Application of serial analysis of gene expression to the study of human genetic disease

Application of multi-omics techniques to androgenetic alopecia: Current status and perspectives

The rapid advancement of sequencing technologies has enabled the generation of vast datasets, allowing for the in-depth analysis of sequencing data. This analysis has facilitated the validation of novel pathogenesis hypotheses for understanding and treating diseases through ex vivo and in vivo experiments. Androgenetic alopecia (AGA), a common hair loss disorder, has been a key focus of investigators attempting to uncover its underlying mechanisms. Abnormal changes in mRNA, proteins, and metabolites have been identified in individuals with AGA, and future developments in sequencing technologies may reveal new biomarkers for AGA. By integrating multiple omics analysis datasets such as genomics, transcriptomics, proteomics, and metabolomics-along with clinical phenotype data-we can achieve a comprehensive understanding of the molecular underpinnings of AGA. This review summarizes the data-mining studies conducted on various omics analysis datasets as related to AGA that have been adopted to interpret the biological data obtained from different omics layers. We herein discuss the challenges of integrative omics analyses, and suggest that collaborative multi-omics studies can enhance the understanding of the complete pathomechanism(s) of AGA by focusing on the interaction networks comprising DNA, RNA, proteins, and metabolites.

The Transcriptomics to Proteomics of Hair Cell Regeneration: Looking for a Hair Cell in a Haystack

Mature mammals exhibit very limited capacity for regeneration of auditory hair cells, while all non-mammalian vertebrates examined can regenerate them. In an effort to find therapeutic targets for deafness and balance disorders, scientists have examined gene expression patterns in auditory tissues under different developmental and experimental conditions. Microarray technology has allowed the large-scale study of gene expression profiles (transcriptomics) at whole-genome levels, but since mRNA expression does not necessarily correlate with protein expression, other methods, such as microRNA analysis and proteomics, are needed to better understand the process of hair cell regeneration. These technologies and some of the results of them are discussed in this review. Although there is a considerable amount of variability found between studies owing to different species, tissues and treatments, there is some concordance between cellular pathways important for hair cell regeneration. Since gene expression and proteomics data is now commonly submitted to centralized online databases, meta-analyses of these data may provide a better picture of pathways that are common to the process of hair cell regeneration and lead to potential therapeutics. Indeed, some of the proteins found to be regulated in the inner ear of animal models (e.g., IGF-1) have now gone through human clinical trials.

Suppression Subtractive Hybridization Versus Next-Generation Sequencing in Plant Genetic Engineering: Challenges and Perspectives

Suppression subtractive hybridization (SSH) is an effective method to identify different genes with different expression levels involved in a variety of biological processes. This method has often been used to study molecular mechanisms of plants in complex relationships with different pathogens and a variety of biotic stresses. Compared to other techniques used in gene expression profiling, SSH needs relatively smaller amounts of the initial materials, with lower costs, and fewer false positives present within the results. Extraction of total RNA from plant species rich in phenolic compounds, carbohydrates, and polysaccharides that easily bind to nucleic acids through cellular mechanisms is difficult and needs to be considered. Remarkable advancement has been achieved in the next-generation sequencing (NGS) field. As a result of progress within fields related to molecular chemistry and biology as well as specialized engineering, parallelization in the sequencing reaction has exceptionally enhanced the overall read number of generated sequences per run. Currently available sequencing platforms support an earlier unparalleled view directly into complex mixes associated with RNA in addition to DNA samples. NGS technology has demonstrated the ability to sequence DNA with remarkable swiftness, therefore allowing previously unthinkable scientific accomplishments along with novel biological purposes. However, the massive amounts of data generated by NGS impose a substantial challenge with regard to data safe-keeping and analysis. This review examines some simple but vital points involved in preparing the initial material for SSH and introduces this method as well as its associated applications to detect different novel genes from different plant species. This review evaluates general concepts, basic applications, plus the probable results of NGS technology in genomics, with unique mention of feasible potential tools as well as bioinformatics.

Metformin, besides exhibiting strong in vivo anti-inflammatory properties, increases mptp-induced damage to the nigrostriatal dopaminergic system

Metformin is a widely used oral antidiabetic drug with known anti-inflammatory properties due to its action on AMPK protein. This drug has shown a protective effect on various tissues, including cortical neurons. The aim of this study was to determine the effect of metformin on the dopaminergic neurons of the substantia nigra of mice using the animal model of Parkinson's disease based on the injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, an inhibitor of the mitochondrial complex I. In vivo and in vitro experiments were used to study the activation of microglia and the damage of the dopaminergic neurons. Our results show that metformin reduced microglial activation measured both at cellular and molecular levels. Rather than protecting, metformin exacerbated dopaminergic damage in response to MPTP. Our data suggest that, contrary to other brain structures, metformin treatment could be deleterious for the dopaminergic system. Hence, metformin treatment may be considered as a risk factor for the development of Parkinson's disease.

The Interplay Between Respiratory Supercomplexes and ROS in Aging

SIGNIFICANCE

The molecular mechanism of aging is still vigorously debated, although a general consensus exists that mitochondria are significantly involved in this process. However, the previously postulated role of mitochondrial-derived reactive oxygen species (ROS) as the damaging agents inducing functional loss in aging has fallen out of favor in the recent past. In this review, we critically examine the role of ROS in aging in the light of recent advances on the relationship between mitochondrial structure and function.

RECENT ADVANCES

The functional mitochondrial respiratory chain is now recognized as a reflection of the dynamic association of respiratory complexes in the form of supercomplexes (SCs). Besides providing kinetic advantage (channeling), SCs control ROS generation by the respiratory chain, thus providing a means to regulate ROS levels in the cell. Depending on their concentration, these ROS are either physiological signals essential for the life of the cell or toxic species that damage cell structure and functions.

CRITICAL ISSUES

We propose that under physiological conditions the dynamic nature of SCs reversibly controls the generation of ROS as signals involved in mitochondrial-nuclear communication. During aging, there is a progressive loss of control of ROS generation so that their production is irreversibly enhanced, inducing a vicious circle in which signaling is altered and structural damage takes place.

FUTURE DIRECTIONS

A better understanding on the forces affecting SC association would allow the manipulation of ROS generation, directing these species to their physiological signaling role.

Copy number variation analysis by ligation-dependent PCR based on magnetic nanoparticles and chemiluminescence

A novel system for copy number variation (CNV) analysis was developed in the present study using a combination of magnetic separation and chemiluminescence (CL) detection technique. The amino-modified probes were firstly immobilized onto carboxylated magnetic nanoparticles (MNPs) and then hybridized with biotin-dUTP products, followed by amplification with ligation-dependent polymerase chain reaction (PCR). After streptavidin-modified alkaline phosphatase (STV-AP) bonding and magnetic separation, the CL signals were then detected. Results showed that the quantification of PCR products could be reflected by CL signal values. Under optimum conditions, the CL system was characterized for quantitative analysis and the CL intensity exhibited a linear correlation with logarithm of the target concentration. To validate the methodology, copy numbers of six genes from the human genome were detected. To compare the detection accuracy, multiplex ligation-dependent probe amplification (MLPA) and MNPs-CL detection were performed. Overall, there were two discrepancies by MLPA analysis, while only one by MNPs-CL detection. This research demonstrated that the novel MNPs-CL system is a useful analytical tool which shows simple, sensitive, and specific characters which are suitable for CNV analysis. Moreover, this system should be improved further and its application in the genome variation detection of various diseases is currently under further investigation.

Gene expression profile in human trabecular meshwork from patients with primary open-angle glaucoma

PURPOSE

To identify the specific genes in human trabecular meshwork (TM) related to POAG.

METHODS

Primary open-angle glaucoma TM specimens were obtained from routine trabeculectomy surgery. Nonglaucomatous control TM specimens were dissected from donor eyes using the same approach as a standard trabeculectomy. All cases were screened for myocilin (MYOC) mutations. Total RNA was extracted, labeled, and hybridized to Illumina HumanWG-6 BeadChips. Expression data were normalized and analyzed using the R package limma in Bioconductor. Pathway analyses were performed using DAVID Bioinformatics Resources.

RESULTS

Our study included surgical TM specimens from 15 cases and 13 controls. One case was identified with a heterozygous Q368X MYOC mutation. If TMs were available from both eyes in an individual, the expression data were combined for analysis. The following three comparisons were performed for differential analyses: (1) MYOC POAG case versus 14 non-MYOC POAG cases, (2) MYOC POAG case versus 13 controls, and (3) 14 non-MYOC POAG cases versus 13 controls. Limited by one MYOC case in comparisons 1 and 2, expression changes were reported comparing the fold changes but without P values. Comparison 3 identified 483 genes, including 36 components of TM exosomes. Gene ontology analysis identified several enriched functional clusters, including cell adhesion, extracellular matrix, and secretion.

CONCLUSIONS

This is the largest TM expression study of POAG cases and controls performed to date and represents the first report of TM expression in a patient having POAG with a Q368X MYOC mutation. Our data suggest the potential role of endocytic and exosome pathways in the pathogenesis of POAG.

RNA-Seq and human complex diseases: recent accomplishments and future perspectives

The availability of the human genome sequence has allowed identification of disease-causing mutations in many Mendelian disorders, and detection of significant associations of nucleotide polymorphisms to complex diseases and traits. Despite these progresses, finding the causative variations for most of the common diseases remains a complex task. Several studies have shown gene expression analyses provide a quite unbiased way to investigate complex traits and common disorders' pathogenesis. Therefore, whole-transcriptome analysis is increasingly acquiring a key role in the knowledge of mechanisms responsible for complex diseases. Hybridization- and tag-based technologies have elucidated the involvement of multiple genes and pathways in pathological conditions, providing insights into the expression of thousand of coding and noncoding RNAs, such as microRNAs. However, the introduction of Next-Generation Sequencing, particularly of RNA-Seq, has overcome some drawbacks of previously used technologies. Identifying, in a single experiment, potentially novel genes/exons and splice isoforms, RNA editing, fusion transcripts and allele-specific expression are some of its advantages. RNA-Seq has been fruitfully applied to study cancer and host-pathogens interactions, and it is taking first steps for studying neurodegenerative diseases (ND) as well as neuropsychiatric diseases. In addition, it is emerging as a very powerful tool to study quantitative trait loci associated with gene expression in complex diseases. This paper provides an overview on gene expression profiling of complex diseases, with emphasis on RNA-Seq, its advantages over conventional technologies for studying cancer and ND, and for linking nucleotide variations to gene expression changes, also discussing its limitations.

Risk of Parkinson disease onset in patients with diabetes: a 9-year population-based cohort study with age and sex stratifications

OBJECTIVE

We retrospectively assessed the age- and sex-specific incidence and relative risk of Parkinson disease (PD) in Taiwan's diabetic population.

RESEARCH DESIGN AND METHODS

Study cohort included 603,416 diabetic patients and 472,188 nondiabetic control subjects. Incidence rate and relative risk of PD (ICD-9-CM 332.0) were evaluated.

RESULTS

The incidence of PD was 3.59 and 2.15 per 10,000 person-years for the diabetic and control group, respectively, representing a covariate adjusted hazard ratio (HR) of 1.61 (95% CI 1.56-1.66), which was substantially reduced to 1.37 (1.32-1.41) after adjusting for medical visits. Diabetes was associated with a significantly elevated risk of PD in all sex and age stratifications except in young women, with the highest HR noted for young men aged 21-40 years (2.10 [1.01-4.42]), followed by women aged 41-60 (2.05 [1.82-2.30]) and >60 years (1.65 [1.58-1.73]).

CONCLUSIONS

Diabetes is associated with an increased risk of PD onset in a Chinese population, and the relation is stronger in women and younger patients.

Single-cell and regional gene expression analysis in Alzheimer's disease

The clinical manifestations of Alzheimer's disease (AD) are secondary to the substantial loss of cortical neurons. To be effective, neuroprotective strategies will need to target the primary pathogenic mechanisms of AD prior to cell loss. The differences between neurons are largely determined by their specific repertoire of mRNAs. Thus, transcriptomic analyses that do not assume a priori etiological hypotheses are potentially powerful tools that can be used to understand the pathogenesis of complex diseases, including AD. The human brain comprises thousands of different cell types of both neuronal and non-neuronal origins. Information about individual cell-type-specific gene expression patterns will allow for a better understanding of the mechanisms that govern the progression of AD, which may lead to new therapeutic targets for prevention and treatment of the disease. This review provides an overview of the current technologies in use and the developments for single-cell extraction and transcriptome analysis. Recent transcriptome profiling studies on individual AD-afflicted brain cells are also discussed.

Telomeres in trisomy 21 amniocytes

Individuals with trisomy 21 have an increased risk of developing leukemia and premature dementia. They also have a higher rate of telomere loss. The aim of the study was to compare telomere length and the hTERC gene copy number, which encodes the telomerase RNA subunit, in amniocytes of trisomy 21 conceptions and normal pregnancies. A quantitative fluorescence-in-situ protocol (Q-FISH) was used to compare telomere length in amniocytes cultured from 11 trisomy 21 conceptions and from 14 normal pregnancies. Quantification was conducted using novel computer software. Fluorescence in situ hybridization (FISH) was used to assess the percentage of cells with additional copies of hTERC. We found that the immunofluorescence intensity, which represents telomere length, was significantly lower in amniocytes from trisomy 21 conceptions compared to the control group. The trisomy 21 group had a higher number of cells with additional copies of hTERC. This observation could be one of the cytogenetic parameters that represent a state of genetic instability and might play a role in the pathomechanism of typical features of Down syndrome, such as dementia and malignancy.

Uncovering the complexity of transcriptomes with RNA-Seq

In recent years, the introduction of massively parallel sequencing platforms for Next Generation Sequencing (NGS) protocols, able to simultaneously sequence hundred thousand DNA fragments, dramatically changed the landscape of the genetics studies. RNA-Seq for transcriptome studies, Chip-Seq for DNA-proteins interaction, CNV-Seq for large genome nucleotide variations are only some of the intriguing new applications supported by these innovative platforms. Among them RNA-Seq is perhaps the most complex NGS application. Expression levels of specific genes, differential splicing, allele-specific expression of transcripts can be accurately determined by RNA-Seq experiments to address many biological-related issues. All these attributes are not readily achievable from previously widespread hybridization-based or tag sequence-based approaches. However, the unprecedented level of sensitivity and the large amount of available data produced by NGS platforms provide clear advantages as well as new challenges and issues. This technology brings the great power to make several new biological observations and discoveries, it also requires a considerable effort in the development of new bioinformatics tools to deal with these massive data files. The paper aims to give a survey of the RNA-Seq methodology, particularly focusing on the challenges that this application presents both from a biological and a bioinformatics point of view.

Computational tools for the interactive exploration of proteomic and structural data

Linking proteomics and structural data is critical to our understanding of cellular processes, and interactive exploration of these complementary data sets can be extremely valuable for developing or confirming hypotheses in silico. However, few computational tools facilitate linking these types of data interactively. In addition, the tools that do exist are neither well understood nor widely used by the proteomics or structural biology communities. We briefly describe several relevant tools, and then, using three scenarios, we present in depth two tools for the integrated exploration of proteomics and structural data.