METHOD FOR IMPROVING PLANT VARIETY
20200008387 ยท 2020-01-09
Inventors
Cpc classification
International classification
A01H6/46
HUMAN NECESSITIES
A01H1/04
HUMAN NECESSITIES
Abstract
The present disclosure relates to a method for improving a plant variety. The present disclosure relates to a method of plant breeding, the method comprising the following steps: 1) Selecting a background variety and a donor variety, 2) Comparing the background variety and the donor variety to identify a module or locus to be improved, 3) Crossing the background variety and the donor variety to obtain a hybrid progeny, backcrossing the hybrid progeny to the background variety to obtain a backcross progeny, and constructing a genetic population using the backcross progeny, 4) Selecting, using molecular markers or a sequencing method, a backcross progeny having chromosomal regions derived from the background variety except for the module or locus to be improved, the molecular markers comprising genome molecular markers and module or locus molecular markers designed according to the selected module or locus, 5) Self-crossing the selected backcross progeny to obtain an improved plant variety.
The present disclosure also relates to a plant variety obtainable by said method.
The method can select a plant in laboratory, obtaining a plant with a definite and improved trait and gene with high breeding efficiency, and achieving division of labour during the breeding process and accumulation of breeding advantages.
Claims
1. A method of plant breeding, the method comprising the following steps: 1) Selecting a background variety and a donor variety, 2) Comparing the background variety and the donor variety to identify a module or locus to be improved, 3) Crossing the background variety and the donor variety to obtain a hybrid progeny, backcrossing the hybrid progeny to the background variety to obtain a backcross progeny, and constructing a genetic population using the backcross progeny, 4) Selecting, using molecular markers or a sequencing method, a backcross progeny having chromosomal regions derived from the background variety except for the module or locus to be improved, the molecular markers comprising genome molecular markers and module or locus molecular markers designed according to the selected module or locus, 5) Self-crossing the selected backcross progeny to obtain an improved plant variety.
2. The method of claim 1, wherein step 2) comprises genome sequencing to compare sequences of the module or locus to be improved, such as sequences of an allele, or performing QTL analysis to identity the module or locus to be improved, wherein the module to be improved can be adjusted to a size of, for example, about 50 kb to 5000 kb.
3. The method of claim 1, wherein the molecular markers comprise RFLP, RAPD, SSR, AFLP and SNP; preferably the molecular markers comprise SNP markers; the module or locus molecular markers comprise at least 3 molecular markers, for example 3, 4, 5, 6, 7, 8, 9, 10 or more molecular markers, designed at upstream of the module or locus, within the module or locus, and downstream of the module or locus, respectively.
4. The method of claim 1, wherein the donor variety has an improved trait compared to the background variety, the improved trait comprising for example a yield trait (such as high yield, stable yield and a trait affecting efficiency of light use), a quality trait (such as amino acid composition, sugar composition, protein composition, lipid composition, trace element composition and harmful component composition, such as protease inhibitor, allergen protein and hydrolase composition) and a stress resistance trait (such as disease resistance, antibacterial, antiviral, herbicide resistance, drought resistance, high temperature resistance, cold resistance, insect resistance and a nutrient utilization trait).
5. The method of claim 1, wherein the plant comprises but not limited to Oryza sativa, Zea mays, Triticum aestivum, Phaseolus vulgaris, Glycine max, Brassica spp., Gossypium hirsutum, Helianthus annuus.
6. The method of claim 1, wherein the plant comprises Oryza sativa, the trait comprising a quality trait or a quantitative trait locus (QTL) trait.
7. The method of claim 1, wherein step 3) comprises Crossing the background variety and the donor variety and continuous backcrossing for 3 or more generations to obtain a BC.sub.3F.sub.1 or later population, Detecting a genotype of the BC.sub.3F.sub.1 or later population with the genome molecular markers and the module or locus molecular markers, and selecting a BC.sub.3F.sub.1 or later population that has the module or locus derived from the donor variety and has the highest recovery ratio, and Self-crossing the selected BC.sub.3F.sub.1 or later population to obtain a BC.sub.3F.sub.2 or later population.
8. The method of claim 7, wherein step 3) comprises Selecting a population with a gene crossover on one side of the module or locus from the BC.sub.3F.sub.2 or later population with the module or locus molecular markers, and self-crossing the selected population to obtain a BC.sub.3F.sub.3 or later population, Selecting a population with a gene crossover on the other side of the module or locus from the BC.sub.3F.sub.3 or later population, Eliminating any chromosome fragment derived from the donor variety which is not the module or locus to be improved using backcrossing or self-crossing separation and selecting a population with only an introgressed chromosome fragment of the module or locus to be improved, and self-crossing the selected population to obtain a population with a fixed homozygous module or locus.
9. The method of claim 1, wherein the method comprises repeating steps 1) to 5) one or more times, each time using an improved variety obtained from the previous breeding process as the background variety, and selecting a different module and locus so as to obtain a variety with a plurality of improved modules and loci.
10. A plant variety, obtainable by the method of claim 1, the plant variety being an improved variety compared with the background variety, the improved plant variety comprising an improved module or locus compared with the background variety.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
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DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENT(S)
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[0105] The main plant variety is used as a background variety, which is modified according to the genome defect of the background variety, and the improved line (upgraded variety) (module) of the specific trait of the background variety is cultivated. These modules are aggregated as needed.
[0106]
[0107] After improving the traits of the background and cultivating enough modules, the genome design can be realized. Not only can a single donor be used to cultivate multiple modules, but multiple donors can also be utilized to cultivate more modules.
EXAMPLE 1
[0108] Using high-yielding gene modules to improve and upgrade the main rice variety, Kongyu 131
[0109] Methods and Results:
[0110] 1.1 Experimental Materials
[0111] 1.1.1 Rice Material
[0112] The recurrent parent Kongyu 131 (background variety): it is an early maturity japonica rice variety grown in the high latitude zone, has strong tillering ability, is fertilizer tolerant, lodging resistant and cold tolerant, and requires an active accumulated temperature of 2320 C. Seeding blast grade 9, leaf blast grade 7, panicle neck blast grade 9 are artificially inoculated, and blast grade 9, leaf blast grade 7, panicle neck blast grade 7 are infected naturally. The head milled rice rate is 73.3%, the amylose content is 17.2%, the protein content is 7.41%, and the average yield in Heilongjiang Province is 7684.5 Kg/ha.
[0113] Donor parent GKBR: it is an indica rice with large panicles and is blast resistant. The growth period of GKBR in Guangzhou, China, is 113 days in late season, but normal heading does not occur in Heilongjiang Province due to unsuitable photoperiod and temperature conditions.
[0114] 1.2 Experimental Methods
[0115] 1.2.1 Parental Resequencing, Sequence Comparison Gn1a and Pi21 Allele and SNP Marker Design
[0116] The genomes of rice parental Kongyu 131 and GKBR were re-sequenced by HiSeq 2000 sequencer, and SNP sites between parents were obtained according to the resequencing information. Based on these SNP information, molecular markers were designed for identification of population genotype and plant selection. The sequence of Gn1a of Koshihikari and Habataki (Ashikari et al., 2005) was also downloaded from Genbank (www.ncbi.nlm.nih.gov/genbank) for allele sequence comparison.
[0117] The Gn1a sequences of Kongyu 131, GKBR, Habataki and Koshihikari were compared using DNAMAN. SNP markers were designed based on the sequence differences between Kongyu 131 and GKBR. A specific sequence of 22-24 bases was selected as a positive and negative primer on both sides of the SNP. The size of the amplified to fragment was 50-100 bp. Five SNP markers were designed within Gn1a (Table 1). SNP3 was located in Gn1a, SNP1 and SNP2 were located upstream of Gn1a, while SNP4 and SNP5 were located downstream of Gn1a. SNP2 and SNP4 were close to the 5-UTR and the 3-UTR of Gn1a. The distance of SNP2 and SNP4 was 5761 bp, while the distance between SNP1 and SNP5 was 856 Kb.
TABLE-US-00001 TABLE1 SequencesoftheSNPmarkersdevelopedfortheselectionofGnla Markers Chr. Position Forwardprimer Reverseprimer SNP1 1 5,006,541 ATGCGTGTGGCCCTTGAAAATG AGATCTTCAAGGACGATTAAG SNP2 1 5,269,396 ATTCAAGCATGCCGTACGTTTG AGCCTTCATATGCATGTCGATC SNP3 1 5,272,491 TCCAAAACAGTGAAAAGCATGC TCTAGCTACTACCTACACTAGC SNP4 1 5,275,157 ACTTGGGCCTAATGGCTAGCAG TAGGGTGGCTATACTAACCAGT SNP5 1 5,862,787 AGCATGCAAATAACGAGATGTC CTATTTTAAATTCTTGAGAGGT Position refers to the physical location of IRGSP-1.0
[0118] 1.2.2 Population Construction and Plant Selection for Improved Grain Number Per Panicle
[0119] Indica rice GKBR with large panicles was used as a donor and crossed with Kongyu 131 and then backcrossed for 3 generations to produce a BC.sub.3F.sub.1 population that comprised 127 lines. 160 SNP markers designed based on sequence differences between parents were used to detect the genotypes of BC.sub.3F.sub.1 population from which an plant BC.sub.3F.sub.1-22F01 with Gn1a chromosomal fragment of the donor introgressed and the highest background recovery ratio were selected based on the genotype information of SNP1SNP5 of Gn1a, and the plant BC.sub.3F.sub.1-22F01 was self-crossed to obtain a BC.sub.3F.sub.2 population. A total of 96 plants were randomly selected from the BC.sub.3F.sub.2 population to form a subpopulation BC.sub.3F.sub.2-LQ96 for QTL analysis validation (
[0120] At the same time, plants with crossovers on one side of the target gene were selected from the large population of BC.sub.3F.sub.2 produced by BC.sub.3F.sub.1-22F01 selfing; then a second crossover and selection was made in the large population of BC.sub.3F.sub.3 produced by self-crossing of the above obtained plants with crossovers, and plants with crossovers on the other side of the target gene were selected; the principle of backcrossing or self-separation was used to exclude all other non-target chromosome fragments on the genetic background, and only plants with small fragments of the target gene introgressed were selected; and finally, homozygous plants were selected in their selfing progeny.
[0121] 1.2.4 DNA Extraction, PCR and HRM Detection
[0122] Genomic DNA from rice leaves was extracted using the quick and easy extraction method described Wang H N, (2013) (Wang H N, Chu Z Z, Ma X L, Li R Q, Liu Y G (2013) A high through-put protocol of plant genomic DNA preparation for PCR. Acta Agron Sin 39:1200-1205). The 10 l PCR reaction system is as follows: about 50 ng of template DNA, 1 l of 10 Easy Taq buffer (Transgen Biotech, Beijing, China), 0.2 l of 2.5 mM dNTPs (Transgen Biotech, Beijing, China), 0.5 U Easy Taq DNA Polymerase (Transgen Biotech, Beijing, China), 0.125 l 20 EvaGreen (Biotium Inc.). PCR amplification was performed on a 96-well PCR plate, and the reaction system was covered with 10 l of mineral oil (Amresco Inc.), amplification was performed by a two-step method, 95 C., 5 mins, 1 cycle; 95 C., 15 s, 5565 C. (depending on the Tin value of the primer), 30 s, 40 cycles (the PCR has no extension step because the amplicon is small). After the end of PCR, LightCycler 96 (Roche, Inc.) was used for high resolution melting (HRM) analysis. The SNP genotyping method was the same as (Hofinger et al., 2009)(Hofinger B J, Jing H C, Hammond-Kosack K E, Kanyuka K (2009) High-resolution melting analysis of cDNA-derived PCR amplicons for rapid and cost-effective identification of novel alleles in barley. Theor Appl Genet 119:851-865).
[0123] 1.2.5 Field Planting of Separated Populations and Investigation of Panicle Traits
[0124] The Kongyu 131 was crossed with GKBR and then backcrossed continually to construct a BC.sub.3F.sub.1 population from which an plant BC.sub.3F.sub.2-22F01 with chromosomal fragment of the target gene Gn1a introduced and the highest background recovery ratio were selected, and the plant BC.sub.3F.sub.2-22F01 was self-crossed to obtain a BC.sub.3F.sub.2-LQ96 population which was planted in the rice field in Jiamusi fo Heilongjiang Province (E130 57, N46 23) in April 2015. Sowing and seedling were carried out on 96-well seeding plates with holes (2.5 mm in diameter) at the bottom. One seed is sown per well, and the embryo is facing upwards. When the seedlings grow to 3-4 leaves, they are transplanted to the rice field, and one plant is inserted into each hole. Each plot contains 8 rows of 12 plants per row, with a plant spacing of 20 cm and a row spacing of 30 cm. The field management is consistent with the local rice field. After maturity, the panicle length (PL), the grain number per panicle (GNP) and the number of primary branches per panicle (NPB) were investigated and the grain density per panicle (GDP) and the density of primary branches (DPB) were calculated as follows: GDP=GNP/PL; DPB=NPB/PL.
[0125] 1.2.8 Evaluation of Agronomic Traits of Improved Lines BC.sub.3F.sub.3-624A05, BC.sub.4F.sub.2-350A09 and Kongyu 131
[0126] On April 18th and Apr. 10, 2016, in Changchun City, Jilin Province (E125 18, N44 43) and Jiamusi City (E130 57, N46 23) in Heilongjiang Province, respectivelly, improved lines BC.sub.3F.sub.3-624A05 from Kongyu 131 containing a small Gn1a chromosomal fragment which can be inherited stablely and Kongyu 131 were used for field trials; on Apr. 10, 2017 in Jiamusi City, Heilongjiang Province (E130 57, N46 23), single point substitution line BC.sub.4F.sub.2-350A09 containing a small Gn1a chromosomal fragment which can be inherited stablely and Kongyu 131 were used for field trials. The field trial used a completely randomized block design with 3 replicates. Each replicates (plot) contains 8 rows of 12 plants per row, with a plant spacing of 20 cm and a row spacing of 30 cm. The field management is consistent with the local regular rice field.
[0127] In the trait investigation, 10 plants with normal growth were randomly selected in the middle of each plot; every selected plant had to meet the condition that its surrounding 8 plants exhibited normal growth vigor. Plant height (PH), effective tillers per plant (PNP), Panicle length (PL), number of primary branches per panicle (NPB), grain number per panicle (GNP), grain length (GL), grain width (GW), grain thickness (GT), thousand grain weight (TGW), grain weight per plant, grain water content, and yield per plant (YP) when water content is 15%, density of primary branches (DPB), grain density per panicle (GDP), seed setting percentage (SSP), grain length to width ratio (LWR), and actual yield per plot (AYP) were investigated. The method for trait investigation is shown in Table 2.
TABLE-US-00002 TABLE 2 The method for investigation of agronomic traits of parents, improved lines and BC.sub.3F.sub.2 plants Traits Evaluation method Heading period (DTH, day) The number of days from soaking to 50% heading of the plants in the plot Plant height (PH, cm) From the base of the stem to the neck of the highest panicle Effective tillers per plant All the number of tillers with grains (PNP) Panicle length (PL, cm) The length from neck of the highest panicle to the grain on the top (excluding the awn) Number of primary branches Number of all primary branches of the highest panicle per panicle (NPB) Density of primary branches The number of primary branches per panicle divided by (DPB) the panicle length, that is, the number of primary branches per panicle per centimeter Grain number per panicle The number of all grains on the highest panicle, including (GNP) full grain and empty grain Grain density per panicle The grain number per panicle divided by the panicle (GDP,/cm) length, that is, the grain number per panicle per centimeter Seed setting percentage The number of full grains divided by the total grain (SSP) number per panicle multiplied by 100% Yield per plant (YP, g) Harvest all the grains of a single plant and calculate the grain weight when the water content is 15%. Thousand grain weight After taking 500 full grains, weighed and converted to (TGW, g) thousand grain weight Grain length (GL, mm) Calculate the mean after measuring the length of 10 full grains Grain width (GW, mm) Calculate the mean after measuring the width of 10 full grains Grain thickness (GT, mm) Calculate the mean value after measuring the thickness of 10 full grains with a vernier caliper Actual yield per plot (AYP After the plants were harvest, the grain weight of the plot kg) plant was measured and calculated when the water content was 15%.
[0128] 2.1 Improvement of the Gn1a Gene Locus of the Grain Number Per Panicle of Kongyu 131
[0129] 2.1.1 Sequence Comparison of Gn1a Alleles
[0130] Comparison of the Gn1a sequences of Kongyu 131, GKBR, Habataki and Koshihikari showed that the CDS region, 5-UTR and 3-UTR sequences of Gn1a of Kongyu 131 and Koshihikari are identical, while the CDS region, 5-UTR and 3-UTR sequences of Gn1a of GKBR and Habataki are identical, that is, the Gn1a sequence of GKBR has a 16-bp and 6-bp deletion in the 5-UTR and the first exon, respectively, relative to Kongyu 131 and the change of three bases in the first exon and the fourth exon resulted in amino acid variation (
[0131] The black vertical line represents that the three base variations of the coding region result in a change in the encoded amino acid, two black triangles represent 16-bp and 6-bp base deletions, and gray rectangles represent 5-UTR and 3-UTR, white rectangle represents the exon and the horizontal black line represents the intron.
[0132] 2.1.2 Detection of Genotype and Background Recovery Ratio
[0133] 160 SNP markers evenly distributed over 12 chromosomes were used to detect the BC.sub.3F.sub.1 population consisting of 127 lines and the background recovery ratio ranged from 86.3% to 99.5% (
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[0135]
[0136] In the figure, the gray bar represents the chromosome fragment derived from KongYu 131, the black bar represents the chromosome fragment derived from the donor GKBR, and the white column represents that the chromosome fragment type is unknown (the genotype is not determined), the thin black horizontal line represents the position of the SNP marks, and the thick black horizontal line represents the centromere.
[0137] 2.1.3 Description and Statistics of Panicle Phenotypes in the Population of Kongyu 131 and BC.sub.3F.sub.2-LQ96
[0138] A field phenotypic investigation in the Jiamusi rice field in 2015 revealed a significant separation of the panicle size in the BC.sub.3F.sub.2-LQ96 population (
[0139]
[0140] The BC.sub.3F.sub.2-LQ96 population was derived from BC.sub.3F.sub.1-22F01 and consisted of 96 randomly selected selfing progeny plants, and was planted in Jiamusi in 2015 with Kongyu 131. The scale bar in the figure represents 5 cm.
TABLE-US-00003 TABLE 3 Phenotypes of Kongyu 131 and random population BC.sub.3F.sub.2-LQ96 derived from BC.sub.3F.sub.1-22F01 KY131 BC.sub.3F.sub.2-LQ96 population Traits Mean SD Mean SD Range PL (cm) 16.8 0.3 17.4 1.5 14.7~20.1 NPB 12.8 0.4 15.2 1.8 12.0~19.0 DPB (/cm) 0.76 0.02 0.88 0.10 0.73~1.22 GNP 120.4 5.9 172.4 29.0 113.0~235.0 GDP (/cm) 7.16 0.37 9.91 0.20 7.09~13.81
[0141] The correlation coefficients of panicle length, number of primary branches per panicle, density of primary branches, and grain density per panicle are shown in Table 3.1. Except for a certain degree of negative correlation between panicle length and density of primary branches, there was a significant positive correlation between other traits. Among them, the correlation coefficient between grain number per panicle and grain density per panicle was the highest, 0.914. The correlation between the density of density of primary branches and grain number per panicle was the lowest, being 0.355.
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[0143] The black and white arrows in the figure indicate the mean (M1 and M2) of Kongyu 131 and the population, respectively. The phenotypic value of Kongyu 131 is from the mean of 10 Kongyu 131, and the phenotype of BC.sub.3F.sub.2-LQ96 population is the mean of 96 plants within the population.
TABLE-US-00004 TABLE 4 Correlation coefficients between five panicle traits in BC.sub.3F.sub.2-LQ96 population PL NPB DPB GNP NPB 0.598** DPB 0.059 0.763** GNP 0.768** 0.777** 0.355* GDP 0.459** 0.721** 0.533** 0.914** * and ** indicate that the correlation is significant at the level of p < 0.05 and p < 0.01.
[0144] 2.1.5 Genetic Analysis of Genotypes and Phenotypes
[0145] Genetic analysis was carried out in terms of the BC.sub.3F.sub.2-LQ96 population genotype and phenotype, and the results showed that the chromosome fragment located on chromosome 1 simultaneously had significant effects on number of primary branches per panicle (NPB), density of primary branches (DPB), grain number per panicle (GNP), and grain density per panicle (GDP) (
TABLE-US-00005 TABLE 5 QTLs of panicle-related traits detected in BC.sub.3F.sub.2-LQ96 population and their effects Marker Additive Dominant Traits Chr interval effect effect LOD Var. % NPB 1 SNP1~SNP5 2.00 0.50 5.0 39.9% DPB 1 SNP1~SNP5 0.08 0.02 2.2 20.3% GNP 1 SNP1~SNP5 34.95 14.05 5.2 41.1% GDP 1 SNP1~SNP5 1.65 0.74 5.1 40.4%
[0146] The additive effect and the dominant effect and LOD values in the table are all calculated for the effect of SNP3 locus, and Var. % indicates the phenotypic variation rate explained by the QTL.
[0147] Comparison of the phenotypic values of the panicles of Kongyu 131, of three different genotypes (homozygous Kongyu 131, heterozygous and homozygous GKBR) at Gn1a loci and of the control Kongyu 131 found: The average value of number of primary branches per panicle (NPB), density of primary branches (DPB), grain number per panicle (GNP), and grain density per panicle (GDP) of homozygous GKBR and heterozygous plants were significant increased than that of Kongyu 131 and homozygous Kongyu 131 plants. There was no significant difference between homogeneous Kongyu 131 and Kongyu 131. In addition, the phenotypic value of homozygous plants with Gn1a is significantly higher than that of heterozygous plants. (
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[0149] 2.1.6 Recombinant Selection, Background Selection and Evaluation of Selected Plants
[0150] First crossover and selection: to shorten the introgressed target chromosome fragment and to minimize linkage drag, 90 recombinant lines with crossovers between SNP1 and SNP5 were selected from 960 BC.sub.3F.sub.2 plants derived from BC.sub.3F.sub.1-22F01. Then, the markers heterozygous for BC.sub.3F.sub.1-22F01 and 60 newly added markers located in the large interval without markers on chromosome were used to detect the 90 recombinant plants, from which a plant named BC.sub.3F.sub.2-2B09 containing to the Gn1a chromosome fragment, and with crossovers between SNP1 and SNP2 upstream of Gn1a and containing the minimum non-target chromosome fragment, was selected (
[0151] The second crossover and selection: to shorten the length of the introgressed target chromosome fragment, 20 plants with crossovers between SNP4 and SNP5 were selected according to the genotype of SNP4 and SNP 5 from 1240 plants in BC.sub.3F.sub.3 population derived from BC.sub.3F.sub.2-2B09 selfing. Then, the markers heterozygous for BC.sub.3F.sub.2-2B09 were used to detect the 20 recombinant plants, from which a line named BC.sub.3F.sub.3-652E09 containing the Gn1a chromosome fragment and the minimum non-target chromosome fragments (
[0152] In addition, in the progeny BC.sub.3F.sub.3 population derived from BC.sub.3F.sub.2-2B09 self-crossing, BC3F3-624A05 was selected according to the genotype of 220 SNP markers (
[0153] Purification and fixation of selected plants: in order to further exclude non-target chromosomal fragments on chromosomes 1 and 4 and obtain a new Kongyu 131 genome containing only a small chromosome fragment of homozygous Gn1a, BC.sub.3F.sub.3-652E09 obtained from the second crossover and selection was backcrossed with Kongyu 131, and the BC.sub.4F.sub.1-255A01 plant was selected among the progeny, and then BC.sub.4F.sub.1-255A01 was self-crossed to obtain 288 progenies from which 3 homozygous BC.sub.4F.sub.2-350A09 plants containing only small target chromosome fragment were selected. The background recovery ratio was 99.89%.
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[0155] (a) BC.sub.3F.sub.2-2B09; (b) BC.sub.3F.sub.3-652E09; (c) BC.sub.3F.sub.3-624A05; (d) BC.sub.4F.sub.2-350A09. In the figure, the gray bar represents the chromosome fragment derived from KongYu 131, the black bar represents the chromosome fragment derived from the donor GKBR, and the white column represents that the chromosome fragment type is unknown (the genotype is not determined), the thin black horizontal line represents the position of the SNP marks, and the thick black horizontal line represents the centromere.
[0156] 2.1.7 Comparison of Agronomic Traits Between Kongyu 131 and its Improved Lines
[0157] In 2016, Jiamusi, the field performance of Kongyu 131 and its improved line BC.sub.3F.sub.3-624A05 in the filling and maturity stages are shown in
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[0159] 2.1.7.1 the Improved Line is Cultivated in Jiamusi, and there is No Significant Difference in Heading Stage.
[0160] In the field trials in 2016 and 2017, seeds were soaked on April 10, and the heading days of the improved lines BC.sub.3F.sub.3-624A05, BC.sub.4F.sub.2-350A09 and Kongyu 131 was not significantly different in Jiamusi, all of which were 103 days; however, in Changchun, the heading date of the improved line is 4 days later than Kongyu 131, and it is speculated that this difference may be affected by the environment, such as the water temperature of irrigation and the influence of fertilizer.
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[0162] 2.1.7.2 the Plant Height of the Improved Line B C.sub.3F.sub.3-624A05 Increased, and the Plant Height of BC.sub.4F.sub.2-350A09 Showed No Significant Difference.
[0163] The plant height of the improved line BC.sub.3F.sub.3-624A05 was increased by 4 cm and 5.4 cm relative to Kongyu 131 in the two test sites of Changchun and Jiamusi respectively, and it is speculated that there are three reasons for this difference in plant height: first, the multi-effect of Gn1a itself; second, the role of other loci near Gn1a; third, possibly the undetected donor chromosome fragments on the genetic background of the improved line. Further field trials of single point substitution line BC.sub.4F.sub.2-350A09 showed that the plant height of BC.sub.4F.sub.2-350A09 was not significantly different from that of Kongyu 131, thus eliminating the plant height increase of improved line BC.sub.3F.sub.3-624A05 due to multi-effect of Gn1a.
[0164] 2.1.7.3 the Yield Traits of the Improved Line, Such as the Number of Branches and the Grain Number Per Panicle, Increased Significantly
[0165] The number of primary branches per panicle (NPB), density of primary branches (DPB), grain number per panicle (GNP) and grain density per panicle (GDP) of the improved lines BC.sub.3F.sub.3-624A05 and BC.sub.4F.sub.2-350A09 were significantly increased in the three different environments than Kongyu 131. Although the panicle length (PL) increased but did not reach a significant level, indicating that the increase of the yield per plant of the improved line was mainly caused by that the number of primary branches per panicle and the grain number per panicle increased so that the density of the grains increased.
[0166] 2.1.7.4 the Thousand Grain Weight Drop of the Improved Line
[0167] At the two test sites in Changchun and Jiamusi, the thousand grain weight (TGW) of the improved line BC.sub.3F.sub.3-624A05 was reduced by 1.3 g and 2.0 g, respectively. The thousand grain weight (TGW) of the improved line BC.sub.4F.sub.2-350A09 was also reduced by 0.8 g compared to the Kongyu 131. Further analysis found that compared with Kongyu 131, the grain length (GL), grain width (GW) and grain thickness (GT) of BC.sub.3F.sub.3-624A05 and BC.sub.4F.sub.2-350A09 were slightly smaller than that of the control Kongyu 131 in three environments, which was consistent with the drop of thousand grain weight of the improved line BC.sub.3F.sub.3-624A05 and the single point substitution line BC.sub.4F.sub.2-350A09 compared to the control Kongyu 131.
[0168] 2.1.7.5 the Yield Per Plant of the Improved Line is Significantly Increased
[0169] In Changchun in 2016, the yield per plant (YP) of the improved line BC.sub.3F.sub.3-624A05 was 4.7 g higher than that of Kongyu 131, an increase of 8.3%; in Jiamusi in 2016, the yield per plant (YP) of the improved line BC.sub.3F.sub.3-624A05 was increased by 6.9 g in Jiamusi, an increase of 11.9%. The actual yield per plot (AYP) of the improved line BC.sub.3F.sub.3-624A05 at two plots increased by 7.8% and 10.1%, respectively, compared with the control Kongyu 131. Compared with Jiamusi, the increase in yield per plant (YP) of the improved line in Changchun was less likely due to less increase in grain number per panicle (GNP) and lower seed setting percentage (SSP) than Kongyu 131. However, the increase in the grain number per panicle (GNP) in the improved line in Changchun was less than that in Jiamusi, which may be due to about 10 days shorter of the heading date of the improved line in Changchun. In 2017, in Jiamusi, the yield per plant (YP) of the improved line BC.sub.4F.sub.2-350A09 increased by 3.5 g, an increase of 6.6%. The increment in yield per plant (YP) was lower than that of BC.sub.3F.sub.3-624A05 in 2016 was likely due to a decrease in the increment.
[0170] 2.1.8 there is No Significant Difference in Quality Traits Between the Improved Line and the Kongyu 131
[0171] The appearance quality and the amylose content and alkali spreading value in cooking quality of milled rice from the improved line and the control Kongyu 131 are shown in
[0172]
TABLE-US-00006 TABLE 6 Comparison of agronomic traits of Kongyu 131 and its improved lines BC.sub.3F.sub.3-624A05 and BC.sub.4F.sub.2-350A09 2016 Changchun (E12518, N4443) 2016 Jiamusi (E13057, N4623) 2017 Jiamusi (E13057, N4623) Traits KY131 BC.sub.3F.sub.3-624A05 KY131 BC.sub.3F.sub.3-624A05 KY131 BC.sub.4F.sub.2-350A09 DTH 93.2 0.8 97.2 1.5** 103.6 0.8 103.1 0.7 103.3 1.4 102.8 2.2 PH (cm) 70.7 2.2 74.7 1.1** 70.6 1.8 76.0 3.1** 64.0 3.5 62.1 2.3 ETP 27.3 3.3 27.1 3.1 31.5 3.6 31.4 2.4 34.7 3.5 35.1 3.5 PL (cm) 16.6 0.5 17.4 0.5 16.5 0.9 17.2 0.4 16.1 0.6 16.1 0.4 NPB 11.8 0.6 14.7 0.6** 12.2 1.0 14.9 0.5** 10.2 0.9 12.6 0.8** DPB (/cm) 0.71 0.04 0.85 0.06** 0.75 0.09 0.86 0.02** 0.63 0.05 0.78 0.05** GNP 119.3 8.0 168.1 2.6** 123.4 8.3 186.2 17.8** 116.3 8.1 136.6 7.5** GDP (/cm) 7.18 0.45 9.79 0.11** 7.50 0.38 10.69 0.79** 7.2 0.4 8.5 0.5** SSP (%) 97.0 1.7 93.8 1.9** 98.0 0.3 97.4 0.6 95.5 1.6 94.8 2.0 YP (g) 56.4 1.1 61.1 1.6** 57.8 1.1 64.7 1.8** 53.0 2.3 56.5 2.0** TGW (g) 27.6 0.6 26.3 0.6** 27.8 0.5 25.8 0.3** 27.2 0.6 26.4 0.7* GL (mm) 7.55 0.08 7.52 0.03 7.48 0.11 7.36 0.10 7.50 0.08 7.46 0.10 GW (mm) 3.69 0.03 3.61 0.06 3.64 0.06 3.54 0.03 3.73 0.03 3.71 0.04 GT (mm) 2.33 0.00 2.28 0.04** 2.33 0.02 2.30 0.01* 2.34 0.03 2.31 0.02* AYP (Kg) 4.38 0.21 4.72 0.26** 4.55 0.25 5.01 0.35** The values in the table are mean standard deviation, and the phenotypic values of Kongyu 131, BC.sub.3F.sub.3-624A05 and BC.sub.4F.sub.2-350A09 are derived from the mean of 30 phenotypic values. The planting density is 30 cm 20 cm, with one plant per hole during cultivation. The actual yield per plot (AYP) is derived from the mean of 10 plots, and the area of a single plot is 5.76 m.sup.2 (2.4 m 2.4 m). *and **indicate significant differences at p 0.05 and p 0.01 according to the T test.
[0173]
EXAMPLE 2
[0174] Improving Kongyu 131 by Updating the Grain Length Locus GS3 to Increase the Yield of Kongyu 131
[0175] The world's population continues to increase, and it is a great challenge to enhance the production of crops to supply the increasing demand continuously. Although traditional breeding methods have made a great contribution to solving human needs for food, these methods have problems such as large workload, unpredictability, and non-repetition. The present disclosure accurately updates GS3 locus of Kongyu 131 through the method of genome upgrading, and overcomes the problems of large workload, unpredictability, and non-repeatable in the traditional breeding methods. We use this method to improve the grain length locus GS3 of Kongyu 131. Single nucleotide polymorphism (SNP) marker primers between Kongyu 131 and donor BR were designed by genomic resequencing of Kongyu 131 and the donor BR; 219 pairs of markers were selected using high resolution dissolution curve analysis (HRM) to screen the designed primers, and then selection was carried out against the whole genome; At the same time, SNP1-SNP5 were designed based on the sequence polymorphism between the two parents at the upstream and downstream of the GS3 locus to select target locus GS3 and minimize linkage drag. We started from BC3F1 and selected a plant, named improved line, in which segment of GS3 locus with a length less than 117 kb is from donor BR and the background recovery ratio was 99.55%. The field cultivation trials in Jiamusi showed that after improvement, the improved line with grain length locus GS3 was significantly increased in grain length and hundred grain weight compared with Kongyu 131, and the yield was also greatly increased. This proves that this is an effective breeding method and is expected to become one of the main methods for future breeding and will play an important role in solving the food problem.
[0176] Keywords: Kongyu 131, GS3, SNP, HRM
Introduction
[0177] As the world's population continues to increase, the total food demand is growing. However, how to continuously and effectively increase food production is a severe challenge. On the one hand, the arable land is decreasing with the development of urbanization; on the other hand, the production of crop is influenced inevitably by some environment factors such as global warming (Takeda and Matsuoka 2008). In the past few decades, global food production has increased significantly twice. One is the application of semi-dwarf genes in wheat and rice, namely the green revolution (A. Sasaki et al. 2002; Jinrong Peng et al. 1999; Spielmeyer et al. 2002); the other one is the cultivation and production of hybrid rice in China and Southeast Asian countries in the 1970s (Shi-Hua Cheng and Ye-Yang Fan 2007). However, studies have shown that food production has increased slowly in some areas in recent years, and even some areas have reduced food production (Ray et al. 2012). Therefore, how to continuously and effectively increase food production to meet increasing demand is an urgent problem to be solved in the future. In the case of a gradual decrease in the area of arable land, increasing the yield per unit area by improving crops is an effective way.
[0178] The traditional way of improving crops, that is, traditional breeding, relies on the experience of breeders to select plants that are considered to be good in the field, and then carry out continuous field screening, and finally obtain good plants and cultivate same as new varieties. However, this method of using experience to select in the field has disadvantages such as unpredictable, non-repeatable and large workload.
[0179] With the discovery and utilization of molecular markers, breeders can use molecular markers that are closely linked to good traits to aid in the selection of plants, i.e., molecular markers-assisted selection (MAS (Knapp 1998)). Molecular markers-assisted selection has indeed brought great convenience to breeders, not only reducing a large amount of field selection work, but also improving the accuracy of selecting target plants. However, the MAS markers commonly used by breeders are only closely linked to the target traits, which inevitably lead to the inconsistency between the selected plants and the expectation, i.e., there are crossovers between the target traits and the markers (Andersen and Lubberstedt 2003). Similarly, this method only focuses on the selection of target traits, without considering the information elsewhere in the genome, so whenever there is a problem with the bred varieties, the cause cannot be found. Therefore, this breeding method still has problems such as poor predictability and poor repeatability.
[0180] At present, the rapid development of genome sequencing, the discovery of a large number of functional genes and the in-depth study of gene regulation mechanisms (Huang et al. 2013; James et al. 2003; Miura et al. 2011; Sakamoto and Matsuoka 2008; Wang and Li 2008, 2011; Xing and Zhang 2010; Zhou et al. 2013; Zuo and Li 2013), provide breeders with a wealth of information available, to some extent allowing breeders to design breeding according to their breeding goals. In 2003, two Israeli scientists proposed the concept of design breeding (Peleman and van der Voort 2003). Future breeders are expected to use the existing genome sequencing information, functional gene information and large amount of other research results, combine genomic information according to different breeding goals, and cultivate crop varieties with high yield, high quality, stress resistance and other good traits to provide a powerful approach for solving food issues.
[0181] This research is based on the rapid development of genomic information, the extensive discovery and research of functional genes, and the extensive use of digital information and is for solving the problems in traditional breeding methods such as large workload in the field, long breeding period, unpredictable and non-predictable breeding results, this study proposes a method of upgrading breeding, which has the following features compares with traditional breeding methods: (1) The method can complete almost all the selection work in the laboratory, that is, the selection work is mainly done indoors by SNP genotype analysis, does not require a large number of field screening, which greatly reduces the workload of field selection; (2) The method can accurately select the cause genes of the target traits, can predict the breeding results, that is, has high predictability; (3) This method can not only select the cause genes of the target traits, but also can select against the whole genome. When there is a problem with the bred varieties, the cause of the problem can be immediately found, that is, it has stability and repeatability.
[0182] Rice is a major food crop, with more than half of the world's population taking rice as main food. At the same time, rice is a monocotyledonous model plant because rice which has a small genome and complete genomic information and a large number of available resources. It is generally believed that the yield per plant of rice depends on the panicle number per plant, grain number per panicle, grain weight and filling (Sakamoto and Matsuoka 2008; Xing and Zhang 2010). Grain weight is one of the key factors in rice production, so increasing grain weight by improving crops is one of the most effective ways to increase yield. In the past few decades, a large number of functional genes related to rice yield have been discovered and studied (Huang et al. 2013; Miura et al. 2011; Wang and Li 2011; Xing and Zhang 2010; Zuo and Li 2013), GS3 is the first grain type gene found in rice (Fan et al. 2006; Mao et al. 2010).
[0183] Therefore, in this study, the grain length of the main rice variety Kongyu 131 was improved. Through the genome sequencing information of donor BR and Kongyu 131, SNP markers covering the whole genome were designed, and SNP1-SNP5 were designed was designed for the GS3 locus to select target genes. Continuous selection was started from BC3F1 and a plant, named improved line, in which segment of target GS3 locus with a length less than 117 kb was from donor BR and the background recovery ratio was 99.55% Through the field cultivation in Jiamusi in the summer of 2016, the investigation of agronomic traits of the improved line and Kongyu 131 found that the grain length and hundred grain weight of the improved line were significantly improved, and the yield was also greatly improved. Therefore, this method is very effective in improving the GS3 locus of Kongyu 131, and has achieved the expected goal, which proves that the method is controllable, predictable, repeatable, and the workload is greatly reduced. Our trial results show that this method is a very effective breeding method and provides a new breakthrough for future breeding methods.
[0184] Materials and Methods
[0185] Parent and Material Construction
[0186] In this experiment, the short-grained japonica rice variety Kongyu 131 was used as the recurrent parent. This variety was once the main plant variety in Heilongjiang Province, and it has the characteristics of early maturity, high yield and low temperature tolerance. The donor BR is a long-grained indica variety. We used Kongyu 131 as the background, crossed with donor BR to obtain F1, and then backcrossed with Kongyu 131 three times to obtain a BC3F1 polulation containing a total of 137 lines. Starting from BC3F1, the target plants were selected by molecular markers analysis, and the target plants were continuously self-crossed to obtain the final improved line BC3F4.
TABLE-US-00007 TABLE 7 Phenotype of Kongyu 131 and improved line BC3F4 2016 2017 Traits BC3F4-4 KY 131 BC3F4-4 KY 131 GL (mm) 7.73 0.14* 6.90 0.11 7.90 0.13* 6.94 0.09 GW (mm) 3.59 0.08 3.53 0.05 3.47 0.11 3.44 0.03 HGW (g) 3.08 0.04* 2.65 0.05 2.98 0.05* 2.73 0.06 TYP (g).sup.a 50.27 4.81 48.11 7.7 48.82 6.45 48.39 5.87 TYP (g).sup.b 55.96 11.16* 40.82 4.31 TYP (g).sup.c 48.52 8.26 48.06 3.79 PNP 27.4 2.87* 31.3 3.16 24.13 1.73* 34 3.38 GNP 125.8 10.51 116.8 23.5 126.5 14.13 116.38 8.42 PH (cm) 72.2 2.82 71.45 1.06 72.63 0.58* 67.60 1.75 PL (cm) 17.7 1.22 17.58 1.74 16.28 1.35 16.06 0.63 DTH 107.25 2.06 107.25 2.63 102.50 1.64 102.83 2.14
[0187] Data presented as the means with standard deviations were obtained from plants in a randomized complete block design with three replications under natural conditions at Jiamusi in 2016 and 2017. The planting density was 30 cm20 cm and one plant per hill GL Grain length, GW Grain width, HGW Hundred grain weight, TYP Total grain yield per plant, PNP panicle number per plant, GNP grain number of main panicle, PH plant height, PL main panicle length, DTH Days to heading * represents significance at p0.05 based on Student's t-tests, n=10 a The planting density was 30 cm20 cm and one plant per hill b The planting density is 30 cm20 cm and three to four plants per hill c The planting density is 30 cm14 cm and three to four plants per hill; indicates no data
[0188] Resequencing of Parent and Sequence Alignment of GS3 Locus Gene
[0189] We used the HiSeq2000 sequencer to re-sequence the genome of Kongyu 131 and obtained the SNP information between the Kongyu 131 and BR. The GS3 gene sequence was downloaded from the NCBI database, and the GS3 gene sequence was aligned and analyzed by DNAMAN between the Kongyu 131 and BR.
[0190] SNP marker design and genotyping Using the SNP information between Kongyu 131 and BR obtained by resequencing, we designed SNP marker primers covering the whole genome, and selected 219 pairs of markers with polymorphism between the Kongyu 131 and the BR for genome-wide selection. According to the difference of GS3 gene and upstream and downstream sequences between Kongyu 131 and BR, five polymorphic SNP markers were designed and screened: SNP1-SNP5, in which SNP1 and SNP2 were located upstream of GS3 gene, and SNP4 and SNP5 were located downstream of GS3 and were mainly used to minimize linkage drag with GS3 gene; SNP3 was located in the GS3 gene, for the selection of target genes. Polymorphism verification analysis of SNP marker primers was performed using the HRM analysis method (Wittwer 2009).
TABLE-US-00008 TABLE8 5SNPmarkersforselectionoftargetgenes Markers Chr. Position Forwardprimer Reverseprimer SNP1 3 16,854,214 TGGTACACAGCATATCATGGAAC CAGAAGTGTTATAACTACATATTTGC SNP2 3 17,296,672 ATCTGCAACAAACAAGAGGATC CTTGAGTTTCCACTCACAAACTTTTC SNP3 3 17,369,402 GAAACAGCTGGCTGGCTTACTCTC GATCCACGCAGCCTCCAGATGC SNP4 3 17,413,766 TTAGGACATATCGGCGTGCGTTTA CAGAGAAGCATCATTGAACGAACA SNP5 3 17,874,647 ATGCAACCTTTTCTCCCTTCCTAT TCTAAAGGTTAACTCAGTAAAATCCT
[0191] Selection of Target Plant (Improved Line)
[0192] In order to obtain plants with GS3 locus from donor BR and other loci in the genome from Kongyu 131, we first select plants with SNP3 as H-type, crossovers between SNP1 and SNP5 as much as possible, and high background recovery ratio in BC3F1. And then in the self-crossed progenies of the plants, target plants were selected through the following two consecutive selections:
[0193] First selection: in about 1,000 progenies (BC3F2) from self-crossing of the plant, plants with crossovers between the GS3 gene (SNP3) and the upstream marker SNP1 and SNP2 or and the downstream marker SNP4 and SNP5 were selected;
[0194] Second selection: in about 1,000 progenies (BC3F3) from self-crossing of the selected plant of the first selection, the plants with crossovers between the GS3 gene (SNP3) and the molecular markers (SNP1, SNP2 or SNP4, SNP5) on the other end were selected;
[0195] Thus the plants with crossovers between the GS3 gene (SNP3) and both the upstream (SNP1 or SNP2) and downstream (SNP4 or SNP5) were selected and self-crossed to select a plant (BC3F4) with homozygous GS3 locus from the donor BR and with the highest background recovery ratio.
[0196] Field Cultivation and Traits Investigation
[0197] In Jiamusi, the target plant (improved line) and Kongyu 131 was cultivated in a plot in a manner of 8*12, and managed according to the general rice cultivation method. After maturity, the traits of grain length, grain width, plant height, panicle length, number of primary branches per panicle, and hundred grain weight were investigated, and the total grain weight per plant was measured.
[0198] In addition, in order to compare the yield difference between the improved line and the Kongyu 131 in the field cultivation, we cultivated the primary improved line with the grain length locs improved and Kongyu 131 in the Jiamusi field according to the normal rice cultivation method, with each 1 mu, and the yield was measured. The primary improved line mentioned here is an improved line that the target locus GS3 has been improved, but the other loci in the genome are not completely from Kongyu 131. We measure the yield of 10 selected plants, and the selection method of the plants is based on the survival of all 8 plants around the plants to be selected, so as to ensure that the growth of the measured plants is affected by the surrounding environment as little as possible, and the measurement error is minimized.
[0199] Results
[0200] Kongyu 131 and BR have only one base variation in the coding region of GS3 gene, and GS3 gene was mapped between SNP1-SNP5.
[0201] Sequence alignment analysis revealed that Kongyu 131 and BR were different in the 2233th base of the second exon of GS3 gene, and the base of Kongyu 131 was C at this position, and the base of BR was A at this position (
[0202]
[0203] The GS3 Locus Fragment in the Improved Line is from the BR and is about 117 kb, and the Background Recovery Ratio is 99.55%.
[0204] In order to select the plants with smallest fragment of GS3 locus from the donor BR, first, we selected 25 plants with H-type at the SNP3 locus among 137 plants in the BC3F1 population, 8 of which had crossovers between SNP1 and SNP3 or SNP3 and SNP5. And we selected one plant from the 8 plants with the highest background recovery ratio as the candidate plant for further selection. The plant was named as BC3F1-1 (
[0205]
[0206] QTL Analysis Confirmed that GS3 Allele Derived from Donor BR could Indeed Improve the Grain Length of Kongyu 131
[0207] In order to confirm that the GS3 gene from donor BR can improve the grain length of Kongyu 131, Kongyu 131 was used as the background, crossed with donor BR and self-crossed to obtain F2 population and BC3F2 population in which traits such as grain length were measured. The relationship between grain length and markers was analyzed by genotype analysis using Mapmaker/QTL 1.1b. A grain length locus (
[0208]
[0209] The Grain Length and Hundred Grain Weight of the Improved Line increased significantly.
[0210] In May 2016, we cultivated 96 plants from the selected improved line BC3F4-4 and Kongyu 131, respectively, in Jiamusi according to the 8*12 cultivation method at the same time. After maturity, the traits such as grain length, grain width, hundred grain weight, plant height, main panicle length, number of primary branches per panicle, and total grain weight per plant were investigated. Compared with Kongyu 131, the grain length and hundred grain weight of the improved line BC3F4-4 were increased significantly (
[0211]
[0212] Significant Increase in Total Grain Weight Per Plant in Primary Improved Line
[0213] We selected 10 plants from Kongyu 131 and primary improved line cultivated in Jiamusi, respectively, for measuring the traits such as grain length and total grain weight per plant. It was found that the grain length and the total grain weight per plant of the primary improved line were significantly increased (
[0214]
Discussion
[0215] We improved the grain length locus GS3 of Kongyu 131, and found that the grain length of the improved line was significantly increased by the field cultivation of the improved line. Therefore, this method is effective in the grain type improvement of Kongyu 131. And controllable and predictable improvement of target traits can be achieved completely by this method, Our process and results of improving the grain length locus GS3 of Kongyu 131 demonstrate that this method overcomes the shortcomings of large workload for field selection, unpredictable and non-repeatable results in traditional breeding. This method selects plants almost entirely indoors using SNP gene analysis, thus greatly reducing field workload. At the same time, the method uses the markers inside the gene to select the target traits, so there is no fear of loss of the target traits, and the selection process is precise and controllable. Furthermore, in addition to the selection of target traits, the method also selects other loci in the whole genome, which avoids the influence of other loci on the target traits, and does not change other good traits of the background variety. More importantly, when problems are found in the improved variety, the cause can be found in time and the same method can be used for improvement. Therefore, this breeding method is a very effective, precise and controllable breeding method, which is expected to play an important role in solving food security problems in the future.
[0216] Although the effect of improvement on the grain length of Kongyu 131 is very significant, it is based on the clear and thorough study of GS3 gene function and the reliable utilization of rice genome information. At the same time, we can see that there are some differences in the investigation results from the cultivation of the GS3 locus improved line and the cultivation of the primary improved line.
[0217] First, we compared the improved BC4F4-4 with Kongyu 131 cultivated in Jiamusi and found that the grain length and hundred grain weight were significantly increased, and the total grain weight per plant was increased but not significant. Among all the traits we investigated, it was found that the number of primary branches per panicle of the main panicle of the improved line was increased significantly, but the panicle number was decreased significantly. This explains to some extent the improved plant had no significant increase in the total grain weight per plant when the hundred grain weight was increased significantly. But we are still not completely sure what causes the number of primary branches per panicle of the main panicle of the improved line to increase significantly, and the panicle number to decreased significantly. We speculate that it may be related to the role of GS3, or it may be related to other loci in the genome, or it may be due to the effect of the cultivation environment. Therefore, we will further carry out cultivation trials on the improved lines to confirm the effects of GS3 on the traits of the improved lines.
[0218] Secondly, we compared the primary improved line with Kongyu 131 cultivated in Jiamusi and found that the the grain length and total grain weight per plant were increased significantly, at the same time found that the plant height was also increased by 10 cm on average, and the heading date was about 10 days later. We found through QTL analysis that the primary improved line contained a locus located on chromosome 1 that affected the heading date. We know that the growth period is one of the important factors affecting yield. Generally, the varieties with longer growth period will have higher yield, which explains why the total grain weight per plant of the primary improved line was significantly increased but the total grain weight per plant of the improved line was not increased significantly. We are performing further QTL analysis and verification of the lous affecting the heading date of the primary improved line. In the next step, we will simultaneously improve and aggregate the lous and the GS3 locus. According to the library-source relationship theory (Wang 2008), by simultaneously aggregating the late heading locus and the GS3 locus, this not only improves the grain length of Kongyu 131 (increased the library), but also provides sufficient source for the increased library.
[0219] Based on the above trials and analysis, we believe that to improve the variety by using upgrade design breeding, the following points must be met: 1. Reliable and accurate genomic information; 2. Large-scale discovery and functional study of functional genes; 3. Accurate and efficient information management.
[0220] With the development of genome sequencing, the genomes of many species have been sequenced and assembled, so the widespread use of genomic information has greatly facilitated the use of this method. However, at the same time, we have seen that in order to accurately select the genome, the accuracy of the genomic information has room for further improvement. In addition, the extensive discovery of functional genes and in-depth research on their regulatory networks has also greatly facilitated the use of this method. Only when the cause gene locus of the target trait is confirmed and the gene function are clearly defined, can the method be effectively used to improve varieties, so the discovery and functional research of genes need to be further broadened and deepened. At present, in the case of clear gene location, QTL analysis can be used initially to verify the loci affecting traits. Finally, the efficient management of large amounts of genomic information and functional gene information is critical, which guarantees the reliability of information utilization. Therefore, only by satisfying the above points can the method be better used to improve varieties.
[0221] We believe that with the further development of genome sequencing, the cost of genome sequencing will be lower and lower, and the accuracy of genome sequencing information will be greatly improved. Then through the exploration of a large number of genes and in-depth study of functions, the use of these information will provide greater convenience for the application of upgrade design breeding in the future. And this method will be more widely used in improving crops, which will be more helpful in solving food problems.
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