Wheat (Triticum spp.) is one of the founder crops that likely drove the Neolithic transition to sedentary agrarian societies in the Fertile Crescent more than 10,000 years ago. Identifying genetic modifications underlying wheat’s domestication requires knowledge about the genome of its allo-tetraploid progenitor, wild emmer (T. turgidum ssp. dicoccoides). We report a 10.1-gigabase assembly of the 14 chromosomes of wild tetraploid wheat, as well as analyses of gene content, genome architecture, and genetic diversity. With this fully assembled polyploid wheat genome, we identified the causal mutations in Brittle Rachis 1 (TtBtr1) genes controlling shattering, a key domestication trait. A study of genomic diversity among wild and domesticated accessions revealed genomic regions bearing the signature of selection under domestication. This reference assembly will serve as a resource for accelerating the genome-assisted improvement of modern wheat varieties.

Pineapple (Ananas comosus (L.) Merr.) is the most economically valuable crop possessing crassulacean acid metabolism (CAM), a photosynthetic carbon assimilation pathway with high water use efficiency, and the second most important tropical fruit after banana in terms of international trade. We sequenced the genomes of pineapple varieties ‘F153’ and ‘MD2’, and a wild pineapple relative A. bracteatus accession CB5. The pineapple genome has one fewer ancient whole genome duplications than sequenced grass genomes and, therefore, provides an important reference for elucidating gene content and structure in the last common ancestor of extant members of the grass family (Poaceae). Pineapple has a conserved karyotype with seven pre rho duplication chromosomes that are ancestral to extant grass karyotypes. The pineapple lineage has transitioned from C3 photosynthesis to CAM with CAM-related genes exhibiting a diel expression pattern in photosynthetic tissues using beta-carbonic anhydrase (βCA) for initial capture of CO2. Promoter regions of all three βCA genes contain a CCA1 binding site that can bind circadian core oscillators. CAM pathway genes were enriched with cis-regulatory elements including the morning (CCACAC) and evening (AAAATATC) elements associated with regulation of circadian-clock genes, providing the first link between CAM and the circadian clock regulation. Gene-interaction network analysis revealed both activation and repression of regulatory elements that control key enzymes in CAM photosynthesis, indicating that CAM evolved by reconfiguration of pathways preexisting in C3 plants. Pineapple CAM photosynthesis is the result of regulatory neofunctionalization of preexisting gene copies and not acquisition of neofunctionalized genes via whole genome or tandem gene duplication.

Multidrug efflux pumps have emerged as relevant elements in the intrinsic and acquired antibiotic resistance of bacterial pathogens. In contrast with other antibiotic resistance genes that have been obtained by virulent bacteria through horizontal gene transfer, genes coding for multidrug efflux pumps are present in the chromosomes of all living organisms. In addition, these genes are highly conserved (all members of the same species contain the same efflux pumps) and their expression is tightly regulated. Together, these characteristics suggest that the main function of these systems is not resisting the antibiotics used in therapy and that they should have other roles relevant to the behavior of bacteria in their natural ecosystems. Among the potential roles, it has been demonstrated that efflux pumps are important for processes of detoxification of intracellular metabolites, bacterial virulence in both animal and plant hosts, cell homeostasis and intercellular signal trafficking.

To assess the value of exosomal miRNAs as biomarkers for Alzheimer disease (AD), the expression of microRNAs was measured in a plasma fraction enriched in exosomes by differential centrifugation, using Illumina deep sequencing. Samples from 35 persons with a clinical diagnosis of AD dementia were compared to 35 age and sex matched controls. Although these samples contained less than 0.1 microgram of total RNA, deep sequencing gave reliable and informative results. Twenty miRNAs showed significant differences in the AD group in initial screening (miR-23b-3p, miR-24-3p, miR-29b-3p, miR-125b-5p, miR-138-5p, miR-139-5p, miR-141-3p, miR-150-5p, miR-152-3p, miR-185-5p, miR-338-3p, miR-342-3p, miR-342-5p, miR-548at-5p, miR-659-5p, miR-3065-5p, miR-3613-3p, miR-3916, miR-4772-3p, miR-5001-3p), many of which satisfied additional biological and statistical criteria, and among which a panel of seven miRNAs were highly informative in a machine learning model for predicting AD status of individual samples with 83–89% accuracy. This performance is not due to over-fitting, because a) we used separate samples for training and testing, and b) similar performance was achieved when tested on technical replicate data. Perhaps the most interesting single miRNA was miR-342-3p, which was a) expressed in the AD group at about 60% of control levels, b) highly correlated with several of the other miRNAs that were significantly down-regulated in AD, and c) was also reported to be down-regulated in AD in two previous studies. The findings warrant replication and follow-up with a larger cohort of patients and controls who have been carefully characterized in terms of cognitive and imaging data, other biomarkers (e.g., CSF amyloid and tau levels) and risk factors (e.g., apoE4 status), and who are sampled repeatedly over time. Integrating miRNA expression data with other data is likely to provide informative and robust biomarkers in Alzheimer disease.

Antibiotic resistance is one of the few examples of evolution that can be addressed experimentally. The present review analyses this resistance, focusing on the networks that regulate its acquisition and its effect on bacterial physiology. It is widely accepted that antibiotics and antibiotic resistance genes play fundamental ecological roles - as weapons and shields, respectively - in shaping the structures of microbial communities. Although this Darwinian view of the role of antibiotics is still valid, recent work indicates that antibiotics and resistance mechanisms may play other ecological roles and strongly influence bacterial physiology. The expression of antibiotic resistance determinants must therefore be tightly regulated and their activity forms part of global metabolic networks. In addition, certain bacterial modes of life can trigger transient phenotypic antibiotic resistance under some circumstances. Understanding resistance thus requires the analysis of the regulatory networks controlling bacterial evolvability, the physiological webs affected and the metabolic rewiring it incurs.