Inbreeding evaluation using microsatellite confirmed inbreeding depression in growth in the natural population.

Front Genet

Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.

Published: February 2023

Understanding inbreeding depressions (IBDs), the effect on the phenotypic performance of inbreeding, is of major importance for evolution and conservation genetics. Inbreeding depressions in aquatic animals were well documented in a domestic or captive population, while there is less evidence of inbreeding depression in natural populations. Chinese shrimp, , is an important species in both aquaculture and fishery activities in China. To investigate inbreeding depression in natural populations, four natural populations (Huanghua, Qinhuangdao, Qingdao, and Haiyang) were collected from the Bohai and Yellow seas. Microsatellite markers were used to evaluate individual inbreeding coefficients (F) of all samples. Furthermore, the effects of inbreeding on growth traits were investigated. The results showed marker-based F was continuous and ranged from 0 to 0.585, with an average of 0.191 ± 0.127, and there was no significant difference among the average F of the four populations. Regression analysis using the four populations showed inbreeding had a very significant ( < 0.01) effect on body weight. When analyzing a single population, regression coefficients were also all negative and those in Huanghua and in Qingdao were significant at the level of < 0.05 and < 0.01, respectively. Inbreeding depressions, expressed as the percent change in body weight per 10% increase in F, were 2.75% in Huanghua, 2.22% in Qingdao, and 3.69% in all samples. This study provided a piece of rare evidence of inbreeding depression in natural populations and also guidance toward the conservation of wild resources.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947229PMC
http://dx.doi.org/10.3389/fgene.2023.1077814DOI Listing

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