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DNA Metabarcoding of Amazonian Ichthyoplankton Swarms

ترميز ميتاباركود الحمض النووي لأسراب العوالق البحرية الأمازونية
Authors: Jesus Nunez; Jesus Nunez; Fabrice Duponchelle; Fabrice Duponchelle; Yves Vigouroux; Jean-François Renno; Jean-François Martin; +6 Authors

DNA Metabarcoding of Amazonian Ichthyoplankton Swarms

Abstract

Les forêts tropicales humides abritent une biodiversité extraordinaire. On pense que le bassin amazonien abrite 30 % de toutes les espèces de poissons de rivière dans le monde. Les informations sur l'écologie, la reproduction et le recrutement de la plupart des espèces font toujours défaut, ce qui entrave la gestion des pêches et le succès des stratégies de conservation. L'un des principaux problèmes peu étudiés dans l'étude de la dynamique des populations est le recrutement. L'écologie larvaire des poissons dans les biomes tropicaux en est encore à ses balbutiements en raison de difficultés d'identification. Les techniques moléculaires sont des outils très prometteurs pour l'identification des larves au niveau des espèces. Cependant, l'une de leurs limites est l'obtention de séquences individuelles avec de grands échantillons de larves. Pour faciliter cette tâche, nous avons développé une nouvelle méthode basée sur la capacité massive de séquençage parallèle du séquençage de prochaine génération (NGS) couplé à la capture d'hybridation. Nous nous sommes concentrés sur le marqueur mitochondrial cytochrome oxydase I (COI). Les résultats obtenus à l'aide de la nouvelle méthode ont été comparés au séquençage larvaire individuel. Nous avons validé la capacité de la méthode à identifier les larves de poisson-chat amazonien au niveau des espèces et à estimer l'abondance relative des espèces dans les lots de larves. Enfin, nous avons appliqué la méthode et fourni des preuves d'une forte variation temporelle de l'activité reproductrice des espèces de poissons-chats dans la rivière Ucayalí en Amazonie péruvienne. Cette nouvelle méthode rapide et rentable permet l'acquisition de grands ensembles de données, ouvrant la voie à une meilleure compréhension de la dynamique de reproduction et des modèles de recrutement des espèces de poissons tropicaux, avec des implications majeures pour la gestion et la conservation des pêches.

Las selvas tropicales albergan una biodiversidad extraordinaria. Se cree que la cuenca del Amazonas alberga el 30% de todas las especies de peces de río del mundo. Todavía falta información sobre la ecología, la reproducción y el reclutamiento de la mayoría de las especies, lo que dificulta la gestión pesquera y las estrategias de conservación exitosas. Uno de los temas clave poco estudiados en el estudio de la dinámica de la población es el reclutamiento. La ecología larvaria de los peces en los biomas tropicales aún está en pañales debido a dificultades de identificación. Las técnicas moleculares son herramientas muy prometedoras para la identificación de larvas a nivel de especie. Sin embargo, uno de sus límites es la obtención de secuencias individuales con grandes muestras de larvas. Para facilitar esta tarea, desarrollamos un nuevo método basado en la capacidad de secuenciación paralela masiva de la secuenciación de próxima generación (NGS) junto con la captura de hibridación. Nos centramos en el marcador mitocondrial citocromo oxidasa I (COI). Los resultados obtenidos utilizando el nuevo método se compararon con la secuenciación larvaria individual. Validamos la capacidad del método para identificar larvas de bagre amazónico a nivel de especie y estimar la abundancia relativa de especies en lotes de larvas. Finalmente, aplicamos el método y proporcionamos evidencia de una fuerte variación temporal en la actividad reproductiva de las especies de bagre en el río Ucayalí en la Amazonía peruana. Este nuevo método rentable y de tiempo permite la adquisición de grandes conjuntos de datos, allanando el camino para una mejor comprensión de la dinámica reproductiva y los patrones de reclutamiento de especies de peces tropicales, con importantes implicaciones para la gestión y conservación de la pesca.

Tropical rainforests harbor extraordinary biodiversity. The Amazon basin is thought to hold 30% of all river fish species in the world. Information about the ecology, reproduction, and recruitment of most species is still lacking, thus hampering fisheries management and successful conservation strategies. One of the key understudied issues in the study of population dynamics is recruitment. Fish larval ecology in tropical biomes is still in its infancy owing to identification difficulties. Molecular techniques are very promising tools for the identification of larvae at the species level. However, one of their limits is obtaining individual sequences with large samples of larvae. To facilitate this task, we developed a new method based on the massive parallel sequencing capability of next generation sequencing (NGS) coupled with hybridization capture. We focused on the mitochondrial marker cytochrome oxidase I (COI). The results obtained using the new method were compared with individual larval sequencing. We validated the ability of the method to identify Amazonian catfish larvae at the species level and to estimate the relative abundance of species in batches of larvae. Finally, we applied the method and provided evidence for strong temporal variation in reproductive activity of catfish species in the Ucayalí River in the Peruvian Amazon. This new time and cost effective method enables the acquisition of large datasets, paving the way for a finer understanding of reproductive dynamics and recruitment patterns of tropical fish species, with major implications for fisheries management and conservation.

تضم الغابات الاستوائية المطيرة تنوعًا بيولوجيًا استثنائيًا. يُعتقد أن حوض الأمازون يحتوي على 30 ٪ من جميع أنواع الأسماك النهرية في العالم. لا يزال هناك نقص في المعلومات حول البيئة والتكاثر وتجنيد معظم الأنواع، مما يعوق إدارة مصايد الأسماك واستراتيجيات الحفظ الناجحة. واحدة من القضايا الرئيسية غير المدروسة في دراسة الديناميات السكانية هي التوظيف. لا تزال بيئة يرقات الأسماك في المناطق الأحيائية الاستوائية في مهدها بسبب صعوبات تحديد الهوية. التقنيات الجزيئية هي أدوات واعدة للغاية لتحديد اليرقات على مستوى الأنواع. ومع ذلك، فإن أحد حدودها هو الحصول على تسلسلات فردية مع عينات كبيرة من اليرقات. لتسهيل هذه المهمة، قمنا بتطوير طريقة جديدة تعتمد على قدرة التسلسل المتوازي الهائلة لتسلسل الجيل التالي (NGS) إلى جانب التقاط التهجين. ركزنا على علامة الميتوكوندريا أوكسيديز السيتوكروم I (COI). تمت مقارنة النتائج التي تم الحصول عليها باستخدام الطريقة الجديدة مع تسلسل اليرقات الفردي. لقد تحققنا من قدرة الطريقة على تحديد يرقات سمك السلور الأمازوني على مستوى الأنواع وتقدير الوفرة النسبية للأنواع على دفعات من اليرقات. أخيرًا، طبقنا الطريقة وقدمنا أدلة على التباين الزمني القوي في النشاط التكاثري لأنواع سمك السلور في نهر أوكايالي في الأمازون البيروفي. وتمكن هذه الطريقة الجديدة الفعالة من حيث الوقت والتكلفة من الحصول على مجموعات بيانات كبيرة، مما يمهد الطريق لفهم أدق للديناميات الإنجابية وأنماط التجنيد لأنواع الأسماك الاستوائية، مع ما يترتب على ذلك من آثار كبيرة على إدارة مصائد الأسماك وحفظها.

Keywords

Next-Generation Sequencing, 570, Neotropical Fish Assemblages, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Amazon rainforest, Science, Population, 590, Abundance (ecology), Environmental DNA, Fish Biodiversity, Sociology, Biochemistry, Genetics and Molecular Biology, [SDV.BID.SPT] Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, Animals, DNA Barcoding, Taxonomic, Molecular Biology, Biology, Nature and Landscape Conservation, Demography, Ecology, Q, R, Fishes, High-Throughput Nucleotide Sequencing, Life Sciences, Phylogenetics and taxonomy, Biodiversity, DNA Barcoding for Food Authentication and Fraud Detection, FOS: Sociology, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, Fishery, Larva, FOS: Biological sciences, Environmental Science, Physical Sciences, Ichthyoplankton, Medicine, Tropical River Fisheries, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Zoology, Biogeography and Conservation of Neotropical Freshwater Fishes, Environmental DNA in Biodiversity Monitoring, Research Article

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Average
Top 10%
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