Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 February 2026 | 18(2): 28343–28349
ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.9679.18.2.28343-28349
#9679 | Received 12 February 2025 | Final received 10 December 2025 |
Finally accepted 06 January 2026
Analysis revealed minuscule DNA
sequence data availability for Indian marine macroalgal diversity
Digvijay Singh Yadav 1 , Aswin Alichen 2 & Vaibhav A. Mantri 3
1,2,3 Applied Phycology and
Biotechnology Division, CSIR- Central Salt and Marine Chemicals Research Institute,
Gijubhai Badheka Marg,
Bhavnagar, Gujarat 364002, India.
3 Academy of Scientific and
Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh
201002, India.
1 digvijaysingh.yadav@gmail.com, 2
aswinalichan12@gmail.com, 3 vaibhav.csmcri@csir.res.in
(corresponding author)
Editor: Ram Chandra Poudel,
Nepal Academy of Science and Technology (NAST), Lalitpur, Nepal. Date of publication: 26 February 2026 (online & print)
Citation: Yadav,
D.S., A. Alichen & V.A. Mantri (2026). Analysis
revealed minuscule DNA sequence data availability for sIndian
marine macroalgal diversity. Journal of
Threatened Taxa 18(2):
28343–28349. https://doi.org/10.11609/jott.9679.18.2.28343-28349
Copyright: © Yadav et al. 2026. Creative Commons Attribution 4.0 International License.
JoTT allows unrestricted use, reproduction, and
distribution of this article in any medium by providing adequate credit to the
author(s) and the source of publication.
Funding: Funding from Council of Scientific and Industrial Research, New Delhi is gratefully acknowledged.
Competing interests: The authors declare no competing interests.
Author details: Digvijay Singh Yadav has PhD in Biosciences with expertise in molecular taxonomy and pharmaceutical application of seaweeds. Currently working as a postdoctoral researcher at the CSIR-Central Salt and Marine Chemicals Research Institute (CSMCRI) in India, his work focuses on seaweed-propagule transport, biostimulant application, and large-scale seaweed cultivation along the Indian coast. Aswin Alichen has completed his post graduation and is a young and motivated researcher with strong interest in seaweed biology and seaweed-based climate changes studies. The research work in the current publication was carried out during his dissertation work at CSMCRI, India. Vaibhav A. Mantri is the chief principal scientist at CSMCRI, Dr. Mantri advances year-round Indian seaweed farming through improved cultivation techniques. His research focuses on strain enhancement, artificial seedling protocols to minimize epiphytic infestation, and developing viable farming methods by analyzing environmental determinants.
Author contributions: DSY-—investigation, formal analysis, methodology, validation, visualization, data curation, manuscript preparation. AA—investigation, formal analysis, methodology, validation, visualization, data curation. VAM—conceptualization, methodology, project administration, supervision, writing – review & editing, funding acquisition. All authors provided critical feedback and helped shape the research analysis and manuscript.
Acknowledgements:
We thank the director, CSIR Central Salt and Marine Chemicals Research Institute, Bhavnagar, for the support and facilities. This manuscript has PRIS registration number 96/2024.
Abstract: Seaweeds hold immense economic
potential due to multifarious applications in pharmaceuticals and everyday
products. India’s 11,099 km coastline harbours a rich
diversity of seaweeds in the Indian Ocean. Identifying seaweeds based on
morphology is challenging due to high phenotypic and reproductive plasticity,
so DNA barcoding is often used. This initiative marks the first national effort
to compile relevant scientific information on DNA barcoding of Indian marine
macroalgae, the current-status of knowledge and the scope for study. Despite
decades of molecular research on Indian macroalgae, the resulting sequence data
remain scattered across online repositories without systematic integration or
quality assessment. The study is a comprehensive analysis of current barcode
coverage of Indian seaweeds available on GenBank. With 207 unique sequences,
only 11% of total Indian macroalgal diversity has been studied yet. The
priority gaps that demonstrate direct benefits such as accurate taxonomic
identification, cultivation strain authentication, and assessment of invasive
species and surveillance of algal blooms, and indirect benefits like policy
support, conservation planning, reference libraries for eDNA, training, and
capacity building were identified. We consider that DNA barcoding at the
national level would not only help in the sustainable commercial utilisation of economically important species but also in
the conservation of endemic taxa. This is identified as a major research gap.
It needs to be addressed through concentrated efforts by national research organisations and universities, ascertaining the
availability of adequate infrastructure, and focused efforts on capacity
building. A comprehensive and collaborative research program is urgently needed
at the Pan-India level.
Keywords: AlgaeBase, aquaculture, bioprospecting,
conservation, DNA barcoding, GenBank, genetic resources, molecular systematics,
species identification, taxonomy.
Introduction
Marine macroalgae are gaining
importance globally due to their multifarious applications in commodity
products being used in day-to-day life. They are the only source of
polysaccharides such as, ulvan, agar, alginates,
mannitol, and carrageen having niche applications in biomedical, and
pharmaceutical domains (Pereira & Cotas 2024).
Studying the marine macro-algal biodiversity is pivotal for understanding the
health of marine ecosystems, searching for potent bioactive compounds, and
finding latent alternatives for food, feed, and fuels (Rajauria
et al. 2015). Conventional morphology-based identification often yields
inaccuracies due to phenotypic plasticity coupled with lack of specialized
taxonomic expertise. Therefore, DNA barcoding offers a universal and standardized
approach including for seaweeds (Hebert et al. 2003; Kowalska
et al. 2019). This technique is less susceptible to errors caused by phenotypic
variation, life stage, reproductive age, and does not require specialized
traditional taxonomy knowledge. Further, it is also important to learn
evolutionary lineages, discover novel species, and identify commercially
valuable species (Saunders 2005; Chac & Thinh 2023). DNA barcoding provides legally defensible
scientific evidence-based lab-to-market species identification, ensuring
traceability and linking product authenticity to performance outcomes. For
example, use of DNA barcoding for identifying novel seaweed species (Lagourgue et al. 2022), uncover genetic groups and morphospecies of Saccharina
sp. (Saunders and McDevit 2014), or correctly
identify Bulung sangu
(Gracilaria sp.) to decide specific and
correct cultivation methods to meet falling supply to high demands (Wirawan et al. 2021). For seaweeds such as Gracilaria dura known for high gel strength
(> 1,900 g cm−2 at 1%) if misidentified with other Gracilaria spp. may lead to performance failure and
economic loss (Mantri et al. 2022a). Further DNA barcode information may be
used to track and stop illegal trade of endangered species (Mishra et al. 2017).
India is globally recognized as a
megadiverse country, with 7–8% of the world’s recognized flora and fauna and
ranks fourth among the 34 biodiversity hotspots across the 17 megadiverse
countries of the world (Mantri et al. 2020). Indian coastline stretches over
11,099 km and the highest number of marine macro-algal taxa have been reported
from India compared to countries neighbouring the
Indian Ocean (Sahoo 2001). Despite decades of research involving molecular
identification of species, the online sequence data for Indian seaweeds is
scarce, for example DBIndalgae, first centralized
database effort in India to systematically compile information on native marine
algae (Bhushan et al. 2016). However, repositories like DIDI (Diatoms image
database of India), and Algal Database exist to address the challenges and
discrepancies in identifying diatoms and freshwater microalgae respectively
(Sharma et al. 2013; Pandey et al. 2016). The studies encompassing systematic
integration or quality assessment are highly desired to ensure accuracy and
reliability. To our knowledge, this is the first attempt to comprehensively analyse the online available sequence data for Indian
seaweeds based on the sequences available in GenBank. The current study aims to
provide a comprehensive, scientific inventory of publicly available DNA
sequence database of Indian seaweeds. Such analyses would establish an
integrated, quality-assured national baseline by consolidating decades of
fragmented DNA sequence records. Standardized markers and metadata would
enhance comparability across national laboratories, strengthening research and
policy synthesis practices. Molecular identification would enhance value-chain
growth and product traceability, along with accurate detection of potential
invasive, harmful bloom-forming taxa thereby reinforcing biosecurity. Further
this effort would be also crucial in identification of rare and threatened
taxa, those need immediate conservation attention. Thus, we emphasize the
urgent need for continued research, including marker-based sequencing efforts
and standardized methodologies to enhance our knowledge base and unlock the
full potential of Indian macroalgal biodiversity.
Methods
DNA-barcode sequences for Indian
macroalgal species reported in the checklist of Indian marine algae by Rao
& Gupta (2015) were obtained from the GenBank database (GenBank 2025). The
search terms used were: “India” + “Chlorophyta”, “India” + “Rhodophyta”, “India”
+ “Phaeophyta”, and “India” + “Ochrophyta”
for all the data available throughout the database, irrespective of submission
date range. All records for Phaeophyta were
combinedly presented under Ochrophyta throughout the
manuscript. For each record, accession, organism name, marker/gene,
publication, and collection location were extracted. The results were then
verified against Web of Science, Scopus, and PubMed databases to confirm
species name, marker usage, and sampling locations. Entries without peer-reviewed
published record, geographical locations, and the duplicate entries were
removed and not considered for the analysis. The accepted taxonomic
nomenclature was confirmed from AlgaeBase (Guiry & Guiry 2024). The
cleaned data of collected sequences were then categorized based on phylum,
class, and primer used to generate the DNA barcodes. The dataset thus obtained
was used for the analysis against the latest checklist by Rao & Gupta
(2015). The checklist represents 865 macro-algal species from India, including
212 green algae from 46 genera, 211 brown algae from 50 genera, and 442 red
algae in 138 genera.
Results
and Discussion
A total of 207 unique sequences
were obtained for Indian macro-algal species (Table 1) across chloroplast (rbcL, tufA, UPA, atpB, psbA),
mitochondria (COI-5P, cox), nucleus (ITS), and ribosome (LSU rDNA, 23S rRNA,18S
rRNA) (Figure 1) loci from GenBank establishing a unified baseline for
national-scale assessment and reuse. The study found that only 11% of the India
marine macro algae were documented from India. The data revealed that in
Chlorophyta, only nine genera containing 33 species from six unique orders have
been amplified based on chloroplast (39), mitochondrial (5), nuclear (22), and
ribosomal (16) gene markers. Ulva sapora and U.
paschima are now recognized as synonyms of Ulva
tepida and Caulerpa
peltata is synonymised
with Caulerpa chemnitzia
(Guiry & Guiry
2024). For Ochrophyta, 13 species of six genera were
identified from three unique orders, with 55% of the generated sequences from
chloroplast, 25% from mitochondria, and 10% each from nuclear and ribosomal
genes. Moreover, 49 species of 22 genera from 10 unique orders and four
varieties have been studied for Rhodophyta. Gracilaria
verrucosa has now been renamed Gracilariopsis longissima
(Guiry & Guiry
2024). Results revealed an uneven focus on molecular studies, with only 19% of
green, 12% of brown, and 16% of red algae species globally. This depends
largely on availability and due to more focused attention towards economically
important seaweeds that are given priority. The observed seaweeds species of
genus Kappaphycus, Gracilaria,
Porphyra, Sargassum,
Turbinaria, Padina
are cultivated at scale for high value compound extraction (carrageenan, agar,
alginates, pigments) and to be used as food (Ulva and Caulerpa species). Further, Laurencia,
Acanthophora, Caulerpa,
Bryopsis were studied for their bioactive
properties due to presence of halogenated and terpenoid metabolites. At the
genus level, it is only nine of the 46 reported green algal genera (20%), six
out of 50 brown algal genera (12%), and 22 of the 138 reported red algal genera
(16%) were reported from India. Further, among the 11 molecular markers that
were investigated rbcL is the most studied
marker (81 sequences), while atpB is the least
(only one sequence) investigated marker for Indian marine macro algae (Figure
1). An effective DNA barcode couples sufficient interspecific sequence
variation and ease of amplification across diverse taxa (Hollingsworth et al.
2009). Based on assessments of recoverability, sequence quality, and levels of
species discrimination, a 2-loci combination of rbcL+matK
as the plant barcode is recommended to provide a universal framework for the
routine use of DNA sequence data to identify specimens and contribute toward
the discovery of overlooked species of land plants (Leliaert
et al. 2012). Because land plants evolved from green algal ancestors, the use
of rbcL succeeded for seaweed DNA barcoding,
as its conserved priming sites and informative variation support dependable
amplification and species discrimination. The species delineation in marine
macro-algal taxa poses a considerable challenge due to high morphological,
anatomical, and reproductive plasticity. Nevertheless, taxonomic concepts in
this group are fast evolving globally with the advent of DNA barcoding
techniques. This is the first national effort to compile relevant scientific
information on DNA barcoding pertaining to Indian marine macro-algae, which was
scattered and difficult to access. The analysis revealed minuscule DNA sequence
data availability.
Seaweeds offer socio-economic
benefits to coastal communities through aquaculture and represent a valuable,
yet underexplored resource (Mantri et al. 2020). The seaweed aquaculture
industry is valued at USD 14 billion globally, producing 34.7 million tonnes of wet weight annually (FAO 2022) encompassing 51.3%
of the global aquaculture industry with 6.2% annual growth (Duarte et al.
2022), but India contributes only 0.01% of the cultivated seaweeds, indicating
a colossal gap (Mantri et al. 2022b). The lack of DNA sequence data
significantly hinders our ability to understand the full spectrum of seaweed
biodiversity range (endemic, exotic, and migratory species), abundance (dominant,
rare, vulnerable, and endangered species), ecological roles, and correct
taxonomic placement of Indian macro-algal species. We consider, DNA barcoding
data at the national level would not only help us in the sustainable commercial
utilisation of economically important species (Rao
& Mantri 2006) but also in the conservation of endemic taxa (Rathod et al.
2023). This is identified as a major research gap. It needs to be addressed
through concentrated efforts by national research organizations and universities,
ascertaining the availability of adequate infrastructure, and focused efforts
on capacity building (Mantri et al. 2020). However, the reliance on
public-domain with heterogenous quality, incomplete metadata, and marker bias
may limit resolution for certain clades and addressing these gaps would require
coordinated national sampling, sequencing efforts, and capacity building.
The results provide first
national current coverage of barcodes for Indian seaweed species, marker bias,
and the availability of miniscule molecular data compared to the huge
biodiversity. This calls for a comprehensive and collaborative research program
urgently needed at the Pan-India level. India is investing large amounts
of money in seaweed farming and value-chain development, and dependable species
authentication underpins quality, traceability of high value products (Mantri
et al. 2022a). Early detection of invasive species, surveillance of harmful
algae, and identifying species at risk would aid in strengthening coastal
biosecurity, select germplasm banking, risk management, and conservation and
policy formation (Armstrong & Ball 2005; Hofmann et al. 2025). Multi-gene
and method-integrated barcoding frameworks further improve resolution for
difficult groups, enhancing surveillance sensitivity and reliability. This
efficiency compounds benefits across ecology, systematics, and bioprospecting,
where barcoding underpins access to novel bioactives
and authentic species-level insights.
Data availability
The datasets generated during
and/or analysed during the current study are
available from the corresponding author upon reasonable request.
Table 1. Marker-wise
distribution of publicly available DNA barcode sequences from GenBank for Indian marine macroalgae by phylum, class,
order and taxonomically accepted scientific names of seaweeds from
India.
|
Phylum |
Class |
Order |
Scientific Name |
Primers |
|
Chlorophyta |
Ulvophyceae |
Bryopsidales |
Bryopsis sp. |
rbcL |
|
Caulerpa racemosa var. lamourouxii |
ITS |
|||
|
Caulerpa agardhii |
rbcL, 18S rRNA |
|||
|
Caulerpa fergusonii |
ITS |
|||
|
Caulerpa mexicana var. pluriseriata |
tufA |
|||
|
Caulerpa mexicana. |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa microphysa |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa peltata (C. chemnitzia) |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa racemosa |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa scalpelliformis |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa serrulata |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa sertularioides |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa taxifolia |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Caulerpa veravalensis |
rbcL, 18S rRNA, tufA, LSU rDNA |
|||
|
Caulerpa verticillata |
rbcL, 18S rRNA, tufA, ITS |
|||
|
Cladophorales |
Chaetomorpha antennina |
rbcL |
||
|
Cladophora goaensis |
ITS |
|||
|
Dasycladales |
Acetabularia jalakanyakae |
18S rRNA |
||
|
Ulvales |
Ulva chaugulei |
rbcL, ITS |
||
|
Ulva compressa |
rbcL, COI-5P, UPA |
|||
|
Caulerpa chemnitzia |
rbcL |
|||
|
Ulva flexuosa |
rbcL, COI-5P, UPA |
|||
|
Ulva intestinalis |
rbcL, ITS, cox |
|||
|
Ulva lactuca |
rbcL, 18S rRNA, ITS |
|||
|
Ulva ohnoi |
rbcL, ITS |
|||
|
Ulva paschima
(U. tepida) |
rbcL, COI-5P, UPA |
|||
|
Ulva reticulata |
rbcL, ITS |
|||
|
Ulva sapora
(U. tepida) |
ITS, atpB,
23S rRNA |
|||
|
Ulva uniseriata
|
ITS |
|||
|
Ulvella leptochaete |
rbcL, ITS, COI-5P |
|||
|
Ulvella sp. |
rbcL, ITS |
|||
|
|
Ulvophyceae |
Ulotrichales |
Gayralia brasiliensis |
ITS |
|
Chlorodendrophyceae |
Chlorodendrales |
Tetraselmis indica |
18S rRNA |
|
|
Ochrophyta |
Phaeophyceae |
Ectocarpales |
Chnoospora implexa |
rbcL, cox |
|
Chnoospora sp. |
rbcL, cox |
|||
|
Dictyotales |
Dictyota bartayresiana |
rbcL |
||
|
Dictyota dichotoma |
rbcL |
|||
|
Padina tetrastromatica |
rbcL |
|||
|
Fucales |
Sargassum aquifolium |
23S rRNA |
||
|
Sargassum linearifolium |
rbcL |
|||
|
Sargassum plagiophyllum |
23S rRNA |
|||
|
Sargassum polycystum |
rbcL |
|||
|
Sargassum swartzii |
rbcL |
|||
|
Sargassum tenerrimum |
rbcL |
|||
|
Sargassum zhangii |
ITS, cox |
|||
|
Turbinaria ornata |
ITS, cox |
|||
|
Anthophycus longifolius |
rbcL |
|||
|
Anthophycus sp. |
rbcL, cox |
|||
|
Rhodophyta |
Bangiophyceae |
Bangiales |
Phycocalidia acanthophora var. robusta |
rbcL, COI-5P |
|
Phycocalidia sukshma |
rbcL, COI-5P |
|||
|
Phycocalidia vietnamensis |
rbcL, COI-5P |
|||
|
Porphyra kanyakumariensis |
rbcL, COI-5P |
|||
|
Porphyra tenera |
rbcL |
|||
|
Porphyra yamadae |
rbcL, cox |
|||
|
Porphyra yezoensis |
rbcL |
|||
|
Pyropia acanthophora var. robusta |
rbcL, cox |
|||
|
Pyropia vietnamensis |
cox |
|||
|
Florideophyceae |
Batrachospermales |
Lemanea manipurensis |
rbcL |
|
|
Sirodotia assamica |
rbcL, COI-5P |
|||
|
Sheathia assamica |
rbcL |
|||
|
Ceramiales |
Caloglossa fluviatilis |
rbcL |
||
|
Palisada perforata |
rbcL |
|||
|
Caloglossa beccarii |
rbcL, LSU rDNA |
|||
|
Acanthophora spicifera |
rbcL |
|||
|
Laurencia thyrsifera |
rbcL, ITS, COI-5P |
|||
|
Rhodophyta |
Florideophyceae |
Ceramiales |
Herposiphonia akidoglossa |
rbcL, COI-5P, psbA |
|
Spyridia hypnoides |
rbcL, UPA, cox, LSU
rDNA |
|||
|
Corallinales |
Jania rubens |
rbcL |
||
|
Gelidiales |
Gelidiella acerosa |
rbcL, COI-5P |
||
|
Gelidiella indica |
rbcL, COI-5P, cox |
|||
|
Gigartinales |
Hypnea bullata |
rbcL, COI-5P, UPA |
||
|
Hypnea indica |
rbcL, COI-5P, UPA |
|||
|
Hypnea musciformis |
rbcL |
|||
|
Hypnea nidifica |
rbcL, COI-5P, UPA, cox |
|||
|
Hypnea nigrescens |
rbcL, COI-5P, UPA |
|||
|
Hypnea spinella |
rbcL, COI-5P, UPA |
|||
|
Hypnea valentiae |
rbcL, ITS |
|||
|
Kappaphycus alvarezii |
rbcL, ITS, COI-5P, UPA,
cox |
|||
|
Sarconema filiforme |
rbcL, COI-5P, cox |
|||
|
Gracilariales |
Gracilaria corticata |
rbcL, ITS, COI-5P, cox |
||
|
Gracilaria corticata var. corticata |
rbcL,18s RNA, cox |
|||
|
Gracilaria dura |
rbcL, 18s RNA, cox |
|||
|
Gracilaria corticata var. cylindrica |
rbcL, 18s RNA, cox |
|||
|
Gracilaria debilis |
rbcL, 18s RNA, cox |
|||
|
Gracilaria edulis |
23S rRNA |
|||
|
Gracilaria fergusonii |
23S rRNA |
|||
|
Gracilaria foliifera |
rbcL, 18s RNA, cox |
|||
|
Gracilaria gracilis |
rbcL, 18s RNA, cox |
|||
|
Gracilaria salicornia |
rbcL |
|||
|
Gracilaria textorii |
rbcL, 18s RNA, cox |
|||
|
Gracilaria verrucosa (Gracilariopsis longissima) |
rbcL, 23S rRNA |
|||
|
Gracilariopsis lemaneiformis |
rbcL, 18s RNA, cox |
|||
|
Hydropuntia edulis |
rbcL |
|||
|
Halymeniales |
Grateloupia catenata |
rbcL |
||
|
Grateloupia orientalis |
rbcL |
|||
|
Grateloupia sp. |
rbcL |
|||
|
Nemaliales |
Liagora albicans |
rbcL |
For figure - - click here for
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