6 results about "Phylogenetic relationship" patented technology

This invention relates to the fields of genomics, molecular biology, bioinformatics, and genome-wide selection breeding, specifically a 20k liquid-phase breeding chip for the whole genome of *S. esculenta* and its applications. The liquid-phase chip contains background SNPs and functional SNPs located on the *S. esculenta* reference genome; wherein the background SNPs are uniformly distributed within the genome; and the functional SNPs are associated with important economic traits of *S. esculenta*; these important economic traits include one or more of the following: saponin content, polysaccharide content, and heat tolerance. The chip can be applied to the assessment of genetic diversity in *S. esculenta*, identification of germplasm resources and phylogenetic relationships, genome-wide association analysis of important economic traits, and genome-wide selection breeding. This chip has advantages such as high throughput, high region coverage, high locus detection rate, and high flexibility, providing powerful tool support for molecular breeding of *S. esculenta*.

This invention provides SSR molecular markers for Hibiscus rosa-sinus and their applications, belonging to the field of molecular marker technology. The invention comprises 15 molecular markers, with corresponding primer sequences shown in SEQ ID NO. 1~30. Testing revealed that this series of markers exhibits a 100% polymorphism rate, excellent polymorphism information content, marker index, and resolution, and strong genetic stability. The molecular marker primers of this invention can efficiently distinguish Hibiscus rosa-sinus germplasm materials, clearly revealing the population's genetic structure and phylogenetic relationships. They are suitable for Hibiscus rosa-sinus germplasm resource identification, genetic diversity analysis, molecular fingerprinting construction, and assisted breeding, possessing the characteristics of high specificity, high resolution, and wide applicability.

The invention provides a formula flora construction method and device, electronic equipment and a storage medium, and belongs to the field of bioinformatics, and the formula flora construction method comprises the following steps: converting a phylogenetic tree constructed by a microbial genome sequence into a weight matrix; performing center logarithm ratio transformation on the original abundance matrix and then inputting the original abundance matrix into an iterative random forest model; correcting the original feature importance into smooth feature importance by using the weight matrix so as to update the feature sampling weight of the next round; and when the model converges, extracting a high-order ecological interaction rule based on a decision path to output a candidate core flora, and further determining a target formula flora. The characteristics are smoothly corrected by introducing the phylogenetic relationship, so that the independence hypothesis of traditional abundance data is broken, the sparsity and false positive interference of high-dimensional sequencing data are effectively overcome, the evolution-driven real inter-species collaborative relationship is accurately captured and reserved, and the accuracy of the method is improved. Therefore, efficient steady-state colonization and precise targeted metabolic regulation of the formula flora in the host microenvironment are guaranteed.

This application discloses a method for identifying SNP molecular markers significantly associated with potato starch content, belonging to the field of SNP molecular marker technology. Based on high-quality SNP sets and starch content phenotypic data, this application employs a mixed linear model for genome-wide association analysis, effectively controlling population structure and phylogenetic relationships, and significantly reducing the false positive rate. By constructing haplotype blocks and introducing an effect accumulation assessment algorithm, it overcomes the limitations of traditional single SNP analysis, detecting the synergistic effect of allele combinations, and the selected haplotype blocks have higher phenotypic explanatory power. Representative SNPs are screened using linkage disequilibrium analysis, and the introduction of independent validation populations ensures the stability and cross-population applicability of the molecular markers. Finally, SNP molecular markers significantly associated with potato starch content are obtained, which can be directly used for early screening of high-starch germplasm and marker-assisted breeding, significantly shortening the breeding cycle and improving selection efficiency.

The application discloses a method for ancestral haplotype typing in a fine genomic interval across tetraploid and hexaploid wheat. The application provides a method, steps of which are as follows: 1) obtaining whole genome resequencing data of each wheat sample to be tested; 2) obtaining filtered DNA sequence alignment files of each sample to be tested; 3) SNP identification and CNV variation identification; 4) obtaining SNP polymorphism site density distribution; 5) fitting the density distribution of the SNP polymorphism sites to obtain a normal distribution, and determining a genetic distance hard threshold according to a boundary; 6) obtaining an initial ancestral haplotype; 7) obtaining an initial priority order of the sample; and 8) obtaining an ancestral haplotype file. The application does not need resequencing data of a reference population as input, which reduces the total detection cost. The application also does not need to limit the phylogenetic relationship between populations to which the samples to be detected belong, which can improve the detection accuracy in crops with complex evolutionary history.

The application provides a formula flora construction method and device, electronic equipment and storage medium, and belongs to the field of bioinformatics, and comprises the following steps: converting a phylogenetic tree constructed by a microbial genome sequence into a weight matrix; inputting a central logarithmic ratio transformed original abundance matrix into an iterative random forest model; correcting the original feature importance to smooth feature importance by using the weight matrix to update the feature sampling weight in the next round; and extracting high-order ecological interaction rules based on the decision path when the model converges to output a candidate core flora, and then determining a target formula flora. The application breaks the independence assumption of traditional abundance data by introducing phylogenetic relationships to smooth correct features, effectively overcomes the sparsity of high-dimensional sequencing data and false positive interference, accurately captures and retains the real interspecies synergistic relationship driven by evolution, and thus guarantees the efficient and stable colonization and precise targeted metabolic regulation of the formula flora in the host microenvironment.