Search for: All records

Abstract Polyploidy complicates transcriptional regulation and increases phenotypic diversity in organisms. The dynamics of genetic regulation of gene expression between coresident subgenomes in polyploids remains to be understood. Here we document the genetic regulation of fiber development in allotetraploid cottonGossypium hirsutumby sequencing 376 genomes and 2,215 time-series transcriptomes. We characterize 1,258 genes comprising 36 genetic modules that control staged fiber development and uncover genetic components governing their partitioned expression relative to subgenomic duplicated genes (homoeologs). Only about 30% of fiber quality-related homoeologs show phenotypically favorable allele aggregation in cultivars, highlighting the potential for subgenome additivity in fiber improvement. We envision a genome-enabled breeding strategy, with particular attention to 48 favorable alleles related to fiber phenotypes that have been subjected to purifying selection during domestication. Our work delineates the dynamics of gene regulation during fiber development and highlights the potential of subgenomic coordination underpinning phenotypes in polyploid plants. 

Abstract Birefringent materials are widely used in various advanced optical systems, owing to their vital role in creating and controlling polarized light. Currently, Sn²⁺‐based compounds containing stereochemically active lone‐pair (SCALP) cations are extensively investigated and considered as one class of promising birefringent materials. To solve the problem of relatively narrow bandgap of Sn²⁺‐based compounds, alkali metals and multiple halogens are introduced to widen the bandgap during the research. Based on this strategy, four new Sn²⁺‐based halides, A₂Sn₂F₅Cl and ASnFCl₂(A = Rb and Cs), with large birefringence, short ultraviolet (UV) cutoff edge, and wide transparent range are successfully found. The birefringences of A₂Sn₂F₅Cl (A = Rb and Cs) are 0.31 and 0.28 at 532 nm, respectively, which are among the largest in Sn‐based halide family. Remarkably, A₂Sn₂F₅Cl possess relatively shorter UV cutoff edge (<300 nm) and broad infrared (IR) transparent range (up to 16.6 µm), so they can become promising candidates as birefringent materials applied in both UV and IR regions. In addition, a comprehensive analysis on crystal structures and structure–property relationship of metal Sn²⁺‐based halides is performed to fully understand this family. Therefore, this work provides insights into designing birefringent materials with balanced optical properties. 

Abstract Motivation Many important cellular processes involve physical interactions of proteins. Therefore, determining protein quaternary structures provide critical insights for understanding molecular mechanisms of functions of the complexes. To complement experimental methods, many computational methods have been developed to predict structures of protein complexes. One of the challenges in computational protein complex structure prediction is to identify near-native models from a large pool of generated models. Results We developed a convolutional deep neural network-based approach named DOcking decoy selection with Voxel-based deep neural nEtwork (DOVE) for evaluating protein docking models. To evaluate a protein docking model, DOVE scans the protein–protein interface of the model with a 3D voxel and considers atomic interaction types and their energetic contributions as input features applied to the neural network. The deep learning models were trained and validated on docking models available in the ZDock and DockGround databases. Among the different combinations of features tested, almost all outperformed existing scoring functions. Availability and implementation Codes available at http://github.com/kiharalab/DOVE, http://kiharalab.org/dove/. Supplementary information Supplementary data are available at Bioinformatics online.