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The introduction of third-generation DNA sequencing technologies in recent years has allowed scientists to generate dramatically longer sequence reads, which when used in whole-genome sequencing projects have yielded better repeat resolution and far more contiguous genome assemblies. While the promise of better contiguity has held true, the relatively high error rate of long reads, averaging 8-15%, has made it challenging to generate a highly accurate final sequence. Current long-read sequencing technologies display a tendency toward systematic errors, in particular in homopolymer regions, which present additional challenges. A cost-effective strategy to generate highly contiguous assemblies with a very low overall error rate is to combine long reads with low-cost short-read data, which currently have an error rate below 0.5%. This hybrid strategy can be pursued either by incorporating the short-read data into the early phase of assembly, during the read correction step, or by using short reads to \"polish\" the consensus built from long reads. In this report, we present the assembly polishing tool POLCA (POLishing by Calling Alternatives) and compare its performance with two other popular polishing programs, Pilon and Racon. We show that on simulated data POLCA is more accurate than Pilon, and comparable in accuracy to Racon. On real data, all three programs show similar performance, but POLCA is consistently much faster than either of the other polishing programs.

RNA sequencing using the latest single-molecule sequencing instruments produces reads that are thousands of nucleotides long. The ability to assemble these long reads can greatly improve the sensitivity of long-read analyses. Here we present StringTie2, a reference-guided transcriptome assembler that works with both short and long reads. StringTie2 includes new methods to handle the high error rate of long reads and offers the ability to work with full-length super-reads assembled from short reads, which further improves the quality of short-read assemblies. StringTie2 is more accurate and faster and uses less memory than all comparable short-read and long-read analysis tools.

Third-generation sequencing technologies can generate very long reads with relatively high error rates. The lengths of the reads, which sometimes exceed one million bases, make them invaluable for resolving complex repeats that cannot be assembled using shorter reads. Many high-quality genome assemblies have already been produced, curated, and annotated using the previous generation of sequencing data, and full re-assembly of these genomes with long reads is not always practical or cost-effective. One strategy to upgrade existing assemblies is to generate additional coverage using long-read data, and add that to the previously assembled contigs. SAMBA is a tool that is designed to scaffold and gap-fill existing genome assemblies with additional long-read data, resulting in substantially greater contiguity. SAMBA is the only tool of its kind that also computes and fills in the sequence for all spanned gaps in the scaffolds, yielding much longer contigs. Here we compare SAMBA to several similar tools capable of re-scaffolding assemblies using long-read data, and we show that SAMBA yields better contiguity and introduces fewer errors than competing methods. SAMBA is open-source software that is distributed at https://github.com/alekseyzimin/masurca .

Advances in long-read sequencing technologies have dramatically improved the contiguity and completeness of genome assemblies. Using the latest nanopore-based sequencers, we can generate enough data for the assembly of a human genome from a single flow cell. With the long-read data from these sequences, we can now routinely produce de novo genome assemblies in which half or more of a genome is contained in megabase-scale contigs. Assemblies produced from nanopore data alone, though, have relatively high error rates and can benefit from a process called polishing, in which more-accurate reads are used to correct errors in the consensus sequence. In this manuscript, we present a novel tool for genome polishing called JASPER (Jellyfish-based Assembly Sequence Polisher for Error Reduction). In contrast to many other polishing methods, JASPER gains efficiency by avoiding the alignment of reads to the assembly. Instead, JASPER uses a database of k-mer counts that it creates from the reads to detect and correct errors in the consensus. Our experiments demonstrate that JASPER is faster than alignment-based polishers, and both faster and more accurate than other k-mer based polishing methods. We also introduce the idea of using a polishing tool to create population-specific reference genomes, and illustrate this idea using sequence data from multiple individuals from Tokyo, Japan.

Abstract Bread wheat (Triticum aestivum) is a major food crop and an important plant system for agricultural genetics research. However, due to the complexity and size of its allohexaploid genome, genomic resources are limited compared to other major crops. The IWGSC recently published a reference genome and associated annotation (IWGSC CS v1.0, Chinese Spring) that has been widely adopted and utilized by the wheat community. Although this reference assembly represents all three wheat subgenomes at chromosome-scale, it was derived from short reads, and thus is missing a substantial portion of the expected 16 Gbp of genomic sequence. We earlier published an independent wheat assembly (Triticum_aestivum_3.1, Chinese Spring) that came much closer in length to the expected genome size, although it was only a contig-level assembly lacking gene annotations. Here, we describe a reference-guided effort to scaffold those contigs into chromosome-length pseudomolecules, add in any missing sequence that was unique to the IWGSC CS v1.0 assembly, and annotate the resulting pseudomolecules with genes. Our updated assembly, Triticum_aestivum_4.0, contains 15.07 Gbp of nongap sequence anchored to chromosomes, which is 1.2 Gbps more than the previous reference assembly. It includes 108,639 genes unambiguously localized to chromosomes, including over 2000 genes that were previously unplaced. We also discovered >5700 additional gene copies, facilitating the accurate annotation of functional gene duplications including at the Ppd-B1 photoperiod response locus.

The genus Quercus , which emerged ∼55 million years ago during globally warm temperatures, diversified into ∼450 extant species. We present a high-quality de novo genome assembly of a California endemic oak, Quercus lobata , revealing features consistent with oak evolutionary success. Effective population size remained large throughout history despite declining since early Miocene. Analysis of 39,373 mapped protein-coding genes outlined copious duplications consistent with genetic and phenotypic diversity, both by retention of genes created during the ancient γ whole genome hexaploid duplication event and by tandem duplication within families, including numerous resistance genes and a very large block of duplicated DUF247 genes, which have been found to be associated with self-incompatibility in grasses. An additional surprising finding is that subcontext-specific patterns of DNA methylation associated with transposable elements reveal broadly-distributed heterochromatin in intergenic regions, similar to grasses. Collectively, these features promote genetic and phenotypic variation that would facilitate adaptability to changing environments. The genus Quercus (oaks) has diversified into over 450 species which often play dominant roles in the ecosystems in which they occur. Here the authors present a genome and methylome for a California endemic oak, Quercus lobata , and describe features relevant to its evolutionary success.

Background Thousands of experiments and studies use the human reference genome as a resource each year. This single reference genome, GRCh38, is a mosaic created from a small number of individuals, representing a very small sample of the human population. There is a need for reference genomes from multiple human populations to avoid potential biases. Results Here, we describe the assembly and annotation of the genome of an Ashkenazi individual and the creation of a new, population-specific human reference genome. This genome is more contiguous and more complete than GRCh38, the latest version of the human reference genome, and is annotated with highly similar gene content. The Ashkenazi reference genome, Ash1, contains 2,973,118,650 nucleotides as compared to 2,937,639,212 in GRCh38. Annotation identified 20,157 protein-coding genes, of which 19,563 are > 99% identical to their counterparts on GRCh38. Most of the remaining genes have small differences. Forty of the protein-coding genes in GRCh38 are missing from Ash1; however, all of these genes are members of multi-gene families for which Ash1 contains other copies. Eleven genes appear on different chromosomes from their homologs in GRCh38. Alignment of DNA sequences from an unrelated Ashkenazi individual to Ash1 identified ~ 1 million fewer homozygous SNPs than alignment of those same sequences to the more-distant GRCh38 genome, illustrating one of the benefits of population-specific reference genomes. Conclusions The Ash1 genome is presented as a reference for any genetic studies involving Ashkenazi Jewish individuals.

The giant sequoia (Sequoiadendron giganteum) of California are massive, long-lived trees that grow along the U.S. Sierra Nevada mountains. Genomic data are limited in giant sequoia and producing a reference genome sequence has been an important goal to allow marker development for restoration and management. Using deep-coverage Illumina and Oxford Nanopore sequencing, combined with Dovetail chromosome conformation capture libraries, the genome was assembled into eleven chromosome-scale scaffolds containing 8.125 Gbp of sequence. Iso-Seq transcripts, assembled from three distinct tissues, was used as evidence to annotate a total of 41,632 protein-coding genes. The genome was found to contain, distributed unevenly across all 11 chromosomes and in 63 orthogroups, over 900 complete or partial predicted NLR genes, of which 375 are supported by annotation derived from protein evidence and gene modeling. This giant sequoia reference genome sequence represents the first genome sequenced in the Cupressaceae family, and lays a foundation for using genomic tools to aid in giant sequoia conservation and management.

Long-read sequencing facilitates assembly of complex genomic regions. In plants, loci containing nucleotide-binding, leucine-rich repeat (NLR) disease resistance genes are an important example of such regions. NLR genes constitute one of the largest gene families in plants and are often clustered, evolving via duplication, contraction, and transposition. We recently mapped the Xo1 locus for resistance to bacterial blight and bacterial leaf streak, found in the American heirloom rice variety Carolina Gold Select, to a region that in the Nipponbare reference genome is NLR gene-rich. Here, toward identification of the Xo1 gene, we combined Nanopore and Illumina reads and generated a high-quality Carolina Gold Select genome assembly. We identified 529 complete or partial NLR genes and discovered, relative to Nipponbare, an expansion of NLR genes at the Xo1 locus. One of these has high sequence similarity to the cloned, functionally similar Xa1 gene. Both harbor an integrated zfBED domain, and the repeats within each protein are nearly perfect. Across diverse Oryzeae, we identified two sub-clades of NLR genes with these features, varying in the presence of the zfBED domain and the number of repeats. The Carolina Gold Select genome assembly also uncovered at the Xo1 locus a rice blast resistance gene and a gene encoding a polyphenol oxidase (PPO). PPO activity has been used as a marker for blast resistance at the locus in some varieties; however, the Carolina Gold Select sequence revealed a loss-of-function mutation in the PPO gene that breaks this association. Our results demonstrate that whole genome sequencing combining Nanopore and Illumina reads effectively resolves NLR gene loci. Our identification of an Xo1 candidate is an important step toward mechanistic characterization, including the role(s) of the zfBED domain. Finally, the Carolina Gold Select genome assembly will facilitate identification of other useful traits in this historically important variety.

Forward genetic screening is a powerful approach to assign functions to genes and can be used to elucidate the many genes whose functions remain unknown. A key step in forward genetic screening is mapping: identification of the gene causing the phenotype. Existing mapping methods use a bioinformatic mapping-by-sequencing approach based on allelic frequency calculations that often identify large genomic regions which contain an intractable number of candidate genes for testing. Here, we describe WheresWalker, a modern mapping-by-sequencing algorithm that identifies a mutation-containing interval and then supports positional cloning to shrink the interval, which drastically reduces the number of potential candidates, allowing for extremely rapid mutation identification. We validated this method using mutants from a forward genetic mutagenesis screen in zebrafish for modifiers of ApoB-lipoprotein metabolism. WheresWalker correctly mapped and identified novel zebrafish mutations in mttp , apobb.1 , and mia2 genes, as well as a previously published mutation in maize. Further, we used WheresWalker to identify a previously unappreciated ApoB-lipoprotein metabolism-modifying locus, slc3a2a .