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April 21, 2020

Antarctic blackfin icefish genome reveals adaptations to extreme environments.

Icefishes (suborder Notothenioidei; family Channichthyidae) are the only vertebrates that lack functional haemoglobin genes and red blood cells. Here, we report a high-quality genome assembly and linkage map for the Antarctic blackfin icefish Chaenocephalus aceratus, highlighting evolved genomic features for its unique physiology. Phylogenomic analysis revealed that Antarctic fish of the teleost suborder Notothenioidei, including icefishes, diverged from the stickleback lineage about 77 million years ago and subsequently evolved cold-adapted phenotypes as the Southern Ocean cooled to sub-zero temperatures. Our results show that genes involved in protection from ice damage, including genes encoding antifreeze glycoprotein and zona pellucida proteins, are highly expanded in the icefish genome. Furthermore, genes that encode enzymes that help to control cellular redox state, including members of the sod3 and nqo1 gene families, are expanded, probably as evolutionary adaptations to the relatively high concentration of oxygen dissolved in cold Antarctic waters. In contrast, some crucial regulators of circadian homeostasis (cry and per genes) are absent from the icefish genome, suggesting compromised control of biological rhythms in the polar light environment. The availability of the icefish genome sequence will accelerate our understanding of adaptation to extreme Antarctic environments.

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April 21, 2020

Efficiency of PacBio long read correction by 2nd generation Illumina sequencing.

Long sequencing reads offer unprecedented opportunities in analysis and reconstruction of complex genomic regions. However, the gain in sequence length is often traded for quality. Therefore, recently several approaches have been proposed (e.g. higher sequencing coverage, hybrid assembly or sequence correction) to enhance the quality of long sequencing reads. A simple and cost-effective approach includes use of the high quality 2nd generation sequencing data to improve the quality of long reads. We designed a dedicated testing procedure and selected universal programs for long read correction, which provide as the output sequences that can be used in further genomic and transcriptomic studies. Our results show that HALC is the best choice for correction of long PacBio reads, when both, read size and quality, are the main focus of the analysis. However, the tested tools show some unexpected behaviors, including read trimming and fragmentation.Copyright © 2017 Elsevier Inc. All rights reserved.

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April 21, 2020

The red bayberry genome and genetic basis of sex determination.

Morella rubra, red bayberry, is an economically important fruit tree in south China. Here, we assembled the first high-quality genome for both a female and a male individual of red bayberry. The genome size was 313-Mb, and 90% sequences were assembled into eight pseudo chromosome molecules, with 32 493 predicted genes. By whole-genome comparison between the female and male and association analysis with sequences of bulked and individual DNA samples from female and male, a 59-Kb region determining female was identified and located on distal end of pseudochromosome 8, which contains abundant transposable element and seven putative genes, four of them are related to sex floral development. This 59-Kb female-specific region was likely to be derived from duplication and rearrangement of paralogous genes and retained non-recombinant in the female-specific region. Sex-specific molecular markers developed from candidate genes co-segregated with sex in a genetically diverse female and male germplasm. We propose sex determination follow the ZW model of female heterogamety. The genome sequence of red bayberry provides a valuable resource for plant sex chromosome evolution and also provides important insights for molecular biology, genetics and modern breeding in Myricaceae family. © 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

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April 21, 2020

Discovery of tandem and interspersed segmental duplications using high-throughput sequencing.

Several algorithms have been developed that use high-throughput sequencing technology to characterize structural variations (SVs). Most of the existing approaches focus on detecting relatively simple types of SVs such as insertions, deletions and short inversions. In fact, complex SVs are of crucial importance and several have been associated with genomic disorders. To better understand the contribution of complex SVs to human disease, we need new algorithms to accurately discover and genotype such variants. Additionally, due to similar sequencing signatures, inverted duplications or gene conversion events that include inverted segmental duplications are often characterized as simple inversions, likewise, duplications and gene conversions in direct orientation may be called as simple deletions. Therefore, there is still a need for accurate algorithms to fully characterize complex SVs and thus improve calling accuracy of more simple variants.We developed novel algorithms to accurately characterize tandem, direct and inverted interspersed segmental duplications using short read whole genome sequencing datasets. We integrated these methods to our TARDIS tool, which is now capable of detecting various types of SVs using multiple sequence signatures such as read pair, read depth and split read. We evaluated the prediction performance of our algorithms through several experiments using both simulated and real datasets. In the simulation experiments, using a 30× coverage TARDIS achieved 96% sensitivity with only 4% false discovery rate. For experiments that involve real data, we used two haploid genomes (CHM1 and CHM13) and one human genome (NA12878) from the Illumina Platinum Genomes set. Comparison of our results with orthogonal PacBio call sets from the same genomes revealed higher accuracy for TARDIS than state-of-the-art methods. Furthermore, we showed a surprisingly low false discovery rate of our approach for discovery of tandem, direct and inverted interspersed segmental duplications prediction on CHM1 (<5% for the top 50 predictions).TARDIS source code is available at https://github.com/BilkentCompGen/tardis, and a corresponding Docker image is available at https://hub.docker.com/r/alkanlab/tardis/.Supplementary data are available at Bioinformatics online. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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April 21, 2020

Genome assembly and gene expression in the American black bear provides new insights into the renal response to hibernation.

The prevalence of chronic kidney disease (CKD) is rising worldwide and 10-15% of the global population currently suffers from CKD and its complications. Given the increasing prevalence of CKD there is an urgent need to find novel treatment options. The American black bear (Ursus americanus) copes with months of lowered kidney function and metabolism during hibernation without the devastating effects on metabolism and other consequences observed in humans. In a biomimetic approach to better understand kidney adaptations and physiology in hibernating black bears, we established a high-quality genome assembly. Subsequent RNA-Seq analysis of kidneys comparing gene expression profiles in black bears entering (late fall) and emerging (early spring) from hibernation identified 169 protein-coding genes that were differentially expressed. Of these, 101 genes were downregulated and 68 genes were upregulated after hibernation. Fold changes ranged from 1.8-fold downregulation (RTN4RL2) to 2.4-fold upregulation (CISH). Most notable was the upregulation of cytokine suppression genes (SOCS2, CISH, and SERPINC1) and the lack of increased expression of cytokines and genes involved in inflammation. The identification of these differences in gene expression in the black bear kidney may provide new insights in the prevention and treatment of CKD. © The Author(s) 2018. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

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April 21, 2020

Genome-Scale Sequence Disruption Following Biolistic Transformation in Rice and Maize.

Biolistic transformation delivers nucleic acids into plant cells by bombarding the cells with microprojectiles, which are micron-scale, typically gold particles. Despite the wide use of this technique, little is known about its effect on the cell’s genome. We biolistically transformed linear 48-kb phage lambda and two different circular plasmids into rice (Oryza sativa) and maize (Zea mays) and analyzed the results by whole genome sequencing and optical mapping. Although some transgenic events showed simple insertions, others showed extreme genome damage in the form of chromosome truncations, large deletions, partial trisomy, and evidence of chromothripsis and breakage-fusion bridge cycling. Several transgenic events contained megabase-scale arrays of introduced DNA mixed with genomic fragments assembled by nonhomologous or microhomology-mediated joining. Damaged regions of the genome, assayed by the presence of small fragments displaced elsewhere, were often repaired without a trace, presumably by homology-dependent repair (HDR). The results suggest a model whereby successful biolistic transformation relies on a combination of end joining to insert foreign DNA and HDR to repair collateral damage caused by the microprojectiles. The differing levels of genome damage observed among transgenic events may reflect the stage of the cell cycle and the availability of templates for HDR. © 2019 American Society of Plant Biologists. All rights reserved.

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April 21, 2020

A 12-kb structural variation in progressive myoclonic epilepsy was newly identified by long-read whole-genome sequencing.

We report a family with progressive myoclonic epilepsy who underwent whole-exome sequencing but was negative for pathogenic variants. Similar clinical courses of a devastating neurodegenerative phenotype of two affected siblings were highly suggestive of a genetic etiology, which indicates that the survey of genetic variation by whole-exome sequencing was not comprehensive. To investigate the presence of a variant that remained unrecognized by standard genetic testing, PacBio long-read sequencing was performed. Structural variant (SV) detection using low-coverage (6×) whole-genome sequencing called 17,165 SVs (7,216 deletions and 9,949 insertions). Our SV selection narrowed down potential candidates to only five SVs (two deletions and three insertions) on the genes tagged with autosomal recessive phenotypes. Among them, a 12.4-kb deletion involving the CLN6 gene was the top candidate because its homozygous abnormalities cause neuronal ceroid lipofuscinosis. This deletion included the initiation codon and was found in a GC-rich region containing multiple repetitive elements. These results indicate the presence of a causal variant in a difficult-to-sequence region and suggest that such variants that remain enigmatic after the application of current whole-exome sequencing technology could be uncovered by unbiased application of long-read whole-genome sequencing.

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April 21, 2020

Fast and accurate genomic analyses using genome graphs.

The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, thus impairing analysis accuracy. Here we present a graph reference genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million insertions and deletions (indels). The pipeline processes one whole-genome sequencing sample in 6.5?h using a system with 36?CPU cores. We show that using a graph genome reference improves read mapping sensitivity and produces a 0.5% increase in variant calling recall, with unaffected specificity. Structural variations incorporated into a graph genome can be genotyped accurately under a unified framework. Finally, we show that iterative augmentation of graph genomes yields incremental gains in variant calling accuracy. Our implementation is an important advance toward fulfilling the promise of graph genomes to radically enhance the scalability and accuracy of genomic analyses.

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April 21, 2020

rMETL: sensitive mobile element insertion detection with long read realignment.

Mobile element insertion (MEI) is a major category of structure variations (SVs). The rapid development of long read sequencing technologies provides the opportunity to detect MEIs sensitively. However, the signals of MEI implied by noisy long reads are highly complex due to the repetitiveness of mobile elements as well as the high sequencing error rates. Herein, we propose the Realignment-based Mobile Element insertion detection Tool for Long read (rMETL). Benchmarking results of simulated and real datasets demonstrate that rMETL enables to handle the complex signals to discover MEIs sensitively. It is suited to produce high-quality MEI callsets in many genomics studies.rMETL is available from https://github.com/hitbc/rMETL.Supplementary data are available at Bioinformatics online. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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April 21, 2020

Full-length transcriptome analysis of Litopenaeus vannamei reveals transcript variants involved in the innate immune system.

To better understand the immune system of shrimp, this study combined PacBio isoform sequencing (Iso-Seq) and Illumina paired-end short reads sequencing methods to discover full-length immune-related molecules of the Pacific white shrimp, Litopenaeus vannamei. A total of 72,648 nonredundant full-length transcripts (unigenes) were generated with an average length of 2545 bp from five main tissues, including the hepatopancreas, cardiac stomach, heart, muscle, and pyloric stomach. These unigenes exhibited a high annotation rate (62,164, 85.57%) when compared against NR, NT, Swiss-Prot, Pfam, GO, KEGG and COG databases. A total of 7544 putative long noncoding RNAs (lncRNAs) were detected and 1164 nonredundant full-length transcripts (449 UniTransModels) participated in the alternative splicing (AS) events. Importantly, a total of 5279 nonredundant full-length unigenes were successfully identified, which were involved in the innate immune system, including 9 immune-related processes, 19 immune-related pathways and 10 other immune-related systems. We also found wide transcript variants, which increased the number and function complexity of immune molecules; for example, toll-like receptors (TLRs) and interferon regulatory factors (IRFs). The 480 differentially expressed genes (DEGs) were significantly higher or tissue-specific expression patterns in the hepatopancreas compared with that in other four tested tissues (FDR <0.05). Furthermore, the expression levels of six selected immune-related DEGs and putative IRFs were validated using real-time PCR technology, substantiating the reliability of the PacBio Iso-seq results. In conclusion, our results provide new genetic resources of long-read full-length transcripts data and information for identifying immune-related genes, which are an invaluable transcriptomic resource as genomic reference, especially for further exploration of the innate immune and defense mechanisms of shrimp. Copyright © 2019 Elsevier Ltd. All rights reserved.

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April 21, 2020

TranscriptClean: variant-aware correction of indels, mismatches and splice junctions in long-read transcripts.

Long-read, single-molecule sequencing platforms hold great potential for isoform discovery and characterization of multi-exon transcripts. However, their high error rates are an obstacle to distinguishing novel transcript isoforms from sequencing artifacts. Therefore, we developed the package TranscriptClean to correct mismatches, microindels and noncanonical splice junctions in mapped transcripts using the reference genome while preserving known variants.Our method corrects nearly all mismatches and indels present in a publically available human PacBio Iso-seq dataset, and rescues 39% of noncanonical splice junctions.All Python and R scripts used in this paper are available at https://github.com/dewyman/TranscriptClean.

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April 21, 2020

Genome Sequence of Jaltomata Addresses Rapid Reproductive Trait Evolution and Enhances Comparative Genomics in the Hyper-Diverse Solanaceae.

Within the economically important plant family Solanaceae, Jaltomata is a rapidly evolving genus that has extensive diversity in flower size and shape, as well as fruit and nectar color, among its ~80 species. Here, we report the whole-genome sequencing, assembly, and annotation, of one representative species (Jaltomata sinuosa) from this genus. Combining PacBio long reads (25×) and Illumina short reads (148×) achieved an assembly of ~1.45?Gb, spanning ~96% of the estimated genome. Ninety-six percent of curated single-copy orthologs in plants were detected in the assembly, supporting a high level of completeness of the genome. Similar to other Solanaceous species, repetitive elements made up a large fraction (~80%) of the genome, with the most recently active element, Gypsy, expanding across the genome in the last 1-2 Myr. Computational gene prediction, in conjunction with a merged transcriptome data set from 11 tissues, identified 34,725 protein-coding genes. Comparative phylogenetic analyses with six other sequenced Solanaceae species determined that Jaltomata is most likely sister to Solanum, although a large fraction of gene trees supported a conflicting bipartition consistent with substantial introgression between Jaltomata and Capsicum after these species split. We also identified gene family dynamics specific to Jaltomata, including expansion of gene families potentially involved in novel reproductive trait development, and loss of gene families that accompanied the loss of self-incompatibility. This high-quality genome will facilitate studies of phenotypic diversification in this rapidly radiating group and provide a new point of comparison for broader analyses of genomic evolution across the Solanaceae.

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April 21, 2020

Hybrid sequencing-based personal full-length transcriptomic analysis implicates proteostatic stress in metastatic ovarian cancer.

Comprehensive molecular characterization of myriad somatic alterations and aberrant gene expressions at personal level is key to precision cancer therapy, yet limited by current short-read sequencing technology, individualized catalog of complete genomic and transcriptomic features is thus far elusive. Here, we integrated second- and third-generation sequencing platforms to generate a multidimensional dataset on a patient affected by metastatic epithelial ovarian cancer. Whole-genome and hybrid transcriptome dissection captured global genetic and transcriptional variants at previously unparalleled resolution. Particularly, single-molecule mRNA sequencing identified a vast array of unannotated transcripts, novel long noncoding RNAs and gene chimeras, permitting accurate determination of transcription start, splice, polyadenylation and fusion sites. Phylogenetic and enrichment inference of isoform-level measurements implicated early functional divergence and cytosolic proteostatic stress in shaping ovarian tumorigenesis. A complementary imaging-based high-throughput drug screen was performed and subsequently validated, which consistently pinpointed proteasome inhibitors as an effective therapeutic regime by inducing protein aggregates in ovarian cancer cells. Therefore, our study suggests that clinical application of the emerging long-read full-length analysis for improving molecular diagnostics is feasible and informative. An in-depth understanding of the tumor transcriptome complexity allowed by leveraging the hybrid sequencing approach lays the basis to reveal novel and valid therapeutic vulnerabilities in advanced ovarian malignancies.

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April 21, 2020

MSC: a metagenomic sequence classification algorithm.

Metagenomics is the study of genetic materials directly sampled from natural habitats. It has the potential to reveal previously hidden diversity of microscopic life largely due to the existence of highly parallel and low-cost next-generation sequencing technology. Conventional approaches align metagenomic reads onto known reference genomes to identify microbes in the sample. Since such a collection of reference genomes is very large, the approach often needs high-end computing machines with large memory which is not often available to researchers. Alternative approaches follow an alignment-free methodology where the presence of a microbe is predicted using the information about the unique k-mers present in the microbial genomes. However, such approaches suffer from high false positives due to trading off the value of k with the computational resources. In this article, we propose a highly efficient metagenomic sequence classification (MSC) algorithm that is a hybrid of both approaches. Instead of aligning reads to the full genomes, MSC aligns reads onto a set of carefully chosen, shorter and highly discriminating model sequences built from the unique k-mers of each of the reference sequences.Microbiome researchers are generally interested in two objectives of a taxonomic classifier: (i) to detect prevalence, i.e. the taxa present in a sample, and (ii) to estimate their relative abundances. MSC is primarily designed to detect prevalence and experimental results show that MSC is indeed a more effective and efficient algorithm compared to the other state-of-the-art algorithms in terms of accuracy, memory and runtime. Moreover, MSC outputs an approximate estimate of the abundances.The implementations are freely available for non-commercial purposes. They can be downloaded from https://drive.google.com/open?id=1XirkAamkQ3ltWvI1W1igYQFusp9DHtVl. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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