Genome-Wide Identification of R2R3-MYB Genes and Expression Analyses During Abiotic Stress in

The R2R3-MYB is one of the largest families of transcription factors, which have been implicated in multiple biological processes. There is great diversity in the number of R2R3-MYB genes in different plants. However, there is no report on genome-wide characterization of this gene family in cotton. In the present study, a total of 205 putative R2R3-MYB genes were identified in cotton D genome (Gossypium raimondii), that are much larger than that found in other cash crops with fully sequenced genomes. These GrMYBs were classified into 13 groups with the R2R3-MYB genes from Arabidopsis and rice. The amino acid motifs and phylogenetic tree were predicted and analyzed. The sequences of GrMYBs were distributed across 13 chromosomes at various densities. The results showed that the expansion of the G. Raimondii R2R3-MYB family was mainly attributable to whole genome duplication and segmental duplication. Moreover, the expression pattern of 52 selected GrMYBs and 46 GaMYBs were tested in roots and leaves under different abiotic stress conditions. The results revealed that the MYB genes in cotton were differentially expressed under salt and drought stress treatment. Our results will be useful for determining the precise role of the MYB genes during stress responses with crop improvement

Hydrogen Peroxide Acts on Sensitive Mitochondrial Proteins to Induce Death of a Fungal Pathogen Revealed by Proteomic Analysis

How the host cells of plants and animals protect themselves against fungal invasion is a biologically interesting and economically important problem. Here we investigate the mechanistic process that leads to death of Penicillium expansum, a widespread phytopathogenic fungus, by identifying the cellular compounds affected by hydrogen peroxide (H2O2) that is frequently produced as a response of the host cells. We show that plasma membrane damage was not the main reason for H2O2-induced death of the fungal pathogen. Proteomic analysis of the changes of total cellular proteins in P. expansum showed that a large proportion of the differentially expressed proteins appeared to be of mitochondrial origin, implying that mitochondria may be involved in this process. We then performed mitochondrial sub-proteomic analysis to seek the H2O2-sensitive proteins in P. expansum. A set of mitochondrial proteins were identified, including respiratory chain complexes I and III, F1F0 ATP synthase, and mitochondrial phosphate carrier protein. The functions of several proteins were further investigated to determine their effects on the H2O2-induced fungal death. Through fluorescent co-localization and the use of specific inhibitor, we provide evidence that complex III of the mitochondrial respiratory chain contributes to ROS generation in fungal mitochondria under H2O2 stress. The undesirable accumulation of ROS caused oxidative damage of mitochondrial proteins and led to the collapse of mitochondrial membrane potential. Meanwhile, we demonstrate that ATP synthase is involved in the response of fungal pathogen to oxidative stress, because inhibition of ATP synthase by oligomycin decreases survival. Our data suggest that mitochondrial impairment due to functional alteration of oxidative stress-sensitive proteins is associated with fungal death caused by H2O2

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Determining crystal structures through crowdsourcing and coursework

We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality