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Abstract Lanternfish not only boast the most abundant biomass among marine fish species but also play a vital role in marine ecosystems. As one of the lanternfish species with the highest global catch, the skinnycheek lanternfish (Benthosema pterotum) is widely distributed in the Indo-Pacific region, playing a pivotal role in the marine biological pump. This study constructed the first chromosome-level genome of B. pterotum using a combination of short-read sequencing, PacBio, and Hi-C sequencing technologies. The genome size of B. pterotum is 1,272.53 Mb, with a contig N50 of 810 Kb and a scaffold N50 of 54.49 M. More than 99.65% of contigs were successfully anchored onto 24 pseudochromosomes, and 95.7% of BUSCO genes were identified within the genome, demonstrating the high level of completeness in genome assembly. A total of 24,934 protein-coding genes were predicted, of which 99.02% were functionally annotated. The successful assembly of a high-quality genome for B. pterotum provides valuable genetic resources for better understanding its biological characteristics and potentially those of all lanternfish species.

Acanthopagrus latus and Rhabdosargus sarba are economically important marine species along the coast of China, with similar external morphological characteristics and living habits, with wide distribution and strong adaptability. To investigate the molecular mechanisms underlying the adaptive evolution of these two species, we conducted whole-genome resequencing of 10 individuals of both species from the coastal waters of Wuyu Island, Fujian, China, using high-throughput sequencing technology. We obtained SNP, InDel, CNV, and SV variation information and annotated these variations, constructing a genomic variation database for both species. By comparing the resequencing data with reference genomes, we identified 9,829,511 SNP loci in the population of A. latus and 34,051,056 SNP loci in the population of R. sarba. Using whole-genome SNP data, we employed Fst and ROD methods to identify candidate genomic regions under selection. Functional annotation and enrichment analysis using GO and KEGG databases revealed potential adaptive evolution in R. sarba associated with immune response, feeding, growth and development, and locomotion, while A. latus showed potential adaptive evolution associated with immune response, nervous system, growth and development, and metabolism.

Studies on the demersal fish composition of the East Antarctic nearshore region are very scarce due to the harsh physical geography of the East Antarctic region, which is covered in ice and snow year round, leading to a scarcity of scientific surveys. Based on the data from the bottom trawl survey conducted by the 37–38th Chinese National Antarctic Research Expedition (CHINARE) program in the Cosmonaut Sea, East Antarctica, the species of demersal fishes were identified, and the demersal fish composition and the characteristics of depth distribution were examined and analyzed. The basic biological information of highly abundant species was analyzed. The results from 97 individuals sampled within 30–60° E, south of −65° S, indicate that the fishes belong to 5 orders, 11 families, 19 genera, and 23 species. Most of the species are found in Myctophidae and Bathydraconidae, and the most common species is Macrourus whitsoni (Macrouridae). Macrourus whitsoni and Prionodraco evansii have a high abundance in the survey. Macrourus whitsoni has body lengths of 144–662 mm and body weights of 17.3–1425.1 g, and Prionodraco evansii has body lengths of 90.18–134.33 mm and body weights of 4.9–20.7 g. The length–weight relationships for Macrourus whitsoni and Prionodraco evansii are y=0.00002x2.748 and y=0.000006x3.353, respectively. All the Macrourus whitsoni samples were found in waters deeper than 1000 m, with the highest number of individuals captured at depths of 1500–2000 m. Prionodraco evansii was found only at stations less than 250 m deep. These results complement the demersal fish composition and distribution data of the Cosmonaut Sea, East Antarctica. These data can provide valuable basic information for characterizing regional assemblages and delineating zoogeographic boundaries.