Presence of novel mitochondrial haplotypes in Indian Cuvier’s beaked whale, Ziphius cavirostris (Cuvier, 1823)

Presence of novel mitochondrial haplotypes in Indian Cuvier’s beaked whale, Ziphius cavirostris (Cuvier, 1823) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Presence of novel mitochondrial haplotypes in Indian Cuvier’s beaked whale, Ziphius cavirostris (Cuvier, 1823) Madhumita Rajkumar, Yuvasri Kasinathan, K Venkatesan Meganath, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9226304/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract The Cuvier’s beaked whale ( Ziphius cavirostris ) is a pelagic marine mammal known for its elusive behavior and ecological importance as a predator in ocean ecosystems. Despite its wide distribution, records from Indian waters remain scarce. Here, we report two strandings of this species along the Tamil Nadu coast in 2024. Mitochondrial DNA (mtDNA) regions, including the COX region (630 bps) and cytochrome b (CYTB) (464 bps), 16S rRNA (520 bps) and 12S rRNA (420 bps), were sequenced and were found to be of two different haplotypes. Comparison with haplotypes previously reported outside India indicates genetic differentiation of the Indian subpopulation, based on the presence of two unique haplotypes. This study provides the first molecular evidence of Ziphius cavirostris from Indian waters and contributes to global phylogeographic datasets. Identification of region-specific haplotypes highlights the potential existence of Indian Ocean management units and emphasizes the need for regional conservation strategies.Additional mtDNA sequences from the India are needed for a better understanding of the genetic population structure of this species and to elaborate on more concrete conservation measures. Cuvier’s beaked whale Phylogeography Population structure Indian Ocean Figures Figure 1 Figure 2 Figure 3 Introduction Marine mammals are indicator species of a healthy marine ecosystem, as they play an ecologically significant role in nutrient recycling, facilitate bioturbation and maintain functional biodiversity and their decline affects prey population size (Katona and Whitehead 1988 ; Bowen 1997 ; Bossart 2011 ; Watson and Estes 2011 ; Roman et al. 2014 ; Kiszka et al. 2015 ; Albouy et al. 2017 ). Being globally distributed, they inhabit a wide range of environments from estuarine and coastal waters to the open oceans (Venu & Malakar, 2015 ). Among marine mammals, cetaceans functionally play a major role as both top predators and nutrient vector due to its large body size which in turn reflects ecosystem productivity (Gilbert et al., 2023 ). Around 90 cetacean species are known globally, comprising whales, dolphins, and porpoises, of which approximately 26 species have been reported from Indian waters, mainly through accidental catches and stranding records along the east and west coasts. (Venu & Malakar, 2015 ; Montgelard et al. , 2007) Among the whales, beaked whales (Ziphiidae) are the most specialized group of deep-sea marine mammals with only one pair of teeth. Among them, Cuvier's beaked whale (CBW; Ziphius cavirostris ) is the only extant member of the genus Ziphius . Being elusive, their occurrences are known mostly when stranded (Bernaldo de Quirós et al., 2019 ; Cox et al., 2006 ; Simonis et al., 2020 ) and are recorded throughout the world including temperate, subtropical, and tropical oceans in deep ocean near the continental slope particularly (Falcone et al., 2009 ; Johnson et al., 2004 ; McSweeney et al., 2007 ; Piboon et al., 2022 ). The highest population were recorded in Pacific Ocean then North Atlantic Ocean especially Hawaii (Barlow et al., 2005 ). CBW from Mediterranean Sea and Alborán sea is known to be connected to Atlantic Ocean (Podestà et al., 2016 ). Apart from the major population, their presence has been recorded through dead stranding in the Malay Peninsula, East Indian Ocean and northern Java Malaysia, Andaman Sea, Satun Province and Thailand (De Boer, 2000 ; Dammerman, 1926 ; Rudolph et al., 1997 ; Jaaman et al., 2002 ; Ponnampalam, 2012 ) In India, occasional strandings have been recorded along the Indian coasts, namely in Gujarat (MMRCNI), Maharashtra (Chatterjee, 2019 ), Karnataka (Naik et al., 2015 ), Tamil Nadu (Oppili, 2016 ), West Bengal (Chakraborty & Mukherjee, 2021 ), and Lakshadweep (Pillai et al ., 1981). In India, it is protected under Schedule I of Wildlife (Protection) Act, 1972 and is also listed under Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Marine mammals are known to be threatened by various anthropogenic activities such as incidental bycatch in fishing, hunting, poaching, collision with aquatic transport, oil and mineral extraction, exposure to pollutants and pathogens, and underwater noise (Avila et al., 2018 ; Gales et al., 2003 ; Helm et al., 2014 ; Parsons et al., 2018 ) which directly impacts at both the population level and the individual level. CBW being cosmopolitan range, its population undergoes both macro- and microevolution to form evolutionarily significant units (ESUs) as well as demographically independent populations (DIPs) (Waples 1995 ; Palsbøll et al. 2007 ; Karen et al. 2019 ). Many studies have used mtDNA genes, because of their high rate of mutation and resistance to selection pressures, to estimate genetic variation, phylogeography and population structure within wild populations of CBW (Dalebout et al. 2008 ; Foote et al. 2012 ; Onoufriou et al. 2022 ; Tonay et al. 2024 ). Such studies will help in developing population-specific management plans and thus help in long-term conservation of this globally threatened marine mammal (Srinivas et al. 2020 ) In India, this species is poorly studied except the records based on the stranding. Furthermore, there are no studies in the genetic field from India on CBW so far. Therefore, this paper presents the first genetic evidence of CBW along the Indian Ocean and also compares its population genetic structure and diversity across its cosmopolitan ranges. Materials and methods Sample collection Given the rare stranding of CBW in the Indian subcontinent, it was logistically difficult to conduct systematic sampling of biological material. Hence, Tissue samples from two individuals were opportunistically collected after necropsy of stranding from the coastal areas of Tamil Nadu. The details of the samples and their geographical sampling locations are provided in Fig. 1 and supplementary table S1 . The samples were stored in ethanol at the field and later sent to the Advanced Institute for Wildlife Conservation (AIWC) for storage at − 20°C until further analysis. DNA isolation, amplification and sequencing Genomic DNA was extracted using a DNeasy Blood & Tissue Kit (QIAGEN, Germany) according to the manufacturer’s protocol. DNA was eluted from 30 µL of elution buffer provided in kit. Extracted DNA samples were prepared for purity evaluation using 2% agarose gel electrophoresis. DNA quantity was determined using a nanodrop spectrophotometer. Diluted samples (10 ng/µL) were stored at − 20°C for subsequent analyzes. PCR amplifications were conducted for four target genes − 12S rRNA, 16S rRNA, CYTB , and COX I - using universal primer sets. Detailed annealing temperature and primer sequences are provided in supplementary table S2. Each reaction (30 µL total volume) contained 1× Ampliqon Taq DNA Polymerase Master Mix RED, 0.10 µM of each primer, and 30 ng of template DNA, alongside a negative control. For amplified mitochondrial gene amplification, conditions were an initial denaturation for 5 min at 95°C, followed by 35 cycles of 30 s at 95°C (denaturation), 35 s at various annealing temperature between 50°C and 61°C (annealing), and 45 s at 72°C (extension) with a final elongation of 5 min at 72°C. Amplified products were resolved on a 2% agarose gel, and corresponding DNA bands were purified using the Qiagen MinElute PCR Product Purification Kit. Purified products were bidirectionally sequenced using the BigDye Terminator Cycle Sequencing Kit (v.3.1 Applied Biosystems) and an AB PRISM 3500 (Applied Biosystems) automatic sequencer at AIWC. Phylogeography Phylogenetic trees of the mitochondrial sequences were constructed using MrBayes program v.3.2.7(Ronquist et al. 2012 ). The obtained sequences were aligned using MAFFT (Katoh et al. 2019 ). Sequences were concatenated in the order 12S RNA, 16S RNA, COX and CYTB using Mesquite 4.02 (Maddison and Maddison 2025 ). jModelTest 2.1.10 was used to select the best tree evolutionary models for individual genes (Posada 2008 ). The run length of Markov Chain Monte Carlo (MCMC) sampling at 10,000,000 iterations for each tree was performed using the convergence diagnostics with an average standard deviation of split frequencies below 0.01. The first 1,000,000 iterations were discarded in the burn-in step. The phylogenetic trees were visualized and annotated using FigTree v.1.4 (Rambaut 2009 ). A posterior probability value ≥ 0.95 was considered for indicating strong relationships (Dalebout et al. 2008 ). Haplotypes and genetic diversity The haplotypes diversity for samples was compared to the worldwide haplotypes using the alignment of the dataset mentioned above via DnaSP program v6.12.3 (Rozas et al. 2017 ). Furthermore, the number of haplotypes ( H ), the number of variable sites ( S ), haplotype diversity ( H d ), and nucleotide diversity ( π ) were calculated using the same program. To examine the regional genetic structure, the Median-Joining Networks (MJNs) of each haplotype (Bandelt et al. 1999 ) were constructed using the PopART program v1.7 (Leigh and Bryant 2015 ). Results Dataset All four genes were sequenced and uploaded to NCBI, with their Accession IDs provided in supplementary table S1 . Previously recorded 35 whole mitogenomes from Onoufriou et al. ( 2022 ) were used. A total of 37 concatenated mitochondrial DNA sequences from four oceanic regions: Atlantic ( n = 18), Pacific ( n = 14), Mediterranean ( n = 3) and Indian Ocean ( n = 2), with all gap-containing sites were analyzed. Phylogeography The best-fit nucleotide substitution models for 12S rRNA, 16S rRNA, COX, and CYTB were TrN + I, HKY + G, K80 and HKY + I, respectively, and were selected based on the Bayesian Information Criterion (BIC) scores in jModelTest.The mtDNA phylogeny of 37 CBW was clearly separated into four distinct clades (Fig. 2 ). Clade 1 represents the Atlantic lineage, including samples from the Mediterranean Sea, whereas Clades 2 and 3 contained individuals from both Atlantic and Pacific lineages. The Indian Ocean lineage formed a separate monophyletic Clade 4 as a separate clade from other clades. Mitochondrial genetic diversity The final alignment of concatenated sequences comprising 2034 bp, with no gaps or missing data after quality filtering. Across the concatenated mitochondrial dataset, 104 polymorphic (segregating) sites were identified, resulting in a total of 107 mutational events (Eta). The analysis revealed a high number of unique haplotypes ( h = 28) among the sampled individuals. Haplotype diversity was very high ( H d = 0.983 ± 0.010), indicating an extensive mitochondrial haplotype variation within the sampled population. The variance of haplotype diversity was low (0.00011), reflecting the robustness of the estimate despite the moderate sample size. Nucleotide diversity ( π ) was estimated at 0.01023 ± 0.00034, suggesting moderate levels of sequence divergence across the concatenated mitochondrial regions. The corresponding average number of nucleotide differences between sequences was k = 25.335, consistent with substantial mitochondrial variation at the population level. The dataset comprised 104 polymorphic sites and 107 mutational events, defining 28 distinct haplotypes. Overall haplotype diversity was very high ( H d = 0.9835), indicating substantial mitochondrial variation. Notably, 22 haplotypes (78.6%) were singletons, whereas only 6 were shared among two or three individuals. The most frequent haplotypes (Hap_3 and Hap_5) were each detected in three individuals, while four additional haplotypes occurred in two individuals each. This pattern reflects high haplotype richness with limited dominance of any single mitochondrial lineage. Mitochondrial genetic and haplotype diversity across oceanic regions A total of 37 sequences give rise to 104 polymorphic sites, defining 28 haplotypes, yielding high overall haplotype diversity ( H d = 0.983) and moderate nucleotide diversity ( π = 0.01023; k = 25.33). Regionally, haplotype diversity remained consistently high. The Atlantic population harboured 14 haplotypes ( H d = 0.967; π = 0.01033), while the Pacific exhibited 10 haplotypes ( H d = 0.956; π = 0.00724). Despite small sample sizes, the Mediterranean and Indian Ocean populations each showed maximal haplotype diversity ( H d = 1.000), with lower nucleotide diversity ( π = 0.00135 and 0.00525, respectively). Genetic differentiation among oceanic regions was significant ( χ ² = 107.87, df = 81, P = 0.0247), indicating population structure. Haplotype distributions revealed predominantly region-specific lineages with limited inter-basin sharing. The Atlantic and Pacific populations contained several unique haplotypes, with only a single haplotype (Hap_3) shared between these basins. The Mediterranean and Indian Ocean samples were composed entirely of unique, region-restricted haplotypes, underscoring restricted mitochondrial connectivity across oceanic regions. Population-level genetic diversity Population-wise estimates of genetic diversity revealed consistently high haplotype diversity across all regions (Table 1 ). The Atlantic population ( n = 18) contained 14 haplotypes with H d = 0.967, while the Pacific population ( n = 14) showed 10 haplotypes with H d = 0.956. Despite smaller sample sizes, the Mediterranean ( n = 3) and Indian Ocean ( n = 2) populations both exhibited maximum haplotype diversity ( H d = 1.000). Nucleotide diversity varied among regions, ranging from π = 0.00135 in the Mediterranean to π = 0.01033 in the Atlantic population. The overall nucleotide diversity across all samples was π = 0.01023, with an average of 25.33 nucleotide differences between sequences. Table 1 Mitogenomic haplotype diversity statistics are provided for each ocean basin: number of sequences ( n ), number of segregating sites ( S ), number of haplotypes ( h ), haplotype diversity ( H d ) and nucleotide diversity ( π ). Population n S h H d π Atlantic 18 78 14 0.96732 0.01033 Pacific 14 43 10 0.95604 0.00724 Mediterranean 3 5 3 1.00000 0.00135 Indian Ocean 2 13 2 1.00000 0.00525 Genetic differentiation among populations Significant genetic differentiation was detected among the four oceanic populations. The chi-square test based on haplotype frequencies revealed significant population structure ( χ ² = 107.87, df = 81, P = 0.0247). Estimates of population subdivision based on haplotype frequencies were relatively low ( H ST = 0.020), whereas sequence-based differentiation measures were higher ( K ST = 0.203; K ST = 0.105*). The nearest-neighbour statistic ( S nn = 0.863) further supported significant phylogeographic structure across oceanic regions. Pairwise comparisons revealed variable levels of differentiation. Lower differentiation was observed between the Atlantic and Pacific populations ( F ST = 0.183), while markedly higher differentiation was detected between geographically distant populations, including Pacific–Mediterranean ( F ST = 0.648) and Mediterranean–Indian Ocean ( F ST = 0.780). Median-joining haplotype network analysis Estimates of gene flow differed substantially between haplotype-based and sequence-based approaches. Haplotype frequency-based estimates (Nei 1973 ) suggested low overall differentiation ( G ST = 0.0468) and relatively high gene flow ( N m ≈ 5.09). In contrast, sequence-based estimators indicated substantially higher differentiation ( N ST = 0.490; F ST = 0.489) and low effective maternal gene flow ( N m ≈ 0.26–0.77), suggesting restricted mitochondrial exchange among oceanic basins. The median-joining haplotype network based on 28 haplotypes (Hap_1–Hap_28) among 37 beaked whale sequences, with high haplotype diversity ( H d = 0.9835) is given in Fig. 3 . Most haplotypes were represented by single sequences, while a limited number were shared by two or three individuals. Hap_3 and Hap_5 each comprised three sequences, whereas Hap_8, Hap_9, Hap_12, Hap_14 and Hap_17 were shared by two sequences each. All remaining haplotypes (Hap_1, Hap_2, Hap_4, Hap_6, Hap_7, Hap_10, Hap_11, Hap_13, Hap_15, Hap_16, Hap_18–Hap_28) were singletons. Hap_3 included sequences from both Pacific and Atlantic regions, while Hap_5, Hap_8, Hap_9 and Hap_10 were composed exclusively of Atlantic sequences. Pacific haplotypes were primarily represented by Hap_11–Hap_19, with limited sharing among regions. The network showed multiple median vectors and several long mutational connections among haplotypes, indicating the presence of unsampled or extinct ancestral lineages. Overall, the predominance of low-frequency and region-specific haplotypes, combined with limited haplotype sharing across ocean basins, suggests strong phylogeographic structuring of maternal lineages in beaked whales. Discussion Presence of unique population was evident based on mitochondrial markers. The current study also follows the global pattern of genetic structure obtained from previous studies (Dalebout et al. 2005 , 2008 ; Onoufriou et al. 2022 ; Tonay et al. 2024 ). The previous studies have confirmed the presence of a heterogeneous genetic population between the Atlantic Ocean and Pacific Ocean, which is also reconfirmed in this study (Onoufriou et al. 2022 ). Earlier studies showed that the Mediterranean Sea lineage clustered within the Atlantic Ocean basin (Tonay et al. 2024 ), whereas in the current study, the Indian Ocean lineage forms clusters with both Pacific and Atlantic Ocean lineage clusters. This pattern may be explained by the strong connectivity among ocean basins, which can facilitate substantial gene flow between populations. Across oceanic regions, haplotype diversity remained consistently high; however, haplotypes were largely restricted to specific basins, with minimal inter-oceanic sharing. The significant chi-square statistic ( χ ² = 107.87, P = 0.0247), elevated sequence-based differentiation ( K ST = 0.203), high nearest-neighbour statistic ( S nn = 0.863) and pairwise F ST values of 0.780 collectively indicate strong phylogeographic structuring. Comparable genetic structuring has been observed in Indo-Pacific cetaceans, where oceanographic barriers and ecological specialization restrict gene flow despite considerable dispersal capacity. Genomic analyses of Indo-Pacific humpback dolphins ( Sousa chinensis ) revealed marked population subdivision and localized inbreeding. These findings collectively underscore limited connectivity within coastal environments (Zhang et al. 2025 ). In Indian waters, genetic studies of baleen whales have demonstrated clear population divergence. For example, Bryde’s whales in the northern Indian Ocean exhibit distinct mitochondrial lineages between coastal and offshore forms, indicating long-term reproductive isolation (Minton et al. 2011 ). In contrast, some localized cetacean populations show reduced genetic diversity due to demographic decline and isolation, reflecting limited gene flow (Taylor et al. 2026 ). The global beaked whale mtDNA dataset indicates high overall mitochondrial diversity. However, pronounced regional differentiation, especially between the Mediterranean and Indian Ocean populations, suggests limited female-mediated gene flow across basins. This pattern aligns with phylogeographic expectations for deep-diving odontocetes, which often exhibit site fidelity and basin-level isolation influenced by ecological factors and historical climatic events. Collectively, these findings align with broader marine mammal genetic research in the Indian and Indo-Pacific regions, underscoring that high genetic diversity does not necessarily equate to panmixia. Significant population subdivision and region-specific haplotypes emphasize the need to define Evolutionarily Significant Units (ESUs) and Management Units (MUs) for effective conservation (Avise 2000 ). Protecting both total genetic diversity and unique regional lineages is essential to maintain long-term adaptability and resilience amid increasing threats such as bycatch, underwater noise and habitat degradation. Currently, the analyses were performed solely based on the mtDNA sequences of the stranded samples collected from Tamil Nadu coast, and thus, it was not possible to represent all the Indian Ocean population with equal efforts. In the future, appropriate microsatellite markers will be used to elucidate the genetic sub-structuring in the population rather than by the mtDNA sequences. Also, additional sampling covering CBW’s entire distribution range, along with the use of multiple mtDNA and nuclear loci are required to further clarify the genetic assemblage. Conservation implications The present study is evidence for the genetic connectivity of the Indian Ocean population with the other seas, which should be taken into consideration while taking conservation measures for this species. As a modern solution, several Ultrasonic antifouling (UA) systems are being used in the maritime industry, which produce sound frequencies like those used by CBW for echolocation-based foraging and navigation and thus causes habitat displacement and increased stranding of CBW (Trickey et al. 2022 ; Feyrer et al. 2024 ; Erbe 2025; Širović 2026). Results showed the importance of integrating genetic studies in designing marine sanctuaries and other biologically sensitive areas, and policy frameworks should consider implementing acoustic regulations in the Important Marine Mammals Areas. Conclusion This is the first study to investigate the genetic diversity of Indian CBW, which provides insights into the genetic groups of CBW at a global scale to date. Earlier work by Onoufriou et al. (2022) on CBW from worldwide provided an incomplete picture of genetic groupings due to limited samples from the Indian Ocean. The findings in this study fill this gap and show that the Indian Ocean CBW are part of a heterogeneous genetic cluster within the Atlantic Ocean and Pacific Ocean with high genetic differentiation. Similar patterns of genetic clustering were observed in earlier studies by Onoufriou et al. (2022). However, addition of critical samples from the South-Asian subcontinents will help in getting a clear picture of genetic groups within this region. Overall, the global data showed a very structured phylogeographic pattern with genetically diverse haplotypes among the different regions identified. Though such a pattern could arise from incomplete sampling effort across the CBW range, it also indicates the presence of DIPs along the Indian coast which are threatened by various anthropogenic activities such as incidental bycatch in fishing, hunting, poaching, collision with aquatic transport, oil and mineral extraction, exposure to pollutants and pathogens, and underwater noise (Gales et al. 2003; Parsons et al. 2018; Helm et al. 2014; Avila et al. 2018) which directly impacts at both the population level and the individual level. The present study is evidence for the genetic connectivity of the Indian Ocean population with the other seas, which should be taken into consideration when elaborating conservation measures for this species. Further long-term studies are needed to understand CBW genetic distribution in the Indian Ocean, so that conservation measures against anthropogenic stress such as seismic surveys and naval exercises can be managed appropriately. Declarations Data availability All the data generated for this study is included in the paper Permits Prior permission from the Principal Chief Conservator of Forest and Chief Wildlife Warden (FAC) has been obtained to collect the tissue samples from stranded mammals under Ref. No.: WL5(A)/8619/2019 dated 01.09.2022. Owing to the non-destructive sampling approach used in this study, no ethical committee approvals were needed. Acknowledgments The authors greatly acknowledge the financial support provided by the Tamil Nadu Forest Department, Government of Tamil Nadu. The Principal Chief Forest Force and Chief Wildlife Warden are acknowledged for their help, support and encouragement. The authors acknowledge Dr Prithiviraj and Dr Asmitha Sivakumar for the necropsy, Deputy directors Ms Senbagapriya Sekar, I.F.S., Mr Yogesh Kumar Meena I.F.S. and Mr. D. Eswaran S.F.S for institutional support. The authors also thank Mr. Manoharan A and Dr. Bala Amaranth for reviewing the final draft. Author Contributions Madhumita Rajkumar contributed to the conceptualization, data analysis, and preparation of the initial draft. K. Venkatesan Meganath contributed to drafting the manuscript. Sivaranjani Adhimoolam and Yuvasri Kasinathan performed the experiments. Dhayanithi Vasanthakumar supervised the experimental work. Prasad Ganesan contributed to sample collection and permits. Arumugam Udhayan provided funding acquisition and institutional support. All authors reviewed earlier versions of the manuscript and approved the final version. Funding The financial support provided by the Tamil Nadu Forest Department, Government of Tamil Nadu under the scheme Annual Planning Operation 2024-2025. References Albouy C, Delattre VL, Mérigot B, Meynard CN, Leprieur F (2017) Multifaceted biodiversity hotspots of marine mammals for conservation priorities. Divers Distrib 23(6):615–626. https://doi.org/10.1111/ddi.12556 Avila, I. C., Kaschner, K., & Dormann, C. F. (2018). 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Marine Mammal Science , 42 (1), e70098. https://doi.org/10.1111/mms.70098 Tonay AM, Karaman K, Dede A, Danyer E, Aytemiz Danyer I, Uzun B, et al. (2024) Genetic investigation of Cuvier’s beaked whale, Ziphius cavirostris , along the coast of Türkiye and Northern Cyprus, based on mtDNA sequences. J Mar Biol Assoc UK, 104:e14. https://doi.org/10.1017/S0025315424000079 Trickey JS, Cárdenas-Hinojosa G, Rojas-Bracho L, et al. (2022) Ultrasonic antifouling devices negatively impact Cuvier’s beaked whales near Guadalupe Island, México. Commun Biol 5:1005. https://doi.org/10.1038/s42003-022-03959-9 Venu S, Malakar B (2015) Diversity of marine mammals of India—status, threats, conservation strategies and future scope of research. In Marine Faunal Diversity in India (pp. 283–302). Academic Press. http://dx.doi.org/10.1016/B978-0-12-801948-1.00018-5 Verma SK, Singh L (2003) Novel universal primers establish identity of an enormous number of animal species for forensic application. Mol Ecol Notes 3(1):28–31. https://doi.org/10.1046/j.1471-8286.2003.00340.x Waples, R. S. (1995). Evolutionarily Significant Units and the Conservation of Biological Diversity under the Endangered ‘Species Act. Evolution and the Aquatic Ecosystem: Defining Unique Units in Population Conservation; American Fisheries Society: Bethesda, MD, USA , 17 , 8-27. Watson J, Estes JA (2011) Stability, resilience, and phase shifts in rocky subtidal communities along the west coast of Vancouver Island, Canada. Ecol Monogr 81(2):215–239. https://doi.org/10.1890/10-0262.1 Zhang, X., Fang, Q., Qin, R., Xiang, Z., Zheng, R., Lin, B., ... & Yu, W. (2025). The conservation outcome of Indo-Pacific humpback Dolphin in China: A habitat suitability-based assessment. Ecological Informatics , 103580. https://doi.org/10.1016/j.ecoinf.2025.103580 Additional Declarations No competing interests reported. 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Conservation","correspondingAuthor":false,"prefix":"","firstName":"Dhayanithi","middleName":"","lastName":"Vasanthakumari","suffix":""},{"id":633233442,"identity":"d3cf4cca-f8ca-41a8-8afb-ae655773fa0a","order_by":5,"name":"Prasad Ganesan","email":"","orcid":"","institution":"Advanced Institute for Wildlife Conservation","correspondingAuthor":false,"prefix":"","firstName":"Prasad","middleName":"","lastName":"Ganesan","suffix":""},{"id":633233444,"identity":"0d1dd0ac-903a-4236-a581-edcb0846abc5","order_by":6,"name":"Arumugam Udhayan","email":"","orcid":"","institution":"Advanced Institute for Wildlife Conservation","correspondingAuthor":false,"prefix":"","firstName":"Arumugam","middleName":"","lastName":"Udhayan","suffix":""}],"badges":[],"createdAt":"2026-03-25 18:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9226304/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9226304/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108800045,"identity":"9854c86a-2f7e-41a2-9bf0-c2a362e6263e","added_by":"auto","created_at":"2026-05-08 14:05:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":282457,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing the locations of the samples that were used in the study\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9226304/v1/360e430680c837219519a1fe.png"},{"id":108800047,"identity":"61bb1dac-f875-4631-995e-52eb2f301528","added_by":"auto","created_at":"2026-05-08 14:05:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":104550,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic relationship among globally distributed and sampled CBW (\u003cem\u003eZ. cavirostris\u003c/em\u003e) using partial mitogenome generated from 28 unique mitogenome haplotypes with branch times\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9226304/v1/8e03dfef674eb68ae629b51f.png"},{"id":108800041,"identity":"6315f56d-2db1-49d7-aab3-9e8554afea74","added_by":"auto","created_at":"2026-05-08 14:05:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":65846,"visible":true,"origin":"","legend":"\u003cp\u003eMedian-joining haplotype network for concatenated mtDNA of CBW\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9226304/v1/26b7cff75acc956082221bd0.png"},{"id":108806989,"identity":"a4d4bdfd-77ea-44ea-96de-a5b2d7fd4e03","added_by":"auto","created_at":"2026-05-08 15:29:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":714030,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9226304/v1/e4093469-3d34-46ea-86de-163f3db78a89.pdf"},{"id":108800044,"identity":"8ea4abeb-e103-4a72-ba10-215e3d14da3c","added_by":"auto","created_at":"2026-05-08 14:05:45","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17458,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-9226304/v1/eef294bbe4671e287fdddd20.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Presence of novel mitochondrial haplotypes in Indian Cuvier’s beaked whale, Ziphius cavirostris (Cuvier, 1823)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMarine mammals are indicator species of a healthy marine ecosystem, as they play an ecologically significant role in nutrient recycling, facilitate bioturbation and maintain functional biodiversity and their decline affects prey population size (Katona and Whitehead \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Bowen \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Bossart \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Watson and Estes \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Roman et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kiszka et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Albouy et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Being globally distributed, they inhabit a wide range of environments from estuarine and coastal waters to the open oceans (Venu \u0026amp; Malakar, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Among marine mammals, cetaceans functionally play a major role as both top predators and nutrient vector due to its large body size which in turn reflects ecosystem productivity (Gilbert et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Around 90 cetacean species are known globally, comprising whales, dolphins, and porpoises, of which approximately 26 species have been reported from Indian waters, mainly through accidental catches and stranding records along the east and west coasts. (Venu \u0026amp; Malakar, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Montgelard \u003cem\u003eet al.\u003c/em\u003e, 2007)\u003c/p\u003e \u003cp\u003eAmong the whales, beaked whales (Ziphiidae) are the most specialized group of deep-sea marine mammals with only one pair of teeth. Among them, Cuvier's beaked whale (CBW; \u003cem\u003eZiphius cavirostris\u003c/em\u003e) is the only extant member of the genus \u003cem\u003eZiphius\u003c/em\u003e. Being elusive, their occurrences are known mostly when stranded (Bernaldo de Quir\u0026oacute;s et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Cox et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Simonis et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and are recorded throughout the world including temperate, subtropical, and tropical oceans in deep ocean near the continental slope particularly (Falcone et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Johnson et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; McSweeney et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Piboon et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The highest population were recorded in Pacific Ocean then North Atlantic Ocean especially Hawaii (Barlow et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). CBW from Mediterranean Sea and Albor\u0026aacute;n sea is known to be connected to Atlantic Ocean (Podest\u0026agrave; et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Apart from the major population, their presence has been recorded through dead stranding in the Malay Peninsula, East Indian Ocean and northern Java Malaysia, Andaman Sea, Satun Province and Thailand (De Boer, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Dammerman, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1926\u003c/span\u003e; Rudolph et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Jaaman et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Ponnampalam, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn India, occasional strandings have been recorded along the Indian coasts, namely in Gujarat (MMRCNI), Maharashtra (Chatterjee, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Karnataka (Naik et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Tamil Nadu (Oppili, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), West Bengal (Chakraborty \u0026amp; Mukherjee, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Lakshadweep (Pillai \u003cem\u003eet al\u003c/em\u003e., 1981). In India, it is protected under Schedule I of Wildlife (Protection) Act, 1972 and is also listed under Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES).\u003c/p\u003e \u003cp\u003eMarine mammals are known to be threatened by various anthropogenic activities such as incidental bycatch in fishing, hunting, poaching, collision with aquatic transport, oil and mineral extraction, exposure to pollutants and pathogens, and underwater noise (Avila et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gales et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Helm et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Parsons et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) which directly impacts at both the population level and the individual level. CBW being cosmopolitan range, its population undergoes both macro- and microevolution to form evolutionarily significant units (ESUs) as well as demographically independent populations (DIPs) (Waples \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Palsb\u0026oslash;ll et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Karen et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Many studies have used mtDNA genes, because of their high rate of mutation and resistance to selection pressures, to estimate genetic variation, phylogeography and population structure within wild populations of CBW (Dalebout et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Foote et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Onoufriou et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tonay et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Such studies will help in developing population-specific management plans and thus help in long-term conservation of this globally threatened marine mammal (Srinivas et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn India, this species is poorly studied except the records based on the stranding. Furthermore, there are no studies in the genetic field from India on CBW so far. Therefore, this paper presents the first genetic evidence of CBW along the Indian Ocean and also compares its population genetic structure and diversity across its cosmopolitan ranges.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e\u0026thinsp;Sample collection\u003c/h2\u003e\n \u003cp\u003eGiven the rare stranding of CBW in the Indian subcontinent, it was logistically difficult to conduct systematic sampling of biological material. Hence, Tissue samples from two individuals were opportunistically collected after necropsy of stranding from the coastal areas of Tamil Nadu. The details of the samples and their geographical sampling locations are provided in Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The samples were stored in ethanol at the field and later sent to the Advanced Institute for Wildlife Conservation (AIWC) for storage at \u0026minus;\u0026thinsp;20\u0026deg;C until further analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eDNA isolation, amplification and sequencing\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted using a DNeasy Blood \u0026amp; Tissue Kit (QIAGEN, Germany) according to the manufacturer\u0026rsquo;s protocol. DNA was eluted from 30 \u0026micro;L of elution buffer provided in kit. Extracted DNA samples were prepared for purity evaluation using 2% agarose gel electrophoresis. DNA quantity was determined using a nanodrop spectrophotometer.\u003c/p\u003e\n\u003cp\u003eDiluted samples (10 ng/\u0026micro;L) were stored at \u0026minus;\u0026thinsp;20\u0026deg;C for subsequent analyzes. PCR amplifications were conducted for four target genes \u0026minus;\u0026thinsp;12S rRNA, 16S rRNA, \u003cem\u003eCYTB\u003c/em\u003e, and \u003cem\u003eCOX I\u003c/em\u003e - using universal primer sets. Detailed annealing temperature and primer sequences are provided in supplementary table S2. Each reaction (30 \u0026micro;L total volume) contained 1\u0026times; Ampliqon Taq DNA Polymerase Master Mix RED, 0.10 \u0026micro;M of each primer, and 30 ng of template DNA, alongside a negative control. For amplified mitochondrial gene amplification, conditions were an initial denaturation for 5 min at 95\u0026deg;C, followed by 35 cycles of 30 s at 95\u0026deg;C (denaturation), 35 s at various annealing temperature between 50\u0026deg;C and 61\u0026deg;C (annealing), and 45 s at 72\u0026deg;C (extension) with a final elongation of 5 min at 72\u0026deg;C. Amplified products were resolved on a 2% agarose gel, and corresponding DNA bands were purified using the Qiagen MinElute PCR Product Purification Kit.\u003c/p\u003e\n\u003cp\u003ePurified products were bidirectionally sequenced using the BigDye Terminator Cycle Sequencing Kit (v.3.1 Applied Biosystems) and an AB PRISM 3500 (Applied Biosystems) automatic sequencer at AIWC.\u003c/p\u003e\n\u003ch3\u003ePhylogeography\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003ePhylogenetic trees of the mitochondrial sequences were constructed using MrBayes program v.3.2.7(Ronquist et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The obtained sequences were aligned using MAFFT (Katoh et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Sequences were concatenated in the order 12S RNA, 16S RNA, COX and CYTB using Mesquite 4.02 (Maddison and Maddison \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). jModelTest 2.1.10 was used to select the best tree evolutionary models for individual genes (Posada \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The run length of Markov Chain Monte Carlo (MCMC) sampling at 10,000,000 iterations for each tree was performed using the convergence diagnostics with an average standard deviation of split frequencies below 0.01. The first 1,000,000 iterations were discarded in the burn-in step. The phylogenetic trees were visualized and annotated using FigTree v.1.4 (Rambaut \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). A posterior probability value\u0026thinsp;\u0026ge;\u0026thinsp;0.95 was considered for indicating strong relationships (Dalebout et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eHaplotypes and genetic diversity\u003c/h3\u003e\n\u003cp\u003eThe haplotypes diversity for samples was compared to the worldwide haplotypes using the alignment of the dataset mentioned above via DnaSP program v6.12.3 (Rozas et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, the number of haplotypes (\u003cem\u003eH\u003c/em\u003e), the number of variable sites (\u003cem\u003eS\u003c/em\u003e), haplotype diversity (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e), and nucleotide diversity (\u003cem\u003e\u0026pi;\u003c/em\u003e) were calculated using the same program. To examine the regional genetic structure, the Median-Joining Networks (MJNs) of each haplotype (Bandelt et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) were constructed using the PopART program v1.7 (Leigh and Bryant \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eDataset\u003c/h2\u003e\n \u003cp\u003eAll four genes were sequenced and uploaded to NCBI, with their Accession IDs provided in supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Previously recorded 35 whole mitogenomes from Onoufriou et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) were used. A total of 37 concatenated mitochondrial DNA sequences from four oceanic regions: Atlantic (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18), Pacific (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;14), Mediterranean (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) and Indian Ocean (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2), with all gap-containing sites were analyzed.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003ePhylogeography\u003c/h3\u003e\n\u003cp\u003eThe best-fit nucleotide substitution models for 12S rRNA, 16S rRNA, COX, and CYTB were TrN\u0026thinsp;+\u0026thinsp;I, HKY\u0026thinsp;+\u0026thinsp;G, K80 and HKY\u0026thinsp;+\u0026thinsp;I, respectively, and were selected based on the Bayesian Information Criterion (BIC) scores in jModelTest.The mtDNA phylogeny of 37 CBW was clearly separated into four distinct clades (Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Clade 1 represents the Atlantic lineage, including samples from the Mediterranean Sea, whereas Clades 2 and 3 contained individuals from both Atlantic and Pacific lineages. The Indian Ocean lineage formed a separate monophyletic Clade 4 as a separate clade from other clades.\u003c/p\u003e\n\u003ch3\u003eMitochondrial genetic diversity\u003c/h3\u003e\n\u003cp\u003eThe final alignment of concatenated sequences comprising 2034 bp, with no gaps or missing data after quality filtering. Across the concatenated mitochondrial dataset, 104 polymorphic (segregating) sites were identified, resulting in a total of 107 mutational events (Eta). The analysis revealed a high number of unique haplotypes (\u003cem\u003eh\u003c/em\u003e\u0026thinsp;=\u0026thinsp;28) among the sampled individuals. Haplotype diversity was very high (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.983\u0026thinsp;\u0026plusmn;\u0026thinsp;0.010), indicating an extensive mitochondrial haplotype variation within the sampled population. The variance of haplotype diversity was low (0.00011), reflecting the robustness of the estimate despite the moderate sample size. Nucleotide diversity (\u003cem\u003e\u0026pi;\u003c/em\u003e) was estimated at 0.01023\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00034, suggesting moderate levels of sequence divergence across the concatenated mitochondrial regions. The corresponding average number of nucleotide differences between sequences was \u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;25.335, consistent with substantial mitochondrial variation at the population level.\u003c/p\u003e\n\u003cp\u003eThe dataset comprised 104 polymorphic sites and 107 mutational events, defining 28 distinct haplotypes. Overall haplotype diversity was very high (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.9835), indicating substantial mitochondrial variation. Notably, 22 haplotypes (78.6%) were singletons, whereas only 6 were shared among two or three individuals. The most frequent haplotypes (Hap_3 and Hap_5) were each detected in three individuals, while four additional haplotypes occurred in two individuals each. This pattern reflects high haplotype richness with limited dominance of any single mitochondrial lineage.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e\u0026thinsp;Mitochondrial genetic and haplotype diversity across oceanic regions\u003c/h2\u003e\n \u003cp\u003eA total of 37 sequences give rise to 104 polymorphic sites, defining 28 haplotypes, yielding high overall haplotype diversity (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.983) and moderate nucleotide diversity (\u003cem\u003e\u0026pi;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01023; \u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;25.33).\u003c/p\u003e\n \u003cp\u003eRegionally, haplotype diversity remained consistently high. The Atlantic population harboured 14 haplotypes (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.967; \u003cem\u003e\u0026pi;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01033), while the Pacific exhibited 10 haplotypes (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.956; \u003cem\u003e\u0026pi;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.00724). Despite small sample sizes, the Mediterranean and Indian Ocean populations each showed maximal haplotype diversity (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 1.000), with lower nucleotide diversity (\u003cem\u003e\u0026pi;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.00135 and 0.00525, respectively). Genetic differentiation among oceanic regions was significant (\u003cem\u003e\u0026chi;\u003c/em\u003e\u0026sup2; = 107.87, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0247), indicating population structure.\u003c/p\u003e\n \u003cp\u003eHaplotype distributions revealed predominantly region-specific lineages with limited inter-basin sharing. The Atlantic and Pacific populations contained several unique haplotypes, with only a single haplotype (Hap_3) shared between these basins. The Mediterranean and Indian Ocean samples were composed entirely of unique, region-restricted haplotypes, underscoring restricted mitochondrial connectivity across oceanic regions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003ePopulation-level genetic diversity\u003c/h2\u003e\n \u003cp\u003ePopulation-wise estimates of genetic diversity revealed consistently high haplotype diversity across all regions (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Atlantic population (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;18) contained 14 haplotypes with \u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.967, while the Pacific population (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;14) showed 10 haplotypes with \u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.956. Despite smaller sample sizes, the Mediterranean (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) and Indian Ocean (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2) populations both exhibited maximum haplotype diversity (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 1.000).\u003c/p\u003e\n \u003cp\u003eNucleotide diversity varied among regions, ranging from \u003cem\u003e\u0026pi;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.00135 in the Mediterranean to \u003cem\u003e\u0026pi;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01033 in the Atlantic population. The overall nucleotide diversity across all samples was\u0026nbsp;\u003cem\u003e\u0026pi;\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01023, with an average of 25.33 nucleotide differences between sequences.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMitogenomic haplotype diversity statistics are provided for each ocean basin: number of sequences (\u003cem\u003en\u003c/em\u003e), number of segregating sites (\u003cem\u003eS\u003c/em\u003e), number of haplotypes (\u003cem\u003eh\u003c/em\u003e), haplotype diversity (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e) and nucleotide diversity (\u003cem\u003e\u0026pi;\u003c/em\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePopulation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u003cem\u003eS\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e\u003cem\u003eh\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026pi;\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtlantic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.96732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.01033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003ePacific\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.95604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.00724\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eMediterranean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.00135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndian Ocean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e1.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\n \u003cp\u003e0.00525\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eGenetic differentiation among populations\u003c/h2\u003e\n \u003cp\u003eSignificant genetic differentiation was detected among the four oceanic populations. The chi-square test based on haplotype frequencies revealed significant population structure (\u003cem\u003e\u0026chi;\u003c/em\u003e\u0026sup2; = 107.87, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0247). Estimates of population subdivision based on haplotype frequencies were relatively low (\u003cem\u003eH\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.020), whereas sequence-based differentiation measures were higher (\u003cem\u003eK\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.203; \u003cem\u003eK\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.105*). The nearest-neighbour statistic (\u003cem\u003eS\u003c/em\u003e\u003csub\u003enn\u003c/sub\u003e = 0.863) further supported significant phylogeographic structure across oceanic regions.\u003c/p\u003e\n \u003cp\u003ePairwise comparisons revealed variable levels of differentiation. Lower differentiation was observed between the Atlantic and Pacific populations (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.183), while markedly higher differentiation was detected between geographically distant populations, including Pacific\u0026ndash;Mediterranean (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.648) and Mediterranean\u0026ndash;Indian Ocean (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.780).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eMedian-joining haplotype network analysis\u003c/h2\u003e\n \u003cp\u003eEstimates of gene flow differed substantially between haplotype-based and sequence-based approaches. Haplotype frequency-based estimates (Nei \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1973\u003c/span\u003e) suggested low overall differentiation (\u003cem\u003eG\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.0468) and relatively high gene flow (\u003cem\u003eN\u003c/em\u003e\u003csub\u003em\u003c/sub\u003e \u0026asymp; 5.09). In contrast, sequence-based estimators indicated substantially higher differentiation (\u003cem\u003eN\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.490; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.489) and low effective maternal gene flow (\u003cem\u003eN\u003c/em\u003e\u003csub\u003em\u003c/sub\u003e \u0026asymp; 0.26\u0026ndash;0.77), suggesting restricted mitochondrial exchange among oceanic basins.\u003c/p\u003e\n \u003cp\u003eThe median-joining haplotype network based on 28 haplotypes (Hap_1\u0026ndash;Hap_28) among 37 beaked whale sequences, with high haplotype diversity (\u003cem\u003eH\u003c/em\u003e\u003csub\u003ed\u003c/sub\u003e = 0.9835) is given in Fig. \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Most haplotypes were represented by single sequences, while a limited number were shared by two or three individuals. Hap_3 and Hap_5 each comprised three sequences, whereas Hap_8, Hap_9, Hap_12, Hap_14 and Hap_17 were shared by two sequences each. All remaining haplotypes (Hap_1, Hap_2, Hap_4, Hap_6, Hap_7, Hap_10, Hap_11, Hap_13, Hap_15, Hap_16, Hap_18\u0026ndash;Hap_28) were singletons. Hap_3 included sequences from both Pacific and Atlantic regions, while Hap_5, Hap_8, Hap_9 and Hap_10 were composed exclusively of Atlantic sequences. Pacific haplotypes were primarily represented by Hap_11\u0026ndash;Hap_19, with limited sharing among regions.\u003c/p\u003e\n \u003cp\u003eThe network showed multiple median vectors and several long mutational connections among haplotypes, indicating the presence of unsampled or extinct ancestral lineages. Overall, the predominance of low-frequency and region-specific haplotypes, combined with limited haplotype sharing across ocean basins, suggests strong phylogeographic structuring of maternal lineages in beaked whales.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv\u003e\n \u003cp\u003ePresence of unique population was evident based on mitochondrial markers. The current study also follows the global pattern of genetic structure obtained from previous studies (Dalebout et al. \u003cspan citationid=\"CR12\"\u003e2005\u003c/span\u003e, \u003cspan citationid=\"CR13\"\u003e2008\u003c/span\u003e; Onoufriou et al. \u003cspan citationid=\"CR39\"\u003e2022\u003c/span\u003e; Tonay et al. \u003cspan citationid=\"CR57\"\u003e2024\u003c/span\u003e). The previous studies have confirmed the presence of a heterogeneous genetic population between the Atlantic Ocean and Pacific Ocean, which is also reconfirmed in this study (Onoufriou et al. \u003cspan citationid=\"CR39\"\u003e2022\u003c/span\u003e). Earlier studies showed that the Mediterranean Sea lineage clustered within the Atlantic Ocean basin (Tonay et al. \u003cspan citationid=\"CR57\"\u003e2024\u003c/span\u003e), whereas in the current study, the Indian Ocean lineage forms clusters with both Pacific and Atlantic Ocean lineage clusters. This pattern may be explained by the strong connectivity among ocean basins, which can facilitate substantial gene flow between populations.\u003c/p\u003e\n \u003cp\u003eAcross oceanic regions, haplotype diversity remained consistently high; however, haplotypes were largely restricted to specific basins, with minimal inter-oceanic sharing. The significant chi-square statistic (\u003cem\u003e\u0026chi;\u003c/em\u003e\u0026sup2; = 107.87, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0247), elevated sequence-based differentiation (\u003cem\u003eK\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = 0.203), high nearest-neighbour statistic (\u003cem\u003eS\u003c/em\u003e\u003csub\u003enn\u003c/sub\u003e = 0.863) and pairwise \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values of 0.780 collectively indicate strong phylogeographic structuring. Comparable genetic structuring has been observed in Indo-Pacific cetaceans, where oceanographic barriers and ecological specialization restrict gene flow despite considerable dispersal capacity. Genomic analyses of Indo-Pacific humpback dolphins (\u003cem\u003eSousa chinensis\u003c/em\u003e) revealed marked population subdivision and localized inbreeding. These findings collectively underscore limited connectivity within coastal environments (Zhang et al. \u003cspan citationid=\"CR63\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIn Indian waters, genetic studies of baleen whales have demonstrated clear population divergence. For example, Bryde\u0026rsquo;s whales in the northern Indian Ocean exhibit distinct mitochondrial lineages between coastal and offshore forms, indicating long-term reproductive isolation (Minton et al. \u003cspan citationid=\"CR35\"\u003e2011\u003c/span\u003e). In contrast, some localized cetacean populations show reduced genetic diversity due to demographic decline and isolation, reflecting limited gene flow (Taylor et al. \u003cspan citationid=\"CR56\"\u003e2026\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe global beaked whale mtDNA dataset indicates high overall mitochondrial diversity. However, pronounced regional differentiation, especially between the Mediterranean and Indian Ocean populations, suggests limited female-mediated gene flow across basins. This pattern aligns with phylogeographic expectations for deep-diving odontocetes, which often exhibit site fidelity and basin-level isolation influenced by ecological factors and historical climatic events.\u003c/p\u003e\n \u003cp\u003eCollectively, these findings align with broader marine mammal genetic research in the Indian and Indo-Pacific regions, underscoring that high genetic diversity does not necessarily equate to panmixia. Significant population subdivision and region-specific haplotypes emphasize the need to define Evolutionarily Significant Units (ESUs) and Management Units (MUs) for effective conservation (Avise \u003cspan citationid=\"CR3\"\u003e2000\u003c/span\u003e). Protecting both total genetic diversity and unique regional lineages is essential to maintain long-term adaptability and resilience amid increasing threats such as bycatch, underwater noise and habitat degradation.\u003c/p\u003e\n \u003cp\u003eCurrently, the analyses were performed solely based on the mtDNA sequences of the stranded samples collected from Tamil Nadu coast, and thus, it was not possible to represent all the Indian Ocean population with equal efforts. In the future, appropriate microsatellite markers will be used to elucidate the genetic sub-structuring in the population rather than by the mtDNA sequences. Also, additional sampling covering CBW\u0026rsquo;s entire distribution range, along with the use of multiple mtDNA and nuclear loci are required to further clarify the genetic assemblage.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003e\u0026thinsp;Conservation implications\u003c/h2\u003e\n \u003cp\u003eThe present study is evidence for the genetic connectivity of the Indian Ocean population with the other seas, which should be taken into consideration while taking conservation measures for this species. As a modern solution, several Ultrasonic antifouling (UA) systems are being used in the maritime industry, which produce sound frequencies like those used by CBW for echolocation-based foraging and navigation and thus causes habitat displacement and increased stranding of CBW (Trickey et al. \u003cspan citationid=\"CR58\"\u003e2022\u003c/span\u003e; Feyrer et al. \u003cspan citationid=\"CR18\"\u003e2024\u003c/span\u003e; Erbe 2025; \u0026Scaron;irović 2026). Results showed the importance of integrating genetic studies in designing marine sanctuaries and other biologically sensitive areas, and policy frameworks should consider implementing acoustic regulations in the Important Marine Mammals Areas.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis is the first study to investigate the genetic diversity of Indian CBW, which provides insights into the genetic groups of CBW at a global scale to date. Earlier work by Onoufriou et al. (2022) on CBW from worldwide provided an incomplete picture of genetic groupings due to limited samples from the Indian Ocean. The findings in this study fill this gap and show that the Indian Ocean CBW are part of a heterogeneous genetic cluster within the Atlantic Ocean and Pacific Ocean with high genetic differentiation. Similar patterns of genetic clustering were observed in earlier studies by Onoufriou et al. (2022). \u0026nbsp;However, addition of critical samples from the South-Asian subcontinents will help in getting a clear picture of genetic groups within this region. Overall, the global data showed a very structured phylogeographic pattern with genetically diverse haplotypes among the different regions identified. Though such a pattern could arise from incomplete sampling effort across the CBW range, it also indicates the presence of DIPs along the Indian coast which are threatened by various anthropogenic activities such as incidental bycatch in fishing, hunting, poaching, collision with aquatic transport, oil and mineral extraction, exposure to pollutants and pathogens, and underwater noise (Gales et al. 2003; Parsons et al. 2018; Helm et al. 2014; Avila et al. 2018) which directly impacts at both the population level and the individual level. The present study is evidence for the genetic connectivity of the Indian Ocean population with the other seas, which should be taken into consideration when elaborating conservation measures for this species. Further long-term studies are needed to understand CBW genetic distribution in the Indian Ocean, so that conservation measures against anthropogenic stress such as seismic surveys and naval exercises can be managed appropriately.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e All the data generated for this study is included in the paper\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermits\u0026nbsp;\u003c/strong\u003ePrior permission from the Principal Chief Conservator of Forest and Chief Wildlife Warden (FAC) has been obtained to collect the tissue samples from stranded mammals under Ref. No.: WL5(A)/8619/2019 dated 01.09.2022. Owing to the non-destructive sampling approach used in this study, no ethical committee approvals were needed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003eThe authors greatly acknowledge the financial support provided by the Tamil Nadu Forest Department, Government of Tamil Nadu. The Principal Chief Forest Force and Chief Wildlife Warden are acknowledged for their help, support and encouragement. The authors acknowledge Dr Prithiviraj and Dr Asmitha Sivakumar for the necropsy, Deputy directors Ms Senbagapriya Sekar, I.F.S., \u0026nbsp;Mr Yogesh Kumar Meena I.F.S. and Mr. D. Eswaran S.F.S for institutional support. The authors also thank Mr.\u0026nbsp;Manoharan A and Dr. Bala Amaranth for reviewing the final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003eMadhumita Rajkumar contributed to the conceptualization, data analysis, and preparation of the initial draft. K. Venkatesan Meganath contributed to drafting the manuscript. Sivaranjani Adhimoolam and Yuvasri Kasinathan performed the experiments. Dhayanithi Vasanthakumar supervised the experimental work. Prasad Ganesan contributed to sample collection and permits. Arumugam Udhayan provided funding acquisition and institutional support. All authors reviewed earlier versions of the manuscript and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e The financial support provided by the Tamil Nadu Forest Department, Government of Tamil Nadu under the scheme Annual Planning Operation 2024-2025.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlbouy C, Delattre VL, M\u0026eacute;rigot B, Meynard CN, Leprieur F (2017) Multifaceted biodiversity hotspots of marine mammals for conservation priorities. Divers Distrib 23(6):615\u0026ndash;626. https://doi.org/10.1111/ddi.12556\u003c/li\u003e\n\u003cli\u003eAvila, I. 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The conservation outcome of Indo-Pacific humpback Dolphin in China: A habitat suitability-based assessment. \u003cem\u003eEcological Informatics\u003c/em\u003e, 103580. https://doi.org/10.1016/j.ecoinf.2025.103580\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"conservation-genetics-resources","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cogr","sideBox":"Learn more about [Conservation Genetics Resources](https://www.springer.com/journal/12686)","snPcode":"12686","submissionUrl":"https://submission.nature.com/new-submission/12686/3","title":"Conservation Genetics Resources","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cuvier’s beaked whale, Phylogeography, Population structure, Indian Ocean","lastPublishedDoi":"10.21203/rs.3.rs-9226304/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9226304/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Cuvier\u0026rsquo;s beaked whale (\u003cem\u003eZiphius cavirostris\u003c/em\u003e) is a pelagic marine mammal known for its elusive behavior and ecological importance as a predator in ocean ecosystems. Despite its wide distribution, records from Indian waters remain scarce. Here, we report two strandings of this species along the Tamil Nadu coast in 2024. Mitochondrial DNA (mtDNA) regions, including the COX region (630 bps) and cytochrome b (CYTB) (464 bps), 16S rRNA (520 bps) and 12S rRNA (420 bps), were sequenced and were found to be of two different haplotypes. Comparison with haplotypes previously reported outside India indicates genetic differentiation of the Indian subpopulation, based on the presence of two unique haplotypes. This study provides the first molecular evidence of \u003cem\u003eZiphius cavirostris\u003c/em\u003e from Indian waters and contributes to global phylogeographic datasets. Identification of region-specific haplotypes highlights the potential existence of Indian Ocean management units and emphasizes the need for regional conservation strategies.Additional mtDNA sequences from the India are needed for a better understanding of the genetic population structure of this species and to elaborate on more concrete conservation measures.\u003c/p\u003e","manuscriptTitle":"Presence of novel mitochondrial haplotypes in Indian Cuvier’s beaked whale, Ziphius cavirostris (Cuvier, 1823)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-08 14:05:34","doi":"10.21203/rs.3.rs-9226304/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"238909808954382926165007185133127437442","date":"2026-05-02T06:47:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-30T06:13:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-27T07:22:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-27T07:22:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Conservation Genetics Resources","date":"2026-03-25T18:09:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"conservation-genetics-resources","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cogr","sideBox":"Learn more about [Conservation Genetics Resources](https://www.springer.com/journal/12686)","snPcode":"12686","submissionUrl":"https://submission.nature.com/new-submission/12686/3","title":"Conservation Genetics Resources","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"39cfe610-4f3f-4da6-9b10-63e7ce2db241","owner":[],"postedDate":"May 8th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"238909808954382926165007185133127437442","date":"2026-05-02T06:47:26+00:00","index":9,"fulltext":""},{"type":"reviewersInvited","content":"4","date":"2026-04-30T06:13:34+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T14:05:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-08 14:05:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9226304","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9226304","identity":"rs-9226304","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}