scholarly journals Single-nucleus full-length RNA profiling in plants incorporates isoform information to facilitate cell type identification

2020 ◽  
Author(s):  
Yanping Long ◽  
Zhijian Liu ◽  
Jinbu Jia ◽  
Weipeng Mo ◽  
Liang Fang ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Molecule ◽  
Large Scale ◽  
Alternative Polyadenylation ◽  
Full Length ◽  
Cell Type ◽  
Arabidopsis Root ◽  
Rna Profiling ◽  
Long Read ◽  
Single Nucleus

AbstractThe broad application of large-scale single-cell RNA profiling in plants has been restricted by the prerequisite of protoplasting. We recently found that the Arabidopsis nucleus contains abundant polyadenylated mRNAs, many of which are incompletely spliced. To capture the isoform information, we combined 10x Genomics and Nanopore long-read sequencing to develop a protoplasting-free full-length single-nucleus RNA profiling method in plants. Our results demonstrated using Arabidopsis root that nuclear mRNAs faithfully retain cell identity information, and single-molecule full-length RNA sequencing could further improve cell type identification by revealing splicing status and alternative polyadenylation at single-cell level.

scholarly journals FlsnRNA-seq: protoplasting-free full-length single-nucleus RNA profiling in plants

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanping Long ◽  
Zhijian Liu ◽  
Jinbu Jia ◽  
Weipeng Mo ◽  
Liang Fang ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Walls ◽  
Large Scale ◽  
Full Length ◽  
Cell Level ◽  
Root Cells ◽  
Rna Profiling ◽  
Different Types ◽  
Long Read ◽  
Single Nucleus

AbstractThe broad application of single-cell RNA profiling in plants has been hindered by the prerequisite of protoplasting that requires digesting the cell walls from different types of plant tissues. Here, we present a protoplasting-free approach, flsnRNA-seq, for large-scale full-length RNA profiling at a single-nucleus level in plants using isolated nuclei. Combined with 10x Genomics and Nanopore long-read sequencing, we validate the robustness of this approach in Arabidopsis root cells and the developing endosperm. Sequencing results demonstrate that it allows for uncovering alternative splicing and polyadenylation-related RNA isoform information at the single-cell level, which facilitates characterizing cell identities.

scholarly journals Single-Molecule Long-Read Sequencing Reveals the Diversity of Full-Length Transcripts in Leaves of Gnetum (Gnetales)

2019 ◽  
Vol 20 (24) ◽  
pp. 6350 ◽  
Author(s):  
Nan Deng ◽  
Chen Hou ◽  
Fengfeng Ma ◽  
Caixia Liu ◽  
Yuxin Tian
Keyword(s):  
Single Molecule ◽  
Developmental Stages ◽  
Alternative Polyadenylation ◽  
Full Length ◽  
Stomatal Development ◽  
Rna Seq ◽  
Leaf Transcriptome ◽  
Long Read ◽  
Non Coding Rnas ◽  
A Site

The limitations of RNA sequencing make it difficult to accurately predict alternative splicing (AS) and alternative polyadenylation (APA) events and long non-coding RNAs (lncRNAs), all of which reveal transcriptomic diversity and the complexity of gene regulation. Gnetum, a genus with ambiguous phylogenetic placement in seed plants, has a distinct stomatal structure and photosynthetic characteristics. In this study, a full-length transcriptome of Gnetum luofuense leaves at different developmental stages was sequenced with the latest PacBio Sequel platform. After correction by short reads generated by Illumina RNA-Seq, 80,496 full-length transcripts were obtained, of which 5269 reads were identified as isoforms of novel genes. Additionally, 1660 lncRNAs and 12,998 AS events were detected. In total, 5647 genes in the G. luofuense leaves had APA featured by at least one poly(A) site. Moreover, 67 and 30 genes from the bHLH gene family, which play an important role in stomatal development and photosynthesis, were identified from the G. luofuense genome and leaf transcripts, respectively. This leaf transcriptome supplements the reference genome of G. luofuense, and the AS events and lncRNAs detected provide valuable resources for future studies of investigating low photosynthetic capacity of Gnetum.

scholarly journals Full-length Transcriptome Analysis of Pecan (Carya illinoinensis) Kernels

2021 ◽  
Author(s):  
Chengcai Zhang ◽  
Huadong Ren ◽  
Xiaohua Yao ◽  
Kailiang Wang ◽  
Jun Chang
Keyword(s):  
Single Molecule ◽  
Molecular Mechanisms ◽  
Draft Genome ◽  
Alternative Polyadenylation ◽  
Full Length ◽  
Functional Annotations ◽  
Predominant Type ◽  
Long Read ◽  
Non Coding Rnas ◽  
Novel Isoforms

Abstract Pecan is rich in bioactive components such as fatty acids and flavonoids and is an important nut type worldwide. Therefore, the molecular mechanisms of phytochemical biosynthesis in pecan are a focus of research. Recently, a draft genome and several transcriptomes have been published. However, the full-length mRNA transcripts remain unclear, and the regulatory mechanisms behind the quality components biosynthesis and accumulation have not been fully investigated. In this study, single-molecule long read sequencing technology was used to obtain full-length transcripts of pecan kernels. In total, 37 504 isoforms of 16 702 genes were mapped to the reference genome. The numbers of known isoforms, new isoforms, and novel isoforms were 9013 (24.03%), 26 080 (69.54%), and 2411 (6.51%), respectively. Over 80% of the transcripts (30 751, 81.99%) had functional annotations. A total of 15 465 alternative splicing (AS) events and 65 761 alternative polyadenylation events were detected; wherein, the retained intron was the predominant type (5652, 36.55%) of AS. Furthermore, 1894 long non-coding RNAs and 1643 transcription factors were predicted using bioinformatics methods. Finally, the structural genes associated with fatty acid (FA) and flavonoid biosynthesis were characterized. A high frequency of AS accuracy (70.31%) was observed in FA synthesis-associated genes. The present study provides a full-length transcriptome dataset of pecan kernels, which will significantly enhance the understanding of the regulatory basis of phytochemical biosynthesis during pecan kernel maturation.

scholarly journals Single-cell isoform RNA sequencing (ScISOr-Seq) across thousands of cells reveals isoforms of cerebellar cell types

2018 ◽  
Author(s):  
Ishaan Gupta ◽  
Paul G Collier ◽  
Bettina Haase ◽  
Ahmed Mahfouz ◽  
Anoushka Joglekar ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Cell Types ◽  
Full Length ◽  
Cell Of Origin ◽  
Cell Type ◽  
Long Reads ◽  
Long Read ◽  
The Individual ◽  
Bulk Tissue

AbstractFull-length isoform sequencing has advanced our knowledge of isoform biology1–11. However, apart from applying full-length isoform sequencing to very few single cells12,13, isoform sequencing has been limited to bulk tissue, cell lines, or sorted cells. Single splicing events have been described for <=200 single cells with great statistical success14,15, but these methods do not describe full-length mRNAs. Single cell short-read 3’ sequencing has allowed identification of many cell sub-types16–23, but full-length isoforms for these cell types have not been profiled. Using our new method of single-cell-isoform-RNA-sequencing (ScISOr-Seq) we determine isoform-expression in thousands of individual cells from a heterogeneous bulk tissue (cerebellum), without specific antibody-fluorescence activated cell sorting. We elucidate isoform usage in high-level cell types such as neurons, astrocytes and microglia and finer sub-types, such as Purkinje cells and Granule cells, including the combination patterns of distant splice sites6–9,24,25, which for individual molecules requires long reads. We produce an enhanced genome annotation revealing cell-type specific expression of known and 16,872 novel (with respect to mouse Gencode version 10) isoforms (see isoformatlas.com).ScISOr-Seq describes isoforms from >1,000 single cells from bulk tissue without cell sorting by leveraging two technologies in three steps: In step one, we employ microfluidics to produce amplified full-length cDNAs barcoded for their cell of origin. This cDNA is split into two pools: one pool for 3’ sequencing to measure gene expression (step 2) and another pool for long-read sequencing and isoform expression (step 3). In step two, short-read 3’-sequencing provides molecular counts for each gene and cell, which allows clustering cells and assigning a cell type using cell-type specific markers. In step three, an aliquot of the same cDNAs (each barcoded for the individual cell of origin) is sequenced using Pacific Biosciences (“PacBio”)1,2,4,5,26 or Oxford Nanopore3. Since these long reads carry the single-cell barcodes identified in step two, one can determine the individual cell from which each long read originates. Since most single cells are assigned to a named cluster, we can also assign the cell’s cluster name (e.g. “Purkinje cell” or “astrocyte”) to the long read in question (Fig 1A) – without losing the cell of origin of each long read.

scholarly journals Single-molecule real-time sequencing identifies massive full-length cDNAs and alternative-splicing events that facilitate comparative and functional genomics study in the hexaploid crop sweet potato

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7933 ◽  
Author(s):  
Na Ding ◽  
Huihui Cui ◽  
Ying Miao ◽  
Jun Tang ◽  
Qinghe Cao ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Functional Genomics ◽  
Real Time ◽  
Sweet Potato ◽  
Single Molecule ◽  
Large Scale ◽  
Full Length ◽  
Full Length Cdna ◽  
Cdna Sequences ◽  
Long Read

Background Sweet potato (Ipomoea batatas (L.) Lam.) is one of the most important crops in many developing countries and provides a candidate source of bioenergy. However, neither a complete reference genome nor large-scale full-length cDNA sequences for this outcrossing hexaploid crop are available, which in turn impedes progress in research studies in I. batatas functional genomics and molecular breeding. Methods In this study, we sequenced full-length transcriptomes in I. batatas and its diploid ancestor I. trifida by single-molecule real-time sequencing and Illumina second-generation sequencing technologies. With the generated datasets, we conducted comprehensive intraspecific and interspecific sequence analyses and experimental characterization. Results A total of 53,861/51,184 high-quality long-read transcripts were obtained, which covered about 10,439/10,452 loci in the I. batatas/I. trifida genome. These datasets enabled us to predict open reading frames successfully in 96.83%/96.82% of transcripts and identify 34,963/33,637 full-length cDNA sequences, 1,401/1,457 transcription factors, 25,315/27,090 simple sequence repeats, 1,656/1,389 long non-coding RNAs, and 5,251/8,901 alternative splicing events. Approximately, 32.34%/38.54% of transcripts and 46.22%/51.18% multi-exon transcripts underwent alternative splicing in I. batatas/I. trifida. Moreover, we validated one alternative splicing event in each of 10 genes and identified tuberous-root-specific expressed isoforms from a starch-branching enzyme, an alpha-glucan phosphorylase, a neutral invertase, and several ABC transporters. Overall, the collection and analysis of large-scale long-read transcripts generated in this study will serve as a valuable resource for the I. batatas research community, which may accelerate the progress in its structural, functional, and comparative genomics studies.

scholarly journals PacBio Single-Molecule Long-Read Sequencing Provides New Light on the Complexity of Full-Length Transcripts in Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Tianpeng Chang ◽  
Bingxing An ◽  
Mang Liang ◽  
Xinghai Duan ◽  
Lili Du ◽  
...  
Keyword(s):  
Single Molecule ◽  
Bos Taurus ◽  
Human Life ◽  
Alternative Polyadenylation ◽  
Transcriptome Profiling ◽  
Full Length ◽  
Consensus Sequences ◽  
Long Read ◽  
Huge Impact ◽  
Whole Transcriptome

Cattle (Bos taurus) is one of the most widely distributed livestock species in the world, and provides us with high-quality milk and meat which have a huge impact on the quality of human life. Therefore, accurate and complete transcriptome and genome annotation are of great value to the research of cattle breeding. In this study, we used error-corrected PacBio single-molecule real-time (SMRT) data to perform whole-transcriptome profiling in cattle. Then, 22.5 Gb of subreads was generated, including 381,423 circular consensus sequences (CCSs), among which 276,295 full-length non-chimeric (FLNC) sequences were identified. After correction by Illumina short reads, we obtained 22,353 error-corrected isoforms. A total of 305 alternative splicing (AS) events and 3,795 alternative polyadenylation (APA) sites were detected by transcriptome structural analysis. Furthermore, we identified 457 novel genes, 120 putative transcription factors (TFs), and 569 novel long non-coding RNAs (lncRNAs). Taken together, this research improves our understanding and provides new insights into the complexity of full-length transcripts in cattle.

scholarly journals Single-cell RNA counting at allele- and isoform-resolution using Smart-seq3

2019 ◽  
Author(s):  
Michael Hagemann-Jensen ◽  
Christoph Ziegenhain ◽  
Ping Chen ◽  
Daniel Ramsköld ◽  
Gert-Jan Hendriks ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Cell Types ◽  
Mouse Strains ◽  
Rna Molecules ◽  
Counting Strategy ◽  
Long Read ◽  
Sequencing Strategy ◽  
Transcriptome Coverage ◽  
Scale Characterization

AbstractLarge-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states1. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells2,3. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5’ unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.

scholarly journals PacBio Single-Molecule Long-Read Sequencing Reveals Genes Tolerating Manganese Stress in Schima superba Saplings

2021 ◽  
Vol 12 ◽  
Author(s):  
Fiza Liaquat ◽  
Muhammad Farooq Hussain Munis ◽  
Samiah Arif ◽  
Urooj Haroon ◽  
Jianxin Shi ◽  
...  
Keyword(s):  
Single Molecule ◽  
Gene Annotation ◽  
Treated Group ◽  
Full Length ◽  
Open Reading Frames ◽  
Interacting Protein ◽  
Schima Superba ◽  
Long Read ◽  
First Time ◽  
Potential Tool

Schima superba (Theaceae) is a subtropical evergreen tree and is used widely for forest firebreaks and gardening. It is a plant that tolerates salt and typically accumulates elevated amounts of manganese in the leaves. With large ecological amplitude, this tree species grows quickly. Due to its substantial biomass, it has a great potential for soil remediation. To evaluate the thorough framework of the mRNA, we employed PacBio sequencing technology for the first time to generate S. Superba transcriptome. In this analysis, overall, 511,759 full length non-chimeric reads were acquired, and 163,834 high-quality full-length reads were obtained. Overall, 93,362 open reading frames were obtained, of which 78,255 were complete. In gene annotation analyses, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Genes (COG), Gene Ontology (GO), and Non-Redundant (Nr) databases were allocated 91,082, 71,839, 38,914, and 38,376 transcripts, respectively. To identify long non-coding RNAs (lncRNAs), we utilized four computational methods associated with protein families (Pfam), Cooperative Data Classification (CPC), Coding Assessing Potential Tool (CPAT), and Coding Non-Coding Index (CNCI) databases and observed 8,551, 9,174, 20,720, and 18,669 lncRNAs, respectively. Moreover, nine genes were randomly selected for the expression analysis, which showed the highest expression of Gene 6 (Na_Ca_ex gene), and CAX (CAX-interacting protein 4) was higher in manganese (Mn)-treated group. This work provided significant number of full-length transcripts and refined the annotation of the reference genome, which will ease advanced genetic analyses of S. superba.

scholarly journals CellMap: Characterizing the types and composition of iPSC-derived cells from RNA-seq data

2021 ◽  
Author(s):  
Zhengyu Ouyang ◽  
Nathanael Bourgeois ◽  
Eugenia Lyashenko ◽  
Paige Cundiff ◽  
Patrick F Cullen ◽  
...  
Keyword(s):  
Single Cell ◽  
Induced Pluripotent Stem Cell ◽  
Cell Types ◽  
Model Systems ◽  
Rna Seq ◽  
Cell Type ◽  
Fine Grained ◽  
Single Nucleus ◽  
Induced Pluripotent

Induced pluripotent stem cell (iPSC) derived cell types are increasingly employed as in vitro model systems for drug discovery. For these studies to be meaningful, it is important to understand the reproducibility of the iPSC-derived cultures and their similarity to equivalent endogenous cell types. Single-cell and single-nucleus RNA sequencing (RNA-seq) are useful to gain such understanding, but they are expensive and time consuming, while bulk RNA-seq data can be generated quicker and at lower cost. In silico cell type decomposition is an efficient, inexpensive, and convenient alternative that can leverage bulk RNA-seq to derive more fine-grained information about these cultures. We developed CellMap, a computational tool that derives cell type profiles from publicly available single-cell and single-nucleus datasets to infer cell types in bulk RNA-seq data from iPSC-derived cell lines.

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