Characterization of Novel Genotyping-by-sequencing (GBS)-based Simple Sequence Repeats (SSRs) and Their Application for Population Genomics of Capoeta Aculeata (Valenciennes, 1844)

doi:10.21203/rs.3.rs-514326/v1

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Characterization of Novel Genotyping-by-sequencing (GBS)-based Simple Sequence Repeats (SSRs) and Their Application for Population Genomics of Capoeta Aculeata (Valenciennes, 1844)

https://doi.org/10.21203/rs.3.rs-514326/v1

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published 22 Aug, 2021

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The species Capoeta aculeata (Valenciennes, 1844) is one of the most important freshwater species endemic to Iran. However, the investigation of a population genetic structure of this species is limited by the low number of molecular markers currently described. In this study, we implemented next generation sequencing technology to identify polymorphic microsatellite markers and investigate the population genetic structure of C. aculeata sampled from three geographical sites in Iran. We sequenced 60 individuals from three populations occurring in the Zagros basin. We characterized and developed 36 novel polymorphic microsatellite markers and these loci were examined in 120 individuals from three populations occurring in the Zagros basin. The average number of alleles per locus varied from 1.7 to 16. (average = 7.89). The results showed that, the polymorphism information content (PCI) of these SSR loci varied from 0.254 to 0.888. The observed heterozygosity (Ho) per locus ranged from 0.170 to 0.881, while the expected heterozygosity (He) per locus was from 0.170 to 0.881. Among these SSR loci, 20 loci deviated significantly from the Hardy–Weinberg equilibrium after Bonferroni correction (p< 0.05). These microsatellite markers could provide a valuable tool for future population and conservation genetics studies of C. aculeate populations and other closely related species.

Molecular Biology

Capoeta aculeata

microsatellite markers

next generation sequencing (NGS)

Genetic structure

The genus Capoeta is a herbivorous cyprinid genus and highly diversified with 14 species and widely distributed in water bodies of Western Iran. Kohgiluyeh and Boyer-Ahmad Province in the southwest part of Iran is a region with high number of endemism in some freshwater fish species including Capoeta aculeata (Valenciennes, 1844) (Zareian et al., 2016). However, populations of this species have experienced significant declines over the last 20 years, due primarily to habitat loss and fragmentation caused by water storage and land clearing. The previous phylogenetic and phylogeographic studies found that populations of C. aculeata are different from the others (Freyhof et al., 2014).

Simple sequence repeat (SSR), also known as microsatellite markers are highly variable DNA sequences, distributed throughout eukaryotic genomes (Sunnucks, 2000; Zane et al., 2002). Given its co-dominant inheritance, bi-parental mode of inheritance, polymerase chain reaction (PCR)-based, high amplification success rate and levels of polymorphism, microsatellite markers have been used in a wide range of applications in population genetics, molecular ecology, conservation genetics and quantitative trait loci (QTL) identification studies (Chang et al., 2009; Xue et al., 2014; Horner et al., 2016; Montanari et al., 2016). Nevertheless, the conventional methods for developing SSR markers are believed to be the key element which limits the application of microsatellite markers due to they are expensive, low efficiency, laborious and time-consuming (Jia et al., 2013; Perina et al., 2016). In fact, SSR markers are tremendously effective tools in population genetic studies because they might reveal the distinct population Segments (DPSs) even in fine-scale genetic structure studies. Until now, microsatellite loci have not been reported in this species (Gandomkar et al., 2020).

The major advantage of Next generation sequencing (NGS) technique is their ability to produce large amounts of sequence data and it can provide wide genetic information of simple sequence repeat (SSR) or microsatellite loci. Restriction-site associated DNA sequencing (RAD-seq) is a powerful tool to develop microsatellite and single nucleotide polymorphism (SNP) markers, which uses Illumina next-generation sequencing (NGS) platforms to discover informative volume of independent markers in a lot of specimens at the same time (Feng et al. 2014; Xiao et al. 2018; Khoshkholgh and Nazari, 2020).

The reads created by RAD-seq can be grouped according to the enzyme recognition sequence, so this procedure could develop the accuracy and precision of contigs assembly, and consistently expand the success rate of polymorphic microsatellite markers development (Wei et al. 2014; Ewers-Saucedo et al. 2016). In comparison with other techniques, restriction site-associated DNA sequencing (RAD-seq) gradually become the most promising method and can give genome-wide genotypic and sequence data adjacent to single restriction enzyme cut sites and generate reduced representation genomic libraries (Davey et al. 2011; Zhou et al. 2017). Recently, the characterization and development of RAD-seq have been used to report microsatellite markers in many cyprinid species, such as Ctenopharyngodon Idella (Yu et al. 2014), Schizothorax prenanti (Luo et al. 2016) and Xenocypris argentea (Peng et al. 2018). However, the genetic background of C. aculeata is limited and no microsatellite locus has been characterized for this species. In this study, RAD-seq was used to isolate and develop the first resource of microsatellite loci for C. aculeata from Iran.

In this study, fin clips of 120 individuals were collected from three wild C. aculeata populations inhabiting the Beshar, Khersan, Maroun rivers in Kohgiluyeh and Boyer-Ahmad Province in Iran (Fig. 1, Table 1). All procedures were approved by the Committee on Animal Care and Use, and Committee on the Ethics of Animal Experiments of Agricultural Research, Education and Extension Organization (AREEO) and Islamic Azad University. The modified method (Nazari et al. 2016) was used to extract genomic DNA using the commercial DN-easy blood and tissue kit (Qiagen™, Germany) following the manufacturer’s instructions. The quality of DNA was assessed using a Nanodrop spectrophotometer (Nanodrop ND1000) and 1% agarose-gel electrophoresis, after which DNA concentration of each sample was diluted to 100 ng in a 100 μL volume and stored at –20 ̊C (Khoshkholgh and Nazari, 2019).

Screening of microsatellite loci by PCR

DNA was isolated and purified from fin clips (about 30–50 mg) or the muscle samples of each fish. DNA was extracted using the commercial DN-easy blood and tissue kit (Qiagen™, Germany) following the manufacturer’s instructions and standardized the final DNA concentration of each sample to 100 ng in a 10 μL volume (Nazari et al. 2016 ). DNA Extraction was examined for concentration using spectrophotometer (Nanodrop ND1000) and standardized to a specific concentration (for example, 100 ng/µl for Polymerase Chain Reaction (PCR)). Quality and concentrations of DNA samples were proved on 1.0% agarose gels and evaluated using a Nanodrop 1000 spectrophotometer.

RAD library construction

RAD library preparation was carried out following the protocol of (Wang et al. 2016). Briefly, genomic DNA from each individual was digested for 2 h at 37 ̊ C in a 40 μL reaction at specific sites with EcoRI-HF restriction enzymes according to the RAD protocol (Bian et al. 2018). Adapter P1 containing individual-specific nucleotide barcodes was ligated to the digested product. Ligation reaction was performed in a 40 μL volume along with 5 μL of ligation buffer, 0.85 μL of P1 adapter, and 300 units of ligase for 2 h at 25 ̊ C. DNA was subsequently ligated to a second adapter (P2), which contains T overhangs. The ligated materials were then pooled, purified, eluted and subjected to PCR enrichment. Total genomic DNA samples were sheared to fragment DNA to an average size of 350 bp and a pool of adapter-ligated molecules with random, variable ends was generated. DNA fragments with lengths of 250–500 bp were isolated using the Qiagen Min Elute Gel Extraction kit (Qiagen™, Germany). The libraries constructed were sequenced on the Illumina HiSeq 4000 platform (BGI, China) using 150 bp paired-end reads.

The quality control of the raw sequences was initially evaluated with the program FastQC (Babraham Bioinformatics) (Andrews 2010). Reads were controlled with Cutadapt to eliminate potential ligated materials of Illumina adapters, permitting a 10% mismatch rate in the adapter sequence (Martin 2011). During this process, the programs process_radtags module and clone_filter from the software Stacks version 2.52 (http://catchenlab.life.illin ois.edu/stacks/) were usedto demultiplex data and trim adapter sequences and remove over-represented sequences, respectively (Catchen et al. 2013; Rochette et al. 2019). To avoid low-quality reads with artificial bias, the following thresholds were set (Li and Godzik 2006): reads with adapter contamination were removed; reads with ≥10% unidentified nucleotides were removed; reads with >50% bases having phred quality <5 were removed; putative duplication reads generated by PCR amplification in library construction were discarded; reads were checked for presence of the partial 5 bp EcoRI motif (AATTC). De novo assembly was performed using software SPAdes (Bankevich et al. 2012). The contigs shorter than 100 bp were removed from the assembly. To evaluate the quality of assembly, the reads involved in alignment were re-mapped onto the assembled genome using BWAprogram (version 0.7.17) (Li and Durbin, 2009).

All clean sequences were aligned to the reference assembly using BWAprogram. Microsatellite motif repeats of mono to hexa-nucleotide microsatellites were identified from the assembled genome using MIcroSAtellite identification tool (MISA) (http://pgrc.ipk-gater slebe n.de/misa/). The following criteria of motifs were required to be met: at least 10 repetitive motifs for mononucleotide, 6 repetitive motifs for di-nucleotide, and 5 repetitive motifs for tri- to hexa-nucleotide. The number of microsatellite loci, repeat motifs, number of repeats, motifs sequence length, repeat type, start and end location of the repeat sequence, and microsatellite sequence, were analyzed using MISA.

A total of 36 polymorphic loci were selected for validation by PCR. Polymerase chain reaction (PCR) reactions were performed in a final volume of 25 μL consisting of 1.2 μL of template DNA (100 ng), 2.5 μL of 10×PCR buffer, 2.5 μL of Mg2+ (20 mM), 0.85 μL of dNTP mixture (2.5 mM each), 0.30 μL of each primer (10 pmol/μl), 17.35 μL of ddH2O, and 0.3 μL of 1 U/μl Taq DNA polymerase (Qiagen™, Germany). Amplified products were checked on 1% agarose gel electrophoresis and sequenced using ABI Prism 3730 automated DNA analyzer (Applied Biosystems). The PCR amplification procedure was performed in a thermal cycler (Bio-Rad, USA) using following program: first denaturation 94 °C, 30 s, one cycle; denaturation 94 °C, 30 s, 12 cycles; a specified annealing temperature for each primer pair for 30 s, 60 s, 12 cycles; then the products were extended at 72 °C for 7 min (for annealing temperatures of each primer pair, see Table 3). The PCR products were electrophoresed on 1.2% agarose gels, stained with ethidium bromide followed by visualization under UV light. SSR loci with single bands were chosen as candidates for additional validation.

Validationof microsatellite polymorphism

For validated SSR loci, each of the selected primer sequences was validated with 120 single individual of C. aculeata from three sampling locations in Iran. From fragment sizing and reporting, GeneMapper (v4.1) was used to analyze genotype data. The negative controls with nuclease-free sterile water were included in each PCR experiment.

For validated loci, statistics including the number of alleles (Na), the effective number of alleles (Ne), the observed heterozygosity (H_O), expected heterozygosity (H_E) indices and inbreeding coefficient (F_IS) were calculated in GenAlex v6.5 (Peakall and Smouse 2012). The Hardy–Weinberg distribution (HWE) with Bonferroni correction was estimated at the population level using Arlequin v3.0 (Excoffier 2005). The inbreeding coefficient index (F_IS) and the polymorphism information content (PIC) were estimated using Genepop V4.7 (Rousset 2008).

In the present study, the total GBS raw reads varied from 11.4 million to 22.38 million, with total raw nucleotides ranging from 0.93 Gb to 2.96 Gb. GBS sequence analysis and microsatellite mining were performed using a modified GBS analysis workflow without using a reference genome (Fig 2). After filtering low-quality reads and reads that lacked enzyme cutting sites by the process_radtags component of Stacks v1.39 software, the total number of clean reads kept in the libraries varied from 10.81 to 21.74 million, with an average of 15.72 million. The summary of sequencing reads generated for 30 samples of C. aculeata were listed in Table 2.

Of the 15,476 sequences, 16,706 microsatellite loci were found by MISA in C. aculeata genome sequences. The number of 926 sequences contains more than one microsatellite. Among the number of microsatellite loci, dinucleotide repeats were the most abundant (6843, 51.91%), followed by trinucleotide repeats (2991, 22.69%), mononucleotide repeats (2756, 20.91%) tetranucleotide repeats (478, 3.62%), pentanucleotide repeats (94, 0.71%), and hexanucleotide repeats (18, 0.13%).

In the present study, the average of the allele numbers inspected at each locus varied between 1.7 for locus Ca04 to 16 for locus Ca25 (Table 2). The results showed that, the polymorphism information content (PCI) of these SSR loci varied from 0.254 to 0.888. The observed heterozygosity (Ho) per locus ranged from 0.170 to 0.881, while the expected heterozygosity (He) per locus was from 0.213 to 0.884. The final set of all microsatellite loci were most informative (PIC > 0.50). Across all samples, 20 SSR loci showed significant deviations from the Hardy–Weinberg equilibrium after Bonferroni correction, (p < 0.05) (Table 2).

For non-model organisms, microsatellite loci were generally identified by 5̕ anchor PCR (Ling et al. 2013), transcriptome sequence analysis (Ariede et al. 2018; Han et al. 2018), and microsatellite library screening (Bazsalovicsová et al. 2018) and development of microsatellite loci through cross-species amplification of closely related species (Gravley et al. 2018). In the present study, RAD-seq method was used for isolating microsatellite loci in C. aculeata. In contrast with conventional approaches, RAD-seq approach is considered to be faster and profitable. Furthermore, this method can produce a large number of microsatellite arkers for one time (Peng et al. 2018; Xiao et al. 2018).

Population structure genetic is very important for the sustainability of many species (Khoshkholgh and Nazari, 2019). Conservation management plans with no prior information of the genetic background could result in disturbance to the genetic structure with adverse effects on the gene pools of wild populations (Khoshkholgh and Nazari, 2020). Until now, the microsatellite loci have not been carefully developed for C. aculeata which has posed a serious obstacle to conservation and management of this species (Gandomkar et al., 2020). The current study detected 16,706 microsatellite markers in C. aculeata genome using MISA, which accounted for 2.12% of the total genome sequence. The relative abundance of microsatellite sequences was calculated at 1.16 loci per kb of C. aculeata genomes. In general, the frequencies of microsatellite loci are expected to decrease with increasing repeat length due to longer repeats have a higher possibility of being mutated. (Pathak et al., 2013), and this tendency has been identified in many organisms (Guichoux et al., 2011; Zalapa et al., 2012; Ma et al., 2013 ) . In summary, this is the first report of SSR loci in C. aculeate developed using RAD-seq and therefore these SSR markers would provide an invaluable resource for population genetics and natural resource conservation in C. aculeata.

Acknowledgements

This work was supported by the Research Fund for the department of fisheries science of the Islamic Azad University of Tehran, Iran.

Author contributions

Habibollah Gandomkar made the literature, sample collection, material preparation. Seyed Pezhman Hosseini Shekarabi has major contribution to the preliminary study design and interpretation of data. The first draft of the manuscript was written by Hossein Ali Abdolhay. Sajad Nazari designed the experiment, institutional support and supervision of the preliminary experiment and made the data analysis. Mehdi Shamsaei Mehrjan has significant contributions to the laboratory work and interpretation of the results. All authors read and approved the final manuscript.

*Consent to Participate (Ethics)

Informed consent was obtained from all individual participants included in the study.

*Consent to Publish (Ethics)

The participant has consented to the submission of the report to the journal.

Availability of data and material (data transparency)

The datasets generated are available from the corresponding author upon request.

Compliance with ethical standards

Conflict of interest: The authors declare that they have no conflict of interest.

Informed consent: This research does not involve humans and therefore informed consents are not applicable.

Ethical approval

The main research project researcher of this work was approved for animal ethics by Iranian Fisheries Sciences Research Institute (IFSRI) for scientific purposes development, Iran. All applicable guidelines for the care and use of animals were followed by the authors. The experiment was approved for Animal Welfare by the Institutional Animal Welfare Committee of Agricultural Research, Education and Extension Organization (AREEO), Iran.

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Table 1: C. aculeata samples collected for population genetic analysis. Sampling localities, numbers (see Fig. 1), and number of individuals sampled (n)

Region	n
Beshar River	40
Khersan River	40
Maroun River	40
Total	120

Table 2: Description of 36 microsatellite markers in Capoeta aculeata (Valenciennes, 1844) (F=forward; R=reverse)

Name	Primer sequence (F and R, 5′-3′)	Allele size (bp)	Repeat motif	N_A	TM ( ̊C)	H_O	H_E	F_IS	PIC	PHWE
Ca01	F: GGCGAACTTGTCTGAGTAAC	202–206	(ATT)8	3.8	54	0.318	0.432	0.275	0.635	0.295
	R: GCATTGCAGATTCCAATA
Ca02	F: CTCATTCCTTGGACTTGA	228–238	(GAT)9	4.3	56	0.854	0.879	-0.028	0.672	0.000*
	R: CGTGCATAGATCCCATGCA
Ca03	F: AGCTGGCTTGGGAAGCTG	142–164	(CTT)4	6.8	56	0.722	0.745	-0.048	0.254	0.926
	R: AGCGGTAGTAGTGAGTACTC
Ca04	F: TCTGCTAAGCACATCTACAGA	98–106	(CGCT)4	1.7	55	0.212	0.268	-0.214	0.701	0.000*
	R: GTCTGTCTCGCTTTCAGTCTC
Ca05	F: TGTACAGTATGTCGTCGTCTCA	274–298	(GAT)7	3.4	56	0.852	0.867	0.086	0.504	0.000*
	R: AGTGTTAGCGTTCGTAAGGG
Ca06	F: GCGTAGTTACGCGTTAGTCTA	94–110	(AT)10	5	58	0.766	0.784	-0.116	0.869	0.122
	R: TGTACGAAGCTAAAGCAGCTG
Ca07	F: TTGCTGAGCTTCGTTACGTGA	100–116	(CA)7	6.6	58	0.484	0.642	-0.127	0.397	0.000*
	R: CGAAATTCACACTATTCTGACT
Ca08	F: ACCGCGCTGATTCTGCTGATCG	192–206	(CT)8	2.4	54	0.214	0.261	0.115	0.588	0.048
	R: GACCGTCCACTATCTCTCGGA
Ca09	F: TAGGAGCCATAGTCTGCTCCTA	242–274	(TG)10	3.8	54	0.224	0.298	0.365	0.766	0.000*
	R: ATCGTTACTCAGAAGTGCTCTG
Ca10	F: TTCGAATAGCTCATCACACCGC	210–242	(AT)12	12	55	0.170	0.213	-0.031	0.656	0.273
	R: TCGTACACACGGAGGACTAGT
Ca11	F: CTTGGTCCTGGCATTGAGTCT	264–286	(CA)8	3.2	58	0.702	0.746	-0.117	0.828	0.000*
	R: ATACTGGGCATGGGGCGTGA
Ca12	F: GTAGCTAGTCGACTCGATTACT	202–236	(TGA)8	2.0	58	0.318	0.389	0.488	0.771	0.000*
	R: ATGTAATCATATGTGACGCGA
Ca13	F: CACTTGCGCTAGGATTATGAT	238–276	(TGA)8	4.1	50	0.278	0.265	0.163	0.758	0.428
	R: GTATCTGAGCTTCTGATCTGTC
Ca14	F: ACTGCGTGGTATGGCTGATCC	210–224	(TC)7	4.2	50	0.881	0.884	0.436	0.857	0.000*
	R: TTCGCGGCGACTATCTAGGGA
Ca15	F: GACTACGTGCCCAGGCCAGTAC	246–282	(AAG)6	6.0	50	0.633	0.679	-0.130	0.835	0.000*
	R: ATCTGTATGATGCCATTTGCG
Ca16	F: TGCTCGTGAGTGGTGTAGTAC	158–184	(ATC)6	8.4	52	0.593	0.489	0.015	0.747	0.178
	R: GTAAGTCTCCATGTGTGCGTAC
Ca17	F: TATCAGTGATAGAGCTGATAG	86–96	(TGA)8	2.6	54	0.571	0.743	0.228	0.825	0.000*
	R: GTCATAGCTATCGAGTAGGTATC
Ca18	F: GGTTGCATCGTACTGTCAACAAT	254–278	(TG)6	3.8	54	0.774	0.627	0.286	0.867	0.387
	R: GGCTCGATAAGTGATACCTCA
Ca19	F: TTCCGCTAGCTATCAGCGGGA	112–128	(TCC)8	10	58	0.633	0.649	0.523	0.341	0.000*
	R: TACACAGCTCATATGGATGTTAG
Ca20	F: GTCTGACATACAGCATCCGGTC	95–106	(AG)9	4.4	60	0.562	0.476	-0.123	0.643	0.188
	R: TCACTCTGACTGCTCTCACTCT
Ca21	F: ACTTGAGCTACTGACATCGGTA	180–204	(TC)8	4.0	58	0.419	0.664	0.606	0.830	0.000*
	R: TCCGATAGCTCTATGCGTGTG
Ca22	F: CGATATGGAACGCTGGCGTTTG	227–263	(ATAC)6	3.1	50	0.318	0.390	-0.044	0.682	0.028
	R: TCGGTTGCTCGGAGGTCCCCTA
Ca23	F: ACTCGCCTAATCCGATCGGATC	158–194	(TC)12	5.4	52	0.579	0.805	-0.171	0.797	0.000*
	R: TTGCTAGTCATTCCAGTAGTA
Ca24	F: GCATGACTATCTCATCGGAGTA	102–136	(TATC)14	4.0	52	0.290	0.478	0.345	0.692	0.000*
	R: GTGTACGATGCGATCTTGGATC
Ca25	F: ACTAGCATACGGATTCAGTGTA	312–374	(TA)5	16	53	0.370	0.584	0.244	0.568	0.000*
	R: TCGGTTATCGGTCCATATATGC
Ca26	F: TTGCCATTAATCGTAGCGACA	224–238	(AT)6	2.6	57	0.675	0.785	0.326	0.731	0.005
	R: GCTACTTAAGCAGCCATCGTG
Ca27	F: CGTCGCCGGCTTTACATCTGGA	124–154	(AT)6	4.1	51	0.325	0.843	0.494	0.745	0.000*
	R: GCTCGCTGCTCGCCATGGTCG
Ca28	F: GATTCTCTAAGTACCTTTGTGT	114–140	(GT)5	14.0	57	0.525	0.713	0.283	0.634	0.000*
	R: TAGACACTTGACATTCTATCG
Ca29	F: GGTGTCATCTCTCATACTAGC	192–210	(AT)5	4.2	58	0.472	0.624	− 0.283	0.888	0.000*
	R: CTGTGTCGACATTGCTAGCCG
Ca30	F: TGGTCGGAGTTAACGCTAGC	134–174	(TA)5	2.0	54	0.551	0.643	− 0.215	0.582	0.094
	R: GAGTACGTCGTGGCTCTAACA
Ca31	F: GGCTAACTACCTGAGGTTATG	142–148	(CT)8	2.2	53	0.188	0.680	− 0.549	0.265	0.343
	R: GTCGGGATATCGCATGTATCA
Ca32	F: AGGTGCATGCACAATCGCGTGC	162–168	(TA)14	4.4	55	0.207	0.642	− 0.074	0.468	0.288
	R: TAGCTCACTCACCGTCATGAG
Ca33	F: TCAGAGATGCTCGGATACTGCA	110–131	(TG)6	5.8	56	0.625	0.685	-0.495	0.726	0.009
	R: ACCTTGGTGTATTGTATGAGCG
Ca34	F: GCATACGCAGACTGTATTCGTG	121–154	(AATC)4	9.2	55	0.567	0.802	0.368	0.387	0.000*
	R: TACAGTCGATGCTAATCATGTC
Ca35	F: GTCTCACATCAATCGATGTGTG	212–224	(AG)9	4.2	56	0.438	0.442	0.166	0.368	0.098
	R: GAACGGATACTCACTTGAGTC
Ca36	F: AGTCCTAGTTCATCATCGCTAG	264–268	(TG)5	4.4	57	0.231	0.587	0.216	0.467	0.000*
	R: CCGAGTTAGAATGAGCAGTAT

Ho: observed heterozygosity, He: expected heterozygosity, N_A: number of allele, F_IS: inbreeding coefficient, PIC: polymorphism information content; PHW: P-values for Hardy–Weinberg equilibrium.

*Indicates significant deviation from Hardy–Weinberg Equilibrium after Bonferroni correction

Table 2 Summary of sequencing reads generated for each samples of Capoeta aculeata

Name	Raw reads (million)	Raw nucleotides (Gb)	Clean reads (million)	Genome Coverage	Unique reads	Reads containing SSRs
Ca1-kh	11.42	1.25	10.81	0.62	641,025	3268
Ca2-kh	14.32	1.58	13.35	0.68	578,246	4598
Ca3-kh	15.65	1.45	14.56	0.64	625,268	5124
Ca4-kh	13.44	1.42	11.30	0.59	396,795	4986
Ca5-kh	14.65	1.74	12.48	0.74	605,436	5468
Ca6-kh	17.21	1.69	16.19	0.69	508,294	5107
Ca7-kh	14.24	1.42	13.28	0.57	512,346	5684
Ca8-kh	11.86	1.24	10.67	0.52	482,247	4936
Ca9-kh	13.12	1.43	12.49	0.54	514,345	5124
Ca10-kh	15.49	1.51	14.44	0.63	758,478	4719
Ca11-Be	11.4	1.28	11.21	0.56	524,635	4281
Ca12-Be	16.52	2.35	16.22	0.85	598,075	5618
Ca13-Be	18.36	2.35	18.12	0.81	605,462	6350
Ca14-Be	16.45	2.96	15.96	0.74	635,153	5637
Ca15-Be	18.24	2.12	17.47	0.69	563,508	4865
Ca16-Be	14.65	2.1	13.35	0.54	532,864	5026
Ca17-Be	20.35	2.3	20.01	0.92	478,652	6258
Ca18-Be	16.25	1.6	15.87	0.68	515,728	6351
Ca19-Be	19.34	2.25	18.65	1.14	496,254	5904
Ca20-Be	21.34	1.35	20.04	0.74	630,542	6743
Ca21-Ma	17.98	1.82	17.13	0.86	563,435	6450
Ca22-Ma	18.27	2.47	17.62	0.54	635,028	6501
Ca23-Ma	19.12	2.35	18.97	0.98	543,759	5642
Ca24-Ma	14.22	1.85	13.35	0.87	431,078	4677
Ca25-Ma	16.35	1.5	15.25	1.02	486,381	3862
Ca26-Ma	19.28	1.25	18.26	0.69	658,582	5562
Ca27-Ma	18.47	0.93	17.98	0.94	546,865	5048
Ca28-Ma	19.25	2.84	19.1	0.75	865,146	6433
Ca29-Ma	16.1	2.37	15.88	0.64	561,353	5031
Ca30-Ma	22.38	1.81	21.74	0.99	765,095	5462
avg	16.52	1.85	15.72	0.73	575,336	5357
Max	22.38	2.96	21.74	1.14	865,146	6501
Min	11.4	0.93	10.81	0.52	431,078	3268
Total	495.72	55.61	471.75	22.17	17,260,075	160,715

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published 22 Aug, 2021

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Editorial decision: Major Revisions Needed
21 Jun, 2021
Reviews received at journal
21 May, 2021
Reviewers invited by journal
21 May, 2021
Editor assigned by journal
11 May, 2021
First submitted to journal
10 May, 2021

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Characterization of Novel Genotyping-by-sequencing (GBS)-based Simple Sequence Repeats (SSRs) and Their Application for Population Genomics of Capoeta Aculeata (Valenciennes, 1844)

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