KR102676313B1 - Method and apparatus for screening gene - Google Patents

Abstract

According to an embodiment of the present disclosure, a phylogenetic tree and expression level data of genes are obtained based on the protein sequences of the genes of the subject, and a specific gene entered as a query is a gene sharing the same domain in the phylogenetic tree. As it is included in the gene, the expression pattern between the specific gene and each of the genes in the phylogenetic tree is compared, a correlation is determined, and based on the correlation determined for the specific gene, overlapping with a specific gene among the genes of the subject A gene selection method for determining a target gene having a function and providing information regarding the determined target gene is disclosed.

Description

Gene screening method and device {METHOD AND APPARATUS FOR SCREENING GENE}

The disclosed embodiment is a method and device for selecting useful genes by predicting functional redundancy between genes due to genome duplication that occurred during the evolution of crops using genome sequence data and data accumulated through next-generation sequencing of various transcripts. It's about.

Genome editing technology that accurately targets target genes using genetic scissors has emerged and is being applied in various fields. However, in the case of plants, extensive duplication at the genome level occurred during most of the evolution process, resulting in high functional redundancy between genes of similar sequence. Therefore, when gene editing technology that accurately targets only target genes is applied, it is difficult to confirm the phenotype. There may be difficulties.

Accordingly, there is a need for a method that can effectively select genes for subjects with high functional redundancy between genes of similar sequence, such as plants.

Stefano Berri et al., “Characterization of WRKY co-regulatory networks in rice and Arabidopsis”, BMC Plant Biology, 9:120. (2009.09.22.)

The disclosed embodiments are intended to provide a method and device for selecting genes for subjects showing high functional redundancy between genes of similar sequences.

A gene selection method according to one embodiment includes obtaining a phylogenetic tree and gene expression level data based on protein sequences for genes of a subject; As a specific gene entered as a query is included in genes sharing the same domain in the phylogenetic tree, comparing expression patterns between the specific gene and each of the genes in the phylogenetic tree to determine a correlation; Based on the correlation determined for a specific gene, determining a target gene having a function overlapping with a specific gene among the genes of the subject; And it may include providing information about the determined target gene.

In the gene selection method according to one embodiment, the obtaining step includes performing annotation on a representative protein sequence of a gene of a subject; Generating a plurality of FASTA files in the Pfam domain based on the annotation results; And it may include obtaining the phylogenetic tree through sequence alignment of the plurality of generated FASTA files.

In the gene selection method according to one embodiment, the obtaining step includes generating expression level information of genes for each tissue by aligning transcriptome sequence analysis data for tissues of the subject with the genome of the subject; And it may include the step of performing normalization on the generated expression level information of genes for each tissue, and obtaining gene data including gene expression values.

In the gene selection method according to one embodiment, the step of determining the correlation may include determining a PCC (Pearson Correlation Coefficient) value between the expression pattern of a specific gene and the expression pattern of the gene in the phylogenetic tree. .

In the gene selection method according to one embodiment, the step of determining the target gene may include determining at least one gene whose PCC value is greater than or equal to a threshold value as the target gene.

In the gene selection method according to one embodiment, the threshold may be determined based on the correlation results for each of the other input genes calculated before a specific gene is input as a query.

A computer program product including a recording medium storing a program for performing a gene selection operation according to an embodiment is a computer program product that obtains a phylogenetic tree and gene expression level data based on the protein sequence of the genes of the subject. movement; As a specific gene entered as a query is included in genes sharing the same domain in the phylogenetic tree, comparing expression patterns between the specific gene and each of the genes in the phylogenetic tree to determine a correlation; and determining a target gene having a function overlapping with a specific gene among the genes of the subject, based on the correlation determined for the specific gene; And it may include an operation of providing information about the determined target gene.

A genetic selection device according to one embodiment includes: memory; input unit; display; and at least one processor coupled to the memory, wherein the at least one processor includes:

A phylogenetic tree and gene expression level data are obtained based on the protein sequences of the genes of the subject, and as the specific gene entered as a query through the input unit is included in the genes sharing the same domain in the phylogenetic tree, The expression pattern between a specific gene and each of the genes in the phylogenetic tree is compared to determine the correlation, and based on the correlation determined for the specific gene, a target gene that has an overlapping function with a specific gene among the genes of the subject is selected. The display can be controlled to display information about the determined correlation and information about the target gene.

The gene selection method according to one embodiment can effectively select genes with similar functions based on the results of next-generation sequencing of the genome and transcriptome, and provides a visualization of the selection results through a UI (user interface). It can provide convenience to users in genetic selection. In particular, the gene selection technology according to one embodiment can more accurately predict functional redundancy by utilizing the genome sequence information and transcriptome information of rice, a crop model that is produced and accumulated in large quantities, and through this, single or Multiple target genes can be selected and research on related agricultural traits can be dramatically promoted.

1 is a flowchart illustrating a gene selection method according to an embodiment.
Figure 2 is a flowchart to explain in more detail a gene selection method according to an embodiment.
FIG. 3 is a diagram illustrating a UI 300 provided for genetic selection according to an embodiment.
Figure 4 is a diagram showing a phylogenetic heatmap obtained as a result of applying a gene selection method to a specific gene entered as a query according to one embodiment.
Figure 5 is a block diagram for explaining a genetic selection device 500 according to an embodiment.

The terms used in this specification will be briefly explained, and the present invention will be described in detail.

The terms used in the present invention are general terms that are currently widely used as much as possible while considering the functions in the present invention, but this may vary depending on the intention or precedent of a technician working in the field, the emergence of new technology, etc. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the relevant invention. Therefore, the terms used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, rather than simply the name of the term.

When it is said that a part "includes" a certain element throughout the specification, this means that, unless specifically stated to the contrary, it does not exclude other elements but may further include other elements. In addition, terms such as "... unit" and "module" used in the specification refer to a unit that processes at least one function or operation, which may be implemented as hardware or software, or as a combination of hardware and software. .

Hereinafter, the present invention will be described in detail with reference to the attached drawings.

1 is a flowchart illustrating a gene selection method according to an embodiment. The gene selection method according to the present disclosure can be applied to various subjects, but in this embodiment, rice is used as an example of the subject.

In step S110, the gene selection device may obtain a phylogenetic tree and gene expression level data based on the protein sequences of the target's genes.

The gene selection device according to one embodiment uses the protein domain information of the gene group provided by the Pfam database to determine whether there is a similar gene in the genome, and then selects the protein sequence of the MSU7 version of the Rice Genome Annotation Project, which is representative genome sequence information of rice. You can create a phylogenetic tree using .

Additionally, the genetic selection device By aligning transcriptome sequencing data for rice tissues with the MSU7 version of the rice genome, gene expression level information can be generated for each tissue. The gene selection device can normalize the expression level information of the generated genes for each tissue.

The gene selection device can combine the phylogenetic tree and normalized gene expression level information for each tissue according to the rice gene input as a query. A genetic selection device according to one embodiment may receive identification information about a specific gene through a query. For example, a gene selection device can obtain a LOCUS ID as identification information for a rice gene to be used for gene editing. At this time, the LOCUS ID can be obtained based on the value entered by the user on the genetic identification information input item on the UI, which will be described later in FIG. 3. However, this is only an example, and the method by which the genetic selection device receives identification information about a specific gene through a query is not limited to the above-described example.

Meanwhile, the Python language and ETE toolkit can be used to combine the phylogenetic tree and gene expression level information.

In step S120, the gene selection device determines a correlation by comparing the expression pattern between the specific gene and each of the genes in the phylogenetic tree, as the specific gene entered as a query is included in genes sharing the same domain in the phylogenetic tree. You can decide.

A gene selection device according to an embodiment can identify genes that share the same domain as a specific gene based on a phylogenetic tree. The gene selection device can obtain a correlation coefficient by comparing the pattern of expression values between each of the identified genes and a specific gene. At this time, the PCC (Pearson Correlation Coefficient) value may be used as the correlation coefficient.

In step S130, the gene selection device may determine a target gene among the genes of the subject based on the correlation determined for the specific gene.

The gene selection device may determine at least one gene whose value is greater than or equal to a threshold among the correlation values determined in step S120 described above as the target gene. At this time, the threshold may be determined based on information about the correlation for each of the other input genes, which is calculated before a specific gene is input as a query. However, this is only an example, and according to another example, the threshold may be determined according to user input.

In step S140, the gene selection device may provide information regarding the determined target gene.

The gene selection device according to one embodiment may display identification information of the target gene and a correlation value between the target gene and a specific gene entered as a query on the UI. Additionally, the gene selection device may display genes whose correlation values are within a critical range on the UI along with their respective correlation values.

Figure 2 is a flowchart to explain in more detail a gene selection method according to an embodiment.

Referring to FIG. 2, according to one embodiment, a phylogenetic data processing process 210 and a transcriptome data processing process 220 may be performed for gene selection. Hereinafter, the phylogenetic data processing process 210 and the transcriptome data processing process 220 will be described in detail.

First, the genetic selection device is the subject's genetic data, and can obtain protein sequences for MSU7 version genes from the Pfam database. The genetic selection device may perform re-annotation on representative protein sequences among the obtained protein sequences in step 212 of the phylogenetic data processing process 210. After performing re-annotation, the gene selection device may generate a FASTA file for each of all Pfam domains in step 214. The genetic selection device may align a plurality of sequences of the generated FASTA files in step 216, and obtain a phylogenetic tree based on the plurality of aligned sequences in step 218. As an example, a genetic selection device may obtain a phylogenetic tree by bootstrapping an approximate maximum likelihood tree several times. For example, as a result of applying bootstrapping to generate an approximate maximum likelihood tree 100 times on the protein sequences of 55,801 MSU7 genes, 3,965 phylogenetic trees could be obtained based on the PFAM domain.

Additionally, the gene selection device may integrate tissue-specific RNA sequence data for MSU7 version genes in step 222 of the transcriptome data processing process 220. In step 224, the genetic selection device can perform quality control on the integrated RNA sequence data and map it to the MSU7 rice standard genome. In step 226, the gene selection device may calculate an expression value from the result of mapping the RNA sequence data to the MSU7 rice standard genome, and in step 228, the calculated expression value may be normalized.

The gene selection device can perform a redundancy digitizing process (230) by combining the phylogenetic tree and normalized expression values to select genes with overlapping functions with specific genes input as queries. Specifically, in step 232, the gene selection device may generate a phylogenetic heatmap composed of genes sharing the same domain from 3965 phylogenetic trees generated in the phylogenetic data processing process 210. Additionally, in step 234, the gene selection device may select the specific gene itself and the sister nodes of the specific gene input as a query from the generated heatmap. In step 236, the genetic selection device can calculate the PCC value for all sister nodes.

The gene selection device can compare the PCC values and threshold values for each of the sister nodes to select genes that have overlapping functions with a specific gene input as a query. The gene selection device can display PCC values for each sister node and information about the selected genes on the UI. This will be described in more detail later with reference to FIG. 3.

The genetic selection method according to one embodiment can provide the above-described series of processes to users through a web tool. In addition, the gene selection device determines whether there is no gene group similar to a specific gene entered as a query, when there is a gene group but has an independent lineage, or when there is a gene group and it belongs to the same phylogenetic tree but has an independent expression pattern, it is classified into a single gene group. They may be determined as targets for gene editing, and for genes that exist in similar gene groups and have similar expression patterns in the same phylogenetic tree, these may be determined as targets for gene editing at the same time. Through this, the gene selection method according to one embodiment can facilitate the acquisition of crop phenotypes, unlike existing gene editing research that had difficulty selecting genes because it did not consider similarity of function.

FIG. 3 is a diagram illustrating a UI 300 provided for genetic selection according to an embodiment.

The UI 300 provided for gene selection according to one embodiment may be provided with hyperlink information 310 providing a phylogenetic heatmap or a data set for gene selection. Additionally, the UI 300 may include explanatory information 320 for interpreting the phylogenetic heatmap, for example, information regarding the value of a color map indicating functional similarity.

Additionally, a search box 330 may be displayed on the UI 300 so that identification information of a gene to be entered as a query can be entered. The user can request selection of genes with overlapping functions with the specific gene by entering identification information of a specific gene of interest in the search box 330 and clicking the submit button.

Depending on the user's request for gene selection, the first panel 340, which provides an entire phylogenetic heatmap, and the second panel 350, which provides a phylogenetic heatmap of genes with similar functions, may be displayed on the UI 300. there is. In a phylogenetic heatmap, a PCC value indicating the similarity of the expression value with a specific gene entered as a query can be displayed, and the PCC value can be displayed in different colors for each specific section so that the similarity can be intuitively identified. .

Figure 4 is a diagram showing a phylogenetic heatmap obtained as a result of applying a gene selection method to a specific gene entered as a query according to one embodiment.

Referring to Figure 4, the gene selection device performs gene selection on a specific gene entered as a query. As a result, if there is no similar gene group (no Pfam information), if there is a similar gene group but has an independent expression pattern ( functional dominant), genes in a similar gene group but independently differentiated (unique clade) can be determined as targets for single gene editing.

In addition, the gene selection device can determine that similar gene groups exist and that all genes (functional redundants) with similar expression patterns in the same phylogenetic tree are targets for gene editing. At this time, the PCC value is used as a standard for determining genes with similar expression patterns. A PCC value closer to 1 corresponds to similar expression characteristics, and a closer value to 0 corresponds to no similarity in expression characteristics.

Meanwhile, by comparing the PCC value and a preset threshold, it is possible to determine whether to determine whether to be a target for gene editing. For example, if the threshold is 0.7, genes with a PCC value of 0.7 or more in the same phylogenetic tree are judged to have functional redundancy and can be determined as targets for gene editing. At this time, the threshold may be preset based on experimentally acquired data. For example, the threshold may be determined based on the correlation results for each of the other input genes calculated before a specific gene is input as a query. According to another example, the threshold may be determined based on user input.

The gene selection method according to one embodiment is provided to the user through a UI on the web, so that the user can easily receive information about genes that have overlapping functions with a specific gene desired by the user with just a few clicks.

Figure 5 is a block diagram for explaining a genetic selection device 500 according to an embodiment.

Referring to FIG. 5 , the genetic selection device 500 may include an input unit 510, a display 520, a processor 530, and a memory 540. The processor 530 may operate according to the gene selection method proposed in the above embodiments. However, the components of the genetic selection device 500 according to one embodiment are not limited to the above-described examples. According to another embodiment, the genetic selection device 500 may include more or fewer components than the above-mentioned components.

The input unit 510 may obtain information about a specific gene input as a query. For example, the input unit 510 may be an input means for a user to input identification information about a specific gene. Additionally, the input unit 510 may receive a user input that triggers each function of the UI provided on the web in order to request selection of a gene having a function overlapping with a specific gene.

The display 520 may display a UI for executing a genetic selection function. For example, the UI described above with reference to FIG. 3 may be displayed on the display 520. Additionally, as a result of gene selection, the display 520 may display whether a gene with an overlapping function with a specific gene exists and, if a gene with an overlapping function exists, identification information and a correlation value for the gene.

The processor 530 may obtain a phylogenetic tree and gene expression level data based on the protein sequences of the genes of the subject. For example, the processor 530 may annotate a representative protein sequence of a gene of a subject and generate a plurality of FASTA files in the Pfam domain based on the annotation results. The processor 530 may obtain a phylogenetic tree through sequence alignment of the plurality of generated FASTA files.

Additionally, the processor 530 may generate expression level information of genes for each tissue by aligning the transcriptome sequence analysis data for the tissues of the object with the genome of the object. The processor 530 can obtain gene data including gene expression values by performing normalization on the generated expression level information of genes for each tissue.

As the specific gene entered as a query is included in the genes sharing the same domain in the phylogenetic tree, the processor 530 can determine a correlation by comparing the expression pattern between the specific gene and each of the genes in the phylogenetic tree. there is.

The processor 530 may determine a target gene among the genes of the subject based on the correlation determined for the specific gene. Processor 530 may provide information regarding the determined target gene.

The memory 540 may store information necessary for the processor 530 to determine whether a target gene having a function overlapping with a specific gene exists. For example, the memory 540 may store gene expression level data and a phylogenetic tree obtained based on protein sequences for genes of the subject.

The device according to the present invention includes a processor, memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with an external device, and a user interface such as a touch panel, keys, buttons, etc. It may include devices, etc. Methods implemented as software modules or algorithms may be stored on a computer-readable recording medium as computer-readable codes or program instructions executable on the processor. Here, computer-readable recording media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disk, hard disk, etc.) and optical read media (e.g., CD-ROM). ), DVD (Digital Versatile Disc), etc. The computer-readable recording medium is distributed among networked computer systems, so that computer-readable code can be stored and executed in a distributed manner. The media may be readable by a computer, stored in memory, and executed by a processor.

All documents, including published documents, patent applications, patents, etc., cited in the present invention may be incorporated into the present invention in the same manner as if each cited document was individually and specifically incorporated or as if it were incorporated in the present invention as a whole. .

For understanding of the present invention, reference numerals are used in the preferred embodiments shown in the drawings, and specific terms are used to describe the embodiments of the present invention. However, the present invention is not limited by the specific terms, and the present invention May include all components commonly conceived by those skilled in the art.

The invention may be represented by functional block configurations and various processing steps. These functional blocks may be implemented in various numbers of hardware or/and software configurations that execute specific functions. For example, the present invention provides integrated circuit components, such as memory, processing, logic, look-up tables, etc., that can execute various functions under the control of one or more microprocessors or other control devices. can be hired. Similar to the fact that the components of the invention can be implemented as software programming or software elements, the invention also includes various algorithms implemented as combinations of data structures, processes, routines or other programming constructs, including C, C++, , may be implemented in a programming or scripting language such as Java, assembler, etc. Functional aspects may be implemented as algorithms running on one or more processors. Additionally, the present invention can employ conventional technologies for electronic environment settings, signal processing, and/or data processing. Terms such as “mechanism,” “element,” “means,” and “configuration” may be used broadly and are not limited to mechanical and physical configurations. The term may include the meaning of a series of software routines in connection with a processor, etc.

The specific implementations described in the present invention are examples and do not limit the scope of the present invention in any way. For the sake of brevity of the specification, descriptions of conventional electronic components, control systems, software, and other functional aspects of the systems may be omitted. In addition, the connections or connection members of lines between components shown in the drawings exemplify functional connections and/or physical or circuit connections, and in actual devices, various functional connections or physical connections may be replaced or added. Can be represented as connections, or circuit connections. Additionally, if there is no specific mention such as “essential,” “important,” etc., it may not be a necessary component for the application of the present invention.

In the specification (particularly in the claims) of the present invention, the use of the term “above” and similar referential terms may refer to both the singular and the plural. In addition, when a range is described in the present invention, it includes the invention to which individual values within the range are applied (unless there is a statement to the contrary), and each individual value constituting the range is described in the detailed description of the invention. It's the same. Finally, unless there is an explicit order or statement to the contrary regarding the steps constituting the method according to the invention, the steps may be performed in any suitable order. The present invention is not necessarily limited by the order of description of the above steps. The use of any examples or illustrative terms (e.g., etc.) in the present invention is merely to describe the present invention in detail, and unless limited by the claims, the scope of the present invention is limited by the examples or illustrative terms. It doesn't work. Additionally, those skilled in the art will recognize that various modifications, combinations and changes may be made depending on design conditions and factors within the scope of the appended claims or their equivalents.

Claims (13)

In the genetic selection method,
Obtaining a phylogenetic tree and gene expression level data based on the protein sequences of the genes of the subject;
generating a phylogenetic heatmap composed of genes sharing the same domain in the phylogenetic tree;
Selecting a specific gene entered as a query and sister nodes of the specific gene from the phylogenetic heatmap;
Comparing the gene expression pattern of the specific gene with the gene expression pattern of each of the sister nodes based on the obtained expression level data, and determining a Pearson Correlation Coefficient (PCC) value of each of the sister nodes;
determining a target gene having a function overlapping with the specific gene among the sister nodes based on the PCC value of each of the sister nodes determined for the specific gene; and
Comprising the step of providing information about the determined target gene,
The obtaining step is,
Annotating a representative protein sequence of a gene of the subject;
Generating a plurality of FASTA files for each of all Pfam domains based on the annotation results; and
Comprising the step of obtaining the phylogenetic tree through sequence alignment of the plurality of generated FASTA files,
Among the sister nodes, the PCC value of the sister node determined by the target gene is greater than or equal to a threshold value,
The threshold is,
A method that is preset based on experimentally acquired data before a specific gene is entered into the query. delete The method of claim 1, wherein the obtaining step includes:
Aligning transcriptome sequence analysis data for tissues of the subject with the genome of the subject, thereby generating expression level information of genes for each tissue; and
A method comprising the step of performing normalization on the generated expression level information of genes for each tissue, and obtaining expression level data of the genes including gene expression values. delete delete delete Obtaining a phylogenetic tree and gene expression level data based on the protein sequences of the genes of the subject;
An operation of generating a phylogenetic heatmap composed of genes sharing the same domain in the phylogenetic tree;
An operation of selecting a specific gene input as a query and sister nodes of the specific gene from the phylogenetic heatmap;
Comparing the gene expression pattern of the specific gene with the gene expression pattern of each of the sister nodes based on the obtained expression level data, and determining a Pearson Correlation Coefficient (PCC) value of each of the sister nodes;
An operation of determining a target gene having a function overlapping with the specific gene among the sister nodes based on the PCC value of each of the sister nodes determined for the specific gene; and
Characterized by storing a program that executes an operation on a computer to provide information about the determined target gene,
The acquisition operation is,
An operation of annotating a representative protein sequence of a gene of the subject;
An operation of generating a plurality of FASTA files for each of all Pfam domains based on the annotation result; and
Comprising an operation of obtaining the phylogenetic tree through sequence alignment of the plurality of generated FASTA files,
Among the sister nodes, the PCC value of the sister node determined by the target gene is greater than or equal to a threshold value,
The threshold is,
A computer-readable recording medium that is preset based on experimentally acquired data before a specific gene is input through the query. delete The method of claim 7, wherein the acquiring operation includes:
An operation of generating expression level information of genes for each tissue by aligning transcriptome sequence analysis data for the tissues of the subject with the genome of the subject; and
A computer-readable recording medium comprising the operation of performing normalization on the generated expression level information of genes for each tissue, and obtaining expression level data of the genes including gene expression values. delete delete delete delete