1816 results about "Phenotype" patented technology

The invention relates to the technical field of data decision, in particular to an analysis decision method for crop growth monitoring data. The method comprises the following steps: collecting crop phenotypic characteristic data through a multi-source sensing array; dynamically dividing crop growth response stages according to phenotypic characteristics; constructing a growth situation prediction model based on the crop growth response stage; inputting the phenotypic characteristic data into a growth situation prediction model, simulating a crop growth process through a digital twin engine, and generating growth situation evolution data; extracting physiological anomaly characteristics of the growth situation evolution data, and generating stress response signals; obtaining a canopy three-dimensional phenotype map based on the stress response signal; positioning vascular bundle nodes of the canopy three-dimensional phenotype map through morphological topology analysis; according to the invention, through multi-source data acquisition, dynamic growth stage division, accurate model prediction, three-dimensional phenotype monitoring and self-correction decision optimization, the accuracy of analysis decision for crop growth monitoring data is improved.

The invention discloses a pennisetum purpureum gene PpbHLH148L and application thereof in improving the cold resistance of plants, and relates to the technical field of gene engineering. The nucleotide sequence of the gene is as shown in SEQ ID NO.5. After the gene is subjected to subcellular localization and expression condition analysis after cold stress, the gene is related to low-temperature tolerance. An overexpression vector of the gene is constructed, Agrobacterium tumefaciens is transferred, then Arabidopsis thaliana infection is carried out, cold tolerance determination is carried out on overexpressed Arabidopsis thaliana, phenotypic difference and physiological index difference between an overexpressed strain after cold treatment and a wild type are observed, and it is found that the gene can significantly improve the low-temperature stress tolerance of Arabidopsis thaliana. And in the low-temperature treatment of the pennisetum alopecuroides transgenic callus, the transgenic callus also shows higher tolerance than the wild callus at low temperature. The pennisetum purpureum gene PpbHLH148L can be used for low-temperature tolerance modification of plants, and has an application prospect in creation of low-temperature-resistant plant materials.

The invention provides a germination form measurement method and system based on improved U-Net to realize automatic measurement, reduce labor cost and significantly improve efficiency, thereby optimizing tomato planting and management. According to the application, the seed germination form acquisition system is used for acquiring images of seed culture and seed germination processes, a data set is constructed, and the data set is used for training the improved U-Net model. According to the invention, the up-sampling of the model is replaced by the DBB module, and the CAA is introduced into the jump joint and the decoder. The MIOU index and the MPA index of the model can be respectively improved by 2.03% and 0.39% compared with those of the basic U-Net. According to the method, based on the segmentation result of the improved model, the radicle length can be extracted in combination with the canny algorithm. Compared with the ImageJ measurement result, the correlation coefficient of the model can reach 0.991, and the measurement efficiency is improved by 300 times. According to the method, the influence of drought, salinization and different molds on tomato radicle germination can be evaluated, and an efficient solution is provided for nondestructive monitoring and crop management in precision agriculture.

The invention belongs to the technical field of agricultural information, and discloses a rape variety environmental adaptability evaluation system based on machine learning. The system is composed of a data acquisition standardization unit, a regional environment feature modeling unit, a variety phenotype and pedigree association unit, a feature screening and model training unit, a regional adaptability scoring and decision-making unit, a dynamic learning and evolution updating unit and an evaluation visualization and variety recommendation unit. By performing standardization processing on multi-source data, format and dimension differences are eliminated, and a high-quality data foundation is laid for subsequent analysis. Fusing environment and variety bilateral characteristics, and enabling the model to capture environment influence and variety heredity characteristics at the same time. Advanced methods such as ensemble learning and a time sequence neural network are adopted, and the complex relation is accurately mined. Compared with a traditional field test and the prior art, errors are greatly reduced, the adaptation degree of the variety in different areas is more accurately judged, a scientific basis is provided for planting recommendation, and the yield and quality of the oilseed rape are improved.

Systems and methods for predicting a medical trait in an individual are provided. The techniques include obtaining genomic data including information indicative of genetic variants present in a genome of the individual and calculating, using an at least one processor and a trained computational model, a trait score based on the information indicative of the genetic variants, wherein the trained computational model was obtained by training a first computational model using data describing phenotypes, genotypes, and / or phenotype-genotype relationships for a population including admixed individuals of multiple ancestries. The trait score may be used to alter a course of medical treatment of the individual and / or to implement a clinical trial.

Embodiments are directed to a method for determining relationships between genes, phenotypes, and diseases that includes extracting a first set of biological data containing gene data, phenotype data, and disease data from a database, extracting a second set of biological data from a database, creating nodes on a network pertaining to each individual gene, phenotype, and disease data extracted from one of a database and documents, training multiple machine learning (ML) algorithms on a set of extracted data with matching empirical results, using at least one of the ML algorithms and the second set of biological data for determining relationships between the nodes, creating at least one of a gene-disease association score, gene-phenotype association score, and disease-phenotype association score for the relationships based on the relative association of the nodes, and displaying at least one of the association scores to a user.

The invention relates to the technical field of bioinformatics, and provides a crop whole genome phenotype prediction method and system fused with an environmental indicator gene, and the method comprises the following steps: collecting re-sequencing data, and carrying out genome comparison to obtain variation site data; performing whole genome association analysis by using the variation site data to obtain phenotype association site information; carrying out gene expression quantity measurement on samples of the crop population material in different environments to obtain gene expression quantity data; performing differential expression analysis on the gene expression quantity data to screen environmental indicator genes to obtain an environmental indicator gene set; constructing a phenotype prediction model of double-branch fusion; and predicting a to-be-predicted material through the phenotype prediction model to obtain phenotype prediction results for different environments. According to the method, environmental factors are incorporated into the whole genome selection model, so that the phenotype prediction precision in different environments is improved.

The present invention relates to the technical field of molecular markers for maize resistance to stalk rot and genetic breeding, and in particular, to a QTL related to maize resistance to stalk rot, SNP molecular markers closely linked with the QTL, and a use of the SNP molecular markers. Provided is a QTL related to maize resistance to stalk rot, wherein the QTL is located on maize chromosome 10. Also provided are SNP molecular markers Ks4 and Ks6 closely linked with a QTL site for maize resistance to stalk rot. By detecting the SNP molecular markers, the genotype of a maize material under test can be accurately identified in a high-throughput manner, a material resistant to stalk rot is selected, and phenotype identification and assisted screening of the maize resistance to stalk rot can also be carried out in a seedling stage, thus significantly reducing production cost and significantly enhancing the efficiency of breeding maize resistant to stalk rot.

The invention belongs to the technical field of crop genetic breeding, and relates to a linked molecular marker of a peanut hypocotyl elongation related gene locus, an identification method and application of the linked molecular marker. The primer pair is C2-15-F / R, and the sequence of the primer pair is as shown in SEQ ID NO. 1 and SEQ ID NO. 2; by designing an InDel marker C2-15, the peanut hypocotyl length character can be quickly distinguished by using a primer to amplify a target band and using polyacrylamide gel electrophoresis detection. The identification method is more accurate and convenient, has good repeatability, can efficiently distinguish the phenotype and genotype of an individual, shortens the experiment process, has the advantages of simple and feasible operation steps and the like, and saves expenditure. The method disclosed by the invention has important application value in the breeding work aspects such as peanut hypocotyl elongation character related gene positioning, genotype typing and later cultivation of excellent peanut varieties.

The invention relates to the technical field of Chinese trumpet creeper breeding, and discloses a Chinese trumpet creeper-based efficient breeding decision support system and method. The method comprises the following steps: acquiring multi-dimensional phenotypic data in a Chinese trumpet creeper breeding test, wherein the multi-dimensional phenotypic data comprises plant height, leaf area, flowering period and yield indexes; performing normalization processing on the multi-dimensional phenotypic data, eliminating influences of different dimensions, and calculating a variable coefficient of each phenotypic index; then screening out phenotypic indexes of which the stability is higher than a preset threshold value based on the variable coefficient, and constructing a Chinese trumpet creeper phenotypic feature matrix; carrying out dimensionality reduction on the Chinese trumpet creeper phenotypic feature matrix by adopting an adaptive weighting algorithm, and extracting key phenotypic features; inputting the key phenotypic features into a genetic algorithm optimization module, and calculating the contribution degree of each genetic locus in combination with the Chinese trumpet creeper genotype data; and constructing a Chinese trumpet creeper breeding decision model according to the contribution degree of the gene locus, and outputting an optimal breeding combination scheme. The system can optimize the Chinese trumpet creeper breeding process and provide effective support for Chinese trumpet creeper breeding work.

The invention belongs to the technical field of sweet potato breeding, and provides an SNP marker related to sweet potato root color and anthocyanin content and application of the SNP marker, the SNP marker is located at the 25658800th site of a chromosome 10a of sweet potatoes, and the base polymorphism is A / T. When the SNP genotype of the sample to be detected is A / T, the content of anthocyanin in the tuberous roots is high, and the color is purple; when the SNP genotype is T / T, the content of anthocyanin in the tuberous roots is low, and the tuberous roots are non-purple in a large probability. According to the detection method and the kit provided by the invention, the efficiency of identifying the purple sweet potatoes by the developed SNP marker through sweet potato natural population phenotype identification and verification reaches 100%, the efficiency of identifying the non-purple sweet potatoes reaches 85.04%, the color of the sweet potato tuberous roots and the anthocyanin content can be rapidly and accurately detected, and the detection method and the kit have the advantages of being simple and convenient to operate, low in cost and the like, and have wide application prospects. The requirement of large-scale molecular marker-assisted selection can be met.

The invention belongs to the technical field of molecular genetic breeding, and particularly relates to a molecular marker Zm00001eb181850 gene related to corn leukoderma resistance and application thereof, the invention provides a molecular marker related to the corn leukoderma resistance, the gene sequence of the molecular marker is shown as SEQ ID NO: 1 and / or SEQ ID NO: 2, and the molecular marker Zm00001eb181850 gene is shown as SEQ ID NO: 1 and / or SEQ ID NO: 2. Researches prove that corn white spot resistance QTL qMWS4-1 and qMWS4-5 intervals and resistance SNP: 4-118983592 have co-localization, the corn white spot resistance QTL has a high phenotypic interpretation rate, the associated gene Zm00001eb181850 (SEQ ID NO: 2) is highly expressed in corn leaves, it is proved that the associated gene Zm00001eb181850 (SEQ ID NO: 2) is associated with the corn leaf spot, the corn white spot resistance is a quantitative character jointly regulated by multiple genes, and the corn leaf spot resistance QTL has a good application prospect. According to the technical scheme provided by the invention, a new method is provided for cultivating a new variety of leukoderma-resistant corn by utilizing a modern molecular breeding technology.

The invention provides application of a Zm00001eb378820 gene in molecular marker-assisted breeding for regulating and controlling the hundred-grain weight of corn grains, and relates to the technical field of agricultural biology. A backbone maize inbred line Ye107 is used as a male parent and hybridized with three excellent inbred lines (D39, R-2-1-1 and YML1218), a multi-parent group with remarkable hundred-grain weight difference is constructed, and SNP27712538 positioned on a chromosome 9 is a remarkable associated site by measuring hundred-grain weight phenotype data in multiple environments and combining high-density SNP (Single Nucleotide Polymorphism) markers, GWAS analysis and QTL (Quantitative Trait Loci) positioning. And the functional gene Zm00001eb378820 which is closely related to the regulation and control of the corn hundred-grain weight is excavated. A new insight is provided for a genetic regulation mechanism of the corn hundred-grain weight, and a key target spot is provided for breeding of high-yield corn varieties, so that the breeding efficiency is remarkably improved.

Provided is the use of overexpression of the auxin transporter PtoPIN1a gene in increasing the biomass of Populus tomentosa. The nucleotide sequence of the auxin transporter PtoPIN1a gene is as shown in SEQ ID No. 1. By means of using a genetic engineering method, wild-type Populus tomentosa is transformed by means of Agrobacterium tumefaciens infection to obtain a tissue-specific PtoPIN1a overexpressing transgenic plant, and subsequently, a plant with a relatively high expression level is selected, by means of positive identification, for phenotype observation. Results show that compared with the wild type in the same period, the PtoPIN1a transgenic plant has an increased plant height, a thicker stem and a significantly increased aboveground biomass. By means of the provided technical cultivation method, a high-biomass high-quality poplar variety is cultivated. The method is of great significance for future molecular breeding to cultivate excellent poplar varieties.

The invention relates to the technical field of teasel breeding, and discloses a teasel germplasm resource multi-character collaborative screening breeding method, which comprises the following steps: multi-omics data acquisition: extracting teasel germplasm leaf DNA (deoxyribonucleic acid), and capturing exon regions of disease resistance and metabolism related genes by adopting a targeted sequencing technology to obtain an SNP (single nucleotide polymorphism) marker matrix; the method comprises the following steps: collecting root extracts, detecting medicinal components through ultra-high performance liquid chromatography-mass spectrometry, and constructing a metabolite abundance matrix; measuring phenotype data of plant height, root length, root weight, root rot morbidity and survival rate under drought stress; key site and metabolite correlation analysis: constructing a Bayesian network containing SNP markers, metabolite and phenotypes by using a graph database, and carrying out cross validation through a leave-one-out method. The dipsacus asper germplasm resource multi-character collaborative screening breeding method aims at solving the problem that a traditional breeding method lacks systematic integration analysis of genomes and metabolic pathways in dipsacus asper multi-character collaborative improvement.

The invention discloses a wheat thousand seed weight identification method based on an SNP molecular marker and application, and relates to the technical field of genetic engineering, and the wheat thousand seed weight identification method comprises the following steps: A1, taking DNA of a wheat sample to be detected as a template, and carrying out PCR amplification by adopting a KASP primer combination according to any one of claims 2-3 or a kit according to claim 4; a2, judging the thousand seed weight of the wheat sample to be detected according to an amplification result. An SNP site related to the thousand seed weight of a plant is obtained through phenotypic difference analysis and exon capture analysis of the thousand seed weight, a corresponding KASP primer combination is designed for the SNP site, and the thousand seed weight of wheat can be rapidly identified through PCR amplification and genotype analysis: the thousand seed weight of AA genotype wheat is significantly higher than that of GG genotype wheat; the method provides an accurate molecular marking tool for high-yield breeding of wheat, has the advantages of high efficiency, accuracy and suitability for high-throughput detection, and has important significance for increasing the yield of wheat.

The invention discloses a breeding pressure simulation-based high-density-resistant penaeus monodon breeding method and system. The method comprises the following steps: determining pressure influence factors of penaeus monodon breeding through data retrieval, and extracting key environment variables by using principal component analysis; setting a plurality of groups of breeding pressure gradients, constructing a plurality of test groups by adopting an orthogonal test method, and collecting environment and phenotype data to evaluate the breeding effect and form a test data set. And constructing a breeding analysis model, and analyzing breeding evolution characteristics by constructing a correlation path and a topological structure chart of the breeding pressure gradient, the breeding effect and the monitoring data. And analyzing breeding demand information, inputting the breeding demand information into the model to obtain candidate breeding schemes, performing breeding feature extraction and cost evaluation on the candidate schemes, and finally recommending an optimal breeding scheme. The overall breeding benefit and production safety are improved, and the breeding period and complexity are reduced.

The invention belongs to the technical field of pepper planting, and discloses a pepper multi-branch gene CaBr1 linked KASP molecular marker as well as a primer, a kit and application thereof, the KASP molecular marker takes pepper S8 (zhangshuang) as a reference genome, and the single nucleotide polymorphism at the 103175415th basic group on the No.8 chromosome is subjected to basic group G-to-A replacement. A chromosome region closely linked with multiple branches of the pepper is obtained by using a BSA (Bovine Serum Albumin) population positioning method, a molecular marker is developed in a candidate region to determine a candidate gene CaBr1, a KASP molecular marker is screened according to base mutation of the candidate gene, and the marker is used for carrying out genotype identification on 90 randomly sampled single plants of an F2 population, and the coincidence rate reaches 100%. The result not only contributes to pepper branch phenotype identification and assistant breeding, but also lays a foundation for map-based cloning of the branch gene and analysis of a molecular mechanism of pepper plant type regulation.

The invention discloses a biological complex trait key gene identification method, device and equipment and a medium, and the method comprises the following steps: obtaining biological reference genome data, and carrying out orthologous gene class group division on a protein sequence coded by the biological reference genome data; determining a characteristic value data set according to the number of the subgroup sequence and the gene number of the subgroup sequence obtained after division; obtaining each piece of biological phenotype data; utilizing a machine algorithm model to construct a phenotype matrix according to the biological phenotype data and the characteristic value data set so as to train a phenotype prediction model, and determining the influence weight of each subgroup sequence on the biological phenotype according to the phenotype prediction model; and according to each influence weight, determining a key gene for regulating and controlling the biological complexity. The method provided by the invention can realize more accurate, efficient and comprehensive identification of key genes of prokaryotes and high biological complexity characters.

The invention relates to the technical field of biomedical data analysis, and discloses a data analysis method and system for genetic disease gene detection and a storage medium, and the method comprises the following steps: collecting a patient sample, and carrying out high-throughput sequencing to obtain original data; performing quality control and comparison processing on the data to generate variation detection data, and calculating variation information amount; suspicious variation sites are automatically screened, variation information amount is analyzed based on information entropy, and key variation is screened according to a preset threshold; performing Bayesian inference analysis on the key variation, calculating pathogenicity probability, and performing pathogenicity judgment based on an ACMG standard; calculating the matching degree of the key variation and the phenotype in combination with the phenotype information of the patient, and screening the variation conforming to phenotype characteristics; submitting the screening result to a doctor for auditing, and generating a final screening result; and generating a standardized gene detection report according to a final result. According to the method, pathogenic variation is efficiently and accurately recognized, and the automation level and clinical application value of genetic disease gene detection are improved.

The invention relates to the technical field of molecular markers, in particular to a biomarker related to the zeaxanthin content character of sweet corn kernels and application of the biomarker. The RIL population is used for performing QTL positioning on the corn kernel zeaxanthin content character, it is found that a major QTL related to the sweet corn kernel zeaxanthin content exists on the sixth chromosome of corn, the major QTL is located between SNP sites Schr6: 83027949 and Schr6: 84835891, the phenotype contribution rate of the corn kernel zeaxanthin content is 18.69%, and the major QTL is a major QTL related to the sweet corn kernel zeaxanthin content. The major QTL can be used for screening or auxiliary screening of sweet corn with relatively high zeaxanthin content, when the genotype of Schr6: 83027949 is GG and the genotype of Schr6: 84835891 is AA, the zeaxanthin content is relatively high, technical support is provided for molecular marker-assisted breeding, and the major QTL has important significance in improving the nutritional quality of the sweet corn.

A crop genotype-to-phenotype general prediction method based on multi-task learning comprises the following steps: collecting genotype and phenotype data sets of five crops, performing quality control and coding on genotype data, and performing standardization processing on phenotype data; dividing the data set into a training set and a test set in proportion by adopting a stratified sampling method; by taking genotype data as input and phenotype data as output, a universal prediction model based on a multi-task learning framework is constructed, information sharing among different phenotype prediction tasks is realized, and potential relations between complex phenotypes and genotypes are accurately captured. According to the method, phenotypes can be accurately predicted according to genotypes in the early stage of breeding, so that materials with target characters are rapidly screened, the breeding period is effectively shortened, the breeding efficiency is remarkably improved, and an efficient and universal technical scheme is provided for crop breeding and related research.

The invention provides a whole genome prediction method and system based on a coordinate attention deep learning model, and the method comprises the steps: obtaining a data set comprising genotype data and phenotype data, and carrying out the preprocessing of the data set, and obtaining a two-dimensional feature matrix; establishing a deep learning model, and predicting a phenotype value through the two-dimensional feature matrix; and dividing the data set into a training set and a test set, and training and testing the deep learning model until a final whole genome prediction model is obtained, so that the function of improving the accuracy of phenotype prediction is realized. According to the novel whole genome prediction method provided by the invention, the complex relationship between the genotype and the phenotype can be better captured by using the coordinate attention module, and the accuracy of whole genome prediction is improved.

The invention discloses a molecular marker closely linked with a cowpea salt tolerance major QTL (quantitative trait loci) and a primer sequence of the molecular marker. The name of the cowpea salt tolerance major QTL is SC300124, a KASP type molecular marker 300124 closely linked with the cowpea salt tolerance major QTL is located at the position of 43716091 bp on a chromosome 11, the marker can be used for amplifying a material to be detected, and whether a sample carries key allelic variation for controlling salt tolerance or not is judged according to the genotype of the marker. The molecular marker and the primer provided by the invention can be used for quickly screening the cowpea salt tolerance major QTL, and compared with a traditional phenotype identification method, the molecular marker and the primer have the advantages of high detection flux, accurate and reliable result and the like, and the typing accuracy can reach 99% or above. The technology can significantly improve the breeding efficiency of the salt-tolerant variety of cowpea and shorten the breeding period.

The invention discloses a method and a system for assisting rice breeding by using a lodging-resistant index, particularly relates to the field of agricultural breeding, and quantifies the lodging-resistant capability of plants by constructing an evaluation model fused with multi-source phenotypic parameters. Key character data are obtained by combining mechanical testing, manual measurement and unmanned aerial vehicle image acquisition, an LRI index is calculated through standardization processing and image recognition, resistance grading is conducted, and lodging-resistant breeding material screening is achieved. According to the method and the system for assisting rice breeding by using the lodging-resistant index, digitization and intellectualization of a rice lodging resistance evaluation process are realized, and scientificity and efficiency of evaluation are remarkably improved. And by introducing an unmanned aerial vehicle remote sensing and image recognition algorithm, the large-scale sample processing capability is improved, and the timeliness and stability of data acquisition are enhanced. A lodging risk thermodynamic diagram and a recommended breeding list can be output through a matched visual analysis function, visual reference is provided for researchers and breeding decisions, and the method has good application and popularization prospects.

The invention provides a gene detection and phenotype verification health detection method and system, and the method comprises the following steps: collecting multi-source data of a user, locking genetic variation highly related to disease and individual specificity through gene sequencing, and building an individualized genetic risk scoring system; wherein the multi-source data comprises gene sequencing and proteomics data of a user; performing gene phenotype coupling analysis, integrating multi-dimensional data of genes, proteins or phenotypes of the user, and constructing a health assessment system with high confidence; the intervention decision generation is used for generating a decision to intervene the user; through gene-phenotype coupling analysis, the disease risk prediction specificity of healthy people is improved, compared with a conventional health monitoring technology, risks are found in advance, the health behavior compliance rate of a user is increased, seamless connection with mainstream wearable equipment and an electronic medical record system is supported, and the utilization rate of data is increased.

The invention relates to the technical field of plant phenotype data processing, in particular to a plant phenotype automatic acquisition and feature processing method oriented to a multi-element environment. According to the method, the plant multi-modal phenotypic data are synchronously collected through the Internet of Things nodes, the coupling strength is calculated in combination with the environmental factors, the phenotypic parameters are divided into an environment sensitive type and a steady type, and the data classification accuracy is improved. A growth trend field is constructed by means of phenological phase decoupling analysis and geographic space superposition, abnormal segments are dynamically eliminated by combining physiological synergy degree and a mutation detection algorithm, and trend analysis stability is enhanced. A phenotype-environment response map is generated through standardized processing and an environment equivalent value model, a key environment sensitive window is recognized, a regional and staged cross-environment regulation scheme is output, intelligent and accurate management of the crop growth environment is achieved, and the method is suitable for agricultural yield increase and breeding optimization.

The invention discloses an application of an OsPES gene and an encoding protein thereof in regulating and controlling the tiller number of rice, and belongs to the technical field of biology. According to the application disclosed by the invention, two OsPES BRCT structural domain homozygous knockout strains Ospesc-cas9-1 and Ospesc-cas9-5, two OsPES overexpression strains OE-OsPES-3 and OE-OsPES-7 and two RNAi (Ribonucleic Acid Interference) interference strains RNAi-OsPES-1 and RNAi-OsPES-6 are respectively obtained by taking japonica rice'cloud guide 'as a background material and utilizing related technologies. Phenotypic observation and statistical analysis find that compared with a wild type, the tiller number of an overexpressed OsPES strain is increased, and the tiller number of an OsPES interference strain and the tiller number of a BRCT structural domain knockout strain are reduced. It is found for the first time that OsPES can positively regulate the tiller number of rice and has application significance in regulation of the tiller number of rice and new strain breeding.

The invention belongs to the technical field of plant gene engineering, and particularly relates to an OsNUC1 gene and application of a gene mutant constructed by the OsNUC1 gene to regulation and control of rice plant height, leaf length and panicle type. The regulation is to regulate the plant height and leaf growth of the rice and influence the shape of the ear part. Compared with the prior art, the OsNUC1 gene mutant has the following advantages: (1) the OsNUC1 is directionally edited by utilizing a CRISPR / Cas9 gene editing technology, an OsNUC1 gene mutant rice material is obtained, the biological phenotype of the OsNUC1 gene mutant rice material is investigated, the phenotype investigation on T1-generation seedlings of the OsNUC1 shows that the plant heights and the leaf lengths of one-week-old and two-week-old seedlings of the mutant are obviously higher than those of wild seedlings, the leaf widths have no obvious difference, and the OsNUC1 gene mutant rice material has a good application prospect; the result shows that the OsNUC1 can regulate the plant height and the leaf growth of the rice and influence the shape of the ear part. (2) it is proved that the nucleolin gene OsNUC1 is negatively regulated by a transcription factor OsARF7, and the phenotypes such as the plant height, the leaf length, the grain length and the grain width of the OsNUC1 / OsARF7 mutant are more obvious than those of the OsNUC1 mutant. The invention further proves the application of the OsNUC1 gene in regulation and control of rice plant height and leaf growth.

The invention relates to the technical field of molecular markers, in particular to an Indel molecular marker related to yellow leaves of a melon seedling growing point and application of the Indel molecular marker. The invention explores a key candidate gene MELO3C016136 for controlling the leaf color of the growth point of the muskmelon seedling, and develops an Indel molecular marker ygp2 for identifying the leaf color change of the growth point of the muskmelon seedling based on the key candidate gene MELO3C016136. The molecular marker ygp2 can be used for identifying the leaf color change character of the growth point of the muskmelon seedling, only one-time PCR amplification and polyacrylamide gel electrophoresis need to be carried out on the DNA of the plant to be detected, the identification result is reliable, the genotype of the target plant can be simply and conveniently identified, and the genotype identification result is completely consistent with the leaf color phenotype of the growth point of the seedling; important technical support is provided for creating new muskmelon germplasm with yellow seedling growing point leaves.