Whole Exome Sequencing Identifies Novel De Novo Variants Interacting with Six Gene Networks in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a highly heritable condition caused by a combination of environmental and genetic factors such as de novo and inherited variants, as well as rare or common variants among hundreds of related genes. Previous genome-wide association studies have identified susceptibility genes; however, most ASD-associated genes remain undiscovered. This study aimed to examine rare de novo variants to identify genetic risk factors of ASD using whole exome sequencing (WES), functional characterization, and genetic network analyses of identified variants using Korean familial dataset. We recruited children with ASD and their biological parents. The clinical best estimate diagnosis of ASD was made according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5TM), using comprehensive diagnostic instruments. The final analyses included a total of 151 individuals from 51 families. Variants were identified and filtered using the GATK Best Practices for bioinformatics analysis, followed by genome alignments and annotation to the reference genome assembly GRCh37 (liftover to GRCh38), and further annotated using dbSNP 154 build databases. To evaluate allele frequencies of de novo variants, we used the dbSNP, gnomAD exome v2.1.1, and genome v3.0. We used Ingenuity Pathway Analysis (IPA, Qiagen) software to construct networks using all identified de novo variants with known autism-related genes to find probable relationships. We identified 36 de novo variants with potential relations to ASD; 27 missense, two silent, one nonsense, one splice region, one splice site, one 5' UTR, and one intronic SNV and two frameshift deletions. We identified six networks with functional relationships. Among the interactions between de novo variants, the IPA assay found that the NF-κB signaling pathway and its interacting genes were commonly observed at two networks. The relatively small cohort size may affect the results of novel ASD genes with de novo variants described in our findings. We did not conduct functional experiments in this study. Because of the diversity and heterogeneity of ASD, the primary purpose of this study was to investigate probable causative relationships between novel de novo variants and known autism genes. Additionally, we based functional relationships with known genes on network analysis rather than on statistical analysis. We identified new variants that may underlie genetic factors contributing to ASD in Korean families using WES and genetic network analyses. We observed novel de novo variants that might be functionally linked to ASD, of which the variants interact with six genetic networks.

Gene Expression Profile in Similar Tissues Using Transcriptome Sequencing Data of Whole-Body Horse Skeletal Muscle.

Horses have been studied for exercise function rather than food production, unlike most livestock. Therefore, the role and characteristics of tissue landscapes are critically understudied, except for certain muscles used in exercise-related studies. In the present study, we compared RNA-Seq data from 18 Jeju horse skeletal muscles to identify differentially expressed genes (DEGs) between tissues that have similar functions and to characterize these differences. We identified DEGs between different muscles using pairwise differential expression (DE) analyses of tissue transcriptome expression data and classified the samples using the expression values of those genes. Each tissue was largely classified into two groups and their subgroups by k-means clustering, and the DEGs identified in comparison between each group were analyzed by functional/pathway level using gene set enrichment analysis and gene level, confirming the expression of significant genes. As a result of the analysis, the differences in metabolic properties like glycolysis, oxidative phosphorylation, and exercise adaptation of the groups were detected. The results demonstrated that the biochemical and anatomical features of a wide range of muscle tissues in horses could be determined through transcriptome expression analysis, and provided proof-of-concept data demonstrating that RNA-Seq analysis can be used to classify and study in-depth differences between tissues with similar properties.

Bioinformatics services for analyzing massive genomic datasets.

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

Genome-wide association and epistatic interactions of flowering time in soybean cultivar.

Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP) markers have also increased, thus enabling the identification of more candidate markers along with GWAS on single-variant-additive-effect. Here, we focused on the identification of candidate markers associated with flowering time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom® SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flowering time. A total of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flowering time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flowering time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flowering pathways. Although further biological validation is needed, our results provide additional information on the existing flowering time markers and present another option to marker-assisted breeding programs for regulating flowering time of soybean.

Dissection of soybean populations according to selection signatures based on whole-genome sequences.

BACKGROUND: Domestication and improvement processes, accompanied by selections and adaptations, have generated genome-wide divergence and stratification in soybean populations. Simultaneously, soybean populations, which comprise diverse subpopulations, have developed their own adaptive characteristics enhancing fitness, resistance, agronomic traits, and morphological features. The genetic traits underlying these characteristics play a fundamental role in improving other soybean populations. RESULTS: This study focused on identifying the selection signatures and adaptive characteristics in soybean populations. A core set of 245 accessions (112 wild-type, 79 landrace, and 54 improvement soybeans) selected from 4,234 soybean accessions was re-sequenced. Their genomic architectures were examined according to the domestication and improvement, and accessions were then classified into 3 wild-type, 2 landrace, and 2 improvement subgroups based on various population analyses. Selection and gene set enrichment analyses revealed that the landrace subgroups have selection signals for soybean-cyst nematode HG type 0 and seed development with germination, and that the improvement subgroups have selection signals for plant development with viability and seed development with embryo development, respectively. The adaptive characteristic for soybean-cyst nematode was partially underpinned by multiple resistance accessions, and the characteristics related to seed development were supported by our phenotypic findings for seed weights. Furthermore, their adaptive characteristics were also confirmed as genome-based evidence, and unique genomic regions that exhibit distinct selection and selective sweep patterns were revealed for 13 candidate genes. CONCLUSIONS: Although our findings require further biological validation, they provide valuable information about soybean breeding strategies and present new options for breeders seeking donor lines to improve soybean populations.

Discovery of Genomic Characteristics and Selection Signatures in Korean Indigenous Goats Through Comparison of 10 Goat Breeds.

Indigenous breeds develop their own genomic characteristics by adapting to local environments or cultures over long periods of time. Most of them are not particularly productive in commercial terms, but they have abilities to survive in harsh environments or tolerate to specific diseases. Their adaptive characteristics play an important role as genetic materials for improving commercial breeds. As a step toward this goal, we analyzed the genome of Korean indigenous goats within 10 goat breeds. We collected 136 goat individuals by sequencing 46 new goats and employing 90 publicly available goats. Our whole-genome data was comprised of three indigenous breeds (Korean indigenous goat, Iranian indigenous goat, and Moroccan indigenous goat; n = 29, 18, 20), six commercial breeds (Saanen, Boer, Anglo-Nubian, British Alpine, Alpine, and Korean crossbred; n = 16, 11, 5, 5, 2, 13), and their ancestral species (Capra aegagrus; n = 17). We identified that the Iranian indigenous goat and the Moroccan indigenous goat have relatively similar genomic characteristics within a large category of genomic diversity but found that the Korean indigenous goat has unique genomic characteristics distinguished from the other nine breeds. Through population analysis, we confirmed that these characteristics have resulted from a near-isolated environment with strong genetic drift. The Korean indigenous goat experienced a severe genetic bottleneck upon entering the Korean Peninsula about 2,000 years ago, and has subsequently rarely experienced genetic interactions with other goat breeds. From selection analysis and gene-set enrichment analysis, we revealed selection signals for Salmonella infection and cardiomyopathy in the genome of the Korean indigenous goat. These adaptive characteristics were further identified with genomic-based evidence. We uncovered genomic regions of selective sweeps in the LBP and BPI genes (Salmonella infection) and the TTN and ITGB6 genes (cardiomyopathy), among several candidate genes. Our research presents unique genomic characteristics and distinctive selection signals of the Korean indigenous goat based on the extensive comparison. Although the adaptive traits require further validation through biological experiments, our findings are expected to provide a direction for future biodiversity conservation strategies and to contribute another option to genomic-based breeding programmes for improving the viability of Capra hircus.

Investigation of Gene Expression and DNA Methylation From Seven Different Brain Regions of a Crab-Eating Monkey as Determined by RNA-Seq and Whole-Genome Bisulfite Sequencing.

The crab-eating monkey is widely used in biomedical research for pharmacological experiments. Epigenetic regulation in the brain regions of primates involves complex patterns of DNA methylation. Previous studies of methylated CpG-binding domains using microarray technology or peak identification of sequence reads mostly focused on developmental stages or disease, rather than normal brains. To identify correlations between gene expression and DNA methylation levels that may be related to transcriptional regulation, we generated RNA-seq and whole-genome bisulfite sequencing data from seven different brain regions from a single crab-eating monkey. We identified 92 genes whose expression levels were significantly correlated, positively or negatively, with DNA methylation levels. Among them, 11 genes exhibited brain region-specific characteristics, and their expression patterns were strongly correlated with DNA methylation level. Nine genes (SLC2A5, MCM5, DRAM1, TTC12, DHX40, COR01A, LRAT, FLVCR2, and PTER) had effects on brain and eye function and development, and two (LHX6 and MEST) were previously identified as genes in which DNA methylation levels change significantly in the promoter region and are therefore considered brain epigenetic markers. Furthermore, we characterized DNA methylation of repetitive elements at the whole genome through repeat annotation at single-base resolution. Our results reveal the diverse roles of DNA methylation at single-base resolution throughout the genome and reflect the epigenetic variations in adult brain tissues.

Identification of DNA-Methylated CpG Islands Associated With Gene Silencing in the Adult Body Tissues of the Ogye Chicken Using RNA-Seq and Reduced Representation Bisulfite Sequencing.

DNA methylation is an epigenetic mark that plays an essential role in regulating gene expression. CpG islands are DNA methylations regions in promoters known to regulate gene expression through transcriptional silencing of the corresponding gene. DNA methylation at CpG islands is crucial for gene expression and tissue-specific processes. At the current time, a limited number of studies have reported on gene expression associated with DNA methylation in diverse adult tissues at the genome-wide level. Expression levels are rarely affected by DNA methylation in normal adult tissues; however, statistical differences in gene expression level correlated with DNA methylation have recently been revealed. In this study, we examined 20 pairs of DNA methylomes and transcriptomes from RNA-seq and reduced representation bisulfite sequencing (RRBS) data using adult Ogye chicken tissues. A total of 3,133 CpG islands were identified from 20 tissue data in a single chicken sample which could affect downstream genes. Analyzing these CpG island and gene pairs, 121 significant units were statistically correlated. Among them, six genes (CLDN3, DECR2, EVA1B, NME4, NTSR1, and XPNPEP2) were highly significantly changed by altered DNA methylation. Finally, our data demonstrated how DNA methylation correlated to gene expression in normal adult tissues. Our source codes can be found at https://github.com/wjlim/correlation-between-rna-seq-and-RRBS.

Tumor Suppressor miRNA-204-5p Regulates Growth, Metastasis, and Immune Microenvironment Remodeling in Breast Cancer.

Various miRNAs play critical roles in the development and progression of solid tumors. In this study, we describe the role of miR-204-5p in limiting growth and progression of breast cancer. In breast cancer tissues, miR-204-5p was significantly downregulated compared with normal breast tissues, and its expression levels were associated with increased survival outcome in patients with breast cancer. Overexpression of miR-204-5p inhibited viability, proliferation, and migration capacity in human and murine breast cancer cells. In addition, miR-204-5p overexpression resulted in a significant alteration in metabolic properties of cancer cells and suppression of tumor growth and metastasis in mouse breast cancer models. The association between miR-204-5p expression and clinical outcomes of patients with breast cancer showed a nonlinear pattern that was reproduced in experimental assays of cancer cell behavior and metastatic capacities. Transcriptome and proteomic analysis revealed that various cancer-related pathways including PI3K/Akt and tumor-immune interactions were significantly associated with miR-204-5p expression. PIK3CB, a major regulator of PI3K/Akt pathway, was a direct target for miR-204-5p, and the association between PIK3CB-related PI3K/Akt signaling and miR-204-5p was most evident in the basal subtype. The sensitivity of breast cancer cells to various anticancer drugs including PIK3CB inhibitors was significantly affected by miR-204-5p expression. In addition, miR-204-5p regulated expression of key cytokines in tumor cells and reprogrammed the immune microenvironment by shifting myeloid and lymphocyte populations. These data demonstrate both cell-autonomous and non-cell-autonomous impacts of tumor suppressor miR-204-5p in breast cancer progression and metastasis. SIGNIFICANCE: This study demonstrates that regulation of PI3K/Akt signaling by miR-204-5p suppresses tumor metastasis and immune cell reprogramming in breast cancer.

Identification of candidate domestication regions in the radish genome based on high-depth resequencing analysis of 17 genotypes.

KEY MESSAGE: This study provides high-quality variation data of diverse radish genotypes. Genome-wide SNP comparison along with RNA-seq analysis identified candidate genes related to domestication that have potential as trait-related markers for genetics and breeding of radish. Radish (Raphanus sativus L.) is an annual root vegetable crop that also encompasses diverse wild species. Radish has a long history of domestication, but the origins and selective sweep of cultivated radishes remain controversial. Here, we present comprehensive whole-genome resequencing analysis of radish to explore genomic variation between the radish genotypes and to identify genetic bottlenecks due to domestication in Asian cultivars. High-depth resequencing and multi-sample genotyping analysis of ten cultivated and seven wild accessions obtained 4.0 million high-quality homozygous single-nucleotide polymorphisms (SNPs)/insertions or deletions. Variation analysis revealed that Asian cultivated radish types are closely related to wild Asian accessions, but are distinct from European/American cultivated radishes, supporting the notion that Asian cultivars were domesticated from wild Asian genotypes. SNP comparison between Asian genotypes identified 153 candidate domestication regions (CDRs) containing 512 genes. Network analysis of the genes in CDRs functioning in plant signaling pathways and biochemical processes identified group of genes related to root architecture, cell wall, sugar metabolism, and glucosinolate biosynthesis. Expression profiling of the genes during root development suggested that domestication-related selective advantages included a main taproot with few branched lateral roots, reduced cell wall rigidity and favorable taste. Overall, this study provides evolutionary insights into domestication-related genetic selection in radish as well as identification of gene candidates with the potential to act as trait-related markers for background selection of elite lines in molecular breeding.

Efficient function and characterization of GH10 xylanase (Xyl10g) from Gloeophyllum trabeum in lignocellulose degradation.

The xylanase gene from Gloeophyllum trabeum was cloned and expressed in Pichia pastoris GS115. Xyl10g has a molecular weight of approximately 50kDa, and exhibits maximum specific activity at 70°C and a broad range of pH 4.0-7.0. Purified recombinant Xyl10g efficiently degraded popping-pretreated corn stover and newspaper waste at 50°C and pH 4.0 after 24h, and showed synergistic effects with Cel5B (endoglucanase) and BglB (ß-glucosidase) to increase reduced sugar levels by about 1.71- to 1.88-fold and 2.26- to 2.48-fold, respectively. Although Xyl10g has low specific activity for beechwood xylan, as compared to XynA, Xyl10g more efficiently degraded corn stover than did XynA. According to immunogold labeling analysis, Xyl10g can attack highly substituted, unsubstituted, and low-substituted xylans, whereas XynA cannot efficiently attack highly substituted xylans, which is important for lignocellulose degradation. These results suggest that GH10 Xyl10g can be used for lignocellulose degradation.

Bioethanol production from the nutrient stress-induced microalga Chlorella vulgaris by enzymatic hydrolysis and immobilized yeast fermentation.

The microalga Chlorella vulgaris is a potential feedstock for bioenergy due to its rapid growth, carbon dioxide fixation efficiency, and high accumulation of lipids and carbohydrates. In particular, the carbohydrates in microalgae make them a candidate for bioethanol feedstock. In this study, nutrient stress cultivation was employed to enhance the carbohydrate content of C. vulgaris. Nitrogen limitation increased the carbohydrate content to 22.4% from the normal content of 16.0% on dry weight basis. In addition, several pretreatment methods and enzymes were investigated to increase saccharification yields. Bead-beating pretreatment increased hydrolysis by 25% compared with the processes lacking pretreatment. In the enzymatic hydrolysis process, the pectinase enzyme group was superior for releasing fermentable sugars from carbohydrates in microalgae. In particular, pectinase from Aspergillus aculeatus displayed a 79% saccharification yield after 72h at 50°C. Using continuous immobilized yeast fermentation, microalgal hydrolysate was converted into ethanol at a yield of 89%.

Bioethanol production from rice straw by popping pretreatment.

BACKGROUND: Rice straw has considerable potential as a raw material for bioethanol production. Popping pretreatment of rice straw prior to downstream enzymatic hydrolysis and fermentation was found to increase cellulose to glucose conversion efficiency. The aim of this study was to investigate the influence of popping pretreatment and determine the optimal enzyme loading using a surface response design. RESULTS: The optimal doses of cellulase and xylanase enzymes were 23 FPU and 62 IU/g biomass, respectively. Using the optimized enzyme condition and popping pretreatment of rice straw (15% substrate loading, w/v), a sugar recovery of 0.567 g/g biomass (glucose; 0.394 g/g) was obtained in 48 h, which was significantly higher than that from untreated rice straw (total sugar recovery; 0.270 g/g biomass). Fermentation of the hydrolyzates by Saccharomyces cerevisiae resulted in 0.172 g ethanol/g biomass after 24 h, equivalent to 80.9% of the maximum theoretical yield (based on the amount of glucose in raw material). Changes in the chemical composition and surface area of rice straw were also investigated before and after popping pretreatment. The results showed little or no difference in chemical composition between the pretreated rice straw and the control. However, the surface area of pretreated rice straw increased twofold compared to the control. CONCLUSION: Popping pretreatment of rice straw can effectively improve downstream saccharification and fermentation, important for bioethanol production.