A method for efficiently identifying ancient introgression genes of poplar ancestors and its application

Abstract

The present invention discloses a method for efficiently identifying ancient ancestral introgressed genes in poplar trees. The method comprises the following steps: obtaining a SNP dataset for a poplar population, obtaining the population structure of the poplar population, preliminarily locating the introgressed regions of the poplar population, locating candidate ancestral introgressed regions of the poplar population, obtaining the ancient ancestral introgressed regions of the poplar population, and obtaining ancient ancestral introgressed genes of the poplar population. The method disclosed in the present invention can effectively reduce false positives, reduce computational complexity, and increase identification speed. It can also obtain ancestral gene flow in multiple poplar populations, accurately identify ancient ancestral introgressed genes in poplar trees, and has a wide range of applicability.

Description

Technical Field

[0001] The present invention belongs to the technical field of genetics, and specifically relates to a method for identifying ancestral introgressed genes, and in particular to a method and application for efficiently identifying ancient introgressed genes of poplar ancestors. Background Art

[0002] Introgression, the introduction of genes from one population into the gene pool of another through hybridization or backcrossing, is a common evolutionary process in nature, influencing both population fitness and genomic landscape. The greater the allelic divergence between the donor and recipient, and the greater the number of donor individuals, the greater the impact on the genetic structure of the recipient population. Even though some existing species are limited by strong reproductive isolation, ancestral gene flow and rapid diversification of species can still occur during the formation of species. Furthermore, through analysis of the historical evolution of various species, there is increasing evidence that certain alleles introduced through introgression can rapidly enhance the adaptive capacity of a species, thereby helping the recipient population adapt to new ecological niches and uncommon habitats.

[0003] Gene introgression leaves detectable traces in the recipient genome, and the introgressed genetic information typically has a genetic background more similar to that of the donor. Detection of gene introgression primarily involves determining whether introgression has occurred, the specific site of introgression, and the proportion of introgression. Currently, statistical methods used to analyze interspecific gene introgression include relative IBD (rIBD) testing, gene tree topology assessment, and the ABBA-BABA test. However, these methods are unable to identify the common ancestral introgression region between two closely related species, limiting their ability to analyze introgression across multi-population phylogenies.

[0004] Poplars are primarily distributed in the Northern Hemisphere between 19 and 70 degrees north latitude, with a smaller number found in tropical Africa. As pioneer species, they play a crucial role in forestry production and ecological conservation, and are a globally important fast-growing tree species with short to medium rotations. Based on morphological characteristics, the genus Populus is divided into six major families: white Populus, black Populus, green Populus, euphratica, large-leaf Populus, and black Populus. Throughout their evolutionary history, they have undergone complex hybridization and clonal expansion. Identifying genes that play a crucial role in poplar evolution is crucial for improving the efficiency of selecting and breeding superior poplar germplasm resources.

[0005] Currently, studies on gene introgression between poplars mostly analyze recent gene flow within a single lineage within the genus Populus, but lack information on ancestral ancient introgression between lineages. Existing methods for detecting gene introgression are unable to accurately identify ancestral introgressed genes or calculate ancestral gene flow across multiple populations. Therefore, it is necessary to provide a method for identifying ancestral ancient introgressed genes in poplars, so as to efficiently and accurately screen ancestral introgression sites in poplars and identify genes that played an important role in poplar evolution. Summary of the Invention

[0006] In order to overcome the above problems, the inventors conducted intensive research. First, they obtained the introgression combination of poplar and preliminarily located the introgression area. Then, they clustered the poplar population according to the topological structure of the population, and then obtained the ancestral introgression area of the cluster combination. Finally, they combined the preliminarily located introgression area with the obtained ancestral introgression area to obtain the ancestral ancient introgression area and ancestral ancient introgression gene of the poplar population, which effectively reduced false positives, increased the identification speed, and accurately located the ancestral ancient introgression gene of poplar, thereby completing the present invention.

[0007] Specifically, the purpose of the present invention is to provide the following aspects:

[0008] In a first aspect, a method for identifying an ancient introgression gene from a poplar ancestor is provided, the method comprising the following steps:

[0009] Step 1, obtain a SNP dataset of a poplar population;

[0010] Step 2, obtaining the population structure of the poplar population;

[0011] Step 3, preliminarily locate the introgression area of the poplar population;

[0012] Step 4, locate candidate ancestral introgression regions of the poplar population;

[0013] Step 5, obtaining the ancestral paleointrogression area of the poplar population;

[0014] Step 6, obtain the ancestral ancient introgression genes of the poplar population.

[0015] In a second aspect, a method for identifying ancient introgressed genes of poplar ancestors described in the first aspect is provided for use in poplar breeding.

[0016] The beneficial effects of the present invention include:

[0017] (1) The method for identifying ancient introgressed genes from poplar ancestors provided by the present invention can effectively reduce false positives, reduce the amount of calculation, and improve the identification speed;

[0018] (2) The method provided by the present invention for identifying ancient introgressed genes from poplar ancestors has a wide range of applications and is not limited to specific species, which is conducive to identifying key genes with important functions in the evolution of species;

[0019] (3) The method provided by the present invention for identifying ancient introgression genes of poplar ancestors can locate the ancestral introgression genes more precisely, which is conducive to better understanding the mixing history between populations, identifying the advantages of certain populations under specific environmental pressures, and exploring certain functional stress-resistant genes that are conducive to adapting to specific environments, laying the foundation for the subsequent molecular technology-assisted breeding. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flow chart illustrating the identification of ancient introgressed genes of the ancestral species of Populus white poplar described in Example 1 of the present invention is shown;

[0021] Figure 2 The poplar population evolutionary tree described in Example 1 of the present invention is shown;

[0022] Figure 3 The candidate ancestral introgression regions of multiple populations of Populus white poplar described in Example 1 of the present invention are shown;

[0023] Figure 4 The whole genome distribution map of the ancient introgressed genes of the poplar ancestor described in Example 1 of the present invention is shown;

[0024] Figures 5 to 7 A comparison of Fst values between the ancestral introgression regions and the non-ancestral introgression regions of three randomly selected pairs of poplar combinations in Experimental Example 1 of the present invention is shown;

[0025] Figure 8 A comparison diagram of introgression signals in Experimental Example 2 of the present invention is shown. DETAILED DESCRIPTION

[0026] The present invention will be further described in detail below through preferred embodiments and examples. Through these descriptions, the characteristics and advantages of the present invention will become more clear and distinct.

[0027] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0028] In the process of molecular breeding of poplars, identifying the segments in the poplar genome where ancestral ancient introgression may have occurred, and then exploring candidate ancestral ancient introgression genes with potential functions, can provide new means for mining the genetic resources of the poplar genome. At the same time, it is conducive to exploring more genes with important functions based on the evolutionary history of the poplar lineage, thus laying the foundation for molecular design breeding of poplars.

[0029] Among them, ancestral paleointrogression refers to the gene introgression that occurred in the common ancestor before species differentiation.

[0030] A first aspect of the present invention provides a method for identifying ancient introgressed genes from poplar ancestors, the method comprising the following steps:

[0031] In the present invention, the SNP is a single nucleotide polymorphism (SNP).

[0032] Preferably, step 1 includes the following sub-steps:

[0033] Step 1-1, obtain the original SNP dataset of the poplar population.

[0034] In the present invention, the poplar population is composed of different species of poplars from around the world, more preferably including Populus euphratica, Populus alba, Populus roxburghii, Populus tremula, Populus tremula, Populus deltoides, Populus trichocarpa, Populus simonii and Populus odorifera.

[0035] According to a preferred embodiment of the present invention, resequencing data of each individual in the poplar population is obtained, and the resequencing data is aligned to the Populus trichocarpa reference genome, SNP sites are identified at the whole genome level and the genotypes of the SNP sites are obtained.

[0036] The DNA of each individual in the poplar population can be resequenced, and resequencing data of different poplars can also be obtained from databases disclosed in the prior art.

[0037] More preferably, the resequencing data of the poplar population are aligned using Burrows-Wheeler Aligner v0.7.5a-r405 (default parameters).

[0038] In a further preferred embodiment, whole genome SNPs are identified using Genome Analysis Toolkit (GATK) v4.0, and the parameters are preferably: SNP: QD < 2.0 || MQ < 20.0 || FS > 60.0 || SOR > 3.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0.

[0039] In the present invention, the original SNP data set of the poplar population is obtained through the above steps.

[0040] According to a preferred embodiment of the present invention, the resequencing data of the poplar population consists of resequencing data of 834 poplar individuals, preferably consisting of resequencing data of 66 alba poplars, 62 clapperwood poplars, 111 European poplars, 93 small-leaved poplars, 97 American black poplars, 96 Chinese poplars, 80 poplars, 95 fragrant poplars and 134 trichocarpa poplars.

[0041] The inventors considered that the ancestral paleointrogression event of a species occurred before species divergence, and that the introgressed region is generally retained in the genomes of the diverging species. Therefore, they selected multiple poplar populations to obtain the ancestral paleointrogression region. These multiple populations can represent the different subclades to which they belong during the identification process. In addition, because the Populus nigra and Populus brevis subclades within the genus are relatively rare and poorly studied, the inventors selected representative populations of the other four most common subclades (i.e., Populus alba, Populus nigra, Populus cathayana, and Populus euphratica) to provide a substantial representation of the genetic information of the genus.

[0042] Step 1-2: Optimize the original SNP dataset of the poplar population to obtain the SNP dataset of the poplar population.

[0043] In the present invention, the optimization includes quality control and filtering.

[0044] Preferably, the quality control standards are: ① biallelic sites; ② Maximum Missing Rate (Maximum Missing Rate) <0.2; ③ Minor Allele Frequency (MAF) >0.05;

[0045] Furthermore, it is preferred to use Vcftools software, for example, Vcftools_0.1.16, to perform filtering according to the above standards.

[0046] According to a preferred embodiment of the present invention, the optimization further includes genotype filling.

[0047] In the present invention, the genotype filling refers to supplementing the missing data based on the known genotype data to increase the marker density and improve the accuracy of the results.

[0048] Preferably, beagle v5.4 software is used for genotype filling, and the software parameters are conventional settings in the prior art.

[0049] In the present invention, a high-quality SNP data set of a poplar population is preferably obtained after screening, with a total of 3,434,667 SNP sites.

[0050] Step 2: Obtain the population structure of the poplar population.

[0051] In the present invention, the population structure of poplars can preferably be obtained using software commonly used in the prior art, such as Admixture v1.3.0 software.

[0052] Furthermore, the poplar population is divided into groups according to the obtained population structure to obtain subpopulations of the poplar population.

[0053] Preferably, based on the SNP dataset of the poplar population obtained in step 1, the population structure of the poplar population is obtained by using Admixture v1.3.0 software, and the minimum cross-validation error value is selected as the optimal clustering.

[0054] Step 3: Preliminary location of the introgression area of the poplar population.

[0055] Wherein, step 3 includes the following sub-steps:

[0056] Step 3-1, determine the introgression combination of the poplar population.

[0057] Preferably, step 3-1 includes the following sub-steps:

[0058] Step 3-1-1, determine whether gene exchange occurs in subpopulations.

[0059] In the present invention, the outgroup is determined based on the subgroup clustering results to determine whether gene exchange occurs between different triplets of subgroups, wherein the triplet refers to a combination of three different subgroups, called a triplet.

[0060] Preferably, the Dtrios program (i.e., D-statistic method) in the Dsuite v0.5 software commonly used in the prior art is used to obtain the D values (i.e., D-statistic, used to determine whether there is gene introgression) between different triplet groups in the subpopulation. When D>0, it is determined that gene exchange may have occurred in the subpopulation.

[0061] Step 3-1-2, obtain subpopulation combinations with significant gene exchange.

[0062] In the present invention, subgroup combinations with significant gene exchange in the triple group were selected, that is, poplar combinations that may undergo introgression.

[0063] According to a preferred embodiment of the present invention, combinations with Z-scores>=3 are selected as introgression combinations with significant gene exchange.

[0064] Among them, Z-scores are the standardized results of D values (Z = D / std _ err (D)).

[0065] Step 3-2, obtain the introgression area of the poplar population.

[0066] According to a preferred embodiment of the present invention, the introgression combination of the poplar population obtained in step 3-1 is detected by a sliding window analysis method to obtain the introgression region of the poplar population.

[0067] In a further preferred embodiment, the sliding window analysis uses 40 to 60 SNPs as a window and 10 to 30 SNPs as a step size;

[0068] Preferably, the sliding window analysis uses 50 SNPs as a window and 20 SNPs as a step size.

[0069] In a further preferred embodiment, the introgression regions of all poplar population combinations are obtained by using the Dinvestigate program in the D-suite software (used to obtain fdM values).

[0070] In the present invention, the poplar introgression region obtained through this step includes the ancestral introgression region and the non-ancestral introgression region.

[0071] The inventors have discovered that by first identifying combinations with significant introgression signals within a poplar population and then determining introgression regions based on these combinations, analysis of incorrect combinations can be effectively avoided, reducing false positives, reducing computational effort, and significantly increasing identification speed. According to a preferred embodiment of the present invention, during the process of determining introgression regions, the window size in the sliding window analysis was set to 50 SNPs, which facilitated accurate identification of introgression regions in poplars, thereby enabling more precise localization of introgressed genes.

[0072] According to a preferred embodiment of the present invention, in the process of obtaining the introgression area of the poplar population, the largest top 5% window of the detection results of each introgression combination is set as the introgression area of the combination.

[0073] Preferably, the largest top 5% windows of the detection results of each introgression combination are the largest top 5% windows of fdM.

[0074] The present study found that the target ancestral introgression occurred before the divergence of the target species. During the long evolutionary history after this divergence, unique changes likely occurred, leading to a weakening of the introgression signal. Therefore, the present invention selected a more relaxed threshold of 5% when screening for introgressed regions using fdM, rather than the commonly used 1%-3%. This threshold also includes weaker signals, thus facilitating further screening of ancestral paleointrogressed regions.

[0075] Step 4: Locate candidate ancestral introgression regions in poplar populations.

[0076] Preferably, step 4 includes the following sub-steps:

[0077] Step 4-1, obtain the topological structure among poplar subpopulations.

[0078] In the present invention, the poplar subpopulation is the poplar subpopulation obtained in step 2.

[0079] In the present invention, the subpopulation topology of poplar can be obtained using software commonly used in the prior art, such as SNPhylo software. Preferably, a phylogenetic tree is generated using Populus euphratica as an outgroup to obtain the topological relationship between different populations of poplar.

[0080] Step 4-2: Group the poplar subpopulations according to the topological structure.

[0081] According to a preferred embodiment of the present invention, different five-taxon combinations of poplar subpopulations are obtained based on the topological structure;

[0082] Preferably, the five taxonomic groups are represented as (((P1, P2), (P3, P4)), O), wherein the divergence time of the P3 and P4 populations cannot be later than that of the P1 and P2 populations, and O represents an outgroup;

[0083] Introgression analysis was performed on the five taxa composed above, that is, to determine whether the ancestors of the two populations P1 and P2 had introgressed with the P3 or P4 population.

[0084] In a further preferred embodiment, P1 and P2 are set as Populus alba populations, P3 and P4 are set as Populus cathayana and Populus nigra populations, and O is set as Populus euphratica, so as to identify the ancestral introgression regions common to multiple populations of Populus alba.

[0085] Step 4-3, obtain the ancestral introgression region for each combination.

[0086] In the present invention, step 4-3 preferably includes the following sub-steps:

[0087] Step 4-3-1, select the resequencing individual with the deepest sequencing depth in each poplar population in the combination.

[0088] The sequencing depth refers to the ratio of the total number of bases (bp) obtained by sequencing to the genome size (Genome), and is one of the indicators for evaluating the sequencing amount.

[0089] Step 4-3-2, splitting the chromosomes of the selected resequencing individual into genomic segments.

[0090] In the present invention, chromosomes are preferably split into 100 kb genomic fragments.

[0091] Step 4-3-3, perform ancestral introgression detection on each genomic segment.

[0092] The inventors have found that the DFOIL method in the prior art can only calculate the ancestral introgression region of two species and cannot directly detect the common ancestral gene flow of multiple populations. Therefore, after a large number of experimental studies, the present invention preferably detects candidate ancestral introgression regions of the five taxonomic groups of poplars according to a method comprising the following steps:

[0093] Step i, obtain all possible ancestral introgression regions for each pair of P1 and P2.

[0094] According to a preferred embodiment of the present invention, in step i, first, for the five taxonomic groups (((P1, P2), (P3, P4)), O), the first group P1 and P2 are controlled to remain unchanged, respectively expressed as $P1 and $P2, and different combinations of P3 and P4 are changed to obtain multiple different introgression results of the first group $P1 and $P2.

[0095] Among them, each time the combination of P3 and P4 is changed, a gradual introgression result is obtained, and by changing different combinations of P3 and P4, multiple different gradual introgression results of the first group $P1 and $P2 are obtained.

[0096] Then, all possible ancestral introgression regions of the first group $P1 and $P2 are obtained, preferably by taking the union of multiple different introgression results, wherein the union is preferably recorded as U1.

[0097] According to a preferred embodiment of the present invention, the combination of P1 and P2 is changed, and step i is repeated to obtain all possible ancestral introgression regions corresponding to n different combinations of P1 and P2.

[0098] Among them, n represents the number of combinations of P1 and P2, that is, a group of P1 and P2 is recorded as: n=1.

[0099] Preferably, all possible ancestral introgression regions of each pair P1 and P2 are obtained by taking the union of multiple different introgression results, and the union is preferably recorded as U2, U3, ..., Un respectively.

[0100] Step ii, confirm candidate ancestral introgression regions in multiple populations.

[0101] According to a preferred embodiment of the present invention, the overlap of all possible ancestral introgression regions of each pair of P1 and P2 is obtained, and the candidate ancestral introgression regions of multiple populations are confirmed based on the overlap.

[0102] In a further preferred embodiment, the overlap degree of U1 to Un is obtained by taking the intersection, that is, taking the intersection of U1, U2, ..., and Un.

[0103] In a further preferred embodiment, the overlap is 80%, that is, when a region exists in ≥80% of the Un union results, the region is considered to be a candidate ancestral introgression region of multiple poplar populations.

[0104] For example, when n = 6, if a region exists in 4.8 or more combinations (i.e., 5 and 6 combinations), the region is considered to be a candidate ancestral introgression region of multiple populations.

[0105] The inventors have found that the accuracy of obtaining the gene flow of the common ancestors of multiple subpopulations through the above method can be significantly improved.

[0106] Step 5, obtain the ancestral paleointrogression area of the poplar population.

[0107] According to a preferred embodiment of the present invention, the introgression regions detected in both step 3 and step 4 are taken as the final ancestral introgression regions of the poplar population, that is, the ancestral ancient introgression regions of the poplar population.

[0108] Preferably, the intersection of the introgression region of the poplar population initially located in step 3 and the candidate ancestral introgression region of the poplar population located in step 4 is taken to obtain the ancestral ancient introgression region of the poplar population.

[0109] The inventors found that in order to eliminate the influence of recombination breakpoints, the DFOIL method often uses a larger detection window, which makes it difficult to effectively determine key functional genes. Therefore, in the present invention, by combining the introgression region located by the 50 SNPs region in step 3 with the ancestral introgression region located in step 4, the size of the ancestral introgression segment can be reduced, false positives can be reduced, and the ancestral introgression gene can be located more precisely. It is also conducive to better understanding the mixing history between populations, identifying the advantages of certain populations under specific environmental pressures, and exploring certain functional stress-resistant genes that are conducive to adapting to specific environments, laying the foundation for the later development of molecular technology-assisted breeding.

[0110] Step 6, obtain the ancestral ancient introgression genes of the poplar population.

[0111] According to a preferred embodiment of the present invention, gene annotation is performed on the ancestral ancient introgression region of the poplar population obtained in step 5 to obtain the ancestral ancient introgression genes of the poplar population.

[0112] In a further preferred embodiment, the 2000 bp before each gene in the genome annotation file of the reference genome (in the present invention, the gene region + the promoter region 2000 bp before the gene) is taken as the gene annotation file of the ancestral ancient introgression segment, and the ancestral ancient introgression genes of the poplar population are preferably annotated using the BEDTools intersect command.

[0113] The method for identifying ancestral ancient introgression genes of poplar described in the present invention first determines the introgression combination and preliminarily locates the poplar introgression area, and then accurately obtains the common ancestral introgression area of multiple populations based on the topological results. The two results are then combined and verified with each other, which can further reduce false positives and more accurately locate the ancestral ancient introgression area, and then explore candidate ancestral ancient introgression genes with potential functions, which is conducive to exploring more genes that play an important role on the basis of the evolutionary history of the poplar lineage, thereby laying the foundation for molecular design breeding of poplar.

[0114] The second aspect of the present invention provides an application of the method for identifying ancient introgressed genes of poplar ancestors described in the first aspect in poplar breeding.

[0115] Example

[0116] The present invention is further described below through specific examples. However, these examples are merely exemplary and do not constitute any limitation to the scope of protection of the present invention.

[0117] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0118] Unless otherwise specified, the databases, bioinformatics software, etc. used in the following examples can be obtained from the corresponding official websites.

[0119] Example 1 Identification of ancestral ancient introgression genes of Populus

[0120] This embodiment follows Figure 1 The process shown is for identification:

[0121] Step 1: Obtain resequencing data of 834 poplar individuals in the database, the specific composition is shown in Table 1.

[0122] Table 1

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132]

[0133] The bam file of each sample was aligned to the reference genome of Populus trichocarpa using Burrows-Wheeler Aligner v0.7.5a-r405 (default parameters). Single nucleotide polymorphisms (SNPs) were identified at the genome-wide level and the genotypes of the SNPs were obtained.

[0134] Genome Analysis Toolkit (GATK) v4.0 was used to identify single nucleotide polymorphism (SNP) sites throughout the genome with the following parameters: SNP: QD < 2.0 || MQ < 20.0 || FS > 60.0 || SOR > 3.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0, and the original SNP dataset of the poplar population was obtained.

[0135] The raw SNP dataset was quality-controlled and filtered using Vcftools_0.1.16, using the following criteria: ① biallelic sites; ② Maximum Missing Rate (MMR) <0.2; and ③ Minor Allele Frequency (MAF) >0.05. A high-quality SNP dataset containing 3,434,667 SNPs was obtained for the poplar population.

[0136] Step 2: Based on the SNPs dataset obtained in step 1, the population structure of the poplar population was obtained using Admixture v1.3.0 software, and the minimum cross-validation error value was selected as the optimal clustering.

[0137] The grouping results are: Populus euphratica, Populus tremula, Populus tremula, Populus alba, Populus roxburghii, Populus nigra, Populus simonii, Populus odoratus, and Populus trichocarpa.

[0138] Step 3: Based on the subpopulation clustering results, using Populus euphratica as the outgroup, the Dtrios program in Dsuite v0.5 software was used to calculate D values between different triplet groups of the eight subpopulations (Populus tremula, Populus tremula, Populus alba, Populus siliqua, Populus deltoides, Populus simonii, Populus odorifera, and Populus trichocarpa). If D values were significant (Z-scores >= 3), it indicated that there was gene exchange between the two populations in the triplet group. The Dtrios results are shown in Table 2:

[0139] Table 2

[0140]

[0141]

[0142]

[0143] As can be seen from Table 2, the triplet groups corresponding to Z-scores>=3 are subpopulation combinations with significant gene exchange. For example, the Z-score of the first row in Table 2 is 41.8332, indicating that there is gene exchange between the Populus simonii, Populus trichocarpa, and Populus deltoides subpopulations and the Populus deltoides subpopulations.

[0144] For combinations with significant gene exchange, we further used the Dinvestigate program to locate introgressed regions using a sliding window algorithm with a window size of 50 SNPs and a step size of 20 SNPs. The introgressed regions were defined as the windows with the largest fdM in the top 5% of the Dinvestigate results.

[0145] Step 4: Based on the subpopulation results of step 2, SNPhylo software was used to generate a phylogenetic tree with Populus euphratica as the outgroup to obtain the topological relationship between different populations of Populus. The results are as follows: Figure 2 shown.

[0146] To identify ancestral introgression regions shared by multiple populations of Populus alba, five taxonomic groups (((P1, P2), (P3, P4)), and O) were further defined based on the topological results. P1 and P2 were designated as Populus alba populations, P3 and P4 as Populus cathayana and Populus nigra populations, and outgroup O as Populus euphratica. The Populus alba populations include Populus siliqua, Populus alba, Populus tremula, and Populus tremula; the Populus cathayana populations include Populus odorifera, Populus simonii, and Populus trichocarpa; and the Populus nigra populations include Populus deliciosa.

[0147] While keeping P1 and P2 constant, we changed different combinations of P3 and P4. We selected the resequenced individuals with the deepest sequencing depth in each poplar population, converted them into fasta format, and split them into 100 kb genomic segments. After alignment, we used the DFOIL method to calculate the introgression results of each combination, as shown in Table 3. There are 6 pairs of P1 and P2 combinations in total, and 6 results were obtained for each pair of P1 and P2 combinations. The union of the 6 results is denoted as U1 (i.e., the union of the 6 results in the first column). Set), which represents the candidate ancestral introgression segment of the pair of P1 and P2 combinations. Among them, the five taxonomic groups of poplars include 6 pairs of poplar combinations (i.e., 6 pairs of P1 and P2 combinations), and their introgression combinations total 36. For example, the first horizontal column is the first pair of P1 and P2 combinations, among which the first introgression combination is: P1 is Populus scolopendra, P2 is Populus alba, P3 is Populus nigra, P4 is Populus odoratus, and O is Populus euphratica. The same applies to other combinations. Table 2 has a total of six horizontal columns, representing 6 pairs of P1 and P2 combinations.

[0148] Table 3

[0149]

[0150]

[0151]

[0152] By changing the population categories of P1 and P2 and repeating the above steps, we can obtain the ancestral introgression segments U2, U3, U4, U5 and U6 corresponding to different combinations of P1 and P2, respectively.

[0153] After the above steps, a total of 6 groups of ancestral introgression segments were obtained from the 36 combinations of the five taxonomic groups of poplars, namely U1, U2, U3, U4, U5 and U6.

[0154] The intersection of each group of ancestral introgression segments (i.e., U1 to U6) was taken, and when a region existed in all five pairs of poplar combinations (P1 and P2 combinations), it was considered to be a candidate ancestral introgression region for multiple poplar populations. The results are as follows: Figure 3 As shown, the solid triangle marks indicate that the same region exists in ≥5 pairs of combinations, that is, the candidate ancestral introgression region of multiple poplar populations.

[0155] Depend on Figure 3 It can be seen that the number of introgression regions present in all six pairs of poplar combinations is the largest, indicating that a considerable number of regions left by ancestral ancient introgression can still be detected in each combination; and the regions present in ≥80% or ≥5 combinations are also considered to be ancestral ancient introgression regions. This is because in the long-term historical evolution process, some regions may have undergone unique changes in individual species and cannot be identified, but they are still detected as ancestral ancient introgression regions in other species. Therefore, these regions are also identified as ancestral ancient introgression regions.

[0156] Step 5: Take the intersection of the introgression segments of each significant triplet obtained in step 3 and the candidate ancestral introgression regions of poplar obtained in step 4 to obtain the final poplar ancestral ancient introgression segments, and use the BEDTools intersect command to take the first 2000bp of each gene for annotation to obtain 2961 candidate ancestral ancient introgression genes of poplar. The results are as follows: Figure 4 shown.

[0157] Figure 4 In the figure, the dark horizontal lines of different thicknesses on the chromosome are the locations of the ancestral ancient introgressed genes. It can be seen that the ancestral ancient introgressed genes are discontinuously distributed on the chromosome. This is because the ancestral introgression occurred earlier, and more recombination occurred over time, gradually forming a discontinuous distribution feature.

[0158] Experimental example

[0159] Experimental Example 1: Validation of the identified ancient introgression regions of Poplar

[0160] Gene introgression will cause the introgressed regions in the two species to be more similar and have a lower Fst value, but because the ancestral introgression occurred earlier and has undergone a longer period of natural changes, the Fst value of the ancestral introgression is slightly higher than that of the non-ancestral introgression.

[0161] In the results of step 4 of Example 1, three pairs of poplar combinations (respectively: Populus alba-Populus trichocarpa, Populus tremula-Populus nigra, Populus tremula-Populus fragrantis) were randomly selected from P1, P2, P3, and P4, and the Fst value of each combination was calculated using vcftools software (normal settings) (with 10 kb as a window and 5 kb as a step size). The Fst values of 1000 regions were randomly selected from the ancestral introgression region and the non-ancestral introgression region (the introgression region obtained in step 3 includes the ancestral introgression region and the non-ancestral introgression region, and the non-introgression region is the result of deleting the ancestral ancient introgression region finally obtained in step 5 from the introgression region obtained in step 3). The significance comparison was performed, and the calculation was repeated three times to take the average value. The results are as follows: Figures 5-7 shown.

[0162] Depend on Figures 5-7 It can be seen that the Fst value of the ancestral introgression region in each combination is slightly higher than that of the non-ancestral introgression region. The results are in line with expectations, indicating that the ancestral ancient introgression region obtained by the method described in Example 1 of the present invention is reliable.

[0163] Experimental Example 2 Comparison of introgression signals

[0164] The ancestral paleointrogression region result finally obtained in Example 1 and the non-ancestral paleointrogression region obtained in step 3 (the introgression region obtained in step 3 includes the ancestral introgression region and the non-ancestral introgression region, and the non-introgression region is the result of the introgression region obtained in step 3 minus the ancestral paleointrogression region finally obtained in step 5) were taken as the top 100 maximum values, standardized, and compared. The results are as follows: Figure 8 shown.

[0165] Depend on Figure 8 It can be seen that the fdM value of the ancestral introgression area is significantly lower than that of the non-ancestral introgression area, indicating that since the ancestral introgression of poplar occurred before the differentiation of poplar, it is very likely that unique changes occurred in the long historical evolution process after differentiation, resulting in the weakening of the introgression signal. The method described in Example 1 of the present invention can avoid missing the ancestral introgression signal.

[0166] The present invention has been described in detail above with reference to specific embodiments and exemplary examples. However, these descriptions are not to be construed as limiting the present invention. Those skilled in the art will appreciate that, without departing from the spirit and scope of the present invention, various equivalent substitutions, modifications, or improvements may be made to the technical solutions and implementations of the present invention, all of which fall within the scope of the present invention.

Claims

1. A method for identifying ancient introgressed genes from poplar ancestors, characterized in that The method comprises the following steps: Step 1, obtain a SNP dataset of a poplar population; Step 2, obtaining the population structure of the poplar population; Step 3, preliminarily locate the introgression area of the poplar population; Step 4, locate candidate ancestral introgression regions of the poplar population; Step 4 includes the following sub-steps: Step 4-1, obtaining the topological structure among poplar subpopulations; Step 4-2, grouping the poplar subpopulations according to the topological structure; Step 4-3, obtain the ancestral introgression region of each combination; Step 4-3 includes the following sub-steps: Step 4-3-1, select the resequenced individual with the deepest sequencing depth in each poplar population in the combination; Step 4-3-2, splitting the chromosomes of the selected resequencing individuals into genomic segments; Step 4-3-3, perform ancestral introgression detection on each genomic segment; Step 5, obtaining the ancestral paleointrogression area of the poplar population; Step 6, obtain the ancestral ancient introgression genes of the poplar population.

2. The method for identifying ancient introgressed genes from poplar ancestors according to claim 1, characterized in that Step 1 includes the following sub-steps: Step 1-1, obtain the original SNP dataset of the poplar population; Steps 1-2: Optimize the original SNP dataset of the poplar population.

3. The method for identifying ancient introgressed genes from poplar ancestors according to claim 1, characterized in that Step 2 also includes: The poplar population was divided into groups according to the obtained population structure to obtain subpopulations of the poplar population.

4. The method for identifying ancient introgressed genes from poplar ancestors according to claim 3, characterized in that Step 3 includes the following sub-steps: Step 3-1, determine the introgression combination of the poplar population; Step 3-2, obtain the introgression area of the poplar population.

5. The method for identifying ancient introgressed genes from poplar ancestors according to claim 4, characterized in that Step 3-1 includes the following sub-steps: Step 3-1-1, determine whether gene exchange occurs in subpopulations; Step 3-1-2, obtain subpopulation combinations with significant gene exchange.

6. The method for identifying ancient introgressed genes from poplar ancestors according to claim 1, characterized in that In step 5, the introgression regions detected in both steps 3 and 4 are taken as the ancestral paleo-introgression regions of the poplar population.

7. Use of the method for identifying ancient introgressed genes of poplar ancestors according to any one of claims 1 to 6 in poplar breeding.

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