Duck paternity test kit and application thereof

Abstract

The invention discloses a duck paternity test kit and an application thereof. The duck paternity test kit comprises amplification primers of gene loci of SICAU07-P, SICAU06-P, SICAU11-P and SICAU08-P. The marker for duck paternity test is selected from common STR loci, the loci have high genetic diversity and obvious genotype difference, high amplification efficiency and stability are shown in the PCR amplification process, the fluorescence labeling effect is good, and the accuracy of genotyping can be improved. Through fluorescence labeling, a plurality of STR sites can be simultaneously detected in the same reaction system, and the analysis flux is improved. In paternity test, Cervus software is used for analyzing the parent-child relationship between parents and offspring, the result shows that the sites can effectively distinguish the relationship between the parents and the offspring, the parent matching probability is obviously higher than that of non-parent pairing, and the high application value of the loci in paternity test is shown.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, and particularly to a duck paternity testing kit and its application. Background Art

[0002] Ducks are one of the important poultry in China, with a long breeding history and are widely distributed throughout the country. There are many varieties, mainly including Beijing ducks, Shaoxing ducks, Gaoyou ducks, etc. Among them, Beijing ducks are famous for their delicious meat and are the main raw materials for making Beijing roast duck. Ducks have strong adaptability and can survive in a variety of environments. Especially in the southern areas with dense water networks, duck farming is more common. Ducks have a wide range of uses. They not only provide food such as meat and eggs, but also duck down can be used to make warm products such as down jackets. Duck meat is rich in protein, vitamins and minerals, with a moderate fat content and high nutritional value, and is deeply loved by consumers. Duck eggs are usually used to make traditional foods such as salted duck eggs and preserved eggs. In terms of breeding, ducks have the characteristics of fast growth and strong reproductive ability. Usually, a combination of free-range and captive breeding methods is adopted, which can not only make full use of natural resources, but also improve breeding efficiency. The feed sources of ducks are extensive, including grains, aquatic plants, insects, etc., and the breeding cost is relatively low. In addition, ducks also play an important role in the ecosystem, being able to help control pests and waterweeds and maintain ecological balance. In recent years, with the progress of breeding technology, large-scale and intensive breeding models have gradually become popular, and the yield and quality of ducks have been significantly improved. Generally speaking, ducks occupy an important position in China's agricultural economy and culture, being both important economic animals and an important part of traditional food culture.

[0003] In duck breeding and germplasm conservation, accurate pedigree information is the basis for breeding excellent varieties. However, currently, the construction of pedigrees still mainly relies on the records of farm employees, so errors in pedigree records caused by humans occur from time to time. The pedigree of poultry records key data such as the family bloodline, genetic information, and growth traits of each individual in the duck flock, providing strong support for duck breeding and germplasm conservation work. Through the pedigree, the family bloodline of the duck flock can be clearly traced. Understanding the ancestors and kinship of each duck helps researchers better grasp the transmission law of genetic genes, so paternity testing technology is crucial in pedigree construction.

[0004] Through paternity testing molecular markers, the parental relationship of poultry individuals can be confirmed, pedigree errors can be avoided, and the accuracy of breeding data can be ensured. The paternity testing technology constructs a molecular pedigree to estimate breeding values to accelerate the breeding improvement of ducks, for breeding excellent varieties with high yield, disease resistance, and strong adaptability; at the same time, in the conservation farms, it helps to formulate effective conservation programs and conduct scientific selection and mating. Fan Xiuqing screened and identified 12 microsatellite molecular markers applicable to chicken paternity testing, with an exclusion probability of 0.9999; similarly, Zhao Mengmeng et al. also identified and screened 15 microsatellite molecular markers for Muscovy duck paternity testing. Fan Wenlei et al. screened and identified 11 molecular markers for duck paternity testing based on the resequencing data of Pekin ducks in 2018, providing escort for the pedigree information in the future breeding and conservation work of Pekin ducks. Paternity testing can ensure the accuracy of the pedigree, thus providing clear and detailed family bloodline information for breeders, helping them avoid mating closely related individuals, maintaining the health of the population, ensuring the stability of genetic diversity, and providing a reference for variety improvement and conservation strategies.

[0005] However, the existing microsatellite molecular markers are mainly identified for a single breed. When screening molecular markers applicable to STR paternity testing, there are strict requirements for characteristics such as high polymorphism, wide applicability, and strong amplification ability. This requires careful thinking and a scientific attitude in every step of experimental design and implementation, otherwise all previous efforts may be wasted. Summary of the Invention

[0006] Aiming at the deficiencies of the existing technology, the present invention provides a duck paternity testing kit and its application. In order to achieve the invention purpose of the present invention, the following technical solutions are proposed: The first aspect of the present invention provides a duck paternity testing kit, which includes the following amplification primers: .

[0007] In a preferred embodiment of the present invention, the kit further includes at least 1 pair, 2 pairs, 3 pairs, 4 pairs or 5 pairs of the following amplification primers: .

[0008] In a preferred embodiment of the present invention, the kit does not include other amplification primers.

[0009] In a preferred embodiment of the present invention, the kit further includes a DNA extraction reagent.

[0010] In a preferred embodiment of the present invention, the kit further includes a DNA amplification reagent.

[0011] Another aspect of the present invention relates to the application of the above kit in duck paternity testing.

[0012] In a preferred embodiment of the present invention, when the information of the other parent is known, only the amplification primers described in claim 1 are used to detect whether the offspring to be tested and the parent to be tested are parent-child relationship.

[0013] The present invention selects 9 loci from the shared STR loci for the development of paternity test markers for multiple breeds of ducks. These loci have high genetic diversity and obvious genotype differences, and show high amplification efficiency and stability during PCR amplification, with good fluorescence labeling effect, which helps to improve the accuracy of genotyping. Through fluorescence labeling, multiple STR loci can be detected simultaneously in the same reaction system, improving the analysis throughput. In paternity testing, the Cervus software is used to analyze the parent-child relationship between parents and offspring. The results show that these loci can effectively distinguish the relationship between parents and offspring, and the parental matching probability is significantly higher than that of non-parental pairs, showing its high application value in paternity testing. In addition, according to actual needs (the situation of conservation farms and breeding farms), appropriate STR combinations can be selected for paternity testing to save costs and time. Brief Description of the Drawings

[0014] Figure 1: Genotyping results of nine microsatellite loci in this individual, including Figure 1a and Figure 1b , which are SICAU01, SICAU02, SICAU03, SICAU05, SICAU06, SICAU07, SICAU08, SICAU10, SICAU11 in sequence.

[0015] Figure 2 : Statistical chart of alleles and allele frequencies. Detailed Embodiments

[0016] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following takes preferred embodiments to illustrate in detail the specific embodiments, technical solutions, features and their effects of the application according to the present invention. The specific features, structures, or characteristics in the following descriptions of multiple embodiments can be combined in any suitable form.

[0017] Example 1: 1.1 Experimental animals The experimental animals used for resequencing to screen STRs in this study included mallards, Tianfu Nonghua Ma ducks, Tianfu Nonghua White ducks, Jinling White ducks, Huaifu meat ducks, Pekin ducks, Jianchang ducks, Cherry Valley ducks, Qiangying ducks, Jinding ducks, Shaoxing ducks, Fujian mountain mallards, Yunnan mallards, Sansui ducks, Jinding ducks, Shaoxing ducks, Fujian mountain mallards, Yunnan mallards, and Sansui ducks. Among them, 255 ducklings were provided by the Waterfowl Breeding Farm of Sichuan Agricultural University (30 Nonghua Ma ducks and 24 Jianchang ducks were provided, among which 30 Nonghua Ma ducks were full-sib families of strain B, with 12 male parents, 41 female parents, and 42 offspring), Henan Xurui Food Co., Ltd. (29 Huaifu meat ducks, 29 Qiangying ducks, 29 Cherry Valley ducks, and 24 BH White ducks were provided), Nanjing Poultry Research Institute (30 Jinling White ducks were provided), Sansui County, Qiandongnan Prefecture, Guizhou Province (30 Sansui ducks), and Fumin County, Kunming City, Yunnan Province (30 Yunnan mallards). Additionally, 79 previously published data were downloaded from the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI) in the United States (23 mallards, 26 Pekin ducks, 10 Fujian mountain mallards, 10 Jinding ducks, and 10 Shaoxing ducks). We used the SRA toolkit (fastq-dump –split-3) to convert the 79 SRA files into fastq format. All samples were sequenced on an Illumina Hi-seq (2500 or X Ten) machine with 125PE or 150PE reads, with an average coverage of 12-fold (range 10 - 16-fold), and each duck population had an equal number of males and females.

[0018] The experimental animal samples for molecular marker-assisted parentage testing were selected from the third and fourth generation populations of the B line of Tianfu Nonghua Ma ducks (high-quality meat duck matching line), totaling 96 individuals, all from the core breeding population strictly managed by the Waterfowl Breeding Farm of Sichuan Agricultural University. The sample population consisted of 12 male parents, 42 female parents, and their corresponding 42 offspring individuals. All experimental subjects had complete pedigree records and standardized individual identification information. This sample population presented a typical three-level genetic structure (parent - parent - offspring) in terms of generation transmission and genetic relationship, providing an ideal genetic analysis model for verifying the parentage testing efficiency of molecular markers.

[0019] 1.2 Experimental methods 1.2.1 Blood sample collection and genomic DNA extraction A total of 351 duck blood samples were collected in this experiment (255 of which were used for sequencing and the other 96 were used for PCR amplification). A 2 mL disposable syringe was used to collect blood from the sub-wing vein of the ducks, and 1 mL of blood was drawn and injected into a pre-prepared autoclaved 1.5 mL centrifuge tube (the centrifuge tube contained EDTA anticoagulant and was numbered on the tube cap). The lid was covered and the mixture was inverted up and down to mix evenly. The cage number or wing number of the numbered ducks was recorded. The collected samples were stored in a -20 °C refrigerator for later use. DNA samples were all extracted from duck whole blood using the standard phenol-chloroform extraction method, and the extracted genomic DNA was stored in a -20 °C refrigerator for later use.

[0020] 1.2.2 Genotype detection Two hundred and fifty-five meat ducks of 14 breeds were selected, and a paired-end library was generated for each qualified sample using standard procedures. The average insert length was 500 bp, and the average read length was 150 bp. All libraries were sequenced on the Illumina® HiSeq X-Ten platform of Personal Biotechnology Co., Ltd., and the average raw reads sequence coverage of each sample was 10×. After the original sequencing image data was converted by base calling on the Illumina BaseSpace platform to generate raw reads, they were stored in FASTQ format. In this study, Trimmomatic was used to filter low-quality reads and other data from the raw data, and clean reads that met the requirements for subsequent analysis were obtained after filtering.

[0021] 1.2.3 Identification and screening of duck genome STRs The duck reference genome used in this study was ZJU.1.0 (GCF_01547-6345.1), which could be obtained from www.duckbase.org / Download. Tandem Repeats Finder (TRF) was run on the duck chromosomes with a match weight of 2, mismatch and indel penalties of 7, a match probability of 80%, and an insertion probability of 10%. The output was filtered to include only repeats with motif lengths between 2 and 6 base pairs. We deleted STRs located in regions that might impede unique mapping, such as large repeats or transposable elements. RepeatMasker was used to identify transposons and other repetitive elements, and the TRF results within or within 20 bases of these regions were deleted. STRs with alignment scores below the threshold recommended by Willems et al. that were located next to or within 20 bases of another STR were further deleted. Finally, a duck whole-genome STR reference containing 617,439 loci was successfully assembled.

[0022] A comprehensive investigation of STR variations was conducted using 334 high-coverage NGS data from 14 duck flocks. LobSTR was used for alignment and STR discovery with default parameters as described previously. Briefly, a lobSTR reference index was created based on the STR reference using the lobstr_index.py script first. Then lobSTR alignment was performed to create an STR alignment bam file, and the final STR variant genotypes were identified in all samples based on the merged alignment files. LobSTR adopted an explicit model to avoid stutter noise caused by PCR amplification of STR loci, thus improving accuracy. Then genotype STR loci were filtered using the following attributes: Average coverage < 3×, Average–log10(1–Q) < 0.8, Call rate <0.8, Reference allele length > 80 bp. After filtering loci, individual calls were also filtered using the following: Coverage < 3×, –log10(1–Q)< 0.8, Absolute value of DISTENDS score > 20. After filtering, 148,489 loci remained for further analysis. The results were mainly reported in the VCF file generated by lobSTR based on coverage, call rate (the percentage of samples with genotype calls for a given locus), and the metrics Q and DISTENDS.

[0023] 1.2.4 Analysis of STR characteristics in the whole genome of ducks Principal component analysis (PCA) was performed on the STR call set using PLINK software. The Tracy-Widom test was used to determine the significance level of the eigenvectors. The top 10% of autosomal STR loci with the highest heterozygosity that were called in at least 80% of the samples were used. To encode STRs in a biallelic format, each STR allele with a frequency range of 5 - 95% was encoded as a separate biallelic marker. This generated 111,606 STR "markers" from 11,748 unique STR loci.

[0024] The top 10% (11,748 loci) of autosomal STR loci with the highest heterozygosity obtained from the above research were used for heterozygosity analysis. To determine whether there were systematically different heterozygosities at these loci, paired comparisons were made for each STR locus, and the P-value was calculated using the cdf function in the scipy.stats.binom python package. The observed heterozygosity (Ho) and expected heterozygosity (He) of the genomes of different mountain duck populations were calculated as indicators to explore the genetic diversity among different duck populations.

[0025] 1.2.5 Development of molecular markers for STR paternity testing Among the 87,758 highly polymorphic STR loci (number of alleles > 3) in 1.2.4, 3,163 STR loci with a call rate above 100% were selected. Using vcftools, the number of alleles, heterozygosity, etc. of each breed were calculated respectively. A total of 18 STR loci with more than 3 alleles and a heterozygosity greater than 0.5 in each breed were selected. Eleven STR loci were selected according to the number of alleles from largest to smallest to develop paternity testing markers applicable to all duck breeds.

[0026] These loci are: SICAU01, SICAU02, SICAU03, SICAU04, SICAU05, SICAU06, SICAU07, SICAU08, SICAU09, SICAU10, SICAU11. The corresponding chromosomes and primer sequences of each locus were found in the Probe of NCBI, and the primer sequences shown were compared with the primers shown in FAO-ISAG. Appropriate primer sequences were selected and primers were synthesized as shown in Table 1 below.

[0027] Table 1. Specific information of primer pairs for identifying or assisting in identifying duck parent-offspring relationships

[0028] In this experiment, the selected microsatellite loci were grouped into 3 groups, with 4 loci in each group. It was required that the loci in each group be labeled with different fluorescent marker groups (Table 1). The PCR products of several loci in each group were mixed from 4 plates into 1 plate according to the grouping (PCR was carried out using a 96-well plate), and then capillary electrophoresis typing was performed on the mixed products. Typing with the mixed products can reduce the experimental cost.

[0029] 1.2.6 Establishment of a paternity testing system Based on the analyzed data, the optimal loci and the number of optimal loci required for duck paternity testing can be determined. Then, these loci are grouped again to confirm the fluorescent labels of each locus, and an efficient and low-cost identification scheme is customized.

[0030] 2 Results and Analysis 2.1 STRs Genotyping Detection Figure 1 shows the genotyping results of nine microsatellite loci in this individual, namely SICAU01, SICAU02, SICAU03, SICAU05, SICAU06, SICAU07, SICAU08, SICAU10, and SICAU11. As can be seen from the figure, there are 1 to multiple peaks in each STR peak map. The higher peak is the main peak, and there are some very low peaks near the main peak. These peaks are called stutter peaks. These peaks are formed by the polymerase slippage of taq enzyme. The presence of stutter peaks generally has no effect on the genotyping results. However, if the height of the stutter peak at a certain locus is close to the main peak, it is very difficult to judge the genotyping results of that locus. Generally, loci with higher stutter peaks are not recommended for use. The genotyping results are as follows: SICAU01: The fluorescent label is FAM (blue), heterozygous, and the molecular weight sizes are 211 and 215 respectively; SICAU02: The fluorescent label is HEX (green), heterozygous, and the molecular weight sizes are 303 and 316 respectively; SICAU03: The fluorescent label is TAMRA (yellow), homozygous, and the molecular weight size is 327; SICAU05: The fluorescent label is FAM (blue), heterozygous, and the molecular weight sizes are 241 and 264 respectively; SICAU06, the fluorescent label is HEX (green), heterozygous, and the molecular weight sizes are 179 and 183; SICAU07, the fluorescent label is TAMRA (yellow), heterozygous, and the molecular weight sizes are 179 and 183 respectively; SICAU08, the fluorescent label is Rox (red), heterozygous, and the molecular weight sizes are 219 and 225 respectively.

[0031] SICAU10: The fluorescent label is FAM (blue), heterozygous, and the molecular weight sizes are 194 and 197 respectively; SICAU11: The fluorescent label is TAMRA (yellow), heterozygous, and the molecular weight sizes are 194 and 197 respectively; The genotyping results showed that the peak maps of SICAU04 and SICAU09 were not good, so these 2 loci were not included in the subsequent analysis. The genotype data of each locus were counted, and the allele numbers and allele frequencies of 9 STR loci were analyzed using CERVUS 3.0 software. There were multiple alleles at all 9 STR loci, that is, they were all polymorphic loci. The alleles and allele frequencies of each STR locus are as Figure 2 .

[0032] Cervus 3.07 software was used to count the genetic polymorphism parameters of 9 microsatellite markers, including allele number, observed heterozygosity, expected heterozygosity, and polymorphic information content. The statistical results are shown in Table 2. The allele numbers of the 9 microsatellite markers were between 5 and 15, all showing high polymorphism; the observed heterozygosity of each marker was between 0.742 and 0.88, and the expected heterozygosity was between 0.717 and 0.968. Moreover, the difference between the observed heterozygosity and the expected heterozygosity of each microsatellite marker was small, between 0.021 and 0.133, indicating that the allele distribution of each microsatellite marker was reasonable and could accurately reflect the genetic structure of the population. The polymorphic information content (PIC) of each marker was between 0.688 and 0.862, and the PIC values of all loci were greater than 0.5, all showing high polymorphism. This shows that these 9 microsatellite markers have high application value in identifying duck parentage.

[0033] Table 2 Heterozygosity and polymorphic information content of 9 STR loci

[0034] The exclusion probabilities of each candidate parent at all microsatellite markers were calculated and sorted from largest to smallest. As can be seen from Table 3, the exclusion probability of the SICAU11 marker was the highest at 0.596, and the exclusion probability of the ISICAU03 marker was relatively low. By calculating the cumulative exclusion probability (Table 4), as can be seen from Table 4, in three different cases, the cumulative exclusion probabilities CPE(1), CPE(2), and CPE(3) of these 11 microsatellite markers were as high as 0.9914, 0.9997, and 0.999999 respectively, indicating that the parentage testing efficiency of these 9 microsatellite markers was extremely high.

[0035] Table 3 Statistical results of the average exclusion probability of 9 STR loci

[0036] Table 4 Cumulative exclusion probability of microsatellite markers

[0037] Note: In the table, CEP-1P represents the combined exclusion probability of a candidate parent; CEP-2P represents the combined exclusion probability of a candidate parent given the genotype of a known opposite-sex parent; CEP-PP represents the combined exclusion probability of a candidate parent pair.

[0038] As can be seen from Table 4, the identification efficacy of microsatellite markers is different under different application scenarios. When the number of microsatellite markers is 7, the cumulative exclusion probability for a single parent (i.e., the cumulative exclusion probability when the information of the other parent is unknown) is greater than 0.99. For the identification of the second parent with known information and candidate parent pairs, only the first 4 microsatellite markers (i.e., SICAU07 marker, SICAU06 marker, SICAU11 marker, and SICAU08 marker) and the first 3 microsatellite markers (i.e., ISICAU07 marker, SICAU06 marker, and SICAU11 marker) are required respectively to make the cumulative exclusion probability greater than 0.99.

[0039] Therefore, according to the standard that the cumulative exclusion probability of paternity testing is not less than 0.99, in order to reduce the detection cost, the microsatellite markers to be selected in actual application are respectively: (1) When the information of the other parent is unknown, to detect whether the tested offspring and the tested parent are parent-child relationship, all 7 microsatellite markers (i.e., SICAU07 marker, SICAU06 marker, SICAU11 marker, SICAU08 marker, SICAU10 marker, SICAU02 marker, SICAU01 marker, SICAU05 marker, and SICAU03 marker used in combination) need to be applied; (2) When the information of the other parent is known, to detect whether the tested offspring and the tested parent are parent-child relationship, the first 4 microsatellite markers (i.e., SICAU07 marker, SICAU06 marker, SICAU11 marker, and SICAU08 marker used in combination) need to be applied; (3) When excluding whether the tested offspring and the tested parent pair are parent-child relationship, only the first 3 microsatellite markers (i.e., ISICAU07 marker, SICAU06 marker, and SICAU11 marker used in combination) need to be applied.

[0040] 2.2 Paternity testing simulation During the detection, there may be a small number of loci that are not amplified. To increase the success rate of detection, it is recommended to add 1-2 loci. That is, 9 microsatellite loci can be used as the core loci for duck parentage identification. The Cervus software can evaluate the credibility through parentage simulation. The purpose of the simulation is to obtain a large number of Delta distributions (simulated 10,000 times) by comparing the LOD values of a large number of random offspring. By comparing the Delta distribution when the most-likely parent is the true parent with the Delta distribution when the most-likely parent is not the true parent, the Delta critical value is obtained. If this critical value is determined at a specific credibility level such as 95%, then when analyzing the parentage relationship of real data, if the LOD value of the most-likely parent exceeds the Delta critical value, the credibility of the parentage identification is 95%.

[0041] The genotype typing results of the 96 Tianfu Nonghua ducks in step two were simulated for different situations of parentage identification using the above 9 microsatellite markers, and sampled 10,000 times to meet the situations in the conservation and breeding farms. The results show that when one parent is known, the Delta critical value is 0, and the identification success rate reaches 99%, and the credibility is greater than 95%; when there is no parent information, the Delta critical value is 1.05, and the identification success rate reaches 87%, and the credibility is greater than 95%.

[0042] 2.2.1 Maternal parentage identification simulation: The results are shown in Tables 5 and 6.

[0043] Table 5 Maternal parentage identification simulation - LOD

[0044] Note: Assignments represents the number of offspring whose parentage identification is successful using this LOD or Delta critical value; Assignment Rate represents the proportion of offspring with successful parentage identification in the total; Unassigned represents those without successful identification.

[0045] Table 6 Maternal parentage identification simulation - Delta

[0046] At the 80% confidence level, the LOD critical value and the Delta critical value are -999 and 0 respectively, indicating that the STR markers used in the maternal parentage identification simulation have very strong capabilities.

[0047] 2.2.2 Paternal parentage identification simulation: The results are shown in Tables 7 and 8.

[0048] Table 7 Paternal parentage identification simulation - LOD

[0049] Table 8 Paternity testing simulation - Delta

[0050] At the 95% and 80% confidence levels, the LOD critical values and Delta critical values are both -999 and 0 respectively, indicating that the STR markers used in the paternity testing simulation have very strong capabilities.

[0051] 2.2.3 Paternity and maternity testing simulation: The results are shown in Tables 9 and 10.

[0052] Table 9 Paternity and maternity testing simulation - LOD

[0053] Table 10 Paternity and maternity testing simulation - Delta

[0054] At the 95% and 80% confidence levels, the LOD critical value is -999, and at the 80% confidence level, the Delta critical value is 0, indicating that the STR markers used in the paternity testing simulation have very strong capabilities.

[0055] Based on the simulation results in Tables 5 to 10, at the 80% confidence level, the Delta critical values are all 0, and the LOD critical values are all -999. This shows that the marker capabilities of the 9 STR loci are very high. In this experiment, two critical values, LOD and Delta, were used for simulation. By comparing the two methods, it was found that when the confidence level is 95%, using the LOD value as the critical value can result in more offspring being identified; when the confidence level is 80%, using the LOD value as the critical value can identify all offspring, while using the Delta value as the critical value fails to identify a few individuals. Therefore, the LOD value is selected as the critical value for subsequent paternity testing.

[0056] 2.3 Paternity testing Using CERVUS 3.0 for paternity testing will obtain a detailed Excel result table recording the identification results and corresponding data, and a text document summarizing the identification results, which counts the number of successfully assigned offspring, the number of unassigned offspring, and their respective proportions.

[0057] 2.3.1 Maternity testing Table 11 shows that at the 95% confidence level, 38 offspring obtained maternity testing results, accounting for 91% of the total; at the 80% confidence level, 42 offspring all obtained maternity testing results, accounting for 100% of the total.

[0058] Table 11 Parameters related to matriarchal identification

[0059] 2.3.2 Identification of paternity The results are shown in Table 12, which shows that at a confidence level of 95%, 42 offspring obtained paternity identification results, accounting for 100% of the total proportion; at a confidence level of 80%, 42 offspring obtained paternity identification results, accounting for 100% of the total proportion.

[0060] Table 12 Parameters related to paternity identification

[0061] 2.3.3 Parental Rights Determination The results are shown in Table 13, which shows that at a confidence level of 95%, 42 offspring obtained parentage identification results, accounting for 100% of the total proportion; at a confidence level of 80%, 42 offspring obtained parentage identification results, accounting for 100% of the total proportion.

[0062] Table 13 Parameters related to parental rights identification

[0063] Table 14 Matching rate between identification results and pedigree

[0064] Comparing the identification results with the pedigree, it was found that 4 offspring were not the offspring of the sampled parents, and there may be recording errors. The matching rates of the results of the maternal identification, paternal identification, and parent pair identification (sex known) with the pedigree were 92.24%, 93.18%, and 91.76%, respectively (Table 14).

[0065] The above marker combination was also applied to the parentage identification of duck breeding farms. When the information of the other parent was known, the first four microsatellite markers, namely SICAU07, SICAU06, SICAU11 and SICAU08, were used in combination to detect whether the offspring to be tested had a parent-offspring relationship with the parent to be tested. The genotypes of the known father (2) and offspring (2) of the above-mentioned Nonghua Mallard individuals and the unknown mother (8) were selected, and after 10,000 simulations using Cervus software, the mother was identified when the father was known.

[0066] Table 15 LOD values ​​and confidence verification results of candidate maternal paternity tests

[0067] By analyzing the genotypes of 4 microsatellite markers of them, the likelihood method was applied to identify the parent-offspring relationships between them. The identification results were consistent with the actual pedigree, and the confidence levels all reached 95% (15). When the biological mother was used as the candidate female parent, the LOD values were all greater than 0 (such as 1363, 1818), while when unrelated female ducks were used as the candidate mothers, the LOD values were all less than 0, indicating that it was impossible for them to be the biological fathers of each offspring. This result further verified that this microsatellite marker combination could be used as a detection system for parentage testing of Pekin ducks, and the test results were accurate and reliable.

[0068] 2.4 Establishment of parentage testing system According to the above simulation data and identification results, it is sufficient to use 9 STR loci for parentage testing of ducks. The molecular marker combinations developed in this paper can be used for duck populations of other breeds after high-throughput sequencing screening and evaluation of exclusion probability. The first group is suitable for identifying female parents in conservation farms. The combination of the two groups can be applied to any situation, especially to make up for the impact caused by the loss of pedigree in duck breeding work.

[0069] Table 16 Duck parentage testing system

[0070] After preliminary screening and filtering, we selected 9 loci from the common STR loci for the development of parentage testing markers. These loci had high genetic diversity and obvious genotype differences, and showed high amplification efficiency and stability during PCR amplification, with good fluorescence labeling effects, which helped to improve the accuracy of genotyping. Through fluorescence labeling, multiple STR loci could be detected simultaneously in the same reaction system, improving the analysis throughput. In parentage testing, the Cervus software was used to analyze the parent-offspring relationships between parents and offspring. The results showed that these loci could effectively distinguish the relationships between parents and offspring, and the parent matching probability was significantly higher than that of non-parent pairs, showing its high application value in parentage testing. In addition, according to the actual needs (the situations of conservation farms and breeding farms), appropriate STR combinations could be selected for parentage testing to save costs and time. The present invention developed 9 highly polymorphic STR markers suitable for parentage testing, and their combined exclusion probability exceeded 99.99%.

[0071] The specific embodiments of the present invention disclosed above are only for illustration, but the protection scope of the present invention is not limited thereto. Any person skilled in the art in the technical field disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the above-mentioned claims.

Claims

1. A duck paternity testing kit, which comprises the following amplification primers: 。 2. The duck paternity testing kit according to claim 1, the kit further comprises at least 1 pair, 2 pairs, 3 pairs, 4 pairs or 5 pairs of the following amplification primers: 。 3. The duck paternity testing kit according to claim 2, the kit does not include other amplification primers.

4. The duck paternity testing kit according to any one of claims 1-3, the kit further comprises a DNA extraction reagent.

5. The duck paternity testing kit according to any one of claims 1-3, the kit further comprises a DNA amplification reagent.

6. Use of the kit according to any one of claims 1-5 in duck paternity testing.

7. Use of the kit according to claim 1 in duck paternity testing, characterized in that When the information of another parent is known and detecting whether the offspring to be tested and the parent to be tested are parent-child relationship, only the amplification primers described in claim 1 are used.

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