Application of Microsatellites in Genetic Diversity Analysis and Population Discrimination of Coilia nasus from the Yangtze River
Year: 2026
Type: article
Abstract: The genetic diversity and population structure of five tapertail anchovy ( Coilia nasus ) populations—four wild populations from the Yangtze River (Taizhou, TZ; Anqing, AQ; Shanghai, SH; Hukou, HK) and one cultured population from Yangzhong (YZ)—were analyzed using 18 highly polymorphic microsatellite loci. All loci exhibited high polymorphism, with genetic parameters as follows: mean number of alleles ( Na ) = 20.567, expected heterozygosity ( He ) = 13.506, Shannon information index (I) = 2.743, and polymorphic information content (PIC) = 0.9624. F-statistics ( Fst ) ranged from 0.023 to 0.037, indicating varying degrees of genetic differentiation between all populations. The average Fst value across all loci was 0.047, suggesting overall low genetic differentiation. Analysis of molecular variance (AMOVA) revealed that 4% of the total genetic variation was attributable to differences among populations, 23% to variation among individuals within populations, and 73% to within-individual genetic variation. A UPGMA phylogenetic tree based on Nei’s genetic distance showed that the SH population clustered first with AQ, followed by TZ, HK, and finally YZ. Structure analysis identified three distinct genetic clusters, with TZ, SH, and AQ populations predominantly assigned to a single genetic group, while HK and YZ exhibited significant differentiation from the others. Additionally, discriminant functions developed from microsatellite data enabled accurate population assignment for all individuals. These findings provide critical insights into the genetic relationships and structure of C. nasus populations, offering valuable implications for their conservation and management.
Source: Animals
DOI: 10.3390/ani16030459
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,896
Awards: G3523585106, G8998766776
OpenAlex ID: W7127133797
