Abstract
Relying solely on cross-species analysis of single nucleotide polymorphisms (SNPs) through single-species genome mining can introduce biases. To address this challenge, we propose a sequencing-based approach for genome-wide genotyping of simple sequence repeats (SSRs) as an alternative method. Megalobrama, belonging to the family Xenocyprididae of the order Cypriniformes, comprises four primary species: M. amblycephala (Mambl), M. terminalis (Mterm), M. pellegrini (Mpell), and M. hoffmanni (Mhoff). This study employs a sequencing-based genome-wide SSR genotyping approach, analyzing genetic information from nine Megalobrama populations using SSRs extracted from the Mambl genome. Our genotyping efforts successfully covered 916 or 24,180 SSR loci, with less than 10% or 30% of missing data, respectively. The analysis reveals significant gene flow between Mterm, Mpell, and Mambl, validated by the D-statistic test. The F3-statistic values, estimated at -0.00868676 or -0.00831186 based on 916 or 24,180 SSR loci respectively, further support these findings. Additionally, the hypothesis of extensive gene flow among Mterm, Mambl, and Mpell gains robust support from Approximate Bayesian Computation, with a posterior probability of 0.674. Species trees and phylogenetic networks, constructed using 4,116 orthogroups identified across all species, corroborate this hypothesis. Importantly, our study emphasizes the suitability of genome-wide SSRs over SNPs for cross-species genetic diversity studies. In conclusion, our study contributes to the discourse of conservation genetics, advocating for a holistic approach that integrates diverse markers while recognizing their limitations. Our findings not only illuminate the genetic landscape of Megalobrama species but also offer guiding principles for conservation efforts.
Similar content being viewed by others
Data Availability
This study utilized several data sets publicly available in the Sequence Read Archive of NCBI, including PRJNA756243, PRJNA813998, and PRJNA846079.
Code Availability
Not applicable.
References
Abdurakhmonov IY (2016) Introduction to Microsatellites: basics, Trends and highlights. Microsatellite Markers IntechOpen. https://doi.org/10.5772/66446
Alexander DH, Lange K (2011) Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics 12:246. https://doi.org/10.1186/1471-2105-12-246
Ali RH, Bogusz M, Whelan S (2019) Identifying clusters of high confidence homologies in multiple sequence alignments. Mol Biol Evol 36(10):2340–2351. https://doi.org/10.1093/molbev/msz142
Altenhoff AM, Train CM, Gilbert KJ, Mediratta I, Mendes de Farias T, Moi D, Nevers Y, Radoykova HS, Rossier V, Warwick Vesztrocy A, Glover NM, Dessimoz C (2021) OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more. Nucleic Acids Res 49(D1):D373–D379. https://doi.org/10.1093/nar/gkaa1007
Anderson EC, Thompson EA (2002) A model-based method for identifying species hybrids using multilocus genetic data. Genetics 160(3):1217–1229. https://doi.org/10.1093/genetics/160.3.1217
Bai XH, Guo XW, Zhang XJ, Song W, Li YH, Luo W, Cao XJ, Wang WM (2015) Species identification and evolutionary inference of the genera Megalobrama and Parabramis (Cyprinidae: Cultrinae) in China. Mitochondrial DNA 26(3):357–366. https://doi.org/10.3109/19401736.2013.823166
Bickel B, Zakharko T (2016) RSplitsTree: SplitsTree File Generation and Invoking from R. https://github.com/IVS-UZH/RSplitsTree. Accessed November 1st, 2022
Bogutskaya N, Naseka A, Shedko S, Vasil’eva E, Chereshnev I (2008) The fishes of the Amur River: updated check-list and zoogeography. Ichthyol Explor Fres 19(4):301–366
Brandt DY, Aguiar VR, Bitarello BD, Nunes K, Goudet J, Meyer D (2015) Mapping Bias overestimates reference allele frequencies at the HLA genes in the 1000 Genomes Project Phase I Data. G3. 5(Bethesda):931–941. https://doi.org/10.1534/g3.114.015784
Chen J, Wang W (2021) Genetic diversity and genetic differentiation of Megalobrama populations inferred by mitochondrial markers. Genes Genom 43(10):1119–1132. https://doi.org/10.1007/s13258-021-01126-8
Chen J, Liu H, Gooneratne R, Wang Y, Wang W (2022a) Population Genomics of Megalobrama provides insights into Evolutionary History and Dietary Adaptation. Biology (Basel) 11(2):186. https://doi.org/10.3390/biology11020186
Chen X, Wang M, Zhang E (2022b) Updated species checklist of fishes from Lake Dongting in Hunan Province, South China: species diversity and conservation. Zookeys 1108:51–88. https://doi.org/10.3897/zookeys.1108.79960
Collin FD, Durif G, Raynal L, Lombaert E, Gautier M, Vitalis R, Marin JM, Estoup A (2021) Extending approximate bayesian computation with supervised machine learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest. Mol Ecol Resour 21(8):2598–2613. https://doi.org/10.1111/1755-0998.13413
Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, Whitwham A, Keane T, McCarthy SA, Davies RM, Li H (2021) Twelve years of SAMtools and BCFtools. Gigascience 10(2):1–4. https://doi.org/10.1093/gigascience/giab008
Dawson DA, Ball AD, Spurgin LG, Martin-Galvez D, Stewart IR, Horsburgh GJ, Potter J, Molina-Morales M, Bicknell AW, Preston SA, Ekblom R, Slate J, Burke T (2013) High-utility conserved avian microsatellite markers enable parentage and population studies across a wide range of species. BMC Genomics 14:176. https://doi.org/10.1186/1471-2164-14-176
Dyldin YV, Hanel L, Fricke R, Orlov AM, Romanov VI, Plesnik JAN, Interesova EA, Vorobiev DS, Kochetkova MO (2020) Fish diversity in freshwater and brackish water ecosystems of Russia and adjacent waters. Publications of the Seto Marine Biological Laboratory 45:47–116. https://doi.org/10.5134/251251
Earl DA, vonHoldt BM (2011) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4(2):359–361. https://doi.org/10.1007/s12686-011-9548-7
Emms DM, Kelly S (2018) STAG: Species Tree inference from all genes. bioRxiv 267914. https://doi.org/10.1101/267914
Emms DM, Kelly S (2019) OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 20(1):238. https://doi.org/10.1186/s13059-019-1832-y
Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14(8):2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x
Feng S, Bai M, Rivas-Gonzalez I, Li C, Liu S, Tong Y, Yang H, Chen G, Xie D, Sears KE, Franco LM, Gaitan-Espitia JD, Nespolo RF, Johnson WE, Yang H, Brandies PA, Hogg CJ, Belov K, Renfree MB, Helgen KM, Boomsma JJ, Schierup MH, Zhang G (2022) Incomplete lineage sorting and phenotypic evolution in marsupials. Cell. https://doi.org/10.1016/j.cell.2022.03.034
Froese R, Pauly D (2023) FishBase. https://www.fishbase.org/. Accessed 04/2023
Galla SJ, Forsdick NJ, Brown L, Hoeppner MP, Knapp M, Maloney RF, Moraga R, Santure AW, Steeves TE (2018) Reference genomes from distantly related species can be used for Discovery of single nucleotide polymorphisms to inform Conservation Management. Genes (Basel) 10(1):9. https://doi.org/10.3390/genes10010009
Goldstein DB, Ruiz Linares A, Cavalli-Sforza LL, Feldman MW (1995) Genetic absolute dating based on microsatellites and the origin of modern humans. Proc Natl Acad Sci U S A 92(15):6723–6727. https://doi.org/10.1073/pnas.92.15.6723
Gong D, Wang X, Yang J, Liang J, Tao M, Hu F, Wang S, Liu Z, Tang C, Luo K, Zhang C, Ma M, Wang Y, Liu S (2023) Protection and utilization status of Parabramis and Megalobrama germplasm resources. Reprod Breed 3(1):26–34. https://doi.org/10.1016/j.repbre.2023.01.003
Green MR, Sambrook J (2018) Isolation of high-molecular-weight DNA from suspension cultures of mammalian cells using proteinase K and phenol. Cold Spring Harb Protoc 2018(4):317–321. https://doi.org/10.1101/pdb.prot093476
Gunther T, Nettelblad C (2019) The presence and impact of reference bias on population genomic studies of prehistoric human populations. PLoS Genet 15(7):e1008302. https://doi.org/10.1371/journal.pgen.1008302
Hagberg L, Celemin E, Irisarri I, Hawlitschek O, Bella JL, Mott T, Pereira RJ (2022) Extensive introgression at late stages of species formation: insights from grasshopper hybrid zones. Mol Ecol 31(8):2384–2399. https://doi.org/10.1111/mec.16406
Han J, Munro JE, Kocoski A, Barry AE, Bahlo M (2022) Population-level genome-wide STR discovery and validation for population structure and genetic diversity assessment of Plasmodium species. PLoS Genet 18(1):e1009604. https://doi.org/10.1371/journal.pgen.1009604
Hauser SS, Athrey G, Leberg PL (2021) Waste not, want not: microsatellites remain an economical and informative technology for conservation genetics. Ecol Evol 11(22):15800–15814. https://doi.org/10.1002/ece3.8250
He Y, Wang J, Lek S, Cao W, Lek-Ang S (2011) Structure of endemic fish assemblages in the upper Yangtze River Basin. River Res Appl 27(1):59–75. https://doi.org/10.1002/rra.1339
Hu X, Shi L (2020) A review: Research Progress on Germplasm Resource of Black Bream (Megalobrama terminalis) in China. Chin J Fisheries 33(3):84–89
Hu X, Luan P, Cao C, Li C, Jia Z, Ge Y, Shang M, Wang S, Meng Z, Tong J, Shi L (2019) Characterization of the mitochondrial genome of Megalobrama terminalis in the Heilong River and a clearer phylogeny of the genus Megalobrama. Sci Rep 9(1):8509. https://doi.org/10.1038/s41598-019-44721-2
Hu X, Ma B, Li C, Jia Z, Jiang X, Ge Y, Tong J, Shi L (2020) Genetic differentiation of an endangered Megalobrama terminalis Population in the Heilong River within the Genus Megalobrama. Diversity 12(10). https://doi.org/10.3390/d12100404
Huang H, Zhang W (1986) Description on three new species of fishes from the changjiang river, China. Acta Hydrobiol Sin 10(1):99–100
Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Inferring weak population structure with the assistance of sample group information. Mol Ecol Resour 9(5):1322–1332. https://doi.org/10.1111/j.1755-0998.2009.02591.x
Huson DH, Bryant D (2006) Application of phylogenetic networks in Evolutionary Studies. Mol Biol Evol 23(2):254–267. https://doi.org/10.1093/molbev/msj030
Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23(14):1801–1806. https://doi.org/10.1093/bioinformatics/btm233
Jung Y, Han D (2022) BWA-MEME: BWA-MEM emulated with a machine learning approach. Bioinformatics 38(9):2404–2413. https://doi.org/10.1093/bioinformatics/btac137
Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16(5):1099–1106. https://doi.org/10.1111/j.1365-294X.2007.03089.x
Kamvar ZN, Tabima JF, Grunwald NJ (2014) Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2:e281. https://doi.org/10.7717/peerj.281
Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30(4):772–780. https://doi.org/10.1093/molbev/mst010
Kumar S, Stecher G, Suleski M, Hedges SB (2017) TimeTree: A Resource for Timelines, Timetrees, and divergence Times. Mol Biol Evol 34(7):1812–1819. https://doi.org/10.1093/molbev/msx116
Langella O (1999) Populations v1.2.32: a population genetic software. http://bioinformatics.org/~tryphon/populations/. Accessed November 10th, 2022
Lewis DH, Jarvis DE, Maughan PJ (2020) SSRgenotyper: a simple sequence repeat genotyping application for whole-genome resequencing and reduced representational sequencing projects. Appl Plant Sci 8(12):e11402. https://doi.org/10.1002/aps3.11402
Li H (2023) Protein-to-genome alignment with miniprot. Bioinformatics 39(1). https://doi.org/10.1093/bioinformatics/btad014
Liu K, Xie N (2022) Pipeline for developing polymorphic microsatellites in species without reference genomes. 3 Biotech 12(10):248. https://doi.org/10.1007/s13205-022-03313-0
Liu K, Feng X, Ma H, Xie N (2020) Complete sequence and gene organization of mitochondrial genome of Megalobrama terminalis from Qiantang River. Acta Agriculturae Zhejiangensis 32(9):1591–1608. https://doi.org/10.3969/j.issn.1004-1524.2020.09.08
Liu H, Chen C, Lv M, Liu N, Hu Y, Zhang H, Enbody ED, Gao Z, Andersson L, Wang W (2021a) A chromosome-level assembly of Blunt Snout Bream (Megalobrama amblycephala) Genome reveals an expansion of olfactory receptor genes in Freshwater Fish. Mol Biol Evol 38(10):4238–4251. https://doi.org/10.1093/molbev/msab152
Liu K, Feng X-y, Ma H-j, Xie N (2021b) Development and characterization of 68 microsatellite markers of Black Amur Bream Megalobrama terminalis by Next-Generation sequencing. Turkish J Fisheries Aquat Sci 21(6):299–308. https://doi.org/10.4194/1303-2712-v21_6_05
Liu K, Xie N, Wang Y, Liu X (2023a) Contribution bias of parental genomes to the hybrid lineages of black Amur bream and topmouth culter revealed by low-coverage whole-genome sequencing. Gene 852:147058. https://doi.org/10.1016/j.gene.2022.147058
Liu K, Xie N, Wang Y, Liu X (2023b) Extensive mitogenomic heteroplasmy and its implications in the phylogeny of the fish genus Megalobrama. 3 Biotech 13(4):115. https://doi.org/10.1007/s13205-023-03523-0
Luo YL (1990) A revision of fishes of the cyprinid genus Megalobrama. Acta Hydrobiol Sin 14(2):160–165
Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y, Pan Q, Liu Y, Tang J, Wu G, Zhang H, Shi Y, Liu Y, Yu C, Wang B, Lu Y, Han C, Cheung DW, Yiu SM, Peng S, Xiaoqian Z, Liu G, Liao X, Li Y, Yang H, Wang J, Lam TW, Wang J (2012) SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1(1):18. https://doi.org/10.1186/2047-217X-1-18
Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD, von Haeseler A, Lanfear R (2020) IQ-TREE 2: New Models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol 37(5):1530–1534. https://doi.org/10.1093/molbev/msaa015
Mukherjee S, Mukherjee A, Kumar S, Verma H, Bhardwaj S, Togla O, Joardar SN, Longkumer I, Mech M, Khate K, Vupru K, Khan MH, Kumar S, Rajkhowa C (2022) Genetic characterization of endangered indian Mithun (Bos frontalis), indian Bison/Wild Gaur (Bos gaurus) and Tho-tho cattle (Bos indicus) populations using SSR markers reveals their diversity and unique phylogenetic status. Diversity 14(7). https://doi.org/10.3390/d14070548
Mussmann SM, Douglas MR, Bangs MR, Douglas ME (2019) Comp-D: a program for comprehensive computation of D-statistics and population summaries of reticulated evolution. Conserv Genet Resour 12(2):263–267. https://doi.org/10.1007/s12686-019-01087-x
Ngangkham U, Dash S, Parida M, Samantaray S, Nongthombam D, Yadav MK, Kumar A, Chidambaranathan P, Katara JL, Patra BC, Bose LK (2019) The potentiality of rice microsatellite markers in assessment of cross-species transferability and genetic diversity of rice and its wild relatives. 3 Biotech 9(6):217. https://doi.org/10.1007/s13205-019-1757-x
Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research–an update. Bioinformatics 28(19):2537–2539. https://doi.org/10.1093/bioinformatics/bts460
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2):945–959. https://doi.org/10.1093/genetics/155.2.945
Quail MA, Kozarewa I, Smith F, Scally A, Stephens PJ, Durbin R, Swerdlow H, Turner DJ (2008) A large genome center’s improvements to the Illumina sequencing system. Nat Methods 5(12):1005–1010. https://doi.org/10.1038/nmeth.1270
Rabiee M, Sayyari E, Mirarab S (2019) Multi-allele species reconstruction using ASTRAL. Mol Phylogenet Evol 130:286–296. https://doi.org/10.1016/j.ympev.2018.10.033
Rice WR (1989) Analyzing tables of statistical tests. Evolution 43(1):223–225. https://doi.org/10.1111/j.1558-5646.1989.tb04220.x
Rosenberg NA (2003) Distruct: a program for the graphical display of population structure. Mol Ecol Notes 4(1):137–138. https://doi.org/10.1046/j.1471-8286.2003.00566.x
Sarver BA, Keeble S, Cosart T, Tucker PK, Dean MD, Good JM (2017) Phylogenomic insights into mouse evolution using a Pseudoreference Approach. Genome Biol Evol 9(3):726–739. https://doi.org/10.1093/gbe/evx034
Schiavinato M, Bodrug-Schepers A, Dohm JC, Himmelbauer H (2021) Subgenome evolution in allotetraploid plants. Plant J 106(3):672–688. https://doi.org/10.1111/tpj.15190
Shen W, Le S, Li Y, Hu F (2016) SeqKit: a cross-platform and Ultrafast Toolkit for FASTA/Q file manipulation. PLoS ONE 11(10):e0163962. https://doi.org/10.1371/journal.pone.0163962
Shimoda N, Knapik EW, Ziniti J, Sim C, Yamada E, Kaplan S, Jackson D, de Sauvage F, Jacob H, Fishman MC (1999) Zebrafish genetic map with 2000 microsatellite markers. Genomics 58(3):219–232. https://doi.org/10.1006/geno.1999.5824
Singh RB, Mahenderakar MD, Jugran AK, Singh RK, Srivastava RK (2020) Assessing genetic diversity and population structure of sugarcane cultivars, progenitor species and genera using microsatellite (SSR) markers. Gene 753:144800. https://doi.org/10.1016/j.gene.2020.144800
Stevenson KR, Coolon JD, Wittkopp PJ (2013) Sources of bias in measures of allele-specific expression derived from RNA-sequence data aligned to a single reference genome. BMC Genomics 14:536. https://doi.org/10.1186/1471-2164-14-536
Suzuki R, Shimodaira H (2006) Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 22(12):1540–1542. https://doi.org/10.1093/bioinformatics/btl117
Szatmari L, Cserkesz T, Laczko L, Lanszki J, Pertoldi C, Abramov AV, Elmeros M, Ottlecz B, Hegyeli Z, Sramko G (2021) A comparison of microsatellites and genome-wide SNPs for the detection of admixture brings the first molecular evidence for hybridization between Mustela eversmanii and M. putorius (Mustelidae, Carnivora). Evol Appl 14(9):2286–2304. https://doi.org/10.1111/eva.13291
Takahata N, Slatkin M (1984) Mitochondrial gene flow. Proc Natl Acad Sci U S A 81(6):1764–1767. https://doi.org/10.1073/pnas.81.6.1764
Tamura K, Battistuzzi FU, Billing-Ross P, Murillo O, Filipski A, Kumar S (2012) Estimating divergence times in large molecular phylogenies. Proc Natl Acad Sci U S A 109(47):19333–19338. https://doi.org/10.1073/pnas.1213199109
Tamura K, Tao Q, Kumar S (2018) Theoretical Foundation of the RelTime Method for estimating divergence Times from Variable Evolutionary Rates. Mol Biol Evol 35(7):1770–1782. https://doi.org/10.1093/molbev/msy044
Tamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol Biol Evol 38(7):3022–3027. https://doi.org/10.1093/molbev/msab120
Than C, Ruths D, Nakhleh L (2008) PhyloNet: a software package for analyzing and reconstructing reticulate evolutionary relationships. BMC Bioinformatics 9:322. https://doi.org/10.1186/1471-2105-9-322
Thiel T, Michalek W, Varshney RK, Graner A (2003) Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L). Theor Appl Genet 106(3):411–422. https://doi.org/10.1007/s00122-002-1031-0
Wang J (2019) A parsimony estimator of the number of populations from a STRUCTURE-like analysis. Mol Ecol Resour 19(4):970–981. https://doi.org/10.1111/1755-0998.13000
Wang W, Gao Z (2018) Recent Developments in Bream Culture: Culture Systems and Genetic Improvement. In: Aquaculture in China. pp 158–173. https://doi.org/10.1002/9781119120759.ch2_5
Wang X, Chatwin W, Hilton A, Kubenka K (2022) Genetic diversity revealed by Microsatellites in Genus Carya. Forests 13(2). https://doi.org/10.3390/f13020188
Xie N, Liu X, Feng X, Guo S (2012) Sequences analysis on mitochondrial cytochrome b gene fragment of Megalobrama spp. Mod Agricultural Sci Technol (1):290–292
Xu W, Xiong B-x (2008) Advances in the Research on Genus Megalobrama in China. J Hydroecology 1(2):7–11. https://doi.org/10.15928/j.1674
Ye S, Li Z, Zhang T, Liu J, Xie S (2013) Assessing fish distribution and threats to fish biodiversity in the Yangtze River Basin, China. Ichthyol Res 61(2):183–188. https://doi.org/10.1007/s10228-013-0376-5
Yih PL (1955) Notes on Megalobrama Amblycephala, sp. nov., a distinct species from M. Terminalis (Richardson). Acta Hydrobiol Sin (2):115–122
Yu Y, Nakhleh L (2015) A maximum pseudo-likelihood approach for phylogenetic networks. BMC Genomics 16(Suppl 10):S10. https://doi.org/10.1186/1471-2164-16-S10-S10
Zhang Q, Chen J, Jiang X, Zou S (2014) Establishment of DNA fingerprinting and analysis on genetic structure of different Parabramis and Megalobrama populations with microsatellite. J Fisheries China 38(1):15–22
Zhivotovsky LA (2001) Estimating divergence time with the use of microsatellite genetic distances: impacts of population growth and gene flow. Mol Biol Evol 18(5):700–709. https://doi.org/10.1093/oxfordjournals.molbev.a003852
Zimmerman SJ, Aldridge CL, Oyler-McCance SJ (2020) An empirical comparison of population genetic analyses using microsatellite and SNP data for a species of conservation concern. BMC Genomics 21(1):382. https://doi.org/10.1186/s12864-020-06783-9
Funding
This work was supported by China Agriculture Research System [Grant numbers CARS-45-38]; Science & Technology Innovation Program of Hangzhou Academy of Agricultural Sciences [Grant numbers 2022HNCT-01].
Author information
Authors and Affiliations
Contributions
Kai Liu conducted the experiments; Kai Liu analyzed the data and wrote the manuscript; Yuxi Wang and Nan Xie participated in preparing the samples and data collection; All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflicts of interest/Competing interests
The authors declare that they have no conflict of interest in the publication.
Ethics approval
Approval from the Science and Technology Bureau of China and the Department of Wildlife Administration is not required for the experiments conducted in this paper when the fish in question are neither rare nor near extinction (first- or second-class state protection level). ALL activities comply with China’s Wildlife Protection and Fishery Law.
Consent to participate
The participant has consented to the participants of the manuscript.
Consent for publication
The participant has consented to the submission of the manuscript to the journal.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Liu, K., Xie, N. & Wang, Y. Exploring cross-species genetic diversity: unveiling new insights in Megalobrama through whole genome-wide simple sequence repeats. Conserv Genet 25, 393–407 (2024). https://doi.org/10.1007/s10592-023-01575-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10592-023-01575-6