Yanfeng Zhou, Chenhe Wang, Binhu Wang, Dongpo Xu, Xizhao Zhang, You Ge, Shulun Jiang, Fujiang Tang, Chunhai Chen, Xuemei Li, Jianbo Jian, Yang You
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引用次数: 0
Abstract
The Asian icefish, Protosalanx chinensis, has undergone extensive colonization in various waters across China for decades due to its ecological and physiological significance as well as its economic importance in the fishery resource. Here, we decoded a telomere-to-telomere (T2T) genome for P. chinensis combining PacBio HiFi long reads and ultra-long ONT (nanopore) reads and Hi-C data. The telomere was identified in both ends of the contig/chromosome. The expanded gene associated with circadian entrainment suggests that P. chinensis may exhibit a high sensitivity to photoperiod. The contracted genes' immune-related families and DNA repair associated with positive selection in P. chinensis suggested the selection pressure during adaptive evolution. The population genetic analysis reported the genetic diversity and genomic footprints in 254 individuals from 8 different locations. The natural seawater samples can be the highest diversity and different from other freshwater and introduced populations. The divergent regions' associated genes were found to be related to the osmotic pressure system, suggesting adaptations to alkalinity and salinity. Thus, the T2T genome and genetic variation can be valuable resources for genomic footprints in P. chinensis, shedding light on its evolution, comparative genomics, and the genetic differences between natural and introduced populations.
期刊介绍:
GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.