CN115323060B - Fish nuclear gene molecular marker primer, molecular marker and molecular marker database - Google Patents
Fish nuclear gene molecular marker primer, molecular marker and molecular marker database Download PDFInfo
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Abstract
The invention discloses a fish universal nuclear gene molecular marker primer, a molecular marker and a molecular marker database, wherein the molecular marker primer comprises one or more of primers shown as SEQ NO. 1-SEQ NO. 328. The invention utilizes 132 fish whole genome data comparison to screen 82 universal nuclear gene molecular markers, and the designed molecular marker primer set has a whole PCR success rate of up to 80%. According to the invention, a large number of universal nuclear gene molecular markers are screened, so that on one hand, the protection of germplasm resources is facilitated, on the other hand, a fish nuclear gene database can be constructed and phylogenetic tree and classification can be constructed on the basis of the molecular markers, so that the rapid germplasm identification of fish is realized, and the problems of time consumption, labor consumption and high cost in the prior art are reduced on the premise of ensuring the accuracy. The method can be used for analyzing the evolutionary origin of fish, and the like, providing data support and promoting the genetic evolutionary research of related fish.
Description
Technical Field
The invention relates to obtaining a fish nuclear gene marker and a molecular marker database, in particular to obtaining a fish nuclear gene molecular marker and establishing a gene database, and more particularly relates to a fish nuclear gene molecular marker primer, a molecular marker and a molecular marker database.
Background
With the technical development of genomics, more and more fish genomes and transcriptomes are measured worldwide, and the exploitation of universal nuclear gene molecular markers by utilizing numerous fish genomes becomes a very effective means. RAG1 has been a widely used nuclear gene molecular marker so far, mainly because it can be easily amplified by PCR in vertebrates and also has a better phylogenetic resolution. However, the nuclear gene molecular marker data which are common to RAG1 are very few. In recent years, many students have performed many similar works. For example, li et al (Li et al 2007) selected 10 molecular marker primers suitable for teleosts based on the whole genome sequences of two fish (zebra fish and globefish). Townsend et al (Townsend et al 2008) used comparative data of puffer fish and human genome, chickens, obtained 26 molecular markers for scaly species. Fong and Fujita (Fong and Fujita 2011) reported research efforts to develop 75 nuclear gene molecular markers for vertebrates. However, the above work was carried out by comparing 2-3 existing species genome data, and the success rate of PCR in the study group with far relatedness was lower. Shen et al (2011) used multi-species genome alignment data for nuclear-encoded gene molecular marker screening and summarized a set of simple, efficient and automated nuclear gene molecular marker screening methods. But if large sample multi-species are involved, a significant amount of money, time and labor is required.
Although recent molecular system development studies have developed a number of independent nuclear gene molecular markers, they have group-specificity and are generally not widely applicable to research in the fields of specific fish germplasm resource protection and the like. Therefore, there is still more vacancy in the universal nuclear gene molecular marker for fish, and there is a need for a new universal nuclear gene molecular marker for fish and a set thereof to achieve the effect of identifying fish germplasm resources.
Disclosure of Invention
The invention aims to overcome at least one defect of the prior art, provides a fish nuclear gene molecular marker primer, a molecular marker and a molecular marker database, is favorable for protecting germplasm resources, rapidly carries out germplasm identification, is also convenient for analyzing the evolution origin relationship of fish, and promotes research of fish inheritance and evolution direction.
The group of finfish (actinomycetes) records over 34,000 species, dominant in vertebrates. In the past 4 hundred million years of evolution history, finfish have evolved an extraordinary diversity in morphology and ecology. Many have attempted to solve the phylogenetic problem at different taxonomic levels, from the traditional Sanger sequencing using 20 genetic markers to the genome-scale approach. However, despite the use of hundreds or thousands of labels, some high-level relationships remain elusive or consensus. Transcriptome sequencing is fast and simple, but requires fresh samples and is therefore not suitable for ethanol preservation or drying of samples. In addition, the problems of multiple isoforms, differences in gene expression in different tissues or life stages, and the like, also make orthologous identification difficult. The sequence capture method requires much less sample quality and is even applicable to highly degraded DNA. However, sequence capture efficiency is strongly affected by probe-to-target DNA sequence differences.
Given that finfish is a highly diverse and ancient population, it may be difficult to design universal capture probes and to effectively capture sequences in the highly differentiated lineage. Large scale studies typically require multiple probe sets tailored to different lineages, which greatly increases the budget of probe synthesis. Furthermore, these genomic methods require expensive equipment and many fish scientists around the world may still not be burdened with next generation sequencing. Furthermore, many studies do not require hundreds to thousands of markers; based on empirical and simulated data, 20 to 50 loci are generally sufficient to accurately restore well-resolved phylogenetic development. One approach to solving these problems is to restore the traditional PCR-based approach, which can be performed in almost every molecular laboratory. Downstream data analysis is simple and can be handled by many researchers. The main disadvantage of using this traditional approach in fish phylogenetic is that PCR on many loci and many samples requires a lot of labor (because the success rate of PCR is often unpredictable), and that the design of universal PCR primers, standard Sanger sequencing, is costly.
However, by carefully selecting the optimal number of phylogenetic information markers, using many publicly available fish genomes and transcriptomes to design universal PCR primers with high PCR success rates, and then sequencing large numbers of PCR products, these drawbacks can be largely overcome. If necessary, by next generation sequencing. The universal nuclear gene molecular marker for fish can achieve the effects and overcome the problems, and the invention provides a group of nuclear protein coding sites (NPCL) with rich information so as to bridge the gap between the traditional marker sequencing and the more advanced high-throughput method.
In more than one embodiment, single copy NPCL is identified from 132 fish genomes, and PCR amplification rates of 203 species of 31 finfish orders are further screened according to the specificity of PCR primers and the PCR amplification rates, so that 82 markers are finally obtained. In combination with homologous genes identified from the genomes and transcriptomes of other fish species, our phylogenetic analysis yields resolution comparable to phylogenetic studies using hundreds of markers, and by introducing new taxonomic groups, can provide new clues for phylogenetic development of certain lineages. Thus, in addition to the high-throughput approach, our 82 NPCL markers provide an alternative approach to perform phylogenetic project studies of various fish branches, and new strategies for fish germplasm resource identification.
The technical scheme adopted by the invention is that the fish universal nuclear gene molecular marker primer comprises one or more of primers shown as SEQ NO.1-SEQ NO. 328.
Further, one or more primer pairs of NP 1-NP 82 are included, wherein primer pair NP1 is shown as SEQ NO.1-SEQ NO.4, primer pair NP2 is shown as SEQ NO.5-SEQ NO.8, primer pair NP3 is shown as SEQ NO.9-SEQ NO.12, primer pair NP4 is shown as SEQ NO.13-SEQ NO.16, primer pair NP5 is shown as SEQ NO.17-SEQ NO.20, primer pair NP6 is shown as SEQ NO.21-SEQ NO.24, primer pair NP7 is shown as SEQ NO.25-SEQ NO.28, primer pair NP8 is shown as SEQ NO. 29-32, primer pair NP9 is shown as SEQ NO.33-SEQ NO.36, primer pair NP10 is shown as SEQ NO. 37-40, primer pair NP11 is shown as SEQ NO. 41-44, primer pair NP12 is shown as SEQ NO.45-SEQ NO.48, primer pair NP7 is shown as SEQ NO.25-SEQ NO.28, primer pair NP9 is shown as SEQ NO. 14-52, primer pair NP9 is shown as SEQ NO.52, primer pair NP15 is shown as SEQ No.57-SEQ No.60, primer pair NP16 is shown as SEQ No.61-SEQ No.64, primer pair NP17 is shown as SEQ No.65-SEQ No.68, primer pair NP18 is shown as SEQ No.69-SEQ No.72, primer pair NP19 is shown as SEQ No.73-SEQ No.76, primer pair NP20 is shown as SEQ No. 77-80, primer pair NP21 is shown as SEQ No. 81-84, primer pair NP22 is shown as SEQ No. 85-88, primer pair NP23 is shown as SEQ No. 89-92, primer pair NP24 is shown as SEQ No. 93-96, primer pair NP25 is shown as SEQ No.97-SEQ No.100, primer pair NP26 is shown as SEQ No. 101-104, primer pair NP27 is shown as SEQ No. 105-108, primer pair NP28 is shown as SEQ No. 85-109, primer pair NP29 is shown as SEQ No. 116-112, primer pair NP30 is shown as SEQ No.117-SEQ No.120, primer pair NP31 is shown as SEQ No.121-SEQ No.124, primer pair NP32 is shown as SEQ No.125-SEQ No.128, primer pair NP33 is shown as SEQ No.129-SEQ No.132, primer pair NP34 is shown as SEQ No.133-SEQ No.136, primer pair NP35 is shown as SEQ No.137-SEQ No.140, primer pair NP36 is shown as SEQ No.141-SEQ No.144, primer pair NP37 is shown as SEQ No.145-SEQ No.148, primer pair NP38 is shown as SEQ No. 149-152, primer pair NP39 is shown as SEQ No.153-SEQ No.156, primer pair NP40 is shown as SEQ No.157-SEQ No.160, primer pair NP41 is shown as SEQ No. 161-164, primer pair NP42 is shown as SEQ No. 165-168, primer pair NP43 is shown as SEQ No. 145-172, primer pair NP44 is shown as SEQ No. 180-169, primer pair NP46 is shown as SEQ No.179-SEQ No.184, primer pair NP47 is shown as SEQ No.185-SEQ No.188, primer pair NP48 is shown as SEQ No.189-SEQ No.192, primer pair NP49 is shown as SEQ No.193-SEQ No.196, primer pair NP50 is shown as SEQ No.197-SEQ No.200, primer pair NP51 is shown as SEQ No.201-SEQ No.204, primer pair NP52 is shown as SEQ No.205-SEQ No.208, primer pair NP53 is shown as SEQ No. 209-212, primer pair NP54 is shown as SEQ No. 213-216, primer pair NP55 is shown as SEQ No.217-SEQ No.220, primer pair NP56 is shown as SEQ No.221-SEQ No.224, primer pair NP57 is shown as SEQ No. 225-228, primer pair NP58 is shown as SEQ No. 229-232, primer pair NP53 is shown as SEQ No.209-SEQ No.212, primer pair NP54 is shown as SEQ No.236 and primer pair NP 60-240 is shown as SEQ No.240, primer pair NP61 is shown as SEQ No. 241-244, primer pair NP62 is shown as SEQ No. 245-248, primer pair NP63 is shown as SEQ No. 249-252, primer pair NP64 is shown as SEQ No. 253-256, primer pair NP65 is shown as SEQ No. 257-260, primer pair NP66 is shown as SEQ No. 261-264, primer pair NP67 is shown as SEQ No. 265-268, primer pair NP68 is shown as SEQ No. 269-272, primer pair NP69 is shown as 273-276, primer pair NP70 is shown as SEQ No. 277-280, primer pair NP71 is shown as SEQ No. 281-284, primer pair NP72 is shown as SEQ No. 285-288, primer pair NP73 is shown as 289-292, primer pair NP74 is shown as SEQ No. 261-264, primer pair NP67 is shown as SEQ No. 265-268, primer pair NP68 is shown as SEQ No.328, primer pair NP70 is shown as SEQ No. 277-280, primer pair NP71 is shown as SEQ No.328, primer pair NP70 is shown as SEQ No.328, primer pair NP No.37 is shown as SEQ No.328, primer pair NP37 is shown as SEQ No.37, primer pair NP37 is shown as SEQ No. 75, primer pair NP37 is shown as SEQ No.37, primer pair NP No. 75 is shown as SEQ No.37, and primer pair NP is shown as SEQ No. 37.
The invention also aims to provide a fish universal nuclear gene molecular marker which is formed by amplifying the molecular marker primer set.
The invention also aims to provide a fish universal nuclear gene molecular marker database which comprises the fish universal nuclear gene molecular marker.
The invention also aims to provide the application of the fish universal nuclear gene molecular marker primer, the fish universal nuclear gene molecular marker and the fish universal nuclear gene molecular marker database in germplasm resource protection. Further, the use of the kit for preparing a reagent for identifying fish germplasm resources and categories is provided.
Another object of the present invention is to provide a species identification method of fish, comprising the steps of:
a1, obtaining DNA of a fish to be identified;
a2, carrying out PCR amplification by the primer of claim 1;
a3, carrying out high-throughput sequencing on the PCR amplification product obtained in the A2, comparing the PCR amplification product with the universal nuclear gene molecular marker database of the fish according to the claim 4, and obtaining species information of the fish to be identified according to molecular markers matched with the fish to be identified in the molecular marker database and a phylogenetic classification tree established on the basis of the molecular marker database.
The invention also provides a kit comprising the above-mentioned fish-versatile nuclear gene molecular marker and/or the above-mentioned fish-versatile nuclear gene molecular marker primer. Further, the kit also comprises reagents required by the PCR amplification system of the universal fish nuclear gene molecular marker primer.
Still another object of the present invention is to provide a phylogenetic model constructed by the above-mentioned fish universal nuclear gene molecular marker primer, fish universal nuclear gene molecular marker and/or fish universal nuclear gene molecular marker database. Further, a phylogenetic tree is included
The screening method of the universal nuclear gene molecular marker database for fishes comprises the following steps:
(1) The similarity comparison is carried out on all the gene sequences of 132 fishes of the disclosed genome sequences, the comparison method is blastn (version 2.10.1+), the comparison method is blastn, and the maximum expected value is set to be 1e -10 If non-unique alignment occurs, selecting an optimal alignment sequence; screening candidate genes according to the following criteria according to the comparison result: more than 80% of species can detect the same similar sequence, and more than 60% of species in the species which are required to be correlated have a comparison length of more than or equal to 1000bp;
(2) Adopting a multi-sequence comparison strategy to perform multi-sequence comparison on the homologous gene set established in the step (1), wherein comparison software is mafft (v 7.475), and screening conserved segments among genes according to the multi-sequence comparison result; according to the multi-sequence comparison result, counting the positions of the first non-blank comparison base and the last non-blank comparison base of each gene sequence, converting the positions into position units of 100bp, and respectively taking the position with the largest gene quantity as a candidate conservation section; performing multi-sequence comparison on the selected conserved regions by using mafft (v 7.475), screening the conserved regions, and counting the lengths of the conserved regions of all species to obtain the length range of the conserved regions of each gene;
(3) According to the multi-sequence comparison result, a primer3 software is combined to select a conserved region to design a nested PCR primer, the primer design selects the conserved region, particularly, the conservation of the 3 'end is required to be controlled, the 3' end does not contain degenerate bases, the amplification length is controlled within the range of 1.0-1.5 Kb, the GC proportion is controlled within the range of 40% -70%, the primer length is controlled within the range of 20 bp-50 bp, the designed primer is compared again with the gene sequence, and the amplification success rate of the primer and the accuracy rate of site binding are evaluated;
(4) Respectively carrying out similarity comparison on the designed nested PCR primer and other genes of the gene family, if the similarity between the PCR primer and other non-target sequences is higher than 95%, considering the redesigned primer, and if a proper region cannot be found for redesign, not considering the gene sequence;
(5) In order to take the purpose as a unit, a plurality of species are randomly selected from different purposes to carry out PCR experiments, the PCR products are subjected to high-throughput sequencing, and sequencing fragments are assembled.
Compared with the prior art, the invention has the beneficial effects that: the invention utilizes the comparison of 132 fish genome data to screen 82 universal nuclear gene molecular markers, and the overall PCR success rate of the primers designed correspondingly is up to 80%. According to the invention, a large number of universal nuclear gene molecular markers are screened, so that on one hand, the protection of germplasm resources is facilitated, on the other hand, a fish nuclear gene database can be constructed and a phylogenetic tree and classification can be constructed on the basis of the molecular markers, so that the rapid germplasm identification of fish is carried out in time, and the problems of time consumption, labor consumption and high cost in the prior art are reduced on the premise of ensuring the accuracy. The method can be used for analyzing the evolutionary origin of fish, and the like, providing data support and promoting the genetic evolutionary research of related fish.
Drawings
FIG. 1 shows the inter-ocular PCR amplification success rate (a) and FishPEI marker retrieval rate (b).
FIG. 2 shows genetic distances (percent distance) of 82 FishPIE markers at the mesh (blue), family (green) and genus (yellow) levels; genes have been ordered by genetic distance at the intergeneric level.
Fig. 3 shows a tree distance (normalized RF index) graph of an ML tree constructed by concatenating fishe flags one by one with a reference tree, showing a plateau at 40 flags.
FIG. 4 shows a mesh-grade backbone tree of finfish based on peptide sequence ML analysis; the numbers in brackets after the name of the mesh represent the number of families and species analyzed.
Fig. 5 shows an exemplary magnified view of the constructed authentication class diagram.
FIG. 6 shows the result of gel electrophoresis of PCR amplification products of kcnf and mab genes in example 3.
FIG. 7 shows the gel electrophoresis results of the NP11 and NP 12-labeled PCR amplification products of example 3.
FIG. 8 shows the gel electrophoresis results of the NP13 and NP14 labeling PCR amplification products of example 3.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
The invention will now be further illustrated with reference to specific examples, which are given solely for the purpose of illustration and are not to be construed as limiting the invention. The test specimens and test procedures used in the following examples include those (if the specific conditions of the experiment are not specified in the examples, generally according to conventional conditions or according to the recommended conditions of the reagent company; the reagents, consumables, etc. used in the examples described below are commercially available unless otherwise specified).
Example 1
1. Ortholog identification
To identify homologous genes, the genome of 132 fish species (as shown in Table 1) was first fragmented into 10kb sequences by iterating over a 5kb sliding window. The sequences of each species were then aligned with zebrafish genome (GCF_ 000002035.6) using BLASTN, with a maximum e value of 1e -10 The minimum alignment length is 1000bp.
Using a maximum e value of 1e -10 Is detected by a mutual best hit. Then reserve: (1) Orthologs located within annotated protein coding regions of the zebra fish genome, (2) exon length>1000bp, and (3) can be measured at 80%Matching was found in the test fish. A total of 2093 genes met the criteria described above.
2. Primer design
The sequences in each homolog were then aligned using MAFFT (ver 7.455). The conserved regions with the least number of gaps and the most conserved sites were calculated with a 25bp sliding step within a 50bp window using custom scripts.
According to the nested PCR strategy, the target PCR amplicon can be obtained efficiently, and the inventor designs two pairs of primers for the homologous sequences respectively.
The primers were selected based on the following criteria: (1) the primer should be located in a conserved region; (2) The 3' end of the primer must be particularly conserved and not contain ambiguous sites; (3) The target region should contain 40% -70% GC content and be >800bp in size; (4) the primer length should be between 20-40 bp. Primers were then mapped to the genomes of 132 fish and specificity assessed using BLASTN. Primers that match more than 95% of similarity to non-target regions, primers that have more than 80% of their primer length not identical to the target region >90%, and primers that show mismatches in the last three bases of the 3' end are considered to be non-specific.
The nested PCR primer sets for each ortholog were sequenced according to the number of species specific for the primers, and then 102 loci of the top primer set were selected as the fishe test primer set. The internal primers are indexed for PCR amplification.
3. Primer test
To examine the general applicability of the primers to the finfish (ray-finished fish), we performed primer tests on each of 102 sites from the 203 species of fish of 31 mesh. Wherein the fresh or ethanol preserved sample is from the national center for fresh water genetic resources, which is the collection of national aquatic organism samples and life specimens.
Genomic DNA of these species was extracted using a fish DNA extraction kit (cwbiotech, china). PCR was performed using the standard protocol of the kit, and the annealing temperatures are shown in Table 2. PCR success was assessed by gel electrophoresis on a 1% agarose gel. Successful PCR must produce a product that matches the predicted size, and in the case of non-specific priming, the band for the non-specific product must be less than 4, and the band is easily distinguishable, the concentration of the non-specific product must be low.
Equal amounts of PCR products of the same species were then pooled, fragmented and treated with Taq DNA polymerase for end repair, 5' phosphorylation and dA tailing, followed by addition of adaptors at both ends by T-a ligation. On the Illumina Hiseq 4000 platform, sequencing was performed using a 150bp opposite end sequencing method. The readings generated were assembled from multiple Kmer sizes, SOAPdenovo (ver 2.04) at default settings. Then we use a maximum e value of 1e -10 The resulting sequences were matched to the reference genome of the most closely related species (as shown in table 1). The selected orthologous sequences are considered to be the effective sequences for best hits. Finally, 82 NPCL are obtained as molecular markers (the NPCL marker sets obtained by screening form the FishPIE set, and the FishPIE set is described before and after), and the corresponding primer sequences are shown as SEQ ID NO. 1-SEQ ID NO. 328.
4. Testing NPCL markers for phylogenetic reconstruction
To examine the phylogenetic utility of selected loci to address phylogenetic relationships at different taxonomic levels, we obtained homologous sequences for these loci from genomic and transcriptomic data of NCBI SRA, thereby improving the taxonomic coverage of the dataset.
Genome sequencing reads were assembled using soapenovo2, transcriptomes were assembled using Trinity ver 2.8.5 (grabher et al 2011), using default parameters. Using a maximum e value of 1e -10 Mapping the resulting sequences to the reference genome of the most closely related species. The mutually optimal hits for the selected loci are considered to be effective sequences.
The potential paralogous sequences are then filtered by examining each gene tree. The gene tree was constructed by aligning the sequences of each selected locus using a MAFFT. Phylogenetic analysis was then performed using an IQtree2 ver 2.0.5 (Minh et al 2020) and an edge-related proportional partitioning model, ultra-fast pilot replication, and SH approximate likelihood ratio test of 1000 replicates.
The phylogenetic resolution of all orthologous markers was examined together. Selected homologous sequences were aligned again using MAFFT and aligned using a "gappyout" setting of trimAL ver 1.4.Rev15 (Capella-Gutierrez, silla-Martinez and Gabaldon, 2009). On nucleotide and polypeptide datasets, the best surrogate model for each marker was selected using IQtree2, respectively, followed by genotyping (same branching length but different evolution rates) and species tree reconstruction using the same software for 1000 ultrafast bootstraps. We use ExaBayes ver 1.5.1 for bayesian reasoning (run at least 10000 generations using four chains and ASDSF <5.00 ").
5. Evolution rate of FishPEI
To check the evolution rate we used the original pair-wise distance calculated by the dist.dna function of R-package ape as a proxy. We examined the average pairwise distances between the genera within one family, between the families within one mesh, and between the meshes within one group (taxonomic classification followed Rabosky et al).
6. Phylogenetic informative of the FishPEI marker set
To test if the number of markers in the fishe ie set is sufficient to produce reliable phylogenetic events, we examined if the phylogenetic tree converged to a similar topology as the number of markers increased. Since this analysis is very time consuming, we narrow the dataset by selecting only individuals with >50% sequenced markers and at most two representatives from one genus.
We then obtained consistency of phylogenetic signals between the fishe markers by calculating the tree distance (normalized RF index) between each nucleotide gene tree and the reference species tree using the rf.dist function of R package phasorn (Schliep, 2010). Gene trees are calculated using the default IQtree, while reference species are reconstructed using the connected dataset based on the same method. Then, we linked the FishPIE markers one by one according to the ascending order of normalized RF according to the respective gene trees, constructing a plurality of phylogenetic trees. The tree distance (normalized RF index) between the individual reconstructions and the reference species tree was calculated as described above.
7. Annotation of FishPEI markers
BLASTP based at 1e -10 E value cutoff of (c) searches the report and nr databases for a representative sequence for each ortholog. Genes were initially identified based on the best hits to the known sequences. And Gene function was inferred using KEGG, gene Ortology, PANTHER and KOG databases.
8. Results
1. Obtained FishPEI database
2093 single copy orthologs were identified in total from the genomes of 132 species, 102 of which were selected for primer design. 82 NPCL markers showed high PCR success (> 75%) in 203 species from 67 families and 31 targets. After trimming the primer sequences and the ambiguous regions, the average PCR product size for each tag ranged from 544 to 1143bp, with an average of 1051bp. The PCR products obtained by PCR of the 82 NPCL-labeled primer sets constitute a molecular marker database useful for sequence alignment and identification of fish germplasm resources.
We obtained orthologous sequences from the RNA-seq data (268 species), genome sequencing data (151 species) and assembled genome (132 species) of the public database. The trim alignment lengths of the 82 NPCL marker sequences in the combined dataset varied from 420 to 1244bp (average = 712 bp), totaling 58,383 bp, gc content ranging from 37.58% to 58.58% (average 47.66%) (table 3)). The number of conclusive information sites ranged from 113 to 602bp (Table 3).
The labels are functionally diverse. For example, in the panher database, 80 markers can be annotated to 74 gene families, where "teneurin and n-acetylglucosamine-1-phosphodiester α -n-acetylglucosamine enzyme", "voltage-gated potassium channel", "chondroitin synthase" and "serine/threonine-protein kinase" each comprise two markers, and where three markers are annotated as "PTHR24028: unnamed family). Gene ontology analysis showed that "biological processes", "molecular functions" and "cellular components" were associated with 65, 64 and 57 markers, respectively.
2. Broad application of FishPEI in classification
The PCR success rate of the fishe primer averaged 74.68% among 203 species using the nested PCR strategy. The PCR success rate was higher for species from the "imperial" group Otomorpha (81.1%) and euteleosporpha (71.4%) compared to species from the elosporpha (46.1%), ostomorpha (47.9%) and exogroup (47.0%). This is probably because most of the sequences used for primer design are from Otomorpha and euteleosporpha. Nonetheless, both of these queues cover over 96% of fish (Fricke et al, 2021). Thus, the FishPEI primer is widely applicable to all taxonomic groups.
3. Evolution rate of FishPEI at different classification levels
In selecting markers for phylogenetic analyses of different classification levels, the evolution rate (using genetic distance as a proxy) is one of the most important attributes, as it is the main determinant of resolution of phylogenetic reconstruction. Genetic distances of the FishPIE markers at the interocular, family and genus levels are shown in FIG. 2. At the interocular level, the genetic distance of 82 markers ranged from 2.52% to 14.47%, with an average of 6.70%; RAG1 is an NPCL marker widely used in fish phylogenetic analysis, and has a genetic distance of 6.81%. The genetic distance between the families is 1.48% -9.45%, and the average is 4.20%, while the genetic distance of RAG1 is 4.58%. At the intergeneric level, the genetic distance averages 1.88% (0.58% to 5.19%), whereas the genetic distance for RAG1 is 1.69%.
Thus, our fisheie markers provide a comparable rate of evolution to the widely used markers, and thus can provide a great deal of information for resolving phylogenetic development at different evolutionary time scales.
4. Information content of FishPEI for phylogenetic reconstruction
One of the most common problems in phylogenetic studies is: whether enough information is collected to resolve the target phylogenetic development. To address this problem, we constructed multiple phylogenetic trees by ligating the fishe markers one by one in ascending order of normalized RF based on the individual gene trees. The graph shows that at 40 markers the drop in RF tended to smooth, normalized RF to 0.224 (fig. 3). The number of markers (or genetic data) is consistent with the perspective of Capella-Gutierrez, kauff and Gabald6n, i.e., not all relationships need to be resolved with genome-scale datasets, rather, judicious selection of markers may be sufficient to produce fully resolved target phylogenetic development. Since the dataset of the present invention covers a broad class level and shows a high phylogenetic accuracy at the three class levels analyzed (see below), convergence of the tree topology at about 40 markers means that 82 carefully selected fishe markers are sufficient to resolve a significant portion of fish phylogenetic development.
5. Overall phylogenetic performance of FishPEI
The linked gene trees and species trees are often well supported. The average ultrafast guidance (BP) support rates for nucleotide and peptide ML trees were 96.26% and 97.00%, respectively, the average Posterior Probability (PP) for both BI trees was 0.96, and the average PP for the ast tree was 0.87.
To further quantify the phylogenetic performance of the fishe ie, we calculated the phylogenetic accuracy index for each gene tree, which is defined as the average of ML BP support for four widely accepted genera, families and orders of clades. Bootstrap support will be considered negative if no branching single lines are restored in the gene tree.
As a result, all of these clades were found to be well supported in the connected gene trees and the ASTRAL species tree (ML tree bp=100%, BI tree PP >0.9, ASTRAL pp=1, except euteleompolpha of 0.74).
Overall, the phylogenetic properties of fishe are satisfactory at three levels. The average accuracy index was highest at the intergeneric level (74.71, ranging from-7.25 to 100), followed by the intergeneric (69.51, ranging from-50 to 100), and lowest at the interocular level (55.68, ranging from-100 to 100). Of these markers, ashll, prdmll and LOC100333177 show complete support for all clades available for analysis, making them excellent markers for phylogenetic analysis at different classification levels. The other 19 markers, including the common RAG2 marker, had an overall average accuracy index of over 90. Thus, these markers are also useful in broad spectrum system developmental assays.
Our FishPIE primer set has lower per base sequencing costs than other systematic genomic approaches. Thus, we believe that they constitute an important tool kit for the advancement of research into the phylogenetic development of fish. The FishPEI can be used in combination with other sequencing methods to increase taxonomic coverage for further phylogenetic studies.
The choice of molecular markers is probably the most critical decision in any molecular phylogenetic study. The selection must balance between DNA quality, compatibility with existing equipment and datasets, phylogenetic resolution and budget. The FishPEI marker has advantages in all these respects. Since PCR is now the standard procedure in molecular laboratories, the fishe marker provides a smooth transition from traditional protocols to the latest high-throughput methods. We also demonstrate high retrieval of the fishe ortholog from NGS datasets so that existing data can be readily exploited. Although the total number of features of the fishe is less than that used in phylogenetic studies (typically more than ten thousand sites), our markers show comparable phylogenetic resolution at different classification levels. The initial investment in fish system genomics analysis using FishPEI using PCR as a conventional protocol is only the cost of primers, and the cost of all 102 test primers in our study is less than $1000, sufficient to perform experiments on >200 samples. For other fish phylogenetic kits, such as UCE, AHE and exon trapping, the initial investment is at least three to four times higher. For about 200 samples, we estimated that the cost of sequencing all the fishe markers for each sample was about $25. Therefore, the FishPEI has good cost performance.
TABLE 1 reference genomic fish species and genomic information table
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TABLE 2 primer sequence information and PCR conditions
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Table 3. Fishe marker details show the ratio of alignment length, GC content, conclusive information sites and conclusive information sites in the complete dataset (sequences generated in connection with this study and sequences obtained from publicly available transcriptome and genomic data).
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Example 2
Fish nuclear gene molecular marker library construction process
The NPCL markers obtained by screening can be used for constructing a molecular marker database for sequence alignment, identification of germplasm resources of genus Coriolis and the like. The partial library construction process represented by 10 random markers out of 82 molecular markers, and 10 random fishes in the foregoing examples is exemplified.
Step 1, sample pretreatment, namely randomly selecting 10 fishes, shearing fin strips, and extracting DNA. 10 out of 82 molecular markers selected randomly were subjected to PCR amplification verification.
Step 2, nest type PCR:
out PCR, using the extracted DNA as a template, was amplified with an outer Primer (out PCR Primer). The reaction system: 2x PCR Mix 5. Mu.l, primer F1.5. Mu.l, primer R1.5. Mu.l, RNA Free H 2 O3. Mu.l, template 1. Mu.l, total 10. Mu.l. Reaction conditions: pre-denaturing at 94 ℃ for 3min; denaturation at 94℃for 30s and annealing at 52℃for 40s for 30 cycles; extending at 72 ℃ for 2 min; finally, the extension is carried out at 72℃for 7min.
inner PCR: the out PCR product was used as a template and amplified with an inner Primer (inner PCR Primer). The reaction system: 2X PCR Mix 10. Mu.l, primer F2 1. Mu.l, primer R2 1. Mu.l, RNAFree H 2 O7. Mu.l, template 1. Mu.l, total 20. Mu.l. Reaction conditions: pre-denaturing at 94 ℃ for 2min; denaturation at 94℃for 30s and annealing at 55℃for 40s, for a total of 35 cycles; extending at 72 ℃ for 1min and 40 s; finally, the extension is carried out at 72℃for 7min. ( Note that: if no band is visible after electrophoresis detection of the partially reacted inner PCR product, the out PCR reaction cycle number can be adjusted to 35 or the annealing temperature of the inner PCR reaction can be adjusted to 50 DEG C )
And 3, agarose gel electrophoresis detection. Glue concentration: glue concentration 1%, voltage 120V, time 30min. Marker: the marker is DM2000.DM2000 DNA Marker consists of 6 DNA fragments of 2,000bp, 1,000bp, 750bp, 500bp, 250bp and 100bp, respectively. 4 μl of the direct electrophoresis was used, and the amount of the 750bp DNA fragment was about 120ng when electrophoresis was performed, and the other bands showed a bright band, and the amount of DNA was about 40ng. 4ul of the inner PCR product was taken and subjected to electrophoresis detection.
And 4, mixing the PCR products. And (3) primarily judging the concentration of the PCR products according to the agarose gel electrophoresis detection results of the PCR products, and mixing the inner PCR products of the same sample to ensure that different inner PCR products have similar total amounts in the mixture as much as possible.
And 5, purifying and recovering the PCR product mixture magnetic beads. The mixed PCR products are subjected to magnetic bead purification and recovery, and the steps are as follows:
step 6, preparing 1.5ml EP tube, adding 100 mu l N411 magnetic beads (which are balanced for more than 30min at room temperature, and fully shaking and uniformly mixing before use) into each tube, and marking. The inner PCR product mixture (about 100. Mu.l) was added to the corresponding EP tube, and after mixing by pipetting, it was allowed to stand at room temperature for 10min.
Step 7, placing the incubated solution on a magnetic rack until the solution is clear (about 1 min), and sucking the supernatant by a pipetting gun; step 8, holding EP tube on magnetic rack, adding 200 μl of 80% ethanol (on-line) to each tube, incubating for 1min, and removing supernatant. And 9, repeating the step 3. And 10, thoroughly sucking out the liquid by using a small-range pipette. And 11, uncovering and drying at room temperature for 3-5min, wherein the specific time is based on the visual reflection of the magnetic beads. Step 12, adding 100 μl ddH into each tube after drying 2 And O, sucking and beating the gun head and uniformly mixing. After incubation for 10min at room temperature, the magnetic rack is put on.Step 13, after the solution is clear (about 1 min), the supernatant is transferred to a new 0.5ml EP tube with a pipette and marked. And 14, carrying out Illumina on the PCR product to construct a high-throughput sequencing library, wherein the library construction flow is carried out according to the specification of an Illumina library-building kit.
Example 3
Species classification identification using DNA molecular markers
The molecular marker database established by the invention is adopted to classify and identify the sequenced species, so that the classification and identification of the detected species at the target, family, genus and species level can be realized. The procedure identified by kcnf and mab genes and NP11, NP12, NP13, and NP14 primers will be described as an example.
1. DNA extraction:
adopting an animal tissue genome DNA rapid extraction kit (CW 2089S, beijing kang is century science and technology Co., ltd.) to extract DNA from a fish tissue sample, wherein the operation method is consistent with the specification of the kit; 1% agarose gel electrophoresis was used, the voltage was 150V, and the electrophoresis time was 25min for DNA quality detection.
2. Molecular marker amplification:
(1) The reagent used is as follows:
(1) PCR Mix cat P2011 Dongsheng Biotechnology Co., ltd; (2) agarose sigma; (3) DM2000 cat: CW0632M kang was century; (4) N411 magnetic beads cat: n411-02 Nanjinouzan Biotechnology Co., ltd;
(2) Sample dilution:
since the DNA sample volume received in this project is about 10ul, the sample is diluted before the experiment is formally started. Each sample was taken in 8ul and 152ul RNA free H2O (20-fold dilution) was added.
(3) Nested PCR
out PCR: amplification of the diluted template with outer Primer (out PCR Primer)
a) The reaction system:
TABLE 1 out PCR System
b) Reaction conditions:
TABLE 2 out PCR reaction conditions
inner PCR: using the out PCR product as a template, amplifying it with an inner Primer (inner PCR Primer)
a) The reaction system:
TABLE 3 inner PCR System
b) Reaction conditions:
TABLE 4 inner PCR reaction conditions
Description: if no band is visible after electrophoresis detection of the partially reacted inner PCR product, the number of out PCR reaction cycles can be adjusted to 30 or the annealing temperature of the inner PCR reaction can be adjusted to 50 ℃.
(4) Agarose gel electrophoresis detection
Glue concentration: glue concentration 1%, voltage 120V, time 30min.
Marker: the marker is DM2000.DM2000 DNA Marker consists of 6 DNA fragments of 2,000bp, 1,000bp, 750bp, 500bp, 250bp and 100bp, respectively. 4 μl of the direct electrophoresis was used, and the amount of the 750bp DNA fragment was about 120ng when electrophoresis was performed, and the other bands showed a bright band, and the amount of DNA was about 40ng.
4ul of the inner PCR product was taken and subjected to electrophoresis detection. Representative results are shown in FIGS. 6, 7, and 8.
3. Library construction:
(1) PCR product mix
And (3) primarily judging the concentration of the PCR products according to the agarose gel electrophoresis detection results of the PCR products, and mixing the inner PCR products of the same sample to ensure that different inner PCR products have similar total amounts in the mixture as much as possible.
(2) Magnetic bead purification and recovery of PCR product mixture
And (3) performing magnetic bead purification and recovery on the mixed PCR product, wherein the steps are as follows: a1.5 ml EP tube was prepared, and 100. Mu.l of N411 magnetic beads (equilibrated at room temperature for 30min or more) were added to each tube, and mixed by shaking thoroughly before use) and labeled. The inner PCR product mixture (about 100. Mu.l) was added to the corresponding EP tube, and after mixing by pipetting, it was allowed to stand at room temperature for 10min. (2) The incubated solution was placed on a magnetic rack until the solution was clear (about 1 min), and the supernatant was removed with a 100. Mu.l pipette. (3) EP tubes were kept on a magnetic rack, 200. Mu.l 80% ethanol (as-prepared) was added to each tube, and the supernatant was removed after incubation for 1 min. (4) EP tubes were kept on a magnetic rack, 200 μl 80% ethanol (as-prepared) was added again to each tube, and the supernatant was removed after incubation for 1 min. (5) A10. Mu.l pipette was used to thoroughly aspirate the liquid. (6) And uncovering and drying at room temperature for 3-5min, wherein the specific time is based on the condition that the magnetic beads are visible to naked eyes to reflect light. (7) After drying was completed, 100. Mu.l of ddH was added to each tube 2 And O, sucking and beating the gun head and uniformly mixing. After incubation for 10min at room temperature, the magnetic rack is put on. (8) After the solution had cleared (about 1 min), the supernatant was transferred to a new 0.5ml EP tube using a pipette and marked. And (9) storing at 20 ℃ for a long time.
4. High throughput sequencing:
sequencing by using an Illumina series sequencing platform, sequencing and reading 150bp at the two ends, wherein the sequencing quantity is 4 Gb/library.
5. Data analysis
(1) The sequencing molecular markers are assembled and spliced, and second-generation sequencing assembly software such as Spades (v3.15.2), SOAPDenovo (version 2.04) and the like can be used for assembly.
(2) And (3) comparing the assembled fragments to a molecular marker database by adopting blastn (version 2.10.1+) comparison software, distinguishing gene sequences corresponding to the molecular markers, and selecting an optimal comparison result as a gene corresponding to the sequencing markers.
(3) And combining the classified molecular markers with the molecular marker sequences of the database, and performing multi-sequence comparison by using a mafft (v 7.475) multi-sequence comparison software.
(4) And adopting IQTree (version 2.0.5) software to select the optimal model substitution type, and constructing the system classification tree for not less than 100 ten thousand times in iteration.
(5) And (3) combining the phylogenetic tree constructed in the previous embodiment, checking the classification tree by adopting analysis software such as FigTree (v1.4.4), and performing species identification and obtaining classification status corresponding to the detected species to finish the identification process.
It should be understood that the foregoing examples of the present invention are merely illustrative of the present invention and are not intended to limit the present invention to the specific embodiments thereof. Any modification, equivalent replacement, improvement, etc. that comes within the spirit and principle of the claims of the present invention should be included in the protection scope of the claims of the present invention.
The sequence information is shown below
SEQ NO.1CTyTAyGGmGAyGAyAGyTGGGA
SEQ NO.2TAAGGrTCwGCyTChArrGGCAT
SEQ NO.3 GAyAGyTGGGAyrCTCCTGTvAArGArTAC
SEQ NO.4 CAAArGGyArrCTyTCyCTGCGrCyrTAGG
SEQ NO.5 AArGACCAGGAryTGCTGTGGGA
SEQ NO.6 CArCAkGGrGTTTTrCTbCGACT
SEQ NO.7 GCmTCwGAyTCyGGyTGyTTTGATGATGA
SEQ NO.8 CAATdGArGGAGAyTCAAArCTrCCmAGTG
SEQ NO.9 CAGyTGGGnyTGGAGCArGACTT
SEQ NO.10 AGCCrTGyACyArTCCkrCTCTT
SEQ NO.11 GTvAGyCGbGGbATGAAyCGhAACTTTGA
SEQ NO.12 TAGGdrTCyCCrCACATyArrCACATGAC
SEQ NO.13 AArGArGArCAGGAyCCmCCTGT
SEQ NO.14 CTGAArATkGTrGGCArsAGGTC
SEQ NO.15 GCCAwAGrAArCGwGGrCAGhCCCAAGACG
SEQ NO.16 CTGnCGdGAsCGyAGTCTGyArGTACTTCT
SEQ NO.17 CATGCAGTGGmGwCGGCGrCACT
SEQ NO.18 TGvGAkGTGATsAGGTGrCTGTA
SEQ NO.19 ACCArAGCArCTChCTGmGrrGCCTbTGGA
SEQ NO.20 CCCyGAGAACACrTAsCCyGTsCCbGAGCA
SEQ NO.21 CGCATGCACAACCTbGAGAGACT
SEQ NO.22 AAyTCrAAyTGsGGCAGrCTGCA
SEQ NO.23 CGCTTyCTGGArGCyCArCTvCGCAGhGAGAGA
SEQ NO.24 CGyGGGCAyACyTTrATTGGCACTGGGCAGCTGG
SEQ NO.25 CCCCAyCGvCTrGAACGCCTTAG
SEQ NO.26 TGCACyGTCAGrTTGCTrCAGTT
SEQ NO.27 TGGGyyTmATCTCmCAGCAyCCCAGTGCCT
SEQ NO.28 GAkGArGTGGCrAAkGGmGATTGTCTGGA
SEQ NO.29 GAyrTsCCwGArGAmAsCTGGCT
SEQ NO.30 TTGCGrTTnGGsCGCCkrCAkCG
SEQ NO.31 GArGAmAsCTGGCTbCAGnTGTG
SEQ NO.32 CAkCGyTCrTCrATGCTyGGCACrCATTC
SEQ NO.33 CGCAChhTrGCyAChTTyAACTC
SEQ NO.34 TyTCCAGyTTbCkCTCrATGGAC
SEQ NO.35 CCACTCyCyhCAGACnAyrCArAArGTGGA
SEQ NO.36 CnGCyykkCkdGCyTTCTGrATCTGyTTCT
SEQ NO.37 GArGCyyTsTTTCGAyAGyCGCT
SEQ NO.38 CAGyTGrAAvACCTCkGGGATGT
SEQ NO.39 AAyGCbCCbCAGTTCAGyGArAArCGCTA
SEQ NO.40 TCrAACACrGGvGGGTTGTCrTTCAC
SEQ NO.41 AAyGGvTACmGrmGmTTyGACCC
SEQ NO.42 TAyTkCTGryGyArnGCyGGCTC
SEQ NO.43 GGbATGGAGTACACsyTrGACyTnCAGsT
SEQ NO.44 GCyGGCTCnAynGCyCkGAAhACrTG
SEQ NO.45 CAACAAGAACCCnCCyTACCAGT
SEQ NO.46 GArCCCAGrCACATyTTrTAyTG
SEQ NO.47 ACCAGTAyCGCCTdCACAGCTACmTGyTsAGCCGvAAGAT
SEQ NO.48 TAnAChACyTTdGGGTCrTACTGrCTGAAGATGAT
SEQ NO.49 ATGGTrGTGACnvArTGyGGCTG
SEQ NO.50 CCrTCnGArGTrCCrTCrAAGCA
SEQ NO.51 ACdGGmTACAArGGhACmTTCTChrTCCA
SEQ NO.52 GTCnAGdGGbGChArCATdGTGAATCTC
SEQ NO.53 GAGAACTTyATGGACATGGAGTG
SEQ NO.54 TkyCTGTTCTGrCAGTCbGACTC
SEQ NO.55 ACATGGAGTGyTTCATGATmCTGACyCCbAGCCAGCAGCT
SEQ NO.56 CTCCTCArrGCrTAGATGATbGGrTTGACrGTGGAGTTGA
SEQ NO.57 CmCGyAArCGyAGCCAyAGyAGC
SEQ NO.58 GTGGyyGTGATvAGbCCdATCCA
SEQ NO.59 AAyTGGTACAGyTGyGGkGArGGkGAGGT
SEQ NO.60 AhGTCATdGGyTGyTGwGGrTTsACrTGCT
SEQ NO.61 GAyGArGTbCCCAydGCvCAyTC
SEQ NO.62 TArTGdGCrTCCCACACrTCCAT
SEQ NO.63 CTbTChAAryACAGrGsvTGGGGvAArCAG
SEQ NO.64 CGyArCCACTTdGmrCAyTCyCCyArCT
SEQ NO.65 GArGCCATCCChCAGCATATCAA
SEQ NO.66 GCrTGbCCnGCnGCCATGTACTC
SEQ NO.67 TrGGvAAGCTGCAGTACCTCTACCTCCAG
SEQ NO.68 ATrTACTTsGAbTCTGACTTGTAGGACG
SEQ NO.69 GGCAGCCGyTCCTTyCCsTGCCA
SEQ NO.70 GCyTGrCAGCTCATbCkyTTGGC
SEQ NO.71 TGmGrGArAGyCAGGCCAGyGAGGTbGACT
SEQ NO.72 TCrTAGCACTGmACyTTGGGsAGyTTGTC
SEQ NO.73 CTsACvTGGCTCAGyTTCATGCT
SEQ NO.74 CCTCyCkyTCrTAhGTmAGCATG
SEQ NO.75 CTTCCCdCTyATyGChCAyTACTACCTCAC
SEQ NO.76 TCvCCrTTGTCrGCCAkGTTrGCrTC
SEQ NO.77 TCyCGvTACGGACAyyTrGAGGT
SEQ NO.78 TCbGCrCCrCACTCyAGsAGCAG
SEQ NO.79 GCTsTGGGCGGCbTCkGCvGCsGGTCACCT
SEQ NO.80 TTGTCyACrGCCATGTGsAGvGGvGTGAA
SEQ NO.81 ATmTChGCvCTsACkGCCTCCAA
SEQ NO.82 TGCTGyGAGAGmAryTGrCTGAT
SEQ NO.83 CGmAArTCrGAGAryGArkCmTGGCAGGAG
SEQ NO.84 GAGGTCCrAAbArdAGsAkrCTsCGAGGTA
SEQ NO.85 CArGAdCArGAvrCCATGACTGC
SEQ NO.86 GGdsCyCCrCTTGTsGGkATGAC
SEQ NO.87 CTCAGCmGrCAGyTnGATGAGCT
SEQ NO.88 AGnGTCTCCATyTCTCkGGCCAG
SEQ NO.89 GArmGsAGCCTGACvTCwGTGCC
SEQ NO.90 CCrTTrGGhGTGTArATGGGCT
SEQ NO.91 CTyTTCCTyACCAArAACCACyTrAGCAG
SEQ NO.92 AGCTGyTCATTGTTyAGhGmCACTATCTG
SEQ NO.93 TCnTCyCCmACwGATGAyGAGCG
SEQ NO.94 GGrCTyTTyTCmACrCTyGCyAC
SEQ NO.95 rGArACAGATGArCGhmGdGChCAryTkCA
SEQ NO.96 TGkGTbTGTGGyTCCTCyTCyTCywCCTC
SEQ NO.97 GCmGGrCTbGAGGTsCACCAGTT
SEQ NO.98 GTGATbCCsACkATCATGGTCAT
SEQ NO.99 GGvTGyGArGCsCTsATGAAyAArTTyGGyTTCCAGTGGC
SEQ NO.100 TCATGAACACbGTGAAGTCbGGvGwCATsGGGGCrAAGTT
SEQ NO.101 GyTCwCGTTCdCGCwsmyACAGC
SEQ NO.102 GGdGTGTGrTGrAGbGCAGArGC
SEQ NO.103 AGrCGbAGCAGCTAyAGyCGnAG
SEQ NO.104 AGrTGrTGyTGrGGwATrTGrTGyACCTG
SEQ NO.105 AAyATGwCyAACCTsrGyGGCTC
SEQ NO.106 TCrGArGAsCkvAGATTGTTCGC
SEQ NO.107 ACAACTAyATyTTyCArGGnGGbCAGCATC
SEQ NO.108 CCArGAAGCGrTCCTTCTCyTTbAGGCTGA
SEQ NO.109 GCdTGTGCmAArCCmAGyGTGCT
SEQ NO.110 GwvTGwCCnGGwGTdGTdGGCAT
SEQ NO.111 GCTkCTmAAACACATmmGrTCyCACACAGG
SEQ NO.112 GrGrdGGwACrGArAGvAGrAAyACTGG
SEQ NO.113 AArAACCAGAGTkGCyhTGAACC
SEQ NO.114 CCAGCTGGTTGTTCTCyAGCCAG
SEQ NO.115 GTbCTGCAGrATCATCAAyGAGACCsACrGCdGCmGCCAT
SEQ NO.116 TTGCTsAGbCkGCCyTTrTCrTTGGTGATkGTGATyTTGT
SEQ NO.117 CCbTTyGTGGArGArTCwGACCT
SEQ NO.118 AAAdGCCATGTGGGAdyGrTAGC
SEQ NO.119 AGrCCywTbGAAGGyATGACyATCATGGA
SEQ NO.120 GrTAGCTGGGrCTTGyyCTyCkGCTGACC
SEQ NO.121 GAGCGyCTbmGrAGyTCTATGTC
SEQ NO.122 ATGCTGTCrTTrTCvCCrTCnGA
SEQ NO.123 GyTTTCbTTyGArGGACCTGArAAAGTCCA
SEQ NO.124 GAArTCvGACTCnGAyTTGCTyTGbCkGTT
SEQ NO.125 GArmGrGTGGTCATyAACATCTC
SEQ NO.126 GCyTCyTGrATyTCCATrTAGTC
SEQ NO.127 AGrATGCGsTAyTTyGAyCCdCTrAGGAAyGArTACTT
SEQ NO.128 TCdCGrTGrTAGAAGTAGTTrAArTTkGAsACdATGACAG
SEQ NO.129 GAGmGvGACTTyTTyTTCCACGA
SEQ NO.130 TArAACATrACsGTkGCrAAGAT
SEQ NO.131 TTCCACGAGGAGAsvAryGArTwCTTyTTyGACCGyGACC
SEQ NO.132 TGATGGCCATGGTGAGvGArAAkAGbAGGAAGCCsAGyTC
SEQ NO.133 ATGATyCGnCGCAAyTTCCACAA
SEQ NO.134 TTyTGbGGCATkGGGTAvCGCTG
SEQ NO.135 GCAAyTTCCACAArGTyATCCAGGAyGAsGArTTyTACAC
SEQ NO.136 TTGCGrTACTGCTTrTChACrTCrTCrCTrTTCTTCCA
SEQ NO.137 GshCCmCCyGTbATGAACTACAT
SEQ NO.138 CvGGbGAbGTyTGrATCTGCTTC
SEQ NO.139 ATGTACmChCCdGGTCCvGCmCmGCA
SEQ NO.140 GGrTAvGGTGGhGGnGGrCAGC
SEQ NO.141 TTyGArmGrGAGCGvATGGCnTA
SEQ NO.142 CAGyTCnGCCArdGTCGATGCAC
SEQ NO.143 GGrGArGCnGGdGAyTTyGCyvkyATGGC
SEQ NO.144 GATvACnGAGTTGCrbGGyTCdATGT
SEQ NO.145 TyCCvTACCTbGTbGTbATCCAC
SEQ NO.146 GTTbTCyyTACAGGTCTCArCTC
SEQ NO.147 CTbGvsAAGATGyTTyGAyTCnCCbTGGAC
SEQ NO.148 AGGCTrAArATCrGCrCTbGGGATnCGyTC
SEQ NO.149 CCCAGyTTyCCrTGGAsyGAGTT
SEQ NO.150 TCnCCrAArTCkGACAGsGACTC
SEQ NO.151 ATyCAGACGCGyAAyGAyGGvAGCAAGTT
SEQ NO.152 GCvGArAGCGGhGGCTGnCCrTTGTCCT
SEQ NO.153 GChAAyAThTCnGArGACATGCC
SEQ NO.154 CCbGTyCChACrAAGGTGTTGG
SEQ NO.155 GAyTCyGGnAAyCCdGCnCTvTChAGCAC
SEQ NO.156 GTCCTGvACnGCyTGGTGyTTCTkdGAGGC
SEQ NO.157 GTsGCbGArAAyGAGmmrGAGCA
SEQ NO.158 CrChAmrTCTGACsCCTCvTCCA
SEQ NO.159 CTCTGArACnCCbTGyGTkAACyTnCAGCT
SEQ NO.160 AAvACvTCmCkrTTCCAvCCCATrGCCATG
SEQ NO.161 ATGGAGGGnrTCAshGAGTTyAC
SEQ NO.162 TTGbGTkGChAChGGrTAbCkCA
SEQ NO.163 TTyGACCTbCTkGAGCCnCCmACnTCyGGA
SEQ NO.164 GTTyTGyGGyGCrTTyCCrGGrAACArmAC
SEQ NO.165 CGhCCbAAyCArCTbGTsGGyTC
SEQ NO.166 GTrCyrTCryTGTACTGyTCCCA
SEQ NO.167 GCdGCdyTmAGCAACATGyTdGGbGGmATG
SEQ NO.168 AGnGCyCTvACwGCCArrTAGTTGATG
SEQ NO.169 CACdGsCAArCTGmGGwCTGACT
SEQ NO.170 AGrTTyCCyCTkGGrCGhACCTC
SEQ NO.171 CAyTCvCCyAAyCACAACAChyTdCArGC
SEQ NO.172 GCrCTGGAbCCyGGrCTbGGrAArATCAT
SEQ NO.173 AyGCmTGyGAryTGAGrTGyCAG
SEQ NO.174 CdbCCCTGTCCrTAvGAyTTGCT
SEQ NO.175 GArrCCrGTbGArGTbCGyrTbGTGCArCG
SEQ NO.176 TCCAkrCCvArhCCyTCyCTGGwrAACTG
SEQ NO.177 GACACvGTkCTdGyrTCyGGrGA
SEQ NO.178 CyACdGGdCCrATrTTGACAGTA
SEQ NO.179 GGvAArAGCACmykrCTyCAGmGrCTrCAC
SEQ NO.180 TGCATGCTyTTCTTyTChCCyksyACAGG
SEQ NO.181 GGhCCrCTbATyGACmGrCAGAT
SEQ NO.182 TCyCkbyknCCCATGTGsACCAG
SEQ NO.183 GATyTTymGnTTCAGyGArGArGGCATGGT
SEQ NO.184 CAsGCmACrTArAACTCrTCsCCrCTGCT
SEQ NO.185 TCyAGCAChGCCATyCTsCArGT
SEQ NO.186 TTGATyTGrAAbGTdGGCTGAGG
SEQ NO.187 GACAAyGTyCChTCyATAGACAC
SEQ NO.188 GTrGGGTCdTCAGGCTTGGATTC
SEQ NO.189 CAsACGACCAsvGCyTCmAmCAC
SEQ NO.190 TGCTTCATrAACTCvCkGCkyTG
SEQ NO.191 GACTAyrCnGACrChGACTTyyTGGGTGAC
SEQ NO.192 TCyTCyTTGCTCCAGTAsCGdCCCATCTTC
SEQ NO.193 CACTAyAACACmAAGCTGGGmTA
SEQ NO.194 TGCTCCTGAGGTTGhGGTTGCAA
SEQ NO.195 CGvAArGACTTyCTrTGCCAGTACTGyGCC
SEQ NO.196 CCCAGCAGrTGrGArAArTCCATGTTAGCA
SEQ NO.197 ATGGTsTGyACyGGsAAGATGCA
SEQ NO.198 ATGTTyTCwGArAAvGTrTAGTT
SEQ NO.199 CyGGsAAGATGCACAChGAyCGCATyTGCCGCTTyGACTA
SEQ NO.200 TrTAAGGCATrTAbGTrTTyTCTCCyTGCTCyTGkATCCA
SEQ NO.201 GACTACyCrCTGCAGAGCAACAG
SEQ NO.202 TTyTCyTTCTGTCTTCCTGTTAC
SEQ NO.203 CTGCAGAGCAACAGyCACmCGCTCAGCCACGCrCACCAGT
SEQ NO.204 TTCCTGTTACAAAACCAAACyCksACyACyTCTTTyTCCA
SEQ NO.205 GTkCCwGAyCChCAryTdGATGA
SEQ NO.206 TCCCArTCrCAyTCyTGrCTCTG
SEQ NO.207 GArACvGArvTsAAAGArGGrGCwCAGCA
SEQ NO.208 GArTGyTCyTTyTCyTGyTGrGGrTCTCTG
SEQ NO.209 ACvCTbAAyGArATGTGGTGCCA
SEQ NO.210 AGCAGrTCrTTsATCTGbTCCAG
SEQ NO.211 GGyTCCAAGCArTTyAArATCCACACCAT
SEQ NO.212 AGvGGrAArCGyTGCyTGTryCTGvAGATG
SEQ NO.213 TCTAyATyATCAACsTTyGGCAT
SEQ NO.214 GTGAGvAGGGAGCAyTTGAACAG
SEQ NO.215 ATCAACsTTyGGCATGGGwGCyAGCCCyTTyACyAACAT
SEQ NO.216 AGTGTAvAGrTGkGGkGCACAGTGATCCAT
SEQ NO.217 TGGGTsCGsCACAsCTACArCCA
SEQ NO.218 CATCCCTTTCTTyTTsCGGTTGA
SEQ NO.219 AAyAGyGAyGArGACAGCAAAGAyGGCA
SEQ NO.220 CGnGCnGGCCACCArGGGAAkCCrTGrAT
SEQ NO.221 TTyCAysmvTTTGArTGGCAGCC
SEQ NO.222 CTGAAsAGyTTGTTbsChGACTC
SEQ NO.223 AArGAyCTbGAGAGAGGACAThATGGArGGdCTGA
SEQ NO.224 GTCATyAryykbCGrGCrTAGTTbCCATTCATCCTCAT
SEQ NO.225 TTWGGNCARAARGGNTGGCCNAA
SEQ NO.226 CATRCAYTGNGCRTGNACCCARTG
SEQ NO.227 AGGGTTTTCCCAGTCACGACGGWGGKAARACNCCNAAYAAYGA
SEQ NO.228 AGATAACAATTTCACACAGGCARCAYTTDATCCARTANCC
SEQ NO.229 ATGCTsTCvGGvTCyCCdCAGTC
SEQ NO.230 AGmCCyCTrGCyTkCTCCACCCA
SEQ NO.231 CAGTCyTACTGCrTbGTrGArAArTGGAG
SEQ NO.232 ChAGyTGsGTTyTkATCCTCTCyTCyTCCA
SEQ NO.233 TCCAGAyCChACnTAyGArCTCA
SEQ NO.234 ACrGTdCGnCCdGTCTCCATGCA
SEQ NO.235 GGyAAAGTyCCyhTrmGrCAGCTkGTsTAC
SEQ NO.236 GTTCATyTTkGCyGGrTCvAGrGCCCAGT
SEQ NO.237 GArCAGACyCArGTGGTGGCyAT
SEQ NO.238 TyTGwkGbkGGTGGTGsAkCTGC
SEQ NO.239 GTrrTyACyAArGAvCAGCCmATGAGCATG
SEQ NO.240 ATsGGkATyTGCATGGGrTArAAGTTCTGC
SEQ NO.241 AAYATHACNAAYGCNTGYTAYAA
SEQ NO.242 GCRAARTGNCCRTTNACRTGRAA
SEQ NO.243 AGGGTTTTCCCAGTCACGACTGYTAYAAYGAYTGYCCNTGGAT
SEQ NO.244 AGATAACAATTTCACACAGGCKGTGRGGYTTYTTRTARTTRTG
SEQ NO.245 GGArCAGyTrGTswGyCTyCAGC
SEQ NO.246 CArATkGGrCAnGAGTGyTGCAT
SEQ NO.247 CArCArCTbTCTGCwGCAGCwGChCTvATw
SEQ NO.248 GTkGwGAAnGCvCkGCCrCAGATyTTGCA
SEQ NO.249 TCATyTTyTCyATmTTyGGCATG
SEQ NO.250 TTbTCrGGyTTGGTyACrCTGTC
SEQ NO.251 GAChTGTAyAACTTyGArACnTTyGGmAACAGyATGATC
SEQ NO.252 GTGCyCTCyTTyTTyTCTTGyTCyTGrTTG
SEQ NO.253 CCdCAyGCyCTrTChCTsCGsAG
SEQ NO.254 ACCTCrCAvsCrsAACTGCTGCC
SEQ NO.255 AGhTGGAGGTrTChTCwCCmAArmTCTACA
SEQ NO.256 TCCTCCTmCTmCTsCrCCTsCryyGGsCAT
SEQ NO.257 GAyAGyTCwGGhGGdGChGTbCA
SEQ NO.258 GCmACyyTyTCnGGyTCrCTGTC
SEQ NO.259 GAymGmTGyACyACbGTvAGyCCnGTGGT
SEQ NO.260 AGGmAywTGGCArGGyTTyAGdAkyTGCTC
SEQ NO.261 GTvATAGAyGGyCArGAGAGACT
SEQ NO.262 GGyCTGAAnGCvGAbAyGTAGCT
SEQ NO.263 GTbGCbCTkGGvATCACyTGyGTsCAGATG
SEQ NO.264 GyrGGCCArAACATsGGrAArGArkGrTAG
SEQ NO.265 ATGCTbTACATGGTvATyGTGCC
SEQ NO.266 AGCAGmAGCArvGCyGGyGCGTA
SEQ NO.267 CTbTTyGCnTChAArGCCATybTsCAGCT
SEQ NO.268 TChGCdATdGCrTAmATCrCTrCCrTACAC
SEQ NO.269 TACATGTTCyTGGGyATGTCCAT
SEQ NO.270 TrGCCTCrTGrCAGCTCACCA
SEQ NO.271 TGTTCyTGGGyATGTCCATCAThGCvGAyCGbTTCATGTC
SEQ NO.272 GCrTGCTTyTTCArrATGTTyCCnGCyCCGATCATCAT
SEQ NO.273 GArGArATmGAyGAGCCyTGCTT
SEQ NO.274 ATvAGvAChGAsAGhGGvACAGC
SEQ NO.275 CArGAyAThCAyGybGGnGCdTTyAATCGG
SEQ NO.276 ATrTCrCAnGAGCAvTCCCAdGGrTTCTG
SEQ NO.277 ACyGTsTAymGrCCbACrCAGCT
SEQ NO.278 TCvTCvAGyTCrTCrATGGTGCT
SEQ NO.279 GArAACyTGGAATACCTyCAGGCyGACTAC
SEQ NO.280 AGGCArAArGCACACrAAvACwGTnAGGAT
SEQ NO.281 GAyTTyGTCATGCTyCAGCAGCC
SEQ NO.282 TAyTGyAGvGArCGCACTTGCAT
SEQ NO.283 GArGTvAAAGCyCAGmGrCCCyTnAGAT
SEQ NO.284 CCyTCbACrTCdGGCTGCTCrTArAAGCT
SEQ NO.285 ATyCChCGnGAGGTGGAGATGGA
SEQ NO.286 CGyTChAGnArCCACTGCATGGT
SEQ NO.287 ACvCCnGAGTGGGAyGTkTCnGGGGAGACT
SEQ NO.288 TThCGCAGAwGTGCCdGACTTkGwGTAGC
SEQ NO.289 GCyCGTyTGArrGArGCbCGdGA
SEQ NO.290 CTvAGAGCnGCCACdATyCTvAG
SEQ NO.291 AGCArCArCCyGCyCTrTCyGArGCCATGA
SEQ NO.292 CmACyTGCATrGCCATbGCyTkrTGGTCCT
SEQ NO.293 GACAGCACvmGrGTyAGCTTCAC
SEQ NO.294 TArTCTCykCTCbCCrAAGTGCA
SEQ NO.295 GACmGGCAGAThTTyCAGsTTCAGyGArGAyGGCATGGT
SEQ NO.296 TArAACTCyTCnCCrCTrCTdATTCTCCAT
SEQ NO.297 AGyCCsTGyTCCAAyGGyTACAT
SEQ NO.298 CCTGrTAGkCyGGmGGrGAAGGT
SEQ NO.299 CCTsGTCATGCTCTAyGTGGTyTACCTkGT
SEQ NO.300 TGGhvCGrTGGCAGCGyTCrCArTTCTGCC
SEQ NO.301 GAGCArbTGGCrkCnGAyCACAG
SEQ NO.302 CCCAryCTyyTyTCCTTCTGCTC
SEQ NO.303 GGnATGAArGArGArAACAGyCAyyTGAAAG
SEQ NO.304 TTvACyGTbGTGATsACCTGCwkCTTCCACT
SEQ NO.305 AACTCyCCACTyAGCAATGGCAC
SEQ NO.306 GGAGyTGrTArGCrGCrTGAATG
SEQ NO.307 TGCAAAyyTGATyTCdGAyGCyTCyTGGTC
SEQ NO.308 TGrGCyTTrCTGATwGCACTkGArACwGT
SEQ NO.309 GAGCTGGTGAArGTrATGGGdCT
SEQ NO.310 TACTGGAACCArTAmACnGTCTC
SEQ NO.311 GGvAGCCTbATmTACCTsCAyGACACyyTGGAGGAG
SEQ NO.312 CChTCCCAGwArTGyTTGAAsCCrCAbCCrCACTT
SEQ NO.313 CATATCdCCACGdGAyAGTACCA
SEQ NO.314 ATGGCTTCryThACAATGAGGTC
SEQ NO.315 TGAGrCAyGTrCGAAGGGCTCAyCCCACTG
SEQ NO.316 TGGCTGAAGATCCAGTGCrAGCATTTCTGC
SEQ NO.317 ACbAACACyGCCATywCCCAGCT
SEQ NO.318 GCTGGCyTGCAysGGGGGCATGA
SEQ NO.319 GACTTCAAyGACTAyAAGCTsATGATGGC
SEQ NO.320 TTGGACAGrTArGCCArGTTsArmGGCTC
SEQ NO.321 GGbGAGsysAAdTTyGGnGACAC
SEQ NO.322 TCTkryGCTCkvTCnGAGAAGTC
SEQ NO.323 GGrCTCTTyTGGGGnCCnyTsTGCTGCTC
SEQ NO.324 GGrAGGAArGCvGGrTCrkTrGwCTTCTG
SEQ NO.325 GyCArCCwATyAGCAGyCAGATG
SEQ NO.326 GTsGTGGAdCGGCTGATGGACTG
SEQ NO.327 TGyGGCAArCGyTTCCGyTTyAACAGCATC
SEQ NO.328 GCkGvTGCTGsTGCTGTGmTCyTTnGGCAT
SEQUENCE LISTING
<110> Zhujiang aquatic institute of China aquatic science institute
<120> a fish nuclear gene molecular marker primer, molecular marker and molecular marker database
<130>
<160> 328
<170> PatentIn version 3.3
<210> 1
<211> 23
<212> DNA
<213> unknown
<400> 1
ctytayggmg aygayagytg gga 23
<210> 2
<211> 23
<212> DNA
<213> unknown
<400> 2
taaggrtcwg cytcharrgg cat 23
<210> 3
<211> 30
<212> DNA
<213> unknown
<400> 3
gayagytggg ayrctcctgt vaargartac 30
<210> 4
<211> 30
<212> DNA
<213> unknown
<400> 4
caaarggyar rctytcyctg cgrcyrtagg 30
<210> 5
<211> 23
<212> DNA
<213> unknown
<400> 5
aargaccagg arytgctgtg gga 23
<210> 6
<211> 23
<212> DNA
<213> unknown
<400> 6
carcakggrg ttttrctbcg act 23
<210> 7
<211> 29
<212> DNA
<213> unknown
<400> 7
gcmtcwgayt cyggytgytt tgatgatga 29
<210> 8
<211> 30
<212> DNA
<213> unknown
<400> 8
caatdgargg agaytcaaar ctrccmagtg 30
<210> 9
<211> 23
<212> DNA
<213> unknown
<400> 9
cagytgggny tggagcarga ctt 23
<210> 10
<211> 23
<212> DNA
<213> unknown
<400> 10
agccrtgyac yartcckrct ctt 23
<210> 11
<211> 29
<212> DNA
<213> unknown
<400> 11
gtvagycgbg gbatgaaycg haactttga 29
<210> 12
<211> 29
<212> DNA
<213> unknown
<400> 12
taggdrtcyc crcacatyar rcacatgac 29
<210> 13
<211> 23
<212> DNA
<213> unknown
<400> 13
aargargarc aggayccmcc tgt 23
<210> 14
<211> 23
<212> DNA
<213> unknown
<400> 14
ctgaaratkg trggcarsag gtc 23
<210> 15
<211> 30
<212> DNA
<213> unknown
<400> 15
gccawagraa rcgwggrcag hcccaagacg 30
<210> 16
<211> 30
<212> DNA
<213> unknown
<400> 16
ctgncgdgas cgyagtctgy argtacttct 30
<210> 17
<211> 23
<212> DNA
<213> unknown
<400> 17
catgcagtgg mgwcggcgrc act 23
<210> 18
<211> 23
<212> DNA
<213> unknown
<400> 18
tgvgakgtga tsaggtgrct gta 23
<210> 19
<211> 30
<212> DNA
<213> unknown
<400> 19
accaragcar ctchctgmgr rgcctbtgga 30
<210> 20
<211> 30
<212> DNA
<213> unknown
<400> 20
cccygagaac acrtasccyg tsccbgagca 30
<210> 21
<211> 23
<212> DNA
<213> unknown
<400> 21
cgcatgcaca acctbgagag act 23
<210> 22
<211> 23
<212> DNA
<213> unknown
<400> 22
aaytcraayt gsggcagrct gca 23
<210> 23
<211> 33
<212> DNA
<213> unknown
<400> 23
cgcttyctgg argcycarct vcgcaghgag aga 33
<210> 24
<211> 34
<212> DNA
<213> unknown
<400> 24
cgygggcaya cyttrattgg cactgggcag ctgg 34
<210> 25
<211> 23
<212> DNA
<213> unknown
<400> 25
ccccaycgvc trgaacgcct tag 23
<210> 26
<211> 23
<212> DNA
<213> unknown
<400> 26
tgcacygtca grttgctrca gtt 23
<210> 27
<211> 30
<212> DNA
<213> unknown
<400> 27
tgggyytmat ctcmcagcay cccagtgcct 30
<210> 28
<211> 29
<212> DNA
<213> unknown
<400> 28
gakgargtgg craakggmga ttgtctgga 29
<210> 29
<211> 23
<212> DNA
<213> unknown
<400> 29
gayrtsccwg argamasctg gct 23
<210> 30
<211> 23
<212> DNA
<213> unknown
<400> 30
ttgcgrttng gscgcckrca kcg 23
<210> 31
<211> 23
<212> DNA
<213> unknown
<400> 31
gargamasct ggctbcagnt gtg 23
<210> 32
<211> 29
<212> DNA
<213> unknown
<400> 32
cakcgytcrt cratgctygg cacrcattc 29
<210> 33
<211> 23
<212> DNA
<213> unknown
<400> 33
cgcachhtrg cyachttyaa ctc 23
<210> 34
<211> 23
<212> DNA
<213> unknown
<400> 34
tytccagytt bckctcratg gac 23
<210> 35
<211> 30
<212> DNA
<213> unknown
<400> 35
ccactcycyh cagacnayrc araargtgga 30
<210> 36
<211> 30
<212> DNA
<213> unknown
<400> 36
cngcyykkck dgcyttctgr atctgyttct 30
<210> 37
<211> 23
<212> DNA
<213> unknown
<400> 37
gargcyytst ttcgayagyc gct 23
<210> 38
<211> 23
<212> DNA
<213> unknown
<400> 38
cagytgraav acctckggga tgt 23
<210> 39
<211> 29
<212> DNA
<213> unknown
<400> 39
aaygcbccbc agttcagyga raarcgcta 29
<210> 40
<211> 26
<212> DNA
<213> unknown
<400> 40
tcraacacrg gvgggttgtc rttcac 26
<210> 41
<211> 23
<212> DNA
<213> unknown
<400> 41
aayggvtacm grmgmttyga ccc 23
<210> 42
<211> 23
<212> DNA
<213> unknown
<400> 42
taytkctgry gyarngcygg ctc 23
<210> 43
<211> 29
<212> DNA
<213> unknown
<400> 43
ggbatggagt acacsytrga cytncagst 29
<210> 44
<211> 26
<212> DNA
<213> unknown
<400> 44
gcyggctcna yngcyckgaa hacrtg 26
<210> 45
<211> 23
<212> DNA
<213> unknown
<400> 45
caacaagaac ccnccytacc agt 23
<210> 46
<211> 23
<212> DNA
<213> unknown
<400> 46
garcccagrc acatyttrta ytg 23
<210> 47
<211> 40
<212> DNA
<213> unknown
<400> 47
accagtaycg cctdcacagc tacmtgytsa gccgvaagat 40
<210> 48
<211> 35
<212> DNA
<213> unknown
<400> 48
tanachacyt tdgggtcrta ctgrctgaag atgat 35
<210> 49
<211> 23
<212> DNA
<213> unknown
<400> 49
atggtrgtga cnvartgygg ctg 23
<210> 50
<211> 23
<212> DNA
<213> unknown
<400> 50
ccrtcngarg trccrtcraa gca 23
<210> 51
<211> 29
<212> DNA
<213> unknown
<400> 51
acdggmtaca argghacmtt ctchrtcca 29
<210> 52
<211> 28
<212> DNA
<213> unknown
<400> 52
gtcnagdggb gcharcatdg tgaatctc 28
<210> 53
<211> 23
<212> DNA
<213> unknown
<400> 53
gagaacttya tggacatgga gtg 23
<210> 54
<211> 23
<212> DNA
<213> unknown
<400> 54
tkyctgttct grcagtcbga ctc 23
<210> 55
<211> 40
<212> DNA
<213> unknown
<400> 55
acatggagtg yttcatgatm ctgacyccba gccagcagct 40
<210> 56
<211> 40
<212> DNA
<213> unknown
<400> 56
ctcctcarrg crtagatgat bggrttgacr gtggagttga 40
<210> 57
<211> 23
<212> DNA
<213> unknown
<400> 57
cmcgyaarcg yagccayagy agc 23
<210> 58
<211> 23
<212> DNA
<213> unknown
<400> 58
gtggyygtga tvagbccdat cca 23
<210> 59
<211> 29
<212> DNA
<213> unknown
<400> 59
aaytggtaca gytgyggkga rggkgaggt 29
<210> 60
<211> 30
<212> DNA
<213> unknown
<400> 60
ahgtcatdgg ytgytgwggr ttsacrtgct 30
<210> 61
<211> 23
<212> DNA
<213> unknown
<400> 61
gaygargtbc ccaydgcvca ytc 23
<210> 62
<211> 23
<212> DNA
<213> unknown
<400> 62
tartgdgcrt cccacacrtc cat 23
<210> 63
<211> 30
<212> DNA
<213> unknown
<400> 63
ctbtchaary acagrgsvtg gggvaarcag 30
<210> 64
<211> 28
<212> DNA
<213> unknown
<400> 64
cgyarccact tdgmrcaytc yccyarct 28
<210> 65
<211> 23
<212> DNA
<213> unknown
<400> 65
gargccatcc chcagcatat caa 23
<210> 66
<211> 23
<212> DNA
<213> unknown
<400> 66
gcrtgbccng cngccatgta ctc 23
<210> 67
<211> 29
<212> DNA
<213> unknown
<400> 67
trggvaagct gcagtacctc tacctccag 29
<210> 68
<211> 28
<212> DNA
<213> unknown
<400> 68
atrtacttsg abtctgactt gtaggacg 28
<210> 69
<211> 23
<212> DNA
<213> unknown
<400> 69
ggcagccgyt ccttyccstg cca 23
<210> 70
<211> 23
<212> DNA
<213> unknown
<400> 70
gcytgrcagc tcatbckytt ggc 23
<210> 71
<211> 30
<212> DNA
<213> unknown
<400> 71
tgmgrgarag ycaggccagy gaggtbgact 30
<210> 72
<211> 29
<212> DNA
<213> unknown
<400> 72
tcrtagcact gmacyttggg sagyttgtc 29
<210> 73
<211> 23
<212> DNA
<213> unknown
<400> 73
ctsacvtggc tcagyttcat gct 23
<210> 74
<211> 23
<212> DNA
<213> unknown
<400> 74
cctcyckytc rtahgtmagc atg 23
<210> 75
<211> 30
<212> DNA
<213> unknown
<400> 75
cttcccdcty atygchcayt actacctcac 30
<210> 76
<211> 26
<212> DNA
<213> unknown
<400> 76
tcvccrttgt crgccakgtt rgcrtc 26
<210> 77
<211> 23
<212> DNA
<213> unknown
<400> 77
tcycgvtacg gacayytrga ggt 23
<210> 78
<211> 23
<212> DNA
<213> unknown
<400> 78
tcbgcrccrc actcyagsag cag 23
<210> 79
<211> 30
<212> DNA
<213> unknown
<400> 79
gctstgggcg gcbtckgcvg csggtcacct 30
<210> 80
<211> 29
<212> DNA
<213> unknown
<400> 80
ttgtcyacrg ccatgtgsag vggvgtgaa 29
<210> 81
<211> 23
<212> DNA
<213> unknown
<400> 81
atmtchgcvc tsackgcctc caa 23
<210> 82
<211> 23
<212> DNA
<213> unknown
<400> 82
tgctgygaga gmarytgrct gat 23
<210> 83
<211> 30
<212> DNA
<213> unknown
<400> 83
cgmaartcrg agarygarkc mtggcaggag 30
<210> 84
<211> 30
<212> DNA
<213> unknown
<400> 84
gaggtccraa bardagsakr ctscgaggta 30
<210> 85
<211> 23
<212> DNA
<213> unknown
<400> 85
cargadcarg avrccatgac tgc 23
<210> 86
<211> 23
<212> DNA
<213> unknown
<400> 86
ggdscyccrc ttgtsggkat gac 23
<210> 87
<211> 23
<212> DNA
<213> unknown
<400> 87
ctcagcmgrc agytngatga gct 23
<210> 88
<211> 23
<212> DNA
<213> unknown
<400> 88
agngtctcca tytctckggc cag 23
<210> 89
<211> 23
<212> DNA
<213> unknown
<400> 89
garmgsagcc tgacvtcwgt gcc 23
<210> 90
<211> 22
<212> DNA
<213> unknown
<400> 90
ccrttrgghg tgtaratggg ct 22
<210> 91
<211> 29
<212> DNA
<213> unknown
<400> 91
ctyttcctya ccaaraacca cytragcag 29
<210> 92
<211> 29
<212> DNA
<213> unknown
<400> 92
agctgytcat tgttyaghgm cactatctg 29
<210> 93
<211> 23
<212> DNA
<213> unknown
<400> 93
tcntcyccma cwgatgayga gcg 23
<210> 94
<211> 23
<212> DNA
<213> unknown
<400> 94
ggrctyttyt cmacrctygc yac 23
<210> 95
<211> 30
<212> DNA
<213> unknown
<400> 95
rgaracagat garcghmgdg chcarytkca 30
<210> 96
<211> 29
<212> DNA
<213> unknown
<400> 96
tgkgtbtgtg gytcctcytc ytcywcctc 29
<210> 97
<211> 23
<212> DNA
<213> unknown
<400> 97
gcmggrctbg aggtscacca gtt 23
<210> 98
<211> 23
<212> DNA
<213> unknown
<400> 98
gtgatbccsa ckatcatggt cat 23
<210> 99
<211> 40
<212> DNA
<213> unknown
<400> 99
ggvtgygarg csctsatgaa yaarttyggy ttccagtggc 40
<210> 100
<211> 40
<212> DNA
<213> unknown
<400> 100
tcatgaacac bgtgaagtcb ggvgwcatsg gggcraagtt 40
<210> 101
<211> 23
<212> DNA
<213> unknown
<400> 101
gytcwcgttc dcgcwsmyac agc 23
<210> 102
<211> 23
<212> DNA
<213> unknown
<400> 102
ggdgtgtgrt gragbgcaga rgc 23
<210> 103
<211> 23
<212> DNA
<213> unknown
<400> 103
agrcgbagca gctayagycg nag 23
<210> 104
<211> 29
<212> DNA
<213> unknown
<400> 104
agrtgrtgyt grggwatrtg rtgyacctg 29
<210> 105
<211> 23
<212> DNA
<213> unknown
<400> 105
aayatgwcya acctsrgygg ctc 23
<210> 106
<211> 23
<212> DNA
<213> unknown
<400> 106
tcrgargasc kvagattgtt cgc 23
<210> 107
<211> 30
<212> DNA
<213> unknown
<400> 107
acaactayat yttycarggn ggbcagcatc 30
<210> 108
<211> 30
<212> DNA
<213> unknown
<400> 108
ccargaagcg rtccttctcy ttbaggctga 30
<210> 109
<211> 23
<212> DNA
<213> unknown
<400> 109
gcdtgtgcma arccmagygt gct 23
<210> 110
<211> 23
<212> DNA
<213> unknown
<400> 110
gwvtgwccng gwgtdgtdgg cat 23
<210> 111
<211> 30
<212> DNA
<213> unknown
<400> 111
gctkctmaaa cacatmmgrt cycacacagg 30
<210> 112
<211> 28
<212> DNA
<213> unknown
<400> 112
grgrdggwac rgaragvagr aayactgg 28
<210> 113
<211> 23
<212> DNA
<213> unknown
<400> 113
aaraaccaga gtkgcyhtga acc 23
<210> 114
<211> 23
<212> DNA
<213> unknown
<400> 114
ccagctggtt gttctcyagc cag 23
<210> 115
<211> 40
<212> DNA
<213> unknown
<400> 115
gtbctgcagr atcatcaayg agaccsacrg cdgcmgccat 40
<210> 116
<211> 40
<212> DNA
<213> unknown
<400> 116
ttgctsagbc kgccyttrtc rttggtgatk gtgatyttgt 40
<210> 117
<211> 23
<212> DNA
<213> unknown
<400> 117
ccbttygtgg argartcwga cct 23
<210> 118
<211> 23
<212> DNA
<213> unknown
<400> 118
aaadgccatg tgggadygrt agc 23
<210> 119
<211> 29
<212> DNA
<213> unknown
<400> 119
agrccywtbg aaggyatgac yatcatgga 29
<210> 120
<211> 29
<212> DNA
<213> unknown
<400> 120
grtagctggg rcttgyycty ckgctgacc 29
<210> 121
<211> 23
<212> DNA
<213> unknown
<400> 121
gagcgyctbm gragytctat gtc 23
<210> 122
<211> 23
<212> DNA
<213> unknown
<400> 122
atgctgtcrt trtcvccrtc nga 23
<210> 123
<211> 30
<212> DNA
<213> unknown
<400> 123
gytttcbtty garggacctg araaagtcca 30
<210> 124
<211> 30
<212> DNA
<213> unknown
<400> 124
gaartcvgac tcngayttgc tytgbckgtt 30
<210> 125
<211> 23
<212> DNA
<213> unknown
<400> 125
garmgrgtgg tcatyaacat ctc 23
<210> 126
<211> 23
<212> DNA
<213> unknown
<400> 126
gcytcytgra tytccatrta gtc 23
<210> 127
<211> 38
<212> DNA
<213> unknown
<400> 127
agratgcgst ayttygaycc dctraggaay gartactt 38
<210> 128
<211> 40
<212> DNA
<213> unknown
<400> 128
tcdcgrtgrt agaagtagtt raarttkgas acdatgacag 40
<210> 129
<211> 23
<212> DNA
<213> unknown
<400> 129
gagmgvgact tyttyttcca cga 23
<210> 130
<211> 23
<212> DNA
<213> unknown
<400> 130
taraacatra csgtkgcraa gat 23
<210> 131
<211> 40
<212> DNA
<213> unknown
<400> 131
ttccacgagg agasvaryga rtwcttytty gaccgygacc 40
<210> 132
<211> 40
<212> DNA
<213> unknown
<400> 132
tgatggccat ggtgagvgar aakagbagga agccsagytc 40
<210> 133
<211> 23
<212> DNA
<213> unknown
<400> 133
atgatycgnc gcaayttcca caa 23
<210> 134
<211> 23
<212> DNA
<213> unknown
<400> 134
ttytgbggca tkgggtavcg ctg 23
<210> 135
<211> 40
<212> DNA
<213> unknown
<400> 135
gcaayttcca caargtyatc caggaygasg arttytacac 40
<210> 136
<211> 38
<212> DNA
<213> unknown
<400> 136
ttgcgrtact gcttrtchac rtcrtcrctr ttcttcca 38
<210> 137
<211> 23
<212> DNA
<213> unknown
<400> 137
gshccmccyg tbatgaacta cat 23
<210> 138
<211> 23
<212> DNA
<213> unknown
<400> 138
cvggbgabgt ytgratctgc ttc 23
<210> 139
<211> 26
<212> DNA
<213> unknown
<400> 139
atgtacmchc cdggtccvgc mcmgca 26
<210> 140
<211> 22
<212> DNA
<213> unknown
<400> 140
ggrtavggtg ghggnggrca gc 22
<210> 141
<211> 23
<212> DNA
<213> unknown
<400> 141
ttygarmgrg agcgvatggc nta 23
<210> 142
<211> 23
<212> DNA
<213> unknown
<220>
<221> misc_feature
<222> (7)..(7)
<223> n is a, c, g, or t
<400> 142
cagytcngcc ardgtcgatg cac 23
<210> 143
<211> 29
<212> DNA
<213> unknown
<400> 143
ggrgargcng gdgayttygc yvkyatggc 29
<210> 144
<211> 26
<212> DNA
<213> unknown
<400> 144
gatvacngag ttgcrbggyt cdatgt 26
<210> 145
<211> 23
<212> DNA
<213> unknown
<400> 145
tyccvtacct bgtbgtbatc cac 23
<210> 146
<211> 23
<212> DNA
<213> unknown
<400> 146
gttbtcyyta caggtctcar ctc 23
<210> 147
<211> 30
<212> DNA
<213> unknown
<400> 147
ctbgvsaaga tgyttygayt cnccbtggac 30
<210> 148
<211> 30
<212> DNA
<213> unknown
<400> 148
aggctraara tcrgcrctbg ggatncgytc 30
<210> 149
<211> 23
<212> DNA
<213> unknown
<400> 149
cccagyttyc crtggasyga gtt 23
<210> 150
<211> 23
<212> DNA
<213> unknown
<400> 150
tcnccraart ckgacagsga ctc 23
<210> 151
<211> 29
<212> DNA
<213> unknown
<400> 151
atycagacgc gyaaygaygg vagcaagtt 29
<210> 152
<211> 28
<212> DNA
<213> unknown
<400> 152
gcvgaragcg ghggctgncc rttgtcct 28
<210> 153
<211> 23
<212> DNA
<213> unknown
<400> 153
gchaayatht cngargacat gcc 23
<210> 154
<211> 22
<212> DNA
<213> unknown
<400> 154
ccbgtyccha craaggtgtt gg 22
<210> 155
<211> 29
<212> DNA
<213> unknown
<400> 155
gaytcyggna ayccdgcnct vtchagcac 29
<210> 156
<211> 30
<212> DNA
<213> unknown
<400> 156
gtcctgvacn gcytggtgyt tctkdgaggc 30
<210> 157
<211> 23
<212> DNA
<213> unknown
<400> 157
gtsgcbgara aygagmmrga gca 23
<210> 158
<211> 23
<212> DNA
<213> unknown
<400> 158
crchamrtct gacscctcvt cca 23
<210> 159
<211> 30
<212> DNA
<213> unknown
<400> 159
ctctgaracn ccbtgygtka acytncagct 30
<210> 160
<211> 30
<212> DNA
<213> unknown
<400> 160
aavacvtcmc krttccavcc catrgccatg 30
<210> 161
<211> 23
<212> DNA
<213> unknown
<400> 161
atggagggnr tcashgagtt yac 23
<210> 162
<211> 23
<212> DNA
<213> unknown
<400> 162
ttgbgtkgch achggrtabc kca 23
<210> 163
<211> 30
<212> DNA
<213> unknown
<400> 163
ttygacctbc tkgagccncc macntcygga 30
<210> 164
<211> 30
<212> DNA
<213> unknown
<400> 164
gttytgyggy gcrttyccrg graacarmac 30
<210> 165
<211> 23
<212> DNA
<213> unknown
<400> 165
cghccbaayc arctbgtsgg ytc 23
<210> 166
<211> 23
<212> DNA
<213> unknown
<400> 166
gtrcyrtcry tgtactgytc cca 23
<210> 167
<211> 30
<212> DNA
<213> unknown
<400> 167
gcdgcdytma gcaacatgyt dggbggmatg 30
<210> 168
<211> 27
<212> DNA
<213> unknown
<400> 168
agngcyctva cwgccarrta gttgatg 27
<210> 169
<211> 23
<212> DNA
<213> unknown
<400> 169
cacdgscaar ctgmggwctg act 23
<210> 170
<211> 23
<212> DNA
<213> unknown
<400> 170
agrttyccyc tkggrcghac ctc 23
<210> 171
<211> 29
<212> DNA
<213> unknown
<400> 171
caytcvccya aycacaacac hytdcargc 29
<210> 172
<211> 29
<212> DNA
<213> unknown
<400> 172
gcrctggabc cyggrctbgg raaratcat 29
<210> 173
<211> 23
<212> DNA
<213> unknown
<400> 173
aygcmtgyga rytgagrtgy cag 23
<210> 174
<211> 23
<212> DNA
<213> unknown
<400> 174
cdbccctgtc crtavgaytt gct 23
<210> 175
<211> 30
<212> DNA
<213> unknown
<400> 175
garrccrgtb gargtbcgyr tbgtgcarcg 30
<210> 176
<211> 29
<212> DNA
<213> unknown
<400> 176
tccakrccva rhccytcyct ggwraactg 29
<210> 177
<211> 23
<212> DNA
<213> unknown
<400> 177
gacacvgtkc tdgyrtcygg rga 23
<210> 178
<211> 23
<212> DNA
<213> unknown
<400> 178
cyacdggdcc ratrttgaca gta 23
<210> 179
<211> 30
<212> DNA
<213> unknown
<400> 179
ggvaaragca cmykrctyca gmgrctrcac 30
<210> 180
<211> 29
<212> DNA
<213> unknown
<400> 180
tgcatgctyt tcttytchcc yksyacagg 29
<210> 181
<211> 23
<212> DNA
<213> unknown
<400> 181
gghccrctba tygacmgrca gat 23
<210> 182
<211> 23
<212> DNA
<213> unknown
<400> 182
tcyckbyknc ccatgtgsac cag 23
<210> 183
<211> 30
<212> DNA
<213> unknown
<400> 183
gatyttymgn ttcagygarg arggcatggt 30
<210> 184
<211> 29
<212> DNA
<213> unknown
<400> 184
casgcmacrt araactcrtc sccrctgct 29
<210> 185
<211> 23
<212> DNA
<213> unknown
<400> 185
tcyagcachg ccatyctsca rgt 23
<210> 186
<211> 23
<212> DNA
<213> unknown
<400> 186
ttgatytgra abgtdggctg agg 23
<210> 187
<211> 23
<212> DNA
<213> unknown
<400> 187
gacaaygtyc chtcyataga cac 23
<210> 188
<211> 23
<212> DNA
<213> unknown
<400> 188
gtrgggtcdt caggcttgga ttc 23
<210> 189
<211> 23
<212> DNA
<213> unknown
<400> 189
casacgacca svgcytcmam cac 23
<210> 190
<211> 23
<212> DNA
<213> unknown
<400> 190
tgcttcatra actcvckgck ytg 23
<210> 191
<211> 30
<212> DNA
<213> unknown
<400> 191
gactayrcng acrchgactt yytgggtgac 30
<210> 192
<211> 30
<212> DNA
<213> unknown
<400> 192
tcytcyttgc tccagtascg dcccatcttc 30
<210> 193
<211> 23
<212> DNA
<213> unknown
<400> 193
cactayaaca cmaagctggg mta 23
<210> 194
<211> 23
<212> DNA
<213> unknown
<400> 194
tgctcctgag gttghggttg caa 23
<210> 195
<211> 30
<212> DNA
<213> unknown
<400> 195
cgvaargact tyctrtgcca gtactgygcc 30
<210> 196
<211> 30
<212> DNA
<213> unknown
<400> 196
cccagcagrt grgaraartc catgttagca 30
<210> 197
<211> 23
<212> DNA
<213> unknown
<400> 197
atggtstgya cyggsaagat gca 23
<210> 198
<211> 23
<212> DNA
<213> unknown
<400> 198
atgttytcwg araavgtrta gtt 23
<210> 199
<211> 40
<212> DNA
<213> unknown
<400> 199
cyggsaagat gcacachgay cgcatytgcc gcttygacta 40
<210> 200
<211> 40
<212> DNA
<213> unknown
<400> 200
trtaaggcat rtabgtrtty tctccytgct cytgkatcca 40
<210> 201
<211> 23
<212> DNA
<213> unknown
<400> 201
gactacycrc tgcagagcaa cag 23
<210> 202
<211> 23
<212> DNA
<213> unknown
<400> 202
ttytcyttct gtcttcctgt tac 23
<210> 203
<211> 40
<212> DNA
<213> unknown
<400> 203
ctgcagagca acagycacmc gctcagccac gcrcaccagt 40
<210> 204
<211> 40
<212> DNA
<213> unknown
<400> 204
ttcctgttac aaaaccaaac ycksacyacy tctttytcca 40
<210> 205
<211> 23
<212> DNA
<213> unknown
<400> 205
gtkccwgayc chcarytdga tga 23
<210> 206
<211> 23
<212> DNA
<213> unknown
<400> 206
tcccartcrc aytcytgrct ctg 23
<210> 207
<211> 29
<212> DNA
<213> unknown
<400> 207
garacvgarv tsaaagargg rgcwcagca 29
<210> 208
<211> 30
<212> DNA
<213> unknown
<400> 208
gartgytcyt tytcytgytg rggrtctctg 30
<210> 209
<211> 23
<212> DNA
<213> unknown
<400> 209
acvctbaayg aratgtggtg cca 23
<210> 210
<211> 23
<212> DNA
<213> unknown
<400> 210
agcagrtcrt tsatctgbtc cag 23
<210> 211
<211> 29
<212> DNA
<213> unknown
<400> 211
ggytccaagc arttyaarat ccacaccat 29
<210> 212
<211> 30
<212> DNA
<213> unknown
<400> 212
agvggraarc gytgcytgtr yctgvagatg 30
<210> 213
<211> 23
<212> DNA
<213> unknown
<400> 213
tctayatyat caacsttygg cat 23
<210> 214
<211> 23
<212> DNA
<213> unknown
<400> 214
gtgagvaggg agcayttgaa cag 23
<210> 215
<211> 39
<212> DNA
<213> unknown
<400> 215
atcaacstty ggcatgggwg cyagcccytt yacyaacat 39
<210> 216
<211> 30
<212> DNA
<213> unknown
<400> 216
agtgtavagr tgkggkgcac agtgatccat 30
<210> 217
<211> 23
<212> DNA
<213> unknown
<400> 217
tgggtscgsc acasctacar cca 23
<210> 218
<211> 23
<212> DNA
<213> unknown
<400> 218
catccctttc ttyttscggt tga 23
<210> 219
<211> 28
<212> DNA
<213> unknown
<400> 219
aayagygayg argacagcaa agayggca 28
<210> 220
<211> 29
<212> DNA
<213> unknown
<400> 220
cgngcnggcc accargggaa kccrtgrat 29
<210> 221
<211> 23
<212> DNA
<213> unknown
<400> 221
ttycaysmvt ttgartggca gcc 23
<210> 222
<211> 23
<212> DNA
<213> unknown
<400> 222
ctgaasagyt tgttbschga ctc 23
<210> 223
<211> 35
<212> DNA
<213> unknown
<400> 223
aargayctbg agagaggaca thatggargg dctga 35
<210> 224
<211> 38
<212> DNA
<213> unknown
<400> 224
gtcatyaryy kbcgrgcrta gttbccattc atcctcat 38
<210> 225
<211> 23
<212> DNA
<213> unknown
<400> 225
ttwggncara arggntggcc naa 23
<210> 226
<211> 24
<212> DNA
<213> unknown
<400> 226
catrcaytgn gcrtgnaccc artg 24
<210> 227
<211> 43
<212> DNA
<213> unknown
<400> 227
agggttttcc cagtcacgac ggwggkaara cnccnaayaa yga 43
<210> 228
<211> 40
<212> DNA
<213> unknown
<400> 228
agataacaat ttcacacagg carcayttda tccartancc 40
<210> 229
<211> 23
<212> DNA
<213> unknown
<400> 229
atgctstcvg gvtcyccdca gtc 23
<210> 230
<211> 23
<212> DNA
<213> unknown
<400> 230
agmccyctrg cytkctccac cca 23
<210> 231
<211> 29
<212> DNA
<213> unknown
<400> 231
cagtcytact gcrtbgtrga raartggag 29
<210> 232
<211> 30
<212> DNA
<213> unknown
<400> 232
chagytgsgt tytkatcctc tcytcytcca 30
<210> 233
<211> 23
<212> DNA
<213> unknown
<400> 233
tccagaycch acntaygarc tca 23
<210> 234
<211> 23
<212> DNA
<213> unknown
<400> 234
acrgtdcgnc cdgtctccat gca 23
<210> 235
<211> 30
<212> DNA
<213> unknown
<400> 235
ggyaaagtyc cyhtrmgrca gctkgtstac 30
<210> 236
<211> 29
<212> DNA
<213> unknown
<400> 236
gttcatyttk gcyggrtcva grgcccagt 29
<210> 237
<211> 23
<212> DNA
<213> unknown
<400> 237
garcagacyc argtggtggc yat 23
<210> 238
<211> 23
<212> DNA
<213> unknown
<400> 238
tytgwkgbkg gtggtgsakc tgc 23
<210> 239
<211> 30
<212> DNA
<213> unknown
<400> 239
gtrrtyacya argavcagcc matgagcatg 30
<210> 240
<211> 30
<212> DNA
<213> unknown
<400> 240
atsggkatyt gcatgggrta raagttctgc 30
<210> 241
<211> 23
<212> DNA
<213> unknown
<400> 241
aayathacna aygcntgyta yaa 23
<210> 242
<211> 23
<212> DNA
<213> unknown
<400> 242
gcraartgnc crttnacrtg raa 23
<210> 243
<211> 43
<212> DNA
<213> unknown
<400> 243
agggttttcc cagtcacgac tgytayaayg aytgyccntg gat 43
<210> 244
<211> 43
<212> DNA
<213> unknown
<400> 244
agataacaat ttcacacagg ckgtgrggyt tyttrtartt rtg 43
<210> 245
<211> 23
<212> DNA
<213> unknown
<400> 245
ggarcagytr gtswgyctyc agc 23
<210> 246
<211> 23
<212> DNA
<213> unknown
<400> 246
caratkggrc angagtgytg cat 23
<210> 247
<211> 30
<212> DNA
<213> unknown
<400> 247
carcarctbt ctgcwgcagc wgchctvatw 30
<210> 248
<211> 29
<212> DNA
<213> unknown
<400> 248
gtkgwgaang cvckgccrca gatyttgca 29
<210> 249
<211> 23
<212> DNA
<213> unknown
<400> 249
tcatyttytc yatmttyggc atg 23
<210> 250
<211> 23
<212> DNA
<213> unknown
<400> 250
ttbtcrggyt tggtyacrct gtc 23
<210> 251
<211> 39
<212> DNA
<213> unknown
<400> 251
gachtgtaya acttygarac nttyggmaac agyatgatc 39
<210> 252
<211> 30
<212> DNA
<213> unknown
<400> 252
gtgcyctcyt tyttytcttg ytcytgrttg 30
<210> 253
<211> 23
<212> DNA
<213> unknown
<400> 253
ccdcaygcyc trtchctscg sag 23
<210> 254
<211> 23
<212> DNA
<213> unknown
<400> 254
acctcrcavs crsaactgct gcc 23
<210> 255
<211> 30
<212> DNA
<213> unknown
<400> 255
aghtggaggt rtchtcwccm aarmtctaca 30
<210> 256
<211> 30
<212> DNA
<213> unknown
<400> 256
tcctcctmct mctscrccts cryyggscat 30
<210> 257
<211> 23
<212> DNA
<213> unknown
<400> 257
gayagytcwg ghggdgchgt bca 23
<210> 258
<211> 23
<212> DNA
<213> unknown
<400> 258
gcmacyytyt cnggytcrct gtc 23
<210> 259
<211> 29
<212> DNA
<213> unknown
<400> 259
gaymgmtgya cyacbgtvag yccngtggt 29
<210> 260
<211> 30
<212> DNA
<213> unknown
<400> 260
aggmaywtgg carggyttya gdakytgctc 30
<210> 261
<211> 23
<212> DNA
<213> unknown
<400> 261
gtvatagayg gycargagag act 23
<210> 262
<211> 23
<212> DNA
<213> unknown
<400> 262
ggyctgaang cvgabaygta gct 23
<210> 263
<211> 30
<212> DNA
<213> unknown
<400> 263
gtbgcbctkg gvatcacytg ygtscagatg 30
<210> 264
<211> 30
<212> DNA
<213> unknown
<400> 264
gyrggccara acatsggraa rgarkgrtag 30
<210> 265
<211> 23
<212> DNA
<213> unknown
<400> 265
atgctbtaca tggtvatygt gcc 23
<210> 266
<211> 23
<212> DNA
<213> unknown
<400> 266
agcagmagca rvgcyggygc gta 23
<210> 267
<211> 29
<212> DNA
<213> unknown
<400> 267
ctbttygcnt chaargccat ybtscagct 29
<210> 268
<211> 30
<212> DNA
<213> unknown
<400> 268
tchgcdatdg crtamatcrc trccrtacac 30
<210> 269
<211> 23
<212> DNA
<213> unknown
<400> 269
tacatgttcy tgggyatgtc cat 23
<210> 270
<211> 21
<212> DNA
<213> unknown
<400> 270
trgcctcrtg rcagctcacc a 21
<210> 271
<211> 40
<212> DNA
<213> unknown
<400> 271
tgttcytggg yatgtccatc athgcvgayc gbttcatgtc 40
<210> 272
<211> 38
<212> DNA
<213> unknown
<400> 272
gcrtgcttyt tcarratgtt yccngcyccg atcatcat 38
<210> 273
<211> 23
<212> DNA
<213> unknown
<400> 273
gargaratmg aygagccytg ctt 23
<210> 274
<211> 23
<212> DNA
<213> unknown
<400> 274
atvagvachg asaghggvac agc 23
<210> 275
<211> 30
<212> DNA
<213> unknown
<400> 275
cargayathc aygybggngc dttyaatcgg 30
<210> 276
<211> 29
<212> DNA
<213> unknown
<400> 276
atrtcrcang agcavtccca dggrttctg 29
<210> 277
<211> 23
<212> DNA
<213> unknown
<400> 277
acygtstaym grccbacrca gct 23
<210> 278
<211> 23
<212> DNA
<213> unknown
<400> 278
tcvtcvagyt crtcratggt gct 23
<210> 279
<211> 30
<212> DNA
<213> unknown
<400> 279
garaacytgg aatacctyca ggcygactac 30
<210> 280
<211> 30
<212> DNA
<213> unknown
<400> 280
aggcaraarg cacacraava cwgtnaggat 30
<210> 281
<211> 23
<212> DNA
<213> unknown
<400> 281
gayttygtca tgctycagca gcc 23
<210> 282
<211> 23
<212> DNA
<213> unknown
<400> 282
taytgyagvg arcgcacttg cat 23
<210> 283
<211> 28
<212> DNA
<213> unknown
<400> 283
gargtvaaag cycagmgrcc cytnagat 28
<210> 284
<211> 29
<212> DNA
<213> unknown
<400> 284
ccytcbacrt cdggctgctc rtaraagct 29
<210> 285
<211> 23
<212> DNA
<213> unknown
<400> 285
atycchcgng aggtggagat gga 23
<210> 286
<211> 23
<212> DNA
<213> unknown
<400> 286
cgytchagna rccactgcat ggt 23
<210> 287
<211> 30
<212> DNA
<213> unknown
<400> 287
acvccngagt gggaygtktc nggggagact 30
<210> 288
<211> 29
<212> DNA
<213> unknown
<400> 288
tthcgcagaw gtgccdgact tkgwgtagc 29
<210> 289
<211> 23
<212> DNA
<213> unknown
<400> 289
gcycgtytga rrgargcbcg dga 23
<210> 290
<211> 23
<212> DNA
<213> unknown
<400> 290
ctvagagcng ccacdatyct vag 23
<210> 291
<211> 30
<212> DNA
<213> unknown
<400> 291
agcarcarcc ygcyctrtcy gargccatga 30
<210> 292
<211> 30
<212> DNA
<213> unknown
<400> 292
cmacytgcat rgccatbgcy tkrtggtcct 30
<210> 293
<211> 23
<212> DNA
<213> unknown
<400> 293
gacagcacvm grgtyagctt cac 23
<210> 294
<211> 23
<212> DNA
<213> unknown
<400> 294
tartctcykc tcbccraagt gca 23
<210> 295
<211> 39
<212> DNA
<213> unknown
<400> 295
gacmggcaga thttycagst tcagygarga yggcatggt 39
<210> 296
<211> 30
<212> DNA
<213> unknown
<400> 296
taraactcyt cnccrctrct dattctccat 30
<210> 297
<211> 23
<212> DNA
<213> unknown
<400> 297
agyccstgyt ccaayggyta cat 23
<210> 298
<211> 23
<212> DNA
<213> unknown
<400> 298
cctgrtagkc yggmggrgaa ggt 23
<210> 299
<211> 30
<212> DNA
<213> unknown
<400> 299
cctsgtcatg ctctaygtgg tytacctkgt 30
<210> 300
<211> 30
<212> DNA
<213> unknown
<400> 300
tgghvcgrtg gcagcgytcr carttctgcc 30
<210> 301
<211> 23
<212> DNA
<213> unknown
<400> 301
gagcarbtgg crkcngayca cag 23
<210> 302
<211> 23
<212> DNA
<213> unknown
<400> 302
cccaryctyy tytccttctg ctc 23
<210> 303
<211> 31
<212> DNA
<213> unknown
<400> 303
ggnatgaarg argaraacag ycayytgaaa g 31
<210> 304
<211> 31
<212> DNA
<213> unknown
<400> 304
ttvacygtbg tgatsacctg cwkcttccac t 31
<210> 305
<211> 23
<212> DNA
<213> unknown
<400> 305
aactcyccac tyagcaatgg cac 23
<210> 306
<211> 23
<212> DNA
<213> unknown
<400> 306
ggagytgrta rgcrgcrtga atg 23
<210> 307
<211> 30
<212> DNA
<213> unknown
<400> 307
tgcaaayytg atytcdgayg cytcytggtc 30
<210> 308
<211> 29
<212> DNA
<213> unknown
<400> 308
tgrgcyttrc tgatwgcact kgaracwgt 29
<210> 309
<211> 23
<212> DNA
<213> unknown
<400> 309
gagctggtga argtratggg dct 23
<210> 310
<211> 23
<212> DNA
<213> unknown
<400> 310
tactggaacc artamacngt ctc 23
<210> 311
<211> 36
<212> DNA
<213> unknown
<400> 311
ggvagcctba tmtacctsca ygacacyytg gaggag 36
<210> 312
<211> 35
<212> DNA
<213> unknown
<400> 312
cchtcccagw artgyttgaa sccrcabccr cactt 35
<210> 313
<211> 23
<212> DNA
<213> unknown
<400> 313
catatcdcca cgdgayagta cca 23
<210> 314
<211> 23
<212> DNA
<213> unknown
<400> 314
atggcttcry thacaatgag gtc 23
<210> 315
<211> 30
<212> DNA
<213> unknown
<400> 315
tgagrcaygt rcgaagggct caycccactg 30
<210> 316
<211> 30
<212> DNA
<213> unknown
<400> 316
tggctgaaga tccagtgcra gcatttctgc 30
<210> 317
<211> 23
<212> DNA
<213> unknown
<400> 317
acbaacacyg ccatywccca gct 23
<210> 318
<211> 23
<212> DNA
<213> unknown
<400> 318
gctggcytgc aysgggggca tga 23
<210> 319
<211> 29
<212> DNA
<213> unknown
<400> 319
gacttcaayg actayaagct satgatggc 29
<210> 320
<211> 29
<212> DNA
<213> unknown
<400> 320
ttggacagrt argccargtt sarmggctc 29
<210> 321
<211> 23
<212> DNA
<213> unknown
<400> 321
ggbgagsysa adttyggnga cac 23
<210> 322
<211> 23
<212> DNA
<213> unknown
<400> 322
tctkrygctc kvtcngagaa gtc 23
<210> 323
<211> 29
<212> DNA
<213> unknown
<400> 323
ggrctcttyt ggggnccnyt stgctgctc 29
<210> 324
<211> 29
<212> DNA
<213> unknown
<400> 324
ggraggaarg cvggrtcrkt rgwcttctg 29
<210> 325
<211> 23
<212> DNA
<213> unknown
<400> 325
gycarccwat yagcagycag atg 23
<210> 326
<211> 23
<212> DNA
<213> unknown
<400> 326
gtsgtggadc ggctgatgga ctg 23
<210> 327
<211> 30
<212> DNA
<213> unknown
<400> 327
tgyggcaarc gyttccgytt yaacagcatc 30
<210> 328
<211> 30
<212> DNA
<213> unknown
<400> 328
gckgvtgctg stgctgtgmt cyttnggcat 30
Claims (12)
1. The universal nuclear gene molecular marker primer kit for the fishes is characterized by comprising an NP11 primer pair; wherein, the NP11 primer pair is shown as SEQ NO. 41-SEQ NO. 44.
2. The kit of claim 1, further comprising one of NP 1-NP 10 or NP 12-NP 82, wherein NP1 is shown as SEQ NO. 1-SEQ NO.4, NP2 is shown as SEQ NO. 5-SEQ NO.8, NP3 is shown as SEQ NO. 9-SEQ NO.12, NP4 is shown as SEQ NO. 13-SEQ NO.16, NP5 is shown as SEQ NO. 17-SEQ NO.20, NP6 is shown as SEQ NO. 21-SEQ NO.24, NP7 is shown as SEQ NO. 25-SEQ NO.28, NP8 is shown as SEQ NO. 29-SEQ NO.32, NP9 is shown as SEQ NO. 33-SEQ NO.36, NP10 is shown as SEQ NO. 37-SEQ NO.40, NP12 is shown as SEQ NO. 17-SEQ NO.20, NP6 is shown as SEQ NO. 25-SEQ NO.28, NP8 is shown as SEQ NO. 29-SEQ NO.32, primer pair NP15 is shown as SEQ No. 57-SEQ No.60, primer pair NP16 is shown as SEQ No. 61-SEQ No.64, primer pair NP17 is shown as SEQ No. 65-SEQ No.68, primer pair NP18 is shown as SEQ No. 69-SEQ No.72, primer pair NP19 is shown as SEQ No. 73-SEQ No.76, primer pair NP20 is shown as SEQ No. 77-SEQ No.80, primer pair NP21 is shown as SEQ No. 81-SEQ No.84, primer pair NP22 is shown as SEQ No. 85-SEQ No.88, primer pair NP23 is shown as SEQ No. 89-SEQ No.92, primer pair NP24 is shown as SEQ No. 93-SEQ No.96, primer pair NP25 is shown as SEQ No. 97-SEQ No.100, primer pair NP26 is shown as SEQ No. 101-SEQ No.104, primer pair NP27 is shown as SEQ No. 105-SEQ No.108, primer pair NP22 is shown as SEQ No. 85-SEQ No.88, primer pair NP24 is shown as SEQ No. 19-SEQ No. 116-124, primer pair NP23 is shown as SEQ No.112 and primer pair NP19 is shown as SEQ No. 116-124, primer pair NP32 is shown as SEQ No. 125-SEQ No.128, primer pair NP33 is shown as SEQ No. 129-SEQ No.132, primer pair NP34 is shown as SEQ No. 133-SEQ No.136, primer pair NP35 is shown as SEQ No. 137-SEQ No.140, primer pair NP36 is shown as SEQ No. 141-SEQ No.144, primer pair NP37 is shown as SEQ No. 145-SEQ No.148, primer pair NP38 is shown as SEQ No. 149-SEQ No.152, primer pair NP39 is shown as SEQ No. 153-SEQ No.156, primer pair NP40 is shown as SEQ No. 157-SEQ No.160, primer pair NP41 is shown as SEQ No. 161-SEQ No.164, primer pair NP42 is shown as SEQ No. 165-SEQ No.168, primer pair NP43 is shown as SEQ No. 141-SEQ No.144, primer pair NP37 is shown as SEQ No. 176-SEQ No.176, primer pair NP38 is shown as SEQ No. 149-SEQ No.152, primer pair NP39 is shown as SEQ No. 153-SEQ No.156, primer pair NP40 is shown as SEQ No. 157-SEQ No.160, primer pair NP41 is shown as SEQ No. 161-SEQ No.161, primer pair NP 180 is shown as SEQ No.180, primer pair NP50 is shown as SEQ NO. 197-SEQ NO.200, primer pair NP51 is shown as SEQ NO. 201-SEQ NO.204, primer pair NP52 is shown as SEQ NO. 205-SEQ NO.208, primer pair NP53 is shown as SEQ NO. 209-SEQ NO.212, primer pair NP54 is shown as SEQ NO. 213-SEQ NO.216, primer pair NP55 is shown as SEQ NO. 217-SEQ NO.220, primer pair NP56 is shown as SEQ NO. 221-SEQ NO.224, primer pair NP57 is shown as SEQ NO. 225-SEQ NO.228, primer pair NP58 is shown as SEQ NO. 229-SEQ NO.232, primer pair NP 59-SEQ NO.236, primer pair NP60 is shown as SEQ NO. 237-SEQ NO.240, primer pair NP61 is shown as SEQ NO. 241-SEQ NO.216, primer pair NP62 is shown as SEQ NO. 245-248, primer pair NP57 is shown as SEQ NO. 225-SEQ NO.264 is shown as SEQ NO. 25-SEQ NO.228, primer pair NP58 is shown as SEQ NO. 59-SEQ NO. 59, primer pair NP59 is shown as SEQ NO. 59-SEQ NO.236, primer pair NP67 is shown as SEQ NO. 265-SEQNO. 268, primer pair NP68 is shown as SEQ NO. 269-SEQNO. 272, primer pair NP69 is shown as SEQ NO. 273-SEQNO. 276, primer pair NP70 is shown as SEQ NO. 277-SEQNO. 280, primer pair NP71 is shown as SEQ NO. 281-SEQNO. 284, primer pair NP72 is shown as SEQ NO. 285-SEQNO. 288, primer pair NP73 is shown as SEQ NO. 289-SEQNO. 292, primer pair NP74 is shown as SEQ NO. 293-SEQNO. 296, primer pair NP75 is shown as SEQ NO. 297-SEQNO. 300, primer pair NP76 is shown as SEQ NO. 301-SEQNO. 304, primer pair NP77 is shown as SEQ NO. 305-SEQNO. 308, primer pair NP78 is shown as SEQ NO. 309-SEQNO. 312, primer pair NP72 is shown as SEQ NO. 285-SEQNO. 313, primer pair NP74 is shown as SEQ NO. 321-SEQNO. 324, and primer pair NP 80-325 is shown as SEQ NO. 82-SEQ NO. 324.
3. The fish universal nuclear gene molecular marker primer kit according to claim 1, further comprising an NP12 primer pair and an NP13 primer pair; wherein, the primer pair NP12 is shown as SEQ NO. 45-SEQ NO.48, and the primer pair NP13 is shown as SEQ NO. 49-SEQ NO. 52.
4. The fish universal nuclear gene molecular marker primer kit according to claim 1, further comprising primer pairs of NP12, NP13 and NP 14; wherein, the primer pair NP12 is shown as SEQ NO. 45-SEQ NO.48, the primer pair NP13 is shown as SEQ NO. 49-SEQ NO.52, and the primer pair NP14 is shown as SEQ NO. 53-SEQ NO. 56.
5. A fish universal nuclear gene molecular marker formed by amplification of a primer contained in the fish universal nuclear gene molecular marker primer kit according to any one of claims 1 to 4.
6. A database of fish universal nuclear gene molecular markers comprising the fish universal nuclear gene molecular markers of claim 5.
7. The universal fish nuclear gene molecular marker primer kit according to any one of claims 1-4, the universal fish nuclear gene molecular marker according to claim 5 and the universal fish nuclear gene molecular marker database according to claim 6 are used for preparing reagents for identifying fish germplasm resources and categories.
8. A method for identifying species of fish, comprising the steps of:
a1, obtaining DNA of a fish to be identified;
a2, carrying out PCR amplification by using the universal fish nuclear gene molecular marker primer kit of claim 1;
a3, carrying out high-throughput sequencing on the PCR amplification product obtained in the A2, comparing the PCR amplification product with the universal nuclear gene molecular marker database of the fish according to the molecular marker matched with the fish to be identified in the molecular marker database, and acquiring species information of the fish to be identified according to a phylogenetic classification tree established on the basis of the molecular marker database.
9. A kit comprising the fish universal nuclear gene molecular marker of claim 5; or comprises the universal fish nuclear gene molecular marker of claim 5 and the universal fish nuclear gene molecular marker primer kit of any one of claims 1-4.
10. The kit according to claim 9, further comprising reagents required for a PCR amplification system of the fish universal nuclear gene molecular marker primer kit according to any one of claims 1 to 4.
11. A phylogenetic model, which is characterized in that the phylogenetic model is constructed by a fish universal nuclear gene molecular marker primer kit according to any one of claims 1 to 4, a fish universal nuclear gene molecular marker according to claim 5 and/or a fish universal nuclear gene molecular marker database according to claim 6.
12. The phylogenetic model of claim 11, comprising a phylogenetic tree.
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| CN107841563A (en) * | 2017-11-22 | 2018-03-27 | 镇江华大检测有限公司 | Differentiate the molecular specificity labeled primers and method of catfish |
| CN109486958A (en) * | 2018-09-26 | 2019-03-19 | 浙江海洋大学 | A kind of EPIC molecular labeling for Sciaenidae fish Phylogenetic Analysis |
| CN112695072A (en) * | 2019-10-23 | 2021-04-23 | 南京尧顺禹生物科技有限公司 | Method for rapidly and effectively identifying embryo genotype of living zebra fish |
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| WO2000042210A2 (en) * | 1999-01-15 | 2000-07-20 | International Paper Company | Microsatellite dna markers and uses thereof |
| CN105002170A (en) * | 2015-07-31 | 2015-10-28 | 中国长江三峡集团公司 | Amur sturgeon germplasm molecular marker identification kit and application thereof |
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