Improving the efficiency of single-cell genome sequencing based on overlapping pooling strategy and CNV analysis
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ABSTRACT:
SUBMITTER: Tu J
PROVIDER: S-EPMC8790377 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND: Cucumis melo (melon) belongs to the Cucurbitaceae family, whose economic importance among horticulture crops is second only to Solanaceae. Melon has a high intra-specific genetic variation, morphologic diversity and a small genome size (454 Mb), which make it suitable for a great variety of molecular and genetic studies. A number of genetic and genomic resources have already been developed, such as several genetic maps, BAC genomic libraries, a BAC-based physical map and EST collections. Sequence information would be invaluable to complete the picture of the melon genomic landscape, furthering our understanding of this species' evolution from its relatives and providing an important genetic tool. However, to this day there is little sequence data available, only a few melon genes and genomic regions are deposited in public databases. The development of massively parallel sequencing methods allows envisaging new strategies to obtain long fragments of genomic sequence at higher speed and lower cost than previous Sanger-based methods. RESULTS: In order to gain insight into the structure of a significant portion of the melon genome we set out to perform massive sequencing of pools of BAC clones. For this, a set of 57 BAC clones from a double haploid line was sequenced in two pools with the 454 system using both shotgun and paired-end approaches. The final assembly consists of an estimated 95% of the actual size of the melon BAC clones, with most likely complete sequences for 50 of the BACs, and a total sequence coverage of 39x. The accuracy of the assembly was assessed by comparing the previously available Sanger sequence of one of the BACs against its 454 sequence, and the polymorphisms found involved only 1.7 differences every 10,000 bp that were localized in 15 homopolymeric regions and two dinucleotide tandem repeats. Overall, the study provides approximately 6.7 Mb or 1.5% of the melon genome. The analysis of this new data has allowed us to gain further insight into characteristics of the melon genome such as gene density, average protein length, or microsatellite and transposon content. The annotation of the BAC sequences revealed a high degree of collinearity and protein sequence identity between melon and its close relative Cucumis sativus (cucumber). Transposon content analysis of the syntenic regions suggests that transposition activity after the split of both cucurbit species has been low in cucumber but very high in melon. CONCLUSIONS: The results presented here show that the strategy followed, which combines shotgun and BAC-end sequencing together with anchored marker information, is an excellent method for sequencing specific genomic regions, especially from relatively compact genomes such as that of melon. However, in agreement with other results, this map-based, BAC approach is confirmed to be an expensive way of sequencing a whole plant genome. Our results also provide a partial description of the melon genome's structure. Namely, our analysis shows that the melon genome is highly collinear with the smaller one of cucumber, the size difference being mainly due to the expansion of intergenic regions and proliferation of transposable elements.
| S-EPMC3095328 | biostudies-literature
Project description:Though single cell RNA sequencing (scRNA-seq) technologies have been well developed, the acquisition of large-scale single cell expression data may still lead to high costs. Single cell expression profile has its inherent sparse properties, which makes it compressible, thus providing opportunities for solutions. Here, by computational simulation as well as experiment of 54 single cells, we propose that expression profiles can be compressed from the dimension of samples by overlapped assigning each cell into plenty of pools. And we prove that expression profiles can be inferred from these pool expression data with overlapped pooling design and compressed sensing strategy. We also show that by combining this approach with plate-based scRNA-seq measurement, it can maintain its superiorities in gene detection sensitivity and individual identity and recover the expression profile with high precision, while saving about half of the library cost. This method can inspire novel conceptions on the measurement, storage or computation improvements for other compressible signals in many biological areas.
| S-EPMC8373083 | biostudies-literature
Project description:In this paper, we present a novel method to improve the efficiency of single-cell transcriptome sequencing for analyzing valuable cell samples. The microfluidic device we designed integrates multiple single-cell isolation chambers with hydrodynamic traps and achieves a nearly 100% single-cell capture rate and minimal cell loss, making it particularly suitable for samples with limited numbers of cells. Single cells were encapsulated using a novel phase-switch method into picoliter-sized hydrogel droplets and easily recovered for subsequent reactions. Minimizing the reaction volume resulted in a high reverse transcription (RT) efficiency for RNA sequencing (RNA-Seq). With this novel microfluidic platform, we captured dozens of hESCs (H9) simultaneously and obtained live cells in individual picoliter volumes, thus allowing for the convenient construction of a high-quality library for deep single-cell RNA-Seq. Our single-cell RNA-Seq results confirmed that a spectrum of pluripotency existed within an H9 colony. This integrated microfluidic platform can be applied to various cell types for the investigation of rare cellular events, and the phase-switch single-cell processing strategy will improve the efficiency and accessibility of single-cell transcriptome sequencing analysis.
| S-EPMC6925944 | biostudies-literature
Project description:BackgroundThe advantages of Pacific Biosciences (PacBio) single-molecule real-time (SMRT) technology include long reads, low systematic bias, and high consensus read accuracy. Here we use these attributes to improve on the genome annotation of the parasitic hookworm Ancylostoma ceylanicum using PacBio RNA-Seq.ResultsWe sequenced 192,888 circular consensus sequences (CCS) derived from cDNAs generated using the CloneTech SMARTer system. These SMARTer-SMRT libraries were normalized and size-selected providing a robust population of expressed structural genes for subsequent genome annotation. We demonstrate PacBio mRNA sequences based genome annotation improvement, compared to genome annotation using conventional sequencing-by-synthesis alone, by identifying 1609 (9.2%) new genes, extended the length of 3965 (26.7%) genes and increased the total genomic exon length by 1.9 Mb (12.4%). Non-coding sequence representation (primarily from UTRs based on dT reverse transcription priming) was particularly improved, increasing in total length by fifteen-fold, by increasing both the length and number of UTR exons. In addition, the UTR data provided by these CCS allowed for the identification of a novel SL2 splice leader sequence for A. ceylanicum and an increase in the number and proportion of functionally annotated genes. RNA-seq data also confirmed some of the newly annotated genes and gene features.ConclusionOverall, PacBio data has supported a significant improvement in gene annotation in this genome, and is an appealing alternative or complementary technique for genome annotation to the other transcript sequencing technologies.
| S-EPMC5833154 | biostudies-literature
Project description:BackgroundCopy number variation (CNV) analysis is an integral component of the study of human genomes in both research and clinical settings. Array-based CNV analysis is the current first-tier approach in clinical cytogenetics. Decreasing costs in high-throughput sequencing and cloud computing have opened doors for the development of sequencing-based CNV analysis pipelines with fast turnaround times. We carry out a systematic and quantitative comparative analysis for several low-coverage whole-genome sequencing (WGS) strategies to detect CNV in the human genome.MethodsWe compared the CNV detection capabilities of WGS strategies (short insert, 3 kb insert mate pair and 5 kb insert mate pair) each at 1×, 3× and 5× coverages relative to each other and to 17 currently used high-density oligonucleotide arrays. For benchmarking, we used a set of gold standard (GS) CNVs generated for the 1000 Genomes Project CEU subject NA12878.ResultsOverall, low-coverage WGS strategies detect drastically more GS CNVs compared with arrays and are accompanied with smaller percentages of CNV calls without validation. Furthermore, we show that WGS (at ≥1× coverage) is able to detect all seven GS deletion CNVs >100 kb in NA12878, whereas only one is detected by most arrays. Lastly, we show that the much larger 15 Mbp Cri du chat deletion can be readily detected with short-insert paired-end WGS at even just 1× coverage.ConclusionsCNV analysis using low-coverage WGS is efficient and outperforms the array-based analysis that is currently used for clinical cytogenetics.
| S-EPMC8131063 | biostudies-literature
Project description:We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method.
| S-EPMC3700900 | biostudies-literature
Project description:Copy number variants (CNVs) constitute an important class of genetic variants in human genome and are shown to be associated with complex diseases. Whole-genome sequencing provides an unbiased way of identifying all the CNVs that an individual carries. In this paper, we consider parametric modeling of the read depth (RD) data from whole-genome sequencing with the aim of identifying the CNVs, including both Poisson and negative-binomial modeling of such count data. We propose a unified approach of using a mean-matching variance stabilizing transformation to turn the relatively complicated problem of sparse segment identification for count data into a sparse segment identification problem for a sequence of Gaussian data. We apply the optimal sparse segment identification procedure to the transformed data in order to identify the CNV segments. This provides a computationally efficient approach for RD-based CNV identification. Simulation results show that this approach often results in a small number of false identifications of the CNVs and has similar or better performances in identifying the true CNVs when compared with other RD-based approaches. We demonstrate the methods using the trio data from the 1000 Genomes Project.
| S-EPMC4059462 | biostudies-literature
Project description:We aimed to develop a whole-genome sequencing (WGS)-based copy number variant (CNV) calling algorithm with the potential of replacing chromosomal microarray assay (CMA) for clinical diagnosis. JAX-CNV is thus developed for CNV detection from WGS data. The performance of this CNV calling algorithm was evaluated in a blinded manner on 31 samples and compared to the 112 CNVs reported by clinically validated CMAs for these 31 samples. The result showed that JAX-CNV recalled 100% of these CNVs. Besides, JAX-CNV identified an average of 30 CNVs per individual, respresenting an approximately seven-fold increase compared to calls of clinically validated CMAs. Experimental validation of 24 randomly selected CNVs showed one false positive, i.e., a false discovery rate (FDR) of 4.17%. A robustness test on lower-coverage data revealed a 100% sensitivity for CNVs larger than 300 kb (the current threshold for College of American Pathologists) down to 10× coverage. For CNVs larger than 50 kb, sensitivities were 100% for coverages deeper than 20×, 97% for 15×, and 95% for 10×. We developed a WGS-based CNV pipeline, including this newly developed CNV caller JAX-CNV, and found it capable of detecting CMA-reported CNVs at a sensitivity of 100% with about a FDR of 4%. We propose that JAX-CNV could be further examined in a multi-institutional study to justify the transition of first-tier genetic testing from CMAs to WGS. JAX-CNV is available at https://github.com/TheJacksonLaboratory/JAX-CNV.
| S-EPMC10225484 | biostudies-literature
Project description:BackgroundBirth defects are responsible for approximately 7% of neonatal deaths worldwide by World Health Organization in 2004. Many methods have been utilized for examining the congenital anomalies in fetuses. This study aims to investigate the efficiency of simultaneous CNV-seq and whole-exome sequencing (WES) in the diagnosis of fetal anomaly based on a large Chinese cohort.MethodsIn this cohort study, 1800 pregnant women with singleton fetus in Hubei Province were recruited from 2018 to 2020 for prenatal ultrasonic screening. Those with fetal structural anomalies were transferred to the Maternal and Child Health Hospital of Hubei Province through a referral network in Hubei, China. After multidisciplinary consultation and decision on fetal outcome, products of conception (POC) samples were obtained. Simultaneous CNV-seq and WES was conducted to identify the fetal anomalies that can compress initial DNA and turnaround time of reports.ResultsIn total, 959 couples were finally eligible for the enrollment. A total of 227 trios were identified with a causative alteration (CNV or variant), among which 191 (84.14%) were de novo. Double diagnosis of pathogenic CNVs and variants have been identified in 10 fetuses. The diagnostic yield of multisystem anomalies was significantly higher than single system anomalies (32.28% vs. 22.36%, P = 0.0183). The diagnostic rate of fetuses with consistent intra- and extra-uterine phenotypes (172/684) was significantly higher than the rate of these with inconsistent phenotypes (17/116, P = 0.0130).ConclusionsSimultaneous CNV-seq and WES analysis contributed to fetal anomaly diagnosis and played a vital role in elucidating complex anomalies with compound causes.
| S-EPMC8722033 | biostudies-literature
Project description:High-throughput transcriptomics is of increasing fundamental biological and clinical interest. The generation of molecular data from large collections of samples, such as biobanks and drug libraries, is boosting the development of new biomarkers and treatments. Focusing on gene expression, the transcriptomic market exploits the benefits of next-generation sequencing (NGS), leveraging RNA sequencing (RNA-seq) as standard for measuring genome-wide gene expression in biological samples. The cumbersome sample preparation, including RNA extraction, conversion to cDNA and amplification, prevents high-throughput translation of RNA-seq technologies. Bulk RNA barcoding and sequencing (BRB-seq) addresses this limitation by enabling sample preparation in multi-well plate format. Sample multiplexing combined with early pooling into a single tube reduces reagents consumption and manual steps. Enabling simultaneous pooling of all samples from the multi-well plate into one tube, our technology relies on smart labware: a pooling lid comprising fluidic features and small pins to transport the liquid, adapted to standard 96-well plates. Operated with standard fluidic tubes and pump, the system enables over 90% recovery of liquid in a single step in less than a minute. Large scale manufacturing of the lid is demonstrated with the transition from a milled polycarbonate/steel prototype into an injection molded polystyrene lid. The pooling lid demonstrated its value in supporting high-throughput barcode-based sequencing by pooling 96 different DNA barcodes directly from a standard 96-well plate, followed by processing within the single sample pool. This new pooling technology shows great potential to address medium throughput needs in the BRB-seq workflow, thereby addressing the challenge of large-scale and cost-efficient sample preparation for RNA-seq.
| S-EPMC10902082 | biostudies-literature