A Genome Annotation Method Using Second- and Third-Generation Transcriptome Sequencing Data

Abstract

The invention relates to the technical field of genome annotation, and provides a genome annotation method using second-generation and third-generation transcriptome sequencing data. The method of the present invention includes the following steps: Step 1: align the three-generation full-length transcriptome sequencing sequence to the target genome to obtain the initial structural information of each coding gene; Step 2: align the second-generation transcriptome sequencing short sequence to the target genome Genome, extract intron splicing site information from the comparison file; step 3: combine the initial structure information of each coding gene and intron splicing site information to obtain the final structure information of each coding gene. The present invention can not only make full use of the advantage of high accuracy that the full-length transcript sequence can be obtained without splicing the third-generation transcriptome, but also fully consider the advantage that the second-generation transcriptome sequencing data can provide a large number of intron splicing site evidences , greatly improving the accuracy and efficiency of genome annotation.

Description

technical field [0001] The invention relates to the technical field of genome annotation, and relates to a method for annotation of eukaryotic whole genome coding gene structure, in particular to a method for genome annotation using second-generation and third-generation transcriptome sequencing data. Background technique [0002] Generally, after the whole genome sequence is assembled, the structure of its protein-coding gene needs to be predicted. Prediction typically employs a combination of three strategies: de novo prediction, prediction based on sequence homology in closely related species, and prediction based on transcriptome data. Since the transcriptome is the most direct evidence of genes expressed by a species, the prediction results based on transcriptome data are considered to be the most reliable, and the weight given by the strategy when integrating the prediction results of all strategies to obtain the final gene set Generally the highest. [0003] Among t...

AI Technical Summary

Problems solved by technology

The advantage of these two strategies is that they can make full use of the information provided by the second-generation sequencing data, but they cannot directly use the third-generation sequencing data

The disadvantage of PASA is that it cannot make full use of the large amount of intron position information that NGS data can provide, and the speed is slow

[0004] It can be seen that the existing genome annotation methods have their own advantages and disadvantages, but none of them can take advantage of the advantages of second-generation and third-generation sequencing at the same time, and the accuracy and efficiency of genome prediction are not high enough

Images