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While the role of G quadruplex (G4) structures has been identified in cancers and metabolic disorders, single nucleotide variations (SNVs) and their effect on G4s in disease contexts have not been extensively studied. The COSMIC and CLINVAR databases were used to detect SNVs present in G4s to identify sequence level changes and their effect on the alteration of the G4 secondary structure. A total of 37,515 G4 SNVs in the COSMIC database and 2378 in CLINVAR were identified. Of those, 7236 COSMIC (19.3%) and 457 (19%) of the CLINVAR variants result in G4 loss, while 2728 (COSMIC) and 129 (CLINVAR) SNVs gain a G4 structure. The remaining variants potentially affect the folding energy without affecting the presence of a G4. Analysis of mutational patterns in the G4 structure shows a higher selective pressure (3-fold) in the coding region on the template strand compared to the reverse strand. At the same time, an equal proportion of SNVs were observed among intronic, promoter, and enhancer regions across strands. [ABSTRACT FROM AUTHOR]

G-quadruplexes (G4s) are short secondary DNA structures located throughout genomic DNA and transcribed RNA. Although G4 structures have been shown to form in vivo, no current search tools that examine these structures based on previously identified G-quadruplexes and filter them based on similar sequence, structure, and thermodynamic properties are known to exist. We present a framework for clustering G-quadruplex sequences into families using the CD-HIT, MeShClust, and DNACLUST methods along with a combination of Starcode and BLAST. Utilizing this framework to filter and annotate clusters, 95 families of G-quadruplex sequences were identified within the human genome. Profiles for each family were created using hidden Markov models to allow for the identification of additional family members and generate homology probability scores. The thermodynamic folding energy properties, functional annotation of genes associated with the sequences, scores from different prediction algorithms, and transcription factor binding motifs within a family were used to annotate and compare the diversity within and across clusters. The resulting set of G-quadruplex families can be used to further understand how different regions of the genome are regulated by factors targeting specific structures common to members of a specific cluster. [ABSTRACT FROM AUTHOR]

While the role of G quadruplex (G4) structures has been identified in cancers and metabolic disorders, single nucleotide variations (SNVs) and their effect on G4s in disease contexts have not been extensively studied. The COSMIC and CLINVAR databases were used to detect SNVs present in G4s to identify sequence level changes and their effect on the alteration of the G4 secondary structure. A total of 37,515 G4 SNVs in the COSMIC database and 2378 in CLINVAR were identified. Of those, 7236 COSMIC (19.3%) and 457 (19%) of the CLINVAR variants result in G4 loss, while 2728 (COSMIC) and 129 (CLINVAR) SNVs gain a G4 structure. The remaining variants potentially affect the folding energy without affecting the presence of a G4. Analysis of mutational patterns in the G4 structure shows a higher selective pressure (3-fold) in the coding region on the template strand compared to the reverse strand. At the same time, an equal proportion of SNVs were observed among intronic, promoter, and enhancer regions across strands.

G-quadruplexes (G4s) are short secondary DNA structures located throughout genomic DNA and transcribed RNA. Although G4 structures have been shown to form in vivo, no current search tools that examine these structures based on previously identified G-quadruplexes and filter them based on similar sequence, structure, and thermodynamic properties are known to exist. We present a framework for clustering G-quadruplex sequences into families using the CD-HIT, MeShClust, and DNACLUST methods along with a combination of Starcode and BLAST. Utilizing this framework to filter and annotate clusters, 95 families of G-quadruplex sequences were identified within the human genome. Profiles for each family were created using hidden Markov models to allow for the identification of additional family members and generate homology probability scores. The thermodynamic folding energy properties, functional annotation of genes associated with the sequences, scores from different prediction algorithms, and transcription factor binding motifs within a family were used to annotate and compare the diversity within and across clusters. The resulting set of G-quadruplex families can be used to further understand how different regions of the genome are regulated by factors targeting specific structures common to members of a specific cluster.

RECQ1 (also known as RECQL or RECQL1) belongs to the RecQ family of DNA helicases, members of which are linked with rare genetic diseases of cancer predisposition in humans. RECQ1 is implicated in several cellular processes, including DNA repair, cell cycle and growth, telomere maintenance, and transcription. Earlier studies have demonstrated a unique requirement of RECQ1 in ensuring chromosomal stability and suggested its potential involvement in tumorigenesis. Recent reports have suggested that RECQ1 is a potential breast cancer susceptibility gene, and missense mutations in this gene contribute to familial breast cancer development. Here, we provide a framework for understanding how the genetic or functional loss of RECQ1 might contribute to genomic instability and cancer.

RECQ1 (also known as RECQL or RECQL1) belongs to the RecQ family of DNA helicases, members of which are linked with rare genetic diseases of cancer predisposition in humans. RECQ1 is implicated in several cellular processes, including DNA repair, cell cycle and growth, telomere maintenance, and transcription. Earlier studies have demonstrated a unique requirement of RECQ1 in ensuring chromosomal stability and suggested its potential involvement in tumorigenesis. Recent reports have suggested that RECQ1 is a potential breast cancer susceptibility gene, and missense mutations in this gene contribute to familial breast cancer development. Here, we provide a framework for understanding how the genetic or functional loss of RECQ1 might contribute to genomic instability and cancer. [ABSTRACT FROM AUTHOR]