Pandey Pramod Kumar, Singh Yambem Suresh, Tripathy Partha Sarathi, Kumar Ram, Abujam Santosh Kumar, Parhi Janmejay
College of Fisheries, CAU (I), Tripura, India.
Fishery & Aquatic Biology Laboratory, Department of Zoology, Rajiv Gandhi University, Arunachal Pradesh, India.
Gene. 2020 Sep 5;754:144860. doi: 10.1016/j.gene.2020.144860. Epub 2020 Jun 10.
Arunachal Pradesh, the largest state of North-East India covers almost 60.93% of the Eastern Himalayan hotspot. Fish diversity and species identification is utmost important for fisheries management. But, in some cases morphological characteristics based identification is difficult for a non-specialist to perform. In view of the above, the present study emphasized on the assessment of DNA barcoding, phylogenetics and genetic diversity of fish species in the Ranganadi River, Arunachal Pradesh, India. India. Arunachal Pradesh, the largest state of North-East India covers almost 60.93% of the Eastern Himalayan hotspot. Altogether 114 specimens, representing 22 species, belonging to 3 orders and 5 families were successfully barcoded and found to be 98-100% identical from both GenBank and BOLD databases. Out of these 22 fish species, it was found that one species assessed was Endangered, three species as Near Threatened and one species as Vulnerable. A Neighbour Joining (NJ) tree was constructed using Rstudio for the purpose of a phylogenetic analysis of the identified species. The barcoding gap analysis using K2P, P-distance and Jukes-Cantor was done to detect the presence of cryptic species and barcoding success. The nucleotide base composition and genetic distance analysis were also performed, using MEGA 6.0. DNA Sequence Polymorphism v6.12.03 analysis revealed the nucleotide diversity (p) and haplotype diversity (Hd). The Hd for the whole dataset was found to be 0.975, which showed high genetic diversity in the Ranganadi River. Both morphological key identifying characters and molecular data corroborated the phylogenetic analysis. This COI barcode library, generated in the present study, not only helped in species identification and molecular study, but also in cryptic species identification.
阿鲁纳恰尔邦是印度东北部最大的邦,覆盖了东喜马拉雅热点地区近60.93%的面积。鱼类多样性和物种鉴定对于渔业管理至关重要。但是,在某些情况下,非专业人员很难基于形态特征进行鉴定。鉴于此,本研究着重评估了印度阿鲁纳恰尔邦朗加讷迪河鱼类物种的DNA条形码、系统发育学和遗传多样性。印度阿鲁纳恰尔邦是印度东北部最大的邦,覆盖了东喜马拉雅热点地区近60.93%的面积。总共114个标本,代表22个物种,分属于3目5科,已成功进行条形码编码,并且发现与GenBank和BOLD数据库中的序列有98 - 100%的一致性。在这22种鱼类中,发现有一种被评估为濒危物种,三种为近危物种,一种为易危物种。使用Rstudio构建了邻接(NJ)树,用于对已鉴定物种进行系统发育分析。使用K2P、P距离和Jukes - Cantor进行条形码间隙分析,以检测隐存物种的存在和条形码编码成功率。还使用MEGA 6.0进行了核苷酸碱基组成和遗传距离分析。DNA序列多态性v6.12.03分析揭示了核苷酸多样性(p)和单倍型多样性(Hd)。整个数据集的Hd为0.975,表明朗加讷迪河具有较高的遗传多样性。形态学关键鉴定特征和分子数据都证实了系统发育分析结果。本研究生成的这个细胞色素氧化酶亚基I(COI)条形码文库不仅有助于物种鉴定和分子研究,还有助于隐存物种的鉴定。