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September 22, 2019

A survey of transcriptome complexity in Sus scrofa using single-molecule long-read sequencing.

Alternative splicing (AS) and fusion transcripts produce a vast expansion of transcriptomes and proteomes diversity. However, the reliability of these events and the extend of epigenetic mechanisms have not been adequately addressed due to its limitation of uncertainties about the complete structure of mRNA. Here we combined single-molecule real-time sequencing, Illumina RNA-seq and DNA methylation data to characterize the landscapes of DNA methylation on AS, fusion isoforms formation and lncRNA feature and further to unveil the transcriptome complexity of pig. Our analysis identified an unprecedented scale of high-quality full-length isoforms with over 28,127 novel isoforms from 26,881 novel genes. More than 92,000 novel AS events were detected and intron retention predominated in AS model, followed by exon skipping. Interestingly, we found that DNA methylation played an important role in generating various AS isoforms by regulating splicing sites, promoter regions and first exons. Furthermore, we identified a large of fusion transcripts and novel lncRNAs, and found that DNA methylation of the promoter and gene body could regulate lncRNA expression. Our results significantly improved existed gene models of pig and unveiled that pig AS and epigenetic modify were more complex than previously thought.


September 22, 2019

Transcriptional diversity during lineage commitment of human blood progenitors.

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine. Copyright © 2014, American Association for the Advancement of Science.


September 22, 2019

Laboratory colonization stabilizes the naturally dynamic microbiome composition of field collected Dermacentor andersoni ticks.

Nearly a quarter of emerging infectious diseases identified in the last century are arthropod-borne. Although ticks and insects can carry pathogenic microorganisms, non-pathogenic microbes make up the majority of their microbial communities. The majority of tick microbiome research has had a focus on discovery and description; very few studies have analyzed the ecological context and functional responses of the bacterial microbiome of ticks. The goal of this analysis was to characterize the stability of the bacterial microbiome of Dermacentor andersoni ticks between generations and two populations within a species.The bacterial microbiome of D. andersoni midguts and salivary glands was analyzed from populations collected at two different ecologically distinct sites by comparing field (F1) and lab-reared populations (F1-F3) over three generations. The microbiome composition of pooled and individual samples was analyzed by sequencing nearly full-length 16S rRNA gene amplicons using a Pacific Biosciences CCS platform that allows identification of bacteria to the species level.In this study, we found that the D. andersoni microbiome was distinct in different geographic populations and was tissue specific, differing between the midgut and the salivary gland, over multiple generations. Additionally, our study showed that the microbiomes of laboratory-reared populations were not necessarily representative of their respective field populations. Furthermore, we demonstrated that the microbiome of a few individual ticks does not represent the microbiome composition at the population level.We demonstrated that the bacterial microbiome of D. andersoni was complex over three generations and specific to tick tissue (midgut vs. salivary glands) as well as geographic location (Burns, Oregon vs. Lake Como, Montana vs. laboratory setting). These results provide evidence that habitat of the tick population is a vital component of the complexity of the bacterial microbiome of ticks, and that the microbiome of lab colonies may not allow for comparative analyses with field populations. A broader understanding of microbiome variation will be required if we are to employ manipulation of the microbiome as a method for interfering with acquisition and transmission of tick-borne pathogens.


September 22, 2019

Defining cell identity with single cell omics.

Cells are a fundamental unit of life, and the ability to study the phenotypes and behaviors of individual cells is crucial to understanding the workings of complex biological systems. Cell phenotypes (epigenomic, transcriptomic, proteomic, and metabolomic) exhibit dramatic heterogeneity between and within the different cell types and states underlying cellular functional diversity. Cell genotypes can also display heterogeneity throughout an organism, in the form of somatic genetic variation-most notably in the emergence and evolution of tumors. Recent technical advances in single-cell isolation and the development of omics approaches sensitive enough to reveal these aspects of cell identity have enabled a revolution in the study of multicellular systems. In this review, we discuss the technologies available to resolve the genomes, epigenomes, transcriptomes, proteomes, and metabolomes of single cells from a wide variety of living systems.© 2018 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


September 22, 2019

Characterization of the human ESC transcriptome by hybrid sequencing.

Although transcriptional and posttranscriptional events are detected in RNA-Seq data from second-generation sequencing, full-length mRNA isoforms are not captured. On the other hand, third-generation sequencing, which yields much longer reads, has current limitations of lower raw accuracy and throughput. Here, we combine second-generation sequencing and third-generation sequencing with a custom-designed method for isoform identification and quantification to generate a high-confidence isoform dataset for human embryonic stem cells (hESCs). We report 8,084 RefSeq-annotated isoforms detected as full-length and an additional 5,459 isoforms predicted through statistical inference. Over one-third of these are novel isoforms, including 273 RNAs from gene loci that have not previously been identified. Further characterization of the novel loci indicates that a subset is expressed in pluripotent cells but not in diverse fetal and adult tissues; moreover, their reduced expression perturbs the network of pluripotency-associated genes. Results suggest that gene identification, even in well-characterized human cell lines and tissues, is likely far from complete.


September 22, 2019

Identification of differentially expressed splice variants by the proteogenomic pipeline Splicify.

Proteogenomics, i.e. comprehensive integration of genomics and proteomics data, is a powerful approach identifying novel protein biomarkers. This is especially the case for proteins that differ structurally between disease and control conditions. As tumor development is associated with aberrant splicing, we focus on this rich source of cancer specific biomarkers. To this end, we developed a proteogenomic pipeline, Splicify, which is able to detect differentially expressed protein isoforms. Splicify is based on integrating RNA massive parallel sequencing data and tandem mass spectrometry proteomics data to identify protein isoforms resulting from differential splicing between two conditions. Proof of concept was obtained by applying Splicify to RNA sequencing and mass spectrometry data obtained from colorectal cancer cell line SW480, before and after siRNA-mediated down-modulation of the splicing factors SF3B1 and SRSF1. These analyses revealed 2172 and 149 differentially expressed isoforms, respectively, with peptide confirmation upon knock-down of SF3B1 and SRSF1 compared to their controls. Splice variants identified included RAC1, OSBPL3, MKI67 and SYK. One additional sample was analyzed by PacBio Iso-Seq full-length transcript sequencing after SF3B1 down-modulation. This analysis verified the alternative splicing identified by Splicify and in addition identified novel splicing events that were not represented in the human reference genome annotation. Therefore, Splicify offers a validated proteogenomic data analysis pipeline for identification of disease specific protein biomarkers resulting from mRNA alternative splicing. Splicify is publicly available on GitHub (https://github.com/NKI-TGO/SPLICIFY) and suitable to address basic research questions using pre-clinical model systems as well as translational research questions using patient-derived samples, e.g. allowing to identify clinically relevant biomarkers. Copyright © 2017, The American Society for Biochemistry and Molecular Biology.


September 22, 2019

A survey of the complex transcriptome from the highly polyploid sugarcane genome using full-length isoform sequencing and de novo assembly from short read sequencing.

Despite the economic importance of sugarcane in sugar and bioenergy production, there is not yet a reference genome available. Most of the sugarcane transcriptomic studies have been based on Saccharum officinarum gene indices (SoGI), expressed sequence tags (ESTs) and de novo assembled transcript contigs from short-reads; hence knowledge of the sugarcane transcriptome is limited in relation to transcript length and number of transcript isoforms.The sugarcane transcriptome was sequenced using PacBio isoform sequencing (Iso-Seq) of a pooled RNA sample derived from leaf, internode and root tissues, of different developmental stages, from 22 varieties, to explore the potential for capturing full-length transcript isoforms. A total of 107,598 unique transcript isoforms were obtained, representing about 71% of the total number of predicted sugarcane genes. The majority of this dataset (92%) matched the plant protein database, while just over 2% was novel transcripts, and over 2% was putative long non-coding RNAs. About 56% and 23% of total sequences were annotated against the gene ontology and KEGG pathway databases, respectively. Comparison with de novo contigs from Illumina RNA-Sequencing (RNA-Seq) of the internode samples from the same experiment and public databases showed that the Iso-Seq method recovered more full-length transcript isoforms, had a higher N50 and average length of largest 1,000 proteins; whereas a greater representation of the gene content and RNA diversity was captured in RNA-Seq. Only 62% of PacBio transcript isoforms matched 67% of de novo contigs, while the non-matched proportions were attributed to the inclusion of leaf/root tissues and the normalization in PacBio, and the representation of more gene content and RNA classes in the de novo assembly, respectively. About 69% of PacBio transcript isoforms and 41% of de novo contigs aligned with the sorghum genome, indicating the high conservation of orthologs in the genic regions of the two genomes.The transcriptome dataset should contribute to improved sugarcane gene models and sugarcane protein predictions; and will serve as a reference database for analysis of transcript expression in sugarcane.


September 22, 2019

No assembly required: Full-length MHC class I allele discovery by PacBio circular consensus sequencing.

Single-molecule real-time (SMRT) sequencing technology with the Pacific Biosciences (PacBio) RS II platform offers the potential to obtain full-length coding regions (~1100-bp) from MHC class I cDNAs. Despite the relatively high error rate associated with SMRT technology, high quality sequences can be obtained by circular consensus sequencing (CCS) due to the random nature of the error profile. In the present study we first validated the ability of SMRT-CCS to accurately identify class I transcripts in Mauritian-origin cynomolgus macaques (Macaca fascicularis) that have been characterized previously by cloning and Sanger-based sequencing as well as pyrosequencing approaches. We then applied this SMRT-CCS method to characterize 60 novel full-length class I transcript sequences expressed by a cohort of cynomolgus macaques from China. The SMRT-CCS method described here provides a straightforward protocol for characterization of unfragmented single-molecule cDNA transcripts that will potentially revolutionize MHC class I allele discovery in nonhuman primates and other species. Published by Elsevier Inc.


September 22, 2019

HapIso: An accurate method for the haplotype-specific isoforms reconstruction from long single-molecule reads

Sequencing of RNA provides the possibility to study an individual’s transcriptome landscape and determine allelic expression ratios. Single-molecule protocols generate multi-kilobase reads longer than most transcripts allowing sequencing of complete haplotype isoforms. This allows partitioning the reads into two parental haplotypes. While the read length of the single-molecule protocols is long, the relatively high error rate limits the ability to accurately detect the genetic variants and assemble them into the haplotype-specific isoforms. In this paper, we present HapIso (Haplotype-specific Isoform Reconstruction), a method able to tolerate the relatively high error-rate of the single-molecule platform and partition the isoform reads into the parental alleles. Phasing the reads according to the allele of origin allows our method to efficiently distinguish between the read errors and the true biological mutations. HapIso uses a k-means clustering algorithm aiming to group the reads into two meaningful clusters maximizing the similarity of the reads within cluster and minimizing the similarity of the reads from different clusters. Each cluster corresponds to a parental haplotype. We use family pedigree information to evaluate our approach. Experimental validation suggests that HapIso is able to tolerate the relatively high error-rate and accurately partition the reads into the parental alleles of the isoform transcripts. Furthermore, our method is the first method able to reconstruct the haplotype-specific isoforms from long single-molecule reads. The open source Python implementation of HapIso is freely available for download at https://?github.?com/?smangul1/?HapIso/?.


September 22, 2019

Indoleacrylic acid produced by commensal Peptostreptococcus species suppresses inflammation.

Host factors in the intestine help select for bacteria that promote health. Certain commensals can utilize mucins as an energy source, thus promoting their colonization. However, health conditions such as inflammatory bowel disease (IBD) are associated with a reduced mucus layer, potentially leading to dysbiosis associated with this disease. We characterize the capability of commensal species to cleave and transport mucin-associated monosaccharides and identify several Clostridiales members that utilize intestinal mucins. One such mucin utilizer, Peptostreptococcus russellii, reduces susceptibility to epithelial injury in mice. Several Peptostreptococcus species contain a gene cluster enabling production of the tryptophan metabolite indoleacrylic acid (IA), which promotes intestinal epithelial barrier function and mitigates inflammatory responses. Furthermore, metagenomic analysis of human stool samples reveals that the genetic capability of microbes to utilize mucins and metabolize tryptophan is diminished in IBD patients. Our data suggest that stimulating IA production could promote anti-inflammatory responses and have therapeutic benefits. Copyright © 2017 Elsevier Inc. All rights reserved.


September 22, 2019

Altered expression of the FMR1 splicing variants landscape in premutation carriers.

FMR1 premutation carriers (55-200 CGG repeats) are at risk for developing Fragile X-associated Tremor/Ataxia Syndrome (FXTAS), an adult onset neurodegenerative disorder. Approximately 20% of female carriers will develop Fragile X-associated Primary Ovarian Insufficiency (FXPOI), in addition to a number of clinical problems affecting premutation carriers throughout their life span. Marked elevation in FMR1 mRNA levels have been observed with premutation alleles resulting in RNA toxicity, the leading molecular mechanism proposed for the FMR1 associated disorders observed in premutation carriers. The FMR1 gene undergoes alternative splicing and we have recently reported that the relative abundance of all FMR1 mRNA isoforms is significantly increased in premutation carriers. In this study, we characterized the transcriptional FMR1 isoforms distribution pattern in different tissues and identified a total of 49 isoforms, some of which observed only in premutation carriers and which might play a role in the pathogenesis of FXTAS. Further, we investigated the distribution pattern and expression levels of the FMR1 isoforms in asymptomatic premutation carriers and in those with FXTAS and found no significant differences between the two groups. Our findings suggest that the characterization of the expression levels of the different FMR1 isoforms is fundamental for understanding the regulation of the FMR1 gene as imbalance in their expression could lead to an altered functional diversity with neurotoxic consequences. Their characterization will also help to elucidating the mechanism(s) by which “toxic gain of function” of the FMR1 mRNA may play a role in FXTAS and/or in the other FMR1-associated conditions. Copyright © 2017. Published by Elsevier B.V.


September 22, 2019

Profiling of metabolome and bacterial community dynamics in ensiled Medicago sativa inoculated without or with Lactobacillus plantarum or Lactobacillus buchneri.

Using gas chromatography mass spectrometry and the PacBio single molecule with real-time sequencing technology (SMRT), we analyzed the detailed metabolomic profiles and microbial community dynamics involved in ensiled Medicago sativa (alfalfa) inoculated without or with the homofermenter Lactobacillus plantarum or heterofermenter Lactobacillus buchneri. Our results revealed that 280 substances and 102 different metabolites were present in ensiled alfalfa. Inoculation of L. buchneri led to remarkable up-accumulation in concentrations of 4-aminobutyric acid, some free amino acids, and polyols in ensiled alfalfa, whereas considerable down-accumulation in cadaverine and succinic acid were observed in L. plantarum-inoculated silages. Completely different microbial flora and their successions during ensiling were observed in the control and two types of inoculant-treated silages. Inoculation of the L. plantarum or L. buchneri alters the microbial composition dynamics of the ensiled forage in very different manners. Our study demonstrates that metabolomic profiling analysis provides a deep insight in metabolites in silage. Moreover, the PacBio SMRT method revealed the microbial composition and its succession during the ensiling process at the species level. This provides information regarding the microbial processes underlying silage formation and may contribute to target-based regulation methods to achieve high-quality silage production.


September 22, 2019

Association of gene expression with biomass content and composition in sugarcane.

About 64% of the total aboveground biomass in sugarcane production is from the culm, of which ~90% is present in fiber and sugars. Understanding the transcriptome in the sugarcane culm, and the transcripts that are associated with the accumulation of the sugar and fiber components would facilitate the modification of biomass composition for enhanced biofuel and biomaterial production. The Sugarcane Iso-Seq Transcriptome (SUGIT) database was used as a reference for RNA-Seq analysis of variation in gene expression between young and mature tissues, and between 10 genotypes with varying fiber content. Global expression analysis suggests that each genotype displayed a unique expression pattern, possibly due to different chromosome combinations and maturation amongst these genotypes. Apart from direct sugar- and fiber-related transcripts, the differentially expressed (DE) transcripts in this study belonged to various supporting pathways that are not obviously involved in the accumulation of these major biomass components. The analysis revealed 1,649 DE transcripts between the young and mature tissues, while 555 DE transcripts were found between the low and high fiber genotypes. Of these, 151 and 23 transcripts respectively, were directly involved in sugar and fiber accumulation. Most of the transcripts identified were up-regulated in the young tissues (2 to 22-fold, FDR adjusted p-value <0.05), which could be explained by the more active metabolism in the young tissues compared to the mature tissues in the sugarcane culm. The results of analysis of the contrasting genotypes suggests that due to the large number of genes contributing to these traits, some of the critical DE transcripts could display less than 2-fold differences in expression and might not be easily identified. However, this transcript profiling analysis identified full-length candidate transcripts and pathways that were likely to determine the differences in sugar and fiber accumulation between tissue types and contrasting genotypes.


September 22, 2019

Bacterial microbiota and metabolic character of traditional sour cream and butter in Buryatia, Russia.

Traditional sour cream and butter are widely popular fermented dairy products in Russia for their flavor and nutrition, and contain rich microbial biodiversity, particularly in terms of lactic acid bacteria (LAB). However, few studies have described the microbial communities and metabolic character of traditional sour cream and butter. The objective of this study was to determine the bacterial microbiota and metabolic character of eight samples collected from herdsmen in Buryatia, Russia. Using single-molecule real-time (SMRT) sequencing techniques, we identified a total of 294 species and/or subspecies in 169 bacterial genera, belonging to 14 phyla. The dominant phylum was Firmicutes (81.47%) and the dominant genus was Lactococcus (59.28%). There were differences between the bacterial compositions of the sour cream and butter samples. The relative abundances of Lactococcus lactis, Lactococcus raffinolactis, and Acetobacter cibinongensis were significantly higher in sour cream than in butter, and the abundance of Streptococcusthermophilus was significantly lower in sour cream than in butter. Using a pure culture method, 48 strains were isolated and identified to represent seven genera and 15 species and/or subspecies. Among these isolates, Lactococccus lactis subsp. lactis (22.50%) was the dominant LAB species. Ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry at elevated energy was used in combination with statistical methods to detect metabolite differences between traditional sour cream and butter. A total of 27,822 metabolites were detected in all samples, and Lys-Lys, isohexanal, palmitic acid, Leu-Val, and 2′-deoxycytidine were the most dominant metabolites found in all samples. In addition, 27 significantly different metabolites were detected between the sour cream and butter samples, including short peptides, organic acids, and amino acids. Based on correlation analyses between the most prevalent bacterial species and the main metabolites in sour cream, we conclude that there may be a connection between the dominant LAB species and these metabolites. This study combined omics techniques to analyze the bacterial diversity and metabolic character of traditional sour cream and butter, and we hope that our findings will enrich species resource libraries and provide valuable resources for further research on dairy product flavor.


September 22, 2019

Assessing the gene content of the megagenome: sugar pine (Pinus lambertiana).

Sugar pine (Pinus lambertiana Douglas) is within the subgenus Strobus with an estimated genome size of 31 Gbp. Transcriptomic resources are of particular interest in conifers due to the challenges presented in their megagenomes for gene identification. In this study, we present the first comprehensive survey of the P. lambertiana transcriptome through deep sequencing of a variety of tissue types to generate more than 2.5 billion short reads. Third generation, long reads generated through PacBio Iso-Seq has been included for the first time in conifers to combat the challenges associated with de novo transcriptome assembly. A technology comparison is provided here contribute to the otherwise scarce comparisons of 2nd and 3rd generation transcriptome sequencing approaches in plant species. In addition, the transcriptome reference was essential for gene model identification and quality assessment in the parallel project responsible for sequencing and assembly of the entire genome. In this study, the transcriptomic data was also used to address some of the questions surrounding lineage-specific Dicer-like proteins in conifers. These proteins play a role in the control of transposable element proliferation and the related genome expansion in conifers. Copyright © 2016 Author et al.


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