Genome and population evolution and environmental adaptation of Glyptosternon maculatum on the Qinghai-Tibet Plateau

Persistent uplift means the Qinghai-Tibet Plateau(QTP)is an ideal natural laboratory to investigate genome evolution and adaptation within highland environments.However,how paleogeographic and paleoclimatic events influence the genome and population of endemic fish species remains unclear.Glyptosternon maculatum is an ancient endemic fish found on the QTP and the only critically endangered species in the Sisoridae family.Here,we found that major transposons in the G.maculatum genome showed episodic bursts,consistent with contemporaneous geological and climatic events during the QTP formation.Notably,histone genes showed significant expansion in the G.maculatum genome,which may be mediated by long interspersed nuclear elements(LINE)repetitive element duplications.Population analysis showed that ancestral G.maculatum populations experienced two significant depressions 2.6 million years ago(Mya)and 10000 years ago,exhibiting excellent synchronization with Quaternary glaciation and the Younger Dryas,respectively.Thus,we propose that paleogeography and paleoclimate were dominating driving forces for population dynamics in endemic fish on the QTP.Tectonic movements and temperature fluctuation likely destroyed the habitat and disrupted the drainage connectivity among populations.These factors may have caused severe bottlenecks and limited migration among ancestral G.maculatum populations,resulting in the low genetic diversity and endangered status of the species today.

3DPhenoFish:Application for two-and three-dimensional fish morphological phenotype extraction from point cloud analysis

Fish morphological phenotypes are important resources in artificial breeding,functional gene mapping,and population-based studies in aquaculture and ecology.Traditional morphological measurement of phenotypes is rather expensive in terms of time and labor.More importantly,manual measurement is highly dependent on operational experience,which can lead to subjective phenotyping results.Here,we developed 3DPhenoFish software to extract fish morphological phenotypes from three-dimensional(3D)point cloud data.Algorithms for background elimination,coordinate normalization,image segmentation,key point recognition,and phenotype extraction were developed and integrated into an intuitive user interface.Furthermore,18 key points and traditional 2D morphological traits,along with 3D phenotypes,including area and volume,can be automatically obtained in a visualized manner.Intuitive fine-tuning of key points and customized definitions of phenotypes are also allowed in the software.Using 3DPhenoFish,we performed high-throughput phenotyping for four endemic Schizothoracinae species,including Schizopygopsis younghusbandi,Oxygymnocypris stewartii,Ptychobarbus dipogon,and Schizothorax oconnori.Results indicated that the morphological phenotypes from 3DPhenoFish exhibited high linear correlation(>0.94)with manual measurements and offered informative traits to discriminate samples of different species and even for different populations of the same species.In summary,we developed an efficient,accurate,and customizable tool,3DPhenoFish,to extract morphological phenotypes from point cloud data,which should help overcome traditional challenges in manual measurements.3DPhenoFish can be used for research on morphological phenotypes in fish,including functional gene mapping,artificial selection,and conservation studies.3DPhenoFish is an open-source software and can be downloaded for free at https://github.com/lyh24k/3DPhenoFish/tree/master.