Pepper species (Capsicum spp.) are widely used as food, spice, decoration, and medicine. Despite the recent old-world culinary impact, more than 50 commercially recognized pod types have been recorded worldwide from three taxonomic complexes (A, B, and P). The current study aimed to apply a pan-plastome approach to resolve the plastomic boundaries among those complexes and identify effective loci for the taxonomical resolution and molecular identification of the studied species/varieties. High-resolution pan-plastomes of five species and two varieties were assembled and compared from 321 accessions. Phyloplastomic and network analyses clarified the taxonomic position of the studied species/varieties and revealed a pronounced number of accessions to be the rare and endemic species, C. galapagoense, that were mistakenly labeled as C. annuum var. glabriusculum among others. Similarly, some NCBI-deposited plastomes were clustered differently from their labels. The rpl23-trnI intergenic spacer contained a 44 bp tandem repeat that, in addition to other InDels, was capable of discriminating the investigated Capsicum species/varieties. The rps16-trnQ/rbcL-accD/ycf3-trnS gene set was determined to be sufficiently polymorphic to retrieve the complete phyloplastomic signal among the studied Capsicum spp. The pan-plastome approach was shown to be useful in resolving the taxonomical complexes, settling the incomplete lineage sorting conflict and developing a molecular marker set for Capsicum spp. identification.

Exploring the composition and structure of the faecal microbial community improves the understanding of the role of the gut microbiota in the gastrointestinal function and the egg-laying performance of hens. Therefore, detection of hen–microbial interactions can explore a new breeding marker for the selection of egg production due to the important role of the gut microbiome in the host’s metabolism and health. Recently, the gut microbiota has been recognised as a regulator of host performance, which has led to investigations of the productive effects of changes in the faecal microbiome in various animals. In the present study, a metagenomics analysis was applied to characterise the composition and structural diversity of faecal microbial communities under two selections of egg-laying performance, high (H, n = 30) and low (L, n = 30), using 16S rRNA-based metagenomic association analysis. The most abundant bacterial compositions were estimated based on the operational classification units among samples and between the groups from metagenomic data sets. The results indicated that Firmicutes phylum has higher significant (P < 0.01) in the H group than in the L group. In addition, higher relative abundance phyla of Bacteroides and Fusobacteria were estimated in the H group than the L group, contrasting the phyla of Actinobacteria, Cyanobacteria and Proteobacteria were more relative abundance in the L group. The families (Lactobacillus, Bifidobacterium, Acinetobacter, Flavobacteriaceae, Lachnoclostridum and Rhodococcus) were more abundant in the H group based on the comparison between the H and L groups. Meanwhile, three types of phyla (Proteobacteria, Actinobacteria and Cyanobacteria) and six families (Acinetobacter, Avibacterium, Clostridium, Corynebacterium, Helicobacter and Peptoclostridium) were more abundant in the L group (P < 0.01). Overall, the selection of genotypes has enriched a relationship between the gut microbiota and the egg-laying performance. These findings suggest that the faecal microbiomes of chickens with high egg-laying performance have more diverse activities than those of chickens with low egg-laying performance, which may be related to the metabolism and health of the host and egg production variation.

Earthy and musty off-flavors are routinely observed in farmed trout worldwide. The microbial association to the production of those off-flavors was previously reported. The current manuscript aimed to catalog the microbial enrichment (eukaryotes and prokaryotes) in semi-intensive aquaculture freshwater sources that might influence the trout aquaculture quality production. The 16S rRNA and ITS metabarcoding analyses were applied on the inflow- and pond-water samples from trout farms previously recorded a malodor fish products and located alongside Moosach and Sempt Rivers in Bavaria province, Germany. The results showed that more than 99% of the detected prokaryotic OTUs (Operational Taxonomic Unit identification) were bacteria as of ~ 75.57% were Proteobacteria, and ~ 14.4% were Bacteroidetes. Meanwhile, 118 out of 233 of the eukaryotic OTUs were known species. Of these, ~ 45% were plant pathogens, and ~ 28% were mushroom/yeasts. Based on the comparative analysis between inflow- and pond-water samples, several pro- and eukaryotic microorganisms that affect the trout aquaculture water quality and industry have been detected, including the malodor-producing microorganisms, e.g., Cyanobacteria and Actinobacteria, along with fish infectious microorganisms, e.g., Chilodonella cyprinid, Metschnikowia bicuspidate. Additionally, the effect of the human- and industrial-related activities around the sampling area on the microbiota of the investigated farms were highlighted.

The common cord moss Funaria hygrometrica has a worldwide distribution and thrives in a wide variety of environments. Here, we studied the genetic diversity in F. hygrometrica along an abiotic gradient in the Mediterranean high mountain of Sierra Nevada (Spain) using a genome scan method. Eighty-four samples from 17 locations from 24 to 2700 m were fingerprinted based on their amplified fragment length polymorphism (AFLP) banding pattern. Using PCA and Bayesian inference we found that the genetic diversity was structured in three or four clusters, respectively. Using a genome scan method we identified 13 outlier loci, which showed a signature of positive selection. Partial Mantel tests were performed between the Euclidean distance matrices of geographic and climatic variables, versus the pair-wise genetic distance of the AFLP dataset and AFLP-positive outliers dataset. AFLP-positive outlier data were significantly correlated with the gradient of the climatic variables, suggesting adaptive variation among populations of F. hygrometrica along the Sierra Nevada Mountains. We highlight the additional analyses necessary to identify the nature of these loci, and their biological role in the adaptation process.