Incomplete Reference Genome Research Articles

The Need for Speed and Energy Efficiency in Genome Analysis

The Need for Speed and Energy Efficiency in Genome Analysis

Genome enrichment of rare and unknown species from complicated microbiome by nanopore selective sequencing.

Rare species are vital members of a microbial community, but retrieving their genomes is difficult due to their low abundance. The ReadUntil (RU) approach allows nanopore devices to sequence specific DNA molecules selectively in real-time, which provides an opportunity for enriching rare species. Despite the robustness of enriching rare species by reducing the sequencing depth of known host sequences, such as the human genome, there is still a gap in RU-based enriching of rare species in environmental samples whose community composition is unclear, and many rare species have poor or incomplete reference genomes in public databases. Therefore, here we present metaRUpore to overcome this challenge. We applied metaRUpore to a thermophilic anaerobic digester (TAD) community and human gut microbial community, it reduced coverage of the high-abundance populations and modestly increased (~2×) the genome coverage of the rare taxa, facilitating successful recovery of near-finished metagenome-assembled genomes (nf-MAGs) of rare species. The simplicity and robustness of the approach make it accessible for labs with moderate computational resources and hold the potential to become the standard practice in future metagenomic sequencing of complicated microbiomes.

Full-Length Transcriptome of the Great Himalayan Leaf-Nosed Bats (Hipposideros armiger) Optimized Genome Annotation and Revealed the Expression of Novel Genes.

The Great Himalayan Leaf-nosed bat (Hipposideros armiger) is one of the most representative species of all echolocating bats and is an ideal model for studying the echolocation system of bats. An incomplete reference genome and limited availability of full-length cDNAs have hindered the identification of alternatively spliced transcripts, which slowed down related basic studies on bats' echolocation and evolution. In this study, we analyzed five organs from H. armiger for the first time using PacBio single-molecule real-time sequencing (SMRT). There were 120 GB of subreads generated, including 1,472,058 full-length non-chimeric (FLNC) sequences. A total of 34,611 alternative splicing (AS) events and 66,010 Alternative Polyadenylation (APA) sites were detected by transcriptome structural analysis. Moreover, a total of 110,611 isoforms were identified, consisting of 52% new isoforms of known genes and 5% of novel gene loci, as well as 2112 novel genes that have not been annotated before in the current reference genome of H. armiger. Furthermore, several key novel genes, including Pol, RAS, NFKB1, and CAMK4, were identified as being associated with nervous, signal transduction, and immune system processes, which may be involved in regulating the auditory nervous perception and immune system that helps bats to regulate in echolocation. In conclusion, the full-length transcriptome results optimized and replenished existing H. armiger genome annotation in multiple ways and offer advantages for newly discovered or previously unrecognized protein-coding genes and isoforms, which can be used as a reference resource.

A Molecular Cloning and Sanger Sequencing-based Protocol for Detecting Site-specific DNA Methylation.

DNA methylation is a conserved chemical modification, by which methyl groups are added to the cytosine of DNA molecules. Methylation can influence gene expression without changing the sequence of a particular gene. This epigenetic effect is an intriguing phenomenon that has puzzled biologists for years. By probing the temporal and spatial patterns of DNA methylation in genomes, it is possible to learn about the biological role of cytosine methylation, as well as its involvement in gene regulation and transposon silencing. Advances in whole-genome sequencing have led to the widespread adoption of methods that examine genome-wide patterns of DNA methylation. Achieving sufficient sequencing depth in these types of experiments is costly, particularly for pilot studies in organisms with large genome sizes, or incomplete reference genomes. To overcome this issue, assays to determine site-specific DNA methylation can be used. Although often used, these assays are rarely described in detail. Here, we describe a pipeline that applies traditional TA cloning, Sanger sequencing, and online tools to examine DNA methylation. We provide an example of how to use this protocol to examine the pattern of DNA methylation at a specific transposable element in maize.

Efficient association mapping from k-mers—An application in finding sex-specific sequences

Genome wide association studies (GWAS) attempt to map genotypes to phenotypes in organisms. This is typically performed by genotyping individuals using microarray or by aligning whole genome sequencing reads to a reference genome. Both approaches require knowledge of a reference genome which hinders their application to organisms with no or incomplete reference genomes. This caveat can be removed by using alignment-free association mapping methods based on k-mers from sequencing reads. Here we present an improved implementation of an alignment free association mapping method. The new implementation is faster and includes additional features to make it more flexible than the original implementation. We have tested our implementation on an E. Coli ampicillin resistance dataset and observe improvement in execution time over the original implementation while maintaining accuracy in results. We also demonstrate that the method can be applied to find sex specific sequences.

Reference-free Association Mapping from Sequencing Reads Using k-mers.

Association mapping is the process of linking phenotypes with genotypes. In genome wide association studies (GWAS), individuals are first genotyped using microarrays or by aligning sequenced reads to reference genomes. However, both these approaches rely on reference genomes which limits their application to organisms with no or incomplete reference genomes. To address this, reference free association mapping methods have been developed. Here we present the protocol of an alignment free method for association studies which is based on counting k-mers in sequenced reads, testing for associations between k-mers and the phenotype of interest, and local assembly of the k-mers of statistical significance. The method can map associations of categorical phenotypes to sequence and structural variations without requiring prior sequencing of reference genomes.

On the critical evaluation and confirmation of germline sequence variants identified using massively parallel sequencing

Although massively parallel sequencing (MPS) is becoming common practice in both research and routine clinical care, confirmation requirements of identified DNA variants using alternative methods are still topics of debate. When evaluating variants directly from MPS data, different read depth statistics, together with specialized genotype quality scores are, therefore, of high relevance. Here we report results of our validation study performed in two different ways: 1) confirmation of MPS identified variants using Sanger sequencing; and 2) simultaneous Sanger and MPS analysis of exons of selected genes. Detailed examination of false-positive and false-negative findings revealed typical error sources connected to low read depth/coverage, incomplete reference genome, indel realignment problems, as well as microsatellite associated amplification errors leading to base miss-calling. However, all these error types were identifiable with thorough manual revision of aligned reads according to specific patterns of distributions of variants and their corresponding reads. Moreover, our results point to dependence of both basic quantitative metrics (such as total read counts, alternative allele read counts and allelic balance) together with specific genotype quality scores on the used bioinformatics pipeline, stressing thus the need for establishing of specific thresholds for these metrics in each laboratory and for each involved pipeline independently.

Blacklisting variants common in private cohorts but not in public databases optimizes human exome analysis

Computational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants (NPVs) as possible, without removing the true disease-causing mutations. This involves comparing the patient's exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance. However, variants frequent in a given exome cohort, but absent or rare in public databases, have also been reported and treated as NPVs, without rigorous exploration. We report the generation of a blacklist of variants frequent within an in-house cohort of 3,104 exomes. This blacklist did not remove known pathogenic mutations from the exomes of 129 patients and decreased the number of NPVs remaining in the 3,104 individual exomes by a median of 62%. We validated this approach by testing three other independent cohorts of 400, 902, and 3,869 exomes. The blacklist generated from any given cohort removed a substantial proportion of NPVs (11-65%). We analyzed the blacklisted variants computationally and experimentally. Most of the blacklisted variants corresponded to false signals generated by incomplete reference genome assembly, location in low-complexity regions, bioinformatic misprocessing, or limitations inherent to cohort-specific private alleles (e.g., due to sequencing kits, and genetic ancestries). Finally, we provide our precalculated blacklists, together with ReFiNE, a program for generating customized blacklists from any medium-sized or large in-house cohort of exome (or other next-generation sequencing) data via a user-friendly public web server. This work demonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis.

CSAR-web: a web server of contig scaffolding using algebraic rearrangements.

CSAR-web is a web-based tool that allows the users to efficiently and accurately scaffold (i.e. order and orient) the contigs of a target draft genome based on a complete or incomplete reference genome from a related organism. It takes as input a target genome in multi-FASTA format and a reference genome in FASTA or multi-FASTA format, depending on whether the reference genome is complete or incomplete, respectively. In addition, it requires the users to choose either ‘NUCmer on nucleotides’ or ‘PROmer on translated amino acids’ for CSAR-web to identify conserved genomic markers (i.e. matched sequence regions) between the target and reference genomes, which are used by the rearrangement-based scaffolding algorithm in CSAR-web to order and orient the contigs of the target genome based on the reference genome. In the output page, CSAR-web displays its scaffolding result in a graphical mode (i.e. scalable dotplot) allowing the users to visually validate the correctness of scaffolded contigs and in a tabular mode allowing the users to view the details of scaffolds. CSAR-web is available online at http://genome.cs.nthu.edu.tw/CSAR-web.

Toward better understanding of artifacts in variant calling from high-coverage samples.

Whole-genome high-coverage sequencing has been widely used for personal and cancer genomics as well as in various research areas. However, in the lack of an unbiased whole-genome truth set, the global error rate of variant calls and the leading causal artifacts still remain unclear even given the great efforts in the evaluation of variant calling methods. We made 10 single nucleotide polymorphism and INDEL call sets with two read mappers and five variant callers, both on a haploid human genome and a diploid genome at a similar coverage. By investigating false heterozygous calls in the haploid genome, we identified the erroneous realignment in low-complexity regions and the incomplete reference genome with respect to the sample as the two major sources of errors, which press for continued improvements in these two areas. We estimated that the error rate of raw genotype calls is as high as 1 in 10-15 kb, but the error rate of post-filtered calls is reduced to 1 in 100-200 kb without significant compromise on the sensitivity. BWA-MEM alignment and raw variant calls are available at http://bit.ly/1g8XqRt scripts and miscellaneous data at https://github.com/lh3/varcmp. hengli@broadinstitute.org Supplementary data are available at Bioinformatics online.

Evaluation of variant identification methods for whole genome sequencing data in dairy cattle.

BackgroundAdvances in human genomics have allowed unprecedented productivity in terms of algorithms, software, and literature available for translating raw next-generation sequence data into high-quality information. The challenges of variant identification in organisms with lower quality reference genomes are less well documented. We explored the consequences of commonly recommended preparatory steps and the effects of single and multi sample variant identification methods using four publicly available software applications (Platypus, HaplotypeCaller, Samtools and UnifiedGenotyper) on whole genome sequence data of 65 key ancestors of Swiss dairy cattle populations. Accuracy of calling next-generation sequence variants was assessed by comparison to the same loci from medium and high-density single nucleotide variant (SNV) arrays.ResultsThe total number of SNVs identified varied by software and method, with single (multi) sample results ranging from 17.7 to 22.0 (16.9 to 22.0) million variants. Computing time varied considerably between software. Preparatory realignment of insertions and deletions and subsequent base quality score recalibration had only minor effects on the number and quality of SNVs identified by different software, but increased computing time considerably. Average concordance for single (multi) sample results with high-density chip data was 58.3% (87.0%) and average genotype concordance in correctly identified SNVs was 99.2% (99.2%) across software. The average quality of SNVs identified, measured as the ratio of transitions to transversions, was higher using single sample methods than multi sample methods. A consensus approach using results of different software generally provided the highest variant quality in terms of transition/transversion ratio.ConclusionsOur findings serve as a reference for variant identification pipeline development in non-human organisms and help assess the implication of preparatory steps in next-generation sequencing pipelines for organisms with incomplete reference genomes (pipeline code is included). Benchmarking this information should prove particularly useful in processing next-generation sequencing data for use in genome-wide association studies and genomic selection.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-948) contains supplementary material, which is available to authorized users.

Revealing the missing expressed genes beyond the human reference genome by RNA-Seq

BackgroundThe complete and accurate human reference genome is important for functional genomics researches. Therefore, the incomplete reference genome and individual specific sequences have significant effects on various studies.Resultswe used two RNA-Seq datasets from human brain tissues and 10 mixed cell lines to investigate the completeness of human reference genome. First, we demonstrated that in previously identified ~5 Mb Asian and ~5 Mb African novel sequences that are absent from the human reference genome of NCBI build 36, ~211 kb and ~201 kb of them could be transcribed, respectively. Our results suggest that many of those transcribed regions are not specific to Asian and African, but also present in Caucasian. Then, we found that the expressions of 104 RefSeq genes that are unalignable to NCBI build 37 in brain and cell lines are higher than 0.1 RPKM. 55 of them are conserved across human, chimpanzee and macaque, suggesting that there are still a significant number of functional human genes absent from the human reference genome. Moreover, we identified hundreds of novel transcript contigs that cannot be aligned to NCBI build 37, RefSeq genes and EST sequences. Some of those novel transcript contigs are also conserved among human, chimpanzee and macaque. By positioning those contigs onto the human genome, we identified several large deletions in the reference genome. Several conserved novel transcript contigs were further validated by RT-PCR.ConclusionOur findings demonstrate that a significant number of genes are still absent from the incomplete human reference genome, highlighting the importance of further refining the human reference genome and curating those missing genes. Our study also shows the importance of de novo transcriptome assembly. The comparative approach between reference genome and other related human genomes based on the transcriptome provides an alternative way to refine the human reference genome.

Genome-wide mapping and assembly of structural variant breakpoints in the mouse genome

Structural variation (SV) is a rich source of genetic diversity in mammals, but due to the challenges associated with mapping SV in complex genomes, basic questions regarding their genomic distribution and mechanistic origins remain unanswered. We have developed an algorithm (HYDRA) to localize SV breakpoints by paired-end mapping, and a general approach for the genome-wide assembly and interpretation of breakpoint sequences. We applied these methods to two inbred mouse strains: C57BL/6J and DBA/2J. We demonstrate that HYDRA accurately maps diverse classes of SV, including those involving repetitive elements such as transposons and segmental duplications; however, our analysis of the C57BL/6J reference strain shows that incomplete reference genome assemblies are a major source of noise. We report 7196 SVs between the two strains, more than two-thirds of which are due to transposon insertions. Of the remainder, 59% are deletions (relative to the reference), 26% are insertions of unlinked DNA, 9% are tandem duplications, and 6% are inversions. To investigate the origins of SV, we characterized 3316 breakpoint sequences at single-nucleotide resolution. We find that approximately 16% of non-transposon SVs have complex breakpoint patterns consistent with template switching during DNA replication or repair, and that this process appears to preferentially generate certain classes of complex variants. Moreover, we find that SVs are significantly enriched in regions of segmental duplication, but that this effect is largely independent of DNA sequence homology and thus cannot be explained by non-allelic homologous recombination (NAHR) alone. This result suggests that the genetic instability of such regions is often the cause rather than the consequence of duplicated genomic architecture.