Improving the accuracy of noninvasive prenatal testing through size-selection between fetal and maternal cfDNA.

OBJECTIVES: In general, fetal cfDNA is shorter than maternal cfDNA, and accuracy of noninvasive prenatal testing (NIPT) results can be improved by selecting shorter cfDNA fragments to enrich fetal-derived cfDNA. This study investigated potential improvements in the accuracy of NIPT by performing classification and analysis based on differences in cfDNA size. METHODS: We performed paired-end sequencing to identify size ranges of fetal and maternal cfDNA from 62,374 pregnant women. We then developed a size-selection method to isolate and analyze both fetal and maternal cfDNA, defining fetal-derived cfDNA as less than 150 bp and maternal-derived cfDNA as greater than 180 bp. RESULTS: By implementing size-selection method, the accuracy of NIPT was improved, resulting in an increase in the overall positive predictive value for all aneuploidies from 89.57% to 97.1%. This was achieved by enriching both fetal and maternal-derived cfDNA, which increased fetal DNA fraction while the number of false positives for all aneuploidies was reduced by more than 70%. CONCLUSIONS: We identified the differences in read length between fetal and maternal-derived cfDNA, and selectively enriched both shorter and longer cfDNA fragments for subsequent analysis. Our approach can increase the detection accuracy of NIPT for detecting fetal aneuploidies and reduce the number of false positives caused by maternal chromosomal abnormalities.

Enhancing Lung Cancer Classification through Integration of Liquid Biopsy Multi-Omics Data with Machine Learning Techniques.

Early detection of lung cancer is crucial for patient survival and treatment. Recent advancements in next-generation sequencing (NGS) analysis enable cell-free DNA (cfDNA) liquid biopsy to detect changes, like chromosomal rearrangements, somatic mutations, and copy number variations (CNVs), in cancer. Machine learning (ML) analysis using cancer markers is a highly promising tool for identifying patterns and anomalies in cancers, making the development of ML-based analysis methods essential. We collected blood samples from 92 lung cancer patients and 80 healthy individuals to analyze the distinction between them. The detection of lung cancer markers Cyfra21 and carcinoembryonic antigen (CEA) in blood revealed significant differences between patients and controls. We performed machine learning analysis to obtain AUC values via Adaptive Boosting (AdaBoost), Multi-Layer Perceptron (MLP), and Logistic Regression (LR) using cancer markers, cfDNA concentrations, and CNV screening. Furthermore, combining the analysis of all multi-omics data for ML showed higher AUC values compared with analyzing each element separately, suggesting the potential for a highly accurate diagnosis of cancer. Overall, our results from ML analysis using multi-omics data obtained from blood demonstrate a remarkable ability of the model to distinguish between lung cancer and healthy individuals, highlighting the potential for a diagnostic model against lung cancer.

Advances in methylation analysis of liquid biopsy in early cancer detection of colorectal and lung cancer.

Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic feature for detecting the presence of cancer and determining its origin. The purpose of this study was to evaluate the diagnostic performance of methylation-sensitive restriction enzyme digestion followed by sequencing (MRE-Seq) using cfDNA, and to investigate the cancer signal origin (CSO) of the cancer using a deep neural network (DNN) analyses for liquid biopsy of colorectal and lung cancer. We developed a selective MRE-Seq method with DNN learning-based prediction model using demethylated-sequence-depth patterns from 63,266 CpG sites using SacII enzyme digestion. A total of 191 patients with stage I-IV cancers (95 lung cancers and 96 colorectal cancers) and 126 noncancer participants were enrolled in this study. Our study showed an area under the receiver operating characteristic curve (AUC) of 0.978 with a sensitivity of 78.1% for colorectal cancer, and an AUC of 0.956 with a sensitivity of 66.3% for lung cancer, both at a specificity of 99.2%. For colorectal cancer, sensitivities for stages I-IV ranged from 76.2 to 83.3% while for lung cancer, sensitivities for stages I-IV ranged from 44.4 to 78.9%, both again at a specificity of 99.2%. The CSO model's true-positive rates were 94.4% and 89.9% for colorectal and lung cancers, respectively. The MRE-Seq was found to be a useful method for detecting global hypomethylation patterns in liquid biopsy samples and accurately diagnosing colorectal and lung cancers, as well as determining CSO of the cancer using DNN analysis.Trial registration: This trial was registered at ClinicalTrials.gov (registration number: NCT04253509) for lung cancer on 5 February 2020, https://clinicaltrials.gov/ct2/show/NCT04253509 . Colorectal cancer samples were retrospectively registered at CRIS (Clinical Research Information Service, registration number: KCT0008037) on 23 December 2022, https://cris.nih.go.kr , https://who.init/ictrp . Healthy control samples were retrospectively registered.

A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women.

Purpose: Changes in facial appearance are affected by various intrinsic and extrinsic factors, which vary from person to person. Therefore, each person needs to determine their skin condition accurately to care for their skin accordingly. Recently, genetic identification by skin-related phenotypes has become possible using genome-wide association studies (GWAS) and machine-learning algorithms. However, because most GWAS have focused on populations with American or European skin pigmentation, large-scale GWAS are needed for Asian populations. This study aimed to evaluate the correlation of facial phenotypes with candidate single-nucleotide polymorphisms (SNPs) to predict phenotype from genotype using machine learning. Materials and Methods: A total of 749 Korean women aged 30-50 years were enrolled in this study and evaluated for five facial phenotypes (melanin, gloss, hydration, wrinkle, and elasticity). To find highly related SNPs with each phenotype, GWAS analysis was used. In addition, phenotype prediction was performed using three machine-learning algorithms (linear, ridge, and linear support vector regressions) using five-fold cross-validation. Results: Using GWAS analysis, we found 46 novel highly associated SNPs (p < 1×10-05): 3, 20, 12, 6, and 5 SNPs for melanin, gloss, hydration, wrinkle, and elasticity, respectively. On comparing the performance of each model based on phenotypes using five-fold cross-validation, the ridge regression model showed the highest accuracy (r2 = 0.6422-0.7266) in all skin traits. Therefore, the optimal solution for personal skin diagnosis using GWAS was with the ridge regression model. Conclusion: The proposed facial phenotype prediction model in this study provided the optimal solution for accurately predicting the skin condition of an individual by identifying genotype information of target characteristics and machine-learning methods. This model has potential utility for the development of customized cosmetics.

Compound heterozygous variants including a novel copy number variation in a child with atypical ataxia-telangiectasia: a case report.

BACKGROUND: Ataxia-telangiectasia is a rare autosomal recessive, neurodegenerative disorder caused by alterations in the ATM gene. The majority of ATM pathogenic variants are frameshift or nonsense variants which are predicted to truncate the whole ATM protein. Herein, we report on an ataxia telangiectasia child with atypical phenotype who was identified as compound heterozygous for two ATM variants involving a previously described pathogenic single nucleotide variation (SNV) and a novel copy number variation (CNV). CASE PRESENTATION: A 6-year-old boy presented with delayed development and oculomotor apraxia. Brain magnetic resonance imaging showed interval development of mild atrophy in the cerebellum. Serum alpha fetoprotein level was in normal range. Next-generation sequencing and single-nucleotide polymorphism array tests were performed. Next-generation sequencing revealed a heterozygous nonsense pathogenic variant in ATM, c.742C > T (p.Arg248Ter) inherited from the father. Single-nucleotide polymorphism array revealed a compound heterozygous CNV, arr[GRCh37] 11q22.3(10851766-108183226) × 1, 31460 bp (exons 24-40 deletion of ATM) inherited from the mother, which was validated by reverse transcription-polymerase chain reaction analysis (RT-PCR). We demonstrated that this variant (NM_000051.4:c.3403_6006del) generated a product of in-frame deletion of exon 24-40 of ATM (p.Ser1135_Gln2002del). CONCLUSIONS: The compound heterozygosity for ATM variants involving a previously described pathogenic SNV and a novel CNV may be associated with the atypical clinical manifestations. This clinical report extends the genetic and phenotypic spectrum of ATM pathogenic variants in atypical ataxia-telangiectasia, thus making implementation of advanced analysis beyond the routine next-generation sequencing an important consideration in diagnosis and rehabilitation services for children with ataxia-telangiectasia.

Hereditary Sensory and Autonomic Neuropathy 2B Caused by a Novel RETREG1 Mutation (c.765dupT) and Paternal Uniparental Isodisomy of Chromosome 5.

Hereditary sensory and autonomic neuropathy (HSAN) 2B is a rare disease and has been reported mostly in offspring of consanguineous parents. Here we report the case of a patient born to non-consanguineous parents who was diagnosed with HSAN 2B caused due to a novel frameshift mutation (NM_001034850.2: c.765dupT/p.Gly256TrpfsTer7) in the RETREG1 gene and paternal uniparental isodisomy of chromosome 5. Uniparental isodisomy of chromosome 5 is also a rare condition, and these two rare events lead to homozygous expression of a recessive mutation, as in the present case. Clinicians should be aware that autosomal recessive disorders due to homozygous variants can occur because of uniparental disomy in offspring of non-consanguineous parents.

The rice SUMO conjugating enzymes OsSCE1 and OsSCE3 have opposing effects on drought stress.

Posttranslational modification of proteins by the small ubiquitin-related modifier (SUMO) protein is involved in diverse cellular processes. In sumoylation, SUMO-conjugating enzyme (SCE) conjugates SUMO to substrate proteins. Similarly to yeast and animals, Arabidopsis encodes a single SCE gene, but other plants encode at least two SCE genes. In this study, we report the molecular characterization of three Oryza sativa SCE genes. Their levels of expression are commonly upregulated by drought stress but are differentially regulated by hormones and sugars. Only the OsSCE1 gene showed photoperiod- and light-dependent diurnal oscillations in the leaves. Yeast two-hybrid assays showed that OsSCEs do not show SUMO isoform specificity. Three rice OsSCE proteins localize primarily to the nucleus. Interestingly, OsSCE1 is distributed in specific parts of the nucleus and shows sumoylation activities in the absence of a SUMO ligase in E. coli. In addition, overexpression of the OsSCE1 gene alters the biomass and grain yield parameters in transgenic rice plants. Overexpression of the OsSCE3 gene in transgenic rice plants enhances drought stress tolerance. In contrast, OsSCE1-OX transgenic rice plants are hypersensitive to drought stress. Our results suggest that these genes may be involved in different cellular processes.

OsbZIP42 is a positive regulator of ABA signaling and confers drought tolerance to rice.

MAIN CONCLUSION: OsbZIP42 is a positive regulator of ABA signaling and drought stress tolerance. The activation of OsbZIP42 depends on stress-/ABA-activated protein kinase 4 (SAPK4) and an additional ABA-dependent modification of OsbZIP42. Basic leucine zipper transcription factors (bZIP TFs) play important roles in the ABA signaling pathway in plants. Rice OsbZIP42 is a member of the group E bZIP, which is an ortholog of Arabidopsis group A bZIP. This latter group includes abscisic acid-responsive element (ABRE)-binding factors (ABFs) involved in abiotic stress tolerance. The expression of OsbZIP42 was induced by ABA treatment, although it was not induced by drought and salt stresses. Unlike other bZIP TFs, OsbZIP42 contained two transcriptional activation domains. Although the full-length OsbZIP42 protein did not, the N-terminus of the protein interacted with SAPK4. Our results suggest that the activation of OsbZIP42 by SAPK4 requires another ABA-dependent modification of OsbZIP42. Transgenic rice overexpressing OsbZIP42 (OsbZIP42-OX) exhibited a rapidly elevated expression of the ABA-responsive LEA3 and Rab16 genes and was hypersensitive to ABA. Analyses of the OsbZIP42-OX plants revealed enhanced tolerance to drought stress. These results suggest that OsbZIP42 is a positive regulator of ABA signaling and drought stress tolerance depending on its activation, which is followed by an additional ABA-dependent modification. We propose that OsbZIP42 is an important player in rice for conferring ABA-dependent drought tolerance.

Over-expression of BvMTSH, a fusion gene for maltooligosyltrehalose synthase and maltooligosyltrehalose trehalohydrolase, enhances drought tolerance in transgenic rice.

Plant abiotic stress tolerance has been modulated by engineering the trehalose synthesis pathway. However, many stress-tolerant plants that have been genetically engineered for the trehalose synthesis pathway also show abnormal development. The metabolic intermediate trehalose 6-phosphate has the potential to cause aberrations in growth. To avoid growth inhibition by trehalose 6-phosphate, we used a gene that encodes a bifunctional in-frame fusion (BvMTSH) of maltooligosyltrehalose synthase (BvMTS) and maltooligosyltrehalose trehalohydrolase (BvMTH) from the nonpathogenic bacterium Brevibacterium helvolum. BvMTS converts maltooligosaccharides into maltooligosyltrehalose and BvMTH releases trehalose. Transgenic rice plants that over-express BvMTSH under the control of the constitutive rice cytochrome c promoter (101MTSH) or the ABA-inducible Ai promoter (105MTSH) show enhanced drought tolerance without growth inhibition. Moreover, 101MTSH and 105MTSH showed an ABA-hyposensitive phenotype in the roots. Our results suggest that over-expression of BvMTSH enhances drought-stress tolerance without any abnormal growth and showes ABA hyposensitive phenotype in the roots.

A transcriptional repressor of the ERF family confers drought tolerance to rice and regulates genes preferentially located on chromosome 11.

Plant-specific ethylene response factors (ERFs) play important roles in abiotic and biotic stress responses in plants. Using a transgenic approach, we identified two rice ERF genes, OsERF4a and OsERF10a, which conferred drought stress tolerance. In particular, OsERF4a contains a conserved ERF-associated amphiphilic repression (EAR) motif in its C-terminal region that has been shown to function as a transcriptional repression domain. Expression profiling of transgenic rice plants over-expressing OsERF4a using either a constitutively active or an ABA-inducible promoter identified 45 down-regulated and 79 up-regulated genes in common. The increased stress tolerance by over-expression of the EAR domain-containing protein OsERF4a could result from suppression of a repressor of the defense response. Expression of the putative silent information regulator 2 (Sir2) repressor protein was repressed, and expression of several stress-response genes were induced by OsERF4a over-expression. The Sir2 and 7 out of 9 genes that were down-regulated by OsERF4a over-expression were induced by high salinity and drought treatments in non-transgenic control plants. Genes that were down- and up-regulated by OsERF4a over-expression were highly biased toward chromosome 11. Rice chromosome 11 has several large clusters of disease-resistance and defense-response genes. Taken together, our results suggest that OsERF4a is a positive regulator of shoot growth and water-stress tolerance in rice during early growth stages. We propose that OsERF4a could work by suppressing a repressor of the defense responses and/or by controlling the expression of a large number of genes located on chromosome 11.

Abiotic stress responsive rice ASR1 and ASR3 exhibit different tissue-dependent sugar and hormone-sensitivities.

The expression of the six rice ASR genes is differentially regulated in a tissue-dependent manner according to environmental conditions and reproductive stages. OsASR1 and OsASR3 are the most abundant and are found in most tissues; they are enriched in the leaves and roots, respectively. Coexpression analysis of OsASR1 and OsASR3 and a comparison of the cis-acting elements upstream of OsASR1 and OsASR3 suggested that their expression is regulated in common by abiotic stresses but differently regulated by hormone and sugar signals. The results of quantitative real-time PCR analyses of OsASR1 and OsASR3 expression under various conditions further support this model. The expression of both OsASR1 and OsASR3 was induced by drought stress, which is a major regulator of the expression of all ASR genes in rice. In contrast, ABA is not a common regulator of the expression of these genes. OsASR1 transcription was highly induced by ABA, whereas OsASR3 transcription was strongly induced by GA. In addition, OsASR1 and OsASR3 expression was significantly induced by sucrose and sucrose/glucose treatments, respectively. The induction of gene expression in response to these specific hormone and sugar signals was primarily observed in the major target tissues of these genes (i.e., OsASR1 in leaves and OsASR3 in roots). Our data also showed that the overexpression of either OsASR1 or OsASR3 in transgenic rice plants increased their tolerance to drought and cold stress. Taken together, our results revealed that the transcriptional control of different rice ASR genes exhibit different tissue-dependent sugar and hormone-sensitivities.

OsbHLH148, a basic helix-loop-helix protein, interacts with OsJAZ proteins in a jasmonate signaling pathway leading to drought tolerance in rice.

Jasmonates play important roles in development, stress responses and defense in plants. Here, we report the results of a study using a functional genomics approach that identified a rice basic helix-loop-helix domain gene, OsbHLH148, that conferred drought tolerance as a component of the jasmonate signaling module in rice. OsbHLH148 transcript levels were rapidly increased by treatment with methyl jasmonate (MeJA) or abscisic acid, and abiotic stresses including dehydration, high salinity, low temperature and wounding. Transgenic over-expression of OsbHLH148 in rice confers plant tolerance to drought stress. Expression profiling followed by DNA microarray and RNA gel-blot analyses of transgenic versus wild-type rice identified genes that are up-regulated by OsbHLH148 over-expression. These include OsDREB and OsJAZ genes that are involved in stress responses and the jasmonate signaling pathway, respectively. OsJAZ1, a rice ZIM domain protein, interacted with OsbHLH148 in yeast two-hybrid and pull-down assays, but it interacted with the putative OsCOI1 only in the presence of coronatine. Furthermore, the OsJAZ1 protein was degraded by rice and Arabidopsis extracts in the presence of coronatine, and its degradation was inhibited by MG132, a 26S proteasome inhibitor, suggesting 26S proteasome-mediated degradation of OsJAZ1 via the SCF(OsCOI1) complex. The transcription level of OsJAZ1 increased upon exposure of rice to MeJA. These results show that OsJAZ1 could act as a transcriptional regulator of the OsbHLH148-related jasmonate signaling pathway leading to drought tolerance. Thus, our study suggests that OsbHLH148 acts on an initial response of jasmonate-regulated gene expression toward drought tolerance, constituting the OsbHLH148-OsJAZ-OsCOI1 signaling module in rice.