Microsporidia are obligate intracellular eukaryotic parasites that infect nearly all animal groups, including humans. The most common molecular methods for Microsporidia detection rely on species-targeting qPCR or end-point PCR using group-specific primers. However, these methods could be not specific enough or fail in case of mixed infections. We developed a method for parallel detection of both microsporidian infection and the host species. We designed new primer sets: one specific for the classical Microsporidia (targeting hypervariable V5 region of ssu rDNA), and a second one targeting a shortened fragment of the COI gene (standard metazoan DNA-barcode); both markers are well suited for a NGS approach. The analysis of ssu rDNA dataset representing 607 microsporidian species (120 genera) indicated that the V5 region enables identification of >98% species in the dataset (596/607). To test the method, we used microsporidians that infect mosquitoes in natural populations. Using mini-COI data, all field-collected mosquitoes were unambiguously assigned to seven species; among them almost 60% of specimens (127/212) were positive for at least 11 different microsporidian species, including a new microsporidian ssu rDNA sequence (Microsporidium sp. PL01). Phylogenetic analysis of Microsporidium sp. PL01 ssu rDNA showed that this species belongs to one of the two main clades in the Terresporidia. In addition, the level of microsporidian mixed infections was relatively high (9.4%). The numbers of sequence reads for the OTUs suggest that the occurrence of Nosema spp. in co-infections could benefit them; however, this observation should be re-tested using more intensive host sampling. The proposed method for detection of Microsporidia can be applied to all types of DNA extracts, including medical and environmental samples.
The leopard coral grouper, Plectropomus leopardus, belonging to genus Plectropomus, family Epinephelinae, is a carnivorous coral reef fish widely distributing in the tropical and subtropical water of Indo-Pacific Oceans. Due to its appealing body appearance and delicious taste, P. leopardus has become a popular commercial fish for aquaculture in many countries. However, the lack of genomic and molecular resources for P. leopardus hinders its biological studies and genomic breeding programs. Here we report the de novo sequencing and assembly of P. leopardus genome using 10× Genomics and high-throughput chromosome conformation capture (Hi-C) technologies. Using 127.36 Gb 10× Genomics we generated a 902.90 Mb genome assembly with a contig and scaffold N50 of 31.8 Kb and 33.47 Mb, respectively. The scaffolds were clustered and oriented into 24 pseudo-chromosomes with 13.39 Gb valid Hi-C data. BUSCO analysis showed that 95.3% of the conserved single-copy genes were retrieved, indicating a good entirety of the assembly. We predicted 23,234 protein-coding genes, among which 96.5% were functional annotated. The P. leopardus genome provides a valuable genomic resource for genetics, evolutionary and biological studies of this species. Particularly, it is expected to benefit the development of genomic breeding programs in the farming industry.
Gene annotation is a critical bottleneck in genomic research, especially for the comprehensive study of very large gene families in the genomes of non-model organisms. Despite the recent progress in automatic methods, state-of-the-art tools used for this task often produce inaccurate annotations, such as fused, chimeric, partial or even completely absent gene models for many family copies, errors that require considerable extra efforts to be corrected. Here we present BITACORA, a bioinformatics solution that integrates popular sequence similarity-based search tools and Perl scripts to facilitate both the curation of these inaccurate annotations and the identification of previously undetected gene family copies directly in genomic DNA sequences. We tested the performance of BITACORA in annotating the members of two chemosensory gene families with different repertoire size in seven available genome sequences, and compared its performance with that of Augustus-PPX, a tool also designed to improve automatic annotations using a sequence similarity-based approach. Despite the relatively high fragmentation of some of these drafts, BITACORA was able to improve the annotation of many members of these families and detected thousands of new chemoreceptors encoded in genome sequences. The program creates general feature format (GFF) files, with both curated and newly identified gene models, and FASTA files with the predicted proteins. These outputs can be easily integrated in genomic annotation editors, greatly facilitating subsequent manual annotation and downstream evolutionary analyses.