A Genetic Evaluation System for New Zealand White Rabbit Germplasm Resources Based on SSR Markers

Microsatellite markers reveal genetic diversity and population structure of Portunus trituberculatus in the Bohai Sea, China

The swimming crab, Portunus trituberculatus, is one of the main aquaculture species in Chinese coastal regions due to its palatability and high economic value. To obtain a better understanding of the genetic diversity of P. trituberculatus in the Bohai Sea, the present study used 40 SSR loci to investigate the genetic diversity and population structure of 420 P. trituberculatus individuals collected from seven populations in the Bohai Sea. Genetic parameters revealed a low level of genetic diversity in the cultured population (SI = 1.374, He = 0.687, and PIC = 0.643) in comparison with wild populations (SI ≥ 1.399, He ≥ 0.692, and PIC ≥ 0.651). The genetic differentiation index (Fst) and gene flow (Nm) ranged from 0.001 to 0.060 (mean: 0.022) and 3.917 to 249.750 (mean: 31.289) respectively, showing a low differentiation among the seven populations of P. trituberculatus. Population structure analysis, phylogenetic tree, and principal component analysis (PCA) demonstrated that the seven groups of P. trituberculatus were divided into four subpopulations (K = 4), but the correlation between genetic structure and geographical distribution was not obvious. These results are expected to provide useful information for the fishery management of wild swimming crabs.

Genetic Diversity and Structure Revealed by Genomic Microsatellite Markers of Mytilus unguiculatus in the Coast of China Sea

The hard-shelled mussel Mytilus unguiculatus plays an important role in mussel aquaculture in China due to its characteristic and nutritive value. In this study, 10 microsatellite loci are used to study the genetic diversity and genetic structure of seven location populations of M. unguiculatus in coastal areas of China. The results of amplification and genotyping show that the observed heterozygosity (H_o) and the expected heterozygosity (H_e) are 0.61~0.71 and 0.72~0.83, respectively. M. unguiculatus has high genetic diversity. The inbreeding index (F_IS) of M. unguiculatus is significantly positive (F_IS: 0.14~0.19), indicating that inbreeding might exist within populations. The genetic structure of M. unguiculatus is weak within populations from the East China Sea All results showed that genetic differences existed between the Qingdao population from the Yellow Sea and other populations from the East China Sea. It does not detect a population bottleneck event or expansion event in the populations. The results from this study can be used to provide important insights in genetic management units and sustainable utilization of M. unguiculatus resources and provide a better understand of genetic structure of marine bivalve with similar planktonic larval stage in the China Sea.

An overview of remote monitoring methods in biodiversity conservation

Conservation of biodiversity is critical for the coexistence of humans and the sustenance of other living organisms within the ecosystem. Identification and prioritization of specific regions to be conserved are impossible without proper information about the sites. Advanced monitoring agencies like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) had accredited that the sum total of species that are now threatened with extinction is higher than ever before in the past and are progressing toward extinct at an alarming rate. Besides this, the conceptualized global responses to these crises are still inadequate and entail drastic changes. Therefore, more sophisticated monitoring and conservation techniques are required which can simultaneously cover a larger surface area within a stipulated time frame and gather a large pool of data. Hence, this study is an overview of remote monitoring methods in biodiversity conservation via a survey of evidence-based reviews and related studies, wherein the description of the application of some technology for biodiversity conservation and monitoring is highlighted. Finally, the paper also describes various transformative smart technologies like artificial intelligence (AI) and/or machine learning algorithms for enhanced working efficiency of currently available techniques that will aid remote monitoring methods in biodiversity conservation.