High-throughput sequencing technologies promise to transform the fields of genetics and comparative biology by delivering tens of thousands of genomes in the near future. Although it is feasible to ...construct de novo genome assemblies in a few months, there has been relatively little attention to what is lost by sole application of short sequence reads. We compared the recent de novo assemblies using the short oligonucleotide analysis package (SOAP), generated from the genomes of a Han Chinese individual and a Yoruban individual, to experimentally validated genomic features. We found that de novo assemblies were 16.2% shorter than the reference genome and that 420.2 megabase pairs of common repeats and 99.1% of validated duplicated sequences were missing from the genome. Consequently, over 2,377 coding exons were completely missing. We conclude that high-quality sequencing approaches must be considered in conjunction with high-throughput sequencing for comparative genomics analyses and studies of genome evolution.
We present a hierarchical genome-assembly process (HGAP) for high-quality de novo microbial genome assemblies using only a single, long-insert shotgun DNA library in conjunction with Single Molecule, ...Real-Time (SMRT) DNA sequencing. Our method uses the longest reads as seeds to recruit all other reads for construction of highly accurate preassembled reads through a directed acyclic graph-based consensus procedure, which we follow with assembly using off-the-shelf long-read assemblers. In contrast to hybrid approaches, HGAP does not require highly accurate raw reads for error correction. We demonstrate efficient genome assembly for several microorganisms using as few as three SMRT Cell zero-mode waveguide arrays of sequencing and for BACs using just one SMRT Cell. Long repeat regions can be successfully resolved with this workflow. We also describe a consensus algorithm that incorporates SMRT sequencing primary quality values to produce de novo genome sequence exceeding 99.999% accuracy.
Complete and accurate genome assemblies form the basis of most downstream genomic analyses and are of critical importance. Recent genome assembly projects have relied on a combination of noisy ...long-read sequencing and accurate short-read sequencing, with the former offering greater assembly continuity and the latter providing higher consensus accuracy. The recently introduced Pacific Biosciences (PacBio) HiFi sequencing technology bridges this divide by delivering long reads (>10 kbp) with high per-base accuracy (>99.9%). Here we present HiCanu, a modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering. We benchmark HiCanu with a focus on the recovery of haplotype diversity, major histocompatibility complex (MHC) variants, satellite DNAs, and segmental duplications. For diploid human genomes sequenced to 30× HiFi coverage, HiCanu achieved superior accuracy and allele recovery compared to the current state of the art. On the effectively haploid CHM13 human cell line, HiCanu achieved an NG50 contig size of 77 Mbp with a per-base consensus accuracy of 99.999% (QV50), surpassing recent assemblies of high-coverage, ultralong Oxford Nanopore Technologies (ONT) reads in terms of both accuracy and continuity. This HiCanu assembly correctly resolves 337 out of 341 validation BACs sampled from known segmental duplications and provides the first preliminary assemblies of nine complete human centromeric regions. Although gaps and errors still remain within the most challenging regions of the genome, these results represent a significant advance toward the complete assembly of human genomes.
Highlights • We describe insights into mutation rate from high-throughput genome sequencing of families. • A paternal bias and agebeffect in mutation has been quantified at the genome-wide level. • ...Copy number variants arise less frequently than do point mutations, but affect more bases. • Future research will yield insights into the mutation rate of other forms of variation.
Despite considerable genetic heterogeneity underlying neurodevelopmental diseases, there is compelling evidence that many disease genes will map to a much smaller number of biological subnetworks. We ...developed a computational method, termed MAGI (merging affected genes into integrated networks), that simultaneously integrates protein-protein interactions and RNA-seq expression profiles during brain development to discover "modules" enriched for de novo mutations in probands. We applied this method to recent exome sequencing of 1116 patients with autism and intellectual disability, discovering two distinct modules that differ in their properties and associated phenotypes. The first module consists of 80 genes associated with Wnt, Notch, SWI/SNF, and NCOR complexes and shows the highest expression early during embryonic development (8-16 post-conception weeks pcw). The second module consists of 24 genes associated with synaptic function, including long-term potentiation and calcium signaling with higher levels of postnatal expression. Patients with de novo mutations in these modules are more significantly intellectually impaired and carry more severe missense mutations when compared to probands with de novo mutations outside of these modules. We used our approach to define subsets of the network associated with higher functioning autism as well as greater severity with respect to IQ. Finally, we applied MAGI independently to epilepsy and schizophrenia exome sequencing cohorts and found significant overlap as well as expansion of these modules, suggesting a core set of integrated neurodevelopmental networks common to seemingly diverse human diseases.
The discovery of genetic variation and the assembly of genome sequences are both inextricably linked to advances in DNA-sequencing technology. Short-read massively parallel sequencing has ...revolutionized our ability to discover genetic variation but is insufficient to generate high-quality genome assemblies or resolve most structural variation. Full resolution of variation is only guaranteed by complete de novo assembly of a genome. Here, we review approaches to genome assembly, the nature of gaps or missing sequences, and biases in the assembly process. We describe the challenges of generating a complete de novo genome assembly using current technologies and the impact that being able to perfectly sequence the genome would have on understanding human disease and evolution. Finally, we summarize recent technological advances that improve both contiguity and accuracy and emphasize the importance of complete de novo assembly as opposed to read mapping as the primary means to understanding the full range of human genetic variation.
Advances in sequencing technology have significantly expanded our understanding of the genetics of autism and neurodevelopmental disorders (NDDs). Continued technological improvements and cost ...reductions have now shifted the focus to investigations into the functional noncoding portions of the genome. There is a patient trend toward an excess of de novo and potentially disruptive mutations among conserved noncoding sequences implicated in the regulation of genes. The signals become stronger when restricted to genes already implicated in NDDs, but de novo mutation in such elements is estimated to account for <5% of patients. Larger sample sizes, improved variant detection, functional testing, and better approaches to classify noncoding variation will be required to identify specific pathogenic variants underlying disease.
Recent sequencing advances have allowed whole-genome sequencing (WGS) of large numbers of individuals with autism.
WGS data are beginning to provide insight into the potential contribution of noncoding variants in neurodevelopmental disorders.
A trend has been observed for an excess of de novo variants in conserved noncoding regions among autism patients with no obvious genic cause.
The noncoding de novo mutation signature is stronger near genes already implicated in autism.
Increased sample size is necessary to further our understanding of these noncoding signals and to refine the picture of their action at the gene level.
Improved variant detection and functional classification of noncoding elements will increase our ability to detect pathogenic variants.
Ultimately, functional testing will be critical to understanding the effect of mutations on gene expression and their relevance to disease.
Advances in genome sequencing technologies have begun to revolutionize neurogenetics, allowing the full spectrum of genetic variation to be better understood in relation to disease. Exome sequencing ...of hundreds to thousands of samples from patients with autism spectrum disorder, intellectual disability, epilepsy and schizophrenia provides strong evidence of the importance of de novo and gene-disruptive events. There are now several hundred new candidate genes and targeted resequencing technologies that allow screening of dozens of genes in tens of thousands of individuals with high specificity and sensitivity. The decision of which genes to pursue depends on many factors, including recurrence, previous evidence of overlap with pathogenic copy number variants, the position of the mutation in the protein, the mutational burden among healthy individuals and membership of the candidate gene in disease-implicated protein networks. We discuss these emerging criteria for gene prioritization and the potential impact on the field of neuroscience.
Deciphering the genetic basis of human disease requires a comprehensive knowledge of genetic variants irrespective of their class or frequency. Although an impressive number of human genetic variants ...have been catalogued, a large fraction of the genetic difference that distinguishes two human genomes is still not understood at the base-pair level. This is because the emphasis has been on single-nucleotide variation as opposed to less tractable and more complex genetic variants, including indels and structural variants. The latter, we propose, will have a large impact on human phenotypes but require a more systematic assessment of genomes at deeper coverage and alternate sequencing and mapping technologies.
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