Quantification of gene expression while taking into account RNA alternative splicing

Integration of Image Pattern Recognition and Photon Sensor for Analyzing Cytokine Gene Expression Using πCode MicroDisc

Current quantitative gene expression detection in genomic and transcriptomic research heavily relies on quantitative real-time PCR (qPCR). While existing multiplex gene detection techniques offer simultaneous analysis of multiple targets, we present an alternative assay capable of detecting gene expression simultaneously within a single well. This highly sensitive method utilizes πCode MicroDiscs, featuring unique identification patterns and fluorescent detection. Our study compared this multiplex πCode platform with a qPCR platform for profiling cytokine gene expression. The πCode MicroDisc assay successfully demonstrated the expression of polymerization markers for M1- and M2-like macrophages generated from THP-1-derived macrophages in a qualitative assay. Additionally, our findings suggest a pattern agreement between the πCode assay and the qPCR assay, indicating the potential of the πCode technology for comparative gene expression analysis. Regarding the inherent sensitivity and linearity, the developed πCode assay primarily provides qualitative gene expression to discriminate the polarization of macrophages. This remarkable capability presents substantial advantages for researchers, rendering the technology highly suitable for high-throughput applications in clinical diagnosis and disease monitoring.

Exploring the molecular mechanisms of increased intensity of pyrethroid resistance in Central African population of a major malaria vector Anopheles coluzzii

Molecular mechanisms driving the escalation of pyrethroid resistance in the major malaria mosquitoes of Central Africa remain largely uncharacterized, hindering effective management strategies. Here, resistance intensity and the molecular mechanisms driving it were investigated in a population of Anopheles coluzzii from northern Cameroon. High levels of pyrethroid and organochloride resistance were observed in An. coluzzii population, with no mortality for 1× permethrin; only 11% and 33% mortalities for 5× and 10× permethrin diagnostic concentrations, and <2% mortalities for deltamethrin and DDT, respectively. Moderate bendiocarb resistance (88% mortality) and full susceptibility to malathion were observed. Synergist bioassays with piperonyl butoxide recovered permethrin susceptibility, with mortalities increasing to 53.39%, and 87.30% for 5× and 10× permethrin, respectively, implicating P450 monooxygenases. Synergist bioassays with diethyl maleate (DEM) recovered permethrin and DDT susceptibilities (mortalities increasing to 34.75% and 14.88%, respectively), implicating glutathione S-transferases. RNA-seq-based genome-wide transcriptional analyses supported by quantitative PCR identified glutathione S-transferase, GSTe2 (RNA-seqFC = 2.93 and qRT-PCRFC = 8.4, p < 0.0043) and CYP450, CYP6Z2 (RNA-seqFC = 2.39 and qRT-PCRFC = 11.7, p < 0.0177) as the most overexpressed detoxification genes in the pyrethroid-resistant mosquitoes, compared to mosquitoes of the susceptible Ngousso colony. Other overexpressed genes include P450s, CYP6M2 (FC = 1.68, p < 0.0114), CYP4G16 (FC = 2.02, p < 0.0005), and CYP4G17 (FC = 1.86, p < 0.0276). While high frequency of the 1014F kdr mutation (50%) and low frequencies of 1014S (6.61%) and 1575Y (10.29%) were observed, no ace-1 mutation was detected in bendiocarb-resistant populations, suggesting the preeminent role of metabolic mechanism. Overexpression of metabolic resistance genes (including GSTe2 and CYP6Z2 known to confer resistance to multiple insecticides) in An. coluzzii from the Sudan Savannah of Cameroon highlights the need for alternative management strategies to reduce malaria burden in northern Cameroon.

Metformin targets intestinal immune system signaling pathways in a high-fat diet-induced mouse model of obesity and insulin resistance

Introduction

Research findings of the past decade have highlighted the gut as the main site of action of the oral antihyperglycemic agent metformin despite its pharmacological role in the liver. Extensive evidence supports metformin's modulatory effect on the composition and function of gut microbiota, nevertheless, the underlying mechanisms of the host responses remain elusive. Our study aimed to evaluate metformin-induced alterations in the intestinal transcriptome profiles at different metabolic states.

Methods

The high-fat diet-induced mouse model of obesity and insulin resistance of both sexes was developed in a randomized block experiment and bulk RNA-Seq of the ileum tissue was the method of choice for comparative transcriptional profiling after metformin intervention for ten weeks.

Results

We found a prominent transcriptional effect of the diet itself with comparatively fewer genes responding to metformin intervention. The overrepresentation of immune-related genes was observed, including pronounced metformin-induced upregulation of immunoglobulin heavy-chain variable region coding Ighv1-7 gene in both high-fat diet and control diet-fed animals. Moreover, we provide evidence of the downregulation NF-kappa B signaling pathway in the small intestine of both obese and insulin-resistant animals as well as control animals after metformin treatment. Finally, our data pinpoint the gut microbiota as a crucial component in the metformin-mediated downregulation of NF-kappa B signaling evidenced by a positive correlation between the Rel and Rela gene expression levels and abundances of Parabacteroides distasonis, Bacteroides spp., and Lactobacillus spp. in the gut microbiota of the same animals.

Discussion

Our study supports the immunomodulatory effect of metformin in the ileum of obese and insulin-resistant C57BL/6N mice contributed by intestinal immunoglobulin responses, with a prominent emphasis on the downregulation of NF-kappa B signaling pathway, associated with alterations in the composition of the gut microbiome.

Transcriptomic approach to uncover dynamic events in the development of mid-season sunburn in apple fruit

Apples grown in high heat, high light, and low humidity environments are at risk for sun injury disorders like sunburn and associated crop losses. Understanding the physiological and molecular mechanisms underlying sunburn will support improvement of mitigation strategies and breeding for more resilient varieties. Numerous studies have highlighted key biochemical processes involved in sun injury, such as the phenylpropanoid and reactive oxygen species (ROS) pathways, demonstrating both enzyme activities and expression of related genes in response to sunburn conditions. Most previous studies have focused on at-harvest activity of a small number of genes in response to heat stress. Thus, it remains unclear how stress events earlier in the season affect physiology and gene expression. Here, we applied heat stress to mid-season apples in the field and collected tissue along a time course-24, 48, and 72 h following a heat stimulus-to investigate dynamic gene expression changes using a transcriptomic lens. We found a relatively small number of differentially expressed genes (DEGs) and enriched functional terms in response to heat treatments. Only a few of these belonged to pathways previously described to be involved in sunburn, such as the AsA-GSH pathway, while most DEGs had not yet been implicated in sunburn or heat stress in pome fruit.

Genetic and molecular dissection of ginseng (Panax ginseng Mey.) germplasm using high-density genic SNP markers, secondary metabolites, and gene expressions

Genetic and molecular knowledge of a species is crucial to its gene discovery and enhanced breeding. Here, we report the genetic and molecular dissection of ginseng, an important herb for healthy food and medicine. A mini-core collection consisting of 344 cultivars and landraces was developed for ginseng that represents the genetic variation of ginseng existing in its origin and diversity center. We sequenced the transcriptomes of all 344 cultivars and landraces; identified over 1.5 million genic SNPs, thereby revealing the genic diversity of ginseng; and analyzed them with 26,600 high-quality genic SNPs or a selection of them. Ginseng had a wide molecular diversity and was clustered into three subpopulations. Analysis of 16 ginsenosides, the major bioactive components for healthy food and medicine, showed that ginseng had a wide variation in the contents of all 16 ginsenosides and an extensive correlation of their contents, suggesting that they are synthesized through a single or multiple correlated pathways. Furthermore, we pair-wisely examined the relationships between the cultivars and landraces, revealing their relationships in gene expression, gene variation, and ginsenoside biosynthesis. These results provide new knowledge and new genetic and genic resources for advanced research and breeding of ginseng and related species.

Alternative splicing shapes the transcriptome complexity in blackgram [Vigna mungo (L.) Hepper]

Vigna mungo, a highly consumed crop in the pan-Asian countries, is vulnerable to several biotic and abiotic stresses. Understanding the post-transcriptional gene regulatory cascades, especially alternative splicing (AS), may underpin large-scale genetic improvements to develop stress-resilient varieties. Herein, a transcriptome based approach was undertaken to decipher the genome-wide AS landscape and splicing dynamics in order to establish the intricacies of their functional interactions in various tissues and stresses. RNA sequencing followed by high-throughput computational analyses identified 54,526 AS events involving 15,506 AS genes that generated 57,405 transcripts isoforms. Enrichment analysis revealed their involvement in diverse regulatory functions and demonstrated that transcription factors are splicing-intensive, splice variants of which are expressed differentially across tissues and environmental cues. Increased expression of a splicing regulator NHP2L1/SNU13 was found to co-occur with lower intron retention events. The host transcriptome is significantly impacted by differential isoform expression of 1172 and 765 AS genes that resulted in 1227 (46.8% up and 53.2% downregulated) and 831 (47.5% up and 52.5% downregulated) transcript isoforms under viral pathogenesis and Fe²⁺ stressed condition, respectively. However, genes experiencing AS operate differently from the differentially expressed genes, suggesting AS is a unique and independent mode of regulatory mechanism. Therefore, it can be inferred that AS mediates a crucial regulatory role across tissues and stressful situations and the results would provide an invaluable resource for future endeavours in V. mungo genomics.

Prediction of transcript structure and concentration using RNA-Seq data

Alternative splicing (AS) is a key post-transcriptional modification that helps in increasing protein diversity. Almost 90% of the protein-coding genes in humans are known to undergo AS and code for different transcripts. Some transcripts are associated with diseases such as breast cancer, lung cancer and glioblastoma. Hence, these transcripts can serve as novel therapeutic and prognostic targets for drug discovery. Herein, we have developed a pipeline, Finding Alternative Splicing Events (FASE), as the R package that includes modules to determine the structure and concentration of transcripts using differential AS. To predict the correct structure of expressed transcripts in given conditions, FASE combines the AS events with the information of exons, introns and junctions using graph theory. The estimated concentration of predicted transcripts is reported as the relative expression in terms of log2CPM. Using FASE, we were able to identify several unique transcripts of EMILIN1 and SLK genes in the TCGA-BRCA data, which were validated using RT-PCR. The experimental study demonstrated consistent results, which signify the high accuracy and precision of the developed methods. In conclusion, the developed pipeline, FASE, can efficiently predict novel transcripts that are missed in general transcript-level differential expression analysis. It can be applied selectively from a single gene to simple or complex genome even in multiple experimental conditions for the identification of differential AS-based biomarkers, prognostic targets and novel therapeutics.

Toward kingdom-wide analyses of gene expression

Gene expression data for Archaeplastida are accumulating exponentially, with more than 300 000 RNA-sequencing (RNA-seq) experiments available for hundreds of species. The gene expression data stem from thousands of experiments that capture gene expression in various organs, tissues, cell types, (a)biotic perturbations, and genotypes. Advances in software tools make it possible to process all these data in a matter of weeks on modern office computers, giving us the possibility to study gene expression in a kingdom-wide manner for the first time. We discuss how the expression data can be accessed and processed and outline analyses that take advantage of cross-species analyses, allowing us to generate powerful and robust hypotheses about gene function and evolution.

Transcriptome and Phenotype Integrated Analysis Identifies Genes Controlling Ginsenoside Rb1 Biosynthesis and Reveals Their Interactions in the Process in Panax ginseng

Genes are the keys to deciphering the molecular mechanism underlying a biological trait and designing approaches desirable for plant genetic improvement. Ginseng is an important medicinal herb in which ginsenosides have been shown to be the major bioactive component; however, only a few genes involved in ginsenoside biosynthesis have been cloned through orthologue analysis. Here, we report the identification of 21 genes controlling Rb1 biosynthesis by stepwise ginseng transcriptome and Rb1 content integrated analysis. We first identified the candidate genes for Rb1 biosynthesis by integrated analysis of genes with the trait from four aspects, including gene transcript differential expression between highest- and lowest-Rb1 content cultivars, gene transcript expression-Rb1 content correlation, and biological impacts of gene mutations on Rb1 content, followed by the gene transcript co-expression network. Twenty-two candidate genes were identified, of which 21 were functionally validated for Rb1 biosynthesis by gene regulation, genetic transformation, and mutation analysis. These genes were strongly correlated in expression with the previously cloned genes encoding key enzymes for Rb1 biosynthesis. Based on the correlations, a pathway for Rb1 biosynthesis was deduced to indicate the roles of the genes in Rb1 biosynthesis. Moreover, the genes formed a strong co-expression network with the previously cloned Rb1 biosynthesis genes, and the variation in the network was associated with the variation in the Rb1 content. These results indicate that Rb1 biosynthesis is a process of correlative interactions among Rb1 biosynthesis genes. Therefore, this study provides new knowledge, 21 new genes, and 96 biomarkers for Rb1 biosynthesis useful for enhanced research and breeding in ginseng.

Genome-wide identification of genes enabling accurate prediction of hybrid performance from parents across environments and populations for gene-based breeding in maize

Accurate prediction of hybrid offspring complex trait phenotype from parents is paramount to enhanced plant breeding, animal breeding, and human medicine. Here we report genome-wide identification of genes enabling accurate prediction of hybrid offspring complex traits from parents using maize grain yield as the target trait. We identified 181 ZmF1GY genes enabling prediction of maize (Zea mays L.) F₁ hybrid grain yield from parents and tested their utility and efficiency for predicting F₁ hybrid grain yields from parents using their expressions, genic SNPs, and number of favorable alleles (NFAs), respectively. The ZmF1GY genes predicted hybrid grain yields from parents at an accuracy of 0.86, presented by correlation coefficient between predicted and observed phenotypes, within an environment, 0.74 across environments, and 0.64 across populations, outperforming genomic prediction by 27-406%, 23%, and 40%, respectively. Furthermore, we identified nine of the ZmF1GY genes containing SNPs or InDels in parents that increased or decreased hybrid grain yields by 14-46%. When the NFAs of these nine ZmF1GY genes were used for hybrid grain yield prediction from parents, they predicted hybrid grain yields at an accuracy of 0.79, outperforming genomic prediction by 21% that was based on up to tens of thousands of genome-wide SNPs. These results demonstrate the feasibility of developing a gene toolkit for a species enabling gene-based breeding across environments and populations that is much more powerful and efficient than current breeding, thereby helping secure the world's food production. The methodology is applicable to all crops, livestock, and humans.

Innovative approaches and recent advances in the study of ontogeny of drug metabolism and transport

The disposition of a drug is driven by various processes, such as drug metabolism, drug transport, glomerular filtration and body composition. These processes are subject to developmental changes reflecting growth and maturation along the paediatric continuum. However, knowledge gaps exist on these changes and their clinical impact. Filling these gaps may aid better prediction of drug disposition and creation of age-appropriate dosing guidelines. We present innovative approaches to study these developmental changes in relation to drug metabolism and transport. First, analytical methods such as including liquid chromatography-mass spectrometry for proteomic analyses allow quantitation of the expressions of a wide variety of proteins, e.g. membrane transporters, in a small piece of organ tissue. The latter is specifically important for paediatric research, where tissues are scarcely available. Second, innovative study designs using radioactive labelled microtracers allowed study-without risk for the child-of the oral bioavailability of compounds used as markers for certain drug metabolism pathways. Third, the use of modelling and simulation to support dosing recommendations for children is supported by both the European Medicines Agency and the US Food and Drug Administration. This may even do away with the need for a paediatric trial. Physiologically based pharmacokinetics models, which include age-specific physiological information are, therefore, increasingly being used, not only to aid paediatric drug development but also to improve existing drug therapies.

Analysis of the genes controlling cotton fiber length reveals the molecular basis of plant breeding and the genetic potential of current cultivars for continued improvement

Stagnated crop improvement has raised questions of whether and how current crop cultivars can be further improved. Genes are the core determinants of performance of all cultivars. Here, we report the molecular basis of plant breeding and address these questions by analyzing 226 GFL genes controlling and accurately predicting fiber length, an important breeding objective trait, in cotton (Gossypium sp.). We first identified the favorable allele and the number of favorable alleles (NFAs) of each GFL gene, calculated the total NFAs of the 226 GFL genes accumulated in 198 advanced breeding lines, and analyzed them against fiber lengths. Fiber lengths of the breeding lines were strongly correlated with the total NFAs of the GFL genes (r = 0.85, P < 0.0001), suggesting that accumulation of the favorable alleles of the genes controlling objective traits is the molecular basis of cotton breeding. Surprisingly, a breeding line with a fiber length of present cultivars having the longest fibers contained only about 51% of the total NFAs of the 226 GFL genes. The genetic potentials of current cultivars were then predicted using linear and non-linear models, respectively, revealing that a breeding line or cultivar with a fiber length of 33.8 mm could be further improved in fiber length by up to 118%. Finally, we showed that the genetic potential of such a breeding line can be realized through gene-based breeding. Therefore, these findings shed light on continued crop improvement in general and provide 740 genic biomarkers desirable for enhanced cotton fiber breeding.

Profiling of mature-stage human breast milk cells identifies six unique lactocyte subpopulations

Breast milk is chock-full of nutrients, immunological factors, and cells that aid infant development. Maternal cells are the least studied breast milk component, and their unique properties are difficult to identify using traditional techniques. Here, we characterized the cells in mature-stage breast milk from healthy donors at the protein, gene, and transcriptome levels. Holistic analysis of flow cytometry, quantitative polymerase chain reaction, and single-cell RNA sequencing data identified the predominant cell population as epithelial with smaller populations of macrophages and T cells. Two percent of epithelial cells expressed four stem cell markers: SOX2, TRA-1-60, NANOG, and SSEA4. Furthermore, milk contained six distinct epithelial lactocyte subpopulations, including three previously unidentified subpopulations programmed toward mucosal defense and intestinal development. Pseudotime analysis delineated the differentiation pathways of epithelial progenitors. Together, these data define healthy human maternal breast milk cells and provide a basis for their application in maternal and infant medicine.

Vitellogenin gene expression in marine mussels exposed to ethinylestradiol: No induction at the transcriptional level

Vitellogenin (Vtg), a large multidomain protein precursor of egg-yolk proteins, is used as an endocrine disruption biomarker in fish, and in the last decades, its use has been extended to invertebrates like mollusks. However, it remains unclear whether invertebrate endocrine system produces Vtg in response to estrogens, like it occurs in oviparous vertebrates. In a previous study, no evidence of induction of Vtg expression at protein level was found in gonads of the marine mussel Mytilus galloprovincialis after exposure to the estrogenic chemical 17α-ethinylestradiol (EE2). In the present follow-up study, it was investigated whether there is any effect of EE2 on Vtg abundance at transcriptional level in M. galloprovincialis gonads. To this aim, RT-qPCR analysis targeting three different domains of Vtg transcript was performed on gonads of mussels that were exposed either 4 or 24 days to 100 ng/L EE2. In addition, several reference genes were analysed and a selection of these for potential use in further RT-qPCR analyses on mussel male and female gonads is provided. Results showed higher expression in females than in males for the three analysed Vtg domains, and no evidence of Vtg mRNA induction due to EE2 either in females or males. The present results, together with those obtained from previous analysis at protein level, support that Vtg is not an adequate biomarker for xenoestrogenicity in marine mussels. Additionally, nucleotide sequences of Vtg transcripts of three closely-related species from Mytilus edulis complex (M. galloprovincialis, M. edulis and M. trossulus) are provided and compared with Vtg sequences from other mollusk species to assess the level of conservation and evolutionary relationships among species.

Integrative transcriptome analysis identifies new oxidosqualene cyclase genes involved in ginsenoside biosynthesis in Jilin ginseng

BACKGROUND

Jilin ginseng, Panax ginseng, is a valuable medicinal herb whose ginsenosides are its major bioactive components. The ginseng oxidosqualene cyclase (PgOSC) gene family is known to play important roles in ginsenoside biosynthesis, but few members of the gene family have been functionally studied.

METHODS

The PgOSC gene family has been studied by an integrated analysis of gene expression-ginsenoside content correlation, gene mutation-ginsenoside content association and gene co-expression network, followed by functional analysis through gene regulation.

RESULTS

We found that five of the genes in the PgOSC gene family, including two published ginsenoside biosynthesis genes and three new genes, were involved in ginsenoside biosynthesis. Not only were the expressions of these genes significantly correlated with ginsenoside contents, but also their nucleotide mutations significantly influenced ginsenoside contents. These results were further verified by regulation analysis of the genes by methyl jasmonate (MeJA) in ginseng hairy roots. Four of these five PgOSC genes were mapped to the ginsenoside biosynthesis pathway. These PgOSC genes expressed differently across tissues, but relatively consistent across developmental stages. These PgOSC genes formed a single co-expression network with those published ginsenoside biosynthesis genes, further confirming their roles in ginsenoside biosynthesis. When the network varied, ginsenoside biosynthesis was significantly influenced, thus revealing the molecular mechanism of ginsenoside biosynthesis.

CONCLUSION

At least five of the PgOSC genes, including the three newly identified and two published PgOSC genes, are involved in ginsenoside biosynthesis. These results provide gene resources and knowledge essential for enhanced research and applications of ginsenoside biosynthesis in ginseng.

Characteristics of RNA alternative splicing and its potential roles in ginsenoside biosynthesis in a single plant of ginseng, Panax ginseng C.A. Meyer

RNA alternative splicing (AS) is prevalent in higher organisms and plays a paramount role in biology; therefore, it is crucial to have comprehensive knowledge on AS to understand biology. However, knowledge is limited about how AS activates in a single plant and functions in a biological process. Ginseng is one of the most widely used medicinal herbs that is abundant in a number of medicinal bioactive components, especially ginsenosides. In this study, we sequenced the transcripts of 14 organs from a 4-year-old ginseng plant and quantified their ginsenoside contents. We identified AS genes by analyzing their transcripts with the ginseng genome and verified their AS events by PCR. The plant had a total of 13,863 AS genes subjected to 30,801 AS events with five mechanisms: skipped exon, retained intron, alternative 5'splice site, alternative 3' splice site, and mutually exclusive exon. The genes that were more conserved, had more exons, and/or expressed across organs were more likely to be subjected to AS. AS genes were enriched in over 500 GO terms in the plant even though the number of AS gene-enriched GO terms varied across organs. At least 24 AS genes were found to be involved in ginsenoside biosynthesis. These AS genes were significantly up-enriched and more likely to form a co-expression network, thus suggesting the functions of AS and correlations of the AS genes in the process. This study provides comprehensive insights into the molecular characteristics and biological functions of AS in a single plant; thus, helping better understand biology.

Whole-blood transcriptome profiling reveals signatures of metformin and its therapeutic response

Metformin, a biguanide agent, is the first-line treatment for type 2 diabetes mellitus due to its glucose-lowering effect. Despite its wide application in the treatment of multiple health conditions, the glycemic response to metformin is highly variable, emphasizing the need for reliable biomarkers. We chose the RNA-Seq-based comparative transcriptomics approach to evaluate the systemic effect of metformin and highlight potential predictive biomarkers of metformin response in drug-naïve volunteers with type 2 diabetes in vivo. The longitudinal blood-derived transcriptome analysis revealed metformin-induced differential expression of novel and previously described genes involved in cholesterol homeostasis (SLC46A1 and LRP1), cancer development (CYP1B1, STAB1, CCR2, TMEM176B), and immune responses (CD14, CD163) after administration of metformin for three months. We demonstrate for the first time a transcriptome-based molecular discrimination between metformin responders (delta HbA1c ≥ 1% or 12.6 mmol/mol) and non-responders (delta HbA1c < 1% or 12.6 mmol/mol), that is determined by expression levels of 56 genes, explaining 13.9% of the variance in the therapeutic efficacy of the drug. Moreover, we found a significant upregulation of IRS2 gene (log₂FC 0.89) in responders compared to non-responders before the use of metformin. Finally, we provide evidence for the mitochondrial respiratory complex I as one of the factors related to the high variability of the therapeutic response to metformin in patients with type 2 diabetes mellitus.

Analysis of the genes controlling three quantitative traits in three diverse plant species reveals the molecular basis of quantitative traits

Most traits of agricultural importance are quantitative traits controlled by numerous genes. However, it remains unclear about the molecular mechanisms underpinning quantitative traits. Here, we report the molecular characteristics of the genes controlling three quantitative traits randomly selected from three diverse plant species, including ginsenoside biosynthesis in ginseng (Panax ginseng C.A. Meyer), fiber length in cotton (Gossypium hirsutum L. and G. barbadense L.) and grain yield in maize (Zea mays L.). We found that a vast majority of the genes controlling a quantitative trait were significantly more likely spliced into multiple transcripts while they expressed. Nevertheless, only one to four, but not all, of the transcripts spliced from each of the genes were significantly correlated with the phenotype of the trait. The genes controlling a quantitative trait were multiple times more likely to form a co-expression network than other genes expressed in an organ. The network varied substantially among genotypes of a species and was associated with their phenotypes. These findings indicate that the genes controlling a quantitative trait are more likely pleiotropic and functionally correlated, thus providing new insights into the molecular basis underpinning quantitative traits and knowledge necessary to develop technologies for efficient manipulation of quantitative traits.

The bHLH gene family and its response to saline stress in Jilin ginseng, Panax ginseng C.A. Meyer

Basic helix-loop-helix (bHLH) gene family is a gene family of transcription factors that plays essential roles in plant growth and development, secondary metabolism and response to biotic and abiotic stresses. Therefore, a comprehensive knowledge of the bHLH gene family is paramount to understand the molecular mechanisms underlying these processes and develop advanced technologies to manipulate the processes efficiently. Ginseng, Panax ginseng C.A. Meyer, is a well-known medicinal herb; however, little is known  about the bHLH genes (PgbHLH) in the species. Here, we identified 137 PgbHLH genes from Jilin ginseng cultivar, Damaya, widely cultivated in Jilin, China, of which 50 are newly identified by pan-genome analysis. These 137 PgbHLH genes were phylogenetically classified into 26 subfamilies, suggesting their sequence diversification. They are alternatively spliced into 366 transcripts in a 4-year-old plant and involved in 11 functional subcategories of the gene ontology, indicating their functional differentiation in ginseng. The expressions of the PgbHLH genes dramatically vary spatio-temporally and across 42 genotypes, but they are still somehow functionally correlated. Moreover, the PgbHLH gene family, at least some of its genes, is shown to have roles in plant response to the abiotic stress of saline. These results provide a new insight into the evolution and functional differentiation of the bHLH gene family in plants, new bHLH genes to the PgbHLH gene family, and saline stress-responsive genes for genetic improvement in ginseng and other plant species.

Accurate Prediction of a Quantitative Trait Using the Genes Controlling the Trait for Gene-Based Breeding in Cotton

Accurate phenotype prediction of quantitative traits is paramount to enhanced plant research and breeding. Here, we report the accurate prediction of cotton fiber length, a typical quantitative trait, using 474 cotton (Gossypium ssp.) fiber length (GFL) genes and nine prediction models. When the SNPs/InDels contained in 226 of the GFL genes or the expressions of all 474 GFL genes was used for fiber length prediction, a prediction accuracy of r = 0.83 was obtained, approaching the maximally possible prediction accuracy of a quantitative trait. This has improved by 116%, the prediction accuracies of the fiber length thus far achieved for genomic selection using genome-wide random DNA markers. Moreover, analysis of the GFL genes identified 125 of the GFL genes that are key to accurate prediction of fiber length, with which a prediction accuracy similar to that of all 474 GFL genes was obtained. The fiber lengths of the plants predicted with expressions of the 125 key GFL genes were significantly correlated with those predicted with the SNPs/InDels of the above 226 SNP/InDel-containing GFL genes (r = 0.892, P = 0.000). The prediction accuracies of fiber length using both genic datasets were highly consistent across environments or generations. Finally, we found that a training population consisting of 100-120 plants was sufficient to train a model for accurate prediction of a quantitative trait using the genes controlling the trait. Therefore, the genes controlling a quantitative trait are capable of accurately predicting its phenotype, thereby dramatically improving the ability, accuracy, and efficiency of phenotype prediction and promoting gene-based breeding in cotton and other species.

Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals

Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes mellitus. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed metformin-induced differential expression of genes involved in intestinal immune network for IgA production and cytokine-cytokine receptor interaction pathways. Significantly elevated faecal sIgA levels during administration of metformin, and its correlation with the expression of genes associated with immune response (CXCR4, HLA-DQA1, MAP3K14, TNFRSF21, CCL4, ACVR1B, PF4, EPOR, CXCL8) supports a novel hypothesis of strong association between metformin and intestinal immune system, and for the first time provide evidence for altered RNA expression as a contributing mechanism of metformin’s action. In addition to universal effects, 4 clusters of functionally related genes with a subject-specific differential expression were distinguished, including genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). This inter-individual variation of the metformin effect on the transcriptional regulation goes in line with well-known variability of the therapeutic response to the drug.

A Comprehensive Analysis of Ontogeny of Renal Drug Transporters: mRNA Analyses, Quantitative Proteomics, and Localization

Human renal membrane transporters play key roles in the disposition of renally cleared drugs and endogenous substrates, but their ontogeny is largely unknown. Using 184 human postmortem frozen renal cortical tissues (preterm newborns to adults) and a subset of 62 tissue samples, we measured the mRNA levels of 11 renal transporters and the transcription factor pregnane X receptor (PXR) with quantitative real‐time polymerase chain reaction, and protein abundance of nine transporters using liquid chromatography tandem mass spectrometry selective reaction monitoring, respectively. Expression levels of p‐glycoprotein, urate transporter 1, organic anion transporter 1, organic anion transporter 3, and organic cation transporter 2 increased with age. Protein levels of multidrug and toxin extrusion transporter 2‐K and breast cancer resistance protein showed no difference from newborns to adults, despite age‐related changes in mRNA expression. Multidrug and toxin extrusion transporter 1, glucose transporter 2, multidrug resistance‐associated protein 2, multidrug resistance‐associated protein 4 (MRP4), and PXR expression levels were stable. Using immunohistochemistry, we found that MRP4 localization in pediatric samples was similar to that in adult samples. Collectively, our study revealed that renal drug transporters exhibited different rates and patterns of maturation, suggesting that renal handling of substrates may change with age.

Transcriptome analysis identifies strong candidate genes for ginsenoside biosynthesis and reveals its underlying molecular mechanism in Panax ginseng C.A. Meyer

Ginseng, Panax ginseng C.A. Meyer, is one of the most important medicinal herbs for human health and medicine in which ginsenosides are known to play critical roles. The genes from the cytochrome P450 (CYP) gene superfamily have been shown to play important roles in ginsenoside biosynthesis. Here we report genome-wide identification of the candidate PgCYP genes for ginsenoside biosynthesis, development of functional SNP markers for its manipulation and systems analysis of its underlying molecular mechanism. Correlation analysis identified 100 PgCYP genes, including all three published ginsenoside biosynthesis PgCYP genes, whose expressions were significantly correlated with the ginsenoside contents. Mutation association analysis identified that six of these 100 PgCYP genes contained SNPs/InDels that were significantly associated with ginsenosides biosynthesis (P ≤ 1.0e-04). These six PgCYP genes, along with all ten published ginsenoside biosynthesis genes from the PgCYP and other gene families, formed a strong co-expression network, even though they varied greatly in spatio-temporal expressions. Therefore, this study has identified six new ginsenoside biosynthesis candidate genes, provided a genome-wide insight into how they are involved in ginsenoside biosynthesis and developed a set of functional SNP markers useful for enhanced ginsenoside biosynthesis research and breeding in ginseng and related species.