Large-scale genomic surveys of crop germplasm are important for understanding the genetic architecture of favorable traits. The genomic basis of geographic differentiation and fiber improvement in cultivated cotton is poorly understood. Here, we analyzed 3,248 tetraploid cotton genomes and confirmed that the extensive chromosome inversions on chromosomes A06 and A08 underlies the geographic differentiation in cultivated Gossypium hirsutum. We further revealed that the haplotypic diversity originated from landraces, which might be essential for understanding adaptative evolution in cultivated cotton. Introgression and association analyses identified new fiber quality-related loci and demonstrated that the introgressed alleles from two diploid cottons had a large effect on fiber quality improvement. These loci provided the potential power to overcome the bottleneck in fiber quality improvement. Our study uncovered several critical genomic signatures generated by historical breeding effects in cotton and a wealth of data that enrich genomic resources for the research community.Known fetal hemoglobin (HbF) silencers have potential on-target liabilities for rational β-hemoglobinopathy therapeutic inhibition. Here, through transcription factor (TF) CRISPR screening, we identify zinc-finger protein (ZNF) 410 as an HbF repressor. ZNF410 does not bind directly to the genes encoding γ-globins, but rather its chromatin occupancy is concentrated solely at CHD4, encoding the NuRD nucleosome remodeler, which is itself required for HbF repression. CHD4 has two ZNF410-bound regulatory elements with 27 combined ZNF410 binding motifs constituting unparalleled genomic clusters. These elements completely account for the effects of ZNF410 on fetal globin repression. Knockout of ZNF410 or its mouse homolog Zfp410 reduces CHD4 levels by 60%, enough to substantially de-repress HbF while eluding cellular or organismal toxicity. These studies suggest a potential target for HbF induction for β-hemoglobin disorders with a wide therapeutic index. More broadly, ZNF410 represents a special class of gene regulator, a conserved TF with singular devotion to regulation of a chromatin subcomplex.A central question in the post-genomic era is how genes interact to form biological pathways. Measurements of gene dependency across hundreds of cell lines have been used to cluster genes into 'co-essential' pathways, but this approach has been limited by ubiquitous false positives. In the present study, we develop a statistical method that enables robust identification of gene co-essentiality and yields a genome-wide set of functional modules. This atlas recapitulates diverse pathways and protein complexes, and predicts the functions of 108 uncharacterized genes. Validating top predictions, we show that TMEM189 encodes plasmanylethanolamine desaturase, a key enzyme for plasmalogen synthesis. We also show that C15orf57 encodes a protein that binds the AP2 complex, localizes to clathrin-coated pits and enables efficient transferrin uptake. Finally, we provide an interactive webtool for the community to explore our results, which establish co-essentiality profiling as a powerful resource for biological pathway identification and discovery of new gene functions.CUB domain-containing protein 1 (CDCP1) is an oncogenic orphan transmembrane receptor and a promising target for the detection and treatment of cancer. Extracellular proteolysis of CDCP1 by poorly defined mechanisms induces pro-metastatic signaling. We describe a new approach for the rapid identification of proteases responsible for key proteolytic events using a substrate-biased activity-based probe (sbABP) that incorporates a substrate cleavage motif grafted onto a peptidyl diphenyl phosphonate warhead for specific target protease capture, isolation and identification. Using a CDCP1-biased probe, we identify urokinase (uPA) as the master regulator of CDCP1 proteolysis, which acts both by directly cleaving CDCP1 and by activating CDCP1-cleaving plasmin. We show that coexpression of uPA and CDCP1 is strongly predictive of poor disease outcome across multiple cancers and demonstrate that uPA-mediated CDCP1 proteolysis promotes metastasis in disease-relevant preclinical in vivo models. These results highlight CDCP1 cleavage as a potential target to disrupt cancer and establish sbABP technology as a new approach to identify disease-relevant proteases.Deep learning methods have been shown to achieve excellent performance on diagnostic tasks, but how to optimally combine them with expert knowledge and existing clinical decision pathways is still an open challenge. This question is particularly important for the early detection of cancer, where high-volume workflows may benefit from (semi-)automated analysis. Here we present a deep learning framework to analyze samples of the Cytosponge-TFF3 test, a minimally invasive alternative to endoscopy, for detecting Barrett's esophagus, which is the main precursor of esophageal adenocarcinoma. We trained and independently validated the framework on data from two clinical trials, analyzing a combined total of 4,662 pathology slides from 2,331 patients. Our approach exploits decision patterns of gastrointestinal pathologists to define eight triage classes of varying priority for manual expert review. By substituting manual review with automated review in low-priority classes, we can reduce pathologist workload by 57% while matching the diagnostic performance of experienced pathologists.Cognition can be defined as computation over meaningful representations in the brain to produce adaptive behaviour. https://www.selleckchem.com/products/terfenadine.html There are two views on the relationship between cognition and the brain that are largely implicit in the literature. The Sherringtonian view seeks to explain cognition as the result of operations on signals performed at nodes in a network and passed between them that are implemented by specific neurons and their connections in circuits in the brain. The contrasting Hopfieldian view explains cognition as the result of transformations between or movement within representational spaces that are implemented by neural populations. Thus, the Hopfieldian view relegates details regarding the identity of and connections between specific neurons to the status of secondary explainers. Only the Hopfieldian approach has the representational and computational resources needed to develop novel neurofunctional objects that can serve as primary explainers of cognition.