TY - JOUR AB - Suppressed recombination allows divergence between homologous sex chromosomes and the functionality of their genes. Here, we reveal patterns of the earliest stages of sex-chromosome evolution in the diploid dioecious herb Mercurialis annua on the basis of cytological analysis, de novo genome assembly and annotation, genetic mapping, exome resequencing of natural populations, and transcriptome analysis. The genome assembly contained 34,105 expressed genes, of which 10,076 were assigned to linkage groups. Genetic mapping and exome resequencing of individuals across the species range both identified the largest linkage group, LG1, as the sex chromosome. Although the sex chromosomes of M. annua are karyotypically homomorphic, we estimate that about one-third of the Y chromosome, containing 568 transcripts and spanning 22.3 cM in the corresponding female map, has ceased recombining. Nevertheless, we found limited evidence for Y-chromosome degeneration in terms of gene loss and pseudogenization, and most X- and Y-linked genes appear to have diverged in the period subsequent to speciation between M. annua and its sister species M. huetii, which shares the same sex-determining region. Taken together, our results suggest that the M. annua Y chromosome has at least two evolutionary strata: a small old stratum shared with M. huetii, and a more recent larger stratum that is probably unique to M. annua and that stopped recombining ∼1 MYA. Patterns of gene expression within the nonrecombining region are consistent with the idea that sexually antagonistic selection may have played a role in favoring suppressed recombination. AU - Veltsos, Paris AU - Ridout, Kate E. AU - Toups, Melissa A AU - González-Martínez, Santiago C. AU - Muyle, Aline AU - Emery, Olivier AU - Rastas, Pasi AU - Hudzieczek, Vojtech AU - Hobza, Roman AU - Vyskot, Boris AU - Marais, Gabriel A. B. AU - Filatov, Dmitry A. AU - Pannell, John R. ID - 7400 IS - 3 JF - Genetics SN - 0016-6731 TI - Early sex-chromosome evolution in the diploid dioecious plant Mercurialis annua VL - 212 ER - TY - JOUR AB - The formation of neuronal dendrite branches is fundamental for the wiring and function of the nervous system. Indeed, dendrite branching enhances the coverage of the neuron's receptive field and modulates the initial processing of incoming stimuli. Complex dendrite patterns are achieved in vivo through a dynamic process of de novo branch formation, branch extension and retraction. The first step towards branch formation is the generation of a dynamic filopodium-like branchlet. The mechanisms underlying the initiation of dendrite branchlets are therefore crucial to the shaping of dendrites. Through in vivo time-lapse imaging of the subcellular localization of actin during the process of branching of Drosophila larva sensory neurons, combined with genetic analysis and electron tomography, we have identified the Actin-related protein (Arp) 2/3 complex as the major actin nucleator involved in the initiation of dendrite branchlet formation, under the control of the activator WAVE and of the small GTPase Rac1. Transient recruitment of an Arp2/3 component marks the site of branchlet initiation in vivo. These data position the activation of Arp2/3 as an early hub for the initiation of branchlet formation. AU - Stürner, Tomke AU - Tatarnikova, Anastasia AU - Müller, Jan AU - Schaffran, Barbara AU - Cuntz, Hermann AU - Zhang, Yun AU - Nemethova, Maria AU - Bogdan, Sven AU - Small, Vic AU - Tavosanis, Gaia ID - 7404 IS - 7 JF - Development SN - 0950-1991 TI - Transient localization of the Arp2/3 complex initiates neuronal dendrite branching in vivo VL - 146 ER - TY - CONF AB - Graph planning gives rise to fundamental algorithmic questions such as shortest path, traveling salesman problem, etc. A classical problem in discrete planning is to consider a weighted graph and construct a path that maximizes the sum of weights for a given time horizon T. However, in many scenarios, the time horizon is not fixed, but the stopping time is chosen according to some distribution such that the expected stopping time is T. If the stopping time distribution is not known, then to ensure robustness, the distribution is chosen by an adversary, to represent the worst-case scenario. A stationary plan for every vertex always chooses the same outgoing edge. For fixed horizon or fixed stopping-time distribution, stationary plans are not sufficient for optimality. Quite surprisingly we show that when an adversary chooses the stopping-time distribution with expected stopping time T, then stationary plans are sufficient. While computing optimal stationary plans for fixed horizon is NP-complete, we show that computing optimal stationary plans under adversarial stopping-time distribution can be achieved in polynomial time. Consequently, our polynomial-time algorithm for adversarial stopping time also computes an optimal plan among all possible plans. AU - Chatterjee, Krishnendu AU - Doyen, Laurent ID - 7402 SN - 9781728136080 T2 - 34th Annual ACM/IEEE Symposium on Logic in Computer Science TI - Graph planning with expected finite horizon ER - TY - JOUR AB - We prove that the observable telegraph signal accompanying the bistability in the photon-blockade-breakdown regime of the driven and lossy Jaynes–Cummings model is the finite-size precursor of what in the thermodynamic limit is a genuine first-order phase transition. We construct a finite-size scaling of the system parameters to a well-defined thermodynamic limit, in which the system remains the same microscopic system, but the telegraph signal becomes macroscopic both in its timescale and intensity. The existence of such a finite-size scaling completes and justifies the classification of the photon-blockade-breakdown effect as a first-order dissipative quantum phase transition. AU - Vukics, A. AU - Dombi, A. AU - Fink, Johannes M AU - Domokos, P. ID - 7451 JF - Quantum SN - 2521-327X TI - Finite-size scaling of the photon-blockade breakdown dissipative quantum phase transition VL - 3 ER - TY - CONF AB - We present a new proximal bundle method for Maximum-A-Posteriori (MAP) inference in structured energy minimization problems. The method optimizes a Lagrangean relaxation of the original energy minimization problem using a multi plane block-coordinate Frank-Wolfe method that takes advantage of the specific structure of the Lagrangean decomposition. We show empirically that our method outperforms state-of-the-art Lagrangean decomposition based algorithms on some challenging Markov Random Field, multi-label discrete tomography and graph matching problems. AU - Swoboda, Paul AU - Kolmogorov, Vladimir ID - 7468 SN - 10636919 T2 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition TI - Map inference via block-coordinate Frank-Wolfe algorithm VL - 2019-June ER - TY - JOUR AU - Morandell, Jasmin AU - Nicolas, Armel AU - Schwarz, Lena A AU - Novarino, Gaia ID - 7415 IS - Supplement 6 JF - European Neuropsychopharmacology SN - 0924-977X TI - S.16.05 Illuminating the role of the e3 ubiquitin ligase cullin3 in brain development and autism VL - 29 ER - TY - JOUR AU - Knaus, Lisa AU - Tarlungeanu, Dora-Clara AU - Novarino, Gaia ID - 7414 IS - Supplement 6 JF - European Neuropsychopharmacology SN - 0924-977X TI - S.16.03 A homozygous missense mutation in SLC7A5 leads to autism spectrum disorder and microcephaly VL - 29 ER - TY - JOUR AU - Benková, Eva AU - Dagdas, Yasin ID - 7394 IS - 12 JF - Current Opinion in Plant Biology SN - 1369-5266 TI - Editorial overview: Cell biology in the era of omics? VL - 52 ER - TY - CONF AB - Multi-exit architectures, in which a stack of processing layers is interleaved with early output layers, allow the processing of a test example to stop early and thus save computation time and/or energy. In this work, we propose a new training procedure for multi-exit architectures based on the principle of knowledge distillation. The method encourage searly exits to mimic later, more accurate exits, by matching their output probabilities. Experiments on CIFAR100 and ImageNet show that distillation-based training significantly improves the accuracy of early exits while maintaining state-of-the-art accuracy for late ones. The method is particularly beneficial when training data is limited and it allows a straightforward extension to semi-supervised learning,i.e. making use of unlabeled data at training time. Moreover, it takes only afew lines to implement and incurs almost no computational overhead at training time, and none at all at test time. AU - Bui Thi Mai, Phuong AU - Lampert, Christoph ID - 7479 SN - 15505499 T2 - IEEE International Conference on Computer Vision TI - Distillation-based training for multi-exit architectures VL - 2019-October ER - TY - CONF AB - We present a novel class of convolutional neural networks (CNNs) for set functions,i.e., data indexed with the powerset of a finite set. The convolutions are derivedas linear, shift-equivariant functions for various notions of shifts on set functions.The framework is fundamentally different from graph convolutions based on theLaplacian, as it provides not one but several basic shifts, one for each element inthe ground set. Prototypical experiments with several set function classificationtasks on synthetic datasets and on datasets derived from real-world hypergraphsdemonstrate the potential of our new powerset CNNs. AU - Wendler, Chris AU - Alistarh, Dan-Adrian AU - Püschel, Markus ID - 7542 SN - 1049-5258 TI - Powerset convolutional neural networks VL - 32 ER -