Three-dimensional (3D) fluorescence microscopy in general requires axial scanning to capture images of a sample at different planes. Here we demonstrate that a deep convolutional neural network can be trained to virtually refocus a 2D fluorescence image onto user-defined 3D surfaces within the sample volume. With this data-driven computational microscopy framework, we imaged the neuron activity of a Caenorhabditis elegans worm in 3D using a time-sequence of fluorescence images acquired at a single focal plane, digitally increasing the depth-of-field of the microscope by 20-fold without any axial scanning, additional hardware, or a trade-off of imaging resolution or speed. Furthermore, we demonstrate that this learning-based approach can correct for sample drift, tilt, and other image aberrations, all digitally performed after the acquisition of a single fluorescence image. This unique framework also cross-connects different imaging modalities to each other, enabling 3D refocusing of a single wide-field fluorescence image to match confocal microscopy images acquired at different sample planes. This deep learning-based 3D image refocusing method might be transformative for imaging and tracking of 3D biological samples, especially over extended periods of time, mitigating photo-toxicity, sample drift, aberration and defocusing related challenges associated with standard 3D fluorescence microscopy techniques. Text:Three-dimensional (3D) fluorescence microscopic imaging is essential for biomedical and physical sciences as well as engineering, covering various applications 1-7 . Despite its broad

Recombination events are not uniformly distributed and often cluster in narrow regions known as recombination hotspots. Several studies using different approaches have dramatically advanced our understanding of recombination hotspot regulation. Population genetic data have been used to map and quantify hotspots in the human genome. Genetic variation in recombination rates and hotspots usage have been explored in human pedigrees, mouse intercrosses, and by sperm typing. These studies pointed to the central role of the PRDM9 gene in hotspot modulation. In this study, we used single nucleotide polymorphisms (SNPs) from wholegenome resequencing and genotyping studies of mouse inbred strains to estimate recombination rates across the mouse genome and identified 47,068 historical hotspots-an average of over 2477 per chromosome. We show by simulation that inbred mouse strains can be used to identify positions of historical hotspots. Recombination hotspots were found to be enriched for the predicted binding sequences for different alleles of the PRDM9 protein. Recombination rates were on average lower near transcription start sites (TSS). Comparing the inferred historical recombination hotspots with the recent genome-wide mapping of double-strand breaks (DSBs) in mouse sperm revealed a significant overlap, especially toward the telomeres. Our results suggest that inbred strains can be used to characterize and study the dynamics of historical recombination hotspots. They also strengthen previous findings on mouse recombination hotspots, and specifically the impact of sequence variants in Prdm9. R ECOMBINATION events are not uniformly distributed across the genome; rather they tend to occur at hotspot regions typically 1-2 kb in size (Jeffreys et al. 2001;Kelmenson et al. 2005;Myers et al. 2005;Mancera et al. 2008). The dense map of single nucleotide polymorphisms (SNPs) created by the HapMap Project enabled the highresolution mapping of recombination rates in the human genome and led to the identification of 33,000 recombination hotspots with a coalescent method . The very large number of hotspots and the very high resolution of this mapping made it possible to pinpoint sequence motifs in these hotspots, one of which was instrumental in finding a gene, PRDM9, thought to be a critical component of the recombination mechanism (Baudat and de Massy 2007;Grey et al. 2009;Parvanov et al. 2009).Until recently, the primary strategy for analysis of recombination hotspots in mice has been to use pedigree analysis in strain crosses (Paigen et al. 2008;. The problem with this approach is the high cost of typing SNPs for sufficient numbers of cases in order to define recombination hotspots with power and precision. A different approach that relies on the binding of RAD51 and DMC1 proteins was recently used to map meiotic DNA double-strand breaks (DSBs) that initiate recombination (Smagulova et al. 2011). Recombination initiation sites were found to be associated with testis-specific trimethylation of lysine 4 on histone H3. ...

Autism spectrum disorders (ASD) are neurodevelopmental disorders with phenotypic and genetic heterogeneity. Recent studies have reported rare and de novo mutations in ASD, but the allelic architecture of ASD remains unclear. To assess the role of common and rare variations in ASD, we constructed a gene co-expression network based on a widespread survey of gene expression in the human brain. We identified modules associated with specific cell types and processes. By integrating known rare mutations and the results of an ASD genome-wide association study (GWAS), we identified two neuronal modules that are perturbed by both rare and common variations. These modules contain highly connected genes that are involved in synaptic and neuronal plasticity and that are expressed in areas associated with learning and memory and sensory perception. The enrichment of common risk variants was replicated in two additional samples which include both simplex and multiplex families. An analysis of the combined contribution of common variants in the neuronal modules revealed a polygenic component to the risk of ASD. The results of this study point toward contribution of minor and major perturbations in the two sub-networks of neuronal genes to ASD risk.

Selfish genetic elements spread in natural populations and have an important role in genome evolution. We discovered a selfish element causing embryonic lethality in crosses between wild strains of the nematode Caenorhabditis elegans. The element is made up of sup-35, a maternal-effect toxin that kills developing embryos, and pha-1, its zygotically expressed antidote. pha-1 has long been considered essential for pharynx development on the basis of its mutant phenotype, but this phenotype arises from a loss of suppression of sup-35 toxicity. Inactive copies of the sup-35/pha-1 element show high sequence divergence from active copies, and phylogenetic reconstruction suggests that they represent ancestral stages in the evolution of the element. Our results suggest that other essential genes identified by genetic screens may turn out to be components of selfish elements.