High-oil peanut breeding method and molecular marker screening method thereof

Abstract

The application discloses a high-oil peanut breeding method and a molecular marker screening method, and comprises the following steps: preparing a combination by performing distant cross breeding of a female parent of a peanut cultivation material of Yueyou 551 and a wild peanut germplasm PI210553, performing data processing on the basis of obtained offspring materials and taking high-oil germplasms as data reference indexes, and obtaining a series of semi-wild blood high-oil germplasms or super high-oil germplasms. Quality trait QTL analysis and positioning are performed on the basis of the semi-wild blood high-oil germplasms or super high-oil germplasms and a construction process thereof, and the semi-wild blood high-oil germplasms or super high-oil germplasms can be used for widening a genetic basis of cultivated peanuts, improving genetic diversity of the cultivated peanuts and increasing a gene resource library of peanut breeding. Development of marker primers is performed on the basis of related sites, and the marker primers can be used for molecular marker assisted selection breeding. The technical scheme of the application has double important values in theory and application.

Description

Technical Field

[0001] This invention relates to the field of crop breeding technology, and in particular to a method for breeding high-oil peanuts and a method for screening them using molecular markers. Background Technology

[0002] my country is the world's largest producer and consumer of peanuts. The national peanut planting area exceeds 70 million mu (approximately 4.7 million hectares), with a total output exceeding 18 million tons, ranking first among domestic oilseed crops. About 55% of the total peanut production is used for oil extraction, with an annual peanut oil production of 3.2 million tons, making it the second largest source of domestic vegetable oil. Developing peanut production is one of the most important ways to ensure my country's edible oil security. Generally, peanut germplasm has an oil content between 40% and 55%, with some high-oil peanut germplasm exceeding 60%. However, in actual production, the oil content of peanuts is generally around 50%. Research shows that for every 1 percentage point increase in peanut oil content, economic benefits can increase by 7%, thus cultivating high-oil peanut varieties is an urgent need for the modern peanut industry.

[0003] However, yield and quality traits in almost all crops are complex, with quantitative traits significantly influenced by both genetic and environmental factors (Baring et al. 2013; Wilson et al. 2013; Cui et al. 2020; Chen et al. 2019). For example, Chen et al. (2019) estimated several yield-related traits under various environments. The heritability of the tested yield-related traits ranged from 0.34 to 0.93, and analysis of variance showed significant differences among RIL populations, environments, and RIL×environment interactions. In some cases, the marginal variation between these continuous quantitative traits and alternating lines makes it difficult to distinguish the best-performing lines in field trials. Therefore, clarifying heritability and mode of inheritance is beneficial for breeders to develop breeding strategies. Currently, determining oil content requires a relatively difficult process and can only be done after harvest. In this context, traditional breeding strategies to increase oil content are considered costly, inefficient, and time-consuming. In modern breeding, marker-assisted selection (MAS) allows for the rapid selection of traits of interest from germplasm resources at an early stage, unaffected by complex environmental conditions. MAS has achieved considerable success in breeding superior crops with complex quantitative traits, such as cotton, rice, and common soybean (Tian et al. 2021; Hulsekemp et al. 2015; Shi et al. 2021), as well as in animal breeding (Chen et al. 2022). However, the establishment of MAS requires successful mapping of specific, useful genes or QTLs.

[0004] To achieve the goals of MAS (Magnetic Oil Spectrum) breeding, breeders have been striving to identify valuable QTLs (Quality Traits). In many cases around the world, identifying QTLs for peanut oil content and conducting targeted breeding efforts is a crucial component of projects aimed at ensuring the supply of edible oil for humanity. Unfortunately, although breeders have recognized the importance of MAS breeding, research into tapping into genetic resources to increase peanut oil content lags significantly behind that of other oilseed crops such as soybeans, especially in the cloning of functional genes. Due to the lack of relevant beneficial genetic resources in peanut varieties, breeding high-oil peanut varieties using MAS remains difficult. Because artificial selection is geographically specific, after several generations of continuous selection by breeders, the genotypes of varieties gradually become homogenized, resulting in a narrow genetic base. It is difficult to create superior varieties using these homogenized genetic resources. Therefore, enriching the genetic diversity of peanuts, especially tapping into wild peanut genetic resources, is crucial for future peanut breeding work. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method for breeding high-oil peanuts and a molecular marker screening method thereof.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows.

[0007] The method for breeding high-oil peanuts involves using cultivated peanut materials as the female parent and conducting distant hybridization combinations with specific wild peanut germplasm. Based on the resulting offspring materials and using high-oil germplasm as a data reference, data processing is performed to obtain semi-wild high-oil germplasm.

[0008] As a preferred technical solution of the present invention, the Yueyou 551 peanut cultivation material is used as the female parent and the wild peanut germplasm PI210553 is used for distant hybridization combination. Based on the obtained offspring materials and using high-oil germplasm as the data reference, a series of semi-wild high-oil germplasm or ultra-high-oil germplasm are obtained.

[0009] As a preferred technical solution of the present invention, the data standard for the high oil content seed is: the oil content is all above 57%; and the seed with an oil content measurement value above 60% is considered to be an ultra-high oil content seed.

[0010] As another aspect of the present invention, the above-mentioned series of semi-wild high-oil or ultra-high-oil germplasm are used to broaden the genetic basis of cultivated peanuts, and / or enhance the genetic diversity of cultivated peanuts, and / or increase the gene resource pool of peanut breeding.

[0011] As another aspect of the present invention, the above-mentioned series of semi-wild high-oil or ultra-high-oil germplasm are used to construct high-density genetic maps based on the semi-wild high-oil or ultra-high-oil germplasm and its construction process. Genotyping of the RIL population during the construction of the semi-wild high-oil or ultra-high-oil germplasm is performed using a liquid-phase chip. Specifically, after rigorous screening, a total of 3,290 polymorphic SNP markers were identified. These polymorphic markers were anchored to the corresponding 20 peanut chromosomes based on the physical location of the SNP loci on the liquid-phase chip. Further, the markers were grouped according to the chromosomes, and high-oil germplasm was constructed. Density genetic linkage map; the map covers a total length of 4,421.92 cM, with an average length of 221.10 cM for each linkage group; among the linkage groups on 20 chromosomes, chromosome 13 has the longest genetic length at 350.86 cM, while chromosome 4 has the shortest at 57.90 cM; each linkage group has an average of 164.5 polymorphic SNP markers, with chromosome 15 having the most at 309 and chromosome 16 having the fewest at 33; the average distance between adjacent polymorphic markers is 1.34 cM, and the average genetic distance between markers on different chromosomes ranges from 0.90 cM to 4.00 cM.

[0012] As another aspect of the present invention, the use of the above-mentioned series of semi-wild high-oil or ultra-high-oil germplasm of semi-wild lineage is based on QTL analysis of quality traits using the semi-wild high-oil or ultra-high-oil germplasm of semi-wild lineage and its construction process. Specifically, QTL detection is performed using ICIM-ADD and confirmed using the R language package "qtl". A total of 12 QTL loci were detected under multiple traits and multiple environments, with LOD values ​​between 3.26 and 17.82, explaining genetic variation between 1.97% and 24.56%. Among them, 7 QTL loci were located using protein-oil trait and 1 QTL locus was located using oleic acid-linoleic acid trait. Six QTLs were identified. Among them, the locus named qSQ_7 was stably detected under multiple environments, with LOD values ​​ranging from 6.01 to 17.82, explaining 4.59% to 24.56% of the genetic variation. The oil content enhancing gene originated from SW9721-3, and this QTL locus has substantial breeding value. The locus named qSQ_19 was simultaneously mapped to three traits—oil content, oleic acid, and linoleic acid—under more than one environment, indicating that qSQ_19 synergistically regulates multiple quality traits. Apart from the above two loci, the remaining 10 QTL loci were detected under only one environment, indicating that the function of these QTL loci is related to the environment.

[0013] As another aspect of the present invention, based on the above-mentioned auxiliary marker development method for the qSQ_7 site, given that qSQ_7 is an environmentally stable major QTL, the SNP-based CAPS marker SM1-5 is developed based on the parental resequencing results.

[0014] Furthermore, to verify the usability of the CAPS marker, SW9721 was crossbred with three cultivated peanut resources—ST320, Jihua 201138, and Jihua 6—to form hybrid combinations. After self-pollination, three F2 populations were formed: pop1, pop2, and pop3. SM1 and SM2 were used for screening in the F2 populations. From each of the three F2 populations, 25 individual plants with genotypes completely identical to ST320, Jihua 201138, and Jihua 6 were selected. The remaining plants were then further screened from the three populations to identify those with genotypes identical to SW9721. Twenty-five individual plants from each of the SM primer pairs were selected. The oil content of these individual plants was measured after harvesting and statistically analyzed. After marker selection, the average oil content of individual plants with the same genotype as SW9721 in pop1, pop2, and pop3 were 51.46%, 51.83%, and 50.96%, respectively, while the average oil content of individual plants with the same genotype as ST320, Jihua 201138, and Jihua 6 were 49.89%, 49.54%, and 48.98%, respectively. This means that after selection with SM primer pairs, the average oil content of the progeny was significantly increased by 1.57, 2.29, and 1.97 percentage points, respectively.

[0015] As another aspect of the present invention, a molecular breeding method related to peanut oil content involves detecting the genotype of the major QTL qSQ_7 related to peanut oil content in the peanut plant genome in the early stage of molecular breeding, thereby conducting peanut variety selection related to oil content.

[0016] In the genotype detection process, firstly, dCAPS primer markers were developed based on five SNP sites closely linked to qSQ_7. This involved extracting the upstream and downstream sequences of the SNP sites and designing a dCAPS primer above and below the mutation site based on the restriction enzyme recognition sequences generated or subtracted before and after the mutation. This amplified the sequence containing the mutation site. Since the amplified products from different parental materials were different, the nucleotide type of the mutation site was identified by enzyme digestion to obtain the genotype of the peanut plant to be tested.

[0017] The dCAPS primers are independently selected from: CAPS markers SM1-5 developed based on tightly linked SNPs on quality trait QTLs; their nucleotide sequences are shown in SEQ ID NO.1 to SEQ ID NO.10 in sequence.

[0018] The sequence information for molecular markers SM1 to SM5 is given below; these molecular markers were developed based on five groups of SNP sites that are closely linked to the genome.

[0019] CAPS1; Ch7_320503; TCTTCTTCCTTACTATACAAAGCGAC (SEQ ID NO.1); AATAGAAAGCTTCATTTGACTAAATAGCC (SEQ ID NO.2); endonuclease MboII; recognition site GAAGA. See SEQ ID NO.11 for variant sites; where A represents the high-oil genotype and G represents the low-oil genotype.

[0020] CAPS2; Ch7_524680; CGAACTCCCAATCCTAAAGT (SEQ ID NO3); CTTCAAATCATTAAACTAATCATA (SEQ ID NO.4); endonuclease MboII; recognition site GAAGA. See SEQ ID NO.12 for variant sites; where T represents the high-oil genotype and A represents the low-oil genotype.

[0021] CAPS3; Ch7_570150; AAGTGGACGAGTGAGTTGAG (SEQ ID NO.5); CTCAATG ACCAAAAGGGCTA (SEQ ID NO.6); endonuclease MboII; recognition site GAAGA. See SEQ ID NO.13 for variant sites; where A represents the high-oil genotype and G represents the low-oil genotype.

[0022] CAPS4; Ch7_586747GAGCATCTAATTTCCCTGAG (SEQ ID NO.7); ATTCCTTCAGAGATTGCTTC (SEQ ID NO.8); endonuclease BseMII; recognition site CTCAG. See SEQ ID NO.14 for variant sites; where A represents the high-oil genotype and C represents the low-oil genotype.

[0023] CAPS5; Ch7_606659; ATTACAACTGAAGGAGGTGC (SEQ ID NO.9); CAAAGG GGAAAGTAATCAGA (SEQ ID NO.10); endonuclease DpnI; recognition site GATC. See SEQ ID NO.15 for variant sites; where A represents the high-oil genotype and G represents the low-oil genotype.

[0024] Based on the location and polymorphic variations of SNPs, 30 bp sequences upstream and downstream of the SNP are extracted from the genome. CAPS primers (Neffetal., 2002) are designed using the "dCAPS Finder" program (http: / / helix.wustl.edu / dcaps / dcaps.html). Primers are designed above and below the mutation site based on the restriction enzyme recognition sequences generated or subtracted before and after the mutation to amplify the sequence containing the mutation site. Since different parental materials produce different amplified products, the nucleotide type of the mutation site can be identified through enzyme digestion, thus determining the gene origin.

[0025] The sites, primer sequences, restriction enzymes, and product information used in this experiment are listed in the primer table above. To detect whether the designed CAPS marker is polymorphic between parents, PCR amplification was first performed using each parent as a template. The PCR reaction system and procedure are shown below:

[0026] PCR reaction system: 10×Ex TagHS buffer 2.5μL; 0.2mM dNTP 2.0μL; Template 1.0μL; Primer-F (10μM) 0.5μL; Primer-R (10μM) 0.5μL; Ex TaqHS 0.2μL; ddH2O 18.3μL; Total 25μL. PCR reaction program: 95℃ 2min; 95℃ 30s; 53℃ 30s; 72℃ 30s; 72℃ 10min; 16℃∞; Total 30 cycles. The amplified PCR products were detected by agarose gel electrophoresis. Products with single bands were further analyzed by enzyme digestion. The restriction enzyme system used was as follows: 10×NEB Buffer 2.5 μL; restriction endonuclease 1.0 μL; PCR product 10 μL; ddH2O 11.5 μL; Total 25 μL. The enzymes were digested at their operating temperature for 30 min, and then routine band detection was performed by 1% agarose gel electrophoresis.

[0027] The technical details not elaborated in the above operation steps are all routine operations in the field of biomolecular technology.

[0028] The beneficial effects of adopting the above technical solution include at least the following aspects: ① The breeding method of this invention can effectively obtain a series of high-oil germplasm resources. This invention obtains a series of semi-wild high-oil germplasm by using peanut cultivated materials as the female parent and conducting distant hybridization with specific wild peanut germplasm, and by processing the data based on the progeny materials and using high-oil germplasm as the data reference, thus enriching peanut germplasm resources. In particular, this invention obtains a series of semi-wild high-oil or ultra-high-oil germplasm by using Yueyou 551 peanut cultivated material as the female parent and conducting distant hybridization with wild peanut germplasm PI210553. The high-oil germplasm has an oil content of over 57%, and the ultra-high-oil germplasm has an oil content of over 60%. ② The research results of this invention effectively broaden the genetic resources of peanut breeding. The series of semi-wild high-oil or ultra-high-oil germplasm obtained by this invention can broaden the genetic basis of cultivated peanuts, enhance the genetic diversity of cultivated peanuts, increase the gene resource bank of peanut breeding, and provide more possibilities for peanut variety improvement. ③ This invention also utilizes semi-wild high-oil or ultra-high-oil germplasm and its construction process to construct a high-density genetic map, identifying a total of 3290 polymorphic SNP markers and anchoring them to the corresponding 20 peanut chromosomes. The constructed high-density genetic linkage map covers a total length of 4421.92 cM, with an average length of 221.10 cM for each linkage group, providing detailed genetic information for peanut genetic research. Based on this, this invention clarifies the genetic length range of different chromosomes (57.90 cM for chromosome 4 and 350.86 cM for chromosome 13), the number of polymorphic SNP markers in each linkage group (309 for chromosome 15 and 33 for chromosome 16), and the average distance between adjacent polymorphic markers (1.34 cM). The average genetic distance between markers on different chromosomes ranges from 0.90 cM to 4.00 cM. ④ This invention analyzed and located QTLs for quality traits, detecting a total of 12 QTL loci under multiple trait and environmental conditions, with LOD values ​​ranging from 3.26 to 17.82 and explained genetic variation ranging from 1.97% to 24.56%, providing target loci for genetic research and improvement of peanut quality traits. Among them, the locus named qSQ_7 was stably detected under multiple environments, and the oil content enhancement gene originated from SW9721-3, possessing substantial breeding value; the locus named qSQ_19 synergistically regulates multiple quality traits; in addition, although the other 10 QTL loci besides qSQ_7 and qSQ_19 were detected under only one environment, it also indicates that these QTL loci are related to the environment, providing clues for further research on the relationship between environment and peanut quality traits.⑤ Furthermore, based on the above-mentioned technical achievements, this invention further develops and applies auxiliary markers for molecular breeding of peanuts. Considering that qSQ_7 is an environmentally stable major-effect QTL, the SNP-based CAPS marker SM1-5 was developed. Through screening and verification in three F2 populations, the results showed that after marker selection, the average oil content of the offspring could be significantly increased by 1.57, 2.29, and 1.97 percentage points, providing an effective tool for molecular-assisted breeding of peanut oil content. Based on this, a molecular breeding method related to peanut oil content is further provided. In the early stage of molecular breeding, the genotype of the selected site qSQ_7 related to peanut oil content in the peanut plant genome is detected, which helps to select peanut varieties with oil content and improves breeding efficiency. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the phenotypes of SW9721-3 and its parent in Example 1.

[0030] Figure 2 This is a schematic diagram showing the changes in quality traits of peanut populations under different environments in Example 2.

[0031] Figure 3 This is a schematic diagram illustrating the correlation analysis of the quality traits of the RIL population in Example 3.

[0032] Figure 4 This is the genetic linkage map of the RIL population in Example 5.

[0033] Figure 5 This is a schematic diagram of the CAPS marker selection efficiency evaluation in Example 7; in the figure, C1, C2 and C3 represent the genotypes of the cultivated parents ST320, Jihua 201138 and Jihua 6, respectively, and SW represents the SW9721 type. Detailed Implementation

[0034] The following embodiments illustrate the present invention in detail. All raw materials and equipment used in the present invention are conventional commercially available products and can be directly obtained through market purchase. It should be understood that, as used in this specification and appended claims, the term "comprising" indicates the presence of a described feature, integral, step, operation, element, and / or component, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof. It should also be understood that the term "and / or" as used in this specification and appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0035] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0036] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance. References to "one embodiment" or "some embodiments" in this application mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0037] Example 1: Creation of the semi-wild, ultra-high-oil germplasm SW9721

[0038] In this embodiment, to enrich the genetic diversity of cultivated peanut germplasm resources, wild peanut germplasm PI210553 was used as the male parent and crossbred with conventional peanut cultivation materials to obtain 584 progeny materials. With ultra-high oil content as the selection target, four SW9721 series ultra-high oil content germplasm with high combining ability (Table 1 and ...) were finally screened from the Yueyou 551 × PI210553 combination. Figure 1 All four germplasm samples had an oil content exceeding 57%, with SW9721-3 having the highest measured oil content at 62.5%, exceeding the national high-oil standard for peanuts by 7.5 percentage points. The creation of SW9721 broadened the genetic basis of cultivated peanuts and enriched their genetic diversity.

[0039] Table 1. Main agronomical properties and quality characteristics of SW9721 series materials

[0040]

[0041] Example 2: Environmental Impact on the Quality of SW9721-3 Derived RIL Population

[0042] In this embodiment, to further investigate the influence of environment on peanut quality traits, the main quality traits of the SW9721-3 and Jihua 5 derived RIL populations were measured under three environments. The results showed that the four quality traits differed significantly under different environments. Figure 2 Among the RIL populations grown under the DS2013 environment, the oil and oleic acid contents were generally higher, with average values ​​of 57.41% and 45.42%, respectively, while the protein and linoleic acid contents were generally lower, with average values ​​of 21.81% and 36.27%, respectively. Furthermore, compared with the quality of the RIL populations grown under the other two environments, the maximum variation in the average values ​​of oil, protein, oleic acid, and linoleic acid contents were 11.02%, 22.66%, 40.80%, and 20.03%, respectively. These results indicate that the environment has a significant impact on peanut quality, especially the oleic acid content.

[0043] Example 3 Correlation analysis among quality traits

[0044] In this embodiment, to further explore the intrinsic relationships among peanut quality traits, correlation analysis was performed using Blup breeding values ​​of four quality traits from RIL populations under three different environments. The results showed ( Figure 3 Significant correlations were found among the four quality traits (p<0.001), with correlation coefficients ranging from 2.3 to 0.97. Specifically, a strong negative correlation was observed between oil content and protein, and between oleic acid and linoleic acid, with correlation coefficients of 0.71 and 0.97, respectively. However, a weak correlation was observed between oil content and protein, and between oleic acid and linoleic acid, with correlation coefficients ranging from 0.23 to 0.34. These results indicate a close relationship between oil content and protein, and between oleic acid and linoleic acid, suggesting they may share a common primary genetic basis. However, the relationships between oil content and protein, and between oleic acid and linoleic acid, are relatively distant, suggesting they may have different primary genetic bases or only partially share them. Therefore, oil content and protein, as well as oleic acid and linoleic acid, need to be considered together during breeding.

[0045] Example 4: Genetic analysis of quality traits

[0046] In this embodiment, to further analyze the genetic patterns of quality-related traits in the semi-wild germplasm SW9721-3, the main quality traits of the RIL population under three environmental conditions were analyzed. The results (Table 1) show that the phenotypic variation rates of the four quality traits in the RIL population ranged from 3.78% to 10.61%. The variation rate of oil content was relatively low, all within 5% under the three environmental conditions, while the variation rate of protein was relatively large, around 10%. The absolute values ​​of skewness and kurtosis of the measured values ​​were all less than 1, basically conforming to a normal distribution. Furthermore, the heritability of all four quality traits was above 0.6, indicating that genetic variation was the main factor in phenotypic variation. Among them, the heritability of protein-oil content was relatively high, at 0.778 and 0.793 respectively, while the heritability of oleic acid-linoleic acid was 0.606 and 0.637 respectively, indicating that the inheritance of protein-oil content was relatively stable and not easily affected by environmental factors, while the content of oleic acid-linoleic acid was easily affected by environmental factors and fluctuated significantly.

[0047] Table 2. Genetic analysis of the RIL population

[0048]

[0049] Example 5: Construction of High-Density Genetic Maps

[0050] In this embodiment, to prepare for subsequent identification of gene loci affecting quality-related traits, genotyping of the RIL population was performed using a liquid-phase microarray. After rigorous screening, a total of 3,290 polymorphic SNP markers were identified. Based on the physical location of the SNP loci on the liquid-phase microarray, these polymorphic markers were anchored to the corresponding 20 peanut chromosomes. Further, the markers were grouped according to the chromosomes, and a high-density genetic linkage map was constructed. The results showed ( Figure 4 The map covers a total length of 4,421.92 cM, with an average length of 221.10 cM for each linkage group. Among the linkage groups on the 20 chromosomes, chromosome 13 has the longest genetic length at 350.86 cM, while chromosome 4 has the shortest at 57.90 cM. ​​Each linkage group has an average of 164.5 polymorphic SNP markers, with chromosome 15 having the most (309) and chromosome 16 having the fewest (33). The average distance between adjacent polymorphic markers is 1.34 cM, and the average genetic distance between markers on different chromosomes ranges from 0.90 cM to 4.00 cM.

[0051] Example 6: QTL Analysis of Quality Traits

[0052] In this embodiment, to explore the superior wild-type gene resources carried by SW9721-3, QTL detection was performed using ICIM-ADD, and confirmed using the R language package "qtl". The detection results (Table 3) show that a total of 12 QTL loci were detected for the four traits under three environments. The LOD values ​​of these loci ranged from 3.26 to 17.82, explaining 1.97% to 24.56% of the genetic variation. Among these, 7 QTL loci were located using the protein-oil content trait, and 6 QTLs were located using the oleic acid-linoleic acid trait. Specifically, qSQ_7 could be stably detected by both protein and oil content under the three environments, with LOD values ​​ranging from 6.01 to 17.82, explaining 4.59% to 24.56% of the genetic variation. The oil content-enhancing gene originated from SW9721-3, indicating that this QTL locus has significant breeding value. The QTL locus qSQ_19 was simultaneously localized to three traits—oil content, oleic acid, and linoleic acid—under two different environments, indicating that qSQ_19 synergistically regulates multiple quality traits. Apart from these two loci, the remaining 10 QTL loci were detected under only one environment, suggesting that the function of these QTL loci is environment-dependent. The results also showed that among all these loci, only qSQ_19 is the same QTL controlling protein-oil content and the QTL controlling oleic acid-linoleic acid, indicating that the main genetic bases of protein-oil content and oleic acid-linoleic acid are different, which is consistent with the correlation analysis results.

[0053] Table 3. QTL analysis of quality-related traits

[0054]

[0055] Example 7: Development and Utilization of the High-Oil Site qSQ_7 Auxiliary Marker

[0056] In this embodiment, given that qSQ_7 is an environmentally stable major-effect QTL, five pairs of SNP-based CAPS markers, named SM1-5, were developed based on the parental resequencing results. To verify the usability of the developed CAPS markers, SW9721 was crossbred with three cultivated peanut resources—ST320, Jihua 201138, and Jihua 6—to form three F2 populations: pop1, pop2, and pop3. SM1 and SM2 were used for screening in the F2 populations. From each of the three F2 populations, 25 individual plants with genotypes completely identical to ST320, Jihua 201138, and Jihua 6 were selected. From the remaining three populations, 25 individual plants with genotypes identical to SW9721 were further selected. The oil content of these individual plants was measured and statistically analyzed after harvesting.

[0057] The results show ( Figure 5After marker selection, the average oil content of individual plants with the same genotype as SW9721 in pop1, pop2, and pop3 were 51.46, 51.83, and 50.96%, respectively, while the average oil content of individual plants with the same genotype as ST320, Jihua 201138, and Jihua 6 were 49.89, 49.54, and 48.98%, respectively. That is, after SM1-5 selection, the average oil content of the offspring can be significantly increased by 1.57, 2.29, and 1.97 percentage points, respectively.

[0058] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0059] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A molecular breeding method related to peanut oil content, characterized by: Early detection of major-effect QTLs related to peanut oil content in the peanut plant genome during molecular breeding. qSQ_7 The genotype of peanuts is used to select peanut varieties with oil content. Regarding genotype testing, firstly, based on... qSQ_7 Five closely linked SNP sites were used to develop dCAPS primer markers. The upstream and downstream sequences of the SNP sites were extracted, and a dCAPS primer was designed above and below the mutation site based on the enzyme digestion recognition sequence generated or reduced before and after the mutation. The sequence containing the mutation site was amplified. Since the amplified products of different parent materials are different, the nucleotide type of the mutation site can be identified by enzyme digestion to obtain the genotype of the peanut plant to be tested. The dCAPS primers are independently selected from: CAPS markers SM1 and SM2 developed based on SNPs tightly linked to quality trait QTLs; SM1 is a primer pair consisting of SEQ ID NO.1 and SEQ ID NO.2, and SM2 is a primer pair consisting of SEQ ID NO.3 and SEQ ID NO.4; both SM1 and SM2 correspond to the restriction enzyme MboII, and the recognition site is GAAGA.

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