In response to the journal’s requirements:

1. We have formatted the manuscript according to PLOS ONE’s style templates, including adjustments to the title and author sections. The document now adheres to the specified formatting guidelines, including Letter paper size, Times New Roman font (12 pt), and double-spaced lines.

2. We have reviewed the guidelines for preparing figures and blot/gel data. All raw gel images underlying our figures have been provided as Supporting Information (S1 Raw images). Additionally, we have detailed any unavailable raw image data for clarity.

3. Figures have been removed from the main manuscript and are submitted as individual TIFF files. The file previously named "Supportingfile_OriginalGel_Figure.pdf" has been revised to "S1 Raw images.pdf," with the duplication of Figure 3 removed.

4. The Sequence data used in the study have been updated with their DRA accession numbers and links.

Line 113: DRA007145 (https://www.ncbi.nlm.nih.gov/sra/?term=DRA007145)

Line 124: DRA018635 (https://www.ncbi.nlm.nih.gov/sra/?term=DRA018635)

Line 237: We are currently in the process of obtaining accession numbers for the sequences of PCR amplicons described in the Materials & Methods section. We can provide this information as soon as the accession numbers become available.

In response to Reviewers:

Comments 1

1. Consider changing the title to “A PCR primer design method for identifying spider mite species using k-mers” or “... using k-mer counts” or “... using k-mer counting”. There are several algorithms for k-mer counting and there is no discussion of those in the paper and that is also not necessary. What matters for the paper is the concept of unique k-mers, not the algorithm used to identify those.

Response 1

We revised the title accordingly. Please refer to line 4.

Before Revision

A PCR primer design method for identifying spider mite species using the k-mer counting algorithm

After Revision (line 4, Revised MS (clean copy))

A PCR primer design method for identifying spider mite species using the k-mer counting

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Comments 2

2. Describe literature for species diagnostic PCR and the way it is used to diagnose species. There are instances where the PCR products have different known lengths for the different species and the diagnosis is based on comparing the query length to the expected lengths for each species. There are instances where the PCR product is sequenced and certain known variants are used to diagnose the species. In this case, the PCR primers should only work in a single species so whether or not PCR amplification is observed is used to diagnose species.

Response 2

The points you raised regarding the use of species- specific diagnostic PCR methods have been incorporated into the manuscript. Please refer to line 37.

Before Revision

Among its many uses, the polymerase chain reaction (PCR) can be used for distinguishing morphologically similar species. Designing the PCR primers to be specific for the target is essential.

After Revision (line 37, Revised MS (clean copy)))

Polymerase chain reaction (PCR) is a method for amplifying DNA fragments in vitro [1]. Because of its convenience and low cost, PCR has become a standard technique not only for biomedical, infectious disease, and forensic applications but also in other fields of biology, such as agricultural and ecological research. Among its many uses, PCR can be used to distinguish morphologically similar species. For example, PCR-RFLP (restriction fragment length polymorphism) distinguishes closely related species by using a single restriction enzyme to produce fragments of different lengths from DNA markers [2-4]. Another method is to design species-specific primers that can only be amplified in certain species and to identify the species based on successful PCR amplification and correct product size [5-7].

1. Mullis K, Faloona F. Specific synthesis of DNA in vitro via a polymerase-catalyzed chain reaction. Methods Enzymol. 1987;155: 335–350.

2. Clark TL, Meinke LJ, Foster JE. PCR–RFLP of the mitochondrial cytochrome oxidase (subunit I) gene provides diagnostic markers for selected Diabrotica species (Coleoptera: Chrysomelidae). Bull Entomol Res. 2001;91: 419–427.

3. Asraoui JF, Sayar NP, Knio KM, Smith CA. Fly diversity revealed by PCR-RFLP of mitochondrial DNA. Biochem Mol Biol Educ. 2008;36: 354–362.

4. Chua TH, Chong YV, Lim SH. Species determination of Malaysian Bactrocera pests using PCR-RFLP analyses (Diptera: Tephritidae). Pest Manag Sci. 2010;66: 379–384.

5. Lu W-N, Wu Y-T, Kuo M-H. Development of species-specific primers for the identification of aphids in Taiwan. Appl Entomol Zool (Jpn). 2008;43: 91–96.

6. Zhang T, Wang Y-J, Guo W, Luo D, Wu Y, Kučerová Z, et al. DNA barcoding, species-specific PCR and real-time PCR techniques for the identification of six Tribolium pests of stored products. Sci Rep. 2016;6: 28494.

7. Zhao Z-H, Cui B-Y, Li Z-H, Jiang F, Yang Q-Q, Kučerová Z, et al. The establishment of species-specific primers for the molecular identification of ten stored-product psocids based on ITS2 rDNA. Sci Rep. 2016;6: 21022.

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Comments 3

3. Motivate why the primers are designed from RNA-Seq data and not from whole genome short read data. The authors briefly mention why they don’t work with genome assemblies (because these are available for fewer species than the RNA-Seq data), but they do not consider whole genome DNA data (without necessarily making this into a genome assembly, but rather work with the reads directly or aligned to an available genome assembly of a related species). Using whole genome data would probably result in more available targets because A) a lot more sequence is considered and B) non-transcribed regions are often less constrained in accumulating variation so likely there are many more species-informative regions among non-transcribed regions.

Response 3

We have added additional information about whole-genome short-read data in the Introduction section. Please refer to line 69.

Before Revision

On the other hand, transcriptome RNA-Seq data for more than 50 species in the family Tetranychidae are publicly available [22].

After Revision (line 69, Revised MS (clean copy))

Using whole genome data would likely increase the number of available targets and the number of sequences and non-transcribed regions considered. However, publicly available sequencing resources for spider mites (Acari, Tetranychidae) are limited, with only 13 species having whole genome short-read data deposited in the SRA, compared to 79 species with available RNA-Seq data [29] (according to the NCBI SRA database accessed on 24 December 2024). In a previous study, we performed RNA-Seq analysis on 72 species (73 strains) of spider mites. The resulting data have been made publicly available in DRA/SRA/ERA databases under the accession number DRA007145.

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Comments 4-a

4. The methods are a bit difficult to follow. To my understanding, RNA reads are assembled and contigs would represent an observed transcript. Then, by orthology search from the annotated T. urticae genome, those contigs corresponding to an intronless gene are selected, and alignments of the 19 species are generated for each gene. On those selected contigs, 30-mers are counted and unique 30-mers were used for primer design. The paired primer was selected manually.

a. Why are alignments done separately for CDS and 5’ and 3’ sequence, also using different alignment methods?

Response 4-a

It is common practice to align coding sequences (CDSs) and untranslated regions (UTRs) separately, as demonstrated in the following previous studies. This approach is necessary because obtaining full-length transcripts across all species is challenging when using Illumina short-read sequencing technology.

Chua, B. H., McMinn, P. C., Lam, S. K. & Chua, K. B. Comparison of the complete nucleotide sequences of echovirus 7 strain UMMC and the prototype (Wallace) strain demonstrates significant genetic drift over time. J. Gen. Virol. 82, 2629–2639 (2001).

Wang, X.-W. et al. Transcriptome analysis and comparison reveal divergence between two invasive whitefly cryptic species. BMC Genomics 12, 458 (2011).

Cheng, J., Zhang, L., Hui, M., Li, Y. & Sha, Z. Insights into adaptive divergence of Japanese mantis shrimp Oratosquilla oratoria inferred from comparative analysis of full-length transcriptomes. Front. Mar. Sci. 9, 975686 (2022).

CDSs were aligned using DIALIGN-TX, which accounts for amino acid sequences to improve alignment accuracy. In contrast, 3' and 5' UTR were aligned using MAFFT, a widely used alignment tool, as considering amino acid sequences is not necessary for these non-coding regions. We have mentioned to these in the Materials & Methods section. Please refer to line 201.

Added text (line 201, Revised MS (clean copy))

CDSs were aligned using DIALIGN-TX, which considers amino acid sequences to improve alignment accuracy, as described in the section 'Identification of putative orthologous genes.' In contrast, 3' and 5' UTR sequences were aligned using MAFFT [56], a widely used alignment tool, as considering amino acid sequences is not necessary for these non-coding regions.

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Comments 4-b

b. In figure 2 there seems to be a step missing, the phylogenetic trees are constructed to distinguish orthologous genes from paralogous genes, true? Also please mention what the distinguishing characteristic is between orthologous and paralogous genes in a phylogenetic tree (now it just says ‘identified visually’).

Response 4-b

Despite recent advances, all existing ortholog detection methods still suffer from false positive and false negative rates. For example, OrthoFinder is widely used to estimate orthologous genes, providing robust phylogenetic inference and orthogroup identification. However, by definition, orthogroups identified using this method may contain both orthologs and paralogs, as OrthoFinder groups all related sequences together without fully distinguishing between the two. Therefore, it is not always possible to completely exclude paralogs entirely using this approach.

We therefore constructed a phylogenetic tree to distinguish between orthologous and paralogous genes. A gene was classified as a paralog if its phylogenetic relationship clearly deviated from the established relationships within known spider mite family Tetranychidae

For example, as illustrated in the figure below, if the phylogenetic tree showed that the sequence from "T. truncatus (1765_T_tru_com938.seq3.p1)" does not cluster with sequences from other species in a manner consistent with their known evolutionary relationships, it was identified as a paralog rather than an ortholog. If a phylogenetic tree included paralogs, the genes used to construct that tree were excluded from the analysis. This visual assessment was based on the topology of the tree and the divergence of specific clades.

We have added these to the Materials & Methods section. Please refer to line 144.

Before Revision

Then, phylogenetic trees based on each orthologous gene were constructed using RAxML [45].

After Revision (line 144, Revised MS (clean copy))

Despite recent advances, existing ortholog detection methods still suffer from false-positive and false-negative rates. We therefore constructed a phylogenetic tree using RAxML [52] to differentiate between orthologous and paralogous genes. A gene was classified as a paralog if its phylogenetic relationship distinctly deviated from the established relationships among known spider mite species in the family Tetranychidae [29].

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Comments 4-c

c. In the Extracting unique k-mers section the criteria could be ordered differently for ease of understanding.

i. Start with requirement 9, which is the crucial step, namely retain only unique k-mers (unique within and across species). NB: the ‘and’ should be replaced by ‘or’ to achieve (unique within and across species).

ii. Then introduce/motivate the remaining requirements: they are important for primer binding/open chromatin or other reasons why they were implemented.

iii. In requirement 6,7,8 replace ‘and’ by ‘or’. A number cannot be smaller than 11 and greater than 17 at the same time.

iv. Add ‘primer melting Temperature’ in brackets after Tm.

Response 4-c

We agree with your observations. As a result, we have revised the structure of these sections to follow a more logical order, ensuring a clearer presentation of each item and its purpose. Please refer to line 158.

Before Revision

The k-mers obtained from Jellyfish were filtered by the following requirements.

1. When a k-mer contained four or more runs of a single base (e.g., AAAAA and GGGG), the k-mer was removed.

2. When both 5' and 3' ends of a k-mer were A or T, the k-mer was removed.

3. When both 5' and 3' ends of a k-mer were three or more of G or C, the k-mer was removed.

4. When both 5' and 3' ends of a k-mer were three or more of A or T, the k-mer was removed.

5. When a k-mer contained more than three times of dinucleotide repeats (e.g., ATATAT and CGCGCG), the k-mer was removed.

6. When the GC content of full-length k-mer (30 mers) was less than 11 and greater than 17, the k-mer was removed.

7. When the GC content of the former and latter half of k-mer (15 mers) was less than four and greater than 10, the k-mer was removed.

8. When the Tm value of k-mer was less than 67 and greater than 82, the k-mer was removed.

9. When a k-mer matched another k-mer within the species and a k-mer of another species, the k-mer was removed.

After Revision (line 158, Revised MS (clean copy))

Primer specificity for species-specific detection:

1. If a k-mer matched another k-mer within the same species or a k-mer of another species, the k-mer was removed.

Tm (primer melting temperature):

2. If the Tm value of a k-mer was less than 67 or greater than 82, the k-mer was removed.

GC Content: Preferably in the range of 40%–60%. Include 1–2 G or C bases at the 3' end to improve binding stability; however, avoid excessive GC content at the 3' terminus to prevent non-specific binding.

3. If the GC content of a full-length k-mer (30-mers) was less than 11 or greater than 17, the k-mer was removed.

4. If the GC content of the former or latter half of a k-mer (15-mers) was less than four or greater than 10, the k-mer was removed.

5. If both the 5' and 3' ends of a k-mer were A or T, the k-mer was removed.

6. If both the 5' and 3' ends of a k-mer contained three or more of G or C, the k-mer was removed.

7. If both the 5' and 3' ends of a k-mer contained three or more of A or T, the k-mer was removed.

Avoid Repeats and Runs: Prevent intra-primer and inter-primer complementarity to reduce primer-dimer formation.

8. If a k-mer contained four or more runs of a single base (e.g., AAAAA or GGGG), the k-mer was removed.

9. If a k-mer contained more than three times of dinucleotide repeats (e.g., ATATAT or CGCGCG), the k-mer was removed.

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Comments 4-d

d. In the Filtering k-mers section, it seems a bit roundabout to use bowtie and blastn to filter k-mers for similarity to the contigs. Under the hood this can probably also be phrased as a k-mer matching criterion. I’m curious to know whether you really need bowtie and blast to get a well filtered set or whether by tweaking the parameters you can get the same level of filtering by just using one of these programs.

R

Attachments

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Submitted filename: Response to Reviewers.docx

In response to the journal’s requirements:

We have thoroughly reviewed our reference list to ensure its completeness and accuracy, and we confirm that no retracted articles are cited. Additionally, we have rechecked the formatting and made minor adjustments as necessary.

Furthermore, we have made the following revisions:

・Added clarifications to the manuscript in response to the reviewers' comments.

・Registered the detailed experimental procedures on protocols.io. Once the review process on protocols.io is complete, we will include the DOI in the manuscript.

・Added a column in Table 2 for entering accession numbers. We are currently in the process of obtaining these numbers and are awaiting a response from the DNA Data Bank of Japan (DDBJ).

・Identified and corrected duplicate entries in Table S2. Consequently, we have updated the manuscript to reflect the correct number of primers, revising the description from "45 primers" to "43 primers."

In response to Reviewers:

Reviewer #2's comments 1

I would remove "the" from the title, so:

A PCR primer design method for identifying spider mite species using the k-mer counting

Response 1

In the manuscript, we had already removed 'the'; however, the title entered in the submission form still included it. The manuscript already contained the correct title, so we have now updated the title in the submission form accordingly.

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Reviewer #2's comments 2

Re comment 5: did you recycle any of the methods from the initial candidate primer identification steps to check the specificity/uniqueness of the complementary primer?

Response 2

We appreciate your suggestion and have conducted an additional BLASTN search to further verify the specificity and uniqueness of the complementary primer. This step has been incorporated into the manuscript.

Added text (line 210, Revised MS (clean copy))

To confirm the uniqueness of the species-specific primers, we conducted additional BLASTN searches to compare the species-specific primers with the contigs from the 19 assemblies after clustering with CD-HIT.

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Reviewer #2's comments 3

Re comment 6: are there any heuristics for which primers pairs to pick first or was that completely at random? And then select another pair at random if the first pair failed?

All other comments have been satisfactorily addressed.

Response 3

The primer pairs were primarily designed at random, including cases where the initial primer failed. However, since alignments were checked when designing the primer pairs, if an alignment was particularly suitable for primer design, additional primers were sometimes designed from the same contig. As a result, there are cases where primers were designed from the same transcript, such as XM_015937235.2 (tetur01g00100) and NW_015449938.1 (tetur09g06570) in S2 Table. We have also incorporated this clarification into the manuscript.

Added text (line 259, Revised MS (clean copy))

The primer pairs were initially designed randomly. However, since sequence alignments were carefully examined during the primer design process, additional primers were occasionally designed from the same contig when a particular alignment was deemed highly suitable for primer design. As a result, multiple primers were designed from the same transcript in certain cases, such as XM_015937235.2 and NW_015449938.1, as shown in Table 2 and S2 Table. Finally, 43 PCR primers were designed to target species-specific sequences.

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Submitted filename: Response to Reviewers 20250217.docx