 5 min; and finally stored at 4°C.

[0051] Next, all the amplification products corresponding to several plant samples are pooled, and the pooled amplification products are electrophoresed overnight at low voltage using agarose gel, controlling the electrophoresis voltage ≤ 5 V / cm to ensure the clarity of the electrophoresis bands; the region of 250 - 500 bp on the agarose gel is selected, and a genomic library is obtained by recovery and purification using an agarose gel recovery kit. In the above steps, through two poolings, the DNA of multiple samples can be mixed for sequencing, thus saving sequencing time and cost to the greatest extent and improving sequencing efficiency.

[0052] Furthermore, the genomic library can be sequenced from both ends to obtain sequencing data, and SNP sites can be identified based on the sequencing data.

[0053] In the present invention, the genomic library is sequenced from both ends with Paired-end150 bp (PE150) using the Illumina HiSeq sequencing platform, and raw image data files can be obtained. After base calling analysis, they are converted into raw sequencing sequences (reads), which are called raw off-machine data (Raw Data), and the results are stored in the FASTQ (abbreviated as fq) file format.

[0054] Finally, based on the SNP sites, the expected heterozygosity, observed heterozygosity, and nucleotide polymorphism of the Myricaria laxiflora population can be calculated to analyze the genetic diversity of Myricaria laxiflora; ancestral component analysis and principal component analysis are performed on the SNP sites to analyze the population genetic structure of Myricaria laxiflora.

[0055] Specifically, based on the SNP sites, the Stacks 2.5.9 software can be used to analyze the expected heterozygosity (H E ), observed heterozygosity (H O ), and nucleotide polymorphism (π) of Myricaria laxiflora. Among them, the expected heterozygosity (H E ) refers to the heterozygosity calculated theoretically; the observed heterozygosity (H O ) refers to the probability that the alleles of two randomly selected samples are different; the nucleotide polymorphism (π) refers to the probability that two homologous sequences randomly selected in the population are the same. The higher the values of H E , H O and π, the higher the genetic diversity of the Myricaria laxiflora population. Furthermore, populations with higher genetic diversity can be selected for in-situ conservation.

[0056] Meanwhile, based on the SNP loci, the ADMIXTURE software (version 1.3) can be used to perform the ancestral component analysis on *Myricaria laxiflora*. The preset population of the ADMIXTURE software consists of several subpopulations (K = x). By means of a simulation algorithm, the most reasonable sample classification method at K = x is searched for, and then the most applicable K value for this population is determined according to the maximum likelihood value or cross-validation error value (CV error) of each simulation. Based on the SNP loci, the Genome-wide Complex Trait Analysis software (version 1.93.2) can be used to perform the principal component analysis (PCA) on *Myricaria laxiflora*. In the present invention, through the K value or principal component analysis, the population genetic structure of *Myricaria laxiflora* can be analyzed, so that the populations can be distinguished according to the genetic structure of *Myricaria laxiflora*, and further it is helpful to select one or more populations with higher genetic diversity for in-situ conservation.

[0057] In the above technical solution, to ensure the randomness and scientific nature of sample acquisition, the acquisition of several plant samples of *Myricaria laxiflora* can be controlled, including: collecting the leaves of several *Myricaria laxiflora*, wherein the interval between each individual *Myricaria laxiflora* plant collected is ≥ 5 m, and placing the leaves in liquid nitrogen for ultra-low temperature preservation to obtain the plant samples of *Myricaria laxiflora*. In the above technical solution, to obtain qualified DNA samples and increase the scientific nature and reliability of the experiment, it can be set that step 1 further includes: performing quality control on the DNA samples. Specifically, the agarose gel electrophoresis is used to detect the fragment size and degradation degree of the DNA samples, so that the DNA samples have integrity; the micro-spectrophotometer is used to detect the OD260 / 280 ratio of the DNA samples, so that the OD260 / 280 ratio of the DNA samples is 1.8 - 2.2, without protein or visible impurity contamination and with high purity; the fluorescence quantitative instrument is used to detect the concentration of the DNA samples, so that the DNA concentration in the DNA samples ≥ 50 ng / μL and the total amount of DNA ≥ 2 μg.

[0058] In the above technical solution, to obtain qualified reduced-representation genomic libraries and increase the scientific nature and reliability of the experiment, it can be set that step 2 further includes: performing quality control on the reduced-representation genomic libraries. Specifically, the fluorescence quantitative instrument is used to preliminarily quantify the DNA concentration in the reduced-representation genomic libraries, so that the DNA concentration in the reduced-representation genomic libraries > 2 nM; the bioanalyzer is used to detect the inserted fragments in the reduced-representation genomic libraries, so that the size of the inserted fragments is 250 - 500 bp and there is no adapter contamination; the real-time fluorescence quantitative PCR instrument is used to accurately quantify the effective DNA concentration in the reduced-representation genomic libraries, so that the effective DNA concentration in the reduced-representation genomic libraries > 2 nM.

[0059] Furthermore, in step 3, the sequencing depth of paired-end sequencing is 8.92X - 107.28X, and the average sequencing depth is 23.30X.

[0060] In the above technical solution, step 3 further includes performing quality control on the sequencing data to obtain qualified sequencing data; performing quality control on the sequencing data includes: removing polyG or polyX with a tail length ≥ 10 bp in the sequencing data, removing Reads with more than 5 Ns in the sequencing data, and removing Reads in which the proportion of bases with a base quality < 15 exceeds 40% of the total number of bases in this Reads; detecting the remaining Reads and removing Reads with a length < 15 bp among them to obtain qualified sequencing data.

[0061] Since the sequencing adapters, sequences with too short length, low-quality reads, etc. contained in the obtained read lengths (Reads) of sequencing will affect the assembly quality, quality control of the sequencing data can filter out the low-quality data and obtain high-quality data (Clean reads), thereby avoiding the interference of low-quality data on sequencing analysis, facilitating the analysis of sequencing data, and effectively improving the reliability of sequencing analysis.

[0062] In the above technical solution, step 3 further includes performing quality control on SNP sites to obtain qualified SNP sites; performing quality control on SNP sites includes: removing SNP sites with a genotype missing ratio > 10% in the SNP sites, removing SNP sites with a minor allele frequency < 0.05 in the SNP sites, and only retaining bi-allelic SNP sites to obtain qualified SNP sites, and the qualified SNP sites have a key impact on the population genetics analysis of Myricaria laxiflora, effectively improving the credibility of genetic analysis.

[0063] In the above technical solution, step 4 further includes: performing analysis of molecular variance, population evolution analysis, and environmental isolation analysis and geographical isolation analysis on SNP sites.

[0064] First of all, the present invention can perform analysis of molecular variance (Analysis of Molecular Variance, AMOVA) on the Myricaria laxiflora population based on SNP sites through Arlequin software, and the analysis of molecular variance reveals that the genetic variation of Myricaria laxiflora mainly exists among populations.

[0065] Secondly, the present invention can also calculate allele frequencies based on SNP loci, and use TreeMix software to infer gene flow among populations of *Metasequoia laxiflora* according to allele frequencies. Herein, gene flow refers to the introduction of new genetic material from one population of a species to another population, thereby changing the composition of the population gene pool. Population evolutionary analysis reveals that the gene flow of *Metasequoia laxiflora* is from the upper Yangtze River population to the lower Yangtze River population, indicating that there has been only one gene migration event in the history of *Metasequoia laxiflora* populations.

[0066] Finally, the present invention can also obtain 19 climate factors from the WorldClim database, download climate data from the Chinese Ecosystem Research Network or the Global Aridity and Potential Evapotranspiration Database, and use ArcGIS software to extract the climate data of *Metasequoia laxiflora* populations from the above climate factors and climate data; to reduce collinearity, climate factors or climate data with a Pearson correlation coefficient ≥ 0.80 are excluded, and finally only 3 climate factors are retained. According to these 3 climate factors, using SPSS 21.0 software, the environmental distance can be calculated using Euclidean distance. Meanwhile, based on SNP loci, the genetic distance of *Metasequoia laxiflora* populations (F ST / (1 - F ST )) is analyzed using Stacks 2.5.9 software, where F ST represents the genetic differentiation index between populations). The significance test between the genetic distance and the environmental distance is performed with 9,999 random permutations, and the Mantel test is implemented using the R software package "vegan 2.6 - 4". Environmental isolation analysis reveals a significant correlation between the environmental distance and the genetic distance, indicating that environmental isolation has a significant impact on promoting the genetic differentiation of *Metasequoia laxiflora* populations, and candidate genes related to the annual mean temperature, isothermality, and annual average precipitation may be useful for *Metasequoia laxiflora* breeding. The present invention can also analyze the geographical distance of *Metasequoia laxiflora* wild populations using GenAlex software according to the longitude and latitude of the distribution points of *Metasequoia laxiflora* wild populations, perform a logarithmic transformation on the geographical distance, and test the significance between the genetic distance and the geographical distance. Geographical isolation analysis reveals a significant correlation between the geographical distance and the genetic distance, indicating that geographical isolation has a significant impact on promoting the genetic differentiation of *Metasequoia laxiflora* populations.

[0067] The second aspect of the present invention provides an application of the above method in the population genetics analysis of *Metasequoia laxiflora*.

[0068] Through the method of the present invention, the genetic diversity of Myricaria laxiflora can be obtained, and further it can be proved that the genetic diversity of the downstream population of Myricaria laxiflora is higher than that of the upstream population; the population genetic structure of Myricaria laxiflora can also be obtained, and further it can be proved that the genetic variation of Myricaria laxiflora mainly exists among populations, and the genetic differentiation between the upstream and downstream populations of Myricaria laxiflora is significant, and the genetic composition of the downstream population of Myricaria laxiflora is quite different from that of the upstream population; at the same time, the population evolution of Myricaria laxiflora can be obtained, and further it can be proved that there has been only one gene migration event in the history of the wild population of Myricaria laxiflora, and the gene flow is from the upstream population in the Yangtze River to the downstream population in the Yangtze River, verifying again that the genetic differentiation between the upstream and downstream populations of Myricaria laxiflora is significant; in addition, the environmental isolation and geographical isolation of Myricaria laxiflora can also be obtained, and further it can be proved that environmental isolation and geographical isolation have a significant impact on promoting the genetic differentiation of Myricaria laxiflora populations. Therefore, through the method of the present invention, a large number of results of population genetics analysis of Myricaria laxiflora can be provided, which is of great significance for the evaluation and utilization of Myricaria laxiflora genetic resources, helps to achieve the efficient protection, utilization and scientific management of Myricaria laxiflora, and can also provide a reference for the evaluation of genetic resources of other endangered wild plants.

[0069] The third aspect of the present invention provides an application of the above method in the in-situ conservation of Myricaria laxiflora.

[0070] Through the method of the present invention, the population genetic structure of Myricaria laxiflora can be effectively distinguished, and the genetic diversity of different genetic groups can be determined, so as to help screen out genetic groups with higher genetic diversity for priority protection, which has important significance for guiding the in-situ conservation work of Myricaria laxiflora. The present invention can conclude that the population of Myricaria laxiflora located downstream of the Yangtze River can be used as a priority population for in-situ conservation.

[0071] For the experimental methods without specific conditions noted in the following examples, they are generally carried out under conventional conditions or according to the conditions recommended by the manufacturers. The reagents or equipment used, unless otherwise specified, are all commercially available or can be obtained through public channels.

[0072] Example 1: Obtaining plant samples

[0073] According to the information of the wild populations of Myricaria laxiflora obtained from the field survey in Table 1, a total of 8 wild populations of Myricaria laxiflora, namely W1-W8, were used as the sources for obtaining plant samples. From each of the above populations, 24 young leaves of mature plant individuals were collected respectively, and it was ensured that the interval between each collected mature plant individual was ≥ 5 m; for the populations with less than 24 mature plant individuals, all were collected, and a total of 186 plant leaf samples were obtained. The plant leaf samples were placed in 2 ml cryopreservation tubes, marked, temporarily stored in liquid nitrogen, and then transferred to a -80 °C ultra-low temperature freezer for long-term storage for later use, thus obtaining plant samples.

[0074] Table 1

[0075]

[0076] Example 2: Obtaining qualified DNA samples

[0077] The genomic DNA of 186 plant samples in Example 1 was extracted respectively according to the improved cetyltrimethylammonium bromide (CTAB) method to obtain DNA samples. Quality control was performed on the DNA samples to obtain qualified DNA samples, and the specific operations were as follows: agarose gel electrophoresis was used to detect the fragment size and degradation degree of the DNA samples to ensure the integrity of the DNA samples; a Nanodrop micro-spectrophotometer was used to detect the OD260 / 280 ratio of the DNA samples to ensure that the OD260 / 280 ratio of the DNA samples was 1.8 - 2.2, free of protein or visible impurity contamination, and with high purity; a Qubit 3.0 fluorescence quantitative analyzer was used to detect the concentration of the DNA samples to ensure that the DNA concentration in the DNA samples was ≥50 ng / μL and the total DNA amount was ≥2 μg.

[0078] Example 3: Construction of a reduced-representation genomic library

[0079] Take 200 ng of the qualified DNA sample in Example 2 and perform complete digestion on it using the restriction enzymes MseI and SacI produced by New England Biolabs to obtain digested fragments. Perform A-tailing on the 3' ends of the digested fragments and ligate MID sequencing adapters to obtain ligation products. Mix (Pooling) the different ligation products corresponding to the same plant sample and purify it using the AMPure XP Beads nucleic acid purification kit to obtain a mixed sample. Use the high-fidelity polymerase KOD-Plus-Neo produced by TOYOBO to perform polymerase chain reaction (PCR) on the mixed sample to obtain amplified products; among them, the PCR amplification program includes: initial denaturation at 94°C for 2 - 3 min, denaturation at 98°C for 10 s, annealing at 55 - 65°C for 30 s, extension at 68°C for 30 s, cycle 35 - 45 times; final extension at 72°C for 5 min; finally store at 4°C. Mix (Pooling) all the amplified products corresponding to 186 plant samples, prepare an agarose gel using the Certified Megabase Agarose produced by Bio-Rad, and perform low-voltage overnight electrophoresis on the mixed amplified products using the agarose gel, controlling the electrophoresis voltage ≤ 5 V / cm to ensure the clarity of the electrophoresis bands. Select the region of 250 - 500 bp on the agarose gel and use the agarose gel recovery kit produced by QIAGEN to perform recovery and purification to obtain a reduced-representation genomic library. Perform quality control on the reduced-representation genomic library to obtain a qualified reduced-representation genomic library, and the specific operations are as follows: Use a Qubit3.0 fluorescence quantifier to preliminarily quantify the DNA concentration in the reduced-representation genomic library to ensure that the DNA concentration in the reduced-representation genomic library > 2 nM; use an Agilent 2100 Bioanalyzer to detect the insert size in the reduced-representation genomic library to ensure that the size of the insert meets the expectations (250 - 500 bp) and there is no adapter contamination; use a QTOWER real-time fluorescence quantitative PCR instrument produced by Analytik Jena AG to accurately quantify the effective DNA concentration in the reduced-representation genomic library to ensure that the effective DNA concentration in the reduced-representation genomic library > 2 nM.

[0080] Example 4: Sequencing of Reduced-Representation Genomic Library

[0081] The qualified reduced-genome library in Example 3 was subjected to Paired-end 150 bp (PE150) paired-end sequencing using the Illumina HiSeq sequencing platform to obtain raw image data files, which were converted into raw sequencing sequences (reads) through base calling analysis and called raw off-machine data (Raw Data). This result was stored in the FASTQ (abbreviated as fq) file format. Among them, the sequencing depth was 8.92X - 107.28X, and the average sequencing depth was 23.30X.

[0082] Since the sequencing adapters, sequences with too short length, low-quality reads, etc. contained in the reads would affect the assembly quality, the Fastp software was used to perform quality control on the Raw Data, filter out the low-quality data, and obtain high-quality data (Clean reads). The specific operations were as follows: Using the Fastp software, polyG or polyX with a tail length ≥ 10 bp in the reads of the raw off-machine data was removed, reads with more than 5 Ns (uncertain base information) in the raw off-machine data were removed, and reads with the proportion of bases with a base quality < 15 exceeding 40% of the total number of bases in the reads in the raw off-machine data were removed; the remaining reads were detected and reads with a length < 15 bp were removed to obtain high-quality sequencing data.

[0083] The Stacks software was used to identify single nucleotide polymorphism (SNP) sites in the high-quality sequencing data, with a total of 145,925. The FastQC software was used to perform quality control on the identified SNP site data. The specific operations were as follows: SNP sites with a genotype deletion (MISS) proportion > 10% in the SNP site data were removed, leaving 95,845 SNP sites; SNP sites with a minor allele frequency (MAF) < 0.05 in the SNP site data were removed, and only biallelic SNP sites were retained, leaving 48,807 high-quality SNP sites.

[0084] Example 5: Genetic diversity analysis

[0085] Based on the 48,807 high-quality SNP sites in Example 4, the Stacks 2.5.9 software was used to analyze the expected heterozygosity (H E ), observed heterozygosity (H O ), and nucleotide polymorphism (π) of 8 wild populations of Myricaria laxiflora. The specific results can be seen in Table 2.

[0086] Table 2

[0087]

[0088] In Table 2, the expected heterozygosity (H E ) refers to the heterozygosity calculated theoretically; the observed heterozygosity (H O ) refers to the probability that the alleles of two randomly selected samples are different; the nucleotide polymorphism (π) refers to the probability that two homologous sequences randomly selected from the population are the same. By comparing the values of H E , H O and π, it can be found that the wild populations W6, W7 and W8 of Myricaria laxiflora in the lower reaches of the Yangtze River are the highest, the wild populations W1, W2 and W5 of Myricaria laxiflora in the upper reaches of the Yangtze River are the second, and the wild populations W3 and W4 of Myricaria laxiflora in the upper reaches of the Yangtze River are the lowest. The above results indicate that the wild populations W6, W7 and W8 of Myricaria laxiflora in the lower reaches of the Yangtze River have the highest genetic diversity, the wild populations W1, W2 and W5 of Myricaria laxiflora in the upper reaches of the Yangtze River have lower genetic diversity, and the wild populations W3 and W4 of Myricaria laxiflora in the upper reaches of the Yangtze River have the lowest genetic diversity.

[0089] Example 6: Population genetic structure analysis

[0090] (1) Ancestral component analysis:

[0091] Based on the 48,807 high-quality SNP loci in Example 4, the ADMIXTURE software (version 1.3) was used to perform ancestral component analysis on 8 wild populations of Myricaria laxiflora. The ADMIXTURE software presupposes that the population is composed of several subpopulations (K = x). By using a simulation algorithm to find the most reasonable sample classification method when K = x, and then determining the most applicable K value for this population according to the maximum likelihood value or cross-validation error value (Cross-validation error, CV error) of each simulation. In this example, the K values were set to 2, 3, 4, 5, 6, 7, 8, 9, and 10 respectively, and the corresponding CV error values were calculated. Each K value was subjected to 10-fold cross-validation. After calculation, the CV error value was 0.25504 when K = 2; the CV error value was 0.23668 when K = 3; the CV error value was 0.21562 when K = 4; the CV error value was 0.20881 when K = 5; the CV error value was 0.20520 when K = 6; the CV error value was 0.20275 when K = 7; the CV error value was 0.20068 when K = 8; the CV error value was 0.20887 when K = 9; the CV error value was 0.19954 when K = 10. For details, see Figure 1 .

[0092] Figure 1Among them, when K = 2, 186 Myricaria laxiflora individuals from 8 wild populations of Myricaria laxiflora were divided into two genetic groups. One group consisted of all individuals from populations W1 - W5, and the other group consisted of all individuals from populations W6 - W8, indicating that the genetic relationships among different individuals within populations W1 - W5 of the 8 wild populations of Myricaria laxiflora were relatively high, the genetic relationships among different individuals within populations W6 - W8 were relatively high, while the genetic relationships between populations W1 - W5 and populations W6 - W8 were relatively far; when K = 8, each of the 8 wild populations of Myricaria laxiflora represented a genetic group; K = 10 was the optimal number of genetic groups for the 8 wild populations of Myricaria laxiflora, reflecting a strong genetic admixture among the wild populations of Myricaria laxiflora.

[0093] (2)Principal component analysis:

[0094] Based on the 48,807 high-quality SNP loci in Example 4, the principal component analysis (PCA) of 8 wild populations of Myricaria laxiflora was carried out using the Genome-wide Complex Trait Analysis software (version 1.93.2). Details can be seen in Figure 2 .

[0095] Figure 2 Two genetic groups were presented. One group consisted of populations W1 - W5, and the other group consisted of populations W6 - W8, indicating that the genetic relationships among different individuals within populations W1 - W5 of the 8 wild populations of Myricaria laxiflora were relatively high, the genetic relationships among different individuals within populations W6 - W8 were relatively high, while the genetic relationships between populations W1 - W5 and populations W6 - W8 were relatively far. The results of the principal component analysis were consistent with the analysis results of the ancestral component analysis when K = 2.

[0096] (3)Analysis of molecular variance:

[0097] Based on the 48,807 high-quality SNP loci in Example 4, the analysis of molecular variance (AMOVA) of 8 wild populations of Myricaria laxiflora was carried out using the Arlequin software (version 3.5.2.2). Details can be seen in Table 3.

[0098] Table 3

[0099]

[0100] The data in Table 3 showed that the variation proportion among populations reached 73.32%, and the variation proportion within populations was only 27.68%. The above experimental results indicated that the genetic variation of Myricaria laxiflora mainly existed among populations.

[0101] Example 7: Population evolutionary analysis

[0102] Calculate the allele frequencies based on the 48,807 high-quality SNP loci in Example 4, and use the TreeMix software (version 1.12) to infer the gene flow among 8 wild populations of *Metasequoia laxiflora* according to the allele frequencies. Here, gene flow refers to the introduction of new genetic material from one population of a species to another population, thereby changing the composition of the population gene pool. In this example, the default parameters are used when running the TreeMix software. Assume there are 0 - 9 migration events (m), and each migration event is iterated 10 times. The optimal m number is determined to be 1 through the R software package OptM (version 0.1.6). Use the result file with the optimal m number of 1 to plot a graph and perform gene flow analysis among populations using TreeMix. Specifically, see Figure 3 .

[0103] According to Figure 3 as indicated by the yellow arrow, the gene flow of *Metasequoia laxiflora* flows from the upstream population to the downstream population. The above results show that there has only been one gene migration event in the wild populations of *Metasequoia laxiflora* in history.

[0104] Example 8: Environmental isolation analysis and geographical isolation analysis

[0105] (1) Environmental isolation analysis

[0106] Nineteen climate factors were downloaded from the WorldClim database (version 2.1), namely Bio1 Annual mean temperature, Bio2 Mean diurnal temperature range, Bio3 Isothermality (Bio2 / Bio7), Bio4 Temperature seasonality, Bio5 Maximum temperature of warmest month, Bio6 Minimum temperature of coldest month, Bio7 Temperature annual range, Bio8 Mean temperature of wettest quarter, Bio9 Mean temperature of driest quarter, Bio10 Mean temperature of warmest quarter, Bio11 Mean temperature of coldest quarter, Bio12 Annual precipitation, Bio13 Precipitation of wettest month, Bio14 Precipitation of driest month, Bio15 Precipitation seasonality, Bio16 Precipitation of wettest quarter, Bio17 Precipitation of driest quarter, Bio18 Precipitation of warmest quarter, Bio19 Precipitation of coldest quarter; the annual photosynthetic active radiation (PAR) climate data was downloaded from the Chinese Ecosystem Research Network (http: / / www.cern.ac.cn), and from the Global Aridity and Potential Evapotranspiration Database (http: / / www.cgiar-csi.Download the climate data of annual potential evapotranspiration (PET) from org / data / global-aridity-and-pet-database; the resolution of the above climate factors or climate data is 30 seconds (about 1×1 km). Use ArcGIS software (version 10.2) to extract the climate data of the wild populations of Myricaria laxiflora from the above climate factors and climate data; to reduce collinearity, eliminate the climate factors or climate data with Pearson correlation coefficient ≥0.80, and finally only retain 3 climate factors (Bio1, Bio3, and Bio12). According to the above Bio1, Bio3, and Bio12, use SPSS 21.0 software to calculate the environmental distance using Euclidean distance. At the same time, based on the 48,807 high-quality SNP loci in Example 4, use Stacks 2.5.9 software to analyze the genetic distance of 8 wild populations of Myricaria laxiflora (F. ST / (1 - F ST ), F ST represents the genetic differentiation index between populations). The significance test between genetic distance and environmental distance uses 9,999 random permutations, and the Mantel test is implemented using the R software package "vegan 2.6-4", and the details can be seen Figure 4 .

[0107] According to Figure 4 it can be seen that there is a significant correlation between environmental distance and genetic distance (Mantel R = 0.516, p = 0.016). The above results indicate that environmental isolation has a significant impact on promoting the genetic differentiation of Myricaria laxiflora populations, and candidate genes related to annual average temperature, isothermality, and annual average precipitation may be useful for Myricaria laxiflora breeding.

[0108] (2) Geographical isolation analysis

[0109] According to the longitude and latitude of the distribution points of the above wild populations of Myricaria laxiflora, use GenAlex software (version 6.503) to analyze the geographical distance of the wild populations of Myricaria laxiflora, and perform logarithmic transformation on the geographical distance. At the same time, based on the 48,807 high-quality SNP loci in Example 4, use Stacks 2.5.9 software to analyze the genetic distance of 8 wild populations of Myricaria laxiflora (F ST / (1 - F ST ), F ST represents the genetic differentiation index between populations). The significance test between genetic distance and geographical distance uses 9,999 random permutations, and the Mantel test is implemented using the R software package "vegan 2.6-4", and the details can be seen Figure 5 .

[0110] According toFigure 5 It can be seen that there is a significant correlation between geographical distance and genetic distance (Mantel R = 0.884, p = 0.001). The above results indicate that geographical isolation has a significant impact on promoting the genetic differentiation of Myricaria laxiflora populations.

[0111] By comparing the Mantel R values and p values between environmental distance and genetic distance with those between geographical distance and genetic distance, it can be found that the p values of both are significant. Therefore, environmental distance and geographical distance significantly promote the genetic differentiation of Myricaria laxiflora populations.

[0112] In summary, based on the genetic diversity analysis, the genetic diversity of the downstream populations of Myricaria laxiflora is higher than that of the upstream populations; based on the population genetic structure analysis, the genetic variation of Myricaria laxiflora mainly exists among populations, and there is significant genetic differentiation between the upstream and downstream populations of Myricaria laxiflora. The genetic composition of the downstream populations of Myricaria laxiflora is quite different from that of the upstream populations; based on the population evolution analysis, there has been only one gene migration event in the history of the wild populations of Myricaria laxiflora, and the gene flow is from populations W1 and W5 to population W8, which verifies again that there is significant genetic differentiation between the upstream and downstream populations of Myricaria laxiflora; based on the environmental isolation analysis and geographical isolation analysis, environmental isolation and geographical isolation have a significant impact on promoting the genetic differentiation of Myricaria laxiflora populations. From the above analysis results, it can be concluded that the downstream populations of Myricaria laxiflora can be used as priority populations for in-situ conservation.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for population genetic analysis of Myricaria laxiflora based on reduced-representation genome sequencing, characterized in that It includes the following steps: Step 1: Obtain a number of plant samples of *Myricaria laxiflora*, extract genomic DNA from the number of plant samples of *Myricaria laxiflora* to obtain a DNA sample; Step 2: Completely digest the DNA sample with MseI enzyme and SacI enzyme to obtain digested fragments; ligate the digested fragments with sequencing adapters to obtain a ligation product; mix the ligation products corresponding to the same plant sample to obtain a mixed sample; amplify the mixed sample to obtain an amplification product; mix the amplification products corresponding to a number of plant samples, perform agarose gel electrophoresis, and select the region of 250 - 500 bp on the agarose gel after electrophoresis for recovery and purification to obtain a reduced-representation genomic library; Step 3: Perform paired-end sequencing on the reduced-representation genomic library to obtain sequencing data, and identify SNP sites based on the sequencing data; Step 4: Calculate the expected heterozygosity, observed heterozygosity, and nucleotide polymorphism of the *Myricaria laxiflora* population based on the SNP sites to analyze the genetic diversity of *Myricaria laxiflora*; perform ancestral component analysis and principal component analysis on the SNP sites to analyze the population genetic structure of *Myricaria laxiflora*.

2. The method according to claim 1, wherein The obtaining of a number of plant samples of *Myricaria laxiflora* includes: collecting the leaves of a number of *Myricaria laxiflora*, where the individuals of each *Myricaria laxiflora* plant collected are spaced ≥ 5 m apart, and placing the leaves in liquid nitrogen for ultra-low temperature preservation to obtain the *Myricaria laxiflora* plant samples.

3. The method according to claim 1 or 2, characterized in that, Step 1 further includes: performing quality control on the DNA sample to obtain a qualified DNA sample; Among them, performing quality control on the DNA sample includes: using agarose gel electrophoresis to detect the fragment size and degradation degree of the DNA sample to make the DNA sample complete; using a micro-spectrophotometer to detect the OD260 / 280 ratio of the DNA sample to make the OD260 / 280 ratio of the DNA sample 1.8 - 2.2; using a fluorescence quantitative instrument to detect the concentration of the DNA sample to make the DNA concentration in the DNA sample ≥ 50 ng / μL and the total DNA amount ≥ 2 μg.

4. The method according to any one of claims 1 to 3, characterized in that, Step 2 further includes: performing quality control on the reduced-representation genomic library to obtain a qualified reduced-representation genomic library; Among them, performing quality control on the reduced-representation genomic library includes: using a fluorescence quantitative instrument to preliminarily quantify the DNA concentration in the reduced-representation genomic library to make the DNA concentration in the reduced-representation genomic library > 2 nM; using a bioanalyzer to detect the inserted fragments in the reduced-representation genomic library to make the size of the inserted fragments 250 - 500 bp and free of adapter contamination; using a real-time fluorescence quantitative PCR instrument to accurately quantify the effective DNA concentration in the reduced-representation genomic library to make the effective DNA concentration in the reduced-representation genomic library > 2 nM.

5. The method according to any one of claims 1-4, characterized in that, In Step 3, the sequencing depth of the paired-end sequencing is 8.92X - 107.28X, and the average sequencing depth is 23.30X.

6. The method according to any one of claims 1-5, characterized in that, Step 3 further includes performing quality control on the sequencing data to obtain qualified sequencing data; The quality control of the sequencing data includes: removing polyG or polyX with a tail length of ≥10 bp in the sequencing data, removing Reads with more than 5 Ns in the sequencing data, and removing Reads in which the proportion of bases with a base quality <15 exceeds 40% of the total number of bases in the Reads; detecting the remaining Reads and removing Reads with a length <15 bp to obtain qualified sequencing data.

7. The method according to any one of claims 1-6, characterized in that Step 3 further includes performing quality control on SNP sites to obtain qualified SNP sites; The quality control of the SNP sites includes: removing SNP sites with a genotype deletion ratio >10% in the SNP sites, removing SNP sites with a minor allele frequency <0.05 in the SNP sites, and only retaining bi-allelic SNP sites to obtain qualified SNP sites.

8. The method according to any one of claims 1 to 7, characterized in that Step 4 further includes: performing molecular variance analysis, population evolution analysis, and environmental isolation analysis and geographical isolation analysis on the SNP sites.

9. Application of the method according to any one of claims 1-8 in the population genetics analysis of Myricaria laxiflora.

10. Application of the method according to any one of claims 1-8 in the in-situ conservation of Myricaria laxiflora.

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