Characterization of RNA Editome in the Mammary Gland of Yaks during the Lactation and Dry Periods

The mammary gland is a complicated organ comprising several types of cells, and it undergoes extensive morphogenetic and metabolic changes during the female reproductive cycle. RNA editing is a posttranscriptional modification event occurring at the RNA nucleotide level, and it drives transcriptomic and proteomic diversities, with potential functional consequences. RNA editing in the mammary gland of yaks, however, remains poorly understood. Here, we used REDItools to identify RNA editing sites in mammary gland tissues in yaks during the lactation period (LP, n = 2) and dry period (DP, n = 3). Totally, 82,872 unique RNA editing sites were identified, most of which were detected in the noncoding regions with a low editing degree. In the coding regions (CDS), we detected 5235 editing sites, among which 1884 caused nonsynonymous amino acid changes. Of these RNA editing sites, 486 were found to generate novel possible miRNA target sites or interfere with the initial miRNA binding sites, indicating that RNA editing was related to gene regulation mediated by miRNA. A total of 14,159 RNA editing sites (involving 3238 common genes) showed a significant differential editing level in the LP when compared with that in the DP through Tukey’s Honest Significant Difference method (p < 0.05). According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, genes that showed different RNA editing levels mainly participated in pathways highly related to mammary gland development, including MAPK, PI3K-Akt, FoxO, and GnRH signaling pathways. Collectively, this work demonstrated for the first time the dynamic RNA editome profiles in the mammary gland of yaks and shed more light on the mechanism that regulates lactation together with mammary gland development.

SARS-CoV-2 Point Mutation and Deletion Spectra, and Their Association with Different Disease Outcome

Mutant spectra of RNA viruses are important to understand viral pathogenesis, and response to selective pressures. There is a need to characterize the complexity of mutant spectra in coronaviruses sampled from infected patients. In particular, the possible relationship between SARS-CoV-2 mutant spectrum complexity and disease associations has not been established. In the present study, we report an ultra-deep sequencing (UDS) analysis of the mutant spectrum of amplicons from the nsp12 (polymerase)- and spike (S)-coding regions of thirty nasopharyngeal isolates (diagnostic samples) of SARS-CoV-2 of the first COVID-19 pandemic wave (Madrid, Spain, April 2020) classified according to the severity of ensuing COVID-19. Low frequency mutations and deletions, counted relative to the consensus sequence of the corresponding isolate, were overwhelmingly abundant. We show that the average number of different point mutations, mutations per haplotype and several diversity indices was significantly higher in SARS-CoV-2 isolated from patients who developed mild disease than in those associated with moderate or severe disease (exitus). No such bias was observed with RNA deletions. Location of amino acid substitutions in the three dimensional structures of nsp12 (polymerase) and S suggest significant structural or functional effects. Thus, patients who develop mild symptoms may be a richer source of genetic variants of SARS-CoV-2 than patients with moderate or severe COVID-19.

Association of mutation signature effectuating processes with mutation hotspots in driver genes and non-coding regions

Cancer driving mutations are difficult to identify especially in the non-coding part of the genome. Here, we present sigDriver, an algorithm dedicated to call driver mutations. Using 3813 whole-genome sequenced tumors from International Cancer Genome Consortium, The Cancer Genome Atlas Program, and a childhood pan-cancer cohort, we employ mutational signatures based on single-base substitution in the context of tri- and penta-nucleotide motifs for hotspot discovery. Knowledge-based annotations on mutational hotspots reveal enrichment in coding regions and regulatory elements for 6 mutational signatures, including APOBEC and somatic hypermutation signatures. APOBEC activity is associated with 32 hotspots of which 11 are known and 11 are putative regulatory drivers. Somatic single nucleotide variants clusters detected at hypermutation-associated hotspots are distinct from translocation or gene amplifications. Patients carrying APOBEC induced PIK3CA driver mutations show lower occurrence of signature SBS39. In summary, sigDriver uncovers mutational processes associated with known and putative tumor drivers and hotspots particularly in the non-coding regions of the genome.

Application of deep learning algorithm on whole genome sequencing data uncovers structural variants associated with multiple mental disorders in African American patients

Mental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patients who have more than one type of mental disorder, especially for young toddlers who are not able to complete questionnaires or standardized rating scales for diagnosis. In the past decade, multiple genomic association signals have been reported for mental disorders, some of which present attractive drug targets. Concurrently, machine learning algorithms, especially deep learning algorithms, have been successful in the diagnosis and/or labeling of complex diseases, such as attention deficit hyperactivity disorder (ADHD) or cancer. In this study, we focused on eight common mental disorders, including ADHD, depression, anxiety, autism, intellectual disabilities, speech/language disorder, delays in developments, and oppositional defiant disorder in the ethnic minority of African Americans. Blood-derived whole genome sequencing data from 4179 individuals were generated, including 1384 patients with the diagnosis of at least one mental disorder. The burden of genomic variants in coding/non-coding regions was applied as feature vectors in the deep learning algorithm. Our model showed ~65% accuracy in differentiating patients from controls. Ability to label patients with multiple disorders was similarly successful, with a hamming loss score less than 0.3, while exact diagnostic matches are around 10%. Genes in genomic regions with the highest weights showed enrichment of biological pathways involved in immune responses, antigen/nucleic acid binding, chemokine signaling pathway, and G-protein receptor activities. A noticeable fact is that variants in non-coding regions (e.g., ncRNA, intronic, and intergenic) performed equally well as variants in coding regions; however, unlike coding region variants, variants in non-coding regions do not express genomic hotspots whereas they carry much more narrow standard deviations, indicating they probably serve as alternative markers.

Molecular and clinical characterization of autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy syndrome (APECED) in Iranian non-Jewish patients: report of two novel AIRE gene pathogenic variants

Objective Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy syndrome (APECED) is a rare autosomal recessive systemic autoimmune disease caused by mutations in the autoimmune regulator (AIRE) gene. Incidence of this genetic disorder is estimated at 1/90,000–200,000 worldwide and 1/6500–9000 in genetically isolated populations such as Iran. Here, we investigated AIRE gene mutations in eight independent Iranian non-Jewish families. Methods We sequenced the coding regions of the AIRE gene and documented mutations which were further confirmed in respective parents. Results In total, 11 cases from 8 independent families were recruited. Mucosal candidiasis, Addison’s disease and hypoparathyroidism were the most common clinical manifestations in these patients. One novel homozygous splice acceptor mutation (c.308-1G>C), and one novel heterozygous stop-gain mutation (c.1496delC) combined with a known heterozygous c.232T>C missense mutation were found. Moreover, we observed previously described splice donor (c.1095+2T>A), frameshift (c.967-979del), stop-gain (c.415C>T), and missense (c.62C>T) mutations among the patients. All results were co-segregated in parents. Conclusion Here, we reported two novel mutations in the AIRE gene leading to APECED. Our data could provide insight into the phenotypic and genotypic spectrum of APECED in the non-Jewish Iranian population. These findings, in addition to future functional assays, can elucidate disease-causing mechanisms related to the AIRE gene and assist in genetic counseling and diagnosis.

Rare schizophrenia risk variant burden is conserved in diverse human populations

Schizophrenia is a chronic mental illness that is amongst the most debilitating conditions encountered in medical practice. A recent landmark schizophrenia study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes1. This study -- and most other large-scale human genetic studies -- was mainly composed of individuals of European ancestry, and the generalizability of the findings in non-European populations is unclear. To address this gap in knowledge, we designed a custom sequencing panel based on current knowledge of the genetic architecture of schizophrenia and applied it to a new cohort of 22,135 individuals of diverse ancestries. Replicating earlier work, cases carried a significantly higher burden of rare protein-truncating variants among constrained genes (OR=1.48, p-value = 5.4 x 10-6). In meta-analyses with existing schizophrenia datasets totaling up to 35,828 cases and 107,877 controls, this excess burden was largely consistent across five continental populations. Two genes (SRRM2 and AKAP11) were newly implicated as schizophrenia risk genes, and one gene (PCLO) was identified as a shared risk gene for schizophrenia and autism. Overall, our results lend robust support to the rare allelic spectrum of the genetic architecture of schizophrenia being conserved across diverse human populations.

Recommendations for clinical interpretation of variants found in non-coding regions of the genome

Purpose: The majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts. Methods: We convened a panel of clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups. Results: We discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight examples of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for these variants. Conclusion: These recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.

Limited, but potentially functional translation of non-coding transcripts in the HEK293T cellular cytosol

Ribosome profiling has revealed translation outside of canonical coding sequences (CDSs) including translation of short upstream ORFs, long non-coding RNAs, overlapping ORFs, ORFs in UTRs or ORFs in alternative reading frames. Studies combining mass spectrometry, ribosome profiling and CRISPR-based screens showed that hundreds of ORFs derived from non-coding transcripts produce (micro)proteins, while other studies failed to find evidence for such types of non-canonical translation products. Here, we attempted to discover translation products from non-coding regions by strongly reducing the complexity of the sample prior to mass spectrometric analysis. We used an extended database as the search space and applied stringent filtering of the identified peptides to find evidence for novel translation events. Theoretically, we show that our strategy facilitates the detection of translation events of transcripts from non-coding regions, but experimentally only find 19 peptides (less than 1% of all identified peptides) that might originate from such translation events. Virotrap based interactome analysis of two N-terminal proteoforms originating from non-coding regions finally showed the functional potential of these novel proteins.

VicRK and CovR polymorphisms in Streptococcus mutans strains associated with cardiovascular infections

Introduction. Streptococcus mutans , a common species of the oral microbiome, expresses virulence genes promoting cariogenic dental biofilms, persistence in the bloodstream and cardiovascular infections. Gap statement. Virulence gene expression is variable among S. mutans strains and controlled by the transcription regulatory systems VicRK and CovR. Aim. This study investigates polymorphisms in the vicRK and covR loci in S. mutans strains isolated from the oral cavity or from the bloodstream, which were shown to differ in expression of covR, vicRK and downstream genes. Methodology. The transcriptional activities of covR, vicR and vicK were compared by RT-qPCR between blood and oral strains after exposure to human serum. PCR-amplified promoter and/or coding regions of covR and vicRK of 18 strains (11 oral and 7 blood) were sequenced and compared to the reference strain UA159. Results. Serum exposure significantly reduced covR and vicR/K transcript levels in most strains (P<0.05), but reductions were higher in oral than in blood strains. Single-nucleotide polymorphisms (SNPs) were detected in covR regulatory and coding regions, but SNPs affecting the CovR effector domain were only present in two blood strains. Although vicR was highly conserved, vicK showed several SNPs, and SNPs affecting VicK regions important for autokinase activity were found in three blood strains. Conclusions. This study reveals transcriptional and structural diversity in covR and vicR/K, and identifies polymorphisms of functional relevance in blood strains, indicating that covR and vicRK might be important loci for S. mutans adaptation to host selective pressures associated with virulence diversity.

The molecular pathogenesis of repeat expansion diseases

Expanded short tandem repeats in the genome cause various monogenic diseases, particularly neurological disorders. Since the discovery of a CGG repeat expansion in the FMR1 gene in 1991, more than 40 repeat expansion diseases have been identified to date. In the coding repeat expansion diseases, in which the expanded repeat sequence is located in the coding regions of genes, the toxicity of repeat polypeptides, particularly misfolding and aggregation of proteins containing an expanded polyglutamine tract, have been the focus of investigation. On the other hand, in the non-coding repeat expansion diseases, in which the expanded repeat sequence is located in introns or untranslated regions, the toxicity of repeat RNAs has been the focus of investigation. Recently, these repeat RNAs were demonstrated to be translated into repeat polypeptides by the novel mechanism of repeat-associated non-AUG translation, which has extended the research direction of the pathological mechanisms of this disease entity to include polypeptide toxicity. Thus, a common pathogenesis has been suggested for both coding and non-coding repeat expansion diseases. In this review, we briefly outline the major pathogenic mechanisms of repeat expansion diseases, including a loss-of-function mechanism caused by repeat expansion, repeat RNA toxicity caused by RNA foci formation and protein sequestration, and toxicity by repeat polypeptides. We also discuss perturbation of the physiological liquid-liquid phase separation state caused by these repeat RNAs and repeat polypeptides, as well as potential therapeutic approaches against repeat expansion diseases.