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Two siblings presented similarly with congenital hypotonia, lactic acidosis, and failure to thrive. Later in childhood, the brother developed cystinuria and nephrolithiasis whereas the older sister suffered from cystinuria and chronic neurobehavioral disturbances. Biopsied muscle studies demonstrated deficient cytochrome c oxidase activities consistent with a mitochondrial disease. Whole exome sequencing (WES), however, revealed a homozygous 2p21 deletion involving two contiquous genes, SLC3A1 (deletion of exons 2‐10) and PREPL (deletion of exons 2‐14). The molecular findings were consistent with the hypotonia–cystinuria 2p21 deletion syndrome, presenting similarly in infancy with mitochondrial dysfunction but diverging later in childhood and displaying intrafamilial phenotypic variability.

Variation in the mitochondrial DNA (mtDNA) sequence is common in certain tumours. Two classes of cancer mtDNA variants can be identified: de novo mutations that act as 'inducers' of carcinogenesis and functional variants that act as 'adaptors', permitting cancer cells to thrive in different environments. These mtDNA variants have three origins: inherited variants, which run in families, somatic mutations arising within each cell or individual, and variants that are also associated with ancient mtDNA lineages (haplogroups) and are thought to permit adaptation to changing tissue or geographic environments. In addition to mtDNA sequence variation, mtDNA copy number and perhaps transfer of mtDNA sequences into the nucleus can contribute to certain cancers. Strong functional relevance of mtDNA variation has been demonstrated in oncocytoma and prostate cancer, while mtDNA variation has been reported in multiple other cancer types. Alterations in nuclear DNA-encoded mitochondrial genes have confirmed the importance of mitochondrial metabolism in cancer, affecting mitochondrial reactive oxygen species production, redox state and mitochondrial intermediates that act as substrates for chromatin-modifying enzymes. Hence, subtle changes in the mitochondrial genotype can have profound effects on the nucleus, as well as carcinogenesis and cancer progression.

Mitochondrial DNA (mtDNA) variant pathogenicity interpretation has special considerations given unique features of the mtDNA genome, including maternal inheritance, variant heteroplasmy, threshold effect, absence of splicing, and contextual effects of haplogroups. Currently there are insufficient standardized criteria for mtDNA variant assessment, which leads to inconsistencies in clinical variant pathogenicity reporting. An international working group of mtDNA experts was assembled within the Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium and obtained Expert Panel status from ClinGen. This group reviewed the 2015 American College of Medical Genetics (ACMG) and Association of Molecular Pathology (AMP) standards and guidelines that are widely used for clinical interpretation of DNA sequence variants and provided further specifications for additional and specific guidance related to mtDNA variant classification. These Expert Panel based consensus specifications allow for consistent consideration of the unique aspects of the mtDNA genome that directly influence variant assessment, including addressing mtDNA genome composition and structure, haplogroups and phylogeny, maternal inheritance, heteroplasmy, and functional analyses unique to mtDNA, as well specifications for utilization of mtDNA genomic databases and computational algorithms.

Defects in mitochondrial oxidative phosphorylation (OXPHOS) have been reported in COVID-19 patients, but the timing and organs affected vary among reports. Here, we reveal the dynamics of COVID-19 through transcription profiles in nasopharyngeal and autopsy samples from patients and infected rodent models. While mitochondrial bioenergetics is repressed in the viral nasopharyngeal portal of entry, it is up regulated in autopsy lung tissues from deceased patients. In most disease stages and organs, discrete OXPHOS functions are blocked by the virus, and this is countered by the host broadly up regulating unblocked OXPHOS functions. No such rebound is seen in autopsy heart, results in severe repression of genes across all OXPHOS modules. Hence, targeted enhancement of mitochondrial gene expression may mitigate the pathogenesis of COVID-19.One-Sentence SummaryCovid-19 is associated with targeted inhibition of mitochondrial gene transcription.

Neurodegenerative disorders that are triggered by injury typically have variable and unpredictable outcomes due to the complex and multifactorial cascade of events following the injury and during recovery. Hence, several factors beyond the initial injury likely contribute to the disease progression and pathology, and among these are genetic factors. Genetics is a recognized factor in determining the outcome of common neurodegenerative diseases. The role of mitochondrial genetics and function in traditional neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases, is well-established. Much less is known about mitochondrial genetics, however, regarding neurodegenerative diseases that result from injuries such as traumatic brain injury and ischaemic stroke. We discuss the potential role of mitochondrial DNA genetics in the progression and outcome of injury-related neurodegenerative diseases. We present a guide for understanding mitochondrial genetic variation, along with the nuances of quantifying mitochondrial DNA variation. Evidence supporting a role for mitochondrial DNA as a risk factor for neurodegenerative disease is also reviewed and examined. Further research into the impact of mitochondrial DNA on neurodegenerative disease resulting from injury will likely offer key insights into the genetic factors that determine the outcome of these diseases together with potential targets for treatment.

The growing number of next-generation sequencing (NGS) data presents a unique opportunity to study the combined impact of mitochondrial and nuclear-encoded genetic variation in complex disease. Mitochondrial DNA variants and in particular, heteroplasmic variants, are critical for determining human disease severity. While there are approaches for obtaining mitochondrial DNA variants from NGS data, these software do not account for the unique characteristics of mitochondrial genetics and can be inaccurate even for homoplasmic variants. We introduce MitoScape, a novel, big-data, software for extracting mitochondrial DNA sequences from NGS. MitoScape adopts a novel departure from other algorithms by using machine learning to model the unique characteristics of mitochondrial genetics. We also employ a novel approach of using rho-zero (mitochondrial DNA-depleted) data to model nuclear-encoded mitochondrial sequences. We showed that MitoScape produces accurate heteroplasmy estimates using gold-standard mitochondrial DNA data. We provide a comprehensive comparison of the most common tools for obtaining mtDNA variants from NGS and showed that MitoScape had superior performance to compared tools in every statistically category we compared, including false positives and false negatives. By applying MitoScape to common disease examples, we illustrate how MitoScape facilitates important heteroplasmy-disease association discoveries by expanding upon a reported association between hypertrophic cardiomyopathy and mitochondrial haplogroup T in men (adjusted p-value = 0.003). The improved accuracy of mitochondrial DNA variants produced by MitoScape will be instrumental in diagnosing disease in the context of personalized medicine and clinical diagnostics., Author summary Recent studies have highlighted the importance of mitochondrial DNA variation in both primary mitochondrial disease and complex, human pathology including COVID-19, and space-flight stress. The vast amount of existing, next-generation sequencing (NGS) data can be leveraged to interrogate both nuclear and mitochondrial DNA (mtDNA) sequence simultaneously, allowing for analysis of the interplay between mitochondrial and nuclear encoded genes in mitochondrial function. Identifying mtDNA sequence accurately is complicated by the presence of nuclear encoded mitochondrial sequences (NUMTs), which are homologous to mtDNA. Current software for analyzing mtDNA from NGS do not accurately model the unique characteristics of mitochondrial genetics. We introduce MitoScape, a novel, big-data, software which models mitochondrial genetics through machine learning to accurately identify mtDNA sequence from NGS data. MitoScape takes advantage of rho-zero cell data to model the characteristics of NUMTs. We show that MitoScape produces more accurate heteroplasmy estimates compared to published software. We provide an example of applying MitoScape in replicating an association between hypertrophic cardiomyopathy and mitochondrial haplogroup T in men. MitoScape is an important contribution to mitochondrial genomics allowing for accurate mtDNA variants, and the ability to tailor mtDNA analysis in different population and disease contexts, which is not available in other software.

Summary: MicroRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation that have a major impact on many diseases and provide an exciting avenue toward antiviral therapeutics. From patient transcriptomic data, we determined that a circulating miRNA, miR-2392, is directly involved with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) machinery during host infection. Specifically, we show that miR-2392 is key in driving downstream suppression of mitochondrial gene expression, increasing inflammation, glycolysis, and hypoxia, as well as promoting many symptoms associated with coronavirus disease 2019 (COVID-19) infection. We demonstrate that miR-2392 is present in the blood and urine of patients positive for COVID-19 but is not present in patients negative for COVID-19. These findings indicate the potential for developing a minimally invasive COVID-19 detection method. Lastly, using in vitro human and in vivo hamster models, we design a miRNA-based antiviral therapeutic that targets miR-2392, significantly reduces SARS-CoV-2 viability in hamsters, and may potentially inhibit a COVID-19 disease state in humans.

Alzheimer’s disease (AD), the most prevalent form of dementia, affects globally more than 30 million people suffering from cognitive deficits and neuropsychiatric symptoms. Substantial evidence for the involvement of mitochondrial dysfunction in the development and/or progression of AD has been shown in addition to the pathological hallmarks amyloid beta (Aβ) and tau. Still, the selective vulnerability and associated selective mitochondrial dysfunction cannot even be resolved to date. We aimed at optically quantifying mitochondrial function on a single-cell level in primary hippocampal neuron models of AD, unraveling differential involvement of cell and mitochondrial populations in amyloid precursor protein (APP)-associated mitochondrial dysfunction. NADH lifetime imaging is a highly sensitive marker-free method with high spatial resolution. However, deciphering cellular bioenergetics of complex cells like primary neurons has still not succeeded yet. To achieve this, we combined highly sensitive NADH lifetime imaging with respiratory inhibitor treatment, allowing characterization of mitochondrial function down to even the subcellular level in primary neurons. Measuring NADH lifetime of the same neuron before and after respiratory treatment reveals the metabolic delta, which can be taken as a surrogate for cellular redox capacity. Correlating NADH lifetime delta with overexpression strength of Aβ-related proteins on the single-cell level, we could verify the important role of intracellular Aβ-mediated mitochondrial toxicity. Subcellularly, we could demonstrate a higher respiration in neuronal somata in general than dendrites, but a similar impairment of somatic and dendritic mitochondria in our AD models. This illustrates the power of NADH lifetime imaging in revealing mitochondrial function on a single and even subcellular level and its potential to shed light into bioenergetic alterations in neuropsychiatric diseases and beyond.

Mitochondrial dysfunction has been implicated in the pathogenesis of primary open-angle glaucoma (POAG). However, the potential significance of mitochondrial DNA (mtDNA) haplogroups to POAG has not been evaluated in the overaffected African American population. To investigate the association of mtDNA haplogroups with POAG and its phenotypic characteristics, genotyping data from 4081 African American subjects (1919 cases and 2162 controls) was analyzed using 1293 positions on mtDNA. The overall frequency of mtDNA haplogroups in the Primary Open-Angle African American Glaucoma Genetics (POAAGG) study cohort was 37% L3, 29% L2, 21% L1, 4% L0, and 10% non-African haplogroups (non-L). When all haplogroups (L0, L1, L2, and non-L) were compared against theL3 reference group, after adjusting by age and principal component of ancestry, the non-L3 haplogroups showed higher risk of POAG (OR-1.19, p = 0.02), with a particularly strong association among males (OR = 1.41, p = 0.003). More specifically the non-L group was associated with higher POAG risk than the L3 haplogroup (OR = 1.77, p = 0.007, Bonferroni adjusted p = 0.027) and to the L3e (n = 256, OR = 1.92, p = 0.007, Bonferroni adjusted p = 0.029). No significant association was found when genders were analyzed together or in female only analysis. There were no significant differences in various POAG endophenotypes across mtDNA haplogroups. This study expands our knowledge of mitochondrial genetics and mtDNA haplogroup associations in African American POAG. Further work is needed to better understand the functional role of mtDNA polymorphisms and their interactions with nuclear genes that affect POAG.

The effect of cardiac arrest (CA) on cerebral transcriptomics and metabolomics is unknown. We previously demonstrated hemodynamic-directed CPR (HD-CPR) improves survival with favorable neurologic outcomes versus standard CPR (Std-CPR). We hypothesized HD-CPR would preserve the cerebral transcriptome and metabolome compared to Std-CPR.Randomized pre-clinical animal trial.Large animal resuscitation laboratory at an academic children's hospital.Four-week-old female piglets (8-11 kg).Pigs (1-month-old), three groups: 1) HD-CPR (compression depth to systolic BP 90 mmHg, vasopressors to coronary perfusion pressure 20 mmHg); 2) Std-CPR and 3) shams (no CPR). HD-CPR and Std-CPR underwent asphyxia, induced ventricular fibrillation, 10-20 min of CPR and post-resuscitation care. Primary outcomes at 24 h in cerebral cortex: 1) transcriptomic analysis (n = 4 per treatment arm, n = 8 sham) of 1727 genes using differential gene expression and 2) metabolomic analysis (n = 5 per group) of 27 metabolites using one-way ANOVA, post-hoc Tukey HSD.65 genes were differentially expressed between HD-CPR and Std-CPR and 72 genes between Std-CPR and sham, but only five differed between HD-CPR and sham. Std-CPR increased the concentration of five AA compared to HD-CPR and sham, including the branched chain amino acids (BCAA), but zero metabolites differed between HD-CPR and sham.In cerebral cortex 24 h post CA, Std-CPR resulted in a different transcriptome and metabolome compared with either HD-CPR or sham. HD-CPR preserves the transcriptome and metabolome, and is neuroprotective. Global molecular analyses may be a novel method to assess efficacy of clinical interventions and identify therapeutic targets.IAC 16-001023.

MicroRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation that have a major impact on many diseases and provide an exciting avenue toward antiviral therapeutics. From patient transcriptomic data, we determined that a circulating miRNA, miR-2392, is directly involved with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) machinery during host infection. Specifically, we show that miR-2392 is key in driving downstream suppression of mitochondrial gene expression, increasing inflammation, glycolysis, and hypoxia, as well as promoting many symptoms associated with coronavirus disease 2019 (COVID-19) infection. We demonstrate that miR-2392 is present in the blood and urine of patients positive for COVID-19 but is not present in patients negative for COVID-19. These findings indicate the potential for developing a minimally invasive COVID-19 detection method. Lastly, using in vitro human and in vivo hamster models, we design a miRNA-based antiviral therapeutic that targets miR-2392, significantly reduces SARS-CoV-2 viability in hamsters, and may potentially inhibit a COVID-19 disease state in humans., Graphical abstract, McDonald et al. uncover a role of a circulating microRNA, miR-2392, as a potential biomarker for COVID-19 and begin development of a potential COVID-19 therapeutic and antiviral to inhibit miR-2392.

Variation in the mitochondrial DNA (mtDNA) sequence is common in certain tumours. Two classes of cancer mtDNA variants can be identified: de novo mutations that act as 'inducers' of carcinogenesis and functional variants that act as 'adaptors', permitting cancer cells to thrive in different environments. These mtDNA variants have three origins: inherited variants, which run in families, somatic mutations arising within each cell or individual, and variants that are also associated with ancient mtDNA lineages (haplogroups) and are thought to permit adaptation to changing tissue or geographic environments. In addition to mtDNA sequence variation, mtDNA copy number and perhaps transfer of mtDNA sequences into the nucleus can contribute to certain cancers. Strong functional relevance of mtDNA variation has been demonstrated in oncocytoma and prostate cancer, while mtDNA variation has been reported in multiple other cancer types. Alterations in nuclear DNA-encoded mitochondrial genes have confirmed the importance of mitochondrial metabolism in cancer, affecting mitochondrial reactive oxygen species production, redox state and mitochondrial intermediates that act as substrates for chromatin-modifying enzymes. Hence, subtle changes in the mitochondrial genotype can have profound effects on the nucleus, as well as carcinogenesis and cancer progression.

Alzheimer’s disease (AD), the most prevalent form of dementia, affects globally more than 30 million people suffering from cognitive deficits and neuropsychiatric symptoms. Substantial evidence for the involvement of mitochondrial dysfunction in the development and/or progression of AD has been shown in addition to the pathological hallmarks amyloid beta (Aβ) and tau. Still, the selective vulnerability and associated selective mitochondrial dysfunction cannot even be resolved to date. We aimed at optically quantifying mitochondrial function on a single-cell level in primary hippocampal neuron models of AD, unraveling differential involvement of cell and mitochondrial populations in amyloid precursor protein (APP)-associated mitochondrial dysfunction. NADH lifetime imaging is a highly sensitive marker-free method with high spatial resolution. However, deciphering cellular bioenergetics of complex cells like primary neurons has still not succeeded yet. To achieve this, we combined highly sensitive NADH lifetime imaging with respiratory inhibitor treatment, allowing characterization of mitochondrial function down to even the subcellular level in primary neurons. Measuring NADH lifetime of the same neuron before and after respiratory treatment reveals the metabolic delta, which can be taken as a surrogate for cellular redox capacity. Correlating NADH lifetime delta with overexpression strength of Aβ-related proteins on the single-cell level, we could verify the important role of intracellular Aβ-mediated mitochondrial toxicity. Subcellularly, we could demonstrate a higher respiration in neuronal somata in general than dendrites, but a similar impairment of somatic and dendritic mitochondria in our AD models. This illustrates the power of NADH lifetime imaging in revealing mitochondrial function on a single and even subcellular level and its potential to shed light into bioenergetic alterations in neuropsychiatric diseases and beyond.

Spaceflight is known to impose changes on human physiology with unknown molecular etiologies. To reveal these causes, we used a multi-omics, systems biology analytical approach using biomedical profiles from fifty-nine astronauts and data from NASA's GeneLab derived from hundreds of samples flown in space to determine transcriptomic, proteomic, metabolomic, and epigenetic responses to spaceflight. Overall pathway analyses on the multi-omics datasets showed significant enrichment for mitochondrial processes, as well as innate immunity, chronic inflammation, cell cycle, circadian rhythm, and olfactory functions. Importantly, NASA's Twin Study provided a platform to confirm several of our principal findings. Evidence of altered mitochondrial function and DNA damage was also found in the urine and blood metabolic data compiled from the astronaut cohort and NASA Twin Study data, indicating mitochondrial stress as a consistent phenotype of spaceflight.

Objective In individuals with mitochondrial disease, respiratory viral infection can result in metabolic decompensation with mitochondrial hepatopathy. Here, we used a mouse model of liver-specific Complex IV deficiency to study hepatic allostasis during respiratory viral infection. Methods Mice with hepatic cytochrome c oxidase deficiency (LivCox10−/−) were infected with aerosolized influenza, A/PR/8 (PR8), and euthanized on day five after infection following three days of symptoms. This time course is marked by a peak in inflammatory cytokines and mimics the timing of a common clinical scenario in which caregivers may first attempt to manage the illness at home before seeking medical attention. Metabolic decompensation and mitochondrial hepatopathy in mice were characterized by serum hepatic testing, histology, electron microscopy, biochemistry, metabolomics, and bioenergetic profiling. Results Following influenza infection, LivCox10−/− mice displayed marked liver disease including hepatitis, enlarged mitochondria with cristae loss, and hepatic steatosis. This pathophysiology was associated with viremia. Primary hepatocytes from LivCox10−/− mice cocultured with WT Kupffer cells in the presence of PR8 showed enhanced lipid accumulation. Treatment of hepatocytes with recombinant TNFα implicated Kupffer cell-derived TNFα as a precipitant of steatosis in LivCox10−/− mice. Eliminating Kupffer cells or blocking TNFα in vivo during influenza infection mitigated the steatosis and mitochondrial morphologic changes. Conclusions Taken together, our data shift the narrative of metabolic decompensation in mitochondrial hepatopathy beyond the bioenergetic costs of infection to include an underlying susceptibility to immune-mediated damage. Moreover, our work suggests that immune modulation during metabolic decompensation in mitochondrial disease represents a future viable treatment strategy needing further exploration., HIGHLIGHTS • Influenza infection leads to worsening mitochondrial function and steatohepatitis in a model of mitochondrial hepatopathy. • Kupffer cells may mediate this damage by the uptake of influenza virus and the secretion of TNFa. • Hepatocytes affected by mitochondrial disease have a lower threshold for immune mediated toxicity by TNFa. • Modulating the immune response leads to an improvement in the phenotype.

Mitochondrial dysfunction has repeatedly been reported associated with type 2 diabetes mellitus (T2DM) and metabolic syndrome (MS), as have mitochondrial DNA (mtDNA) tRNA and duplication mutations and mtDNA haplogroup lineages. We identified 19 Taiwanese T2DM and MS pedigrees from Taiwan, with putative matrilineal transmission, one of which harbored the pathogenic mtDNA tRNALeu(UUR) nucleotide (nt) 3243A>G mutation on the N9a3 haplogroup background. We then recruited three independent Taiwanese cohorts, two from Taipei (N = 498, mean age 52 and N = 1002, mean age 44) and one from a non-urban environment (N = 501, mean age 57). All three cohorts were assessed for an array of metabolic parameters, their mtDNA haplogroups determined, and the haplogroups correlated with T2DM/MS phenotypes. Logistic regression analysis revealed that mtDNA haplogroups D5, F4, and N9a conferred T2DM protection, while haplogroups F4 and N9a were risk factors for hypertension (HTN), and F4 was a risk factor for obesity (OB). Additionally, the 5263C>T (ND2 A165V) variant commonly associated with F4 was associated with hypertension (HTN). Cybrids were prepared with macro-haplogroup N (defined by variants m.ND3 10398A (114T) and m.ATP6 8701A (59T)) haplogroups B4 and F1 mtDNAs and from macro-haplogroup M (variants m.ND3 10398G (114A) and m.ATP6 8701G (59A)) haplogroup M9 mtDNAs. Additionally, haplogroup B4 and F1 cybrids were prepared with and without the mtDNA variant in ND1 3394T>C (Y30H) reported to be associated with T2DM. Assay of mitochondria complex I in these cybrids revealed that macro-haplogroup N cybrids had lower activity than M cybrids, that haplogroup F cybrids had lower activity than B4 cybrids, and that the ND1 3394T>C (Y30H) variant reduced complex I on both the B4 and F1 background but with very different cumulative effects. These data support the hypothesis that functional mtDNA variants may contribute to the risk of developing T2DM and MS.

Changes in the gut microbiota and the mitochondrial genome are both linked with the development of disease. To investigate why, we examined the gut microbiota of mice harboring various mutations in genes that alter mitochondrial function. These studies revealed that mitochondrial genetic variations altered the composition of the gut microbiota community. In cross-fostering studies, we found that although the initial microbiota community of newborn mice was that obtained from the nursing mother, the microbiota community progressed toward that characteristic of the microbiome of unfostered pups of the same genotype within 2 months. Analysis of the mitochondrial DNA variants associated with altered gut microbiota suggested that microbiome species diversity correlated with host reactive oxygen species (ROS) production. To determine whether the abundance of ROS could alter the gut microbiota, mice were aged, treated with N-acetylcysteine, or engineered to express the ROS scavenger catalase specifically within the mitochondria. All three conditions altered the microbiota from that initially established. Thus, these data suggest that the mitochondrial genotype modulates both ROS production and the species diversity of the gut microbiome, implying that the connection between the gut microbiome and common disease phenotypes might be due to underlying changes in mitochondrial function.

Significance Mitochondrial DNA (mtDNA) mutations have been associated with common metabolic and degenerative disease phenotypes, implying a bioenergetic etiology for these diseases. For example, the mtDNA tRNALeu(UUR) m.3243A > G mutation manifests as diabetes, neurodegenerative disease, or lethal pediatric disease, depending on the percentage of mutant mtDNAs within the cell (heteroplasmy). Cultured cybrid cell lines harboring 3243G heteroplasmy levels corresponding to the different clinical phenotypes have distinct transcriptional profiles. Exhaustive metabolomic and histone posttranscriptional modification analysis of these 3243G cybrids revealed that changes in mtDNA heteroplasmy cause changes in mitochondrial intermediates and redox state, which result in distinctive histone modification changes. Thus, changes in the mitochondrial genotype change mitochondrial metabolism, which change the epigenome and transcriptome, which induce distinct clinical phenotypes., Diseases associated with mitochondrial DNA (mtDNA) mutations are highly variable in phenotype, in large part because of differences in the percentage of normal and mutant mtDNAs (heteroplasmy) present within the cell. For example, increasing heteroplasmy levels of the mtDNA tRNALeu(UUR) nucleotide (nt) 3243A > G mutation result successively in diabetes, neuromuscular degenerative disease, and perinatal lethality. These phenotypes are associated with differences in mitochondrial function and nuclear DNA (nDNA) gene expression, which are recapitulated in cybrid cell lines with different percentages of m.3243G mutant mtDNAs. Using metabolic tracing, histone mass spectrometry, and NADH fluorescence lifetime imaging microscopy in these cells, we now show that increasing levels of this single mtDNA mutation cause profound changes in the nuclear epigenome. At high heteroplasmy, mitochondrially derived acetyl-CoA levels decrease causing decreased histone H4 acetylation, with glutamine-derived acetyl-CoA compensating when glucose-derived acetyl-CoA is limiting. In contrast, α-ketoglutarate levels increase at midlevel heteroplasmy and are inversely correlated with histone H3 methylation. Inhibition of mitochondrial protein synthesis induces acetylation and methylation changes, and restoration of mitochondrial function reverses these effects. mtDNA heteroplasmy also affects mitochondrial NAD+/NADH ratio, which correlates with nuclear histone acetylation, whereas nuclear NAD+/NADH ratio correlates with changes in nDNA and mtDNA transcription. Thus, mutations in the mtDNA cause distinct metabolic and epigenomic changes at different heteroplasmy levels, potentially explaining transcriptional and phenotypic variability of mitochondrial disease.

Summary Increasing evidence suggests that regulation of heterochromatin at the nuclear envelope underlies metabolic disease susceptibility and age‐dependent metabolic changes, but the mechanism is unknown. Here, we profile lamina‐associated domains (LADs) using lamin B1 ChIP‐Seq in young and old hepatocytes and find that, although lamin B1 resides at a large fraction of domains at both ages, a third of lamin B1‐associated regions are bound exclusively at each age in vivo. Regions occupied by lamin B1 solely in young livers are enriched for the forkhead motif, bound by Foxa pioneer factors. We also show that Foxa2 binds more sites in Zmpste24 mutant mice, a progeroid laminopathy model, similar to increased Foxa2 occupancy in old livers. Aged and Zmpste24‐deficient livers share several features, including nuclear lamina abnormalities, increased Foxa2 binding, de‐repression of PPAR‐ and LXR‐dependent gene expression, and fatty liver. In old livers, additional Foxa2 binding is correlated to loss of lamin B1 and heterochromatin (H3K9me3 occupancy) at these loci. Our observations suggest that changes at the nuclear lamina are linked to altered Foxa2 binding, enabling opening of chromatin and de‐repression of genes encoding lipid synthesis and storage targets that contribute to etiology of hepatic steatosis.

In response to infection, patients with inborn errors of metabolism may develop a functional deterioration termed metabolic decompensation. The biochemical hallmarks of this disruption of metabolic homeostasis are disease specific and may include acidosis, hyperammonemia or hypoglycemia. In a model system previously published by our group, we noted that during influenza infection, mice displayed a depression in hepatic mitochondrial enzymes involved in nitrogen metabolism. Based on these findings, we hypothesized that this normal adaptation may extend to other metabolic pathways, and as such, may impact various inborn errors of metabolism. Since the liver is a critical organ in inborn errors of metabolism, we carried out untargeted metabolomic profiling of livers using mass spectrometry in C57Bl/6 mice infected with influenza to characterize metabolic adaptation. Pathway analysis of metabolomic data revealed reductions in CoA synthesis, and long chain fatty acyl CoA and carnitine species. These metabolic adaptations coincided with a depression in hepatic long chain β-oxidation mRNA and protein. To our surprise, the metabolic changes observed occurred in conjunction with a hepatic innate immune response, as demonstrated by transcriptional profiling and flow cytometry. By employing an immunomodulation strategy to deplete Kupffer cells, we were able to improve the expression of multiple genes involved in β-oxidation. Based on these findings, we are the first to suggest that the role of the liver as an immunologic organ is central in the pathophysiology of hepatic metabolic decompensation in inborn errors of metabolism due to respiratory viral infection.

Next-generation sequencing provides the opportunity to practice predictive medicine based on identified variants. Putative loss-of-function (pLOF) variants are common in genomes and understanding their contribution to disease is critical for predictive medicine. To this end, we characterized the consequences of pLOF variants in an exome cohort by iterative phenotyping. Exome data were generated on 951 participants from the ClinSeq cohort and filtered for pLOF variants in genes likely to cause a phenotype in heterozygotes. 103 of 951 exomes had such a pLOF variant and 79 participants were evaluated. Of those 79, 34 had findings or family histories that could be attributed to the variant (28 variants in 18 genes), 2 had indeterminate findings (2 variants in 2 genes), and 43 had no findings or a negative family history for the trait (34 variants in 28 genes). The presence of a phenotype was correlated with two mutation attributes: prior report of pathogenicity for the variant (p = 0.0001) and prior report of other mutations in the same exon (p = 0.0001). We conclude that 1/30 unselected individuals harbor a pLOF mutation associated with a phenotype either in themselves or their family. This is more common than has been assumed and has implications for the setting of prior probabilities of affection status for predictive medicine.

Coronary artery calcification (CAC) is a heritable and definitive morphologic marker of atherosclerosis that strongly predicts risk for future cardiovascular events. To search for genes involved in CAC, we used an integrative transcriptomic, genomic, and protein expression strategy by using next-generation DNA sequencing in the discovery phase with follow-up studies using traditional molecular biology and histopathology techniques. RNA sequencing of peripheral blood from a discovery set of CAC cases and controls was used to identify dysregulated genes, which were validated by ClinSeq and Framingham Heart Study data. Only a single gene, TREML4, was upregulated in CAC cases in both studies. Further examination showed that rs2803496 was a TREML4 cis-eQTL and that the minor allele at this locus conferred up to a 6.5-fold increased relative risk of CAC. We characterized human TREML4 and demonstrated by immunohistochemical techniques that it is localized in macrophages surrounding the necrotic core of coronary plaques complicated by calcification (but not in arteries with less advanced disease). Finally, we determined by von Kossa staining that TREML4 colocalizes with areas of microcalcification within coronary plaques. Overall, we present integrative RNA, DNA, and protein evidence implicating TREML4 in coronary artery calcification. Our findings connect multimodal genomics data with a commonly used clinical marker of cardiovascular disease.

To the editor Proteus syndrome (PS) is characterized by progressive, mosaic, segmental overgrowth and occurs sporadically (Biesecker 2001; 2006). The mosaic nature and sporadic occurrence with lack of familial transmission led to the hypothesis that PS is caused by a post-zygotic somatic mutation, which was confirmed with the discovery of a mosaic activating c.49G>A, p.Glu17Lys AKT1 mutation (Lindhurst et al. 2011). To date, all patients who meet the clinical diagnostic criteria for PS and have been tested have this mutation (Lindhurst and Biesecker, unpublished results). While any organ or tissue can be affected, skeletal overgrowth and dermatologic lesions are the most common manifestations of PS (Turner et al. 2004; Beachkofsky et al. 2010). Cerebriform connective tissue nevi (CCTN) are a highly specific and common lesion in patients with PS (Biesecker et al. 2001; Nguyen et al. 2004). These lesions are very firm and contain deep sulci that resemble the brain, for which the lesion is named. Histology sections of CCTN show massively expanded dermis filled with thick collagen bundles (Figure 1d-f) (McCuaig et al. 2012). Epidermal nevi (EN) can be non-syndromic or occur as part of several syndromes including PS (Happle 2010). The keratinocytic EN found in PS have a rough surface, are dark in color, usually follow the lines of Blaschko, and exhibit epidermal hyperkeratosis, papillomatosis, and acanthosis (Figure 1a-c) (Nguyen et al. 2004). EN are generally noticed in the first year of life and are stable in extent whereas CCTN grow progressively after first appearing later in the first or second year (Twede et al. 2005). Figure 1 Representative examples of an EN and CCTN. Panel a shows the rough surface of the linear EN on the infraaxillary vault in patient 101. Hematoxylin and eosin stain (b, scale bar = 100 μm; c, scale bar = 50 μm) of a skin biopsy from the ... It is unknown which cells determine the formation of these lesions. Based on the histology, we hypothesized that CCTN were generated by AKT1 p.Glu17Lys in the dermis and that EN were generated by this mutation in the epidermis. To test this hypothesis, we isolated fibroblasts and keratinocytes from lesional (CCTN or EN) and non-lesional (“normal”) skin samples and measured the level of the mutant allele in each cell type. Skin samples were collected during surgical procedures or by punch biopsies from patients with PS under an IRB-approved protocol. The epidermis was separated from the dermis by treatment with dispase and keratinocyte and fibroblast cultures were established using standard protocols (Aasen and Belmonte 2010). A single keratinocyte culture was established from each biopsy. Fibroblasts were allowed to grow out of the dermal tissue until the dish was confluent. The dermal tissue was then transferred to a new dish to allow another fibroblast culture to be established from that same tissue. The number of fibroblast cultures established from a piece of dermis ranged from one to six. DNA was isolated from cultured cells harvested between passages one and four, and the mutation level was assayed using a PCR-based restriction fragment length polymorphism (RFLP) assay as described (Lindhurst et al. 2011). This assay has a lower limit of sensitivity of 0.5%. Each DNA preparation was tested at least twice and the values were averaged. In ten of the 20 samples, DNA was also isolated from the dermal tissue used to establish the fibroblast cultures after the final transfer. Seven CCTN biopsies were obtained from the feet of three patients (Table S1). The mutant allele was not detected in CCTN keratinocyte cultures whereas the mutation level from the CCTN fibroblast cultures was 9-32%. In the dermal tissue post-culturing, the mutation level was 12-21% (Figure 2). Figure 2 Percentage of AKT1 c.49G>A, p.Glu17Lys mutation in epidermal and dermal cells and tissue. One keratinocyte culture (left panel) was established from each epidermal sample. Mutation percentages are indicated by the blue circles. Multiple fibroblast ... Nine EN samples were obtained from the hand, trunk, or neck from seven patients (Table S1). The mutation level in the keratinocyte cultures was 0-44% whereas the mutation level in the fibroblast cultures was 0-38%. The mutation level in the cultured dermal tissue was 9-25%. Interestingly, the two samples with the highest levels of mutation in the keratinocytes (101EN1 and 78EN2) had the lowest mutation percentages in dermal cells or tissue. Detection of the mutant allele in the EN keratinocytes is consistent with the identification of the AKT1 p.Glu17Lys mutation in skin scrapings of PS epidermal nevi (Wieland et al. 2013). Four biopsies from two patients were obtained from tissue that appeared normal by gross examination but was from an area that was far removed from lesional tissue (designated as unaffected) or bordered a CCTN (designated as unknown) (Table S1). No evidence of the mutant allele was present in the keratinocyte cultures. The mean mutation level in the fibroblast cultures was 6-27%. We conclude that the AKT1 p.Glu17Lys activating mutation in keratinocytes is a key determinant of EN formation. Mutations in the FGFR3, PIK3CA, and RAS genes have been identified in epidermal cells of EN not associated with PS, supporting this hypothesis (Hafner et al. 2006; 2007; 2012). Histopathologically, these keratinocytic EN are strikingly similar to those found in PS and it should be noted that PIK3CA encodes the catalytic subunit of the PI3K complex which functions upstream of AKT in the same signaling pathway. In contrast, there was no correlation of the mutation levels in fibroblasts or cultured dermal tissue with the clinical lesion type. The inability to detect an AKT1 mutation in two of the EN keratinocyte cultures could be due to a sampling artifact if the mutant cells were not uniformly distributed throughout the lesion and the sample was from an area with low-level mosaicism. It seems unlikely that the lack of mutant keratinocytes in some EN indicates that these lesions form as a result of signaling from mutant cells in the dermis, since even organoid EN, such as nevus sebaceous have been shown to result from mutant cells in the epidermis. (Groesser et al. 2012) Mutant cells were found in dermal fibroblasts of both CCTN and normal-appearing skin, suggesting that the presence of mutant cells in the dermis is necessary but not sufficient to drive the formation of CCTN. The propensity of CCTNs to develop on soles and palms in PS may reflect a greater role of AKT1 in postnatal regulation of tissue architecture at these sites than elsewhere on the skin.

Background— Massively parallel sequencing to identify rare variants is widely practiced in medical research and in the clinic. Genome and exome sequencing can identify the genetic cause of a disease (primary results), but it can also identify pathogenic variants underlying diseases that are not being sought (secondary or incidental results). A major controversy has developed surrounding the return of secondary results to research participants. We have piloted a method to analyze exomes to identify participants at risk for cardiac arrhythmias, cardiomyopathies, or sudden death. Methods and Results— Exome sequencing was performed on 870 participants not selected for arrhythmia, cardiomyopathy, or a family history of sudden death. Exome data from 22 cardiac arrhythmia- and 41 cardiomyopathy-associated genes were analyzed using an algorithm that filtered results on genotype quality, frequency, and database information. We identified 1367 variants in the cardiomyopathy genes and 360 variants in the arrhythmia genes. Six participants had pathogenic variants associated with dilated cardiomyopathy (n=1), hypertrophic cardiomyopathy (n=2), left ventricular noncompaction (n=1), or long-QT syndrome (n=2). Two of these participants had evidence of cardiomyopathy and 1 had left ventricular noncompaction on echocardiogram. Three participants with likely pathogenic variants had prolonged QTc. Family history included unexplained sudden death among relatives. Conclusions— Approximately 0.5% of participants in this study had pathogenic variants in known cardiomyopathy or arrhythmia genes. This high frequency may be due to self-selection, false positives, or underestimation of the prevalence of these conditions. We conclude that clinically important cardiomyopathy and dysrhythmia secondary variants can be identified in unselected exomes.

The aim of the study was to assess exome data for preemptive pharmacogenetic screening for 203 clinically relevant pharmacogenetic variant positions from the Pharmacogenomics Knowledgebase and Clinical Pharmacogenetics Implementation Consortium and identify copy-number variants (CNVs) in CYP2D6. We examined the coverage and genotype quality of 203 pharmacogenetic variant positions in 973 exomes compared with five genomes and with five genotyping chip data sets. Then, we determined the agreement of exome and chip genotypes by evaluating concordance in a three-way comparison of exome, genome, and chip-based genotyping at 1,929 variant positions in five individuals. Finally, we evaluated the utility of exomes for detecting CYP2D6 CNVs. For 5 individuals examined for 203 pharmacogenetic variants (5 × 203 = 1,015), 998/1,015 were identified by genome, 849/1,015 were identified by exome, and 295/1,015 by genotyping chip. Thirty-six pharmacogenetic star allele variants with moderate to strong Clinical Pharmacogenetics Implementation Consortium (CPIC) therapeutic recommendations were identified in 973 exomes. Exomes had high (98%) genotype concordance with chip-based genotyping. CYP2D6 CNVs were identified in 57/973 exomes. Exomes outperformed the current chip-based assay in detecting more important pharmacogenetic variant positions and CYP2D6 CNVs for preemptive pharmacogenetic screening. Tools should be developed to derive pharmacogenetic variants from exomes. Genet Med 19 3, 357–361.

Despite the presence of a cytosolic fatty acid synthesis pathway, mitochondria have retained their own means of creating fatty acids via the mitochondrial fatty acid synthesis (mtFASII) pathway. The reason for its conservation has not yet been elucidated. Therefore, to better understand the role of mtFASII in the cell, we used thin layer chromatography to characterize the contribution of the mtFASII pathway to the fatty acid composition of selected mitochondrial lipids. Next, we performed metabolomic analysis on HeLa cells in which the mtFASII pathway was either hypofunctional (through knockdown of mitochondrial acyl carrier protein, ACP) or hyperfunctional (through overexpression of mitochondrial enoyl-CoA reductase, MECR). Our results indicate that the mtFASII pathway contributes little to the fatty acid composition of mitochondrial lipid species examined. Additionally, loss of mtFASII function results in changes in biochemical pathways suggesting alterations in glucose utilization and redox state. Interestingly, levels of bioactive lipids, including lysophospholipids and sphingolipids, directly correlate with mtFASII function, indicating that mtFASII may be involved in the regulation of bioactive lipid levels. Regulation of bioactive lipid levels by mtFASII implicates the pathway as a mediator of intracellular signaling.

Genome- and exome-sequencing costs are continuing to fall, and many individuals are undergoing these assessments as research participants and patients. The issue of secondary (so-called incidental) findings in exome analysis is controversial, and data are needed on methods of detection and their frequency. We piloted secondary variant detection by analyzing exomes for mutations in cancer-susceptibility syndromes in subjects ascertained for atherosclerosis phenotypes. We performed exome sequencing on 572 ClinSeq participants, and in 37 genes, we interpreted variants that cause high-penetrance cancer syndromes by using an algorithm that filtered results on the basis of mutation type, quality, and frequency and that filtered mutation-database entries on the basis of defined categories of causation. We identified 454 sequence variants that differed from the human reference. Exclusions were made on the basis of sequence quality (26 variants) and high frequency in the cohort (77 variants) or dbSNP (17 variants), leaving 334 variants of potential clinical importance. These were further filtered on the basis of curation of literature reports. Seven participants, four of whom were of Ashkenazi Jewish descent and three of whom did not meet family-history-based referral criteria, had deleterious BRCA1 or BRCA2 mutations. One participant had a deleterious SDHC mutation, which causes paragangliomas. Exome sequencing, coupled with multidisciplinary interpretation, detected clinically important mutations in cancer-susceptibility genes; four of such mutations were in individuals without a significant family history of disease. We conclude that secondary variants of high clinical importance will be detected at an appreciable frequency in exomes, and we suggest that priority be given to the development of more efficient modes of interpretation with trials in larger patient groups.

Purpose: To determine whether mitochondrial DNA haplogroups or rare variants associate with primary open-angle glaucoma in subjects of European descent. Methods: A case-control comparison of age- and sex-matched cohorts of 90 primary open-angle glaucoma patients and 95 population controls. Full mitochondrial DNA sequences from peripheral blood were generated by next-generation sequencing and compared to the revised Cambridge Reference Sequence to define mitochondrial haplogroups and variants. Results: Most subjects were of the major European haplogroups H, J, K, U, and T. Logistic regression analysis showed haplogroup U to be significantly underrepresented in male primary open-angle glaucoma subjects (odds ratio 0.25; 95% confidence interval [CI] 0.09-0.67; P = 0.007; Bonferroni multiple testing P = 0.022). Variants in the mitochondrial DNA gene MT-ND2 were overrepresented in the control group (P = 0.005; Bonferroni multiple testing correction P = 0.015). Conclusions: Mitochondrial DNA ancestral lineages modulate the risk for primary open-angle glaucoma in populations of European descent. Haplogroup U and rare variants in the mitochondrial DNA-encoded MT-ND2 gene may be protective against primary open-angle glaucoma. Larger studies are warranted to explore haplogroup associations with disease risk in different ethnic groups and define biomarkers of primary open-angle glaucoma endophenotypes to target therapeutic strategies.

In eukaryotes, U1 small nuclear ribonucleoprotein (snRNP) forms spliceosomes in equal stoichiometry with U2, U4, U5 and U6 snRNPs; however, its abundance in human far exceeds that of the other snRNPs. Here we used antisense morpholino oligonucleotide to U1 snRNA to achieve functional U1 snRNP knockdown in HeLa cells, and identified accumulated unspliced pre-mRNAs by genomic tiling microarrays. In addition to inhibiting splicing, U1 snRNP knockdown caused premature cleavage and polyadenylation in numerous pre-mRNAs at cryptic polyadenylation signals, frequently in introns near (

Gene duplication is integral to evolution, providing novel opportunities for organisms to diversify in function. One fundamental pathway of functional diversification among initially redundant gene copies, or paralogs, is via alterations in their expression patterns. Although the mechanisms underlying expression divergence are not completely understood, transcription factor binding sites and nucleosome occupancy are known to play a significant role in the process. Previous attempts to detect genomic variations mediating expression divergence in orthologs have had limited success for two primary reasons. First, it is inherently challenging to compare expressions among orthologs due to variable trans-acting effects and second, previous studies have quantified expression divergence in terms of an overall similarity of expression profiles across multiple samples, thereby obscuring condition-specific expression changes. Moreover, the inherently inter-correlated expressions among homologs present statistical challenges, not adequately addressed in many previous studies. Using rigorous statistical tests, here we characterize the relationship between cis element divergence and condition-specific expression divergence among paralogous genes in Saccharomyces cerevisiae. In particular, among all combinations of gene family and TFs analyzed, we found a significant correlation between TF binding and the condition-specific expression patterns in over 20% of the cases. In addition, incorporating nucleosome occupancy reveals several additional correlations. For instance, our results suggest that GAL4 binding plays a major role in the expression divergence of the genes in the sugar transporter family. Our work presents a novel means of investigating the cis regulatory changes potentially mediating expression divergence in paralogous gene families under specific conditions.

A transcriptional module (TM) is a collection of transcription factors (TF) that as a group, co-regulate multiple, functionally related genes. The task of identifying TMs poses an important biological challenge. Since TFs belong to evolutionarily and structurally related families, TF family members often bind to similar DNA motifs and can confound sequence-based approaches to TM identification. A previous approach to TM detection addresses this issue by pre-selecting a single representative from each TF family. One problem with this approach is that closely related transcription factors can still target sufficiently distinct genes in a biologically meaningful way, and thus, pre-selecting a single family representative may in principle miss certain TMs. Here we report a method-TREMOR (Transcriptional Regulatory Module Retriever). This method uses the Mahalanobis distance to assess the validity of a TM and automatically incorporates the inter-TF binding similarity without resorting to pre-selecting family representatives. The application of TREMOR on human muscle-specific, liver-specific and cell-cycle-related genes reveals TFs and TMs that were validated from literature and also reveals additional related genes.

This paper solves the problem of estimation of the parameters of a hyperexponential density and presents a practical application of the solution in sensor networks. Two novel algorithms for estimating the parameters of the density are formulated. In the first algorithm, an objective function is constructed as a function of the unknown component means and an estimate of the cumulative distribution function (cdf) of the hyperexponential density. The component means are obtained by minimizing this objective function, using quasi-Newtonian techniques. The mixing probabilities are then computed using these known means and linear least squares analysis. In the second algorithm, an objective function of the unknown component means, mixing probabilities, and an estimate of the cdf is constructed. All the 2M parameters are computed by minimizing this objective function, using quasi-Newtonian techniques. The developed algorithms are also compared to the basic EM algorithm, and their relative advantages over the EM algorithm are discussed. The algorithms developed are computationally efficient and easily implemented, and hence, are suitable for low-power and sensor nodes with limited storage and computational capacity. In particular, we demonstrate how the structure of these algorithms may be exploited to be effectively utilized in practical situations, and are hence ideal for sensor networks.

Ornithine transcarbamylase deficiency (OTCD, OMIM# 311250) is an inherited X-linked urea cycle disorder that is characterized by hyperammonemia and orotic aciduria. In this report, we describe a new animal model of OTCD caused by a spontaneous mutation in the mouse Otc gene (c.240T>A, p.K80N). This transversion in exon 3 of ornithine transcarbamylase leads to normal levels of mRNA with low levels of mature protein and is homologous to a mutation that has also been described in a single patient affected with late-onset OTCD. With higher residual enzyme activity, spf-J were found to have normal plasma ammonia and orotate. Baseline plasma amino acid profiles were consistent with mild OTCD: elevated glutamine, and lower citrulline and arginine. In contrast to WT, spf-J displayed baseline elevations in cerebral amino acids with depletion following immune challenge with polyinosinic:polycytidylic acid. Our results indicate that the mild spf-J mutation constitutes a new mouse model that is suitable for mechanistic studies of mild OTCD and the exploration of cerebral pathophysiology during acute decompensation that characterizes proximal urea cycle dysfunction in humans.

Estimation of channel and data characteristics by the receiver is important in adaptive wireless transmission protocols and in cognitive radio. This paper formulates the estimation problem with the help of an illustrative example from the IEEE 802.11a OFDM standard. The problem reduces to the estimation of the common component variance and mixing probabilities in a finite Gaussian mixture, with known values for component means. Using the known component means, μ1, ... , μ M , a set of non-linear transformations, $${\sinh \mu_i x}$$ and $${\cosh \mu_i x}$$ of the data (mixture random variable X) are used to develop convergent and computationally efficient estimators for both the noise variance and the vector of symbol probabilities. The estimation equations can be implemented recursively or with a batch processing algorithm. Asymptotic variances of the estimates and the Cramer–Rao minimum variance bounds are derived. The estimates converge to true unknowns even when the sequences of noise and data symbols are dependent sequences. The OFDM example is simulated with parameters corresponding to the highest acceptable error rate. For a time-varying channel model chosen from the literature, it is shown that our estimator receives considerably more than adequate amount of data during an average time interval of unchanging channel characteristics. Analytical results, numerical results and related issues are discussed.

Importance Autism spectrum disorders (ASD) are characterized by impairments in social interaction, communication, and repetitive or restrictive behavior. Although multiple physiologic and biochemical studies have reported defects in mitochondrial oxidative phosphorylation in patients with ASD, the role of mitochondrial DNA (mtDNA) variation has remained relatively unexplored. Objective To assess what impact mitochondrial lineages encompassing ancient mtDNA functional polymorphisms, termed haplogroups, have on ASD risk. Design, Setting, and Participants In this cohort study, individuals with autism and their families were studied using the Autism Genetic Resource Exchange cohort genome-wide association studies data previously generated at the Children’s Hospital of Philadelphia. From October 2010 to January 2017, we analyzed the data and used the mtDNA single-nucleotide polymorphisms interrogated by the Illumina HumanHap 550 chip to determine the mtDNA haplogroups of the individuals. Taking into account the familial structure of the Autism Genetic Resource Exchange data, we then determined whether the mtDNA haplogroups correlate with ASD risk. Main Outcomes and Measures Odds ratios of mitochondrial haplogroup as predictors of ASD risk. Results Of 1624 patients with autism included in this study, 1299 were boys (80%) and 325 were girls (20%). Families in the Autism Genetic Resource Exchange collection (933 families, encompassing 4041 individuals: 1624 patients with ASD and 2417 healthy parents and siblings) had been previously recruited in the United States with no restrictions on age, sex, race/ethnicity, or socioeconomic status. Relative to the most common European haplogroup HHV, European haplogroups I, J, K, O-X, T, and U were associated with increased risk of ASD, as were Asian and Native American haplogroups A and M, with odds ratios ranging from 1.55 (95% CI, 1.16-2.06) to 2.18 (95% CI, 1.59-3) (adjusted P Conclusions and Relevance Because haplogroups I, J, K, O-X, T, and U encompass 55% of the European population, mtDNA lineages must make a significant contribution to overall ASD risk.

The motor neuron (MN) degenerative disease, spinal muscular atrophy (SMA) is caused by deficiency of SMN (survival motor neuron), a ubiquitous and indispensable protein essential for biogenesis of snRNPs, key components of pre-mRNA processing. However, SMA’s hallmark MN pathology, including neuromuscular junction (NMJ) disruption and sensory-motor circuitry impairment, remains unexplained. Toward this end, we used deep RNA sequencing (RNA-seq) to determine if there are any transcriptome changes in MNs and surrounding spinal cord glial cells (white matter, WM) microdissected from SMN-deficient SMA mouse model at presymptomatic postnatal day 1 (P1), before detectable MN pathology (P4–P5). The RNA-seq results, previously unavailable for SMA at any stage, revealed cell-specific selective mRNA dysregulations (∼300 of 11,000 expressed genes in each, MN and WM), many of which are known to impair neurons. Remarkably, these dysregulations include complete skipping of agrin’s Z exons, critical for NMJ maintenance, strong up-regulation of synapse pruning-promoting complement factor C1q, and down-regulation of Etv1/ER81, a transcription factor required for establishing sensory-motor circuitry. We propose that dysregulation of such specific MN synaptogenesis genes, compounded by many additional transcriptome abnormalities in MNs and WM, link SMN deficiency to SMA’s signature pathology.

Transcriptional regulation critically depends on proper interactions between transcription factors (TF) and their cognate DNA binding sites. The widely used model of TF-DNA binding – the Positional Weight Matrix (PWM) – presumes independence between positions within the binding site. However, there is evidence to show that the independence assumption may not always hold, and the extent of interposition dependence is not completely known. We hypothesize that the interposition dependence should partly be manifested as correlated evolution at the positions. We report a Maximum-Likelihood (ML) approach to infer correlated evolution at any two positions within a PWM, based on a multiple alignment of 5 mammalian genomes. Application to a genome-wide set of putative cis elements in human promoters reveals a prevalence of correlated evolution within cis elements. We found that the interdependence between two positions decreases with increasing distance between the positions. The interdependent positions tend to be evolutionarily more constrained and moreover, the dependence patterns are relatively similar across structurally related transcription factors. Although some of the detected mutational dependencies may be due to context-dependent genomic hyper-mutation, notably CG to TG, the majority is likely due to context-dependent preferences for specific nucleotide combinations within the cis elements. Patterns of evolution at individual nucleotide positions within mammalian TF binding sites are often significantly correlated, suggesting interposition dependence. The proposed methodology is also applicable to other classes of non-coding functional elements. A detailed investigation of mutational dependencies within specific motifs could reveal preferred nucleotide combinations that may help refine the DNA binding models.

Background Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation. Results Here we present a novel mixture modeling approach where a TF-Gene pair is presumed to be significantly correlated (with unknown coefficient) in an (unknown) subset of expression samples. The parameters of the model are estimated using a Maximum Likelihood approach. The estimated mixture of expression samples is then mined to identify genes potentially modulating the TF-Gene interaction. We have validated our approach using synthetic data and on four biological cases in cow, yeast, and humans. Conclusions While limited in some ways, as discussed, the work represents a novel approach to mine expression data and detect potential modulators of regulatory interactions.

Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation. Here we present a novel mixture modeling approach where a TF-Gene pair is presumed to be significantly correlated (with unknown coefficient) in a (unknown) subset of expression samples. The parameters of the model are estimated using a Maximum Likelihood approach. The estimated mixture of expression samples is then mined to identify genes potentially modulating the TF-Gene interaction. We have validated our approach using synthetic data and on three biological cases in cow and in yeast. While limited in some ways, as discussed, the work represents a novel approach to mine expression data and detect potential modulators of regulatory interactions.

Background Gene duplication is a major driver of evolutionary innovation as it allows for an organism to elaborate its existing biological functions via specialization or diversification of initially redundant gene paralogs. Gene function can diversify in several ways. Transcription factor gene paralogs in particular, can diversify either by changes in their tissue-specific expression pattern or by changes in the DNA binding site motif recognized by their protein product, which in turn alters their gene targets. The relationship between these two modes of functional diversification of transcription factor paralogs has not been previously investigated, and is essential for understanding adaptive evolution of transcription factor gene families. Findings Based on a large set of human paralogous transcription factor pairs, we show that when the DNA binding site motifs of transcription factor paralogs are similar, the expressions of the genes that encode the paralogs have diverged, so in general, at most one of the paralogs is highly expressed in a tissue. Moreover, paralogs with diverged DNA binding site motifs tend to be diverged in their function. Conversely, two paralogs that are highly expressed in a tissue tend to have dissimilar DNA binding site motifs. We have also found that in general, within a paralogous family, tissue-specific decrease in gene expression is more frequent than what is expected by chance. Conclusions While previous investigations of paralogous gene diversification have only considered coding sequence divergence, by explicitly quantifying divergence in DNA binding site motif, our work presents a new paradigm for investigating functional diversification. Consistent with evolutionary expectation, our quantitative analysis suggests that paralogous transcription factors have survived extinction in part, either through diversification of their DNA binding site motifs or through alterations in their tissue-specific expression levels.

Cognitive radio is being heralded as an important, new frontier in radio communication; one that promises to overcome spectrum-congestion hotspots. In the cognitive radio approach, different groups of radio users may operate in the same spectrum region. The radio systems intelligently and dynamically change their transmission schemes during operation to co-exist. Therefore, a fundamental issue in cognitive radio is being able to assess and track users on a wireless channel. This problem occurs when the cognitive radio system is searching for friendly data or usable channels. The received and preprocessed signal typically turns out to be a Gaussian mixture random variable with common component variance. The task then is to quickly estimate and continue tracking the parameters of this mixture random variable from samples of data. Two efficient and easily- implemented methods for estimating all these parameters are developed, using a novel approach of fitting the cumulative distribution function (cdf) to the estimated cdf, and nonlinear, unconstrained optimization. The algorithms are demonstrated through simulation experiments. The algorithms presented here compare favourably with the general EM algorithm and are better suited for cognitive radio and wireless network surveillance applications.

Blind estimation of noise variance and data statistics in some classes of M-symbol wireless digital communication systems is studied. Automatic gain control in pulse amplitude modulation systems und the reference carrier in coherent demodulation systems provide the noise-free signal values for the set of symbols at the receiver. This reduces the problem of channel and data statistics estimation to the estimation of the common component variance and mixing probabilities in a finite Gaussian mixture, with known values for component means. Using these known component means, /spl mu//sub 1/...../spl mu//sub M/, a set of non-linear transformations, sinh(/spl mu//sub i/x) and cosh(/spl mu//sub i/x) of the data (mixture random variable X) are used to develop convergent and computationally efficient estimators for both the noise variance and the vector of symbol probabilities. The estimation equations can be implemented recursively or with a batch processing algorithm. Asymptotic variances of the estimates are derived and the developed estimator is simulated for a specific problem.

CTCF DNA binding sites are classified into distinct functional classes, with distinct biological properties, shedding light on the differing functional roles of CTCF binding., Background CTCF (CCCTC-binding factor) is an evolutionarily conserved zinc finger protein involved in diverse functions ranging from negative regulation of MYC, to chromatin insulation of the beta-globin gene cluster, to imprinting of the Igf2 locus. The 11 zinc fingers of CTCF are known to differentially contribute to the CTCF-DNA interaction at different binding sites. It is possible that the differences in CTCF-DNA conformation at different binding sites underlie CTCF's functional diversity. If so, the CTCF binding sites may belong to distinct classes, each compatible with a specific functional role. Results We have classified approximately 26,000 CTCF binding sites in CD4+ T cells into three classes based on their similarity to the well-characterized CTCF DNA-binding motif. We have comprehensively characterized these three classes of CTCF sites with respect to several evolutionary, genomic, epigenomic, transcriptomic and functional features. We find that the low-occupancy sites tend to be cell type specific. Furthermore, while the high-occupancy sites associate with repressive histone marks and greater gene co-expression within a CTCF-flanked block, the low-occupancy sites associate with active histone marks and higher gene expression. We found that the low-occupancy sites have greater conservation in their flanking regions compared to high-occupancy sites. Interestingly, based on a novel class-conservation metric, we observed that human low-occupancy sites tend to be conserved as low-occupancy sites in mouse (and vice versa) more frequently than expected. Conclusions Our work reveals several key differences among CTCF occupancy-based classes and suggests a critical, yet distinct functional role played by low-occupancy sites.

SummaryU1 snRNP (U1), in addition to its splicing role, protects pre-mRNAs from drastic premature termination by cleavage and polyadenylation (PCPA) at cryptic polyadenylation signals (PASs) in introns. Here, a high-throughput sequencing strategy of differentially expressed transcripts (HIDE-seq) mapped PCPA sites genome wide in divergent organisms. Surprisingly, whereas U1 depletion terminated most nascent gene transcripts within ∼1 kb, moderate functional U1 level decreases, insufficient to inhibit splicing, dose-dependently shifted PCPA downstream and elicited mRNA 3′ UTR shortening and proximal 3′ exon switching characteristic of activated immune and neuronal cells, stem cells, and cancer. Activated neurons' signature mRNA shortening could be recapitulated by U1 decrease and antagonized by U1 overexpression. Importantly, we show that rapid and transient transcriptional upregulation inherent to neuronal activation physiology creates U1 shortage relative to pre-mRNAs. Additional experiments suggest cotranscriptional PCPA counteracted by U1 association with nascent transcripts, a process we term telescripting, ensuring transcriptome integrity and regulating mRNA length.