Identification and analysis of the first 2009 pandemic H1N1 influenza virus from U.S. feral swine

The first case of pandemic H1N1 influenza (pH1N1) virus in feral swine in the United States was identified in Texas through the United States Department of Agriculture (USDA) Wildlife Services' surveillance program. Two samples were identified as pandemic influenza by reverse transcriptase quantitative PCR (RT-qPCR). Full-genome Sanger sequencing of all eight influenza segments was performed. In addition, Illumina deep sequencing of the original diagnostic samples and their respective virus isolation cultures were performed to assess the feasibility of using an unbiased whole-genome linear target amplification method and multiple sample sequencing in a single Illumina GAIIx lane. Identical sequences were obtained using both techniques. Phylogenetic analysis indicated that all gene segments belonged to the pH1N1 (2009) lineage. In conclusion, we have identified the first pH1N1 isolate in feral swine in the United States and have demonstrated the use of an easy unbiased linear amplification method for deep sequencing of multiple samples.

Emerging frontiers in pancreatic cancer research: elaboration of key genes, cells and the extracellular milieu

PURPOSE OF REVIEW

We review recent literature with a view to forge an integrative understanding of the molecular, cellular and extracellular milieu of pancreatic cancer, and discuss them in the context of development of novel, personalized therapeutic options.

RECENT FINDINGS

Pancreatic tumorigenesis, examined using genetically engineered mouse models, appears to be driven by local inflammation, in concert with the 'big four' mutations involving oncogenic KRAS, SMAD4, CDKN2A, and TP53, through induction of epithelial-to-mesenchymal transition (EMT) and cancer stem cells, and accompanied by metastasis. High-throughput sequencing of pancreatic ductal adenocarcinoma as well as neuroendocrine tumors and rarer subtypes of cancers of the pancreas has revealed several novel mutations in genes like PALB2, guanine nucleotide-binding protein, alpha stimulating, death-domain-associated protein, α thalassemia/mental retardation syndrome X linked, switch/sucrose nonfermentable pathway related, and in genes in the ubiquitin-dependent pathways such as USP9X. Therapeutic targeting of the tumor-stroma axis by cytokines and immune response modulators and the role of autophagy in pancreatic cancer are some other salient themes explored in the recent publications.

SUMMARY

Recent publications shed new light on the mutational landscape of pancreatic cancer and further delineate the distinctive pancreatic cancer-stroma ecosystem as determined by the dynamic interplay of inflammation, hallmark mutations, EMT, and cancer stem cells.

Gene expression divergence and nucleotide differentiation between males of different color morphs and mating strategies in the ruff

By next generation transcriptome sequencing, it is possible to obtain data on both nucleotide sequence variation and gene expression. We have used this approach (RNA-Seq) to investigate the genetic basis for differences in plumage coloration and mating strategies in a non-model bird species, the ruff (Philomachus pugnax). Ruff males show enormous variation in the coloration of ornamental feathers, used for individual recognition. This polymorphism is linked to reproductive strategies, with dark males (Independents) defending territories on leks against other Independents, whereas white morphs (Satellites) co-occupy Independent's courts without agonistic interactions. Previous work found a strong genetic component for mating strategy, but the genes involved were not identified. We present feather transcriptome data of more than 6,000 de-novo sequenced ruff genes (although with limited coverage for many of them). None of the identified genes showed significant expression divergence between males, but many genetic markers showed nucleotide differentiation between different color morphs and mating strategies. These include several feather keratin genes, splicing factors, and the Xg blood-group gene. Many of the genes with significant genetic structure between mating strategies have not yet been annotated and their functions remain to be elucidated. We also conducted in-depth investigations of 28 pre-identified coloration candidate genes. Two of these (EDNRB and TYR) were specifically expressed in black- and rust-colored males, respectively. We have demonstrated the utility of next generation transcriptome sequencing for identifying and genotyping large number of genetic markers in a non-model species without previous genomic resources, and highlight the potential of this approach for addressing the genetic basis of ecologically important variation.

Turning pipe dreams into reality

A report on the Galaxy Community Conference at the University of Illinois, Chicago, July 25-27, 2012.

High-throughput sequencing offers insight into mechanisms of resource partitioning in cryptic bat species

Sympatric cryptic species, characterized by low morphological differentiation, pose a challenge to understanding the role of interspecific competition in structuring ecological communities. We used traditional (morphological) and novel molecular methods of diet analysis to study the diet of two cryptic bat species that are sympatric in southern England (Plecotus austriacus and P. auritus) (Fig. 1). Using Roche FLX 454 (Roche, Basel, CH) high-throughput sequencing (HTS) and uniquely tagged generic arthropod primers, we identified 142 prey Molecular Operational Taxonomic Units (MOTUs) in the diet of the cryptic bats, 60% of which were assigned to a likely species or genus. The findings from the molecular study supported the results of microscopic analyses in showing that the diets of both species were dominated by lepidopterans. However, HTS provided a sufficiently high resolution of prey identification to determine fine-scale differences in resource use. Although both bat species appeared to have a generalist diet, eared-moths from the family Noctuidae were the main prey consumed. Interspecific niche overlap was greater than expected by chance (O(jk) = 0.72, P < 0.001) due to overlap in the consumption of the more common prey species. Yet, habitat associations of nongeneralist prey species found in the diets corresponded to those of their respective bat predator (grasslands for P. austriacus, and woodland for P. auritus). Overlap in common dietary resource use combined with differential specialist prey habitat associations suggests that habitat partitioning is the primary mechanism of coexistence. The performance of HTS is discussed in relation to previous methods of molecular and morphological diet analysis. By enabling species-level identification of dietary components, the application of DNA sequencing to diet analysis allows a more comprehensive comparison of the diet of sympatric cryptic species, and therefore can be an important tool for determining fine-scale mechanisms of coexistence.

Deciphering the complex leaf transcriptome of the allotetraploid species Nicotiana tabacum: a phylogenomic perspective

BACKGROUND

Polyploidization is an important mechanism in plant evolution. By analyzing the leaf transcriptomes taken from the allotetraploid Nicotiana tabacum (tobacco) and parental genome donors, N. sylvesteris (S-Genome) and N. tomentosiformis (T-Genome), a phylogenomic approach was taken to map the fate of homeologous gene pairs in this plant.

RESULTS

A comparison between the genes present in the leaf transcriptomes of N. tabacum and modern day representatives of its progenitor species demonstrated that only 33% of assembled transcripts could be distinguished based on their sequences. A large majority of the genes (83.6% of the non parent distinguishable and 87.2% of the phylogenetic topology analyzed clusters) expressed above background level (more than 5 reads) showed similar overall expression levels. Homeologous sequences could be identified for 968 gene clusters, and 90% (6% of all genes) of the set maintained expression of only one of the tobacco homeologs. When both homeologs were expressed, only 15% (0.5% of the total) showed evidence of differential expression, providing limited evidence of subfunctionalization. Comparing the rate of synonymous nucleotide substitution (Ks) and non-synonymous nucleotide substitution (Kn) provided limited evidence for positive selection during the evolution of tobacco since the polyploidization event took place.

CONCLUSIONS

Polyploidization is a powerful mechanism for plant speciation that can occur during one generation; however millions of generations may be necessary for duplicate genes to acquire a new function. Analysis of the tobacco leaf transcriptome reveals that polyploidization, even in a young tetraploid such as tobacco, can lead to complex changes in gene expression. Gene loss and gene silencing, or subfunctionalization may explain why both homeologs are not expressed by the associated genes. With Whole Genome Duplication (WGD) events, polyploid genomes usually maintain a high percentage of gene duplicates. The data provided little evidence of preferential maintenance of gene expression from either the T- or S-genome. Additionally there was little evidence of neofunctionalization in Nicotiana tabacum suggesting it occurs at a low frequency in young polyploidy.

Molecular tools for exploring polyploid genomes in plants

Polyploidy is a very common phenomenon in the plant kingdom, where even diploid species are often described as paleopolyploids. The polyploid condition may bring about several advantages compared to the diploid state. Polyploids often show phenotypes that are not present in their diploid progenitors or exceed the range of the contributing species. Some of these traits may play a role in heterosis or could favor adaptation to new ecological niches. Advances in genomics and sequencing technology may create unprecedented opportunities for discovering and monitoring the molecular effects of polyploidization. Through this review, we provide an overview of technologies and strategies that may allow an in-depth analysis of polyploid genomes. After introducing some basic aspects on the origin and genetics of polyploids, we highlight the main tools available for genome and gene expression analysis and summarize major findings. In the last part of this review, the implications of next generation sequencing are briefly discussed. The accumulation of knowledge on polyploid formation, maintenance, and divergence at whole-genome and subgenome levels will not only help plant biologists to understand how plants have evolved and diversified, but also assist plant breeders in designing new strategies for crop improvement.

A solid quality-control analysis of AB SOLiD short-read sequencing data

Next generation sequencers have greatly improved our ability to mine polymorphisms and mutations out of entire (or portions of) genomes. The reliability of their outputs, though, showed to be very related to the sequencing chemistry and to deeply affect the quality of the downstream analyses. We focus here on the two-base color code chemistry of AB SOLiD sequencers and propose a comprehensive quality control methodological and software pipeline. We used existing and custom tools to detect and purge short-reads of some common flaws due to sequencing errors and chemical hitches. We apply them to a cohort of SOLiD 4 runs and measure their joint efficacy in terms of the resulting ability to detect the greatest possible number of true variants.

Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives

Gene fusions are important genomic events in human cancer because their fusion gene products can drive the development of cancer and thus are potential prognostic tools or therapeutic targets in anti-cancer treatment. Major advancements have been made in computational approaches for fusion gene discovery over the past 3 years due to improvements and widespread applications of high-throughput next generation sequencing (NGS) technologies. To identify fusions from NGS data, existing methods typically leverage the strengths of both sequencing technologies and computational strategies. In this article, we review the NGS and computational features of existing methods for fusion gene detection and suggest directions for future development.

Perspectives of integrative cancer genomics in next generation sequencing era

The explosive development of genomics technologies including microarrays and next generation sequencing (NGS) has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research.

The importance of living botanical collections for plant biology and the "next generation" of evo-devo research

Living botanical collections include germplasm repositories, long-term experimental plantings, and botanical gardens. We present here a series of vignettes to illustrate the central role that living collections have played in plant biology research, including evo-devo research. Looking toward the future, living collections will become increasingly important in support of future evo-devo research. The driving force behind this trend is nucleic acid sequencing technologies, which are rapidly becoming more powerful and cost-effective, and which can be applied to virtually any species. This allows for more extensive sampling, including non-model organisms with unique biological features and plants from diverse phylogenetic positions. Importantly, a major challenge for sequencing-based evo-devo research is to identify, access, and propagate appropriate plant materials. We use a vignette of the ongoing 1,000 Transcriptomes project as an example of the challenges faced by such projects. We conclude by identifying some of the pinch points likely to be encountered by future evo-devo researchers, and how living collections can help address them.

How do alignment programs perform on sequencing data with varying qualities and from repetitive regions?

BACKGROUND

Next-generation sequencing technologies generate a significant number of short reads that are utilized to address a variety of biological questions. However, quite often, sequencing reads tend to have low quality at the 3' end and are generated from the repetitive regions of a genome. It is unclear how different alignment programs perform under these different cases. In order to investigate this question, we use both real data and simulated data with the above issues to evaluate the performance of four commonly used algorithms: SOAP2, Bowtie, BWA, and Novoalign.

METHODS

The performance of different alignment algorithms are measured in terms of concordance between any pair of aligners (for real sequencing data without known truth) and the accuracy of simulated read alignment.

RESULTS

Our results show that, for sequencing data with reads that have relatively good quality or that have had low quality bases trimmed off, all four alignment programs perform similarly. We have also demonstrated that trimming off low quality ends markedly increases the number of aligned reads and improves the consistency among different aligners as well, especially for low quality data. However, Novoalign is more sensitive to the improvement of data quality. Trimming off low quality ends significantly increases the concordance between Novoalign and other aligners. As for aligning reads from repetitive regions, our simulation data show that reads from repetitive regions tend to be aligned incorrectly, and suppressing reads with multiple hits can improve alignment accuracy.

CONCLUSIONS

This study provides a systematic comparison of commonly used alignment algorithms in the context of sequencing data with varying qualities and from repetitive regions. Our approach can be applied to different sequencing data sets generated from different platforms. It can also be utilized to study the performance of other alignment programs.

A post-assembly genome-improvement toolkit (PAGIT) to obtain annotated genomes from contigs

Genome projects now produce draft assemblies within weeks owing to advanced high-throughput sequencing technologies. For milestone projects such as Escherichia coli or Homo sapiens, teams of scientists were employed to manually curate and finish these genomes to a high standard. Nowadays, this is not feasible for most projects, and the quality of genomes is generally of a much lower standard. This protocol describes software (PAGIT) that is used to improve the quality of draft genomes. It offers flexible functionality to close gaps in scaffolds, correct base errors in the consensus sequence and exploit reference genomes (if available) in order to improve scaffolding and generating annotations. The protocol is most accessible for bacterial and small eukaryotic genomes (up to 300 Mb), such as pathogenic bacteria, malaria and parasitic worms. Applying PAGIT to an E. coli assembly takes ∼24 h: it doubles the average contig size and annotates over 4,300 gene models.

Evaluation of normalization methods in mammalian microRNA-Seq data

Simple total tag count normalization is inadequate for microRNA sequencing data generated from the next generation sequencing technology. However, so far systematic evaluation of normalization methods on microRNA sequencing data is lacking. We comprehensively evaluate seven commonly used normalization methods including global normalization, Lowess normalization, Trimmed Mean Method (TMM), quantile normalization, scaling normalization, variance stabilization, and invariant method. We assess these methods on two individual experimental data sets with the empirical statistical metrics of mean square error (MSE) and Kolmogorov-Smirnov (K-S) statistic. Additionally, we evaluate the methods with results from quantitative PCR validation. Our results consistently show that Lowess normalization and quantile normalization perform the best, whereas TMM, a method applied to the RNA-Sequencing normalization, performs the worst. The poor performance of TMM normalization is further evidenced by abnormal results from the test of differential expression (DE) of microRNA-Seq data. Comparing with the models used for DE, the choice of normalization method is the primary factor that affects the results of DE. In summary, Lowess normalization and quantile normalization are recommended for normalizing microRNA-Seq data, whereas the TMM method should be used with caution.

Normal and compound poisson approximations for pattern occurrences in NGS reads

Next generation sequencing (NGS) technologies are now widely used in many biological studies. In NGS, sequence reads are randomly sampled from the genome sequence of interest. Most computational approaches for NGS data first map the reads to the genome and then analyze the data based on the mapped reads. Since many organisms have unknown genome sequences and many reads cannot be uniquely mapped to the genomes even if the genome sequences are known, alternative analytical methods are needed for the study of NGS data. Here we suggest using word patterns to analyze NGS data. Word pattern counting (the study of the probabilistic distribution of the number of occurrences of word patterns in one or multiple long sequences) has played an important role in molecular sequence analysis. However, no studies are available on the distribution of the number of occurrences of word patterns in NGS reads. In this article, we build probabilistic models for the background sequence and the sampling process of the sequence reads from the genome. Based on the models, we provide normal and compound Poisson approximations for the number of occurrences of word patterns from the sequence reads, with bounds on the approximation error. The main challenge is to consider the randomness in generating the long background sequence, as well as in the sampling of the reads using NGS. We show the accuracy of these approximations under a variety of conditions for different patterns with various characteristics. Under realistic assumptions, the compound Poisson approximation seems to outperform the normal approximation in most situations. These approximate distributions can be used to evaluate the statistical significance of the occurrence of patterns from NGS data. The theory and the computational algorithm for calculating the approximate distributions are then used to analyze ChIP-Seq data using transcription factor GABP. Software is available online (www-rcf.usc.edu/∼fsun/Programs/NGS_motif_power/NGS_motif_power.html). In addition, Supplementary Material can be found online (www.liebertonline.com/cmb).

Metatranscriptomic analysis of small RNAs present in soybean deep sequencing libraries

A large number of small RNAs unrelated to the soybean genome were identified after deep sequencing of soybean small RNA libraries. A metatranscriptomic analysis was carried out to identify the origin of these sequences. Comparative analyses of small interference RNAs (siRNAs) present in samples collected in open areas corresponding to soybean field plantations and samples from soybean cultivated in greenhouses under a controlled environment were made. Different pathogenic, symbiotic and free-living organisms were identified from samples of both growth systems. They included viruses, bacteria and different groups of fungi. This approach can be useful not only to identify potentially unknown pathogens and pests, but also to understand the relations that soybean plants establish with microorganisms that may affect, directly or indirectly, plant health and crop production.

VERSE: a varying effect regression for splicing elements discovery

Identification of splicing regulatory elements (SREs) deserves special attention because these cis-acting short sequences are vital parts of splicing code. The fact that a variety of other biological signals cooperatively govern the splicing pattern indicates the necessity of developing novel tools to incorporate information from multiple sources to improve splicing factor binding sites prediction. Under this context, we proposed a Varying Effect Regression for Splicing Elements (VERSE) to discover intronic SREs in the proximity of exon junctions by integrating other biological features. As a result, 1562 intronic SREs were identified in 16 human tissues, many of which overlapped with experimentally verified binding motifs for several well-known splicing factors, including FOX-1, PTB, hnRNP A/B, hnRNP F/H, and so on. The discovered tissue, region, and conservation preferences of the putative motifs demonstrate that splice site selection is a complicated process that needs subtle and delicate regulation. VERSE may serve as a powerful tool to not only discover SREs by incorporating additional informative signals but also precisely quantify their varying contribution under different biological contexts.

Reducing ligation bias of small RNAs in libraries for next generation sequencing

BACKGROUND

The use of nucleic acid-modifying enzymes has driven the rapid advancement in molecular biology. Understanding their function is important for modifying or improving their activity. However, functional analysis usually relies upon low-throughput experiments. Here we present a method for functional analysis of nucleic acid-modifying enzymes using next generation sequencing.

FINDINGS

We demonstrate that sequencing data of libraries generated by RNA ligases can reveal novel secondary structure preferences of these enzymes, which are used in small RNA cloning and library preparation for NGS. Using this knowledge we demonstrate that the cloning bias in small RNA libraries is RNA ligase-dependent. We developed a high definition (HD) protocol that reduces the RNA ligase-dependent cloning bias. The HD protocol doubled read coverage, is quantitative and found previously unidentified microRNAs. In addition, we show that microRNAs in miRBase are those preferred by the adapters of the main sequencing platform.

CONCLUSIONS

Sequencing bias of small RNAs partially influenced which microRNAs have been studied in depth; therefore most previous small RNA profiling experiments should be re-evaluated. New microRNAs are likely to be found, which were selected against by existing adapters. Preference of currently used adapters towards known microRNAs suggests that the annotation of all existing small RNAs, including miRNAs, siRNAs and piRNAs, has been biased.

An In-Solution Hybridisation Method for the Isolation of Pathogen DNA from Human DNA-rich Clinical Samples for Analysis by NGS

Studies on DNA from pathogenic organisms, within clinical samples, are often complicated by the presence of large amounts of host, e.g., human DNA. Isolation of pathogen DNA from these samples would improve the efficiency of next-generation sequencing (NGS) and pathogen identification. Here we describe a solution-based hybridisation method for isolation of pathogen DNA from a mixed population. This straightforward and inexpensive technique uses probes made from whole-genome DNA and off-the-shelf reagents. In this study, Escherichia coli DNA was successfully enriched from a mixture of E.coli and human DNA. After enrichment, genome coverage following NGS was significantly higher and the evenness of coverage and GC content were unaffected. This technique was also applied to samples containing a mixture of human and Plasmodium falciparum DNA. The P.falciparum genome is particularly difficult to sequence due to its high AT content (80.6%) and repetitive nature. Post enrichment, a bias in the recovered DNA was observed, with a poorer representation of the AT-rich non-coding regions. This uneven coverage was also observed in pre-enrichment samples, but to a lesser degree. Despite the coverage bias in enriched samples, SNP (single-nucleotide polymorphism) calling in coding regions was unaffected and the majority of samples had over 90% of their coding region covered at 5× depth. This technique shows significant promise as an effective method to enrich pathogen DNA from samples with heavy human contamination, particularly when applied to GC-neutral genomes.

What is Next in Bark Beetle Phylogeography?

Bark beetle species within the scolytid genera Dendroctonus, Ips, Pityogenes and Tomicus are known to cause extensive ecological and economical damage in spruce and pine forests during epidemic outbreaks all around the world. Dendroctonus ponderosae poses the most recent example having destroyed almost 100,000 km² of conifer forests in North America. The success and effectiveness of scolytid species lies mostly in strategies developed over the course of time. Among these, a complex system of semiochemicals promotes the communication and aggregation on the spot of infestation facilitating an en masse attack against a host tree's defenses; or an association with fungi that evolved either in the form of nutrition (ambrosia fungi) or even by reducing the resistance of host trees (blue-stain fungi). Although often specific to a tree genus or species, some bark beetles are polyphagous and have the ability to switch on to new hosts and extend their host range (i.e., between conifer genera such as Pityogenes chalcographus or even from conifer to deciduous trees as Polygraphus grandiclava). A combination of these capabilities in concert with life history or ecological traits explains why bark beetles are considered interesting subjects in evolutionary studies. Several bark beetle species appear in phylogeographic investigations, in an effort to improve our understanding of their ecology, epidemiology and evolution. In this paper investigations that unveil the phylogeographic history of bark beetles are reviewed. A close association between refugial areas and postglacial migration routes that insects and host trees have followed in the last 15,000 BP has been suggested in many studies. Finally, a future perspective of how next generation sequencing will influence the resolution of phylogeographic patterns in the coming years is presented. Utilization of such novel techniques will provide a more detailed insight into the genome of scolytids facilitating at the same time the application of neutral and non-neutral markers. The latter markers in particular promise to enhance the study of eco-physiological reaction types like the so-called pioneer beetles or obligate diapausing individuals.

Identification of a novel nidovirus associated with a neurological disease of the Australian brushtail possum (Trichosurus vulpecula)

A novel, fatal neurological disease of the Australian brushtail possum (Trichosurus vulpecula) was first identified in 1995 in a research facility and subsequently in free-living possums in New Zealand and termed wobbly possum disease (WPD). The results of previous transmission studies suggested that the aetiological agent of WPD is most likely a virus. However, the identity of the presumed viral agent had not been elucidated. In the current report, we describe identification of a novel virus from tissues of WPD-affected possums using a combination of next generation sequencing and traditional molecular methods. The proportion of possums positive for the novel virus by PCR was significantly higher (p<0.0001) among animals with WPD than clinically healthy possums, strongly suggesting an aetiological involvement of the virus in WPD. Analysis of the partial genomic sequence of the putative WPD virus indicated that it is a novel nidovirus, most closely related to the current members of the family Arteriviridae.

Disease gene identification strategies for exome sequencing

Next generation sequencing can be used to search for Mendelian disease genes in an unbiased manner by sequencing the entire protein-coding sequence, known as the exome, or even the entire human genome. Identifying the pathogenic mutation amongst thousands to millions of genomic variants is a major challenge, and novel variant prioritization strategies are required. The choice of these strategies depends on the availability of well-phenotyped patients and family members, the mode of inheritance, the severity of the disease and its population frequency. In this review, we discuss the current strategies for Mendelian disease gene identification by exome resequencing. We conclude that exome strategies are successful and identify new Mendelian disease genes in approximately 60% of the projects. Improvements in bioinformatics as well as in sequencing technology will likely increase the success rate even further. Exome sequencing is likely to become the most commonly used tool for Mendelian disease gene identification for the coming years.

De novo assembly of the carrot mitochondrial genome using next generation sequencing of whole genomic DNA provides first evidence of DNA transfer into an angiosperm plastid genome

BACKGROUND

Sequence analysis of organelle genomes has revealed important aspects of plant cell evolution. The scope of this study was to develop an approach for de novo assembly of the carrot mitochondrial genome using next generation sequence data from total genomic DNA.

RESULTS

Sequencing data from a carrot 454 whole genome library were used to develop a de novo assembly of the mitochondrial genome. Development of a new bioinformatic tool allowed visualizing contig connections and elucidation of the de novo assembly. Southern hybridization demonstrated recombination across two large repeats. Genome annotation allowed identification of 44 protein coding genes, three rRNA and 17 tRNA. Identification of the plastid genome sequence allowed organelle genome comparison. Mitochondrial intergenic sequence analysis allowed detection of a fragment of DNA specific to the carrot plastid genome. PCR amplification and sequence analysis across different Apiaceae species revealed consistent conservation of this fragment in the mitochondrial genomes and an insertion in Daucus plastid genomes, giving evidence of a mitochondrial to plastid transfer of DNA. Sequence similarity with a retrotransposon element suggests a possibility that a transposon-like event transferred this sequence into the plastid genome.

CONCLUSIONS

This study confirmed that whole genome sequencing is a practical approach for de novo assembly of higher plant mitochondrial genomes. In addition, a new aspect of intercompartmental genome interaction was reported providing the first evidence for DNA transfer into an angiosperm plastid genome. The approach used here could be used more broadly to sequence and assemble mitochondrial genomes of diverse species. This information will allow us to better understand intercompartmental interactions and cell evolution.

A whole-genome massively parallel sequencing analysis of BRCA1 mutant oestrogen receptor-negative and -positive breast cancers

BRCA1 encodes a tumour suppressor protein that plays pivotal roles in homologous recombination (HR) DNA repair, cell-cycle checkpoints, and transcriptional regulation. BRCA1 germline mutations confer a high risk of early-onset breast and ovarian cancer. In more than 80% of cases, tumours arising in BRCA1 germline mutation carriers are oestrogen receptor (ER)-negative; however, up to 15% are ER-positive. It has been suggested that BRCA1 ER-positive breast cancers constitute sporadic cancers arising in the context of a BRCA1 germline mutation rather than being causally related to BRCA1 loss-of-function. Whole-genome massively parallel sequencing of ER-positive and ER-negative BRCA1 breast cancers, and their respective germline DNAs, was used to characterize the genetic landscape of BRCA1 cancers at base-pair resolution. Only BRCA1 germline mutations, somatic loss of the wild-type allele, and TP53 somatic mutations were recurrently found in the index cases. BRCA1 breast cancers displayed a mutational signature consistent with that caused by lack of HR DNA repair in both ER-positive and ER-negative cases. Sequencing analysis of independent cohorts of hereditary BRCA1 and sporadic non-BRCA1 breast cancers for the presence of recurrent pathogenic mutations and/or homozygous deletions found in the index cases revealed that DAPK3, TMEM135, KIAA1797, PDE4D, and GATA4 are potential additional drivers of breast cancers. This study demonstrates that BRCA1 pathogenic germline mutations coupled with somatic loss of the wild-type allele are not sufficient for hereditary breast cancers to display an ER-negative phenotype, and has led to the identification of three potential novel breast cancer genes (ie DAPK3, TMEM135, and GATA4).

Genomics of acute myeloid leukemia: the next generation

Acute myeloid leukemia (AML) is, as other types of cancer, a genetic disorder of somatic cells. The detection of somatic molecular abnormalities that may cause and maintain AML is crucial for patient stratification. The development of mutation-specific therapeutic interventions will hopefully increase cure rates and improve patients’ quality of life. This review illustrates how next generation sequencing technologies are changing the study of cancer genomics of adult AML patients.

HPV-associated head and neck cancer: molecular and nano-scale markers for prognosis and therapeutic stratification. Sensors (Basel). 2012;12:5159-5169. [PMID: 22666080 PMCID: PMC3355463 DOI: 10.3390/s120405159]

Over the last 10 years, it has become clear that patients with head and neck cancer can be stratified into two distinct subgroups on the basis of the etiology of their disease. Patients with human papillomavirus-related cancers have significantly better survival rates and may necessitate different therapeutic approaches than those with tobacco and/or alcohol related cancers. This review discusses the various biomarkers currently in use for identification of patients with HPV-positive cancers with a focus on the advantages and limitations of molecular and nano-scale markers.

RNA-sequencing analysis of 5' capped RNAs identifies many new differentially expressed genes in acute hepatitis C virus infection

We describe the first report of RNA sequencing of 5' capped (Pol II) RNAs isolated from acutely hepatitis C virus (HCV) infected Huh 7.5 cells that provides a general approach to identifying differentially expressed annotated and unannotated genes that participate in viral-host interactions. We identified 100, 684, and 1,844 significantly differentially expressed annotated genes in acutely infected proliferative Huh 7.5 cells at 6, 48, and 72 hours, respectively (fold change ≥ 1.5 and Bonferroni adjusted p-values < 0.05). Most of the differentially expressed genes (>80%) and biological pathways (such as adipocytokine, Notch, Hedgehog and NOD-like receptor signaling) were not identified by previous gene array studies. These genes are critical components of host immune, inflammatory and oncogenic pathways and provide new information regarding changes that may benefit the virus or mediate HCV induced pathology. RNAi knockdown studies of newly identified highly upregulated FUT1 and KLHDC7B genes provide evidence that their gene products regulate and facilitate HCV replication in hepatocytes. Our approach also identified novel Pol II unannotated transcripts that were upregulated. Results further identify new pathways that regulate HCV replication in hepatocytes and suggest that our approach will have general applications in studying viral-host interactions in model systems and clinical biospecimens.

Detecting false-positive signals in exome sequencing

Disease gene discovery has been transformed by affordable sequencing of exomes and genomes. Identification of disease-causing mutations requires sifting through a large number of sequence variants. A subset of the variants are unlikely to be good candidates for disease causation based on one or more of the following criteria: (1) being located in genomic regions known to be highly polymorphic, (2) having characteristics suggesting assembly misalignment, and/or (3) being labeled as variants based on misleading reference genome information. We analyzed exome sequence data from 118 individuals in 29 families seen in the NIH Undiagnosed Diseases Program (UDP) to create lists of variants and genes with these characteristics. Specifically, we identified several groups of genes that are candidates for provisional exclusion during exome analysis: 23,389 positions with excess heterozygosity suggestive of alignment errors and 1,009 positions in which the hg18 human genome reference sequence appeared to contain a minor allele. Exclusion of such variants, which we provide in supplemental lists, will likely enhance identification of disease-causing mutations using exome sequence data.

Genetics of pancreatitis: an update for clinicians and genetic counselors

With novel genetic technologies available, there is a paradigm shift in the way that risk assessments, diagnoses,and therapies for genetic susceptibility syndromes are addressed. Hereditary pancreatitis is among these conditions, for which genetic counseling and next generation sequencing, help families better understand, cope with and live healthier lives. Identifying a genetic etiology to a condition formally believed to be solely environmentally induced can alter the path for treatment for many patients. This finding introduces the concept of gene-environment interactions in human disease and the relationship between genetic predisposition and exposure risk in disease development. The genetic counseling process is complex with medical explanations, psychosocial issues relating to coping with diagnosis, potential future health problems, recurrence risks and family planning. These sometimes difficult conversations can be facilitated by a genetic counselor as a member of the multidisciplinary team. This chapter addresses the intricate medical and psychosocial issues that can arise in the setting of treating patients with hereditary pancreatitis.

De novo sequencing and characterization of Picrorhiza kurrooa transcriptome at two temperatures showed major transcriptome adjustments

BACKGROUND

Picrorhiza kurrooa Royle ex Benth. is an endangered plant species of medicinal importance. The medicinal property is attributed to monoterpenoids picroside I and II, which are modulated by temperature. The transcriptome information of this species is limited with the availability of few hundreds of expressed sequence tags (ESTs) in the public databases. In order to gain insight into temperature mediated molecular changes, high throughput de novo transcriptome sequencing and analyses were carried out at 15 °C and 25 °C, the temperatures known to modulate picrosides content.

RESULTS

Using paired-end (PE) Illumina sequencing technology, a total of 20,593,412 and 44,229,272 PE reads were obtained after quality filtering for 15 °C and 25 °C, respectively. Available (e.g., De-Bruijn/Eulerian graph) and in-house developed bioinformatics tools were used for assembly and annotation of transcriptome. A total of 74,336 assembled transcript sequences were obtained, with an average coverage of 76.6 and average length of 439.5. Guanine-cytosine (GC) content was observed to be 44.6%, while the transcriptome exhibited abundance of trinucleotide simple sequence repeat (SSR; 45.63%) markers.Large scale expression profiling through "read per exon kilobase per million (RPKM)", showed changes in several biological processes and metabolic pathways including cytochrome P450s (CYPs), UDP-glycosyltransferases (UGTs) and those associated with picrosides biosynthesis. RPKM data were validated by reverse transcriptase-polymerase chain reaction using a set of 19 genes, wherein 11 genes behaved in accordance with the two expression methods.

CONCLUSIONS

Study generated transcriptome of P. kurrooa at two different temperatures. Large scale expression profiling through RPKM showed major transcriptome changes in response to temperature reflecting alterations in major biological processes and metabolic pathways, and provided insight of GC content and SSR markers. Analysis also identified putative CYPs and UGTs that could help in discovering the hitherto unknown genes associated with picrosides biosynthesis.

Targeted parallel sequencing of large genetically-defined genomic regions for identifying mutations in Arabidopsis

Large-scale genetic screens in Arabidopsis are a powerful approach for molecular dissection of complex signaling networks. However, map-based cloning can be time-consuming or even hampered due to low chromosomal recombination. Current strategies using next generation sequencing for molecular identification of mutations require whole genome sequencing and advanced computational devises and skills, which are not readily accessible or affordable to every laboratory. We have developed a streamlined method using parallel massive sequencing for mutant identification in which only targeted regions are sequenced. This targeted parallel sequencing (TPSeq) method is more cost-effective, straightforward enough to be easily done without specialized bioinformatics expertise, and reliable for identifying multiple mutations simultaneously. Here, we demonstrate its use by identifying three novel nitrate-signaling mutants in Arabidopsis.

New perspectives on the evolution of plant mating systems

BACKGROUND

The remarkable diversity of mating patterns and sexual systems in flowering plants has fascinated evolutionary biologists for more than a century. Enduring questions about this topic include why sexual polymorphisms have evolved independently in over 100 plant families, and why proportions of self- and cross-fertilization often vary dramatically within and among populations. Important new insights concerning the evolutionary dynamics of plant mating systems have built upon a strong foundation of theoretical models and innovative field and laboratory experiments. However, as the pace of advancement in this field has accelerated, it has become increasingly difficult for researchers to follow developments outside their primary area of research expertise.

SCOPE

In this Viewpoint paper we highlight three important themes that span and integrate different subdisciplines: the changes in morphology, phenology, and physiology that accompany the transition to selfing; the evolutionary consequences of pollen pool diversity in flowering plants; and the evolutionary dynamics of sexual polymorphisms. We also highlight recent developments in molecular techniques that will facilitate more efficient and cost-effective study of mating patterns in large natural populations, research on the dynamics of pollen transport, and investigations on the genetic basis of sexual polymorphisms. This Viewpoint also serves as the introduction to a Special Issue on the Evolution of Plant Mating Systems. The 15 papers in this special issue provide inspiring examples of recent discoveries, and glimpses of exciting developments yet to come.

Pharmacogenomics: what is next?

Pharmacogenomics is moving from a candidate gene strategy to large scale approaches. This is in line with the new paradigm of linking a trait to (a) pathway(s) rather than to single genes. In addition, breakthroughs in genomics offer a non-a priori assessment of implicated genes, expanding the possibilities in pharmacogenomics research. In this review, we discuss the pros and cons of new concepts in study design and on high throughput approaches to be implemented in the near future.

Identification of transcriptome SNPs between Xiphophorus lines and species for assessing allele specific gene expression within F₁ interspecies hybrids

Variations in gene expression are essential for the evolution of novel phenotypes and for speciation. Studying allelic specific gene expression (ASGE) within interspecies hybrids provides a unique opportunity to reveal underlying mechanisms of genetic variation. Using Xiphophorus interspecies hybrid fishes and high-throughput next generation sequencing technology, we were able to assess variations between two closely related vertebrate species, Xiphophorus maculatus and Xiphophorus couchianus, and their F(1) interspecies hybrids. We constructed transcriptome-wide SNP polymorphism sets between two highly inbred X. maculatus lines (JP 163 A and B), and between X. maculatus and a second species, X. couchianus. The X. maculatus JP 163 A and B parental lines have been separated in the laboratory for ≈70 years and we were able to identify SNPs at a resolution of 1 SNP per 49 kb of transcriptome. In contrast, SNP polymorphisms between X. couchianus and X. maculatus species, which diverged ≈5-10 million years ago, were identified about every 700 bp. Using 6524 transcripts with identified SNPs between the two parental species (X. maculatus and X. couchianus), we mapped RNA-seq reads to determine ASGE within F(1) interspecies hybrids. We developed an in silico X. couchianus transcriptome by replacing 90,788 SNP bases for X. maculatus transcriptome with the consensus X. couchianus SNP bases and provide evidence that this procedure overcomes read mapping biases. Employment of the in silico reference transcriptome and tolerating 5 mismatches during read mapping allow direct assessment of ASGE in the F(1) interspecies hybrids. Overall, these results show that Xiphophorus is a tractable vertebrate experimental model to investigate how genetic variations that occur during speciation may affect gene interactions and the regulation of gene expression.

The Charophycean green algae as model systems to study plant cell walls and other evolutionary adaptations that gave rise to land plants

The Charophycean green algae (CGA) occupy a key phylogenetic position as the evolutionary grade that includes the sister group of the land plants (embryophytes), and so provide potentially valuable experimental systems to study the development and evolution of traits that were necessary for terrestrial colonization. The nature and molecular bases of such traits are still being determined, but one critical adaptation is thought to have been the evolution of a complex cell wall. Very little is known about the identity, origins and diversity of the biosynthetic machinery producing the major suites of structural polymers (i. e., cell wall polysaccharides and associated molecules) that must have been in place for land colonization. However, it has been suggested that the success of the earliest land plants was partly based on the frequency of gene duplication, and possibly whole genome duplications, during times of radical habitat changes. Orders of the CGA span early diverging taxa retaining more ancestral characters, through complex multicellular organisms with morphological characteristics resembling those of land plants. Examination of gene diversity and evolution within the CGA could help reveal when and how the molecular pathways required for synthesis of key structural polymers in land plants arose.

RNA-Seq Assembly - Are We There Yet?

Transcriptomic sequence resources represent invaluable assets for research, in particular for non-model species without a sequenced genome. To date, the Next Generation Sequencing technologies 454/Roche and Illumina have been used to generate transcriptome sequence databases by mRNA-Seq for more than fifty different plant species. While some of the databases were successfully used for downstream applications, such as proteomics, the assembly parameters indicate that the assemblies do not yet accurately reflect the actual plant transcriptomes. Two different assembly strategies have been used, overlap consensus based assemblers for long reads and Eulerian path/de Bruijn graph assembler for short reads. In this review, we discuss the challenges and solutions to the transcriptome assembly problem. A list of quality control parameters and the necessary scripts to produce them are provided.

Multiplex Chromosomal Exome Sequencing Accelerates Identification of ENU-Induced Mutations in the Mouse

Forward genetic screens in Mus musculus have proved powerfully informative by revealing unsuspected mechanisms governing basic biological processes. This approach uses potent chemical mutagens, such as N-ethyl-N-nitrosourea (ENU), to randomly induce mutations in mice, which are then bred and phenotypically screened to identify lines that disrupt a specific biological process of interest. Although identifying a mutation using the rich resources of mouse genetics is straightforward, it is unfortunately neither fast nor cheap. Here we show that detecting newly induced causal variants in a forward genetic screen can be accelerated dramatically using a methodology that combines multiplex chromosome-specific exome capture, next-generation sequencing, rapid mapping, sequence annotation, and variation filtering. The key innovation of our method is multiplex capture and sequence that allows the simultaneous survey of both mutant, parental, and background strains in a single experiment. By comparing variants identified in mutant offspring with those found in dbSNP, the unmutagenized background strains, and parental lines, induced causative mutations can be distinguished immediately from preexisting variation or experimental artifact. Here we demonstrate this approach to find the causative mutations induced in four novel ENU lines identified from a recent ENU screen. In all four cases, after applying our method, we found six or fewer putative mutations (and sometimes only a single one). Determining the causative variant was then easily achieved through standard segregation approaches. We have developed this process into a community resource that will speed up individual labs’ ability to identify the genetic lesion in mutant mouse lines; all of our reagents and software tools are open source and available to the broader scientific community.

The quest for rare variants: pooled multiplexed next generation sequencing in plants

Next generation sequencing (NGS) instruments produce an unprecedented amount of sequence data at contained costs. This gives researchers the possibility of designing studies with adequate power to identify rare variants at a fraction of the economic and labor resources required by individual Sanger sequencing. As of today, few research groups working in plant sciences have exploited this potentiality, showing that pooled NGS provides results in excellent agreement with those obtained by individual Sanger sequencing. The aim of this review is to convey to the reader the general ideas underlying the use of pooled NGS for the identification of rare variants. To facilitate a thorough understanding of the possibilities of the method, we will explain in detail the possible experimental and analytical approaches and discuss their advantages and disadvantages. We will show that information on allele frequency obtained by pooled NGS can be used to accurately compute basic population genetics indexes such as allele frequency, nucleotide diversity, and Tajima's D. Finally, we will discuss applications and future perspectives of the multiplexed NGS approach.

A Survey of MicroRNA Length Variants Contributing to miRNome Complexity in Peach (Prunus Persica L.)

MicroRNAs (miRNAs) are short non-coding RNA molecules produced from hairpin structures and involved in gene expression regulation with major roles in plant development and stress response. Although each annotated miRNA in miRBase (www.mirbase.org) is a single defined sequence with no further details on possible variable sequence length, isomiRs - namely the population of variants of miRNAs coming from the same precursors - have been identified in several species and could represent a way of broadening the regulatory network of the cell. Next-gen-based sequencing makes it possible to comprehensively and accurately assess the entire miRNA repertoire including isomiRs. The aim of this work was to survey the complexity of the peach miRNome by carrying out Illumina high-throughput sequencing of miRNAs in three replicates of five biological samples arising from a set of different peach organs and/or phenological stages. Three hundred-ninety-two isomiRs (miRNA and miRNA*-related) corresponding to 26 putative miRNA coding loci, have been highlighted by mirDeep-P and analyzed. The presence of the same isomiRs in different biological replicates of a sample and in different tissues demonstrates that the generation of most of the detected isomiRs is not random. The degree of mature sequence heterogeneity is very different for each individual locus. Results obtained in the present work can thus contribute to a deeper view of the miRNome complexity and to better explore the mechanism of action of these tiny regulators.

Next generation quantitative genetics in plants

Most characteristics in living organisms show continuous variation, which suggests that they are controlled by multiple genes. Quantitative trait loci (QTL) analysis can identify the genes underlying continuous traits by establishing associations between genetic markers and observed phenotypic variation in a segregating population. The new high-throughput sequencing (HTS) technologies greatly facilitate QTL analysis by providing genetic markers at genome-wide resolution in any species without previous knowledge of its genome. In addition HTS serves to quantify molecular phenotypes, which aids to identify the loci responsible for QTLs and to understand the mechanisms underlying diversity. The constant improvements in price, experimental protocols, computational pipelines, and statistical frameworks are making feasible the use of HTS for any research group interested in quantitative genetics. In this review I discuss the application of HTS for molecular marker discovery, population genotyping, and expression profiling in QTL analysis.

Applications of next-generation sequencing technologies to diagnostic virology

Novel DNA sequencing techniques, referred to as “next-generation” sequencing (NGS), provide high speed and throughput that can produce an enormous volume of sequences with many possible applications in research and diagnostic settings. In this article, we provide an overview of the many applications of NGS in diagnostic virology. NGS techniques have been used for high-throughput whole viral genome sequencing, such as sequencing of new influenza viruses, for detection of viral genome variability and evolution within the host, such as investigation of human immunodeficiency virus and human hepatitis C virus quasispecies, and monitoring of low-abundance antiviral drug-resistance mutations. NGS techniques have been applied to metagenomics-based strategies for the detection of unexpected disease-associated viruses and for the discovery of novel human viruses, including cancer-related viruses. Finally, the human virome in healthy and disease conditions has been described by NGS-based metagenomics.

Next generation sequencing technologies for insect virus discovery

Insects are commonly infected with multiple viruses including those that cause sublethal, asymptomatic, and latent infections. Traditional methods for virus isolation typically lack the sensitivity required for detection of such viruses that are present at low abundance. In this respect, next generation sequencing technologies have revolutionized methods for the discovery and identification of new viruses from insects. Here we review both traditional and modern methods for virus discovery, and outline analysis of transcriptome and small RNA data for identification of viral sequences. We will introduce methods for de novo assembly of viral sequences, identification of potential viral sequences from BLAST data, and bioinformatics for generating full-length or near full-length viral genome sequences. We will also discuss implications of the ubiquity of viruses in insects and in insect cell lines. All of the methods described in this article can also apply to the discovery of viruses in other organisms.

Large-scale transcriptome analysis in chickpea (Cicer arietinum L.), an orphan legume crop of the semi-arid tropics of Asia and Africa

Chickpea (Cicer arietinum L.) is an important legume crop in the semi-arid regions of Asia and Africa. Gains in crop productivity have been low however, particularly because of biotic and abiotic stresses. To help enhance crop productivity using molecular breeding techniques, next generation sequencing technologies such as Roche/454 and Illumina/Solexa were used to determine the sequence of most gene transcripts and to identify drought-responsive genes and gene-based molecular markers. A total of 103,215 tentative unique sequences (TUSs) have been produced from 435,018 Roche/454 reads and 21,491 Sanger expressed sequence tags (ESTs). Putative functions were determined for 49,437 (47.8%) of the TUSs, and gene ontology assignments were determined for 20,634 (41.7%) of the TUSs. Comparison of the chickpea TUSs with the Medicago truncatula genome assembly (Mt 3.5.1 build) resulted in 42,141 aligned TUSs with putative gene structures (including 39,281 predicted intron/splice junctions). Alignment of ∼37 million Illumina/Solexa tags generated from drought-challenged root tissues of two chickpea genotypes against the TUSs identified 44,639 differentially expressed TUSs. The TUSs were also used to identify a diverse set of markers, including 728 simple sequence repeats (SSRs), 495 single nucleotide polymorphisms (SNPs), 387 conserved orthologous sequence (COS) markers, and 2088 intron-spanning region (ISR) markers. This resource will be useful for basic and applied research for genome analysis and crop improvement in chickpea.

From RNA-seq to large-scale genotyping - genomics resources for rye (Secale cereale L.)

BACKGROUND

The improvement of agricultural crops with regard to yield, resistance and environmental adaptation is a perpetual challenge for both breeding and research. Exploration of the genetic potential and implementation of genome-based breeding strategies for efficient rye (Secale cereale L.) cultivar improvement have been hampered by the lack of genome sequence information. To overcome this limitation we sequenced the transcriptomes of five winter rye inbred lines using Roche/454 GS FLX technology.

RESULTS

More than 2.5 million reads were assembled into 115,400 contigs representing a comprehensive rye expressed sequence tag (EST) resource. From sequence comparisons 5,234 single nucleotide polymorphisms (SNPs) were identified to develop the Rye5K high-throughput SNP genotyping array. Performance of the Rye5K SNP array was investigated by genotyping 59 rye inbred lines including the five lines used for sequencing, and five barley, three wheat, and two triticale accessions. A balanced distribution of allele frequencies ranging from 0.1 to 0.9 was observed. Residual heterozygosity of the rye inbred lines varied from 4.0 to 20.4% with higher average heterozygosity in the pollen compared to the seed parent pool.

CONCLUSIONS

The established sequence and molecular marker resources will improve and promote genetic and genomic research as well as genome-based breeding in rye.

Partial short-read sequencing of a highly inbred Iberian pig and genomics inference thereof

Despite dramatic reduction in sequencing costs with the advent of next generation sequencing technologies, obtaining a complete mammalian genome sequence at sufficient depth is still costly. An alternative is partial sequencing. Here, we have sequenced a reduced representation library of an Iberian sow from the Guadyerbas strain, a highly inbred strain that has been used in numerous QTL studies because of its extreme phenotypic characteristics. Using the Illumina Genome Analyzer II (San Diego, CA, USA), we resequenced ∼ 1% of the genome with average 4 × depth, identifying 68,778 polymorphisms. Of these, 55,457 were putative fixed differences with respect to the assembly, based on the genome of a Duroc pig, and 13,321 were heterozygous positions within Guadyerbas. Despite being highly inbred, the estimate of heterozygosity within Guadyerbas was ∼ 0.78 kb(-1) in autosomes, after correcting for low depth. Nucleotide variability was consistently higher at the telomeric regions than on the rest of the chromosome, likely a result of increased recombination rates. Further, variability was 50% lower in the X-chromosome than in autosomes, which may be explained by a recent bottleneck or by selection. We divided the whole genome in 500 kb windows and we analyzed overrepresented gene ontology terms in regions of low and high variability. Multi organism process, pigmentation and cell killing were overrepresented in high variability regions and metabolic process ontology, within low variability regions. Further, a genome wide Hudson-Kreitman-Aguadé test was carried out per window; overall, variability was in agreement with neutral expectations.

Phylogeny, phylogeography, phylobetadiversity and the molecular analysis of biological communities

There has been much recent interest and progress in the characterization of community structure and community assembly processes through the application of phylogenetic methods. To date most focus has been on groups of taxa for which some relevant detail of their ecology is known, for which community composition is reasonably easily quantified and where the temporal scale is such that speciation is not likely to feature. Here, we explore how we might apply a molecular genetic approach to investigate community structure and assembly at broad taxonomic and geographical scales, where we have little knowledge of species ecology, where community composition is not easily quantified, and where speciation is likely to be of some importance. We explore these ideas using the class Collembola as a focal group. Gathering molecular evidence for cryptic diversity suggests that the ubiquity of many species of Collembola across the landscape may belie greater community complexity than would otherwise be assumed. However, this morphologically cryptic species-level diversity poses a challenge for attempts to characterize diversity both within and among local species assemblages. Recent developments in high throughput parallel sequencing technology, combined with mtDNA barcoding, provide an advance that can bring together the fields of phylogenetic and phylogeographic analysis to bear on this problem. Such an approach could be standardized for analyses at any geographical scale for a range of taxonomic groups to quantify the formation and composition of species assemblages.

Estimating allele frequency from next-generation sequencing of pooled mitochondrial DNA samples

Background: Both common and rare mitochondrial DNA (mtDNA) variants may contribute to genetic susceptibility to some complex human diseases. Understanding of the role of mtDNA variants will provide valuable insights into the etiology of these diseases. However, to date, there have not been any large-scale, genome-wide association studies of complete mtDNA variants and disease risk. One reason for this might be the substantial cost of sequencing the large number of samples required for genetic epidemiology studies. Next-generation sequencing of pooled mtDNA samples will dramatically reduce the cost of such studies and may represent an appealing approach for large-scale genetic epidemiology studies. However, the performance of the different designs of sequencing pooled mtDNA has not been evaluated. Methods: We examined the approach of sequencing pooled mtDNA of multiple individuals for estimating allele frequency using the Illumina genome analyzer (GA) II sequencing system. In this study the pool included mtDNA samples of 20 subjects that had been sequenced previously using Sanger sequencing. Each pool was replicated once to assess variation of the sequencing error between pools. To reduce such variation, barcoding was used for sequencing different pools in the same lane of the flow cell. To evaluate the effect of different pooling strategies pooling was done at both the pre- and post-PCR amplification step. Results: The sequencing error rate was close to that expected based on the Phred score. When only reads with Phred ≥ 20 were considered, the average error rate was about 0.3%. However, there was significant variation of the base-calling errors for different types of bases or at different loci. Using the results of the Sanger sequencing as the standard, the sensitivity of single nucleotide polymorphism detection with post-PCR pooling (about 99%) was higher than that of the pre-PCR pooling (about 82%), while the two approaches had similar specificity (about 99%). Among a total of 298 variants in the sample, the allele frequencies of 293 variants (98%) were correctly estimated with post-PCR pooling, the correlation between the estimated and the true allele frequencies being >0.99, while only 206 allele frequencies (69%) were correctly estimated in the pre-PCR pooling, the correlation being 0.89. Conclusion: Sequencing of mtDNA pooled after PCR amplification is a viable tool for screening mitochondrial variants potentially related to human diseases.

Genetic variations and associated pathophysiology in the management of epilepsy

The genomic era has enabled the application of molecular tools to the solution of many of the genetic epilepsies, with and without comorbidities. Massively parallel sequencing has recently reinvigorated gene discovery for the monogenic epilepsies. Recurrent and novel copy number variants have given much-needed impetus to the advancement of our understanding of epilepsies with complex inheritance. Superimposed upon that is the phenotypic blurring by presumed genetic modifiers scattering the effects of the primary mutation. The genotype-first approach has uncovered associated syndrome constellations, of which epilepsy is only one of the syndromes. As the molecular genetic basis for the epilepsies unravels, it will increasingly influence the classification and diagnosis of the epilepsies. The ultimate goal of the molecular revolution has to be the design of treatment protocols based on genetic profiles, and cracking the 30% of epilepsies refractory to current medications, but that still lies well into the future. The current focus is on the scientific basis for epilepsy. Understanding its genetic causes and biophysical mechanisms is where we are currently positioned: prizing the causes of epilepsy "out of the shadows" and exposing its underlying mechanisms beyond even the ion-channels.

A role for noncanonical microRNAs in the mammalian brain revealed by phenotypic differences in Dgcr8 versus Dicer1 knockouts and small RNA sequencing

Noncanonical microRNAs (miRNAs) and endogenous small interfering RNAs (endo-siRNAs) are distinct subclasses of small RNAs that bypass the DGCR8/DROSHA Microprocessor but still require DICER1 for their biogenesis. What role, if any, they have in mammals remains unknown. To identify potential functional properties for these subclasses, we compared the phenotypes resulting from conditional deletion of Dgcr8 versus Dicer1 in post-mitotic neurons. The loss of Dicer1 resulted in an earlier lethality, more severe structural abnormalities, and increased apoptosis relative to that from Dgcr8 loss. Deep sequencing of small RNAs from the hippocampus and cortex of the conditional knockouts and control littermates identified multiple noncanonical microRNAs that were expressed at high levels in the brain relative to other tissues, including mirtrons and H/ACA snoRNA-derived small RNAs. In contrast, we found no evidence for endo-siRNAs in the brain. Taken together, our findings provide evidence for a diverse population of highly expressed noncanonical miRNAs that together are likely to play important functional roles in post-mitotic neurons.