Universal parentage identification snp marker combination for grass carp
By developing a universal parentage identification set for grass carp containing 34 SNP loci, and combining multiplex PCR and third-generation Nanopore sequencing technologies, the problem of obtaining pedigree information in grass carp breeding was solved, achieving efficient and accurate breeding assistance and reducing costs.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- INST OF AQUATIC LIFE ACAD SINICA
- Filing Date
- 2026-06-17
- Publication Date
- 2026-07-21
AI Technical Summary
In the process of grass carp breeding, existing technologies are unable to accurately obtain pedigree information, resulting in low breeding efficiency, and the existing SNP marker sets are not very universal.
A universal parentage identification set for grass carp containing 34 SNP loci was developed. The set was validated using multiplex PCR and third-generation Nanopore sequencing technologies, combined with virtual and real populations, to ensure its high universality and accuracy.
It enables accurate acquisition of pedigree information during grass carp breeding, improves breeding efficiency, reduces usage costs, and achieves 100% accuracy in the identification set.
Smart Images
Figure CN122428045A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of molecular marker technology for aquatic animals, specifically involving a universal marker set for grass carp parentage identification consisting of 34 SNP loci. Background Technology
[0002] grass carp( Ctenopharyngodon idella Grass carp (Cypriniformes), belonging to the family Cyprinidae, genus Cypriniformes. Ctenopharyngodon Grass carp, with a diploid genome, is one of China's four traditional freshwater aquaculture fish. Its simple diet, wide availability of feed, and tender flesh make it an excellent aquaculture fish with high economic value. Its aquaculture scale is expanding, and it is widely distributed throughout my country. Its germplasm is diverse and complex, and samples are readily available, making it a good experimental material. Obtaining reliable and accurate pedigree information is crucial and essential in grass carp breeding. However, because reproduction occurs in the eggs, making tagging impossible, and because fertilization is in vitro, obtaining accurate pedigree information is relatively difficult.
[0003] With the rapid development of biotechnology, paternity testing technology has been widely applied in fish breeding to assist in related breeding work. In this process, microsatellites (SSRs) are commonly used as genetic markers in aquatic animals, while single nucleotide polymorphisms (SNPs) are more commonly used in humans. With the continuous development of high-throughput sequencing technology, SNPs have received increasing attention and are gradually being applied to aquatic animals. The biggest drawback of SSRs is that genotyping requires gel electrophoresis of PCR products, and because base slippage occurs during DNA replication, effective genotyping is not possible, resulting in a high error rate. Compared to SSRs, SNPs exhibit advantages such as a lower genotyping error rate and wider applicability. Considering the current state of grass carp breeding, SNPs are a more suitable molecular marker for constructing a grass carp paternity testing marker set.
[0004] Research on the application of SNPs in grass carp parentage identification is still incomplete, and existing identification sets are not very universal. Therefore, we have developed a universal SNP parentage identification set for grass carp, which can be widely used in grass carp populations to improve breeding efficiency and promote the development of grass carp breeding. Summary of the Invention
[0005] To address the difficulty in obtaining pedigree information during grass carp breeding and improve breeding efficiency, this invention provides a universal SNP combination for parentage identification in grass carp, which contains 34 SNP loci.
[0006] The grass carp universal paternity testing SNP combination includes 34 SNP loci, the information of which is shown in Table 1. The CPE (cumulative exclusion probability) of the loci is greater than 0.9999, which meets the industry standard for paternity testing and has high universality and accuracy.
[0007] Preferably, 28 of these loci are used as the core marker combination for grass carp parentage identification. These 28 loci can be divided into 5 groups (group information is shown in Groups 1 to 5 in Table 2) for multiplex PCR and sequencing. The CPE (cumulative exclusion probability) of the loci is greater than 0.9999.
[0008] Compared with the prior art, the present invention has the following advantages and beneficial effects: 1. The SNP loci in this invention come from grass carp populations in multiple water areas, which are universal. The parentage test set constructed using these loci has a certain degree of universality, and it has been verified that the test set has high universality.
[0009] 2. The molecular marker used in this invention is SNP, which is combined with parentage testing technology and applied to grass carp breeding. This not only makes full use of the advantages of both, but also promotes their application in the field of aquatic animal breeding.
[0010] 3. The grass carp universal SNP parentage test set provided by this invention has been verified by both "virtual population" and "real population". This test set is not only highly universal but also highly accurate, with an accuracy rate of up to 100%, and has good application value.
[0011] 4. When using the identification set provided by this invention, "multiplex PCR" can be combined with "third-generation Nanopore sequencing technology" for complementary use, which can further reduce the cost of use. Attached Figure Description
[0012] Figure 1 Example 1: Germplasm source diagram of grass carp in Example 1.
[0013] Figure 2 Example 1: Flowchart of the specific operation for SNP site polymorphism verification. Detailed Implementation
[0014] The technical solution of the present invention will be described in detail below with reference to embodiments. The embodiments below are only for illustrating the present invention and should not be regarded as limiting the present invention. Specific techniques or conditions not specified in the embodiments are all operated in accordance with the literature in the field or conventional technical means in the field.
[0015] Example 1: Screening a general SNP set for parentage testing in grass carp 1. Quality control of SNP sites: First, [the following steps are taken]... Figure 1Whole-genome sequencing was performed on 267 grass carp samples from known sources collected from the five major water bodies shown. The Plink tool was then used to calculate and quality control the parameters of the SNP sites included in the sequencing results. The parameters and their standards were: minimum allele frequency (MAF) > 0.35, linkage disequilibrium (LD) r 2 With a value ≤ 0.5, 952,375 SNP sites were selected from 14,903,179 sites after quality control.
[0016] 2. Screening for SNP sites (1) Calculate PE: Use the parameter "excluding probability of paternity (PE)" to screen SNP loci used to form the paternity test set. The calculation formula is as follows:
[0017]
[0018] Among them, "p" j "S" represents the allele frequency of the j-th allele at that locus; t "" represents the sum of the allele frequencies of all alleles at that locus raised to the power of t.
[0019] (2) After obtaining the PE values, the loci are sorted from largest to smallest, with high PE values being the preferred choice. Four loci from each chromosome are selected to form a "temporary identification set subset" of 96 SNPs as the screening unit. The linkage disequilibrium r between each locus is calculated. 2 The value, r 2 Sites with a value >0.5 were removed. The remaining sites were then validated experimentally and using high-throughput sequencing technology to systematically identify and confirm their single nucleotide polymorphism (SNP) properties. The specific procedure is as follows: Figure 2 The filtered set is called the "identification set subset".
[0020] (3) Calculate CPE: "CPE" is the cumulative exclusion probability, used to evaluate the cumulative exclusion power of multiple markers. When CPE > 0.9999, it can be used for paternity testing. The calculation formula is as follows:
[0021] “i” represents the number of sites, and “PE” represents the exclusion probability mentioned above. Calculate the CPE value of the subset of the identification set. If the CPE does not reach 0.9999, step (2) needs to be repeated to integrate all the filtered subsets and calculate the CPE again until the CPE > 0.9999.
[0022] Finally, 34 loci were selected, with a CPE of 0.999986706, which is greater than 0.9999. At this point, the grass carp universal paternity identification SNP set of this invention is complete. The information for each locus is shown in Table 1. The physical location of the loci was determined based on the grass carp GC_3rd.3 reference genome (http: / / bioinfo.ihb.ac.cn / download / genomes / Grass_carp_Ctenopharyngodon_idella / GC_3rd.3 / ).
[0023] Table 1 Summary of SNP data points in paternity testing
[0024] Example 2: Application of the universal SNP set for parentage testing of grass carp 1. Virtual group verification First, a large parental population (with known sex) was formed, consisting of two parts: the source sample population (267 samples) of the SNP loci in Example 1, and other sample populations (94 samples). Ten females and ten males were randomly selected from this population (there are three selection methods: all from the source sample population; all from other sample populations; and from both sample populations) to form virtual parental pairs (families). Then, PMSeeker (http: / / bioinfo.ihb.ac.cn / pmseeker) was used to distinguish these 10 virtual families based on a paternity testing set composed of 34 loci. The specific method is as follows: First, prepare the genotype information file for all tested samples at the 34 loci shown in Table 1, and use it as input file 1; randomly select the parental pair information file, including sample name and corresponding sex, and use it as input file 2; run the PMSeeker script to obtain the output result file, which contains the distinction information. This process was repeated 1000 times, and the number of successful distinctions was counted. The statistical results for the three random sampling methods are as follows: ① All 10 pairs were drawn from the source sample group, and the results were successfully distinguished 1000 times, with a success rate of 100%; ② All 10 pairs were drawn from other sample groups, and the results were successfully distinguished 1000 times, with a success rate of 100%; ③ Five pairs were drawn from each of the two sample groups, and the results were successfully distinguished 1000 times, with a success rate of 100%. This demonstrates the high versatility of this paternity testing dataset.
[0025] 2. Real-world group validation A parentage test dataset consisting of 34 loci was used in Cervus 3.0 to perform parentage analysis on a 2016 grass carp population (239 offspring, 5 parents) with known parent-offspring relationships. When using Cervus 3.0, input files were prepared according to the tool's requirements, including genotype files, candidate paternal information files, and candidate maternal information files. Then, the steps of allele frequency calculation (Allele frequency analysis), simulation of parentage analysis, and parentage analysis were performed sequentially. The final summary file contained the parentage results, i.e., the parent-offspring relationships. The parentage test results showed that all 239 offspring were successfully assigned to a parent. Comparison of the obtained parentage relationships with existing parentage relationships showed that all matched, with a 100% accuracy rate. This indicates that this parentage test dataset has 100% accuracy.
[0026] The above verification shows that the parentage test set provided by this invention is usable and has high versatility and accuracy, and can be applied to related work on grass carp breeding.
[0027] Example 3: Application of multiplex PCR and third-generation Nanopore sequencing technology in grass carp parentage testing To further reduce the cost of using this identification set, we first grouped these 34 loci as much as possible, then performed multiplex PCR on each group, and finally sequenced them using third-generation Nanopore sequencing technology. This effectively reduces the cost of genotyping by reducing the number of experiments and sequencing runs.
[0028] First, multiplex PCR was performed to group the loci. The grouping criteria were: after amplification and sequencing in the same PCR system, all loci and their genotyping results in that component could be obtained. The grouping of the 34 loci is shown in Table 2. 28 loci were successfully divided into 5 groups, while the remaining 6 loci could not be included (due to primer incompatibility, which would disrupt the amplification of other loci within the group) and had to be grouped separately, resulting in a total of 11 groups. When using the identification set of this invention, a maximum of 11 PCR experiments and 11 sequencing samples are required to obtain the genotyping results for these 34 loci. The first 5 groups, totaling 28 loci, are now considered the "core set," and the remaining 6 are considered "alternate" loci.
[0029] The CPE of the "core set" is 0.999903577, which is greater than 0.9999, meeting the industry standard for paternity testing. The "core set" was validated as follows: The results of the "virtual population validation" (PMSeeker) were: ① All 10 pairs were drawn from the sample population described in Example 1, successfully distinguishing 1000 times with a success rate of 98.8%; ② All 10 pairs were drawn from other sample populations, successfully distinguishing 1000 times with a success rate of 100%; ③ Five pairs were drawn from each of the two sample populations, successfully distinguishing 1000 times with a success rate of 100%, resulting in a virtual validation success rate of 99.6% (average). The results of the "real population validation" (2016 grass carp population, including 239 offspring and 5 parents; the tool used was Cervus 3.0) were: all offspring were assigned to parents and the parentage completely matched the existing parentage correspondence, with an accuracy rate of 100%. Therefore, the "core set" can be used for paternity testing with an accuracy rate of 100%. Although it is slightly less universal than using the entire "test set", the difference is minimal. Therefore, in practical applications, it is advisable to prioritize the use of the "core set" and use the other 6 loci as supplements.
[0030] Table 2 Summary of Grouping of Each Point
[0031] In summary, this invention provides a set of SNP markers that can be widely used for grass carp parentage identification. Its versatility and accuracy are very high, both reaching the theoretical upper limit, and it can serve as an auxiliary tool for grass carp breeding. In practical use, combining "multiplex PCR" with "third-generation Nanopore technology" can further reduce the cost of use.
Claims
1. The application of a reagent for detecting SNP marker combinations in grass carp parentage testing, characterized in that, The core marker combination for paternity testing consists of 28 SNP loci, and the information of these SNP loci is as follows: SNP locus 1 is located at position 10202716 on chromosome 12; SNP locus 2 is located at position 1086148 on chromosome 12; SNP locus 3 is located at position 11400057 on chromosome 12; SNP locus 4 is located at position 10,129,483 on chromosome 14; SNP locus 5 is located at position 10175340 on chromosome 1; SNP locus 6 is located at position 10,165,488 on chromosome 15; SNP locus 7 is located at position 1094690 on chromosome 16; SNP locus 8 is located at position 10582535 on chromosome 17; SNP locus 9 is located at position 10590531 on chromosome 17; SNP locus 11 is located at position 1128232 on chromosome 18; SNP locus 12 is located at position 12159472 on chromosome 18; SNP locus 13 is located at position 10091774 on chromosome 19; SNP locus 14 is located at position 1040745 on chromosome 20; SNP locus 15 is located at position 10559721 on chromosome 21; SNP locus 16 is located at position 10231319 on chromosome 22; SNP locus 17 is located at position 10523850 on chromosome 2; SNP locus 18 is located at position 10557420 on chromosome 2; SNP locus 19 is located at position 10492642 on chromosome 3; SNP locus 21 is located at position 10428645 on chromosome 6; SNP locus 22 is located at position 10520006 on chromosome 7; SNP locus 24 is located at position 10386309 on chromosome 9; SNP locus 25 is located at position 10403632 on chromosome 9; SNP locus 28 is located at position 12378409 on chromosome 6; SNP locus 29 is located at position 259247 on contig h2tg0000321; SNP site 30 is located at position 64605 on contig h2tg000005l; SNP locus 31 is located at position 217260 on chromosome 8; SNP locus 33 is located at position 459635 on chromosome 21; SNP locus 34 is located at position 32714655 on chromosome 11; The physical location of the locus is determined based on the grass carp GC_3rd.3 reference genome. The genotype of the tested sample at the locus is obtained, and the paternity test results are obtained by analyzing the data using PMSeeker or Cervus3.0 software.
2. The application according to claim 1, characterized in that, It also includes 6 SNP sites, the information of which is as follows: SNP locus 10 is located at position 1023549 on chromosome 18; SNP locus 20 is located at position 10089953 on chromosome 5; SNP locus 23 is located at position 10742325 on chromosome 7; SNP locus 26 is located at position 300646 on chromosome 9; SNP locus 27 is located at position 13923200 on chromosome 9; SNP locus 32 is located at position 118740 on chromosome 17; The physical location of the site was determined based on the grass carp GC_3rd.3 reference genome.
3. The application according to claim 1, characterized in that, The 28 SNP sites were divided into 5 groups for multiplex PCR and sequencing, as follows: The first group includes SNP sites 1, 6, 11, 12, and 13. The primer sequences for detecting SNP site 1 are shown in SEQ ID NO. 1 and 2, the primer sequences for detecting SNP site 6 are shown in SEQ ID NO. 11 and 12, the primer sequences for detecting SNP site 11 are shown in SEQ ID NO. 21 and 22, the primer sequences for detecting SNP site 12 are shown in SEQ ID NO. 23 and 24, and the primer sequences for detecting SNP site 13 are shown in SEQ ID NO. 25 and 26. The second group includes SNP loci 3, 7, 8, 14, 17, 19, 22, 29, and 33. The primer sequences for detecting SNP loci 3 are shown in SEQ ID NO. 5 and 6; for SNP loci 7, SEQ ID NO. 13 and 14; for SNP loci 8, SEQ ID NO. 15 and 16; for SNP loci 14, SEQ ID NO. 27 and 28; for SNP loci 17, SEQ ID NO. 33 and 34; for SNP loci 19, SEQ ID NO. 37 and 38; for SNP loci 22, SEQ ID NO. 43 and 44; and for SNP loci 29, SEQ ID NO. 33 and 34. As shown in NO.57 and 58, the detection primer sequences for SNP site 33 are shown in SEQ ID NO.65 and 66; The third group includes SNP sites 2, 4, 21, 25, 28, and 30. The primer sequences for detecting SNP site 2 are shown in SEQ ID NO. 3 and 4, the primer sequences for detecting SNP site 4 are shown in SEQ ID NO. 7 and 8, the primer sequences for detecting SNP site 21 are shown in SEQ ID NO. 41 and 42, the primer sequences for detecting SNP site 25 are shown in SEQ ID NO. 49 and 50, the primer sequences for detecting SNP site 28 are shown in SEQ ID NO. 55 and 56, and the primer sequences for detecting SNP site 30 are shown in SEQ ID NO. 59 and 60. The fourth group includes SNP sites 5, 15, 16, 18, 24, and 31. The primer sequences for detecting SNP site 5 are shown in SEQ ID NO. 9 and 10, the primer sequences for detecting SNP site 15 are shown in SEQ ID NO. 29 and 30, the primer sequences for detecting SNP site 16 are shown in SEQ ID NO. 31 and 32, the primer sequences for detecting SNP site 18 are shown in SEQ ID NO. 35 and 36, the primer sequences for detecting SNP site 24 are shown in SEQ ID NO. 47 and 48, and the primer sequences for detecting SNP site 31 are shown in SEQ ID NO. 61 and 62. The fifth group includes SNP site 9 and SNP site 34. The detection primer sequences for SNP site 9 are shown in SEQ ID NO.17 and 18, and the detection primer sequences for SNP site 34 are shown in SEQ ID NO.67 and 68.