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G-quadruplexes (G4s) are among the best-characterized DNA secondary structures and are enriched in regulatory regions, especially promoters, of several prokaryote and eukaryote genomes, indicating a possible role in cis regulation of genes. Many studies have focused on evaluating the impact of specific G4-forming sequences in the promoter regions of genes. However, the lack of correlation between the presence of G4s and the functional impact on cis gene regulation, evidenced by the variable expression fold change in the presence of G4 stabilizers, shows that not all G4s affect transcription in the same manner. This indicates that the regulatory effect of the G4 is significantly influenced by its position, the surrounding DNA topology, and other environmental factors within the cell. In this review, we compare individual gene studies with high-throughput differential expression studies to highlight the importance of formulating a combined approach that can be applied in humans, bacteria, and viruses to better understand the effect of G4-mediated gene regulation.

G-quadruplexes (G4s) are among the best-characterized DNA secondary structures and are enriched in regulatory regions, especially promoters, of several prokaryote and eukaryote genomes, indicating a possible role in cis regulation of genes. Many studies have focused on evaluating the impact of specific G4-forming sequences in the promoter regions of genes. However, the lack of correlation between the presence of G4s and the functional impact on cis gene regulation, evidenced by the variable expression fold change in the presence of G4 stabilizers, shows that not all G4s affect transcription in the same manner. This indicates that the regulatory effect of the G4 is significantly influenced by its position, the surrounding DNA topology, and other environmental factors within the cell. In this review, we compare individual gene studies with high-throughput differential expression studies to highlight the importance of formulating a combined approach that can be applied in humans, bacteria, and viruses to better understand the effect of G4-mediated gene regulation. [ABSTRACT FROM AUTHOR]

Whole-genome association studies typically focus on genetic markers with the strongest evidence of association. However, single markers often explain only a small component of the genetic variance and hence offer a limited understanding of the trait under study. As such, the objective of this study was to perform a pathway-based association analysis in Holstein dairy cattle in order to identify relevant pathways involved in bull fertility. The results of a single-marker association analysis, using 1,755 bulls with sire conception rate data and genotypes for 38,650 single nucleotide polymorphisms (SNPs), were used in this study. A total of 16,819 annotated genes, including 2,767 significantly associated with bull fertility, were used to interrogate a total of 662 Gene Ontology (GO) terms and 248 InterPro (IP) entries using a test of proportions based on the cumulative hypergeometric distribution. After multiple testing correction, twenty GO categories and one IP entry showed significant overrepresentation of genes statistically associated with bull fertility. Several of these functional categories such as small GTPases mediated signal transduction, neurogenesis, calcium ion binding, and cytoskeleton are known to be involved in biological processes closely related to male fertility. These results could provide insight into the genetic architecture of this complex trait in dairy cattle. In addition, this study shows that quantitative trait pathways inferred from single-marker analyses could enhance our interpretations of the results of genome-wide association studies.

Whole-genome association studies typically focus on genetic markers with the strongest evidence of association. However, single markers often explain only a small component of the genetic variance and hence offer a limited understanding of the trait under study. As such, the objective of this study was to perform a pathway-based association analysis in Holstein dairy cattle in order to identify relevant pathways involved in bull fertility. The results of a single-marker association analysis, using 1,755 bulls with sire conception rate data and genotypes for 38,650 single nucleotide polymorphisms (SNPs), were used in this study. A total of 16,819 annotated genes, including 2,767 significantly associated with bull fertility, were used to interrogate a total of 662 Gene Ontology (GO) terms and 248 InterPro (IP) entries using a test of proportions based on the cumulative hypergeometric distribution. After multiple-testing correction, 20 GO categories and one IP entry showed significant overrepresentation of genes statistically associated with bull fertility. Several of these functional categories such as small GTPases mediated signal transduction, neurogenesis, calcium ion binding, and cytoskeleton are known to be involved in biological processes closely related to male fertility. These results could provide insight into the genetic architecture of this complex trait in dairy cattle. In addition, this study shows that quantitative trait pathways inferred from single-marker analyses could enhance our interpretations of the results of genome-wide association studies.