<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Brasó-Vives, Marina</style></author><author><style face="normal" font="default" size="100%">Povolotskaya, Inna S</style></author><author><style face="normal" font="default" size="100%">Hartasánchez, Diego A</style></author><author><style face="normal" font="default" size="100%">Farré, Xavier</style></author><author><style face="normal" font="default" size="100%">Fernandez-Callejo, Marcos</style></author><author><style face="normal" font="default" size="100%">Raveendran, Muthuswamy</style></author><author><style face="normal" font="default" size="100%">Harris, R Alan</style></author><author><style face="normal" font="default" size="100%">Rosene, Douglas L</style></author><author><style face="normal" font="default" size="100%">Lorente-Galdos, Belen</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author><author><style face="normal" font="default" size="100%">Marques-Bonet, Tomas</style></author><author><style face="normal" font="default" size="100%">Rogers, Jeffrey</style></author><author><style face="normal" font="default" size="100%">Juan, David</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Copy number variants and fixed duplications among 198 rhesus macaques (Macaca mulatta).</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Duplication</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Macaca mulatta</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Open Reading Frames</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Species Specificity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">e1008742</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The rhesus macaque is an abundant species of Old World monkeys and a valuable model organism for biomedical research due to its close phylogenetic relationship to humans. Copy number variation is one of the main sources of genomic diversity within and between species and a widely recognized cause of inter-individual differences in disease risk. However, copy number differences among rhesus macaques and between the human and macaque genomes, as well as the relevance of this diversity to research involving this nonhuman primate, remain understudied. Here we present a high-resolution map of sequence copy number for the rhesus macaque genome constructed from a dataset of 198 individuals. Our results show that about one-eighth of the rhesus macaque reference genome is composed of recently duplicated regions, either copy number variable regions or fixed duplications. Comparison with human genomic copy number maps based on previously published data shows that, despite overall similarities in the genome-wide distribution of these regions, there are specific differences at the chromosome level. Some of these create differences in the copy number profile between human disease genes and their rhesus macaque orthologs. Our results highlight the importance of addressing the number of copies of target genes in the design of experiments and cautions against human-centered assumptions in research conducted with model organisms. Overall, we present a genome-wide copy number map from a large sample of rhesus macaque individuals representing an important novel contribution concerning the evolution of copy number in primate genomes.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32392208?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Weissensteiner, Matthias H</style></author><author><style face="normal" font="default" size="100%">Bunikis, Ignas</style></author><author><style face="normal" font="default" size="100%">Catalán, Ana</style></author><author><style face="normal" font="default" size="100%">Francoijs, Kees-Jan</style></author><author><style face="normal" font="default" size="100%">Knief, Ulrich</style></author><author><style face="normal" font="default" size="100%">Heim, Wieland</style></author><author><style face="normal" font="default" size="100%">Peona, Valentina</style></author><author><style face="normal" font="default" size="100%">Pophaly, Saurabh D</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Suh, Alexander</style></author><author><style face="normal" font="default" size="100%">Warmuth, Vera M</style></author><author><style face="normal" font="default" size="100%">Wolf, Jochen B W</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Discovery and population genomics of structural variation in a songbird genus.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Inversion</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Deletion</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomic Structural Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Phylogeny</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Retroelements</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Songbirds</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">3403</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Structural variation (SV) constitutes an important type of genetic mutations providing the raw material for evolution. Here, we uncover the genome-wide spectrum of intra- and interspecific SV segregating in natural populations of seven songbird species in the genus Corvus. Combining short-read (N = 127) and long-read re-sequencing (N = 31), as well as optical mapping (N = 16), we apply both assembly- and read mapping approaches to detect SV and characterize a total of 220,452 insertions, deletions and inversions. We exploit sampling across wide phylogenetic timescales to validate SV genotypes and assess the contribution of SV to evolutionary processes in an avian model of incipient speciation. We reveal an evolutionary young (~530,000 years) cis-acting 2.25-kb LTR retrotransposon insertion reducing expression of the NDP gene with consequences for premating isolation. Our results attest to the wealth and evolutionary significance of SV segregating in natural populations and highlight the need for reliable SV genotyping.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32636372?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yuan, Yuan</style></author><author><style face="normal" font="default" size="100%">Xie, Shirley</style></author><author><style face="normal" font="default" size="100%">Darnell, Jennifer C</style></author><author><style face="normal" font="default" size="100%">Darnell, Andrew J</style></author><author><style face="normal" font="default" size="100%">Saito, Yuhki</style></author><author><style face="normal" font="default" size="100%">Phatnani, Hemali</style></author><author><style face="normal" font="default" size="100%">Murphy, Elisabeth A</style></author><author><style face="normal" font="default" size="100%">Zhang, Chaolin</style></author><author><style face="normal" font="default" size="100%">Maniatis, Tom</style></author><author><style face="normal" font="default" size="100%">Darnell, Robert B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cell type-specific CLIP reveals that NOVA regulates cytoskeleton interactions in motoneurons.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Biol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alternative Splicing</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Cercopithecus aethiops</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosomes, Artificial, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">COS Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Cross-Linking Reagents</style></keyword><keyword><style  face="normal" font="default" size="100%">Cytoskeleton</style></keyword><keyword><style  face="normal" font="default" size="100%">Dendrites</style></keyword><keyword><style  face="normal" font="default" size="100%">Exons</style></keyword><keyword><style  face="normal" font="default" size="100%">Immunoprecipitation</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipoylation</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice, Transgenic</style></keyword><keyword><style  face="normal" font="default" size="100%">Motor Neurons</style></keyword><keyword><style  face="normal" font="default" size="100%">Nerve Tissue Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">NIH 3T3 Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Pseudopodia</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Septins</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 08 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">117</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Alternative RNA processing plays an essential role in shaping cell identity and connectivity in the central nervous system. This is believed to involve differential regulation of RNA processing in various cell types. However, in vivo study of cell type-specific post-transcriptional regulation has been a challenge. Here, we describe a sensitive and stringent method combining genetics and CLIP (crosslinking and immunoprecipitation) to globally identify regulatory interactions between NOVA and RNA in the mouse spinal cord motoneurons.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We developed a means of undertaking motoneuron-specific CLIP to explore motoneuron-specific protein-RNA interactions relative to studies of the whole spinal cord in mouse. This allowed us to pinpoint differential RNA regulation specific to motoneurons, revealing a major role for NOVA in regulating cytoskeleton interactions in motoneurons. In particular, NOVA specifically promotes the palmitoylated isoform of the cytoskeleton protein Septin 8 in motoneurons, which enhances dendritic arborization.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Our study demonstrates that cell type-specific RNA regulation is important for fine tuning motoneuron physiology and highlights the value of defining RNA processing regulation at single cell type resolution.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/30111345?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stitziel, Nathan O</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Wang, Xiao</style></author><author><style face="normal" font="default" size="100%">Bierhals, Andrew J</style></author><author><style face="normal" font="default" size="100%">Vourakis, A Christina</style></author><author><style face="normal" font="default" size="100%">Sperry, Alexandra E</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Klarin, Derek</style></author><author><style face="normal" font="default" size="100%">Emdin, Connor A</style></author><author><style face="normal" font="default" size="100%">Zekavat, Seyedeh M</style></author><author><style face="normal" font="default" size="100%">Nomura, Akihiro</style></author><author><style face="normal" font="default" size="100%">Erdmann, Jeanette</style></author><author><style face="normal" font="default" size="100%">Schunkert, Heribert</style></author><author><style face="normal" font="default" size="100%">Samani, Nilesh J</style></author><author><style face="normal" font="default" size="100%">Kraus, William E</style></author><author><style face="normal" font="default" size="100%">Shah, Svati H</style></author><author><style face="normal" font="default" size="100%">Yu, Bing</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Rader, Daniel J</style></author><author><style face="normal" font="default" size="100%">Gupta, Namrata</style></author><author><style face="normal" font="default" size="100%">Frossard, Philippe M</style></author><author><style face="normal" font="default" size="100%">Rasheed, Asif</style></author><author><style face="normal" font="default" size="100%">Danesh, John</style></author><author><style face="normal" font="default" size="100%">Lander, Eric S</style></author><author><style face="normal" font="default" size="100%">Gabriel, Stacey</style></author><author><style face="normal" font="default" size="100%">Saleheen, Danish</style></author><author><style face="normal" font="default" size="100%">Musunuru, Kiran</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">PROMIS and Myocardial Infarction Genetics Consortium Investigators</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">ANGPTL3 Deficiency and Protection Against Coronary Artery Disease.</style></title><secondary-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiopoietin-Like Protein 3</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiopoietin-like Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiopoietins</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Atherosclerosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronary Artery Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice, Inbred C57BL</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice, Knockout</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Myocardial Infarction</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Apr 25</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">69</style></volume><pages><style face="normal" font="default" size="100%">2054-2063</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Familial combined hypolipidemia, a Mendelian condition characterized by substantial reductions in all 3 major lipid fractions, is caused by mutations that inactivate the gene angiopoietin-like 3 (ANGPTL3). Whether ANGPTL3 deficiency reduces risk of coronary artery disease (CAD) is unknown.&lt;/p&gt;&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;The study goal was to leverage 3 distinct lines of evidence-a family that included individuals with complete (compound heterozygote) ANGPTL3 deficiency, a population based-study of humans with partial (heterozygote) ANGPTL3 deficiency, and biomarker levels in patients with myocardial infarction (MI)-to test whether ANGPTL3 deficiency is associated with lower risk for CAD.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We assessed coronary atherosclerotic burden in 3 individuals with complete ANGPTL3 deficiency and 3 wild-type first-degree relatives using computed tomography angiography. In the population, ANGPTL3 loss-of-function (LOF) mutations were ascertained in up to 21,980 people with CAD and 158,200 control subjects. LOF mutations were defined as nonsense, frameshift, and splice-site variants, along with missense variants resulting in &lt;25% of wild-type ANGPTL3 activity in a mouse model. In a biomarker study, circulating ANGPTL3 concentration was measured in 1,493 people who presented with MI and 3,232 control subjects.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The 3 individuals with complete ANGPTL3 deficiency showed no evidence of coronary atherosclerotic plaque. ANGPTL3 gene sequencing demonstrated that approximately 1 in 309 people was a heterozygous carrier for an LOF mutation. Compared with those without mutation, heterozygous carriers of ANGPTL3 LOF mutations demonstrated a 17% reduction in circulating triglycerides and a 12% reduction in low-density lipoprotein cholesterol. Carrier status was associated with a 34% reduction in odds of CAD (odds ratio: 0.66; 95% confidence interval: 0.44 to 0.98; p = 0.04). Individuals in the lowest tertile of circulating ANGPTL3 concentrations, compared with the highest, had reduced odds of MI (adjusted odds ratio: 0.65; 95% confidence interval: 0.55 to 0.77; p &lt; 0.001).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;ANGPTL3 deficiency is associated with protection from CAD.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">16</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28385496?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hwang, Hun-Way</style></author><author><style face="normal" font="default" size="100%">Saito, Yuhki</style></author><author><style face="normal" font="default" size="100%">Park, Christopher Y</style></author><author><style face="normal" font="default" size="100%">Blachère, Nathalie E</style></author><author><style face="normal" font="default" size="100%">Tajima, Yoko</style></author><author><style face="normal" font="default" size="100%">Fak, John J</style></author><author><style face="normal" font="default" size="100%">Zucker-Scharff, Ilana</style></author><author><style face="normal" font="default" size="100%">Darnell, Robert B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">cTag-PAPERCLIP Reveals Alternative Polyadenylation Promotes Cell-Type Specific Protein Diversity and Shifts Araf Isoforms with Microglia Activation.</style></title><secondary-title><style face="normal" font="default" size="100%">Neuron</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Neuron</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Antigens, Neoplasm</style></keyword><keyword><style  face="normal" font="default" size="100%">Astrocytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain</style></keyword><keyword><style  face="normal" font="default" size="100%">Cells, Cultured</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Microglia</style></keyword><keyword><style  face="normal" font="default" size="100%">Nerve Tissue Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Neuro-Oncological Ventral Antigen</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurons</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Polyadenylation</style></keyword><keyword><style  face="normal" font="default" size="100%">Polypyrimidine Tract-Binding Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Isoforms</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Serine-Threonine Kinases</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA-Binding Proteins</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Sep 13</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">95</style></volume><pages><style face="normal" font="default" size="100%">1334-1349.e5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Alternative polyadenylation (APA) is increasingly recognized to regulate gene expression across different cell types, but obtaining APA maps from individual cell types typically requires prior purification, a stressful procedure that can itself alter cellular states. Here, we describe a new platform, cTag-PAPERCLIP, that generates APA profiles from single cell populations in intact tissues; cTag-PAPERCLIP requires no tissue dissociation and preserves transcripts in native states. Applying cTag-PAPERCLIP to profile four major cell types in the mouse brain revealed common APA preferences between excitatory and inhibitory neurons distinct from astrocytes and microglia, regulated in part by neuron-specific RNA-binding proteins NOVA2 and PTBP2. We further identified a role of APA in switching Araf protein isoforms during microglia activation, impacting production of downstream inflammatory cytokines. Our results demonstrate the broad applicability of cTag-PAPERCLIP and a previously undiscovered role of APA in contributing to protein diversity between different cell types and cellular states within the brain.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28910620?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lu, Hsiang-Chih</style></author><author><style face="normal" font="default" size="100%">Tan, Qiumin</style></author><author><style face="normal" font="default" size="100%">Rousseaux, Maxime W C</style></author><author><style face="normal" font="default" size="100%">Wang, Wei</style></author><author><style face="normal" font="default" size="100%">Kim, Ji-Yoen</style></author><author><style face="normal" font="default" size="100%">Richman, Ronald</style></author><author><style face="normal" font="default" size="100%">Wan, Ying-Wooi</style></author><author><style face="normal" font="default" size="100%">Yeh, Szu-Ying</style></author><author><style face="normal" font="default" size="100%">Patel, Jay M</style></author><author><style face="normal" font="default" size="100%">Liu, Xiuyun</style></author><author><style face="normal" font="default" size="100%">Lin, Tao</style></author><author><style face="normal" font="default" size="100%">Lee, Yoontae</style></author><author><style face="normal" font="default" size="100%">Fryer, John D</style></author><author><style face="normal" font="default" size="100%">Han, Jing</style></author><author><style face="normal" font="default" size="100%">Chahrour, Maria</style></author><author><style face="normal" font="default" size="100%">Finnell, Richard H</style></author><author><style face="normal" font="default" size="100%">Lei, Yunping</style></author><author><style face="normal" font="default" size="100%">Zurita-Jimenez, Maria E</style></author><author><style face="normal" font="default" size="100%">Ahimaz, Priyanka</style></author><author><style face="normal" font="default" size="100%">Anyane-Yeboa, Kwame</style></author><author><style face="normal" font="default" size="100%">Van Maldergem, Lionel</style></author><author><style face="normal" font="default" size="100%">Lehalle, Daphne</style></author><author><style face="normal" font="default" size="100%">Jean-Marcais, Nolwenn</style></author><author><style face="normal" font="default" size="100%">Mosca-Boidron, Anne-Laure</style></author><author><style face="normal" font="default" size="100%">Thevenon, Julien</style></author><author><style face="normal" font="default" size="100%">Cousin, Margot A</style></author><author><style face="normal" font="default" size="100%">Bro, Della E</style></author><author><style face="normal" font="default" size="100%">Lanpher, Brendan C</style></author><author><style face="normal" font="default" size="100%">Klee, Eric W</style></author><author><style face="normal" font="default" size="100%">Alexander, Nora</style></author><author><style face="normal" font="default" size="100%">Bainbridge, Matthew N</style></author><author><style face="normal" font="default" size="100%">Orr, Harry T</style></author><author><style face="normal" font="default" size="100%">Sillitoe, Roy V</style></author><author><style face="normal" font="default" size="100%">Ljungberg, M Cecilia</style></author><author><style face="normal" font="default" size="100%">Liu, Zhandong</style></author><author><style face="normal" font="default" size="100%">Schaaf, Christian P</style></author><author><style face="normal" font="default" size="100%">Zoghbi, Huda Y</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Disruption of the ATXN1-CIC complex causes a spectrum of neurobehavioral phenotypes in mice and humans.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Ataxin-1</style></keyword><keyword><style  face="normal" font="default" size="100%">Autism Spectrum Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Cerebellum</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Intellectual Disability</style></keyword><keyword><style  face="normal" font="default" size="100%">Interpersonal Relations</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Nerve Tissue Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurodegenerative Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Nuclear Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Repressor Proteins</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">527-536</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Gain-of-function mutations in some genes underlie neurodegenerative conditions, whereas loss-of-function mutations in the same genes have distinct phenotypes. This appears to be the case with the protein ataxin 1 (ATXN1), which forms a transcriptional repressor complex with capicua (CIC). Gain of function of the complex leads to neurodegeneration, but ATXN1-CIC is also essential for survival. We set out to understand the functions of the ATXN1-CIC complex in the developing forebrain and found that losing this complex results in hyperactivity, impaired learning and memory, and abnormal maturation and maintenance of upper-layer cortical neurons. We also found that CIC activity in the hypothalamus and medial amygdala modulates social interactions. Informed by these neurobehavioral features in mouse mutants, we identified five individuals with de novo heterozygous truncating mutations in CIC who share similar clinical features, including intellectual disability, attention deficit/hyperactivity disorder (ADHD), and autism spectrum disorder. Our study demonstrates that loss of ATXN1-CIC complexes causes a spectrum of neurobehavioral phenotypes.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28288114?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Huang, Yi-Fei</style></author><author><style face="normal" font="default" size="100%">Gulko, Brad</style></author><author><style face="normal" font="default" size="100%">Siepel, Adam</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Base Sequence</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Evolution, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Mammals</style></keyword><keyword><style  face="normal" font="default" size="100%">Metagenomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Primates</style></keyword><keyword><style  face="normal" font="default" size="100%">Vertebrates</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">618-624</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Many genetic variants that influence phenotypes of interest are located outside of protein-coding genes, yet existing methods for identifying such variants have poor predictive power. Here we introduce a new computational method, called LINSIGHT, that substantially improves the prediction of noncoding nucleotide sites at which mutations are likely to have deleterious fitness consequences, and which, therefore, are likely to be phenotypically important. LINSIGHT combines a generalized linear model for functional genomic data with a probabilistic model of molecular evolution. The method is fast and highly scalable, enabling it to exploit the 'big data' available in modern genomics. We show that LINSIGHT outperforms the best available methods in identifying human noncoding variants associated with inherited diseases. In addition, we apply LINSIGHT to an atlas of human enhancers and show that the fitness consequences at enhancers depend on cell type, tissue specificity, and constraints at associated promoters.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28288115?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetics of coronary artery disease: discovery, biology and clinical translation.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Rev Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Rev Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronary Artery Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Precision Medicine</style></keyword><keyword><style  face="normal" font="default" size="100%">Translational Research, Biomedical</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">331-344</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Coronary artery disease is the leading global cause of mortality. Long recognized to be heritable, recent advances have started to unravel the genetic architecture of the disease. Common variant association studies have linked approximately 60 genetic loci to coronary risk. Large-scale gene sequencing efforts and functional studies have facilitated a better understanding of causal risk factors, elucidated underlying biology and informed the development of new therapeutics. Moving forwards, genetic testing could enable precision medicine approaches by identifying subgroups of patients at increased risk of coronary artery disease or those with a specific driving pathophysiology in whom a therapeutic or preventive approach would be most useful.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28286336?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Turner, Tychele N</style></author><author><style face="normal" font="default" size="100%">Coe, Bradley P</style></author><author><style face="normal" font="default" size="100%">Dickel, Diane E</style></author><author><style face="normal" font="default" size="100%">Hoekzema, Kendra</style></author><author><style face="normal" font="default" size="100%">Nelson, Bradley J</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Kronenberg, Zev N</style></author><author><style face="normal" font="default" size="100%">Hormozdiari, Fereydoun</style></author><author><style face="normal" font="default" size="100%">Raja, Archana</style></author><author><style face="normal" font="default" size="100%">Pennacchio, Len A</style></author><author><style face="normal" font="default" size="100%">Darnell, Robert B</style></author><author><style face="normal" font="default" size="100%">Eichler, Evan E</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genomic Patterns of De Novo Mutation in Simplex Autism.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Autistic Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Mutational Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">INDEL Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Oct 19</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">171</style></volume><pages><style face="normal" font="default" size="100%">710-722.e12</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;To further our understanding of the genetic etiology of autism, we generated and analyzed genome sequence data from 516 idiopathic autism families (2,064 individuals). This resource includes &gt;59 million single-nucleotide variants (SNVs) and 9,212 private copy number variants (CNVs), of which 133,992 and 88 are de novo mutations (DNMs), respectively. We estimate a mutation rate of ∼1.5 × 10 SNVs per site per generation with a significantly higher mutation rate in repetitive DNA. Comparing probands and unaffected siblings, we observe several DNM trends. Probands carry more gene-disruptive CNVs and SNVs, resulting in severe missense mutations and mapping to predicted fetal brain promoters and embryonic stem cell enhancers. These differences become more pronounced for autism genes (p = 1.8 × 10, OR = 2.2). Patients are more likely to carry multiple coding and noncoding DNMs in different genes, which are enriched for expression in striatal neurons (p = 3 × 10), suggesting a path forward for genetically characterizing more complex cases of autism.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28965761?dopt=Abstract</style></custom1></record></records></xml>