CN115083516A

CN115083516A - Panel design and evaluation method for detecting gene fusion based on targeted RNA sequencing technology

Info

Publication number: CN115083516A
Application number: CN202210818316.6A
Authority: CN
Inventors: 巩小芬; 邓望龙; 杨雪雨; 张超; 李诗濛; 任用
Original assignee: Jiangsu Xiansheng Medical Diagnosis Co ltd; Nanjing Xiansheng Medical Laboratory Co ltd; Beijing Xiansheng Medical Examination Laboratory Co ltd
Current assignee: Jiangsu Xiansheng Medical Diagnosis Co ltd; Nanjing Xiansheng Medical Laboratory Co ltd; Beijing Xiansheng Medical Examination Laboratory Co ltd
Priority date: 2022-07-13
Filing date: 2022-07-13
Publication date: 2022-09-20
Anticipated expiration: 2042-07-13
Also published as: CN115083516B

Abstract

The application belongs to the technical field of student's information analysis, and particularly relates to a Panel design and evaluation method for detecting gene fusion based on a targeted RNA sequencing technology.

Description

Panel design and evaluation method for detecting gene fusion based on targeted RNA sequencing technology

Technical Field

The application belongs to the technical field of biogenic analysis, and particularly relates to a method for designing and evaluating Panel based on gene fusion detection by a targeted RNA sequencing technology.

Background

Gene fusion (gene fusion) refers to the fusion of partial or complete sequences of two different genes together to form a new gene due to some mechanism (such as genomic variation) (fig. 1). The fusion gene has important significance for clinical diagnosis, drug treatment and prognosis. The fusion gene is represented by the connection of two gene exons on the front and the back on the RNA level, and the fusion site is relatively fixed, so the fusion gene is not limited by an intron probe during detection, more new fusion types can be found, and the sensitivity is higher.

RNA is transcribed from DNA, and due to complex transcriptional modification processes such as alternative splicing (FIG. 2), there may be multiple transcript sequences in a gene, and different transcripts have differences in exon composition, which may result in different transcripts producing different functional protein products. In order to enrich multiple transcripts of a target gene, the traditional design idea is to combine exon regions of all transcripts of the gene, and design based on genome sequence, and the method has the following problems: on the one hand, as shown in fig. 2, when the exon composition of different transcripts is similar, there are a large number of regions that can be covered by the same set of probes, resulting in redundancy of probe coverage, thereby increasing cost; on the other hand, as shown in FIG. 3, if an exon region is short, probes with sufficient binding length are not designed, and only indirect coverage by adjacent exon probes is needed, which may result in missed fusion.

The existing RNA probe capture performance evaluation has great difficulty: the RNA capture library of the sample is easily influenced by gene expression quantity, the sequencing depth of high-expression genes is high, the sequencing depth of low-expression genes is low, and a reasonable evaluation result of probe capture performance cannot be obtained; although the gDNA capture library can exclude the influence of different gene expression amounts on the probe indexes, the RNA probe is a discontinuous region on the genome, so that the gDNA library cannot be effectively captured by a shorter exon region, and whether the probe is uniformly captured to each targeted region cannot be evaluated.

In summary, the design of the target RNA fusion detection Panel is influenced by limited probe binding due to the short length of the exon and redundant probe coverage due to the same exon of different transcripts. Meanwhile, the evaluation of probe capture performance is affected by the expression levels of different genes, and gDNA cannot effectively evaluate a shorter exon coverage area.

In view of this, the present application is specifically made.

Disclosure of Invention

Aiming at the technical problems, the design method for detecting the Panel through targeted RNA gene fusion is developed based on an NGS platform, probe enrichment effect evaluation is carried out by combining RNA and a gDNA capture library, and scientificity and rationality of design and capture performance evaluation of the Panel through targeted RNA fusion gene detection are guaranteed.

The application firstly provides a design method for detecting Panel by gene fusion based on a targeted RNA sequencing technology, which comprises the following steps:

1) determining a candidate gene;

2) determining the longest transcript of each gene according to the annotation information of the candidate gene structure, and performing probe coverage on all CDS regions of the longest transcript; if the untranslated region UTR region has gene fusion with definite clinical significance, probe coverage is carried out on the untranslated region UTR region;

3) and according to the gene structure annotation information of the candidate genes, comparing the CDS of the non-longest transcript corresponding to each gene with the CDS of the longest transcript one by one, if the CDS is different, reserving the corresponding CDS, and performing probe coverage.

4) For the candidate genes containing special type gene fusion, probe coverage is further carried out on the region near the breakpoint of the special type gene fusion, and the detection sensitivity is increased.

5) And designing probes based on the coverage of the probes, obtaining the bed files of the capture intervals, and assembling the gene fusion detection Panel.

Further, if the CDS sequence reserved in the step 3) is not long enough to bind to the probe, the sequence is externally amplified to an upstream CDS and a downstream CDS so that the probe has enough binding length;

further, the specific types of gene fusions in 4) include, but are not limited to: MET exon14 skiping, AR-V7, EGFR vIII, EGFR KDD.

The application also relates to a data analysis method for evaluating the probe capture performance, which comprises the following steps:

1) constructing a library for a sample by using the gene fusion detection Panel prepared by the method to obtain a corresponding gDNA capture library and an RNA capture library, and respectively counting the sequencing depth of a probe coverage area by taking an uncaptured rRNA strand-specific library (rRNA-truncated total RNA library) as a reference;

2) the enrichment factor FC of the sample at each exon was calculated, and at the same time, the lower quartile LQ of all exon enrichment factors was calculated. The enrichment factor FC is: the ratio of the sequencing depth of the target RNA library in each exon of the same sample to the sequencing depth of a de-rRNA strand specific library (rRNA-deplated total RNA library) without probe capture under a unit sequencing data volume;

FC＝(target RNA depth/raw data)/(RNA depth/raw data)

3) calculating the relative sequencing depth RD of the sample at each exon to obtain a DNA sample score gScore and an RNA sample score rScore;

the relative sequencing Depth RD is the sequencing Depth Raw Depth of each bed interval divided by the Median Depth of the sequencing depths of all the bed intervals of the sample;

RD＝(bed Raw Depth)/(sample bed Median Depth)；

determining a composite score, eScore, based on gsore and rsore;

eScore＝max(gScore,rScore)。

further, in the step 2), if the enrichment factor FC is greater than the lower quartile LQ of all exon enrichment factors, it indicates that the exon probe has a better capture performance, and is not included in the evaluation range.

Further, in the step 3), for the interval with the exon length of more than 120bp, the eScore is the larger value of the two exons gScore and rScore, and for the interval with the exon length of less than 120bp, the eScore is the maximum value of the two adjacent exons gScore of the gScore and the rScore;

further, in the above 3), when the eScore > -0.2, it indicates that the capture performance in the gDNA or RNA sample is better in this interval.

The application also relates to a probe capture performance evaluation system, which comprises a module for executing the steps of any one of the methods.

The present application also relates to a computer-readable medium, in which a computer program is stored, which computer program, when being executed by a processor, is adapted to carry out any of the above-mentioned methods.

The application also relates to an electronic device comprising a processor and a memory, wherein one or more readable instructions are stored on the memory, and when executed by the processor, the one or more readable instructions implement any of the above methods.

The beneficial technical effect of this application:

1) according to the method, a set of comprehensive and simplified RNA level gene fusion Panel design strategy is constructed, each transcript can be effectively covered, meanwhile, redundant probes covering consistent regions repeatedly are removed, and the sensitivity of clinical key fusion detection is improved.

2) The application solves the difficulty in the evaluation of the capture performance of the RNA level gene fusion probe by combining the evaluation algorithm of the eSacre of gDNA and RNA.

Drawings

In order to more clearly illustrate the detailed description of the present application or the technical solutions in the prior art, the drawings needed to be used in the detailed description of the present application or the prior art description will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1, schematic representation of gene fusion;

FIG. 2, schematic of alternative splicing;

FIG. 3 is a diagram showing the design scheme of the capture region of the conventional gene fusion gene for detecting RNA level;

FIG. 4 is a schematic view of coverage extension;

FIG. 5, result of shorter exon coverage;

FIG. 6 is a supplementary area coverage result graph;

FIG. 7 is a graph showing the result of sequencing depth of partial exon in the MET gene;

FIG. 8 is a graph showing the results of sequencing depth of partial exons of AR gene;

FIG. 9, fold enrichment for probe coverage.

Detailed Description

The technical solutions of the present application will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The following terms or definitions are provided solely to aid in the understanding of the present application. These definitions should not be construed to have a scope less than understood by those skilled in the art.

Unless defined otherwise below, all technical and scientific terms used in the detailed description of the present application are intended to have the same meaning as commonly understood by one of ordinary skill in the art. While the following terms are believed to be well understood by those skilled in the art, the following definitions are set forth to better explain the present application.

As used in this application, the terms "comprising," "including," "having," "containing," or "involving" are inclusive or open-ended and do not exclude additional unrecited elements or method steps. The term "consisting of …" is considered to be a preferred embodiment of the term "comprising". If in the following a certain group is defined to comprise at least a certain number of embodiments, this should also be understood as disclosing a group which preferably only consists of these embodiments.

Where an indefinite or definite article is used when referring to a singular noun e.g. "a" or "an", "the", this includes a plural of that noun.

The terms "about" and "substantially" in this application denote the interval of accuracy that a person skilled in the art can understand while still guaranteeing the technical effect of the feature in question. The term generally denotes a deviation of ± 10%, preferably ± 5%, from the indicated value.

Furthermore, the terms first, second, third, (a), (b), (c), and the like in the description and in the claims, are used for distinguishing between similar elements and not necessarily for describing a sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances and that the embodiments described herein are capable of operation in other sequences than described or illustrated herein.

According to some aspects of the present application, the present application relates to a method for designing gene fusion detection Panel based on a targeted RNA sequencing technology, which comprises the following steps:

1) determining a candidate gene;

2) determining the longest transcript of each gene according to the annotation information of the candidate gene structure, and performing probe coverage on all CDS regions of the longest transcript; if the region UTR region has gene fusion with definite clinical significance, probe coverage is carried out on the region UTR region;

4) For the candidate gene containing the special type gene fusion, the probe coverage is further carried out on the region near the breakpoint of the special type gene fusion so as to increase the detection sensitivity.

5) Gene fusion detection Panel was based on probe preparation.

In some embodiments, the CDS sequence retained in 3) is extended to the upstream and downstream CDSs if not long enough to bind to the probe, so that the probe has sufficient binding length;

in some embodiments, the specific type of gene fusion in 4) includes, but is not limited to: MET exon14 skiping, AR-V7, EGFR vIII, EGFR KDD.

According to some aspects of the present application, the data analysis method for probe capture performance evaluation of the present application comprises the following steps:

1) constructing a library for a sample by using the gene fusion detection Panel prepared by the method to obtain a corresponding gDNA capture library and an RNA capture library, and respectively counting the sequencing depth of a probe coverage area by taking an uncaptured rRNA-depleted total RNA library as a reference;

2) the enrichment factor FC of the sample at each exon was calculated, and at the same time, the lower quartile LQ of all exon enrichment factors was calculated. The enrichment factor FC is: under the unit sequencing data quantity, the ratio of the sequencing depth of the target RNA library in each exon of the same sample to the sequencing depth of the rRNA-deplated total RNA library which is not captured by the probe;

FC＝(target RNA depth/raw data)/(RNA depth/raw data)

3) calculating the relative sequencing depth RD of the sample at each exon to obtain a DNA sample score gScore and an RNA sample score rScore; the relative sequencing Depth RD is the sequencing Depth of each exon, Raw Depth, divided by the Median Depth of all exon sequencing depths of the sample;

RD＝(bed Raw Depth)/(sample bed Median Depth)；

determining a composite score, eScore, based on gsore and rsore;

eScore＝max(gScore,rScore)。

in some embodiments, the 2) is not included in the evaluation range if the fold enrichment FC is greater than the lower quartile LQ of all exon fold enrichments, indicating that the exon probe capture performance is better.

In some embodiments, the 3) is the larger of gScore and rScore for the interval with exon length greater than 120bp, and the maximum of gScore and rScore for the interval with exon length less than 120 bp;

in some embodiments, the 3) indicates that the interval has better capture performance in gDNA or RNA samples when eScore > -0.2.

Embodiments of the present application will be described in detail below with reference to examples, but those skilled in the art will appreciate that the following examples are only illustrative of the present application and should not be construed as limiting the scope of the present application. The examples, in which specific conditions are not specified, were conducted under conventional conditions or conditions recommended by the manufacturer. The reagents or instruments used are not indicated by manufacturers, and are all conventional products available on the market.

Experimental examples the method and System establishment of the present application

1. Panel design method

Based on hg19 reference genome and annotated transcript information, the design method was as follows:

1) determining candidate genes according to purposes;

2) determining the longest transcript of each gene according to a gene structure annotation file (such as Ensembl, release-75, http:// ftp. Ensembl. org/pub/grch37/), performing probe coverage on all CDS regions of the longest transcript, and supplementing a UTR region if the UTR region (untranslated region) has definite clinical fusion;

3) the CDS of the non-longest transcripts corresponding to the gene are compared with the region reserved in 1) one by one for difference, if there is a difference, the corresponding CDS is reserved, as shown in FIG. 4, for the CDS sequence of the supplemented non-longest transcript, if the length is shorter, the CDS sequences are externally amplified to the upstream and downstream CDS, so that the probe has enough binding length.

4) For the particular type of intragenic fusion tested: taking MET exon14 skiping and AR-V7 as examples, on the basis of the above design strategy, probe coverage is carried out near the fusion breakpoint of the specific detection region so as to increase the detection sensitivity.

2. Probe evaluation method

Data analysis for probe capture performance evaluation (taking leukocyte samples as an example):

1) based on the method, WBC samples are respectively subjected to library building, the sequencing depth of a probe coverage area is respectively counted for the obtained gDNA capture library, RNA capture library (target RNA) and the uncaptured rRNA-truncated total RNA library, and the uncaptured rRNA-truncated total RNA library is used as a contrast.

2) And (3) calculating the enrichment factor FC of the sample in each exon, namely the ratio of the sequencing depth of the target RNA library in each exon of the same sample to the sequencing depth of the rRNA-deplated total RNA library which is not captured by the probe under the unit sequencing data volume. Meanwhile, the lower quartile LQ of all exon enrichment multiples was calculated. If the enrichment multiple is greater than the lower quartile LQ of all exon enrichment multiples (the determination of the value is shown in FIG. 9, and it can be seen from the figure that the lower quartile LQ of all FC values can obviously distinguish abnormal values with lower enrichment multiples, so the value is set as a filtering threshold value in the present application), when the value is greater than the threshold value, the probe capture performance of the exon interval is better, and the exon interval is not included in the subsequent evaluation range any more;

the FC is target (RNA depth/rawdata)/(RNA depth/rawdata).

3) And calculating the relative sequencing Depth RD of the sample in each bed interval, namely dividing the sequencing Depth Raw Depth of each bed interval by the Median Depth of the sequencing Depth in all exon of the sample, wherein the gScore and the rScore are the relative sequencing depths of the DNA sample and the RNA sample respectively. For the interval with the exon length of more than 120bp, the eSCore is the larger value of the gScore and the rScore, and for the interval with the exon length of less than 120bp, the eSCore is the maximum value of the gScore, the rScore and the gScore of the adjacent exons at two ends according to the principle that the probe is continuously laid on an RNA sequence. The eScore > -0.2 sample, indicating that the interval is at least better for capture in gDNA or RNA samples.

RD＝(bed Raw Depth)/(sample bed Median Depth)；

gScore＝RD(gDNA)；

rScore＝RD(RNA)；

eScore＝max(gScore,rScore)。

Example 1 data simulation

Panel capture region design results and comparisons with conventional designs

This example utilized the Panel design method described above in this application. Based on hg19 reference genome and gene structure annotation information, 329 transcript sequences of 148 genes are finally obtained, 1852 exon regions on the genome are covered, all transcript regions of the genes are covered, the reliability of hybridization capture and the sensitivity of fusion detection are ensured, and by removing redundant probes repeatedly covering consistent sections, the coverage of each transcript is more reasonable, the probe utilization rate is improved, and the cost is reduced.

Probes are designed according to the exon of all transcripts of 148 genes, the comparison result of each index with the traditional method is shown in the table 1, the coverage area of the probes laid by the traditional design method is 1,777,265bp, and after the probes are simplified according to the method, the probe area laid is only 372,151bp, and 79% of redundant sequences are removed.

Table 1Panel coverage area comparison

Example 2 Probe coverage Performance evaluation

1) Evaluation results show that shorter exon coverage is better: as shown in FIG. 5, the No. 3 exon of the gene GOPC is only 24bp (NM-020399), but the capture result shows that the exon coverage is better and is consistent with the exon coverage level at two ends; at the same time, the exon coverage of the supplemented non-longest transcript was also better, as shown in fig. 6, the gene NRG1, the supplemented transcript NM — 001159996, the exon length of which is 40bp, still had better coverage depth after supplementation.

2) The probe added aiming at the special fusion form has better coverage effect: as shown in fig. 7, for the MET exon14 skiping jump event, the capture regions of exon13-exon15 were added, so that it can be clearly seen that the coverage depth of exon12, exon13, exon15, exon16 is significantly higher than that of the other exon. Similarly, when designing a probe for AR-V7(exon4-8 deletion), the probe is additionally added to exon3-3 'UTR, and FIG. 8 shows the coverage depth of part of exon in the AR gene, and it can be seen that the coverage depth of exon2, exon3, exon8 and 3' UTR is obviously higher than that of other exons. The 2 probe capture area designs aiming at the special rearrangement type can ensure better coverage near a special site, thereby increasing the sensitivity of detecting the special fusion type.

Example 3 evaluation of Probe Capture Performance

The higher the enrichment factor, the better the capture performance of the probe, fig. 9 is a distribution diagram of the enrichment factor in the coverage interval of the probe, and the lower quartile FQ of the enrichment factor FC in all intervals is 322, i.e., the enrichment factor in the interval of 75% or more is 322 or more. For the region with low enrichment factor, the rScore is further evaluated by using three indexes of gScore, rScore and eScore, the rScore is easily affected by the expression amount, the capture performance of the probe in the interval cannot be evaluated by the rScore for the gene with partial non-expression or low expression amount, the gScore is affected by the length of the exon when being evaluated, the eScore is the evaluation result combining the rScore and the gScore, and the effective evaluation result can be obtained in the interval of 99.78% (1848) when the cut off of the eScore is set to be 0.2, which is far higher than 94% (1741) of the rScore and 98.38% (1822) of the gScore.

The foregoing descriptions of specific exemplary embodiments of the present application have been presented for purposes of illustration and description. It is not intended to limit the application to the precise form disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiments were chosen and described in order to explain certain principles of the present application and its practical application to enable one skilled in the art to make and use various exemplary embodiments of the present application and various alternatives and modifications thereof. It is intended that the scope of the application be defined by the claims and their equivalents.

Claims

1. A design method for detecting Panel by gene fusion based on a targeted RNA sequencing technology is characterized by comprising the following steps:

1) determining a candidate gene;

2) determining the longest transcript of each gene according to the candidate gene structure annotation file, and performing probe coverage on all CDS regions of the longest transcript; preferably, if the untranslated region UTR region has a gene fusion of clear clinical significance, probe coverage is performed on the untranslated region UTR region;

3) according to the gene structure annotation information of the candidate genes, the CDS of the non-longest transcript corresponding to each gene is compared with the CDS of the longest transcript one by one in a difference mode, if the CDS is different, the corresponding CDS is reserved, and probe coverage is carried out;

4) for the candidate genes containing special type gene fusion, further performing probe coverage on the region near the breakpoint of the special type gene fusion;

2. The method of claim 1 wherein the CDS sequence retained in 3) is extended to the upstream and downstream CDS if not long enough to bind to the probe, so that the probe has sufficient binding length;

3. the method of claim 1, wherein the specific type of gene fusion in 4) includes but is not limited to: MET exon14 skiping, AR-V7, EGFR vIII, and EGFR KDD.

4. A data analysis method for evaluating probe capture performance is characterized by comprising the following steps:

1) performing library construction on a sample by using gene fusion detection Panel prepared by the method of any one of claims 1 to 4 to obtain corresponding gDNA capture libraries and RNA capture libraries, and simultaneously counting the sequencing depth of a probe coverage area by taking an uncaptured rRNA chain-specific library as a control;

2) according to the position information stored in the bed file, calculating the enrichment multiple FC of the sample in each exon and the lower quartile LQ of all exon enrichment multiples; the enrichment factor FC is the ratio of the sequencing depth of a target RNA library in each exon of the same sample to the sequencing depth of a de-rRNA strand specific library which is not captured by a probe under the unit sequencing data volume:

FC＝(target RNA depth/raw data)/(RNA depth/raw data)；

3) calculating the relative sequencing depth RD of the sample in each bed interval to obtain a DNA sample score gScore and an RNA sample score rScore;

the relative sequencing Depth RD is the sequencing Depth of each exon, Raw Depth, divided by the Median Depth of all exon sequencing depths of the sample;

RD＝(bed Raw Depth)/(sample bed Median Depth)；

determining a composite score, eScore, based on gsore and rsore;

eScore＝max(gScore,rScore)。

5. the method according to claim 4, wherein in the step 2), when a certain exon enrichment factor FC is larger than the lower quartile LQ of all exon enrichment factors, the exon probe capture performance is better and is not included in the evaluation range.

6. The method according to claim 4, wherein in 3), the eSCore is the larger of gScore and rScore for the interval with the exon length larger than 120bp, and the eSCore is the maximum of gScore and gScore of adjacent exons at two ends of rScore for the interval with the exon length smaller than 120 bp;

7. the method according to claim 4, wherein in 3), when eSCore > -0.2, the interval has better capture performance in gDNA or RNA samples.

8. A probe capture performance evaluation system comprising means for performing the steps of the method of any one of claims 4 to 7.

9. A computer-readable medium, in which a computer program is stored which, when being executed by a processor, carries out the method of any one of claims 1 to 7.

10. An electronic device comprising a processor and a memory, the memory having stored thereon one or more readable instructions that, when executed by the processor, implement the method of any of claims 1-7.