As high-throughput sequencing platforms produce longer and longer reads, sequences generated from short inserts, such as those obtained from fossil and degraded material, are increasingly expected to contain adapter sequences. Efficient adapter trimming algorithms are also needed to process the growing amount of data generated per sequencing run. We introduce AdapterRemoval v2, a major revision of AdapterRemoval v1, which introduces (i) striking improvements in throughput, through the use of single instruction, multiple data (SIMD; SSE1 and SSE2) instructions and multi-threading support, (ii) the ability to handle datasets containing reads or read-pairs with different adapters or adapter pairs, (iii) simultaneous demultiplexing and adapter trimming, (iv) the ability to reconstruct adapter sequences from paired-end reads for poorly documented data sets, and (v) native gzip and bzip2 support. We show that AdapterRemoval v2 compares favorably with existing tools, while offering superior throughput to most alternatives examined here, both for single and multi-threaded operations.

/pdf/adapterremoval-v2-rapid-adapter-trimming-identification-and-1ml1rcsk5u.pdf

AdapterRemoval v2: rapid adapter trimming, identification, and read merging.

Summary: GenomeScope is an open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads. These features are essential for studying genome evolution, and help to choose parameters for downstream analysis. We demonstrate its accuracy on 324 simulated and 16 real datasets with a wide range in genome sizes, heterozygosity levels, and error rates. Availability and Implementation: http://genomescope.org , https://github.com/schatzlab/genomescope.git. Contact: mschatz@jhu.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

/pdf/genomescope-fast-reference-free-genome-profiling-from-short-9ed9nwons6.pdf

GenomeScope: fast reference-free genome profiling from short reads

Wild relatives of crops are an important source of genetic diversity for agriculture, but their gene repertoire remains largely unexplored. We report the establishment and analysis of a pan-genome of Glycine soja, the wild relative of cultivated soybean Glycine max, by sequencing and de novo assembly of seven phylogenetically and geographically representative accessions. Intergenomic comparisons identified lineage-specific genes and genes with copy number variation or large-effect mutations, some of which show evidence of positive selection and may contribute to variation of agronomic traits such as biotic resistance, seed composition, flowering and maturity time, organ size and final biomass. Approximately 80% of the pan-genome was present in all seven accessions (core), whereas the rest was dispensable and exhibited greater variation than the core genome, perhaps reflecting a role in adaptation to diverse environments. This work will facilitate the harnessing of untapped genetic diversity from wild soybean for enhancement of elite cultivars.

/pdf/de-novo-assembly-of-soybean-wild-relatives-for-pan-genome-4b7icy5cd3.pdf

De novo assembly of soybean wild relatives for pan-genome analysis of diversity and agronomic traits

Autism Spectrum Disorder (ASD) demonstrates high heritability and familial clustering, yet the genetic causes remain only partially understood as a result of extensive clinical and genomic heterogeneity. Whole-genome sequencing (WGS) shows promise as a tool for identifying ASD risk genes as well as unreported mutations in known loci, but an assessment of its full utility in an ASD group has not been performed. We used WGS to examine 32 families with ASD to detect de novo or rare inherited genetic variants predicted to be deleterious (loss-of-function and damaging missense mutations). Among ASD probands, we identified deleterious de novo mutations in six of 32 (19%) families and X-linked or autosomal inherited alterations in ten of 32 (31%) families (some had combinations of mutations). The proportion of families identified with such putative mutations was larger than has been previously reported; this yield was in part due to the comprehensive and uniform coverage afforded by WGS. Deleterious variants were found in four unrecognized, nine known, and eight candidate ASD risk genes. Examples include CAPRIN1 and AFF2 (both linked to FMR1, which is involved in fragile X syndrome), VIP (involved in social-cognitive deficits), and other genes such as SCN2A and KCNQ2 (linked to epilepsy), NRXN1, and CHD7, which causes ASD-associated CHARGE syndrome. Taken together, these results suggest that WGS and thorough bioinformatic analyses for de novo and rare inherited mutations will improve the detection of genetic variants likely to be associated with ASD or its accompanying clinical symptoms.

https://www.cell.com/ajhg/pdf/S0002-9297(13)00281-4.pdf

Detection of Clinically Relevant Genetic Variants in Autism Spectrum Disorder by Whole-Genome Sequencing

Locusts are one of the world's most destructive agricultural pests and represent a useful model system in entomology. Here we present a draft 6.5 Gb genome sequence of Locusta migratoria, which is the largest animal genome sequenced so far. Our findings indicate that the large genome size of L. migratoria is likely to be because of transposable element proliferation combined with slow rates of loss for these elements. Methylome and transcriptome analyses reveal complex regulatory mechanisms involved in microtubule dynamic-mediated synapse plasticity during phase change. We find significant expansion of gene families associated with energy consumption and detoxification, consistent with long-distance flight capacity and phytophagy. We report hundreds of potential insecticide target genes, including cys-loop ligand-gated ion channels, G-protein-coupled receptors and lethal genes. The L. migratoria genome sequence offers new insights into the biology and sustainable management of this pest species, and will promote its wide use as a model system.

http://www.ipm.ioz.cas.cn/kydw/yjz/kangle/jqwz/201506/W020160323572986037339.pdf

The locust genome provides insight into swarm formation and long-distance flight

Background: With the fast development of next generation sequencing technologies, increasing numbers of genomes are being de novo sequenced and assembled. However, most are in fragmental and incomplete draft status, and thus it is often difficult to know the accurate genome size and repeat content. Furthermore, many genomes are highly repetitive or heterozygous, posing problems to current assemblers utilizing short reads. Therefore, it is necessary to develop efficient assembly-independent methods for accurate estimation of these genomic characteristics. Results: Here we present a framework for modeling the distribution of k-mer frequency from sequencing data and estimating the genomic characteristics such as genome size, repeat structure and heterozygous rate. By introducing novel techniques of k-mer individuals, float precision estimation, and proper treatment of sequencing error and coverage bias, the estimation accuracy of our method is significantly improved over existing methods. We also studied how the various genomic and sequencing characteristics affect the estimation accuracy using simulated sequencing data, and discussed the limitations on applying our method to real sequencing data. Conclusion: Based on this research, we show that the k-mer frequency analysis can be used as a general and assembly-independent method for estimating genomic characteristics, which can improve our understanding of a species genome, help design the sequencing strategy of genome projects, and guide the development of assembly algorithms. The programs developed in this research are written using C/C++, and freely accessible at Github URL (this https URL) or BGI ftp ( this ftp URL).

/pdf/estimation-of-genomic-characteristics-by-analyzing-k-mer-3itdhlxaoz.pdf

Estimation of genomic characteristics by analyzing k-mer frequency in de novo genome projects

Since the completion of the cucumber and panda genome projects using Illumina sequencing in 2009, the global scientific community has had to pay much more attention to this new cost-effective approach to generate the draft sequence of large genomes. To allow new users to more easily understand the assembly algorithms and the optimum software packages for their projects, we make a detailed comparison of the two major classes of assembly algorithms: overlap-layout-consensus and de-bruijn-graph, from how they match the Lander-Waterman model, to the required sequencing depth and reads length. We also discuss the computational efficiency of each class of algorithm, the influence of repeats and heterozygosity and points of note in the subsequent scaffold linkage and gap closure steps. We hope this review can help further promote the application of second-generation de novo sequencing, as well as aid the future development of assembly algorithms.

/pdf/comparison-of-the-two-major-classes-of-assembly-algorithms-3sq6lsd2ud.pdf

Comparison of the two major classes of assembly algorithms: overlap-layout-consensus and de-bruijn-graph.

M otivation: The next generation high-throughput sequencing technologies, especially from Illumina, have been widely used in re- sequencing and de novo assembly studies. However, there is no existing software that can simulate Illumina reads with real error and quality distributions and coverage bias yet, which is very useful in relevant software development and study designing of sequencing projects. Results: We provide a software package, pIRS (profile based Illumina pair-end Reads Simulator), which simulates Illumina reads with empirical Base-Calling and GC%-depth profiles trained from real re-sequencing data. The error and quality distributions as well as coverage bias patterns of simulated reads using pIRS fit the properties of real sequencing data better than existing simulators. In addition, pIRS also comes with a tool to simulate the heterozygous diploid genomes. Availability: pIRS is written in C++ and Perl, and is freely available at ftp://ftp.genomics.org.cn/pub/pIRS/ .

/pdf/pirs-profile-based-illumina-pair-end-reads-simulator-2syn6u68xe.pdf

pIRS: Profile-based Illumina pair-end reads simulator

Since the completion of the cucumber and panda genome projects using Illumina sequencing in 2009, the global scientific community has had to pay much more attention to this new cost-effective approach to generate the draft sequence of large genomes. To allow new users to more easily understand the assembly algorithms and the optimum software packages for their projects, we make a detailed comparison of the two major classes of assembly algorithms: overlap ^ layout^ consensus and de-bruijn-graph, from how they match the Lander^Waterman model, to the required sequencing depth and reads length. We also discuss the computational efficiency of each class of algorithm, the influence of repeats and heterozygosity and points of note in the subsequent scaffold linkage and gap closure steps. We hope this review can help further promote the application of second-generation de novo sequencing, as well as aid the future development of assembly algorithms.

Nan Li

Papers

Estimation of genomic characteristics by analyzing k-mer frequency in de novo genome projects

Comparison of the two major classes of assembly algorithms: overlap-layout-consensus and de-bruijn-graph.

pIRS: Profile-based Illumina pair-end reads simulator

Comparison of the two major classes of assembly algorithms: overlap^layout^consensus and