We applied the phylogenomics to clarify the concept of rice species, aid in the identification and use of rice germplasms, and support rice biodiversity.
Abstract
Rice (genus Oryza) is one of the most important crops in the world, supporting half of the world’s population. Breeding of high-yielding and quality cultivars relies on genetic resources from both cultivated and wild species, which are collected and maintained in seed banks. Unfortunately, numerous seeds are mislabeled due to taxonomic issues or misidentifications. Here, we applied the phylogenomics of 58 complete chloroplast genomes and two hypervariable nuclear genes to determine species identity in rice seeds. Twenty-one Oryza species were identified. Conspecific relationships were determined between O. glaberrima and O. barthii, O. glumipatula and O. longistaminata, O. grandiglumis and O. alta, O. meyeriana and O. granulata, O. minuta and O. malampuzhaensis, O. nivara and O. sativa subsp. indica, and O. sativa subsp. japonica and O. rufipogon.D and L genome types were not found and the H genome type was extinct. Importantly, we evaluated the performance of four conventional plant DNA barcodes (matK, rbcL, psbA-trnH, and ITS), six rice-specific chloroplast DNA barcodes (psaJ-rpl33, trnC-rpoB, rps16-trnQ, rpl22-rps19, trnK-matK, and ndhC-trnV), two rice-specific nuclear DNA barcodes (NP78 and R22), and a chloroplast genome super DNA barcode. The latter was the most reliable marker. The six rice-specific chloroplast barcodes revealed that 17% of the 53 seed accessions from rice seed banks or field collections were mislabeled. These results are expected to clarify the concept of rice species, aid in the identification and use of rice germplasms, and support rice biodiversity.
Bacterial pneumonia is a major cause of morbidity and mortality in elderly. We hypothesize that dysbiosis between regular residents of the upper respiratory tract (URT) microbiome, that is balance between commensals and potential pathogens, is involved in pathogen overgrowth and consequently disease. We compared oropharyngeal microbiota of elderly pneumonia patients (n=100) with healthy elderly (n=91) by 16S-rRNA-based sequencing and verified our findings in young adult pneumonia patients (n=27) and young healthy adults (n=187). Microbiota profiles differed significantly between elderly pneumonia patients and healthy elderly (PERMANOVA, P<0.0005). Highly similar differences were observed between microbiota profiles of young adult pneumonia patients and their healthy controls. Clustering resulted in 11 (sub)clusters including 95% (386/405) of samples. We observed three microbiota profiles strongly associated with pneumonia (P<0.05) and either dominated by lactobacilli (n=11), Rothia (n=51) or Streptococcus (pseudo)pneumoniae (n=42). In contrast, three other microbiota clusters (in total n=183) were correlated with health (P<0.05) and were all characterized by more diverse profiles containing higher abundances of especially Prevotella melaninogenica, Veillonella and Leptotrichia. For the remaining clusters (n=99), the association with health or disease was less clear. A decision tree model based on the relative abundance of five bacterial community members in URT microbiota showed high specificity of 95% and sensitivity of 84% (89% and 73%, respectively, after cross-validation) for differentiating pneumonia patients from healthy individuals. These results suggest that pneumonia in elderly and young adults is associated with dysbiosis of the URT microbiome with bacterial overgrowth of single species and absence of distinct anaerobic bacteria. Whether the observed microbiome changes are a cause or a consequence of the development of pneumonia or merely coincide with disease status remains a question for future research. 相似文献