cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22708027
title: The complete chloroplast genome sequence of <i>Camellia atrothea</i> (Ericales: Theaceae)

description: <i>Camellia atrothea</i> H.T. Chang, H.S. Wang & B.H. Chen 1983 is a native <i>Camellia</i> species in China, which has significant economic and breeding values. Here, we assembled and analyzed the complete chloroplast genome sequence of <i>C. atrothea</i> based on the whole genome sequencing data from Illumina NovaSeq6000 platform. Results show that the complete chloroplast genome of <i>C. atrothea</i> is 157,099 bp in length, and comprises a large single-copy (LSC, 86,643 bp) region, a small single-copy (SSC, 18,276 bp) region, and a pair of inverted repeats (IRs, 26,090 bp) region. Annotation of the <i>C. atrothea</i> chloroplast genome predicts a total of 133 genes, including 88 protein-coding genes, 8 ribosomal RNA genes, and 37 transfer RNA genes. The overall GC content accounts for 37.30% of the genome, which is clearly consistent with that of other previously published <i>Camellia</i> species from section <i>Thea</i>. Phylogenetic analyses of the whole chloroplast genome sequences of 14 <i>Camellia</i> species using <i>Actinidia chinensis</i> as outgroup reveals that <i>C. atrothea</i> has a close relationship with <i>C. leptophylla</i>.
DOI: 10.6084/m9.figshare.13270810.v1
title: Identification of miRNA responsive to early flowering in tree peony (<i>Paeonia ostii</i>) by high-throughput sequencing

description: MicroRNA (miRNA) belongs to a class of non-coding small RNAs that post-transcriptionally regulate gene expression. In this study, we employed transcriptome, small RNA, and degradome sequencing to systematically investigate the miRNAs in <i>Paeonia ostii</i>. In total, 113 novel miRNA hairpin precursors were predicted, and 123 novel potential miRNAs were identified. Among them, five novel miRNAs and 23 known miRNAs were verified. Expression analyses further reveal that the levels of Pos-miR121, Pos-miR156, and Pos-miR 393 were negatively correlated with the age of <i>Paeonia ostii</i> in leaves, whereas those of Pos-miR159, Pos-miR165, Pos-miR166, Pos-miR172, and Pos-miR319 were gradually increased with age, implying that these miRNAs may play important roles in the acquisition of the floral competence in <i>Paeonia ostii</i>. Taken together, our results provide an important resource for further studies of the molecular basis of floral transition in <i>Paeonia ostii</i>.
DOI: 10.6084/m9.figshare.16940890.v1
title: Multi-Omics analysis identifies a lncRNA-related prognostic signature to predict bladder cancer recurrence

description: Bladder cancer (BLCA) is one of the most common cancers worldwide with high recurrence rate. Hence, we intended to establish a recurrence-related long non-coding RNA (lncRNA) model of BLCA as a potential biomarker based on multi-omics analysis. Multi-omics data including copy number variation (CNV) data, mutation annotation files, RNA expression profiles and clinical data of The Cancer Genome Atlas (TCGA) BLCA cohort (303 cases) and GSE31684 (93 cases) were downloaded from public database. With multi-omics analysis, twenty lncRNAs were identified as the candidates related with BLCA recurrence, CNVs and mutations in training set. Ten-lncRNA signature were established using least absolute shrinkage and selection operation (LASSO) and Cox regression. Then, various survival analysis was used to assess the power of lncRNA model in predicting BLCA recurrence. The results showed that the recurrence-free survival time of high-risk group was significantly shorter than that of low-risk group in training and testing sets, and the predictive value of ten-lncRNA signature was robust and independent of other clinical variables. Gene Set Enrichment Analysis (GSEA) showed this signature were associated with immune disorders, indicating this signature may be involved in tumor immunology. After compared with the other reported lncRNA signatures, ten-lncRNA signature was validated as a superior prognostic model in predicting the recurrence of BLCA. The effectiveness of the model was also evaluated in bladder cancer samples via qRT-PCR. Thus, the novel ten-lncRNA signature, constructed based on multi-omics data, had robust prognostic power in predicting the recurrence of BLCA and potential clinical implications as biomarkers.
DOI: 10.34740/kaggle/dsv/7613294
title: Jgggghbccff
DOI: 10.6084/m9.figshare.14843427
title: Additional file 4 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 4: Table S4. Phenotype of the four leaf-related traits of BC1 population from 2015 to 2019 (XLSX).
DOI: 10.6084/m9.figshare.14843424.v1
title: Additional file 3 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 3: Table S3. The information of 37 KASP markers in 147 individuals of BC1 population from 2019 (XLSX).
DOI: 10.6084/m9.figshare.14843433
title: Additional file 6 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 6:Table S6. The number of genes within the region on chromosome 1 from 41.470 to 42.045 Mb (XLSX).
DOI: 10.6084/m9.figshare.14843436
title: Additional file 7 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 7: Table S7. The genotype of 90 BC1 individuals from 2020 tested by KM2191098 (XLSX).
DOI: 10.6084/m9.figshare.14843439.v1
title: Additional file 8 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 8:Table S8. The primer sequences of KM2191098 (XLSX).
DOI: 10.6084/m9.figshare.14843421.v1
title: Additional file 2 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 2:Table S2. The information of 181 KASP markers in 147 individuals of BC1 population from 2015 (XLSX).
DOI: 10.6084/m9.figshare.14843418
title: Additional file 1 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 1:Table S1. The information of 4080 SLAF markers in 147 individuals of BC1 population from 2015 (XLSX).
DOI: 10.6084/m9.figshare.14843427.v1
title: Additional file 4 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 4: Table S4. Phenotype of the four leaf-related traits of BC1 population from 2015 to 2019 (XLSX).
DOI: 10.6084/m9.figshare.14843436.v1
title: Additional file 7 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 7: Table S7. The genotype of 90 BC1 individuals from 2020 tested by KM2191098 (XLSX).
DOI: 10.6084/m9.figshare.14843430
title: Additional file 5 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 5: Table S5. The number of genes on the three scaffolds related to LL, PL and LR (XLSX)
DOI: 10.6084/m9.figshare.14843439
title: Additional file 8 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 8:Table S8. The primer sequences of KM2191098 (XLSX).
DOI: 10.6084/m9.figshare.14843418.v1
title: Additional file 1 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 1:Table S1. The information of 4080 SLAF markers in 147 individuals of BC1 population from 2015 (XLSX).
DOI: 10.6084/m9.figshare.14843424
title: Additional file 3 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 3: Table S3. The information of 37 KASP markers in 147 individuals of BC1 population from 2019 (XLSX).
DOI: 10.6084/m9.figshare.14843433.v1
title: Additional file 6 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 6:Table S6. The number of genes within the region on chromosome 1 from 41.470 to 42.045 Mb (XLSX).
DOI: 10.6084/m9.figshare.14843421
title: Additional file 2 of Quantitative trait loci (QTL) analysis of leaf related traits in spinach (Spinacia oleracea L.)

description: Additional file 2:Table S2. The information of 181 KASP markers in 147 individuals of BC1 population from 2015 (XLSX).
DOI: 10.6084/m9.figshare.7504046
title: Additional file 10: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S8. Detailed annotation and expression levels for the nine positively selected genes with significant GO-enrichment. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.7504064.v1
title: Additional file 12: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S9. Detailed information for the 164 Rosa-specific genes. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.16940892.v2
title: A comprehensive genome-wide analysis of long non-coding RNA and mRNA expression profiles of JAK2V617F-positive classical myeloproliferative neoplasms

description: Aberrant expression of long non-coding RNAs (lncRNAs) is involved in the progression of myeloid neoplasms, but the role of lncRNAs in the JAK2V617F-positive subtype of classical myeloproliferative neoplasms (cMPNs) remains unclear. This study was conducted to clarify the expression and regulation patterns of lncRNAs in JAK2V617F-positive cMPNs, and to explore new potential carcinogenic factors of cMPNs. Bioinformatics analysis of microarray detection and wet testing verification were performed to study the expression and regulation signature of differentially expressed lncRNAs (DELs) and related genes (DEGs) in cMPNs. The expression of lncRNAs and mRNAs were observed to significantly dysregulated in JAK2V617F-positive cMPN patients compared with the normal controls. Co-expression analysis indicated that there were significant differences of the co-expression pattern of lncRNAs and mRNAs in JAK2V617F-positive cMPN patients compared to normal controls. GO and KEGG pathway analysis of DEGs and DELs showed the involvement of several pathways previously reported to regulate the pathogenesis of leukemia and cMPNs. Cis- and trans-regulation analysis of lncRNAs showed that ZNF141, DHX29, NOC2L, MAS1L, AFAP1L1, and CPN2 were significantly cis-regulated by lncRNA ENST00000356347, ENST00000456816, hsa-mir-449c, NR_026874, TCONS_00012136, uc003lqp.2, and ENST00000456816, respectively, and DELs were mostly correlated with transcription factors including CTBP2, SUZ12, REST, STAT2, and GATA4 to jointly regulate multiple target genes. In summary, expression profiles of lncRNAs and mRNAs were significantly altered in JAK2V617F-positive cMPNs, the relative signaling pathway, co-expression, cis- and trans-regulation were regulated by dysregulation of lncRNAs and several important genes, such as ITGB3, which may act as a promising carcinogenic factor, warrant further investigation.
DOI: 10.6084/m9.figshare.7504076
title: Additional file 2: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S2. Annotation details for both genotypes. COG, GO, KEGG, KOG, Pfam, Swissprot, TrEMBL, NR and NT database were used in the annotation process. (XLS 24958 kb)
DOI: 10.6084/m9.figshare.7504100
title: Additional file 5: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S4. KEGG and GO clustering information of 4447 Rosaceae-common genes. (XLSX 274 kb)
DOI: 10.6084/m9.figshare.23751788.v1
title: Additional file 3 of CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes

description: Additional file 3: Table S2. Associated Genes.
DOI: 10.6084/m9.figshare.7504127.v1
title: Additional file 1: of Choice of fluids in critically ill patients

description: Output of the systematic search. Description of data: Excel table reporting the output of the systematic search (XLSX 485 kb)
DOI: 10.6084/m9.figshare.7504070
title: Additional file 1: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S1. BUSCO analysis of the assemblies and coreset1. C, S, D, F, and M represent the proportion of the complete, the complete and single-copy, the complete and duplicated, the fragmented, and the missing BUSCO transcripts, respectively. (XLSX 128 kb)
DOI: 10.6084/m9.figshare.7504076.v1
title: Additional file 2: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S2. Annotation details for both genotypes. COG, GO, KEGG, KOG, Pfam, Swissprot, TrEMBL, NR and NT database were used in the annotation process. (XLS 24958 kb)
DOI: 10.6084/m9.figshare.7504118
title: Additional file 8: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S6. Raw data for the positively selected genes in the Rosaceae-common transcripts. (XLSX 185 kb)
DOI: 10.6084/m9.figshare.7504118.v1
title: Additional file 8: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S6. Raw data for the positively selected genes in the Rosaceae-common transcripts. (XLSX 185 kb)
DOI: 10.6084/m9.figshare.7504100.v1
title: Additional file 5: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S4. KEGG and GO clustering information of 4447 Rosaceae-common genes. (XLSX 274 kb)
DOI: 10.6084/m9.figshare.7504121
title: Additional file 9: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S7. GO annotation for the 409 positively selected genes. (XLSX 22 kb)
DOI: 10.6084/m9.figshare.22708027.v1
title: The complete chloroplast genome sequence of <i>Camellia atrothea</i> (Ericales: Theaceae)

description: <i>Camellia atrothea</i> H.T. Chang, H.S. Wang & B.H. Chen 1983 is a native <i>Camellia</i> species in China, which has significant economic and breeding values. Here, we assembled and analyzed the complete chloroplast genome sequence of <i>C. atrothea</i> based on the whole genome sequencing data from Illumina NovaSeq6000 platform. Results show that the complete chloroplast genome of <i>C. atrothea</i> is 157,099 bp in length, and comprises a large single-copy (LSC, 86,643 bp) region, a small single-copy (SSC, 18,276 bp) region, and a pair of inverted repeats (IRs, 26,090 bp) region. Annotation of the <i>C. atrothea</i> chloroplast genome predicts a total of 133 genes, including 88 protein-coding genes, 8 ribosomal RNA genes, and 37 transfer RNA genes. The overall GC content accounts for 37.30% of the genome, which is clearly consistent with that of other previously published <i>Camellia</i> species from section <i>Thea</i>. Phylogenetic analyses of the whole chloroplast genome sequences of 14 <i>Camellia</i> species using <i>Actinidia chinensis</i> as outgroup reveals that <i>C. atrothea</i> has a close relationship with <i>C. leptophylla</i>.
DOI: 10.6084/m9.figshare.23751772.v1
title: Additional file 2 of Restoring Wnt signaling in a hormone-simulated postpartum depression model remediated imbalanced neurotransmission and depressive-like behaviors

description: Additional file 2. Supplementary table 1-3: The formulations of Artificial Cerebrospinal Fluid (aCSF).
DOI: 10.6084/m9.figshare.23751793.v1
title: Additional file 3 of The determination of peanut (Arachis hypogaea L.) pod-sizes during the rapid-growth stage by phytohormones

description: Additional file 3: Table S1. Gene-specific primers for qRT-PCR.
DOI: 10.6084/m9.figshare.23751805
title: Additional file 7 of The determination of peanut (Arachis hypogaea L.) pod-sizes during the rapid-growth stage by phytohormones

description: Additional file 7: Table S5. KEGG enrichment analysis.
DOI: 10.6084/m9.figshare.6979925
title: De novo genome assemblies of Neurospora intermedia, N. metzenbergii and N. crassa, based on Illumina HiSeq reads

description: This dataset contains in total 29 de novo genome assemblies of three different species of the fungus <i>Neurospora</i> (21 N. intermedia, 5 <i>N. metzenbergii</i> and 3 <i>N. crassa</i>). All strains are listed using the strain number from the Fungal Genetics Stock Center (www.fgsc.net), where they also can be ordered from.<br><br>These genome assemblies were assembled from paired-end Illumina HiSeq 2500 reads using ABySS 1.3.7 in the following way:<br>abyss k=64 a=2 n=10 s=200 J016 in="read1.fastq.gz read2.fastq.gz" name="assembly_name"<br><br>Raw paired-end reads have been deposited in the Sequence Read Archive (SRA) in BioProjects PRJNA486257 (http://www.ncbi.nlm.nih.gov/bioproject/486257).<br><br>Strain list:<br><br>FGSC # | Species<br>-------+----------------------<br> 1785 | Neurospora intermedia<br> 1786 | Neurospora intermedia<br> 1787 | Neurospora intermedia<br> 1795 | Neurospora intermedia<br> 1832 | Neurospora intermedia<br> 1938 | Neurospora intermedia<br> 2316 | Neurospora intermedia<br> 2365 | Neurospora intermedia<br> 3194 | Neurospora intermedia<br> 5124 | Neurospora intermedia<br> 6249 | Neurospora intermedia<br> 6263 | Neurospora intermedia<br> 6595 | Neurospora intermedia<br> 7402 | Neurospora intermedia<br> 7426 | Neurospora intermedia<br> 7427 | Neurospora intermedia<br> 7429 | Neurospora intermedia<br> 8761 | Neurospora intermedia<br> 8767 | Neurospora intermedia<br> 8769 | Neurospora intermedia<br> 8793 | Neurospora intermedia<br> 5119 | Neurospora metzenbergii<br> 6795 | Neurospora metzenbergii<br> 8853 | Neurospora metzenbergii<br> 10411 | Neurospora metzenbergii<br> P4149 | Neurospora metzenbergii<br> 4723 | Neurospora crassa<br> 4829 | Neurospora crassa<br> 8863 | Neurospora crassa<br><br><br>For further information on the strains and the genome assemblies, please see:<br>Svedberg et al., (2018) "Convergent evolution of complex genomic rearrangements in two fungal meiotic drive elements": https://www.nature.com/articles/s41467-018-06562-x (DOI:10.1038/s41467-018-06562-x)<br>Supplementary Table 11 contains Illumina sequencing statistics.<br>
DOI: 10.6084/m9.figshare.7504046.v1
title: Additional file 10: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S8. Detailed annotation and expression levels for the nine positively selected genes with significant GO-enrichment. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.14320480.v1
title: De novo sequencing of Bletilla striata (Orchidaceae) transcriptome and identification of genes involved in polysaccharide biosynthesis

description: Abstract Bletilla striata polysaccharide (BSP) is the main component of Bletilla striata, which has important pharmacological and pharmacological effects; however, due to the lack of genetic data, the metabolic pathways of BSP remain unclear. For this study, 11 representative resources of B. striata were analyzed, and the BSP contents of the different samples were significantly different; however, the monosaccharide composition of BSP was glucose and mannose. The representative samples were selected to observe their life history in situ, which were then divided and cultured in a greenhouse. Finally, samples from various organs of different plants were combined for transcriptome sequencing using the Illumina system. Our results summarized the BSP metabolic pathway, and we found that there were eight enzyme genes involved in biosynthesis, but these genes showed tissue specificity. Following qRT-PCR validation and comparative analysis, manA showed the highest expression; however, there were significant differences between the two germplasm resources in which the BSP content was significantly different, while UGP2, GPI, PMM, and GMPP had significant differences between the two samples. In summary, this study lays the foundation for further research into BSP metabolism and other physiological processes at the molecular level.
DOI: 10.6084/m9.figshare.16416807.v1
title: 24-epibrassinolide confers tolerance against deep-seeding stress in <i>Zea mays</i> L. coleoptile development by phytohormones signaling transduction and their interaction network

description: Coleoptile/mesocotyl elongation influence seedling emergence and establishment, is major causes of maize deep-seeding tolerance (DST). Detailed analyses on molecular basis underlying their elongation mediated by brassinosteroid under deep-seeding stress (DSS) could provide meaningful information for key factors controlling their elongation. Here we monitored transcriptome and phytohormones changes specifically in elongating coleoptile/mesocotyl in response to DSS and 24-epibrassinolide (EBR)-signaling. Phenotypically, contrasting maize evolved variant organs to positively respond to DST, longer coleoptile/mesocoty of K12/W64A was a desirable organ for seedling under DSS. Applied-EBR improved maize DST, and their coleoptiles/mesocotyls were further elongated. 15,607/20,491 differentially expressed genes (DEGs) were identified in W64A/K12 coleoptile, KEGG analysis showed plant hormone signal transduction, starch and sucrose metabolism, valine, leucine, and isoleucine degradation were critical processes of coleoptile elongation under DSS and EBR signaling, further highly interconnected network maps including 79/142 DEGs for phytohormones were generated. Consistent with these DEGs expression, interactions, and transport, IAA, GA<sub>3</sub>, ABA, and Cis-ZT were significantly reduced while EBR, Trans-ZT, JA, and SA were clearly increased in coleoptile under DSS and EBR-signaling. These results enrich our knowledge about the genes and phytohormones regulating coleoptile elongation in maize, and help improve future studies on corresponding genes and develop varieties with DST.
DOI: 10.6084/m9.figshare.7504028
title: MOESM8 of Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer

description: Additional file 8: Table S6. The quantified urinary protein list.
DOI: 10.6084/m9.figshare.7504064
title: Additional file 12: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S9. Detailed information for the 164 Rosa-specific genes. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.7504028.v1
title: MOESM8 of Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer

description: Additional file 8: Table S6. The quantified urinary protein list.
DOI: 10.6084/m9.figshare.7504094
title: Additional file 4: of Comparative transcriptomics identifies patterns of selection in roses

description: Table S3. KEGG and GO enrichment analysis for coreset1 transcripts. Note that each transcript could be mapped to several GO terms and KEGG categories. (XLSX 306 kb)
DOI: 10.6084/m9.figshare.23751772
title: Additional file 2 of Restoring Wnt signaling in a hormone-simulated postpartum depression model remediated imbalanced neurotransmission and depressive-like behaviors

description: Additional file 2. Supplementary table 1-3: The formulations of Artificial Cerebrospinal Fluid (aCSF).
DOI: 10.6084/m9.figshare.13265907
title: Additional file 1 of Deep sequencing reveals a DAP1 regulatory haplotype that potentiates autoimmunity in systemic lupus erythematosus

description: Additional file 1: Table S1. DAP1-SLE association results based on Immunochipv.1. Table S2. List of sequencing variants in DAP1 gene region-European cohort. Table S3. 19 SLE associated DAP1 variants used for haplotype analysis. Table S4. List of variants in African-American and Chinese cohort. Table S5. Cochran-Mantel-Haenszel test result on SNPs. Table S6. DAP1 haplotype association analysis results. Table S7. Trans-ethnic analysis by Cochran-Mantel-Haenszel and MR-MEGA program. Table S8. Diplotypes analysis in Caucasian data. Table S9. Potentially regulatory variant annotations. Table S10- eQTL effects of SLE associated variants. Table S11. Lymphoblastoid Cell Lines (LCL) used in study. Table S12. PBMCs RNA-Seq analysis. Table S13. Reactome pathway analysis. Table S14. Autoantibody data. Table S15. List of participating institutions and investigators.