Method for efficiently identifying ancestor ancient introgression gene of poplar and application

Abstract

The invention discloses a method for efficiently identifying an ancestral ancient introgression gene of a poplar. The method comprises the following steps: obtaining an SNP data set of a poplar population, obtaining a population structure of the poplar population, preliminarily positioning an introgression region of the poplar population, positioning a candidate ancestor introgression region of the poplar population, obtaining an ancestor ancient introgression region of the poplar population, and obtaining an ancestor ancient introgression gene of the poplar population. The method disclosed by the invention can effectively reduce false positive, reduce the calculation amount and improve the identification speed, can obtain the progenitor gene flow of multiple populations of the poplar, can accurately identify the progenitor paleo-introgression gene of the poplar, and is wide in application range.

Description

Technical Field

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

[0002] Gene introgression refers to the process of genes from one group entering the gene pool of another group through hybridization or backcrossing. This is a common evolutionary process in nature, which affects both population fitness and genomic landscape. The greater the difference in alleles between the donor and the 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 strongly restricted by reproductive isolation, ancestral gene flow may still occur during the formation of species history and promote rapid species diversification. In addition, through the analysis of the historical evolution of different species, there is increasing evidence that certain alleles introduced through gene introgression will quickly improve the adaptability of species, thereby helping the recipient population adapt to new ecological niches and unused habitats.

[0003] Gene introgression will leave detectable traces in the recipient genome, and the introgressed genetic information usually has a genetic background that is more similar to the donor. The detection of gene introgression mainly includes determining whether introgression has occurred, the specific site and the introgression ratio. At present, the statistical methods used to analyze interspecific gene introgression include relative IBD (rIBD) detection, gene tree topology evaluation, ABBA-BABA test, etc., but these methods cannot identify the common ancestral introgression area of ​​two closely related species, and the ability to analyze the introgression of multiple population phylogeny is limited.

[0004] Poplars are mainly distributed in the northern hemisphere between 19 and 70 degrees north latitude, with a few distributed in tropical Africa. As pioneer species, they play a very important role in forestry production and ecological environment construction, and are important fast-growing tree species with medium and short rotation periods in the world. According to morphological characteristics, the genus Populus is divided into six major factions, namely, white poplar, black poplar, green poplar, euphratica, large-leaf poplar, and black poplar. They have undergone complex hybridization and asexual expansion during their historical evolution. Identifying genes that play an important role in the evolution of poplars is of great significance to improving the efficiency of breeding excellent germplasm resources of poplars.

[0005] At present, most of the studies on gene introgression between poplars are analyses of recent gene flow within a certain faction of the genus Populus, and the ancestral ancient introgression information between factions is unclear. The gene introgression detection methods in the prior art cannot accurately identify ancestral introgression genes, nor can they calculate ancestral gene flow in multiple populations. Therefore, it is necessary to provide a method for identifying ancestral ancient introgression genes of poplars, so as to efficiently and accurately screen ancestral introgression sites of poplars and identify genes that play an important role in the evolution of poplars. Summary of the invention

[0006] In order to overcome the above-mentioned problems, the inventors conducted intensive research and first obtained the introgression combination of poplar and preliminarily located the introgression region. Then, the poplar population was clustered according to the topological structure of the population, and the ancestral introgression region of the clustered combination was obtained. Finally, the preliminarily located introgression region was combined with the obtained ancestral introgression region to obtain the ancestral ancient introgression region and ancestral ancient introgression genes of the poplar population, which effectively reduced false positives, increased the identification speed, and accurately located the ancestral ancient introgression genes 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, obtaining 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 paleo-introgression 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 introgression 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 introgression genes of 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 for identifying ancient introgressed genes of poplar ancestors provided by the present invention 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 process of species evolution;

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

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

[0021] Figure 2 The poplar population evolution 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 introgression genes of the ancestor of Populus chinensis described in Example 1 of the present invention is shown;

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

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

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

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

[0031] Step 1: Obtain the SNP dataset of the poplar population.

[0032] In the present invention, the SNP is a single nucleotide polymorphism (SNP).

[0033] Preferably, step 1 includes the following sub-steps:

[0034] Step 1-1, obtain the original SNP data set of the poplar population.

[0035] In the present invention, the poplar population is composed of different types of poplars from all over the world, more preferably including Populus euphratica, Populus alba, Populus robur, Populus tremula, Populus tremula, Populus nigra, Populus trichocarpa, Populus simonii and Populus odorifera.

[0036] 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 reference genome of Populus trichocarpa ( https: / / phytozome-next.jgi.doe.gov / info / Ptrichocarpa_v4_1 ) to identify SNP loci at the whole genome level and obtain the genotypes of SNP loci.

[0037] The DNA of each individual in the poplar population can be resequenced, and the resequencing data of different poplars can also be obtained from the database disclosed in the prior art.

[0038] Preferably, the resequencing data of the poplar population is obtained in the National Center for Biotechnology Information (NCBI) and the China National Center for Bioinformation (CNCB) databases.

[0039] More preferably, the resequencing data of the poplar population are aligned using Burrows-Wheeler Aligner v0.7.5a-r405 (default parameters).

[0040] In a further preferred embodiment, the 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.

[0041] In the present invention, the original SNP data set of the poplar population is obtained through the above steps.

[0042] 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 clavicula sirmifolia, 111 European poplars, 93 small-leaved poplars, 97 American black poplars, 96 Chinese poplars, 80 poplars, 95 fragrant poplars and 134 trichocarpa poplars.

[0043] The inventors consider that the ancestral ancient introgression event of the species occurred before the species differentiation, and the introgression region is generally retained in the genome of the different species after differentiation, so multiple poplar populations are selected to obtain the ancestral ancient introgression region, and multiple populations can represent the different sub-branches to which they belong during the identification process. In addition, since the number and research of the black poplar and large-leaf poplar schools in the genus Populus are relatively small, the present invention selects representative tree species groups from the other four most common sub-branches (i.e., white poplar, black poplar, green poplar and euphratica), which can basically represent the genetic information of the genus Populus.

[0044] Step 1-2, optimizing the original SNP data set of the poplar population to obtain the SNP data set of the poplar population.

[0045] In the present invention, the optimization includes quality control and filtering.

[0046] 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;

[0047] Furthermore, it is preferred to use Vcftools software, for example, Vcftools_0.1.16 to filter according to the above standards.

[0048] According to a preferred embodiment of the present invention, the optimization further includes genotype filling.

[0049] 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.

[0050] Preferably, beagle v5.4 software is used for genotype filling, and the software parameters are conventional settings in the prior art.

[0051] 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.

[0052] Step 2, obtain the population structure of the poplar population.

[0053] In the present invention, the population structure of poplars can preferably be obtained by using commonly used software in the prior art, such as Admixture v1.3.0 software.

[0054] Furthermore, the poplar population is grouped according to the obtained population structure to obtain subpopulations of the poplar population.

[0055] Preferably, based on the SNP data set 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.

[0056] Step 3: Preliminary location of the introgression area of ​​the poplar population.

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

[0058] Step 3-1, determine the introgression combinations of the poplar population.

[0059] Preferably, step 3-1 includes the following sub-steps:

[0060] Step 3-1-1, determine whether gene exchange occurs in subpopulations.

[0061] In the present invention, the outgroup is determined based on the subgrouping results to determine whether gene exchange occurs between different triplets of subgroups, wherein the triplets refer to a combination of three different subgroups, called a triplet.

[0062] 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.

[0063] Step 3-1-2, obtain subgroup combinations with significant gene exchange.

[0064] In the present invention, subgroup combinations with significant gene exchange in the triple group are selected, that is, poplar combinations that may undergo introgression.

[0065] According to a preferred embodiment of the present invention, combinations with Z-scores>=3 are selected as introgression combinations with significant gene exchange.

[0066] Among them, Z-scores are the standardized results of D values ​​(Z=D / std_err(D)).

[0067] Step 3-2, obtain the introgression area of ​​the poplar population.

[0068] 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 area of ​​the poplar population.

[0069] 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;

[0070] Preferably, the sliding window analysis uses 50 SNPs as a window and 20 SNPs as a step size.

[0071] 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).

[0072] In the present invention, the poplar introgression region obtained through this step includes the ancestral introgression region and the non-ancestral introgression region.

[0073] The inventors have found that by first determining the combinations with significant introgression signals in the poplar population, and then determining the introgression regions for these combinations, the analysis of wrong combinations can be effectively avoided, false positives can be reduced, the amount of calculation can be reduced, and the identification speed can be effectively improved. According to a preferred embodiment of the present invention, in the process of determining the introgression region, the window size in the sliding window analysis is set to 50 SNPs, which is conducive to accurately identifying the poplar introgression region, so that the introgression gene can be more precisely located.

[0074] According to a preferred embodiment of the present invention, in the process of obtaining the introgression area of ​​the poplar population, the maximum top 5% window of the detection results of each introgression combination is set as the introgression area of ​​the combination.

[0075] Preferably, the largest top 5% windows of the detection results of each introgression combination are the largest top 5% windows of fdM.

[0076] The present invention found that the target ancestral introgression occurred before the differentiation of the target species, and unique changes were likely to occur in the long historical evolutionary process after differentiation, resulting in the weakening of the introgression signal. Therefore, in the present invention, a looser threshold of 5% is selected in the process of using fdM to screen the introgression area, rather than the commonly used 1%-3%, that is, the weaker signal is also included, which is conducive to the subsequent further screening of the ancestral ancient introgression area.

[0077] Step 4, locate candidate ancestral introgression regions in poplar populations.

[0078] Preferably, step 4 includes the following sub-steps:

[0079] Step 4-1, obtain the topological structure among poplar subpopulations.

[0080] In the present invention, the poplar subpopulation is the poplar subpopulation obtained in step 2.

[0081] In the present invention, the subpopulation topological structure of poplar can be obtained by using commonly used software 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.

[0082] Step 4-2, grouping poplar subpopulations according to topological structure.

[0083] According to a preferred embodiment of the present invention, different combinations of five taxa of poplar subpopulations are obtained based on the topological structure;

[0084] 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;

[0085] Introgression analysis was performed on the five taxonomic groups composed above, that is, to determine whether the ancestors of the two populations P1 and P2 had introgressed with the P3 or P4 population.

[0086] In a further preferred embodiment, P1 and P2 are set to Populus alba populations, P3 and P4 are set to Populus cathayana and Populus nigra populations, and O is set to Populus euphratica, so as to identify the ancestral introgression regions common to multiple populations of Populus alba.

[0087] Step 4-3, obtain the ancestral introgression region for each combination.

[0088] In the present invention, step 4-3 preferably includes the following sub-steps:

[0089] Step 4-3-1, select the resequenced individual with the deepest sequencing depth in each poplar population in the combination.

[0090] The sequencing depth refers to the ratio of the total number of bases (bp) obtained by sequencing to the size of the genome (Genome), and is one of the indicators for evaluating the sequencing amount.

[0091] Step 4-3-2, split the chromosomes of the selected resequenced individuals into genomic segments.

[0092] In the present invention, chromosomes are preferably split into 100 kb genomic fragments.

[0093] Step 4-3-3, perform ancestral introgression detection on each genomic segment.

[0094] The inventors have found that the DFOIL method in the prior art can only calculate the ancestral introgression regions 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 the candidate ancestral introgression regions of the poplar combination of five taxa according to a method comprising the following steps:

[0095] Step i, obtain all possible ancestral introgression regions for each pair of P1 and P2.

[0096] 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 groups P1 and P2 are controlled to remain unchanged, represented as $P1 and $P2 respectively, and different combinations of P3 and P4 are changed to obtain multiple different introgression results of the first group $P1 and $P2.

[0097] 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.

[0098] 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 denoted as U1.

[0099] 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.

[0100] Here, n represents the number of combinations of P1 and P2, that is, a group of P1 and P2 is recorded as: n=1.

[0101] Preferably, all possible ancestral introgression regions of each pair of 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.

[0102] Step ii, confirm candidate ancestral introgression regions in multiple populations.

[0103] 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.

[0104] 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, ..., Un.

[0105] 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 populations of poplar.

[0106] For example, when n=6, when a region exists in greater than or equal to 4.8 combinations (i.e., 5 and 6 combinations), the region is considered to be a candidate ancestral introgression region of multiple populations.

[0107] The inventors have found that the accuracy rate can be significantly improved by obtaining the gene flow of the common ancestors of multiple subpopulations through the above method.

[0108] Step 5, obtain the ancestral paleointrogression area of ​​the poplar population.

[0109] 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.

[0110] 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.

[0111] The inventors have found that in order to exclude 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 genes can be located more precisely. It is also beneficial to better understand the mixing history between populations, identify the advantages of certain populations under specific environmental pressures, and explore certain functional stress-resistant genes that are beneficial to adapting to specific environments, laying the foundation for the later development of molecular technology-assisted breeding.

[0112] Step 6, obtain the ancestral ancient introgression genes of the poplar population.

[0113] 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.

[0114] 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 of 2000 bp before the gene) is taken as the gene annotation file of the ancestral ancient introgression segment, and the BEDTools intersect command is preferably used to annotate the ancestral ancient introgression genes of the poplar population.

[0115] The method for identifying ancient introgression genes of poplar ancestors described in the present invention first determines the introgression combination and preliminarily locates the introgression area of ​​poplar, and then accurately obtains the common ancestral introgression area of ​​multiple populations according to the topological result, and then combines the two results and verifies each other, which can further reduce false positives and more precisely locate the ancestral ancient introgression area, and then mine candidate ancestral ancient introgression genes with potential functions, which is conducive to mining more genes that play important functions on the basis of the evolutionary history of poplar lineage, thereby laying the foundation for molecular design breeding of poplar.

[0116] The second aspect of the present invention provides an application of the method for identifying ancient introgression genes of poplar ancestors described in the first aspect in poplar breeding.

[0117] Example

[0118] The present invention is further described below through specific examples, but these examples are merely exemplary and do not constitute any limitation to the scope of protection of the present invention.

[0119] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0120] Unless otherwise specified, the databases, bioinformatics software, etc. used in the following embodiments can be obtained from the corresponding official websites.

[0121] Example 1 Identification of ancestral ancient introgression genes of poplar

[0122] This embodiment follows Figure 1 The process shown is used for identification:

[0123] Step 1: Obtain resequencing data of 834 poplar individuals from the databases of the National Center for Biotechnology Information (NCBI) and the China National Center for Bioinformation (CNCB). The specific composition is shown in Table 1.

[0124] Table 1

[0125]

[0126]

[0127]

[0128]

[0129]

[0130]

[0131] 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). https: / / phytozome-next.jgi.doe.gov / info / Ptrichocarpa_ v4_1 ) to identify single nucleotide polymorphism sites at the whole genome level and obtain the genotype of the SNP sites.

[0132] Genome Analysis Toolkit (GATK) v4.0 was used to identify genome-wide single nucleotide polymorphism (SNP) sites 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 data set of the poplar population was obtained.

[0133] The above raw SNP dataset was quality controlled and filtered using Vcftools_0.1.16, with the following criteria: ① biallelic sites; ② Maximum Missing Rate < 0.2; ③ Minor Allele Frequency (MAF) > 0.05. A total of 3,434,667 SNP sites were obtained for the high-quality SNP dataset of the poplar population.

[0134] Step 2: Based on the SNPs data set 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.

[0135] The grouping results are: Populus euphratica, European Populus, Chinese Populus, Alpine Populus, Cottonwood Populus, American Black Populus, Small-leaved Populus, Fragrant Populus, and Trichocarpa Populus.

[0136] Step 3, according to the subgrouping results, with Populus euphratica as the outgroup, the Dtrios program in the Dsuite v0.5 software was used to calculate the D value between different triple groups of 8 subgroups (Populus tremula, Populus tremula, Populus alba, Populus scolopendra, Populus nigra, Populus simonii, Populus odoratus, Populus trichocarpa). If D is significant (Z-scores>=3), it means that there is gene exchange between the two groups in the triple group. The Dtrios results are shown in Table 2:

[0137] Table 2

[0138]

[0139]

[0140] It can be seen from Table 2 that the triple groups corresponding to Z-scores>=3 are the subpopulation combinations with significant gene exchange. For example, the first row in Table 2 has a Z-score of 41.8332, indicating that there is gene exchange between the Populus simonii, Populus trichocarpa and Populus deltoides subpopulations and the Populus trichocarpa subpopulations.

[0141] For the combinations with significant gene exchange, the Dinvestigate program was further used to locate the introgression region by a sliding window algorithm, with the window size set to 50 SNPs and the step length to 20 SNPs. The introgression region was defined as the window with the largest fdM in the top 5% of the Dinvestigate results.

[0142] Step 4: Based on the subpopulation results of step 2, the phylogenetic tree was generated using SNPhylo software with Populus euphratica as the outgroup to obtain the topological relationship between different populations of Populus. The results are as follows: Figure 2 shown.

[0143] In order to identify the ancestral gene introgression regions shared by multiple populations of white poplar, five taxonomic groups (((P1, P2), (P3, P4)), O) were further determined based on the topological results. P1 and P2 were defined as white poplar populations, P3 and P4 were defined as Populus cathayana and Populus nigra populations, and outgroup O was defined as Populus euphratica. Among them, white poplar populations include Populus siliquae, Populus alba, Populus tremula, and Populus tremula; Populus cathayana populations include Populus fragrantis, Populus simonii, and Populus trichocarpa; and Populus nigra populations include Populus nigra.

[0144] P1 and P2 were kept constant, and different combinations of P3 and P4 were changed. The resequenced individuals with the deepest sequencing depth in each poplar population were selected, converted into fasta format and split into 100 kb genomic segments. After alignment, the introgression results of each combination were calculated using the DFOIL method, as shown in Table 3. There were 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 was recorded as U1 (i.e., the union of the 6 results in the first horizontal column). Set), which represents the candidate ancestral introgression segment of the pair of P1 and P2 combinations. Among them, the five taxonomic groups of poplar 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, and the first introgression combination is: P1 is Populus scolopendra, P2 is Populus alba, P3 is Populus nigra, P4 is Populus odoratus, O is Populus euphratica, and the same goes for other combinations. Table 2 has a total of six horizontal columns, representing 6 pairs of P1 and P2 combinations.

[0145] Table 3

[0146]

[0147]

[0148] Change the population categories of P1 and P2, repeat the above steps, and obtain the ancestral introgression segments U2, U3, U4, U5 and U6 corresponding to different combinations of P1 and P2, respectively.

[0149] After the above steps, a total of 6 groups of ancestral introgression segments were obtained for the 36 combinations of five taxa of poplars, namely U1, U2, U3, U4, U5 and U6.

[0150] Take the intersection of each group of ancestral introgression segments (i.e., U1 to U6) and determine that when a region exists in all five pairs of poplar combinations (P1 and P2 combinations), the region is 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, i.e., the candidate ancestral introgression regions of multiple poplar populations.

[0151] Depend on Figure 3 It can be seen that the number of introgression areas that exist in all six pairs of poplar combinations is the largest, indicating that a considerable number of areas left by ancestral ancient introgression can still be detected in each combination; and the areas that exist in ≥80% or ≥5 combinations are also considered to be ancestral ancient introgression areas, because in the long-term historical evolution process, some areas may have undergone unique changes in individual species and cannot be identified, but are still detected as ancestral ancient introgression areas in other species, so these areas are also identified as ancestral ancient introgression areas.

[0152] Step 5: Take the intersection of the introgression segments of each significant triplet result obtained in step 3 and the candidate ancestral introgression region of poplar obtained in step 4 to obtain the final poplar ancestral ancient introgression segment, 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.

[0153] Figure 4 In the figure, the dark horizontal lines of different thicknesses on the chromosome are the locations of the ancestral ancient introgression genes. It can be seen that the ancestral ancient introgression genes show discontinuous distribution characteristics on the chromosome. This is because the ancestral introgression occurred earlier, and more recombination occurred over time, gradually forming a discontinuous distribution characteristic.

[0154] Experimental example

[0155] Experimental Example 1: Validation of the identified ancient introgression area of ​​Populus sibiricum

[0156] Genetic introgression will cause the introgressed regions in the two species to be more similar and have lower Fst values, 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.

[0157] In the results of step 4 of embodiment 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 window and 5 kb as step length), and the Fst values ​​of 1000 regions were randomly selected from the ancestral introgression regions and non-ancestral introgression regions (the introgression regions obtained in step 3 include the ancestral introgression regions and non-ancestral introgression regions, and the non-introgression regions are the results of the introgression regions obtained in step 3 minus the ancestral ancient introgression regions finally obtained in step 5), and significance comparison was performed. The calculation was repeated three times and the average value was taken. The results are as follows: Figures 5 to 7 shown.

[0158] Depend on Figures 5 to 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 result is 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.

[0159] Experimental Example 2 Comparison of introgression signals

[0160] The ancestral ancient introgression region result finally obtained in Example 1 and the non-ancestral introgression ancient introgression 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 ancient introgression region finally obtained in step 5) are taken as the first 100 maximum values, standardized and compared, and the results are as follows Figure 8 shown.

[0161] 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, unique changes are likely to have occurred in the long historical evolutionary 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.

[0162] The present invention has been described in detail above in conjunction with specific implementation methods and exemplary examples, but these descriptions cannot be understood 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 solution of the present invention and its implementation methods, all of which fall within the scope of the present invention.

Claims

1. A method for identifying ancient introgression genes from poplar ancestors, characterized in that: The method comprises the following steps: Step 1, obtaining 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 5, obtaining the ancestral paleo-introgression area of ​​the poplar population; Step 6, obtain the ancestral ancient introgression genes of the poplar population.

2. The method for identifying ancient introgression genes of poplar ancestors according to claim 1, characterized in that Step 1 includes the following sub-steps: Step 1-1, obtaining the original SNP data set of the poplar population; Step 1-2, optimize the original SNP dataset of the poplar population.

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

4. The method for identifying ancient introgression genes of 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 introgression genes of 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 subgroup combinations with significant gene exchange.

6. The method for identifying ancient introgression genes of poplar ancestors according to claim 3, characterized in that: 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 for each combination.

7. The method for identifying ancient introgression genes of poplar ancestors according to claim 6, characterized in that Step 4-3 includes the following sub-steps: Step 4-3-1, select the resequencing individual with the deepest sequencing depth in each poplar population in the combination; Step 4-3-2, splitting the chromosomes of the selected resequenced individuals into genomic segments; Step 4-3-3, perform ancestral introgression detection on each genomic segment.

8. The method for identifying ancient introgression genes of 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.

9. Use of the method for identifying ancient introgression genes of poplar ancestors as claimed in any one of claims 1 to 8 in poplar breeding.

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