What cause isolated huge cock gene-

Biomedical research has been previously reported to primarily focus on a minority of all known genes. Here, we demonstrate that these differences in attention can be explained, to a large extent, exclusively from a small set of identifiable chemical, physical, and biological properties of genes. Together with knowledge about homologous genes from model organisms, these features allow us to accurately predict the number of publications on individual human genes, the year of their first report, the levels of funding awarded by the National Institutes of Health NIH , and the development of drugs against disease-associated genes. By explicitly identifying the reasons for gene-specific bias and performing a meta-analysis of existing computational and experimental knowledge bases, we describe gene-specific strategies for the identification of important but hitherto ignored genes that can open novel directions for future investigation. Biomedical research is one of the largest areas of present-day science and embeds the hope and potential to improve the lives of the general public.

What cause isolated huge cock gene

What cause isolated huge cock gene

Environment plays siolated major role in effects of the human genetic disease phenylketonuria. Rodriguez-Esteban R, Jiang X. Genes on the same chromosome would theoretically never recombine. Luis Amaral. Am J Hum Genet ; 91 : — Heteroplasmic mutations often have a variable threshold, i.

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Mitochondrial function is under dual genetic control — the

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Biomedical research has been previously reported to primarily focus on a minority of all known genes. Here, we demonstrate that these differences in attention can be explained, to a large extent, exclusively from a small set of identifiable chemical, physical, and biological properties of genes. Together with knowledge about homologous genes from model organisms, these features allow us to accurately predict the number of publications on individual human genes, the year of their first report, the levels of funding awarded by the National Institutes of Health NIH , and the development of drugs against disease-associated genes.

By explicitly identifying the reasons for gene-specific bias and performing a meta-analysis of existing computational and experimental knowledge bases, we describe gene-specific strategies for the identification of important but hitherto ignored genes that can open novel directions for future investigation.

Biomedical research is one of the largest areas of present-day science and embeds the hope and potential to improve the lives of the general public.

In order to understand how individual scientists choose individual research questions, we study why certain genes are well studied but others are not. While it has been previously observed that most research on human genes only concentrates on approximately 2, of the 19, genes of the human genome, the reasons for this ignorance are largely unknown. We systematically test explanations for this observation by compiling an extensive resource that characterizes biomedical research, including but not limited to hundreds of chemical and biological properties of gene-encoded proteins, and the published scientific literature on individual genes.

Using machine learning methods, we can predict the number of publications on individual genes, the year of the first publication about them, the extent of funding by the National Institutes of Health, and the existence of related medical drugs. We find that biomedical research is primarily guided by a handful of generic chemical and biological characteristics of genes, which facilitated experimentation during the s and s, rather than the physiological importance of individual genes or their relevance to human disease.

PLoS Biol 16 9 : e This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Patent data was obtained from Rosenfeld and Mason. Disambiguated authorship information was obtained from Clarivate Analytics. Allele frequencies in human populations were obtained from the ExAc database. Compartment information and protein abundance was obtained from Itzhak and colleagues. Loss-of-function information in human cell lines was obtained from Blomen and colleagues, Hart and colleagues, and Wang and colleagues. Thermal stability on proteins was obtained from Leuenberger and colleagues.

Transcript abundance in cells and tissues was obtained from the human protein atlas. Transcript stability was obtained from Tani and colleagues.

Drugs and their targets were obtained from DrugBank Version 5. Bioplex 2. GenomeRNAi v17 was obtained from www. Richard Morimoto. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Daniel F. Rice Foundation. Luis Amaral. Thomas Stoeger. NSF grant number Simons Foundation grant number Competing interests: The authors have declared that no competing interests exist. Recent studies have demonstrated the highly imbalanced research effort directed towards individual human protein-coding genes [ 1 — 8 ], which manifests itself in several ways, including the number of publications per gene, the number of human-curated and computationally predicted functional annotations, the number of gene names and gene symbols, and the number of patents containing their nucleotide sequences S1 Fig.

Plausibly, this observed disparity could reflect a lack of importance of many genes, but more likely it could also reflect existing social structures of research [ 9 , 10 ], scientific and economic reward systems [ 11 , 12 ], medical and societal relevance [ 13 — 15 ], preceding discoveries [ 2 , 16 ], serendipity [ 17 , 18 ], the availability of technologies [ 19 , 20 ] and reagents [ 6 , 21 ], and other intrinsic characteristics of genes [ 22 — 24 ].

It remains unclear, however, if any of these factors can significantly explain the observed number of publications on individual human genes. Nor is it known whether descriptions about the formation of scientific knowledge translate into gene-specific insight, and whether these reasons for historically grown bias could already be mitigated by current experimental possibilities.

In order to address these challenges, we created a database cross-referencing chemical, physical, biological, historical, bibliometric, financial, technological, and experimental data on all human protein-coding genes from 36 different sources see Materials and methods. Using this resource, we show how characteristics of genes relate to the macroscopic output of biomedical research in terms of the number of publications, perceived biological importance of genes, funding, and translational activities.

We show different examples of how this resource can be used to define strategies for a more efficient exploration of the space of biological functions, and provide high-level gene-specific analyses in a series of supplementary tables.

To test if measurable intrinsic chemical, physical, and biological features of genes and gene products alone suffice to describe the number of publications per gene, we gathered features per gene, which could either be computed from known sequences of these genes or obtained from previously published genome-scale experiments Fig 1A.

Foreshadowing our subsequent analyses, the absence of reported features correlated with a lower number of reported publications S2A Fig. This initial result illustrates limitations in experimental approaches and a surprising degree of uncertainty that remains about human genes and the existence of their gene products. A Illustration of modeling approach and prediction of number of research publications for single genes using information on physical, chemical, and biological features of genes S1 Data.

B Research publications on individual genes grouped by t-SNE visualization using the 15 features most important to the models used in A. Heatmaps show z-scored values of the 15 features for the genes in each cluster. To assess whether the values of these features, rather than solely their presence, would quantitatively inform on the number of publications of individual genes, we proceeded by only considering the 12, genes with a complete set of features S2 Table.

Using gradient boosting regressions with out-of-sample Monte Carlo cross-validation [ 25 ], we could predict to a significant extent the number of publications on any given gene Fig 1A , Spearman: 0. We therefore used these 15 features to define a dimensional space for the 15, genes that reflects the correlation between publications and individual features and combinations of distinct features S3 Table.

Clusters of genes within this space were enriched for distinct Gene Ontology annotations and thus known biological roles Fig 1B , S4 Fig. This initial finding demonstrates that the number of publications on genes can be attributed in a large extent solely to a small set of their physical, chemical, and biological characteristics.

The 15 features described above have all been suspected to affect the ability to study specific genes by traditional methodologies [ 23 , 26 — 28 ]. In line with the similarity among prior reports on the disparity in the number of publications per gene, we found that the present inequality in the number of publications has stayed constant since the year S5A and S5B Fig.

Similarly, we found the number of publications per gene to be highly correlated between the current decade and preceding time periods of research Fig 2A , Spearman: 0.

Interestingly, we also identify six genes that are presently experiencing a strong increase in their number of publications, which can be traced back to a recent acknowledgment of their medical importance S4 Table. A Number of publications per gene for past and recent research. Publications of past research until are scaled so that the total number of publications matches present research — Dashed grey lines delimit three standard deviations away from the mean.

B Prediction of the number of research publications for the model of Fig 1A extended by including the year of the first publication on the specific human gene S1 Data. D Percentage of publications that cite publications with nonhuman genes more frequently than they cite publications with human genes S1 Data.

E Prediction of the year of initial publications on individual genes using the features from Fig 1A and the year of the initial publication on homologous genes of nonhuman model organisms S1 Data. F Prediction of the number of research publications using the features of Fig 1A and the number of publications on homologous genes S1 Data.

In contrast to the alternative hypothesis that research patterns on human genes would be particularly dynamic [ 1 , 2 ], and generalizing beyond earlier studies on two gene families [ 6 , 21 ] and genes expressed specifically in the brain [ 30 ], we find that human genes that had been reported early—as indicated by an early initial publication date on the genes or their encoded gene products [ 19 , 31 ]—tend to also be more studied presently S5C Fig , Spearman: 0.

To identify the factors associated with the initial reports of genes, we next created separate models with the above features and trained them to predict the year of initial publications.

While these predictions are slightly less accurate Fig 2C , Spearman: 0. This shows that characteristics of genes, which have been important for the initial discovery of genes, remain partially correlated with the number of present publications on those genes.

Similarly, we observe that while the number of publications is correlated between the first entry e. This demonstrates that even among evolutionary and chemically highly related genes, early initial reports coincide with a higher number of publications S5F Fig.

Yet, the reduced prediction accuracy observed for the prediction of the year of the initial report may hint at the presence of another factor or factors that were not included in our curation of gene-intrinsic features. Thus, we performed a bibliometric analysis of PubMed to compare individual publications against the genes contained in the publications that they cite. Focusing on the publications reporting the discovery of new human genes, we found an overrepresentation of publications that cite studies of nonhuman genes Figs 2D and S6A.

Inspecting the organisms of these genes, we observed two classes of organisms. Assuming that citations are one proxy of scientific impact, this finding suggests that initial reports on human genes have been particularly influenced by research in model organisms and that multiple model organisms have contributed complementary roles in the discovery of human genes.

With these insights, we dramatically increased the prediction accuracy of the year of initial report of a human gene by including the years of the initial reports on homologous genes of model organisms Fig 2E , from Spearman: 0. Moreover, the years of the initial reports on homologous genes improved prediction accuracy of the number of publications to a greater extent than the year of the initial report on the human genes themselves S7A Fig , Spearman: 0.

Consistent with the picture emerging from these analyses, the homologous genes of unstudied human genes are likewise unstudied in model organisms S6 Table , and including the number of publications on homologous genes yielded almost perfect predictions of the number of publications for individual human genes Fig 2F , Spearman: 0. Taken together, these findings demonstrate the impact of research on model organisms on the knowledge acquired on human biology—a hypothesis that had been proposed but not demonstrated previously [ 32 ].

Given the observed historic continuity of scientific endeavors, we wondered whether biomedical research has already identified all particularly important human genes and hence allocates the production of publications accordingly. Despite this simplifying assumption, we reassuringly observe that genes that have received the most attention in publications are around three to five times more likely to be sensitive to loss-of-function mutations or to have been identified in genome-wide association studies GWAS Fig 3A.

This enrichment is greatest for genes that have been repeatedly identified by several independent studies on the most frequently studied human phenotypic traits. However, we observe an extraordinarily more extreme fold enrichment in the average attention when comparing the genes that have received the least attention to those genes that have received the highest attention Fig 3A.

Hence, while biomedical research does focus on important genes, a disproportionally high amount of research effort concentrates on already well-studied genes. A Relative enrichment of the presence of genes with genetic loss-of-function LoF intolerance, presence of genes with GWAS traits, and the attention within publications.

B Predicted versus actual NIH budget spending on individual genes dots. The black line shows a lowess fit and the dashed lines show the two distinct regimes of the prediction S1 Data.

C Fraction of disease-linked genes with at least one experimental drug conditioned on the predicted order of discovery according to the model shown in Fig 2B. We observe a similar pattern when inspecting the allocation of funding by the National Institutes of Health NIH as another proxy of importance.

Although not surprising given the correlation between the number of publications per gene and the amount of funding allocation by the NIH S9A and S9B Fig , Spearman: 0. Yet, prediction accuracy only marginally improves by additionally considering 3, features detailing known annotations between genes and diseases S9D Fig , Spearman: 0.

This shows that the previously uncovered intrinsic characteristics of genes and the year of the initial report of homologous genes not only correlate with research funding, but that they would do so to a larger extent than presently existent knowledge about the role of genes in disease. Along the same lines, if exclusively considering genes with a reported role in disease, we found that the same models that had predicted the year of the initial publication of genes Fig 2E also predicted the likelihood of the existence of both approved and preclinical drugs Fig 3C , S9F Fig.

Collectively, these findings show that a small number of characteristics of genes and the availability of model organisms exert a strong influence on basic and applied research on human disease and that the resulting research can significantly deviate from the actual biological importance of individual genes.

The strong correlations uncovered, and earlier work on the availability of reagents [ 5 , 6 , 21 ] suggest, that researchers may face very practical constraints that prevent them from exploring little-studied genes and that there might be a need for alternative discovery strategies [ 33 ].

In support of this possibility and extending beyond the above findings on the bulk of accrued knowledge, we observe that the fraction of genes that have been described in focused single-gene studies has only been increasing at a constant rate Fig 4A.

Extrapolating from this trend, we estimate that it would take at least five decades until all genes are sufficiently studied. Similarly, simply studying little-studied genes might not be very informative and could expose junior scientists at an increased career risk S10A Fig.

Given a recent bibliometric study, which demonstrated that novelty could, however, be beneficial for the impact of a scientific publication if combined with an established research context [ 34 ], we therefore thought to build a resource that provides a context for the exploration of little-studied genes.

A Estimation of the years until all genes are studied if scientific enterprise continues to follow trends reported above. Number of genes with at least n focused single-gene publications per year. Dashed lines show extrapolation of the bounds of linear regression for recent years.

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What cause isolated huge cock gene

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Mitochondrial function is under dual genetic control — the Mitochondrial dysfunction can arise because of defects in either mitochondrial DNA or nuclear mitochondrial genes, and can present in childhood or adulthood in association with vast clinical heterogeneity, with symptoms affecting a single organ or tissue, or multisystem involvement. There is no cure for mitochondrial disease for the vast majority of mitochondrial disease patients, and a genetic diagnosis is therefore crucial for genetic counselling and recurrence risk calculation, and can impact on the clinical management of affected patients.

This review focuses on the current genetic landscape associated with mitochondrial disease, before focusing on advances in studying associated mitochondrial pathology in two, clinically relevant organs — skeletal muscle and brain. With bacterial origins, a historical symbiotic relationship evolved during which mitochondria became normal constituents of eukaryotic cells 3.

Their ancestry remains apparent from their own multicopy genetic material [mitochondrial DNA mtDNA ], with copy number varying greatly between individuals and across different tissues from the same individual. The There is a general lack of genotype—phenotype correlations in many mitochondrial disorders, which means that establishing a genetic diagnosis can be a complicated process, and remains elusive for many patients. This review provides a concise update on three areas where there have been major advances in our understanding in recent years 10 , i.

In contrast, homoplasmy occurs when all of the mtDNA molecules have the same genotype. Heteroplasmic mutations often have a variable threshold, i. When the mutation load exceeds this threshold, metabolic dysfunction and associated clinical symptoms occur.

Maternally transmitted mtDNA defects may involve a clinically unaffected mother who harbours the familial mtDNA mutation below the threshold required for cellular dysfunction, although her oocytes harbour varying mutation loads, owing to the selection pressures of the mitochondrial bottleneck It is therefore almost impossible to predict the recurrence risk for subsequent pregnancies, although prenatal testing of embryonic tissues by the use of chorionic villus biopsy or amniocentesis can provide an accurate measure of mtDNA heteroplasmy in the fetus, which can inform reproductive choices The recurrence risk of de novo mtDNA point mutations is very low, except for the risk of germline mosaicism in maternal oocytes PEO is the more benign presentation attributable to single mtDNA deletions, and is associated with ophthalmoplegia, ptosis, and myopathy Defective mtDNA maintenance, transcription, or protein translation, or a defective ancillary process such as mitochondrial import, can cause either quantitative depletion of mtDNA copy number or qualitative affecting mtDNA genome integrity, resulting in multiple large mtDNA deletions effects.

These result from mutations affecting nuclear genes, and inheritance occurs in a Mendelian or de novo fashion. The majority of the genes encoding the mitoproteome are in the nuclear genome 5 and follow Mendelian inheritance patterns. The first nuclear mitochondrial gene mutation was identified in in SDHA , encoding a structural subunit of complex II 25 , and there has been monumental progress in the discovery of mitochondrial disease candidate genes since then.

New proteomic and transcriptomic approaches are being applied to models of human disease to uncover new candidates 26 , 27 , and patient analyses are validating their involvement in human pathology The traditional approach of linkage analysis by the use of multiple affected family members has given way to massively parallel sequencing strategies, including whole exome sequencing WES , either of affected singletons or of proband—parent trios, and new disease genes are still emerging over 20 years later.

It is apparent that more severe clinical phenotypes are often associated with recessive defects, presumably because of varying heteroplasmy levels in clinically affected tissues and the dichotomous effect of recessive mutations; therefore, mtDNA mutations are more common in adults, whereas nuclear gene defects are overrepresented in paediatric cases In this review, we delineate the nuclear mitochondrial disease genes into those that cause isolated and those that cause multiple respiratory chain complex deficiencies, for simplicity and brevity.

Multimeric protein complexes I—IV shuttle electrons along the respiratory chain, facilitated by the reduction of the cofactors coenzyme Q 10 Q and cytochrome c cyt c. The clinical symptoms associated with complex I deficiency are heterogeneous, although the prognosis is typically poor, with rapid progression. Lactic acidosis is a common feature, although it is often present with other symptoms, such as cardiomyopathy or leukodystrophy.

Mutations have been identified in 19 of the 37 structural subunits, and in 10 of 14 identified assembly factors. Although there are a few exceptions, such as the p. Biallelic mutations have been associated with congenital metabolic presentations, predominantly affecting either the central nervous system CNS or heart hypertrophic cardiomyopathy, leukodystrophy, Leigh syndrome, and encephalopathy 43 , whereas heterozygous mutations are associated with cancer susceptibility, particularly pheochromocytoma and paraganglioma Ubiquinol—cytochrome c oxidoreductase, complex III of the respiratory chain, functions as a homodimer to transfer electrons from ubiquinol to cytochrome b , and then to cytochrome c.

Complex III is composed of 11 structural subunits plus two heme groups and the Rieske iron—sulphur protein. Complex IV pumps protons across the inner mitochondrial membrane, contributing to the proton motive force for ATP synthase exploitation, and donates electrons to oxygen at the respiratory chain termini to form water.

Complex IV has 13 structural subunits, and at least 26 additional proteins involved in assembly and biogenesis Some proteins are linked tightly with specific aspects of COX biogenesis e.

Clinically, presentations are often early onset and devastating, predominantly affecting the heart and CNS e. Defects have been reported in only four nuclear complex V genes to date, with varied clinical phenotypes. The most common defects involve TMEM70 , including a Roma TMEM70 founder mutation causing lactic acidosis and cardiomyopathy 58 , although encephalopathy and cataracts have been reported in other populations These include the transcription of mitochondrial mRNA e.

RRM2B 62 , cellular signalling e. Numerous subgroups of proteins are involved in mitochondrial gene translation: mitochondrial aminoacyl tRNA synthetases, which are responsible for charging each mitochondrial tRNA molecule with the appropriate amino acid e. MTPAP 65 , mitoribosomal proteins e. TRMU The genetic diagnostic pathway for these disorders is complex, and WES is often the most successful strategy Not all mitochondrial disease patients have evidence of respiratory chain enzyme dysfunction, but have other evidence of mitochondrial disease, such as elevated lactate levels, suggestive magnetic resonance imgaing brain changes, and multisystem involvement.

Genetic causes include defective enzymes of the Krebs cycle e. In the absence of effective treatments, provision of a firm genetic diagnosis facilitates genetic counselling and access to reproductive options for patients and their families. Given the small size of the mtDNA genome, this is often sequenced in suspected mitochondrial disease patients to exclude a primary mtDNA defect before nuclear genes are scrutinized.

Stratification according to respiratory chain defect can be appropriate for many patients in whom muscle biopsy is available, but even then it may be misleading — a number of patients with an isolated complex I deficiency have, in fact, a defect of mitochondrial translation 40 ; moreover, this strategy can be ineffective for genes that show inconsistent biochemical profiles Stratification according to clinical phenotype is similarly complicated by genetic heterogeneity NGS strategies employed in the genetic diagnosis of mitochondrial disease.

B WES targets only the coding exons plus immediate intron—exon boundaries. C Target capture facilitates sequencing of a predetermined genomic region or list of candidate disease genes. Despite a proven track record in a research setting and the increasing availability of affordable NGS options to diagnostic laboratories, the case has yet to be made regarding the clinical validity of unrestricted WES within a diagnostic setting.

Further analysis of the WES data for patients lacking a diagnosis following virtual panel analysis could be subsequently undertaken in a research setting. Indeed, most of the candidate genes included in diagnostic virtual panels have their origins in research.

Similarly, characterization of predicted mitochondrial proteins of unknown function is another critical strategy for identifying novel disease candidate genes As discussed above, the laboratory investigation of suspected mitochondrial disease is complex, and algorithms employ a multidisciplinary approach using clinical and functional studies to guide genetic analysis Although mitochondrial disorders are characterized by a wide spectrum of clinical presentations, owing to the high metabolic requirements, muscle is frequently affected — either exclusively e.

In both scenarios, muscle involvement can arise from mutations in nuclear or mtDNA genes, and the association with distinctive histopathological hallmarks makes muscle an excellent postmitotic surrogate for the study of many multisystem mitochondrial disorders. Diagnostic centres specializing in mitochondrial disorders employ numerous techniques to assess mitochondrial function, including the assessment of individual mitochondrial OXPHOS activities in vitro Although useful for identifying widespread mitochondrial defects, this technique has some limitations; it requires large quantities of muscle typically 50— mg of tissue and may fail to detect subtle OXPHOS deficiencies, especially when only a few muscle fibres are affected e.

Furthermore, only complexes I—IV can be reliably assessed in frozen muscle. RRFs can show either normal oxidative enzyme activities often reported in association with the m. They represent a characteristic histopathological feature of mitochondrial disorders, however, they are not entirely diagnostic, as they are also seen with normal ageing 6 and other muscle conditions 89 , Given its capacity to interrogate levels of both complex I and IV — and additional OXPHOS components — at a single muscle fibre level, we believe that the quadruple immunofluorescence assay can be applied to several areas of diagnostic and research activity in the laboratory to help investigate the role of mitochondrial biochemical defects The assay also shows promise as a powerful tool with which to investigate the mitochondrial pathological changes observed in ageing and other myopathies e.

Neurological symptoms are particularly common, and may be devastating in patients with mitochondrial disease, including sensorineural deafness, cerebellar ataxia, peripheral neuropathy, dementia, and epilepsy In recent years, a number of neuropathological studies have documented the characteristic features of neurodegeneration in patients with mitochondrial disease, and these have spurred the development of novel tools with which to understand the mechanisms underlying neural dysfunction and cell death.

Upon neuropathological investigation, the brains from patients with mitochondrial disease often show atrophy, cortical lesions, evidence of neuronal cell loss, and mitochondrial OXPHOS abnormalities in the remaining cells. Patients with the heteroplasmic m. Although focal necrotic changes associated with the m. Although the precise mechanisms are not known, the emergence of lesions in the brain reflect an acute process leading to rapid neuronal loss that can occur on the background of more chronic and protracted cell loss throughout the brain.

A Extensive cortical necrosis affecting the occipital, temporal and parietal lobes in a brain from a patient harbouring the m. B, C Microscopic analysis reveals atrophy, microvacuolation and severe neuronal loss in the frontal cortex of a patient with the m. The cerebellum is frequently involved in mitochondrial disease, with many patients developing cerebellar ataxia.

In conjunction, there is evidence of neuronal network remodelling with thickened dendritic arborizations, axonal torpedoes, and altered synaptic density , , There is a distinct lack of correlation between the severity of cell loss and the heteroplasmy level of mutated mtDNA in surviving neurons, suggesting that other factors must be important in determining cell loss Cerebellar pathology in patients with the m. B Extreme neuronal loss is seen microscopically, affecting Purkinje cells and granule cells in the cortex Cresyl fast violet staining.

It is not known why the mtDNA deletion preferentially affects oligodendrocytes. There is no evidence of protein accumulation within neurons, surviving neurons frequently show respiratory chain deficiency, including downregulation of complex I subunits, and there is a lack of correlation of cell loss and mtDNA heteroplasmy in remaining neurons.

Recently, a number of novel methods have been developed to provide further insights into potential mechanisms of neurodegeneration, particularly for understanding the early events leading to irreversible neuronal cell loss. This will enable a greater understanding of neuronal vulnerability in mitochondrial disease The recent development of induced pluripotent stem cell technology allows the cellular transfection of human patient fibroblasts with four key transcription factors to confer pluripotency.

These pluripotent cells can subsequently be differentiated into neurons and glial cells, and the effects of both the nuclear genome and mitochondrial genome can be investigated to determine disease mechanisms, efficacy of drug treatment, and cell replacement therapies , Developing an effective treatment for mitochondrial disease is an enormous challenge that is dependent on the integration of clinical understanding of disease progression, molecular genetic mechanisms, and neuropathological features in mitochondrial disease.

All authors contributed to the drafting of the manuscript and its critical revision for important intellectual content. The authors would like to thank Alexia Chrysostomou, Hannah Rosa and Amy Vincent for contributing images shown in the figures.

No conflicts of interest were declared. National Center for Biotechnology Information , U. The Journal of Pathology. J Pathol. Published online Nov 2.

Author information Article notes Copyright and License information Disclaimer. Robert W Taylor, Email: ku.

Corresponding author. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. This article has been cited by other articles in PMC.

What cause isolated huge cock gene

What cause isolated huge cock gene