SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells.

Simultaneous sequencing of the genome and transcriptome at the single-cell level is a powerful tool for characterizing genomic and transcriptomic variation and revealing correlative relationships. However, it remains technically challenging to analyze both the genome and transcriptome in the same cell. Here, we report a novel method for simultaneous isolation of genomic DNA and total RNA (SIDR) from single cells, achieving high recovery rates with minimal cross-contamination, as is crucial for accurate description and integration of the single-cell genome and transcriptome. For reliable and efficient separation of genomic DNA and total RNA from single cells, the method uses hypotonic lysis to preserve nuclear lamina integrity and subsequently captures the cell lysate using antibody-conjugated magnetic microbeads. Evaluating the performance of this method using real-time PCR demonstrated that it efficiently recovered genomic DNA and total RNA. Thorough data quality assessments showed that DNA and RNA simultaneously fractionated by the SIDR method were suitable for genome and transcriptome sequencing analysis at the single-cell level. The integration of single-cell genome and transcriptome sequencing by SIDR (SIDR-seq) showed that genetic alterations, such as copy-number and single-nucleotide variations, were more accurately captured by single-cell SIDR-seq compared with conventional single-cell RNA-seq, although copy-number variations positively correlated with the corresponding gene expression levels. These results suggest that SIDR-seq is potentially a powerful tool to reveal genetic heterogeneity and phenotypic information inferred from gene expression patterns at the single-cell level.

Performance evaluation of commercial library construction kits for PCR-based targeted sequencing using a unique molecular identifier.

BACKGROUND: Target enrichment is a critical component of targeted deep next-generation sequencing for the cost-effective and sensitive detection of mutations, which is predominantly performed by either hybrid selection or PCR. Despite the advantages of efficient enrichment, PCR-based methods preclude the identification of PCR duplicates and their subsequent removal. Recently, this limitation was overcome by assigning a unique molecular identifier(UMI) to each template molecule. Currently, several commercial library construction kits based on PCR enrichment are available for UMIs, but there have been no systematic studies to compare their performances. In this study, we evaluated and compared the performances of five commercial library kits from four vendors: the Archer® Reveal ctDNA™ 28 Kit, NEBNext Direct® Cancer HotSpot Panel, Nugen Ovation® Custom Target Enrichment System, Qiagen Human Comprehensive Cancer Panel(HCCP), and Qiagen Human Actionable Solid Tumor Panel(HASTP). RESULTS: We evaluated and compared the performances of the five kits using 50 ng of genomic DNA for the library construction in terms of the library complexity, coverage uniformity, and errors in the UMIs. While the duplicate rates for all kits were dramatically decreased by identifying unique molecules with UMIs, the Qiagen HASTP achieved the highest library complexity based on the depth of unique coverage indicating superb library construction efficiency. Regarding the coverage uniformity, the kits from Nugen and NEB performed the best followed by the kits from Qiagen. We also analyzed the UMIs, including errors, which allowed us to adjust the depth of unique coverage and the length required for sufficient complexity. Based on these comparisons, we selected the Qiagen HASTP for further performance evaluations. The targeted deep sequencing method based on PCR target enrichment combined with UMI tagging sensitively detected mutations present at a frequency as low as 1% using 6.25 ng of human genomic DNA as the starting material. CONCLUSION: This study is the first systematic evaluation of commercial library construction kits for PCR-based targeted deep sequencing utilizing UMIs. Because the kits displayed significant variability in different quality metrics, our study offers a practical guideline for researchers to choose appropriate options for PCR-based targeted sequencing and useful benchmark data for evaluating new kits.

Behavioral Changes in Preschool- and School-Age Korean Children: A Network Analysis.

The relationships between symptoms that comprise behavioral problems in children can be traced longitudinally to provide long-term support. This study identified signs that should be considered important in school age children by tracking changes in the relationships between different symptoms of behavioral problems in preschool and school age children. This study used Gaussian graphical network analysis to clarify the interaction of the overall subscales constituting the K-CBCL (Korean Child Behavior Checklist) and centrality in the network. In the Panel Study on Korean Children (PSKC), the K-CBCL/1.5-5 was used for children up to age six (first grade, elementary school), and the K-CBCL/6-18 was used for older children. In this study, 1323 PSKC samples (boys, n = 671; girls, n = 652) were used to distinguish nonclinical and (sub)clinical groups (T-score ≥ 60) compared to node centrality in each group's CBCL subscale networks. Depression/anxiety was a persistent core symptom of the behavioral problem network in 5- and 7-year-old children. A new core symptom in 7-year-old children was posttraumatic stress problems added in version CBCL/6-18. Based on these results, it is necessary to consider both anxiety/depression and posttraumatic stress problems in preschool children to support the adaptation of school-age children.

Application of a Bayesian Network Learning Model to Predict Longitudinal Trajectories of Executive Function Difficulties in Elementary School Students.

Executive function is the mental ability to modulate behavior or thinking to accomplish a task. This is developmentally important for children's academic achievements and ability to adjust to school. We classified executive function difficulties (EFDs) in longitudinal trajectories in Korean children from 7 to 10 years old. We found predictors of EFDs using latent class growth analysis and Bayesian network learning methods with Panel Study data. Three types of latent class models of executive function difficulties were identified: low, intermediate, and high EFDs. The modeling performance of the high EFD group was excellent (AUC = .91), and the predictors were the child's gender, temperamental emotionality, happiness, DSM (Diagnostic and Statistical Manual of Mental Disorders) anxiety problems, and the mother's depression as well as coparenting conflict recognized by the mother. The results show that using latent class growth analysis and Bayesian network learning are helpful in classifying the longitudinal EFD patterns in elementary school students. Furthermore, school-age EFD is affected by emotional problems in parents and children that continue from early life. These findings can support children's development and prevent risk by preclassifying children who may experience persistent EFD and tracing causes.

Timing of Adiposity Rebound and Determinants of Early Adiposity Rebound in Korean Infants and Children Based on Data from the National Health Insurance Service.

Adiposity rebound (AR) is defined as the second rise in the body mass index (BMI) usually occurring in early childhood. This study aimed to investigate the timing of AR and the factors determining early AR (EAR) by tracking BMI patterns using large-scale longitudinal nationwide data (n = 142,668; 73,389 boys and 69,279 girls) over seven time periods (4-6, 9-12, 18-24, 30-36, 42-48, 54-60, and 66-71 months). The average BMI rebound indicating AR was found before the age of 5 years (6th time period, 54-60 months). Interestingly, children experiencing BMI rebound during the 4th to 6th time periods showed a small increase in the proportion of underweight in the 2nd time period, but a dramatically higher proportion of underweight during the corresponding time period, similar to M-shaped patterns. In contrast, overweight or obese children in the above group showed opposite W-shaped patterns. The parameters predicting the risk of EAR are diverse for each time period by sex. Adequate breastfeeding before the age of 1 year, adequate diet, and reduced sugar-sweetened beverage consumption after the age of 1 year were important for reducing EAR. This study presents for the first time, the timing of AR and the major determinants of EAR among Korean infants and children based on large-scale nationwide data.

Utility of targeted deep sequencing for detecting circulating tumor DNA in pancreatic cancer patients.

Targeted deep sequencing across broad genomic regions has been used to detect circulating tumor DNA (ctDNA) in pancreatic ductal adenocarcinoma (PDAC) patients. However, since most PDACs harbor a mutation in KRAS, sequencing of broad regions needs to be systemically compared to analyzing only KRAS mutations for PDAC. Using capture-based targeted deep sequencing, we detected somatic tumor mutations in 17 fine needle aspiration biopsy and 69 longitudinal cell-free DNA (cfDNA) samples from 17 PDAC patients. KRAS mutations were detected in 10 out of 17 pretreatment patient plasma samples. Next, interrogation of genetic alterations in matched primary tumor samples detected ctDNA in 12 of 17 pretreatment plasma samples and cfDNA sequencing across the 83 target genes identified ctDNA in 15 of 17 cases (88.2% sensitivity). This improved sensitivity of ctDNA detection resulted in enhanced tumor burden monitoring when we analyzed longitudinal plasma samples. We found that cfDNA sequencing detected the lowest mutant allelic fractions and number of variants when complete response or partial response to chemotherapy was achieved. We demonstrated that ctDNA levels measured by targeted deep sequencing sensitively indicate the presence of cancer and correlate well with clinical responses to therapy and disease progression in PDAC patients.

Depression Is a Mediator for the Relationship between Physical Symptom and Psychological Well-being in Obese People.

This present study aimed to investigate the association effect of obesity status, physical symptom, insecure attachment, and depression on psychological well-being in non-diabetic healthy Koreans. Height, weight, waist circumference, blood pressure, and socio-psychological questionnaires (insecure attachment, depression, and physical symptom psychological well-being, etc.) were examined in 123 healthy Koreans. Student t-test, correlation analysis, and mediation analysis were performed. Study subjects were divided into 2 groups based on body mass index (BMI, kg/m2): obesity (BMI ≥ 25, n = 36) and non-obesity (BMI < 25, n = 87). Obese people were older and showed higher proportion of males than non-obese ones. Regarding the values of socio-psychological test, obesity group showed lower insecure attachment, and higher physical symptom than non-obesity group. In correlation and mediation analyses, depression was positively related to insecure attachment and physical symptom in both BMI groups. Positive relationship between physical symptom and insecure attachment was observed only in non-obesity group, but not in obesity group. The effect of insecure attachment on psychological well-being was completely mediated by depression in both BMI groups. On the other hand, the effect of physical symptom on psychological well-being was completely mediated by depression in obesity group, but not in non-obesity group. In conclusion, this study presented that the effects of physical symptom and insecure attachment on psychological well-being were completely mediated by depression in obese healthy Koreans, but not in non-obese ones. It will provide useful data for extending the knowledge on the relationship between the physical health and mental health.

Characterization of background noise in capture-based targeted sequencing data.

BACKGROUND: Targeted deep sequencing is increasingly used to detect low-allelic fraction variants; it is therefore essential that errors that constitute baseline noise and impose a practical limit on detection are characterized. In the present study, we systematically evaluate the extent to which errors are incurred during specific steps of the capture-based targeted sequencing process. RESULTS: We removed most sequencing artifacts by filtering out low-quality bases and then analyze the remaining background noise. By recognizing that plasma DNA is naturally fragmented to be of a size comparable to that of mono-nucleosomal DNA, we were able to identify and characterize errors that are specifically associated with acoustic shearing. Two-thirds of C:G > A:T errors and one quarter of C:G > G:C errors were attributed to the oxidation of guanine during acoustic shearing, and this was further validated by comparative experiments conducted under different shearing conditions. The acoustic shearing step also causes A > G and A > T substitutions localized to the end bases of sheared DNA fragments, indicating a probable association of these errors with DNA breakage. Finally, the hybrid selection step contributes to one-third of the remaining C:G > A:T and one-fifth of the C > T errors. CONCLUSIONS: The results of this study provide a comprehensive summary of various errors incurred during targeted deep sequencing, and their underlying causes. This information will be invaluable to drive technical improvements in this sequencing method, and may increase the future usage of targeted deep sequencing methods for low-allelic fraction variant detection.

Prevalence and detection of low-allele-fraction variants in clinical cancer samples.

Accurate detection of genomic alterations using high-throughput sequencing is an essential component of precision cancer medicine. We characterize the variant allele fractions (VAFs) of somatic single nucleotide variants and indels across 5095 clinical samples profiled using a custom panel, CancerSCAN. Our results demonstrate that a significant fraction of clinically actionable variants have low VAFs, often due to low tumor purity and treatment-induced mutations. The percentages of mutations under 5% VAF across hotspots in EGFR, KRAS, PIK3CA, and BRAF are 16%, 11%, 12%, and 10%, respectively, with 24% for EGFR T790M and 17% for PIK3CA E545. For clinical relevance, we describe two patients for whom targeted therapy achieved remission despite low VAF mutations. We also characterize the read depths necessary to achieve sensitivity and specificity comparable to current laboratory assays. These results show that capturing low VAF mutations at hotspots by sufficient sequencing coverage and carefully tuned algorithms is imperative for a clinical assay.

The minimal amount of starting DNA for Agilent's hybrid capture-based targeted massively parallel sequencing.

Targeted capture massively parallel sequencing is increasingly being used in clinical settings, and as costs continue to decline, use of this technology may become routine in health care. However, a limited amount of tissue has often been a challenge in meeting quality requirements. To offer a practical guideline for the minimum amount of input DNA for targeted sequencing, we optimized and evaluated the performance of targeted sequencing depending on the input DNA amount. First, using various amounts of input DNA, we compared commercially available library construction kits and selected Agilent's SureSelect-XT and KAPA Biosystems' Hyper Prep kits as the kits most compatible with targeted deep sequencing using Agilent's SureSelect custom capture. Then, we optimized the adapter ligation conditions of the Hyper Prep kit to improve library construction efficiency and adapted multiplexed hybrid selection to reduce the cost of sequencing. In this study, we systematically evaluated the performance of the optimized protocol depending on the amount of input DNA, ranging from 6.25 to 200 ng, suggesting the minimal input DNA amounts based on coverage depths required for specific applications.