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Cephalopods are known for their large nervous systems, complex behaviors and morphological innovations. To investigate the genomic underpinnings of these features, we assembled the chromosomes of the Boston market squid, Doryteuthis (Loligo) pealeii, and the California two-spot octopus, Octopus bimaculoides, and compared them with those of the Hawaiian bobtail squid, Euprymna scolopes. The genomes of the soft-bodied (coleoid) cephalopods are highly rearranged relative to other extant molluscs, indicating an intense, early burst of genome restructuring. The coleoid genomes feature multi-megabase, tandem arrays of genes associated with brain development and cephalopod-specific innovations. We find that a known coleoid hallmark, extensive A-to-I mRNA editing, displays two fundamentally distinct patterns: one exclusive to the nervous system and concentrated in genic sequences, the other widespread and directed toward repetitive elements. We conclude that coleoid novelty is mediated in part by substantial genome reorganization, gene family expansion, and tissue-dependent mRNA editing.

International audience; Abstract Background and Aims Modern sugarcane cultivars (Saccharum spp.) are high polyploids, aneuploids (2n = ~12x = ~120) derived from interspecific hybridizations between the domesticated sweet species Saccharum officinarum and the wild species S. spontaneum. Methods To analyse the architecture and origin of such a complex genome, we analysed the sequences of all 12 hom(oe)ologous haplotypes (BAC clones) from two distinct genomic regions of a typical modern cultivar, as well as the corresponding sequence in Miscanthus sinense and Sorghum bicolor, and monitored their distribution among representatives of the Saccharum genus. Key Results The diversity observed among haplotypes suggested the existence of three founding genomes (A, B, C) in modern cultivars, which diverged between 0.8 and 1.3 Mya. Two genomes (A, B) were contributed by S. officinarum; these were also found in its wild presumed ancestor S. robustum, and one genome (C) was contributed by S. spontaneum. These results suggest that S. officinarum and S. robustum are derived from interspecific hybridization between two unknown ancestors (A and B genomes). The A genome contributed most haplotypes (nine or ten) while the B and C genomes contributed one or two haplotypes in the regions analysed of this typical modern cultivar. Interspecific hybridizations likely involved accessions or gametes with distinct ploidy levels and/or were followed by a series of backcrosses with the A genome. The three founding genomes were found in all S. barberi, S. sinense and modern cultivars analysed. None of the analysed accessions contained only the A genome or the B genome, suggesting that representatives of these founding genomes remain to be discovered. Conclusions This evolutionary model, which combines interspecificity and high polyploidy, can explain the variable chromosome pairing affinity observed in Saccharum. It represents a major revision of the understanding of Saccharum diversity.

For many vertebrate species, vocalizations are essential components of social communication. Animals call in a variety of social contexts including courtship, mating, rivalry, and alarm signaling. In diverging populations, co-evolution of courtship signals and preferential responses to those signals can generate barriers to reproduction and lead to speciation. In the 29 species of the fully aquatic frog genus Xenopus, vocal signaling predominates in social interactions and is innate. Males produce an advertisement call in which the combination of spectral (pitch) and temporal (rhythm and pattern) features is a unique species identifier. To uncover genetic differences across species that support divergent advertisement calls, we performed quantitative trait locus (QTL) mapping using F2 hybrids between related species with different male advertisement calls: X. petersii and X. laevis. To phenotype each individual F2 male, we developed a pipeline for automated analysis of spectral and temporal features. To genotype the F2 males, we first identified ~3.8 million candidate species-specific markers from whole genome sequences (>10x coverage) of 4 X. laevis and 2 X.petersii including the founders of the F2 intercross. We then whole genome sequenced the F2s at 0.01-0.03x coverage, and used a HMM-based imputation and pruning of the initial candidate SNP set to obtain 533 informative genome-wide markers for QTL analysis. Our preliminary results identify QTLs on chromosomes 3, 5, 8, and 9 for vocal spectral features. Determining how variations in spectral features affect female preference will help to elucidate the genetic basis and evolution of courtship-based vocal signaling in Xenopus and more broadly, provide further insight to how vocal communication has evolved across vertebrates.

Genetic diseases of blood cells are prime candidates for treatment through ex vivo gene editing of CD34+ hematopoietic stem/progenitor cells (HSPCs), and a variety of technologies have been proposed to treat these disorders. Sickle cell disease (SCD) is a recessive genetic disorder caused by a single-nucleotide polymorphism in the β-globin gene (HBB). Sickle hemoglobin damages erythrocytes, causing vasoocclusion, severe pain, progressive organ damage, and premature death. We optimize design and delivery parameters of a ribonucleoprotein (RNP) complex comprising Cas9 protein and unmodified single guide RNA, together with a single-stranded DNA oligonucleotide donor (ssODN), to enable efficient replacement of the SCD mutation in human HSPCs. Corrected HSPCs from SCD patients produced less sickle hemoglobin RNA and protein and correspondingly increased wild-type hemoglobin when differentiated into erythroblasts. When engrafted into immunocompromised mice, ex vivo treated human HSPCs maintain SCD gene edits throughout 16 weeks at a level likely to have clinical benefit. These results demonstrate that an accessible approach combining Cas9 RNP with an ssODN can mediate efficient HSPC genome editing, enables investigator-led exploration of gene editing reagents in primary hematopoietic stem cells, and suggests a path toward the development of new gene editing treatments for SCD and other hematopoietic diseases.

Principal investigators John P. Vogel1, David F. Garvin2, Todd C. Mockler3, Jeremy Schmutz4, Dan Rokhsar5,6, Michael W. Bevan7; DNA sequencing and assembly Kerrie Barry5, Susan Lucas5, Miranda Harmon-Smith5, Kathleen Lail5, Hope Tice5, Jeremy Schmutz4 (Leader), Jane Grimwood4, Neil McKenzie7, Michael W. Bevan7; Pseudomolecule assembly and BACend sequencing Naxin Huo1, Yong Q.Gu1,Gerard R. Lazo1, Olin D.Anderson1, John P. Vogel1 (Leader), Frank M. You8,Ming-Cheng Luo8, Jan Dvorak8, Jonathan Wright7, Melanie Febrer7, Michael W. Bevan7, Dominika Idziak9, Robert Hasterok9, David F. Garvin2; Transcriptome sequencing and analysis Erika Lindquist5, Mei Wang5, Samuel E. Fox3, Henry D. Priest3, Sergei A. Filichkin3, Scott A. Givan3, Douglas W. Bryant3, Jeff H.Chang3, Todd C.Mockler3 (Leader), Haiyan Wu10,24, Wei Wu10, An-Ping Hsia10, Patrick S. Schnable10,24, Anantharaman Kalyanaraman11, Brad Barbazuk12, Todd P.Michael13, Samuel P.Hazen14, Jennifer N. Bragg1, Debbie Laudencia-Chingcuanco1, John P. Vogel1, David F. Garvin2, Yiqun Weng15, Neil McKenzie7, Michael W. Bevan7; Gene analysis and annotation Georg Haberer16, Manuel Spannagl16, Klaus Mayer16 (Leader), Thomas Rattei17, Therese Mitros6, Dan Rokhsar6, Sang-Jik Lee18, Jocelyn K.C. Rose18, Lukas A. Mueller19, Thomas L. York19; Repeats analysis Thomas Wicker20 (Leader), Jan P. Buchmann20, Jaakko Tanskanen21, Alan H. Schulman21 (Leader), Heidrun Gundlach16, Jonathan Wright7, Michael Bevan7, Antonio Costa de Oliveira22, Luciano da C. Maia22, William Belknap1, Yong Q. Gu1, Ning Jiang23, Jinsheng Lai24, Liucun Zhu25, JianxinMa25, Cheng Sun26, Ellen Pritham26; Comparative genomics Jerome Salse27 (Leader), Florent Murat27, Michael Abrouk27, Georg Haberer16, Manuel Spannagl16, Klaus Mayer16, Remy Bruggmann13, Joachim Messing13, Frank M. You8, Ming-Cheng Luo8, Jan Dvorak8; Small RNA analysis Noah Fahlgren3, Samuel E. Fox3, Christopher M. Sullivan3, Todd C. Mockler3, James C. Carrington3, Elisabeth J. Chapman3,28, Greg D.May29, Jixian Zhai30, Matthias Ganssmann30, Sai Guna Ranjan Gurazada30, Marcelo German30, Blake C. Meyers30, Pamela J. Green30 (Leader); Manual annotation and gene family analysis Jennifer N. Bragg1, Ludmila Tyler1,6, Jiajie Wu1,8, Yong Q. Gu1, Gerard R. Lazo1, Debbie Laudencia-Chingcuanco1, James Thomson1, John P. Vogel1 (Leader), Samuel P. Hazen14, Shan Chen14, Henrik V. Scheller31, Jesper Harholt32, Peter Ulvskov32, Samuel E. Fox3, Sergei A. Filichkin3, Noah Fahlgren3, Jeffrey A. Kimbrel3, Jeff H. Chang3, Christopher M. Sullivan3, Elisabeth J. Chapman3,27, James C. Carrington3, Todd C. Mockler3, Laura E. Bartley8,31, Peijian Cao8,31, Ki-Hong Jung8,31, Manoj K Sharma8,31, Miguel Vega-Sanchez8,31, Pamela Ronald8,31, Christopher D.Dardick33, Stefanie De Bodt34,Wim Verelst34, Dirk Inze34, Maren Heese35, Arp Schnittger35, Xiaohan Yang36, Udaya C. Kalluri36, Gerald A. Tuskan36, Zhihua Hua37, Richard D. Vierstra37, David F. Garvin3, Yu Cui24, Shuhong Ouyang24, Qixin Sun24, Zhiyong Liu24, Alper Yilmaz38, Erich Grotewold38, Richard Sibout39, Kian Hematy39, Gregory Mouille39, Herman Höfte39, Todd Michael13, Jérome Pelloux40, Devin O'Connor41, James Schnable41, Scott Rowe41, Frank Harmon41, Cynthia L. Cass42, John C. Sedbrook42, Mary E. Byrne7, Sean Walsh7, Janet Higgins7, Michael Bevan7, Pinghua Li19, Thomas Brutnell19, Turgay Unver43,Hikmet Budak43, Harry Belcram44, Mathieu Charles44, Boulos Chalhoub44, Ivan Baxter45 1 USDA-ARS Western Regional Research Center, Albany, California 94710, USA. 2 USDA-ARS Plant Science Research Unit and University of Minnesota, St Paul, Minnesota 55108, USA. 3 Oregon State University, Corvallis, Oregon 97331-4501, USA. 4 HudsonAlpha Institute, Huntsville, Alabama 35806, USA. 5 US DOE Joint Genome Institute, Walnut Creek, California 94598, USA. 6 University of California Berkeley, Berkeley, California 94720, USA. 7 John Innes Centre, Norwich NR4 7UJ, UK. 8 University of California Davis, Davis, California 95616, USA. 9 University of Silesia, 40-032 Katowice, Poland. 10 Iowa State University, Ames, Iowa 50011, USA. 11 Washington State University, Pullman, Washington 99163, USA. 12 University of Florida, Gainsville, Florida 32611, USA. 13 Rutgers University, Piscataway, New Jersey 08855-0759, USA. 14 University of Massachusetts, Amherst, Massachusetts 01003-9292, USA. 15 USDA-ARS Vegetable Crops Research Unit, Horticulture Department, University of Wisconsin, Madison, Wisconsin 53706, USA. 16 Helmholtz Zentrum München, D-85764 Neuherberg, Germany. 17 Technical University München, 80333 München, Germany. 18 Cornell University, Ithaca, New York 14853, USA. 19 Boyce Thompson Institute for Plant Research, Ithaca, New York 14853-1801, USA. 20 University of Zurich, 8008 Zurich, Switzerland. 21 MTT Agrifood Research and University of Helsinki, FIN-00014 Helsinki, Finland. 22 Federal University of Pelotas, Pelotas, 96001-970, RS, Brazil. 23 Michigan State University, East Lansing, Michigan 48824, USA. 24 China Agricultural University, Beijing 10094, China. 25 Purdue University, West Lafayette, Indiana 47907, USA. 26 The University of Texas, Arlington, Arlington, Texas 76019, USA. 27 Institut National de la Recherche Agronomique UMR 1095, 63100 Clermont-Ferrand, France. 28 University of California San Diego, La Jolla, California 92093, USA. 29 National Centre for Genome Resources, Santa Fe, New Mexico 87505, USA. 30 University of Delaware, Newark, Delaware 19716, USA. 31 Joint Bioenergy Institute, Emeryville, California 94720, USA. 32 University of Copenhagen, Frederiksberg DK-1871, Denmark. 33 USDA-ARS Appalachian Fruit Research Station, Kearneysville, West Virginia 25430, USA. 34 VIB Department of Plant Systems Biology, VIB and Department of Plant Biotechnology and Genetics, Ghent University, Technologiepark 927, 9052 Gent, Belgium. 35 Institut de Biologie Moléculaire des Plantes du CNRS, Strasbourg 67084, France. 36 BioEnergy Science Center and Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6422, USA. 37 University of Wisconsin-Madison, Madison, Wisconsin 53706, USA. 38 The Ohio State University, Columbus, Ohio 43210, USA. 39 Institut Jean-Pierre Bourgin, UMR1318, Institut National de la Recherche Agronomique, 78026 Versailles cedex, France. 40 Université de Picardie, Amiens 80039, France. 41 Plant Gene Expression Center, University of California Berkeley, Albany, California 94710, USA. 42 Illinois State University and DOE Great Lakes Bioenergy Research Center, Normal, Illinois 61790, USA. 43 Sabanci University, Istanbul 34956, Turkey. 44 Unité de Recherche en Génomique Végétale: URGV (INRA-CNRS-UEVE), Evry 91057, France. 45 USDA-ARS/Donald Danforth Plant Science Center, St Louis, Missouri 63130, USA.; Three subfamilies of grasses, the Ehrhartoideae, Panicoideae and Pooideae, provide the bulk of human nutrition and are poised to become major sources of renewable energy. Here we describe the genome sequence of the wild grass Brachypodium distachyon (Brachypodium), which is, to our knowledge, the first member of the Pooideae subfamily to be sequenced. Comparison of the Brachypodium, rice and sorghum genomes shows a precise history of genome evolution across a broad diversity of the grasses, and establishes a template for analysis of the large genomes of economically important pooid grasses such as wheat. The high-quality genome sequence, coupled with ease of cultivation and transformation, small size and rapid life cycle, will help Brachypodium reach its potential as an important model system for developing new energy and food crops.