April 21, 2020  |  

Chromosome-length haplotigs for yak and cattle from trio binning assembly of an F1 hybrid

Background Assemblies of diploid genomes are generally unphased, pseudo-haploid representations that do not correctly reconstruct the two parental haplotypes present in the individual sequenced. Instead, the assembly alternates between parental haplotypes and may contain duplications in regions where the parental haplotypes are sufficiently different. Trio binning is an approach to genome assembly that uses short reads from both parents to classify long reads from the offspring according to maternal or paternal haplotype origin, and is thus helped rather than impeded by heterozygosity. Using this approach, it is possible to derive two assemblies from an individual, accurately representing both parental contributions in their entirety with higher continuity and accuracy than is possible with other methods.Results We used trio binning to assemble reference genomes for two species from a single individual using an interspecies cross of yak (Bos grunniens) and cattle (Bos taurus). The high heterozygosity inherent to interspecies hybrids allowed us to confidently assign >99% of long reads from the F1 offspring to parental bins using unique k-mers from parental short reads. Both the maternal (yak) and paternal (cattle) assemblies contain over one third of the acrocentric chromosomes, including the two largest chromosomes, in single haplotigs.Conclusions These haplotigs are the first vertebrate chromosome arms to be assembled gap-free and fully phased, and the first time assemblies for two species have been created from a single individual. Both assemblies are the most continuous currently available for non-model vertebrates.MbmegabaseskbkilobasesMYAmillions of years agoMHCmajor histocompatibility complexSMRTsingle molecule real time

April 21, 2020  |  

Featherweight long read alignment using partitioned reference indexes.

The advent of Nanopore sequencing has realised portable genomic research and applications. However, state of the art long read aligners and large reference genomes are not compatible with most mobile computing devices due to their high memory requirements. We show how memory requirements can be reduced through parameter optimisation and reference genome partitioning, but highlight the associated limitations and caveats of these approaches. We then demonstrate how these issues can be overcome through an appropriate merging technique. We incorporated multi-index merging into the Minimap2 aligner and demonstrate that long read alignment to the human genome can be performed on a system with 2?GB RAM with negligible impact on accuracy.

April 21, 2020  |  

Long-read assembly of the Chinese rhesus macaque genome and identification of ape-specific structural variants.

We present a high-quality de novo genome assembly (rheMacS) of the Chinese rhesus macaque (Macaca mulatta) using long-read sequencing and multiplatform scaffolding approaches. Compared to the current Indian rhesus macaque reference genome (rheMac8), rheMacS increases sequence contiguity 75-fold, closing 21,940 of the remaining assembly gaps (60.8 Mbp). We improve gene annotation by generating more than two million full-length transcripts from ten different tissues by long-read RNA sequencing. We sequence resolve 53,916 structural variants (96% novel) and identify 17,000 ape-specific structural variants (ASSVs) based on comparison to ape genomes. Many ASSVs map within ChIP-seq predicted enhancer regions where apes and macaque show diverged enhancer activity and gene expression. We further characterize a subset that may contribute to ape- or great-ape-specific phenotypic traits, including taillessness, brain volume expansion, improved manual dexterity, and large body size. The rheMacS genome assembly serves as an ideal reference for future biomedical and evolutionary studies.

April 21, 2020  |  

Genome-wide mutational biases fuel transcriptional diversity in the Mycobacterium tuberculosis complex.

The Mycobacterium tuberculosis complex (MTBC) members display different host-specificities and virulence phenotypes. Here, we have performed a comprehensive RNAseq and methylome analysis of the main clades of the MTBC and discovered unique transcriptional profiles. The majority of genes differentially expressed between the clades encode proteins involved in host interaction and metabolic functions. A significant fraction of changes in gene expression can be explained by positive selection on single mutations that either create or disrupt transcriptional start sites (TSS). Furthermore, we show that clinical strains have different methyltransferases inactivated and thus different methylation patterns. Under the tested conditions, differential methylation has a minor direct role on transcriptomic differences between strains. However, disruption of a methyltransferase in one clinical strain revealed important expression differences suggesting indirect mechanisms of expression regulation. Our study demonstrates that variation in transcriptional profiles are mainly due to TSS mutations and have likely evolved due to differences in host characteristics.

April 21, 2020  |  

Strain-level metagenomic assignment and compositional estimation for long reads with MetaMaps.

Metagenomic sequence classification should be fast, accurate and information-rich. Emerging long-read sequencing technologies promise to improve the balance between these factors but most existing methods were designed for short reads. MetaMaps is a new method, specifically developed for long reads, capable of mapping a long-read metagenome to a comprehensive RefSeq database with >12,000 genomes in <16?GB or RAM on a laptop computer. Integrating approximate mapping with probabilistic scoring and EM-based estimation of sample composition, MetaMaps achieves >94% accuracy for species-level read assignment and r2?>?0.97 for the estimation of sample composition on both simulated and real data when the sample genomes or close relatives are present in the classification database. To address novel species and genera, which are comparatively harder to predict, MetaMaps outputs mapping locations and qualities for all classified reads, enabling functional studies (e.g. gene presence/absence) and detection of incongruities between sample and reference genomes.

April 21, 2020  |  

IMOS: improved Meta-aligner and Minimap2 On Spark.

Long reads provide valuable information regarding the sequence composition of genomes. Long reads are usually very noisy which renders their alignments on the reference genome a daunting task. It may take days to process datasets enough to sequence a human genome on a single node. Hence, it is of primary importance to have an aligner which can operate on distributed clusters of computers with high performance in accuracy and speed.In this paper, we presented IMOS, an aligner for mapping noisy long reads to the reference genome. It can be used on a single node as well as on distributed nodes. In its single-node mode, IMOS is an Improved version of Meta-aligner (IM) enhancing both its accuracy and speed. IM is up to 6x faster than the original Meta-aligner. It is also implemented to run IM and Minimap2 on Apache Spark for deploying on a cluster of nodes. Moreover, multi-node IMOS is faster than SparkBWA while executing both IM (1.5x) and Minimap2 (25x).In this paper, we purposed an architecture for mapping long reads to a reference. Due to its implementation, IMOS speed can increase almost linearly with respect to the number of nodes in a cluster. Also, it is a multi-platform application able to operate on Linux, Windows, and macOS.

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