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      First Draft Assembly and Annotation of the Genome of a California Endemic Oak Quercus lobata Née (Fagaceae)

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          Abstract

          Oak represents a valuable natural resource across Northern Hemisphere ecosystems, attracting a large research community studying its genetics, ecology, conservation, and management. Here we introduce a draft genome assembly of valley oak ( Quercus lobata) using Illumina sequencing of adult leaf tissue of a tree found in an accessible, well-studied, natural southern California population. Our assembly includes a nuclear genome and a complete chloroplast genome, along with annotation of encoded genes. The assembly contains 94,394 scaffolds, totaling 1.17 Gb with 18,512 scaffolds of length 2 kb or longer, with a total length of 1.15 Gb, and a N50 scaffold size of 278,077 kb. The k-mer histograms indicate an diploid genome size of ∼720–730 Mb, which is smaller than the total length due to high heterozygosity, estimated at 1.25%. A comparison with a recently published European oak ( Q. robur) nuclear sequence indicates 93% similarity. The Q. lobata chloroplast genome has 99% identity with another North American oak, Q. rubra. Preliminary annotation yielded an estimate of 61,773 predicted protein-coding genes, of which 71% had similarity to known protein domains. We searched 956 Benchmarking Universal Single-Copy Orthologs, and found 863 complete orthologs, of which 450 were present in > 1 copy. We also examined an earlier version (v0.5) where duplicate haplotypes were removed to discover variants. These additional sources indicate that the predicted gene count in Version 1.0 is overestimated by 37–52%. Nonetheless, this first draft valley oak genome assembly represents a high-quality, well-annotated genome that provides a tool for forest restoration and management practices.

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          Toward almost closed genomes with GapFiller

          De novo assembly is a commonly used application of next-generation sequencing experiments. The ultimate goal is to puzzle millions of reads into one complete genome, although draft assemblies usually result in a number of gapped scaffold sequences. In this paper we propose an automated strategy, called GapFiller, to reliably close gaps within scaffolds using paired reads. The method shows good results on both bacterial and eukaryotic datasets, allowing only few errors. As a consequence, the amount of additional wetlab work needed to close a genome is drastically reduced. The software is available at http://www.baseclear.com/bioinformatics-tools/.
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            Ab initio gene finding in Drosophila genomic DNA.

            Ab initio gene identification in the genomic sequence of Drosophila melanogaster was obtained using (human gene predictor) and Fgenesh programs that have organism-specific parameters for human, Drosophila, plants, yeast, and nematode. We did not use information about cDNA/EST in most predictions to model a real situation for finding new genes because information about complete cDNA is often absent or based on very small partial fragments. We investigated the accuracy of gene prediction on different levels and designed several schemes to predict an unambiguous set of genes (annotation CGG1), a set of reliable exons (annotation CGG2), and the most complete set of exons (annotation CGG3). For 49 genes, protein products of which have clear homologs in protein databases, predictions were recomputed by Fgenesh+ program. The first annotation serves as the optimal computational description of new sequence to be presented in a database. Reliable exons from the second annotation serve as good candidates for selecting the PCR primers for experimental work for gene structure verification. Our results shows that we can identify approximately 90% of coding nucleotides with 20% false positives. At the exon level we accurately predicted 65% of exons and 89% including overlapping exons with 49% false positives. Optimizing accuracy of prediction, we designed a gene identification scheme using Fgenesh, which provided sensitivity (Sn) = 98% and specificity (Sp) = 86% at the base level, Sn = 81% (97% including overlapping exons) and Sp = 58% at the exon level and Sn = 72% and Sp = 39% at the gene level (estimating sensitivity on std1 set and specificity on std3 set). In general, these results showed that computational gene prediction can be a reliable tool for annotating new genomic sequences, giving accurate information on 90% of coding sequences with 14% false positives. However, exact gene prediction (especially at the gene level) needs additional improvement using gene prediction algorithms. The program was also tested for predicting genes of human Chromosome 22 (the last variant of Fgenesh can analyze the whole chromosome sequence). This analysis has demonstrated that the 88% of manually annotated exons in Chromosome 22 were among the ab initio predicted exons. The suite of gene identification programs is available through the WWW server of Computational Genomics Group at http://genomic.sanger.ac.uk/gf. html.
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              The UCSC genome browser and associated tools

              The UCSC Genome Browser (http://genome.ucsc.edu) is a graphical viewer for genomic data now in its 13th year. Since the early days of the Human Genome Project, it has presented an integrated view of genomic data of many kinds. Now home to assemblies for 58 organisms, the Browser presents visualization of annotations mapped to genomic coordinates. The ability to juxtapose annotations of many types facilitates inquiry-driven data mining. Gene predictions, mRNA alignments, epigenomic data from the ENCODE project, conservation scores from vertebrate whole-genome alignments and variation data may be viewed at any scale from a single base to an entire chromosome. The Browser also includes many other widely used tools, including BLAT, which is useful for alignments from high-throughput sequencing experiments. Private data uploaded as Custom Tracks and Data Hubs in many formats may be displayed alongside the rich compendium of precomputed data in the UCSC database. The Table Browser is a full-featured graphical interface, which allows querying, filtering and intersection of data tables. The Saved Session feature allows users to store and share customized views, enhancing the utility of the system for organizing multiple trains of thought. Binary Alignment/Map (BAM), Variant Call Format and the Personal Genome Single Nucleotide Polymorphisms (SNPs) data formats are useful for visualizing a large sequencing experiment (whole-genome or whole-exome), where the differences between the data set and the reference assembly may be displayed graphically. Support for high-throughput sequencing extends to compact, indexed data formats, such as BAM, bigBed and bigWig, allowing rapid visualization of large datasets from RNA-seq and ChIP-seq experiments via local hosting.
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                Author and article information

                Journal
                G3 (Bethesda)
                Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                12 September 2016
                November 2016
                : 6
                : 11
                : 3485-3495
                Affiliations
                [* ]Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095
                []Institute of the Environment and Sustainability, University of California, Los Angeles, California 90095
                []Institute of Genomics and Proteomics, University of California, Los Angeles, California 90095
                [§ ]Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
                [** ]Department of Evolution and Ecology, University of California, Davis, California 95616
                [†† ]University of Maryland Center for Environmental Science, Appalachian Laboratory, Frostburg, Maryland 21532
                [‡‡ ]Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218
                [§§ ]Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, California 90095
                [*** ]Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218
                [††† ]Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland 21218
                Author notes
                [1 ]Corresponding author: Department of Ecology and Evolutionary Biology, University of California, Los Angeles, 4139 Terasaki Life Sciences Building, 610 Charles E. Young Drive East, Los Angeles, CA 90095-7239. E-mail: vlsork@ 123456ucla.edu
                Author information
                http://orcid.org/0000-0002-4464-8453
                http://orcid.org/0000-0002-8859-743
                Article
                GGG_030411
                10.1534/g3.116.030411
                5100847
                27621377
                70381479-d1a2-4830-99b5-b3b2f60845c6
                Copyright © 2016 Sork et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 April 2016
                : 21 August 2016
                Page count
                Figures: 5, Tables: 4, Equations: 0, References: 62, Pages: 11
                Categories
                Genomic Selection

                Genetics
                adaptation,annotation,chloroplast,nuclear genome assembly,quercus,genpred,shared data resources,genomic selection

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