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Background Elevated water temperature, as is expected through climate change, leads to masculinization in fish species with sexual plasticity, resulting in changes in population dynamics. These changes are one important ecological consequence, contributing to the risk of extinction in small and inbred fish populations under natural conditions, due to male-biased sex ratio. Here we investigated the effect of elevated water temperature during embryogenesis on sex ratio and sex-biased gene expression profiles between two different tissues, namely gonad and caudal fin of adult zebrafish males and females, to gain new insights into the molecular mechanisms underlying sex determination (SD) and colour patterning related to sexual attractiveness. Results Our study demonstrated sex ratio imbalances with 25.5% more males under high-temperature condition, resulting from gonadal masculinization. The result of transcriptome analysis showed a significantly upregulated expression of male SD genes (e.g. dmrt1, amh, cyp11c1 and sept8b ) and downregulation of female SD genes (e.g. zp2.1, vtg1, cyp19a1a and bmp15 ) in male gonads compared to female gonads. Contrary to expectations, we found highly differential expression of colour pattern (CP) genes in the gonads, suggesting the ‘neofunctionalisation’ of those genes in the zebrafish reproduction system. However, in the caudal fin, no differential expression of CP genes was identified, suggesting the observed differences in colouration between males and females in adult fish may be due to post-transcriptional regulation of key enzymes involved in pigment synthesis and distribution. Conclusions Our study demonstrates male-biased sex ratio under high temperature condition and support a polygenic SD (PSD) system in laboratory zebrafish. We identify a subset of pathways (tight junction, gap junction and apoptosis), enriched for SD and CP genes, which appear to be co-regulated in the same pathway, providing evidence for involvement of those genes in the regulation of phenotypic sexual dimorphism in zebrafish. Electronic supplementary material The online version of this article (10.1186/s12864-019-5722-1) contains supplementary material, which is available to authorized users.

BackgroundThe identification of functionally or structurally important non-conserved residue sites in protein MSAs is an important challenge for understanding the structural basis and molecular mechanism of protein functions. Despite the rich literature on compensatory mutations as well as sequence conservation analysis for the detection of those important residues, previous methods often rely on classical information-theoretic measures. However, these measures usually do not take into account dis/similarities of amino acids which are likely to be crucial for those residues. In this study, we present a new method, the Quantum Coupled Mutation Finder (QCMF) that incorporates significant dis/similar amino acid pair signals in the prediction of functionally or structurally important sites.ResultsThe result of this study is twofold. First, using the essential sites of two human proteins, namely epidermal growth factor receptor (EGFR) and glucokinase (GCK), we tested the QCMF-method. The QCMF includes two metrics based on quantum Jensen-Shannon divergence to measure both sequence conservation and compensatory mutations. We found that the QCMF reaches an improved performance in identifying essential sites from MSAs of both proteins with a significantly higher Matthews correlation coefficient (MCC) value in comparison to previous methods. Second, using a data set of 153 proteins, we made a pairwise comparison between QCMF and three conventional methods. This comparison study strongly suggests that QCMF complements the conventional methods for the identification of correlated mutations in MSAs.ConclusionsQCMF utilizes the notion of entanglement, which is a major resource of quantum information, to model significant dissimilar and similar amino acid pair signals in the detection of functionally or structurally important sites. Our results suggest that on the one hand QCMF significantly outperforms the previous method, which mainly focuses on dissimilar amino acid signals, to detect essential sites in proteins. On the other hand, it is complementary to the existing methods for the identification of correlated mutations. The method of QCMF is computationally intensive. To ensure a feasible computation time of the QCMF’s algorithm, we leveraged Compute Unified Device Architecture (CUDA).The QCMF server is freely accessible at http://qcmf.informatik.uni-goettingen.de/.

Sex determination in zebrafish by manual approaches according to current guidelines relies on human observation. These guidelines for sex recognition have proven to be subjective and highly labor‐intensive. To address this problem, we present a methodology to automatically classify the phenotypic sex using two machine learning methods: Deep Convolutional Neural Networks (DCNNs) based on the whole fish appearance and Support Vector Machine (SVM) based on caudal fin coloration. Machine learning techniques in sex classification provide potential efficiency with the advantage of automatization and robustness in the prediction process. Furthermore, since developmental plasticity can be influenced by environmental conditions, we have investigated the impact of elevated water temperature during embryogenesis on sex and sex‐related differences in color intensity of adult zebrafish. The estimated color intensity based on SVM was then applied to detect the association between coloration and body weight and length. Phenotypic sex classifications using machine learning methods resulted in a high degree of association with the real sex in nontreated animals. In temperature‐induced animals, DCNNs reached a performance of 100%, whereas 20% of males were misclassified using SVM due to a lower color intensity. Furthermore, a positive association between color intensity and body weight and length was observed in males. Our study demonstrates that high ambient temperature leads to a lower color intensity in male animals and a positive association of male caudal fin coloration with body weight and length, which appears to play a significant role in sexual attraction. The software developed for sex classification in this study is readily applicable to other species with sex‐linked visible phenotypic differences.