Ontology highlight
ABSTRACT:
PROVIDER: PRJNA905566 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22419600_1.fastq.gz | Fastqsanger.gz | |||
| SRR22419600_2.fastq.gz | Fastqsanger.gz | |||
| SRR22419601_1.fastq.gz | Fastqsanger.gz | |||
| SRR22419601_2.fastq.gz | Fastqsanger.gz | |||
| SRR22419602_1.fastq.gz | Fastqsanger.gz |
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Project description:Alfalfa (Medicago sativa L.) is a forage legume with significant agricultural value worldwide. MicroRNAs (miRNAs) are key components of post-transcriptional gene regulation and essentially control almost all aspect of plant growth and development. Although miRNAs have been reported from alfalfa but their expression profiles in different tissues and novel miRNAs as well as their targets have not been confirmed in this plant species. Therefore, we sequenced small RNAs in whole plantlets, shoots and roots of three different alfalfa genotypes (Altet-4, NECS-141 and NF08ALF06) to identify tissue-specific profiles. After comprehensive analysis using bioinformatics methods, we have identified 100 miRNA families, of which 21 belongs to the highly conserved families whereas the remaining 79 families are conserved between M. truncatula and M. sativa. The profiles of the six highly expressed conserved miRNA families (miR156, 159, 166, 319, 396, 398,) were relatively similar between the plantlets, roots and shoots of three genotypes. Contrastingly, the differenecs were robust between shoots and roots for miR160 and miR408 levels, which were low in roots compared to shoots. The study also has identified 17 novel miRNAs that also differed in their abundanecs between tissues of the alfalfa genotypes. Additionally, we have generated and analyzed the degradome libraries from three alfalfa genotypes that has confirmed 69 genes as targets for 31 miRNA families in alfalfa. The identification of conserved and novel miRNAs as well as their targets in different tissues of three genotypes not only enhanced our understanding of miRNA-mediated gene regulation in alfalfa but could also be useful for practical applications in alfalfa as well as related legume species.
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Project description:We present a draft genome assembly that includes 200 Gb of Illumina reads, 4 Gb of Moleculo synthetic long-reads and 108 Gb of Chicago libraries, with a final size matching the estimated genome size of 2.7 Gb, and a scaffold N50 of 4.8 Mb. We also present an alternative assembly including 27 Gb raw reads generated using the Pacific Biosciences platform. In addition, we sequenced the proteome of the same individual and RNA from three different tissue types from three other species of squid species (Onychoteuthis banksii, Dosidicus gigas, and Sthenoteuthis oualaniensis) to assist genome annotation. We annotated 33,406 protein coding genes supported by evidence and the genome completeness estimated by BUSCO reached 92%. Repetitive regions cover 49.17% of the genome.
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Project description:Alfalfa, [Medicago sativa (L.) sativa], a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. The application of genomic approaches would advance development of alfalfa as a cellulosic feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analysis, provides an opportunity to expand the identification of alfalfa genes and polymorphisms, and conduct in-depth transcript profiling. Cell walls in stems of alfalfa genotype 708 have higher cellulose and lower lignin concentrations compared to cell walls in stems of genotype 773. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. These ESTs were de novo assembled into 132,153 unique sequences. By combining the de novo assembled ESTs (132,153 sequences) with our previously identified EST sequences (341,984 sequences, unpublished data), and the ESTs available from GenBank (12,371 sequences), we built the first Alfalfa Gene Index (MSGI 1.0). MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons and 78,981 pseudo-singletons. We identified a total of 1, 294 simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, a total of 10,826 single nucleotide polymorphisms (SNPs) were predicted between the two genotypes. Transcript profiling of stem internodes of genotypes 708 and 773 was conducted by quantifying the number of Illumina EST reads that were mapped to sequences in MSGI 1.0. We identified numerous candidate genes that may play a role in stem development as well as candidate genes that may contribute to the differences in cell wall composition in stems of the two genotypes. Our results demonstrate that RNA-Seq can be successfully used for gene identification, polymorphism detection and transcript profiling in alfalfa, a non-model, allogamous, autotetraploid species. The alfalfa gene index (MSGI 1.0) assembled in this study, and the SNPs, SSRs and candidate genes identified can be used to improve alfalfa as a cellulosic feedstock. Examination of 2 different tissue types at different developmental stages (Elongating vs. post-elongation stem internodes) in two alfalfa genotypes (708 and 773) with divergent cell wall composition in stems.
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Project description:Alfalfa, [Medicago sativa (L.) sativa], a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. The application of genomic approaches would advance development of alfalfa as a cellulosic feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analysis, provides an opportunity to expand the identification of alfalfa genes and polymorphisms, and conduct in-depth transcript profiling. Cell walls in stems of alfalfa genotype 708 have higher cellulose and lower lignin concentrations compared to cell walls in stems of genotype 773. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. These ESTs were de novo assembled into 132,153 unique sequences. By combining the de novo assembled ESTs (132,153 sequences) with our previously identified EST sequences (341,984 sequences, unpublished data), and the ESTs available from GenBank (12,371 sequences), we built the first Alfalfa Gene Index (MSGI 1.0). MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons and 78,981 pseudo-singletons. We identified a total of 1, 294 simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, a total of 10,826 single nucleotide polymorphisms (SNPs) were predicted between the two genotypes. Transcript profiling of stem internodes of genotypes 708 and 773 was conducted by quantifying the number of Illumina EST reads that were mapped to sequences in MSGI 1.0. We identified numerous candidate genes that may play a role in stem development as well as candidate genes that may contribute to the differences in cell wall composition in stems of the two genotypes. Our results demonstrate that RNA-Seq can be successfully used for gene identification, polymorphism detection and transcript profiling in alfalfa, a non-model, allogamous, autotetraploid species. The alfalfa gene index (MSGI 1.0) assembled in this study, and the SNPs, SSRs and candidate genes identified can be used to improve alfalfa as a cellulosic feedstock.
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Project description:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.
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