Deep Ancestral Introgression Shapes Evolutionary History of Dragonflies and Damselflies.

Introgression is an important biological process affecting at least 10% of the extant species in the animal kingdom. Introgression significantly impacts inference of phylogenetic species relationships where a strictly binary tree model cannot adequately explain reticulate net-like species relationships. Here, we use phylogenomic approaches to understand patterns of introgression along the evolutionary history of a unique, nonmodel insect system: dragonflies and damselflies (Odonata). We demonstrate that introgression is a pervasive evolutionary force across various taxonomic levels within Odonata. In particular, we show that the morphologically "intermediate" species of Anisozygoptera (one of the three primary suborders within Odonata besides Zygoptera and Anisoptera), which retain phenotypic characteristics of the other two suborders, experienced high levels of introgression likely coming from zygopteran genomes. Additionally, we find evidence for multiple cases of deep inter-superfamilial ancestral introgression. [Gene flow; Odonata; phylogenomics; reticulate evolution.].

Proximal-end bias from in-vitro reconstituted nucleosomes and the result on downstream data analysis.

The most basic level of eukaryotic gene regulation is the presence or absence of nucleosomes on DNA regulatory elements. In an effort to elucidate in vivo nucleosome patterns, in vitro studies are frequently used. In vitro, short DNA fragments are more favorable for nucleosome formation, increasing the likelihood of nucleosome occupancy. This may in part result from the fact that nucleosomes prefer to form on the terminal ends of linear DNA. This phenomenon has the potential to bias in vitro reconstituted nucleosomes and skew results. If the ends of DNA fragments are known, the reads falling close to the ends are typically discarded. In this study we confirm the phenomenon of end bias of in vitro nucleosomes. We describe a method in which nearly identical libraries, with different known ends, are used to recover nucleosomes which form towards the terminal ends of fragmented DNA. Finally, we illustrate that although nucleosomes prefer to form on DNA ends, it does not appear to skew results or the interpretation thereof.

Opsins have evolved under the permanent heterozygote model: insights from phylotranscriptomics of Odonata.

Gene duplication plays a central role in adaptation to novel environments by providing new genetic material for functional divergence and evolution of biological complexity. Several evolutionary models have been proposed for gene duplication to explain how new gene copies are preserved by natural selection, but these models have rarely been tested using empirical data. Opsin proteins, when combined with a chromophore, form a photopigment that is responsible for the absorption of light, the first step in the phototransduction cascade. Adaptive gene duplications have occurred many times within the animal opsins' gene family, leading to novel wavelength sensitivities. Consequently, opsins are an attractive choice for the study of gene duplication evolutionary models. Odonata (dragonflies and damselflies) have the largest opsin repertoire of any insect currently known. Additionally, there is tremendous variation in opsin copy number between species, particularly in the long-wavelength-sensitive (LWS) class. Using comprehensive phylotranscriptomic and statistical approaches, we tested various evolutionary models of gene duplication. Our results suggest that both the blue-sensitive (BS) and LWS opsin classes were subjected to strong positive selection that greatly weakens after multiple duplication events, a pattern that is consistent with the permanent heterozygote model. Due to the immense interspecific variation and duplicability potential of opsin genes among odonates, they represent a unique model system to test hypotheses regarding opsin gene duplication and diversification at the molecular level.

A novel approach for multi-SNP GWAS and its application in Alzheimer's disease.

BACKGROUND: Genome-wide association studies (GWAS) have effectively identified genetic factors for many diseases. Many diseases, including Alzheimer's disease (AD), have epistatic causes, requiring more sophisticated analyses to identify groups of variants which together affect phenotype. RESULTS: Based on the GWAS statistical model, we developed a multi-SNP GWAS analysis to identify pairs of variants whose common occurrence signaled the Alzheimer's disease phenotype. CONCLUSIONS: Despite not having sufficient data to demonstrate significance, our preliminary experimentation identified a high correlation between GRIA3 and HLA-DRB5 (an AD gene). GRIA3 has not been previously reported in association with AD, but is known to play a role in learning and memory.

ScaffoldScaffolder: solving contig orientation via bidirected to directed graph reduction.

MOTIVATION: The contig orientation problem, which we formally define as the MAX-DIR problem, has at times been addressed cursorily and at times using various heuristics. In setting forth a linear-time reduction from the MAX-CUT problem to the MAX-DIR problem, we prove the latter is NP-complete. We compare the relative performance of a novel greedy approach with several other heuristic solutions. RESULTS: Our results suggest that our greedy heuristic algorithm not only works well but also outperforms the other algorithms due to the nature of scaffold graphs. Our results also demonstrate a novel method for identifying inverted repeats and inversion variants, both of which contradict the basic single-orientation assumption. Such inversions have previously been noted as being difficult to detect and are directly involved in the genetic mechanisms of several diseases. AVAILABILITY AND IMPLEMENTATION: http://bioresearch.byu.edu/scaffoldscaffolder. CONTACT: paulmbodily@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Heterozygous genome assembly via binary classification of homologous sequence.

BACKGROUND: Genome assemblers to date have predominantly targeted haploid reference reconstruction from homozygous data. When applied to diploid genome assembly, these assemblers perform poorly, owing to the violation of assumptions during both the contigging and scaffolding phases. Effective tools to overcome these problems are in growing demand. Increasing parameter stringency during contigging is an effective solution to obtaining haplotype-specific contigs; however, effective algorithms for scaffolding such contigs are lacking. METHODS: We present a stand-alone scaffolding algorithm, ScaffoldScaffolder, designed specifically for scaffolding diploid genomes. The algorithm identifies homologous sequences as found in "bubble" structures in scaffold graphs. Machine learning classification is used to then classify sequences in partial bubbles as homologous or non-homologous sequences prior to reconstructing haplotype-specific scaffolds. We define four new metrics for assessing diploid scaffolding accuracy: contig sequencing depth, contig homogeneity, phase group homogeneity, and heterogeneity between phase groups. RESULTS: We demonstrate the viability of using bubbles to identify heterozygous homologous contigs, which we term homolotigs. We show that machine learning classification trained on these homolotig pairs can be used effectively for identifying homologous sequences elsewhere in the data with high precision (assuming error-free reads). CONCLUSION: More work is required to comparatively analyze this approach on real data with various parameters and classifiers against other diploid genome assembly methods. However, the initial results of ScaffoldScaffolder supply validity to the idea of employing machine learning in the difficult task of diploid genome assembly. Software is available at http://bioresearch.byu.edu/scaffoldscaffolder.

Effects of error-correction of heterozygous next-generation sequencing data.

BACKGROUND: Error correction is an important step in increasing the quality of next-generation sequencing data for downstream analysis and use. Polymorphic datasets are a challenge for many bioinformatic software packages that are designed for or assume homozygosity of an input dataset. This assumption ignores the true genomic composition of many organisms that are diploid or polyploid. In this survey, two different error correction packages, Quake and ECHO, are examined to see how they perform on next-generation sequence data from heterozygous genomes. RESULTS: Quake and ECHO perform well and were able to correct many errors found within the data. However, errors that occur at heterozygous positions had unique trends. Errors at these positions were sometimes corrected incorrectly, introducing errors into the dataset with the possibility of creating a chimeric read. Quake was much less likely to create chimeric reads. Quake's read trimming removed a large portion of the original data and often left reads with few heterozygous markers. ECHO resulted in more chimeric reads and introduced more errors than Quake but preserved heterozygous markers. CONCLUSIONS: These findings suggest that Quake and ECHO both have strengths and weaknesses when applied to heterozygous data. With the increased interest in haplotype specific analysis, new tools that are designed to be haplotype-aware are necessary that do not have the weaknesses of Quake and ECHO.

De novo genome assembly of the fungal plant pathogen Pyrenophora semeniperda.

Pyrenophora semeniperda (anamorph Drechslera campulata) is a necrotrophic fungal seed pathogen that has a wide host range within the Poaceae. One of its hosts is cheatgrass (Bromus tectorum), a species exotic to the United States that has invaded natural ecosystems of the Intermountain West. As a natural pathogen of cheatgrass, P. semeniperda has potential as a biocontrol agent due to its effectiveness at killing seeds within the seed bank; however, few genetic resources exist for the fungus. Here, the genome of P. semeniperda isolate assembled from sequence reads of 454 pyrosequencing is presented. The total assembly is 32.5 Mb and includes 11,453 gene models encoding putative proteins larger than 24 amino acids. The models represent a variety of putative genes that are involved in pathogenic pathways typically found in necrotrophic fungi. In addition, extensive rearrangements, including inter- and intrachromosomal rearrangements, were found when the P. semeniperda genome was compared to P. tritici-repentis, a related fungal species.

Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing.

BACKGROUND: To facilitate the clinical implementation of genomic medicine by next-generation sequencing, it will be critically important to obtain accurate and consistent variant calls on personal genomes. Multiple software tools for variant calling are available, but it is unclear how comparable these tools are or what their relative merits in real-world scenarios might be. METHODS: We sequenced 15 exomes from four families using commercial kits (Illumina HiSeq 2000 platform and Agilent SureSelect version 2 capture kit), with approximately 120X mean coverage. We analyzed the raw data using near-default parameters with five different alignment and variant-calling pipelines (SOAP, BWA-GATK, BWA-SNVer, GNUMAP, and BWA-SAMtools). We additionally sequenced a single whole genome using the sequencing and analysis pipeline from Complete Genomics (CG), with 95% of the exome region being covered by 20 or more reads per base. Finally, we validated 919 single-nucleotide variations (SNVs) and 841 insertions and deletions (indels), including similar fractions of GATK-only, SOAP-only, and shared calls, on the MiSeq platform by amplicon sequencing with approximately 5000X mean coverage. RESULTS: SNV concordance between five Illumina pipelines across all 15 exomes was 57.4%, while 0.5 to 5.1% of variants were called as unique to each pipeline. Indel concordance was only 26.8% between three indel-calling pipelines, even after left-normalizing and intervalizing genomic coordinates by 20 base pairs. There were 11% of CG variants falling within targeted regions in exome sequencing that were not called by any of the Illumina-based exome analysis pipelines. Based on targeted amplicon sequencing on the MiSeq platform, 97.1%, 60.2%, and 99.1% of the GATK-only, SOAP-only and shared SNVs could be validated, but only 54.0%, 44.6%, and 78.1% of the GATK-only, SOAP-only and shared indels could be validated. Additionally, our analysis of two families (one with four individuals and the other with seven), demonstrated additional accuracy gained in variant discovery by having access to genetic data from a multi-generational family. CONCLUSIONS: Our results suggest that more caution should be exercised in genomic medicine settings when analyzing individual genomes, including interpreting positive and negative findings with scrutiny, especially for indels. We advocate for renewed collection and sequencing of multi-generational families to increase the overall accuracy of whole genomes.

Exome sequencing and unrelated findings in the context of complex disease research: ethical and clinical implications.

Exome sequencing has identified the causes of several Mendelian diseases, although it has rarely been used in a clinical setting to diagnose the genetic cause of an idiopathic disorder in a single patient. We performed exome sequencing on a pedigree with several members affected with attention deficit/hyperactivity disorder (ADHD), in an effort to identify candidate variants predisposing to this complex disease. While we did identify some rare variants that might predispose to ADHD, we have not yet proven the causality for any of them. However, over the course of the study, one subject was discovered to have idiopathic hemolytic anemia (IHA), which was suspected to be genetic in origin. Analysis of this subject's exome readily identified two rare non-synonymous mutations in PKLR gene as the most likely cause of the IHA, although these two mutations had not been documented before in a single individual. We further confirmed the deficiency by functional biochemical testing, consistent with a diagnosis of red blood cell pyruvate kinase deficiency. Our study implies that exome and genome sequencing will certainly reveal additional rare variation causative for even well-studied classical Mendelian diseases, while also revealing variants that might play a role in complex diseases. Furthermore, our study has clinical and ethical implications for exome and genome sequencing in a research setting; how to handle unrelated findings of clinical significance, in the context of originally planned complex disease research, remains a largely uncharted area for clinicians and researchers.