Phasianidae is a family of Galliformes containing 38 genera and approximately 138 species, which is grouped into two tribes based on their morphological features, the Pheasants and Partridges. Several studies have attempted to reconstruct the phylogenetic relationships of the Phasianidae, but many questions still remain unaddressed, such as the taxonomic status and phylogenetic relationships among Crossoptilon species. The mitochondrial genome (mitogenome) has been extensively used to infer avian genetic diversification with reasonable resolution. Here, we sequenced the entire mitogenomes of three Crossoptilon species (C. harmani, C. mantchuricum and C. crossoptilon) to investigate their evolutionary relationship among Crossoptilon species. The complete mitogenomes of C. harmani, C. mantchuricum and C. crossoptilon are 16682 bp, 16690 bp and 16680 bp in length, respectively, encoding a standard set of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes, and a putative control region. C. auritum and C. mantchuricum are more closely related genetically, whereas C. harmani is more closely related to C. crossoptilon. Crossoptilon has a closer relationship with Lophura, and the following phylogenetic relationship was reconstructed: ((Crossoptilon + Lophura) + (Phasianus + Chrysolophus)). The divergence time between the clades C. harmani-C. crossoptilon and C. mantchuricum-C. auritum is consistent with the uplift of the Tibetan Plateau during the Tertiary Pliocene. The Ka/Ks analysis showed that atp8 gene in the Crossoptilon likely experienced a strong selective pressure in adaptation to the plateau environment. C. auritum with C. mantchuricum and C. harmani with C. crossoptilon form two pairs of sister groups. The genetic distance between C. harmani and C. crossoptilon is far less than the interspecific distance and is close to the intraspecific distance of Crossoptilon, indicating that C. harmani is much more closely related to C. crossoptilon. Our mito-phylogenomic analysis supports the monophyly of Crossoptilon and its closer relationship with Lophura. The uplift of Tibetan Plateau is suggested to impact the divergence between C. harmani-C. crossoptilon clade and C. mantchuricum-C. auritum clade during the Tertiary Pliocene. Atp8 gene in the Crossoptilon species might have experienced a strong selective pressure for adaptation to the plateau environment.

We tested the performance of DNA barcoding in Acridoidea and attempted to solve species boundary delimitation problems in selected groups using COI barcodes. Three analysis methods were applied to reconstruct the phylogeny. K2P distances were used to assess the overlap range between intraspecific variation and interspecific divergence. “Best match (BM)”, “best close match (BCM)”, “all species barcodes (ASB)” and “back-propagation neural networks (BP-based method)” were utilized to test the success rate of species identification. Phylogenetic species concept and network analysis were employed to delimitate the species boundary in eight selected species groups. The results demonstrated that the COI barcode region performed better in phylogenetic reconstruction at genus and species levels than at higher-levels, but showed a little improvement in resolving the higher-level relationships when the third base data or both first and third base data were excluded. Most overlaps and incorrect identifications may be due to imperfect taxonomy, indicating the critical role of taxonomic revision in DNA barcoding study. Species boundary delimitation confirmed the presence of oversplitting in six species groups and suggested that each group should be treated as a single species.

Background: Transposable elements (TEs) have been likened to parasites in the genome that reproduce and move ceaselessly in the host, continuously enlarging the host genome. However, the Piwi-interacting RNA (piRNA) pathway defends animal genomes against the harmful consequences of TE invasion by imposing small-RNA-mediated silencing. Here we compare the TE activity of two grasshopper species with different genome sizes in Acrididae (Locusta migratoria manilensis♀1C = 6.60 pg, Angaracris rhodopa♀1C = 16.36 pg) to ascertain the influence of piRNAs. Results: We discovered that repetitive sequences accounted for 74.56% of the genome in A. rhodopa, more than 56.83% in L. migratoria, and the large-genome grasshopper contained a higher TEs proportions. The comparative analysis revealed that 41 TEs (copy number > 500) were shared in both species. The two species exhibited distinct “landscapes” of TE divergence. The TEs outbreaks in the small-genome grasshopper occurred at more ancient times, while the large-genome grasshopper maintains active transposition events in the recent past. Evolutionary history studies on TEs suggest that TEs may be subject to different dynamics and resistances in these two species. We found that TE transcript abundance was higher in the large-genome grasshopper and the TE-derived piRNAs abundance was lower than in the small-genome grasshopper. In addition, we found that the piRNA methylase HENMT, which is underexpressed in the large-genome grasshopper, impedes the piRNA silencing to a lower level. Conclusions: Our study revealed that the abundance of piRNAs is lower in the gigantic genome grasshopper than in the small genome grasshopper. In addition, the key gene HENMT in the piRNA biogenesis pathway (Ping-Pong cycle) in the gigantic genome grasshopper is underexpressed. We hypothesize that low-level piRNA silencing unbalances the original positive correlation between TEs and piRNAs, and triggers TEs to proliferate out of control, which may be one of the reasons for the gigantism of grasshopper genomes.

Background: Amino acid substitution models play an important role in inferring phylogenies from proteins. Although different amino acid substitution models have been proposed, only a few were estimated from mitochondrial protein sequences for specific taxa such as the mtArt model for Arthropoda. The increasing of mitochondrial genome data from broad Orthoptera taxa provides an opportunity to estimate the Orthoptera-specific mitochondrial amino acid empirical model. Results: We sequenced complete mitochondrial genomes of 54 Orthoptera species, and estimated an amino acid substitution model (named mtOrt) by maximum likelihood method based on the 283 complete mitochondrial genomes available currently. The results indicated that there are obvious differences between mtOrt and the existing models, and the new model can better fit the Orthoptera mitochondrial protein datasets. Moreover, topologies of trees constructed using mtOrt and existing models are frequently different. MtOrt does indeed have an impact on likelihood improvement as well as tree topologies. The comparisons between the topologies of trees constructed using mtOrt and existing models show that the new model outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein data. Conclusions: The new mitochondrial amino acid substitution model of Orthoptera shows obvious differences from the existing models, and outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein sequences.