Paired-end Data Research Articles

The complete sequence of chloroplast genome of Baeckea frutescens Linaeus 1753 (Myrtoideae), a traditional folk medicinal plant

Baeckea frutescens Linaeus 1753, as a traditional folk medicine in South East Asia, possesses sesquiterpenes, phloroglucinols, chromones, and essential oil, and is utilized for traditional Chinese medicinal purposes. The genetic diversity of the plant must be better understood, considering its significance. The complete chloroplast (cp) genome of B. frutescens was sequenced and assembled by using Illumina paired-end data, marking a significant advancement toward comprehending its genetic composition. The complete cp genome is 158,939 bp in length and contains 128 genes, consisting of 83 protein-coding genes, 8 ribosomal RNA genes, and 37 transfer RNA genes. Phylogenetic analyses indicated that B. frutescens and other the 13 were clustered to the family of Myrtaceae. These findings are crucial for the conservation and utilization of this important plant species. Additionally, they underscore the potential for future research on the evolution and preservation of B. frutescens, which could be advantageous in pharmaceutical applications.

Accurate assembly of circular RNAs with TERRACE.

Circular RNA (circRNA) is a class of RNA molecules that forms a closed loop with their 5' and 3' ends covalently bonded. CircRNAs are known to be more stable than linear RNAs, have distinct properties and functions, and are promising biomarkers. Existing methods for assembling circRNAs heavily rely on the annotated transcriptomes, hence exhibiting unsatisfactory accuracy without a high-quality transcriptome. We present TERRACE, a new algorithm for full-length assembly of circRNAs from paired-end total RNA-seq data. TERRACE uses the splice graph as the underlying data structure that organizes the splicing and coverage information. We transform the problem of assembling circRNAs into finding paths that "bridge" the three fragments in the splice graph induced by back-spliced reads. We adopt a definition for optimal bridging paths and a dynamic programming algorithm to calculate such optimal paths. TERRACE features an efficient algorithm to detect back-spliced reads missed by RNA-seq aligners, contributing to its much-improved sensitivity. It also incorporates a new machine-learning approach trained to assign a confidence score to each assembled circRNA, which is shown to be superior to using abundance for scoring. On both simulations and biological data sets, TERRACE consistently outperforms existing methods by a large margin in sensitivity while achieving better or comparable precision. In particular, when the annotations are not provided, TERRACE assembles 123%-413% more correct circRNAs than state-of-the-art methods. TERRACE presents a significant advance in assembling full-length circRNAs from RNA-seq data, and we expect it to be widely used in future research on circRNAs.

Don't let valuable microbiome data go to waste: combined usage of merging and direct-joining of sequencing reads for low-quality paired-end amplicon data.

The pernicious nature of low-quality sequencing data warrants improvement in the bioinformatics workflow for profiling microbial diversity. The conventional merging approach, which drops a copious amount of sequencing reads when processing low-quality amplicon data, requires alternative methods. In this study, a computational workflow, a combination of merging and direct-joining where the paired-end reads lacking overlaps are concatenated and pooled with the merged sequences, is proposed to handle the low-quality amplicon data. The proposed computational strategy was compared with two workflows; the merging approach where the paired-end reads are merged, and the direct-joining approach where the reads are concatenated. The results showed that the merging approach generates a significantly low number of amplicon sequences, limits the microbiome inference, and obscures some microbial associations. In comparison to other workflows, the combination of merging and direct-joining strategy reduces the loss of amplicon data, improves the taxonomy classification, and importantly, abates the misleading results associated with the merging approach when analysing the low-quality amplicon data. The mock community analysis also supports the findings. In summary, the researchers are suggested to follow the merging and direct-joining workflow to avoid problems associated with low-quality data while profiling the microbial community structure.

CAREx: context-aware read extension of paired-end sequencing data

BackgroundCommonly used next generation sequencing machines typically produce large amounts of short reads of a few hundred base-pairs in length. However, many downstream applications would generally benefit from longer reads.ResultsWe present CAREx—an algorithm for the generation of pseudo-long reads from paired-end short-read Illumina data based on the concept of repeatedly computing multiple-sequence-alignments to extend a read until its partner is found. Our performance evaluation on both simulated data and real data shows that CAREx is able to connect significantly more read pairs (up to 99%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$99\\%$$\\end{document} for simulated data) and to produce more error-free pseudo-long reads than previous approaches. When used prior to assembly it can achieve superior de novo assembly results. Furthermore, the GPU-accelerated version of CAREx exhibits the fastest execution times among all tested tools.ConclusionCAREx is a new MSA-based algorithm and software for producing pseudo-long reads from paired-end short read data. It outperforms other state-of-the-art programs in terms of (i) percentage of connected read pairs, (ii) reduction of error rates of filled gaps, (iii) runtime, and (iv) downstream analysis using de novo assembly. CAREx is open-source software written in C++ (CPU version) and in CUDA/C++ (GPU version). It is licensed under GPLv3 and can be downloaded at (https://github.com/fkallen/CAREx).

Diagnostic Utility of Comprehensive RNA-Seq Analysis in Adult B-ALL

Introduction Adult B-cell acute lymphoblastic leukemia (B-ALL) comprises 75% of adult ALL cases. The classification and risk stratification of patients have conventionally relied on cytogenetics analysis. However, cytogenetics has limitations due to its reliance on metaphase cells, which can mitigate classification accuracy. In recent years, transcriptome sequencing (RNA-seq) of large pediatrics ALL cohorts has expanded the number of recurrent gene fusions recognized as disease defining events and informed risk stratification [Brady et al. 2022, Mullighan et al. 2017]. This study aims to evaluate the diagnostic utility of RNA-seq for clinical subtype classification in adult B-ALL in a large representative cohort. Methods The study cohort comprised 338 adult patients (25-65 years) with newly diagnosed ALL (UKALL14, ISRCTN66541317, NCT01085617). Paired-end RNA-seq data at 60 Million reads per sample were generated. Analysis focused on the detection of disease-defining gene fusions and gene expression signatures. Three RNA fusion callers (FusionCatcher, FuSeq, and STAR-Fusion) and three expression-based classifiers (ALLSorts, ALLspice, and ALLCatchR) were used for consensus fusion calling and expression-based classification, respectively [Nicorici et al. 2014, Vu et al. 2018, Haas et al. 2019, Schmidt et al., Mäkinen et al., Bader et al. 2022]. Integration of classification results from expression-based classifiers and the consensus gene fusions provides 4 levels of RNA-derived subtype information, denoted as “RNA evidence” in this study. These RNA-seq based classification results were compared with clinical cytogenetics findings. Results Out of 338 samples in this cohort, cytogenetics unequivocally classified 73% (246/338) of the samples. By integrating RNA expression-based classification with fusion subtypes, we confidently classified 87% (295/338) of the cohort with at least 2 levels of RNA evidence. In total, consensus gene fusions were identified in 74% (249/338), while expression-based classifiers assigned a confident subtype to 82% (319/338). Subsequently, we compared cytogenetics with RNA-seq derived classification and found a high concordance of 98% (240/246) between the two approaches. Only 6 (<2%) samples with cytogenetics subtypes were not classified by RNA-seq, attributed to specific subtype characteristics (near-haploid) or lower RNA purity/quality. 27% (92/338) of subjects were not classified by cytogenetics (31 missing/failed and 61 indeterminate cytogenetics). Of the 31 samples with failed/missing cytogenetics, RNA-seq confidently assigned a class in 74% (23/31). For the remaining 61 cases with indeterminate cytogenetic (complex/other), RNA-seq resolved classification in 74% (45/61). Taken together, this improved the classification for 20% (68/338) of the entire cohort that was previously unclassified through cytogenetics. Notably, RNA-seq-exclusive findings were enriched in subtypes like DUX4, PAX5alt, and ZNF384, which are challenging for cytogenetics to discern. Importantly, integration of RNA-seq with cytogenetics led to a confident subtype classification for 93% of the cohort (314/338), a significant improvement over the initial 73% based on cytogenetics alone. Conclusions In conclusion, our study highlights the relevance of integrated RNA-seq analysis for reliable and comprehensive subtype classification in adult B-ALL. The high concordance between cytogenetics and RNA-derived subtypes underscores their complementary roles, providing valuable insights into disease mechanisms and guiding personalized treatment strategies.

Deep Resequencing of the 1q22 Locus in Non-Lobar Intracerebral Hemorrhage.

Genome-wide association studies have identified 1q22 as a susceptibility locus for cerebral small vessel diseases, including non-lobar intracerebral hemorrhage (ICH) and lacunar stroke. In the present study, we performed targeted high-depth sequencing of 1q22 in ICH cases and controls to further characterize this locus and prioritize potential causal mechanisms, which remain unknown. A total of 95,000 base pairs spanning 1q22, including SEMA4A, SLC25A44, and PMF1/PMF1-BGLAP were sequenced in 1,055 spontaneous ICH cases (534 lobar and 521 non-lobar) and 1,078 controls. Firth regression and Rare Variant Influential Filtering Tool analysis were used to analyze common and rare variants, respectively. Chromatin interaction analyses were performed using Hi-C, chromatin immunoprecipitation followed by sequencing, and chromatin interaction analysis with paired-end tag databases. Multivariable Mendelian randomization assessed whether alterations in gene-specific expression relative to regionally co-expressed genes at 1q22 could be causally related to ICH risk. Common and rare variant analyses prioritized variants in SEMA4A 5'-UTR and PMF1 intronic regions, overlapping with active promoter and enhancer regions based on ENCODE annotation. Hi-C data analysis determined that 1q22 is spatially organized in a single chromatin loop, and that the genes therein belong to the same topologically associating domain. Chromatin immunoprecipitation followed by sequencing and chromatin interaction analysis with paired-end tag data analysis highlighted the presence of long-range interactions between the SEMA4A-promoter and PMF1-enhancer regions prioritized by association testing. Multivariable Mendelian randomization analyses demonstrated that PMF1 overexpression could be causally related to non-lobar ICH risk. Altered promoter-enhancer interactions leading to PMF1 overexpression, potentially dysregulating polyamine catabolism, could explain demonstrated associations with non-lobar ICH risk at 1q22, offering a potential new target for prevention of ICH and cerebral small vessel disease. ANN NEUROL 2024;95:325-337.

INSurVeyor: improving insertion calling from short read sequencing data

Insertions are one of the major types of structural variations and are defined as the addition of 50 nucleotides or more into a DNA sequence. Several methods exist to detect insertions from next-generation sequencing short read data, but they generally have low sensitivity. Our contribution is two-fold. First, we introduce INSurVeyor, a fast, sensitive and precise method that detects insertions from next-generation sequencing paired-end data. Using publicly available benchmark datasets (both human and non-human), we show that INSurVeyor is not only more sensitive than any individual caller we tested, but also more sensitive than all of them combined. Furthermore, for most types of insertions, INSurVeyor is almost as sensitive as long reads callers. Second, we provide state-of-the-art catalogues of insertions for 1047 Arabidopsis Thaliana genomes from the 1001 Genomes Project and 3202 human genomes from the 1000 Genomes Project, both generated with INSurVeyor. We show that they are more complete and precise than existing resources, and important insertions are missed by existing methods.

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture

ASAS-EGB: A statistical framework for estimating allele-specific alternative splicing events using transcriptome data

Ubiquitous Alternative splicing (AS) in eukaryotes greatly increases the biodiversity of proteins and involves in disease and cancer. Allele-specific AS studies can facilitate the identification of cis-acting elements because both alleles share the same cellular environment. Due to the limited information provided on the exons defined by AS events, we propose a statistical framework and algorithm ASAS-EGB for ASAS analysis using the gene transcriptome. The framework obtains exclusively compatible sets of gene isoforms supporting each event isoform, and uses both phased and non-phased SNPs within the exons on the gene isoforms for inference. Using this strategy, we have demonstrated ASAS-EGB can yield better ASAS inferential performance than using event isoforms. ASAS-EGB supports both single-end and paired-end RNA-seq data, and we have proved its robustness using RNA-seq replicates of individual NA12878. ASAS-EGB builds Bayesian models for ASAS analysis, and the MCMC method is used to solve the problem. With more detailed annotations for individual genomes and transcriptomes appearing in the future, the algorithm proposed by the paper can provide better support for these data to reveal the regulatory mechanisms of individual genomes.

Genetic and Microenvironment Features Do Not Distinguish Follicular Lymphoma Patients Requiring Immediate or Deferred Treatment.

Genetic and Microenvironment Features Do Not Distinguish Follicular Lymphoma Patients Requiring Immediate or Deferred Treatment.

FishGET: A fish gene expression and transcriptome database with improved accuracy and visualization

With the rapid expansion of transcriptome studies in many fishes, a great number of RNA-seq data have been published, allowing for a more systematic understanding of the general profiles and details of gene expression in fish. FishGET is dedicated to gathering and curating fish RNA-seq data to discover more new RNAs, including mRNA and lncRNA, thereby getting a more complete reference transcriptome and providing more comprehensive and accurate transcriptome annotations. We obtained a total of 1362 RNA-seq paired-end data of 8 fishes from 97 different studies, and then we performed transcript assembly, meta-assembly, weighted gene co-expression network analysis (WGCNA), functional annotations, neighbor location annotation, lncRNA type annotation, homology annotation. To promote research into fish genes at the transcriptional level, we developed a user-friendly web interface that allows users to view all information and makes use of multiple types of dynamic interactive visualization services.

Plumbagin modulates RANKL-induced osteoclast and osteoblast differentiation

BackgroundBone remodeling is a balanced, dynamic function of two counteractive processes: osteoblasts-mediated bone formation and osteoclasts-dependent bone resorption. An imbalance between these two processes causes bone diseases. Herein, the effects and molecular modus operandi of plumbagin- a bioactive phytometabolite from Plumbago sp. have been investigated on osteoblast and osteoclast differentiation. Material and MethodsCell viability assay and Alizarin red-S staining assessed the plumbagin effects on pre-osteoblastic MC3T3-E1 cell viability and differentiation. Alkaline phosphatase activity, the osteoblast-specific genes, and protein expression were investigated by colorimetry, quantitative-PCR and immunoblotting, respectively. TRAP assay and osteoclast-specific proteins' expression assessed plumbagin's effect on osteoclastogenesis. During plumbagin-driven osteoclastogenesis, we used paired-end RNA-sequencing data to identify the key up-/down-regulated DEGs, validation by qPCR, and bioinformatics-based pathway analysis. ResultsPlumbagin at a very low dose (0.25 µM) significantly promoted osteoblast differentiation, as evident from alkaline phosphatase, matrix mineralization, and enhanced expression of osteoblast-specific markers, including Runx2 and its target genes. The reduced TRAP activity, osteoclast-specific protein expression, and RNA sequencing suggested RANKL-induced osteoclastogenesis inhibition by plumbagin at 2 µM.. ConclusionPlumbagin significantly enhances osteoblast differentiation by enhanced matrix mineralization and osteoblast-specific gene expression but suppresses the RANKL-induced osteoclastogenesis by regulating key osteoclast-specific DEGs and protein expression. Plumbagin can thus significantly influence bone biology and affect bone diseases.

Sample paired-end RNA-seq data from four human macophage samples (chromsome 21 only)

Sample paired-end RNA-seq data from four human macophage samples (chromsome 21 only)

The complete chloroplast genome of Prunus phaeosticta (Hance) Maxim. (Rosaceae) and its phylogenetic implications

The complete chloroplast (cp) genome of Prunus phaeosticta (Hance) Maxim. has been characterized by reference-based assembly using Illumina paired-end data. The circular complete cp genome is 158,752 bp in length, comprising a large single-copy (LSC) region of 87,085 bp, a small single-copy (SSC) region of 18,923 bp, and a pair of inverted repeats (IRs) of 26,372 bp.A total of 129 functional genes were identified, including 84 protein-coding genes, 37 tRNA genes, and 8 ribosomal RNA genes. The phylogenetic analysis showed that P. phaeosticta displayed a kinship to Prunus zippeliana.

Genome survey sequencing and mining of genome-wide microsatellite markers in yellow-billed babbler (Turdoides affinis)

Turdoides affinis is a species of group dwelling old world passerine of family Leiothrichidae. Unavailability of genome-wide sequence and species-specific molecular markers have hindered comprehensive understanding of cooperative breeding behaviour in T. affinis. Therefore, we generated genome-wide microsatellite markers through whole genome short read sequencing of T. affinis. A total of 68.8 gigabytes of paired-end raw data were sequenced containing 195,067,054 reads. Total sequenced reads spanned a coverage of 17X with genome size of 1.18 Gb. A large number of microsatellite markers (265,297) were mined in the T. affinis genome using Krait, and 50 most informative markers were identified and validated further. In-silico PCR results validated 47 markers. Of these 47 markers, five were randomly selected and validated in-vitro in twelve individuals of T. affinis. Genotyping data on these five loci estimated observed heterozygosity (H0) and expected heterozygosity (He) ratios between 0.333 – 0.833 and 0.851–0.906, respectively. Effective allele size ranged from 6.698 to 10.667, inbreeding coefficient of the population ranged from 0.080 to 0.631 and null allele frequency was calculated at 0.055 to 0.303. Polymorphic information content of all the five loci varied between 0.850 and 0.906. Probabilities of exclusion and identity across 5 loci was estimated to be 0.95 and 0.0036, respectively. All the loci showed significant adherence to Hardy-Weinberg equilibrium. The microsatellite markers reported in this study will facilitate future population genetics studies on T. affinis and other congeneric species.

SAMStat 2: quality control for next generation sequencing data.

SAMStat is an efficient program to extract quality control metrics from fastq and SAM/BAM files. A distinguishing feature is that it displays sequence composition, base quality composition and mapping error profiles split by mapping quality. This allows users to rapidly identify reasons for poor mapping including the presence of untrimmed adapters or poor sequencing quality at individual read positions. Here, we present a major update to SAMStat. The new version now supports paired-end and long-read data. Quality control plots are drawn using the ploty javascript library. The source code of SAMStat and code to reproduce the results are found here: https://github.com/timolassmann/samstat.

TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile

Determining transcriptional factor binding sites (TFBSs) is critical for understanding the molecular mechanisms regulating gene expression in different biological conditions. Biological assays designed to directly mapping TFBSs require large sample size and intensive resources. As an alternative, ATAC-seq assay is simple to conduct and provides genomic cleavage profiles that contain rich information for imputing TFBSs indirectly. Previous footprint-based tools are inheritably limited by the accuracy of their bias correction algorithms and the efficiency of their feature extraction models. Here we introduce TAMC (Transcriptional factor binding prediction from ATAC-seq profile at Motif-predicted binding sites using Convolutional neural networks), a deep-learning approach for predicting motif-centric TF binding activity from paired-end ATAC-seq data. TAMC does not require bias correction during signal processing. By leveraging a one-dimensional convolutional neural network (1D-CNN) model, TAMC make predictions based on both footprint and non-footprint features at binding sites for each TF and outperforms existing footprinting tools in TFBS prediction particularly for ATAC-seq data with limited sequencing depth.

The complete chloroplast genome of Rubus pacificus (Rosaceae)

The complete chloroplast genome of Rubus pacificus, a representative species of R. sect. Malachobatus subsect. Stipulosi, has been characterized by reference-based assembly using Illumina paired-end data. The complete chloroplast genome is 156,255 bp in length, containing a large single-copy region (LSC) of 85,864 bp and a small single-copy region (SSC) of 18,849 bp, which are separated by a pair of inverted repeat regions (IR) of 25,771 bp. A total of 129 genes were predicted from the chloroplast genome, including 85 protein-coding genes, 36 tRNA genes, and eight rRNA genes. According to the present sampling, phylogenetic analysis reveals that R. pacificus and R. laciniatostipulatus form a strongly supported clade and R. sect. Malachobatus subsect. Stipulosi is not monophyletic.

P-530 tRNA fragments in follicle fluid can be explored in Diminished Ovarian Reserve patients as a marker of IVF outcomes

Abstract Study question Can tRNA fragments in follicle fluid be explored for markers that predict blastocyst formation in patients with diminished ovarian reserve? Summary answer tRNA-Ser-CGA-4 is up-regulated in the follicle fluid of patients with diminished ovarian reserve (DOR) What is known already tRNA fragments are a novel class of small non-coding RNAs that have been shown to play regulatory roles in reproductive biology. Study design, size, duration Non-Randomized case control study in patients presenting for IVF treatment at a University affiliated fertility clinic from September 2020- January 2021. Thirty three patients were included: 15 patients with DOR and 18 controls. Participants/materials, setting, methods Patients were stimulated by appropriate protocols according to their age, diagnosis and AMH. At retrieval, non-bloody follicle fluid (FF) was retrieved for after removing the cumulus-oophorus complex. FF was centrifuged at 1600 g x 10 mins and filtered with 80 nm filter for analysis. Main results and the role of chance There were no differences between the two groups with respect to age, BMI and duration of infertility. The mean age was 35.1 years As anticipated, the mean AMH, antral follicle count and number of eggs retrieved were statistically lower in the DOR groups compared with controls (<0.05) The fertilization rate was 61.2% in DOR vs 79.5% in controls The blastocyst rate was 39.5% in DOR patients and 50.6% in controls Total RNA yield was lower in DOR patients, as 50% of the DOR samples had undetectable levels (p < 0.001). Samples were predominantly processed in duplicate. Input into the pipeline was paired end data which showed an overall tRNA fragment count that was higher in the DOR population. Log2FC showed an up-regulation of the tRNA fragments tRNA-Ser-CGA-4, tRNA-Cys-GCA-15, tRNA-Cys-GCA-10 and tRNA-Cys-GCA-19 in the DOR population. Limitations, reasons for caution Undetectable levels in follicle fluid of some of the DOR patients introduced selection bias Larger sample size and broader applicability across various ethnic groups. Wider implications of the findings Follicle fluid can be explored to give insight into the signaling pathways of ovarian biology Non-invasive method of assessing oocyte competence Useful in explaining the pathophysiology of DOR Can these findings assist is in the identification of therapeutic targets to delay the progression of age related/non-age related DOR? Trial registration number not applicable

The complete chloroplast genome of Crepis rigescens (Cichorioideae), a traditional Chinese medicinal plant

Crepis rigescens, Diels 1921 is a traditional Chinese medicinal plant of Cichorioideae, which contains many chemicals, such as friedelin, β-sitosterol, stigmasterol, chlorogenic acid, and flavonoids, and so on, which has the characteristics of high medicinal value and small side effect. Crepis rigescens was used as folk medicines for anti-bacterial, and anti-oxidation, which also had a potential curative effect in preventing cardiovascular disease and anti-tumor. Illumina paired-end reads data were used to assemble the complete chloroplast (cp) genome. 14,425,796 raw paired-end reads and the length distribution in 124,685 bp, including a large single copy (LSC) region of 82,924 bp, a small single copy (SSC) region of 18,150 bp, and a pair of inverted repeat (IRs) regions of 25,128 bp. Besides, 10 protein-coding genes (PCGs) genes and 6 tRNAs genes possess a single intron, while clpP and ycf3 have a couple of introns. Based on the concatenated coding sequences of cp PCGs, the phylogenetic analysis showed that C. rigescens and Hypochaeris radicata (MH746729) are closely related to each other within the family Cichorioideae.