Project description:Purpose: Investigation of effects of early adversity in mice deficient for serotonin transporter on H3K4me3 enrichment in the context of differential susceptibility Methods: Following prenatal stress and behavioural screening in adulthood, 3 month old females, either wildtype or carrying a heterozygous knockout of the serotonin transporter gene, were sacrificed, brains extracted, the hippocampi of both hemispheres dissected, blended and separated in two protions. For one of these portions the material was split again in two portions, of which one was fixed using 1% PFA, and was subsequently processed using a standard Chromatin immuno precipitation protocol. Following ChIP, the samples were processed by Nxt-Dx Belgium. Library preparation was performed using the NEBNext Ultra II DNA Library prep kit for Illumina (NEB, Ipswitch, Massatchusettes, USA). Subsequently, the whole IP material was subjected to ends prep and ligation of Illumina adaptors. A clean up of the adaptor-ligated DNA with AMPure XP beads (Beckman Coulter) was performed without size selection. The eluted material was subjected to enrichment PCR (14 cycles) with the NEBNext Index primers, and a last clean up with AMPure XP beads followed. The quality of the final libraries was checked on a Bioanalyzer 2100 DNA 1000 chip (Agilent, Santa Clara, CA, USA). The concentration was determined by performing qPCR on the samples using a dilution of PhiX index3 as standard. The concentration of all indexed samples was adjusted to 10 nM and samples were pooled for sequencing. Sequencing was performed on an Illumina HiSeq4000 (read-length of 50 bp with 25-30 million reads/sample, paired-end). Results: dependent on the serotonin transporter genotype and behaviourally determined susceptibility to early life adversity, animals displayed distinct H3K4me3 enrichment. As expected, the effect sizes and significances were rather subtle. Conclusion: the epigenetic regulation by prenatal stress seems to be modulated by the serotonin transporter genotype
Project description:To analyse gene expression pattern in different disease state of COVID-19 patients. Experimental workflow: 1) Small RNA enrichment and purification, 2) Adaptor ligation and Unique molecular identifiers (UMI) labeled Primer addition, 3) RT-PCR, Library quantitation and pooling cyclization, 4) Library quality control, 5) Small RNAs were sequenced by BGI500 platform with 50bp single-end reads resulting in at least 20M reads for each sample. Analysis steps: 1) Small RNA raw sequencing reads with low quality tags (which have more than four bases whose quality is less than ten, or have more than six bases with a quality less than thirteen.), the reads with poly A tags, and the tags without 3’ primer or tags shorter than 18nt were removed. 2) After data filtering, the clean reads were mapped to the reference genome and other sRNA database including miRbase, siRNA, piRNA and snoRNA using Bowtie2 (Langmead and Salzberg, 2012). Particularly, cmsearch (Nawrocki and Eddy, 2013) was performed for Rfam mapping. 3) The small RNA expression level was calculated by counting absolute numbers of molecules using unique molecular identifiers (UMI, 8-10nt). MiRNA with UMI count lager than 1 in at least one sample were considered as expressed.
Project description:Purpose:using m6A modified RNA immunoprecipitation sequence (m6A-seq), to establish the m6A methylation transcription profiles in recurrent implantation failure (RIF). Methods: GenSeq® Low Input Whole RNA Library Prep Kit (GenSeq, Inc.) was used to construct RNA libraries for IP and input samples by following the manufacturer's instructions. The library quality was evaluated using Agilent 2100 bioanalyzer and then sequenced in a NovaSeq platform (Illumina 6000). Result:using m6A modified RNA immunoprecipitation sequence (m6A-seq), methylated sites in mRNA,lncRNA and circRNA are identified. Conclusions: Our study revealed the m6A methylation landscape by MERIP sequencing.
Project description:High throughput sequencing is frequently used to discover the location of regulatory interactions on chromatin. However, techniques that enrich DNA where regulatory activity takes place, such as chromatin immunoprecipitation (ChIP), often yield less DNA than optimal for sequencing library preparation. Existing protocols for picogram-scale libraries require concomitant fragmentation of DNA, pre-amplification, or long overnight steps. We report a simple and fast library construction method that produces libraries from sub-nanogram quantities of DNA. This protocol yields conventional libraries with barcodes suitable for multiplexed sample analysis on the Illumina platform. We demonstrate the utility of this method by constructing a ChIP-seq library from 100 pg of ChIP DNA that demonstrates equivalent genomic coverage of target regions to a library produced from a larger scale experiment. Application of this method allows whole genome studies from samples where material or yields are limiting. Comparison of ChIP-seq libraries constructed from 100 pg DNA (this study) and nanograms of DNA (modENCODE). ChIP antibody: H3K27me3, Active Motif 31955.
Project description:Purpose: We aimed to dissect response of bermudagrass to drought, salt, submergence and heat stresses and identify stress responsive genes inbermudagrass. Methods: A total amount of 3 µg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated.Paired-end clean reads were aligned to the reference genome of TAIR10 and rice protein sequence from MSU (version_7.0) using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then RPKM of each gene was calculated . Differential expression analysis of abiotic stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, 12 samples with two biological replicates per treatment were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis identified genes modulated by different abiotic stress treatments.
Project description:The goal of this study was to find the differentially expressed circRNAs/linear RNA in AKI mice model compared to normal mice. We established cisplatin-induced AKI mice models and then extracted RNAs from isolated renal tubular tissues for Next Generation Sequencing(NGS) at different time points during early stage of AKI. CircRNA library was constructed by NEB Next®Ultra™ small RNA Sample Library Prep Kit for Illumina®. NGS was performed by using Illumina HiSeq 2500 Genome Sequencers.The original image data file was transformed into Raw Data by Base Calling. Clean Data was obtained by removing reads that containing joints and more than 5% N (undetermined base information). Mapped Reads were obtained by sequence alignment between Clean Reads and reference genome sequenced using BWA software package. CIRI software was used to predict circRNAs. Finally, we identified 2162 circRNAs and our study represents the first detailed analysis of AKI mice circRNA transcriptomes, which provide a framework for investigations of circRNAs expression profiles in AKI
Project description:To analyse gene expression pattern in different disease state of COVID-19 patients. Experimental workflow: 1) rRNA was removed by using RNase H method, 2) QAIseq FastSelect RNA Removal Kit was used to remove the Globin RNA, 3) The purified fragmented cDNA was combined with End Repair Mix, then add A-Tailing Mix, mix well by pipetting, incubation, 4) PCR amplification, 5) Library quality control and pooling cyclization, 6) The RNA library was sequenced by MGI2000 PE100 platform with 100bp paired-end reads. Analysis steps: 1) RNA-seq raw sequencing reads were filtered by SOAPnuke (Li et al., 2008) to remove reads with sequencing adapter, with low-quality base ratio (base quality < 5) > 20%, and with unknown base (’N’ base) ratio > 5%. 2) Reads aligned to rRNA by Bowtie2 (v2.2.5) (Langmead and Salzberg, 2012) were removed. 3) The clean reads were mapped to the reference genome using HISAT2 (Kim et al., 2015). Bowtie2 (v2.2.5) was applied to align the clean reads to the transcriptome. 4)Then the gene expression level (FPKM) was determined by RSEM (Li and Dewey, 2011). Genes with FPKM > 0.1 in at least one sample were retained.
Project description:Purpose: We aimed to identify ZAT18 target genes and characterize functions of ZAT18 during plant drought tolerance Methods: A total amount of 3 μg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, eight samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis revealed that 1777 genes were transcriptionally affected by AtZAT18 trasngene or drought treatment. The results showed that overexpression of AtZAT18 modulated expression level changes of 423 and 561genes under control and drought stress conditions, respectively. Drought stress treatment changed expression of 971 genes with 768 up-regulated and 203 down-regulated.
Project description:Determining the role of DDX17 in the formation of DNA:RNA-hybrids around active DNA double-strand breaks (DSBs) using DRIP-seq in the damaged induced via AsiSI (DIvA) cell system that induced DSBs at known genomic loci in response to hydroxytamoxifen (OHT) treatment via and AsiSI enzyme fused to an oestrogen receptor. Sequencing was done using either control or DDX17 siRNA, and mock or 4 hours 300nM OHT treatment. Paired-end 150 cycles was completed on an Illumina NextSeq 500 and library prep was completed using the NEB NEBNext Ultra II library prep kit.