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September 22, 2019

Transcriptional fates of human-specific segmental duplications in brain.

Despite the importance of duplicate genes for evolutionary adaptation, accurate gene annotation is often incomplete, incorrect, or lacking in regions of segmental duplication. We developed an approach combining long-read sequencing and hybridization capture to yield full-length transcript information and confidently distinguish between nearly identical genes/paralogs. We used biotinylated probes to enrich for full-length cDNA from duplicated regions, which were then amplified, size-fractionated, and sequenced using single-molecule, long-read sequencing technology, permitting us to distinguish between highly identical genes by virtue of multiple paralogous sequence variants. We examined 19 gene families as expressed in developing and adult human brain, selected for their high sequence identity (average >99%) and overlap with human-specific segmental duplications (SDs). We characterized the transcriptional differences between related paralogs to better understand the birth-death process of duplicate genes and particularly how the process leads to gene innovation. In 48% of the cases, we find that the expressed duplicates have changed substantially from their ancestral models due to novel sites of transcription initiation, splicing, and polyadenylation, as well as fusion transcripts that connect duplication-derived exons with neighboring genes. We detect unannotated open reading frames in genes currently annotated as pseudogenes, while relegating other duplicates to nonfunctional status. Our method significantly improves gene annotation, specifically defining full-length transcripts, isoforms, and open reading frames for new genes in highly identical SDs. The approach will be more broadly applicable to genes in structurally complex regions of other genomes where the duplication process creates novel genes important for adaptive traits.© 2018 Dougherty et al.; Published by Cold Spring Harbor Laboratory Press.


September 22, 2019

The state of play in higher eukaryote gene annotation.

A genome sequence is worthless if it cannot be deciphered; therefore, efforts to describe – or ‘annotate’ – genes began as soon as DNA sequences became available. Whereas early work focused on individual protein-coding genes, the modern genomic ocean is a complex maelstrom of alternative splicing, non-coding transcription and pseudogenes. Scientists – from clinicians to evolutionary biologists – need to navigate these waters, and this has led to the design of high-throughput, computationally driven annotation projects. The catalogues that are being produced are key resources for genome exploration, especially as they become integrated with expression, epigenomic and variation data sets. Their creation, however, remains challenging.


September 22, 2019

Full-length transcriptome of Misgurnus anguillicaudatus provides insights into evolution of genus Misgurnus.

Reconstruction and annotation of transcripts, particularly for a species without reference genome, plays a critical role in gene discovery, investigation of genomic signatures, and genome annotation in the pre-genomic era. This study generated 33,330 full-length transcripts of diploid M. anguillicaudatus using PacBio SMRT Sequencing. A total of 6,918 gene families were identified with two or more isoforms, and 26,683 complete ORFs with an average length of 1,497?bp were detected. Totally, 1,208 high-confidence lncRNAs were identified, and most of these appeared to be precursor transcripts of miRNAs or snoRNAs. Phylogenetic tree of the Misgurnus species was inferred based on the 1,905 single copy orthologous genes. The tetraploid and diploid M. anguillicaudatus grouped into a clade, and M. bipartitus showed a closer relationship with the M. anguillicaudatus. The overall evolutionary rates of tetraploid M. anguillicaudatus were significantly higher than those of other Misgurnus species. Meanwhile, 28 positively selected genes were identified in M. anguillicaudatus clade. These positively selected genes may play critical roles in the adaptation to various habitat environments for M. anguillicaudatus. This study could facilitate further exploration of the genomic signatures of M. anguillicaudatus and provide potential insights into unveiling the evolutionary history of tetraploid loach.


September 22, 2019

Bacteroides dorei dominates gut microbiome prior to autoimmunity in Finnish children at high risk for type 1 diabetes.

The incidence of the autoimmune disease, type 1 diabetes (T1D), has increased dramatically over the last half century in many developed countries and is particularly high in Finland and other Nordic countries. Along with genetic predisposition, environmental factors are thought to play a critical role in this increase. As with other autoimmune diseases, the gut microbiome is thought to play a potential role in controlling progression to T1D in children with high genetic risk, but we know little about how the gut microbiome develops in children with high genetic risk for T1D. In this study, the early development of the gut microbiomes of 76 children at high genetic risk for T1D was determined using high-throughput 16S rRNA gene sequencing. Stool samples from children born in the same hospital in Turku, Finland were collected at monthly intervals beginning at 4-6 months after birth until 2.2 years of age. Of those 76 children, 29 seroconverted to T1D-related autoimmunity (cases) including 22 who later developed T1D, the remaining 47 subjects remained healthy (controls). While several significant compositional differences in low abundant species prior to seroconversion were found, one highly abundant group composed of two closely related species, Bacteroides dorei and Bacteroides vulgatus, was significantly higher in cases compared to controls prior to seroconversion. Metagenomic sequencing of samples high in the abundance of the B. dorei/vulgatus group before seroconversion, as well as longer 16S rRNA sequencing identified this group as Bacteroides dorei. The abundance of B. dorei peaked at 7.6 months in cases, over 8 months prior to the appearance of the first islet autoantibody, suggesting that early changes in the microbiome may be useful for predicting T1D autoimmunity in genetically susceptible infants. The cause of increased B. dorei abundance in cases is not known but its timing appears to coincide with the introduction of solid food.


September 22, 2019

Fungal ITS1 deep-sequencing strategies to reconstruct the composition of a 26-species community and evaluation of the gut mycobiota of healthy Japanese individuals.

The study of mycobiota remains relatively unexplored due to the lack of sufficient available reference strains and databases compared to those of bacterial microbiome studies. Deep sequencing of Internal Transcribed Spacer (ITS) regions is the de facto standard for fungal diversity analysis. However, results are often biased because of the wide variety of sequence lengths in the ITS regions and the complexity of high-throughput sequencing (HTS) technologies. In this study, a curated ITS database, ntF-ITS1, was constructed. This database can be utilized for the taxonomic assignment of fungal community members. We evaluated the efficacy of strategies for mycobiome analysis by using this database and characterizing a mock fungal community consisting of 26 species representing 15 genera using ITS1 sequencing with three HTS platforms: Illumina MiSeq (MiSeq), Ion Torrent Personal Genome Machine (IonPGM), and Pacific Biosciences (PacBio). Our evaluation demonstrated that PacBio’s circular consensus sequencing with greater than 8 full-passes most accurately reconstructed the composition of the mock community. Using this strategy for deep-sequencing analysis of the gut mycobiota in healthy Japanese individuals revealed two major mycobiota types: a single-species type composed of Candida albicans or Saccharomyces cerevisiae and a multi-species type. In this study, we proposed the best possible processing strategies for the three sequencing platforms, of which, the PacBio platform allowed for the most accurate estimation of the fungal community. The database and methodology described here provide critical tools for the emerging field of mycobiome studies.


September 22, 2019

Molecular mechanisms of acclimatization to phosphorus starvation and recovery underlying full-length transcriptome profiling in barley (Hordeum vulgare L.).

A lack of phosphorus (P) in plants can severely constrain growth and development. Barley, one of the earliest domesticated crops, is extensively planted in poor soil around the world. To date, the molecular mechanisms of enduring low phosphorus, at the transcriptional level, in barley are still unclear. In the present study, two different barley genotypes (GN121 and GN42)-with contrasting phosphorus efficiency-were used to reveal adaptations to low phosphorus stress, at three time points, at the morphological, physiological, biochemical, and transcriptome level. GN121 growth was less affected by phosphorus starvation and recovery than that of GN42. The biomass and inorganic phosphorus concentration of GN121 and GN42 declined under the low phosphorus-induced stress and increased after recovery with normal phosphorus. However, the range of these parameters was higher in GN42 than in GN121. Subsequently, a more complete genome annotation was obtained by correcting with the data sequenced on Illumina HiSeq X 10 and PacBio RSII SMRT platform. A total of 6,182 and 5,270 differentially expressed genes (DEGs) were identified in GN121 and GN42, respectively. The majority of these DEGs were involved in phosphorus metabolism such as phospholipid degradation, hydrolysis of phosphoric enzymes, sucrose synthesis, phosphorylation/dephosphorylation and post-transcriptional regulation; expression of these genes was significantly different between GN121 and GN42. Specifically, six and seven DEGs were annotated as phosphorus transporters in roots and leaves, respectively. Furthermore, a putative model was constructed relying on key metabolic pathways related to phosphorus to illustrate the higher phosphorus efficiency of GN121 compared to GN42 under low phosphorus conditions. Results from this study provide a multi-transcriptome database and candidate genes for further study on phosphorus use efficiency (PUE).


September 22, 2019

Somatic APP gene recombination in Alzheimer’s disease and normal neurons.

The diversity and complexity of the human brain are widely assumed to be encoded within a constant genome. Somatic gene recombination, which changes germline DNA sequences to increase molecular diversity, could theoretically alter this code but has not been documented in the brain, to our knowledge. Here we describe recombination of the Alzheimer’s disease-related gene APP, which encodes amyloid precursor protein, in human neurons, occurring mosaically as thousands of variant ‘genomic cDNAs’ (gencDNAs). gencDNAs lacked introns and ranged from full-length cDNA copies of expressed, brain-specific RNA splice variants to myriad smaller forms that contained intra-exonic junctions, insertions, deletions, and/or single nucleotide variations. DNA in situ hybridization identified gencDNAs within single neurons that were distinct from wild-type loci and absent from non-neuronal cells. Mechanistic studies supported neuronal ‘retro-insertion’ of RNA to produce gencDNAs; this process involved transcription, DNA breaks, reverse transcriptase activity, and age. Neurons from individuals with sporadic Alzheimer’s disease showed increased gencDNA diversity, including eleven mutations known to be associated with familial Alzheimer’s disease that were absent from healthy neurons. Neuronal gene recombination may allow ‘recording’ of neural activity for selective ‘playback’ of preferred gene variants whose expression bypasses splicing; this has implications for cellular diversity, learning and memory, plasticity, and diseases of the human brain.


September 22, 2019

Active microorganisms in forest soils differ from the total community yet are shaped by the same environmental factors: the influence of pH and soil moisture.

Predicting the impact of environmental change on soil microbial functions requires an understanding of how environmental factors shape microbial composition. Here, we investigated the influence of environmental factors on bacterial and fungal communities across an expanse of northern hardwood forest in Michigan, USA, which spans a 500-km regional climate gradient. We quantified soil microbial community composition using high-throughput DNA sequencing on coextracted rDNA (i.e. total community) and rRNA (i.e. active community). Within both bacteria and fungi, total and active communities were compositionally distinct from one another across the regional gradient (bacteria P = 0.01; fungi P < 0.01). Taxonomically, the active community was a subset of the total community. Compositional differences between total and active communities reflected changes in the relative abundance of dominant taxa. The composition of both the total and active microbial communities varied by site across the gradient (P < 0.01) and was shaped by differences in soil moisture, pH, SOM carboxyl content, as well as C and N concentration. Our study highlights the importance of distinguishing between metabolically active microorganisms and the total community, and emphasizes that the same environmental factors shape the total and active communities of bacteria and fungi in this ecosystem.© FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.


September 22, 2019

MEGAN-LR: new algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs.

There are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing, and there is a need to adapt short read tools to long read datasets.We describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.All presented methods are implemented in the open source edition of MEGAN, and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.This article was reviewed by Nicola Segata together with Moreno Zolfo, Pete James Lockhart and Serghei Mangul.This work extends the applicability of the widely-used metagenomic analysis software MEGAN to long reads. Our study suggests that the presented LAST+MEGAN-LR pipeline is sufficiently fast and accurate.


September 22, 2019

Fusion of TTYH1 with the C19MC microRNA cluster drives expression of a brain-specific DNMT3B isoform in the embryonal brain tumor ETMR.

Embryonal tumors with multilayered rosettes (ETMRs) are rare, deadly pediatric brain tumors characterized by high-level amplification of the microRNA cluster C19MC. We performed integrated genetic and epigenetic analyses of 12 ETMR samples and identified, in all cases, C19MC fusions to TTYH1 driving expression of the microRNAs. ETMR tumors, cell lines and xenografts showed a specific DNA methylation pattern distinct from those of other tumors and normal tissues. We detected extreme overexpression of a previously uncharacterized isoform of DNMT3B originating at an alternative promoter that is active only in the first weeks of neural tube development. Transcriptional and immunohistochemical analyses suggest that C19MC-dependent DNMT3B deregulation is mediated by RBL2, a known repressor of DNMT3B. Transfection with individual C19MC microRNAs resulted in DNMT3B upregulation and RBL2 downregulation in cultured cells. Our data suggest a potential oncogenic re-engagement of an early developmental program in ETMR via epigenetic alteration mediated by an embryonic, brain-specific DNMT3B isoform.


September 22, 2019

Interaction between the microbiome and TP53 in human lung cancer.

Lung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesize that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from 33 controls and 143 cancer cases, we conduct 16S ribosomal RNA (rRNA) bacterial gene sequencing, with RNA-sequencing data from lung cancer cases in The Cancer Genome Atlas serving as the validation cohort.Overall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma specifically, a separate group of taxa are identified, in which Acidovorax is enriched in smokers. Acidovorax temporans is identified within tumor sections by fluorescent in situ hybridization and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax, exhibit higher abundance among the subset of squamous cell carcinoma cases with TP53 mutations, an association not seen in adenocarcinomas.The results of this comprehensive study show both microbiome-gene and microbiome-exposure interactions in squamous cell carcinoma lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can impair epithelial function, have a unique bacterial consortium that is higher in relative abundance in smoking-associated tumors of this type. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection.


September 22, 2019

Extensive horizontal gene transfer in cheese-associated bacteria.

Acquisition of genes through horizontal gene transfer (HGT) allows microbes to rapidly gain new capabilities and adapt to new or changing environments. Identifying widespread HGT regions within multispecies microbiomes can pinpoint the molecular mechanisms that play key roles in microbiome assembly. We sought to identify horizontally transferred genes within a model microbiome, the cheese rind. Comparing 31 newly sequenced and 134 previously sequenced bacterial isolates from cheese rinds, we identified over 200 putative horizontally transferred genomic regions containing 4733 protein coding genes. The largest of these regions are enriched for genes involved in siderophore acquisition, and are widely distributed in cheese rinds in both Europe and the US. These results suggest that HGT is prevalent in cheese rind microbiomes, and that identification of genes that are frequently transferred in a particular environment may provide insight into the selective forces shaping microbial communities.


September 22, 2019

Multiscale patterns and drivers of arbuscular mycorrhizal fungal communities in the roots and root-associated soil of a wild perennial herb.

Arbuscular mycorrhizal (AM) fungi form diverse communities and are known to influence above-ground community dynamics and biodiversity. However, the multiscale patterns and drivers of AM fungal composition and diversity are still poorly understood. We sequenced DNA markers from roots and root-associated soil from Plantago lanceolata plants collected across multiple spatial scales to allow comparison of AM fungal communities among neighbouring plants, plant subpopulations, nearby plant populations, and regions. We also measured soil nutrients, temperature, humidity, and community composition of neighbouring plants and nonAM root-associated fungi. AM fungal communities were already highly dissimilar among neighbouring plants (c. 30 cm apart), albeit with a high variation in the degree of similarity at this small spatial scale. AM fungal communities were increasingly, and more consistently, dissimilar at larger spatial scales. Spatial structure and environmental drivers explained a similar percentage of the variation, from 7% to 25%. A large fraction of the variation remained unexplained, which may be a result of unmeasured environmental variables, species interactions and stochastic processes. We conclude that AM fungal communities are highly variable among nearby plants. AM fungi may therefore play a major role in maintaining small-scale variation in community dynamics and biodiversity.© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.


September 22, 2019

Next generation sequencing data of a defined microbial mock community.

Generating sequence data of a defined community composed of organisms with complete reference genomes is indispensable for the benchmarking of new genome sequence analysis methods, including assembly and binning tools. Moreover the validation of new sequencing library protocols and platforms to assess critical components such as sequencing errors and biases relies on such datasets. We here report the next generation metagenomic sequence data of a defined mock community (Mock Bacteria ARchaea Community; MBARC-26), composed of 23 bacterial and 3 archaeal strains with finished genomes. These strains span 10 phyla and 14 classes, a range of GC contents, genome sizes, repeat content and encompass a diverse abundance profile. Short read Illumina and long-read PacBio SMRT sequences of this mock community are described. These data represent a valuable resource for the scientific community, enabling extensive benchmarking and comparative evaluation of bioinformatics tools without the need to simulate data. As such, these data can aid in improving our current sequence data analysis toolkit and spur interest in the development of new tools.


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