The study of Hemipteran mitochondrial genomes (mitogenomes) began with the Chagas disease vector, Triatoma dimidiata, in 2001. At present, 90 complete Hemipteran mitogenomes have been sequenced and annotated. This review examines the history of Hemipteran mitogenomes research and summarizes the main features of them including genome organization, nucleotide composition, protein-coding genes, tRNAs and rRNAs, and non-coding regions. Special attention is given to the comparative analysis of repeat regions. Gene rearrangements are an additional data type for a few families, and most mitogenomes are arranged in the same order to the proposed ancestral insect. We also discuss and provide insights on the phylogenetic analyses of a variety of taxonomic levels. This review is expected to further expand our understanding of research in this field and serve as a valuable reference resource.

The mitochondrial gene COI has been widely used by taxonomists as a standard DNA barcode sequence for the identification of many animal species. However, the COI region is of limited use for identifying certain species and is not efficiently amplified by PCR in all animal taxa. To evaluate the utility of COI as a DNA barcode and to identify other barcode genes, we chose the aphid subfamily Lachninae (Hemiptera: Aphididae) as the focus of our study. We compared the results obtained using COI with two other mitochondrial genes, COII and Cytb. In addition, we propose a new method to improve the efficiency of species identification using DNA barcoding. Three mitochondrial genes (COI, COII and Cytb) were sequenced and were used in the identification of over 80 species of Lachninae. The COI and COII genes demonstrated a greater PCR amplification efficiency than Cytb. Species identification using COII sequences had a higher frequency of success (96.9% in “best match” and 90.8% in “best close match”) and yielded lower intra- and higher interspecific genetic divergence values than the other two markers. The use of “tag barcodes” is a new approach that involves attaching a species-specific tag to the standard DNA barcode. With this method, the “barcoding overlap” can be nearly eliminated. As a result, we were able to increase the identification success rate from 83.9% to 95.2% by using COI and the “best close match” technique. A COII-based identification system should be more effective in identifying lachnine species than COI or Cytb. However, the Cytb gene is an effective marker for the study of aphid population genetics due to its high sequence diversity. Furthermore, the use of “tag barcodes” can improve the accuracy of DNA barcoding identification by reducing or removing the overlap between intra- and inter-specific genetic divergence values.

Aphids of the subtribe Aphidina are found mainly in the North Temperate Zone. The relative lack of diagnostic morphological characteristics has obscured the identification of species in this group. However, DNA-based taxonomic methods can clarify species relationships within this group. Sequence variation in a partial segment of the mitochondrial COI gene was highly effective for resolving species relationships within Aphidina. Forty-five species were correctly identified in a neighbor-joining tree. Mean intraspecific sequence divergence was 0.17%, with a range of 0.00% to 1.54%. Mean interspecific divergence within previously recognized genera or morphologically similar species groups was 4.54%, with variation mainly in the range of 3.50% to 8.00%. Possible reasons for anomalous levels of mean nucleotide divergence within or between some taxa are discussed.

Chaitophorinae aphids are widespread across Eurasia and North America, and include some important agricultural and horticultural pests. So, accurate rapid species identification is very important. Here, we used three mitochondrial genes and one endosymbiont gene to calculate and analyze the genetic distances within different datasets. For species delimitation, two distance-based methods were employed, threshold with NJ (neighbor-joining) and ABGD (Automatic Barcode Gap Discovery), and two tree-based approaches, GMYC (General Mixed Yule Coalescent) and PTP (Poisson Tree Process). The genetic interspecific divergence was clearly larger than the intraspecific divergence for four molecular markers. COI and COII genes were found to be more suitable for Chaitophorinae DNA barcoding. For species delimitation, at least one distance-based method combined with one tree-based method would be preferable. Based on the data for Chaitophorus saliniger and Laingia psammae, DNA barcoding may also reveal geographical variation. Chaitophorinae aphids are widespread across Eurasia and North America, and include some important agricultural and horticultural pests. So, accurate rapid species identification is very important. Here, we used three mitochondrial genes and one endosymbiont gene to calculate and analyze the genetic distances within different datasets. For species delimitation, two distance-based methods were employed, threshold with NJ (neighbor-joining) and ABGD (Automatic Barcode Gap Discovery), and two tree-based approaches, GMYC (General Mixed Yule Coalescent) and PTP (Poisson Tree Process). The genetic interspecific divergence was clearly larger than the intraspecific divergence for four molecular markers. COI and COII genes were found to be more suitable for Chaitophorinae DNA barcoding. For species delimitation, at least one distance-based method combined with one tree-based method would be preferable. Based on the data for Chaitophorus saliniger and Laingia psammae, DNA barcoding may also reveal geographical variation.

Insects harbor diverse assemblages of bacterial and fungal symbionts, which play crucial roles in host life history. Insects and their various symbionts represent a good model for studying host–microbe interactions. Phylosymbiosis is used to describe an eco-evolutionary pattern, providing a new cross-system trend in the research of host-associated microbiota. The phylosymbiosis pattern is characterized by a significant positive correlation between the host phylogeny and microbial community dissimilarities. Although host–symbiont interactions have been demonstrated in many insect groups, our knowledge of the prevalence and mechanisms of phylosymbiosis in insects is still limited. Here, we provide an order-by-order summary of the phylosymbiosis patterns in insects, including Blattodea, Coleoptera, Diptera, Hemiptera, Hymenoptera, and Lepidoptera. Then, we highlight the potential contributions of stochastic effects, evolutionary processes, and ecological filtering in shaping phylosymbiotic microbiota. Phylosymbiosis in insects can arise from a combination of stochastic and deterministic mechanisms, such as the dispersal limitations of microbes, codiversification between symbionts and hosts, and the filtering of phylogenetically conserved host traits (incl., host immune system, diet, and physiological characteristics).