Biology subjects

Chiaromonte, F.

Publications and source records attributed to Chiaromonte, F..

12 recordsLinked to original sources

bioRxiv2026

Variation and selection at predicted G-quadruplexes across the human pangenome

G-quadruplexes (G4s), non-canonical DNA structures whose sequence motifs occupy approximately 1% of the human genome, are important for myriad cellular functions, including regulating transcription and replication. Yet they also contribute to genomic instability by increasing mutations and structural variation. Despite their significance, G4 motifs have not been studied in detail across multiple human genomes. Here, we conducted a comprehensive analysis of presence/absence and sequence variation, measured selection strength, and evaluated gene expression regulation potential for predicted G4s (pG4s) across population groups in the second release of the Human Pangenome Reference Consortium dataset, comprising high-quality, near-telomere-to-telomere diploid genomes from 231 individuals worldwide, along with three reference assemblies. Across the human pangenome, we identified over 353 million pG4s, including 1.15 million pG4s absent from reference assemblies but shared across other haplotypes. Our analysis revealed that pG4 sharing patterns recapitulate human population structure: African individuals displayed lower levels of pG4 sharing than non-Africans, whereas East Asian individuals exhibited higher levels of sharing. By analyzing the site frequency spectrum across various genomic annotations, we computed and compared selection coefficients (Sd) at pG4 vs. non-pG4 sites. As expected, the strongest purifying selection (Sd [≥] 10) was detected at protein-coding exons, where pG4 sites had similar or lower selection coefficients compared with those for pG4 sites. Strikingly, this pattern reversed at regulatory regions: although purifying selection was weaker overall at promoters, introns, enhancers, and replication origins (1 [≤] Sd < 10), pG4 sites at these regions experienced stronger selection than non-pG4 sites--suggesting that pG4s play functional roles outside coding sequences. Additionally, by integrating pG4 data with long-read transcriptome data profiles from this large cohort, we found that pG4s located at promoters and at (or near) exon-intron junctions may influence variation in gene expression levels and transcript isoforms, respectively, across the human pangenome individuals. Leveraging extensive population-scale data, our research illuminates the fundamental importance and functional relevance of G4s across human genomes.

genomics↗

bioRxiv2025

Comparative analysis of single-stranded and non-canonical DNA formation in human and other ape cells with telomere-to-telomere genomes

Non-canonical (non-B) DNA secondary structures, e.g., G-quadruplexes and triplex DNA, are mutation hotspots and genome regulators contributing to disease and evolution. Yet they remain uncharacterized in complete genomes in vivo. Here we exploited the fact that many non-B DNA structures form single-stranded DNA (ssDNA). Using permanganate/S1 footprinting across 14 cell lines, we generated ssDNA profiles for human and six non-human ape telomere-to-telomere (T2T) genomes. Newly resolved satellite arrays--e.g., at ribosomal DNA and centromeres--displayed high ssDNA levels, implicating non-B DNA in satellite expansion and function. Hidden Markov Models applied to our ssDNA data revealed active genomic domains with specific functions--e.g., replication, transcription, or recombination--each enriched in particular non-B DNA types. Human-specific ssDNA domains correlated with nervous system genes, whereas cancer and embryonic cells showed increased ssDNA in transposable elements. Our ssDNA analysis across ape T2T genomes uncovered conserved and species-specific DNA structural dynamics central to genome regulation.

genomics↗

bioRxiv2025

Non-canonical DNA in bird telomere-to-telomere genomes

Non-canonical (non-B) DNA motifs are sequences that can fold into structures (e.g., G-quadruplexes and Z-DNA) distinct from the canonical right-handed helix. In mammals, these structures regulate gene expression, act as mutation hotspots, and are associated with cancer, yet they remain undercharacterized in other species. Because non-B DNA motifs are difficult to sequence, many are absent from incomplete genome assemblies, limiting functional analyses. Here, we present the first comprehensive analysis of non-B DNA motifs in birds, using the telomere-to-telomere genome of zebra finch, the near-complete chicken genome, and high-quality genomes of six additional bird species. We show that, first, unlike in mammals, the non-B DNA landscape in birds differs markedly among chromosome groups: gene-rich and extremely small dot chromosomes show the highest coverage (15.1-30.1% in zebra finch), microchromosomes--intermediate coverage (6.4-18.1%), and macrochromosomes--the lowest (5.9-6.9%). Non-B DNA motif coverage on dot chromosomes negatively correlates with PacBio sequencing depth, potentially explaining their assembly challenges. Second, similar to mammals, in zebra finch, G-quadruplexes are enriched at promoters and 5'UTRs, implying regulatory roles. We experimentally validated four common G-quadruplexes and predicted others using long-read methylation data. Overall, non-B DNA distribution reflects distinct features of avian genome architecture, suggests a role in gene regulation, and informs strategies for complete bird genome sequencing.

genomics↗

bioRxiv2025

Substitution spectrum and selection at G-quadruplexes in great ape telomere-to-telomere genomes

G-quadruplexes (G4s) are noncanonical DNA secondary structures formed by runs of guanines (stems) connected by other nucleotides (loops). These structures are enriched at regulatory regions such as promoters, CpG islands, untranslated regions (UTRs), enhancers, and replication origins, where they play key roles in transcription and replication. Although prior studies have demonstrated that G4s exhibit higher mutation rates than canonical DNA, little is known about the substitution patterns and selection acting specifically on G4 stems and loops. In this study, we utilized Telomere-to-Telomere (T2T) genome assemblies from human and two non-human great apes (chimpanzee and Bornean orangutan) to analyze substitution spectra and selective constraints within G4s, focusing on differences between stems and loops. We observed that fixed nucleotide substitutions leading to the gain or loss of G4 structures are more frequently located at stems, while those in G4s conserved across species are more often found at loops. On the other hand, single nucleotide polymorphisms had higher frequencies at stems than loops for all G4s, with a particularly high difference for singleton polymorphisms, suggesting higher mutation rates at stems than loops. To evaluate selection, we employed two approaches: we computed the ratio of substitution to polymorphism frequencies at stems vs. loops and performed phylogenetic modeling using PhyloFit. Both methods consistently revealed that stems of shared G4s experience stronger purifying selection than loops, particularly at promoters, enhancers, and UTRs. Our results provide novel insights into the sequence variation and selection of G4s, informing our understanding of their contributions to genome evolution and function. Significance StatementG-quadruplexes (G4s) are non-canonical DNA structures that influence transcription, genome stability, and epigenetic regulation, yet their evolutionary dynamics in primates remain poorly understood. Leveraging recent T2T genome assemblies, we conducted a sequence-level analysis of G4 evolution across three ape lineages and used two methods to infer selection in G4. Shared G4s and species-specific G4s display distinct evolutionary signatures. Using PhyloFit to estimate substitution rates and the Hudson-Kreitman-Aguade test to contrast divergence with polymorphism, we found stems under markedly stronger purifying selection than loops, especially within promoters, CpG islands, and 5'UTRs. This pattern indicates that maintaining stem integrity is functionally critical and evolutionarily conserved. Our findings reveal how selective constraints vary both within G4 motifs and across genomic landscapes, offering insights for future studies on their functional importance and structural stability.

evolutionary biology↗

bioRxiv2024

Mitochondrial DNA mutations in human oocytes undergo frequency-dependent selection but do not increase with age

Mitochondria, cellular powerhouses, harbor DNA (mtDNA) inherited from the mothers. MtDNA mutations can cause diseases, yet whether they increase with age in human germline cells--oocytes--remains understudied. Here, using highly accurate duplex sequencing of full-length mtDNA, we detected de novo mutations in single oocytes, blood, and saliva in women between 20 and 42 years of age. We found that, with age, mutations increased in blood and saliva but not in oocytes. In oocytes, mutations with high allele frequencies ([≥]1%) were less prevalent in coding than non-coding regions, whereas mutations with low allele frequencies (<1%) were more uniformly distributed along mtDNA, suggesting frequency-dependent purifying selection. In somatic tissues, mutations caused elevated amino acid changes in protein-coding regions, suggesting positive or destructive selection. Thus, mtDNA in human oocytes is protected against accumulation of mutations having functional consequences and with aging. These findings are particularly timely as humans tend to reproduce later in life. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/627454v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@18242f6org.highwire.dtl.DTLVardef@fa5a97org.highwire.dtl.DTLVardef@51a452org.highwire.dtl.DTLVardef@1fb2374_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Evolutionary Dynamics of G-Quadruplexes in Human and Other Great Ape Telomere-to-Telomere Genomes

G-quadruplexes (G4s) are non-canonical DNA structures that can form at approximately 1% of the human genome. G4s contribute to point mutations and structural variation and thus facilitate genomic instability. They play important roles in regulating replication, transcription, and telomere maintenance, and some of them evolve under purifying selection. Nevertheless, the evolutionary dynamics of G4s has remained underexplored. Here we conducted a comprehensive analysis of predicted G4s (pG4s) in the recently released, telomere-to-telomere (T2T) genomes of human and other great apes--bonobo, chimpanzee, gorilla, Bornean orangutan, and Sumatran orangutan. We annotated tens of thousands of new pG4s in T2T compared to previous ape genome assemblies, including 41,236 in the human genome. Analyzing species alignments, we found approximately one-third of pG4s shared by all apes studied and identified thousands of species- and genus-specific pG4s. pG4s accumulated and diverged at rates consistent with divergence times between the studied species. We observed a significant enrichment and hypomethylation of pG4 shared across species at regulatory regions, including promoters, 5 and 3UTRs, and origins of replication, strongly suggesting their formation and functional role in these regions. pG4s shared among great apes displayed lower methylation levels compared to species-specific pG4s, suggesting evolutionary conservation of functional roles of the former. Many species-specific pG4s were located in the repetitive and satellite regions deciphered in the T2T genomes. Our findings illuminate the evolutionary dynamics of G4s, their role in gene regulation, and their potential contribution to species-specific adaptations in great apes, emphasizing the utility of high-resolution T2T genomes in uncovering previously elusive genomic features.

genomics↗

bioRxiv2022

Altered sequencing success at non-B-DNA motifs

Modern sequencing technologies are not error-free, and might have elevated error rates at some locations of the genome. A potential cause for such elevated error rates is the formation of alternative DNA structures (non-B DNA), such as G-quadruplexes (G4s), Z-DNA, or cruciform structures, during sequencing. Approximately 13% of the human genome has the potential to form such structures, which have been previously shown to affect the activity of DNA polymerases and helicases. Here we tested whether motifs with the potential to form non-B DNA (non-B motifs) influence the sequencing success of three major sequencing technologies--Illumina, Pacific Biosciences (PacBio) HiFi, and Oxford Nanopore Technologies (ONT). We estimated sequencing success by computing the rates of single-nucleotide, insertion, and deletion errors, as well as by evaluating mean read depth and mean base quality. Overall, all technologies exhibited altered sequencing success for most non-B motif types. Single-nucleotide error rates were generally increased for G-quadruplexes (G4s) and Z-DNA motifs in all three technologies. Illumina and PacBio HiFi deletion error rates were also increased for all non-B types except for Z-DNA motifs, while in ONT they were increased substantially only for G4 motifs. Insertion error rates for non-B motifs were highly elevated in Illumina, moderately elevated in PacBio HiFi, and only slightly elevated in ONT. Using Poisson regression modeling, we evaluated how non-B DNA motifs and other factors influence sequencing error profiles. Using the error rates at non-B motifs, we developed a probabilistic approach to determine the number of false-positive single-nucleotide variants (SNVs) in different sample size and variant frequency cutoff scenarios, as well as in previously generated sequencing data sets (1000Genomes, Simons Genome Diversity Project, and gnomAD). Overall, the effect of non-B DNA on sequencing should be considered in downstream analyses, particularly in studies with limited read depth--e.g., single-cell and ancient DNA sequencing, as well as sequencing of pooled population samples--and when scoring variants with low frequency (e.g., singletons). Because each sequencing technology analyzed has a unique error profile at non-B motifs, a combination of different technologies should be considered in future sequencing studies of such motifs, to maximize accuracy.

genomics↗

bioRxiv2019

Learning the properties of adaptive regions with functional data analysis

Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.

genomics↗

bioRxiv2019

Polygenic risk score based on weight gain trajectories is a strong predictor of childhood obesity

Obesity is highly heritable, yet only a small fraction of its heritability has been attributed to specific genetic variants. These variants are traditionally ascertained from genome-wide association studies (GWAS), which utilize samples with tens or hundreds of thousands of individuals for whom a single summary measurement (e.g., BMI) is collected. An alternative approach is to focus on a smaller, more deeply characterized sample in conjunction with advanced statistical models that leverage detailed phenotypes. Here we use novel functional data analysis (FDA) techniques to capitalize on longitudinal growth information and construct a polygenic risk score (PRS) for obesity in children followed from birth to three years of age. This score, comprised of 24 single nucleotide polymorphisms (SNPs), is significantly higher in children with (vs. without) rapid infant weight gain--a predictor of obesity later in life. Using two independent cohorts, we show that genetic variants identified in early childhood are also informative in older children and in adults, consistent with early childhood obesity being predictive of obesity later in life. In contrast, PRSs based on SNPs identified by adult obesity GWAS are not predictive of weight gain in our cohort of children. Our research provides an example of a successful application of FDA to GWAS. We demonstrate that a deep, statistically sophisticated characterization of a longitudinal phenotype can provide increased statistical power to studies with relatively small sample sizes. This study shows how FDA approaches can be used as an alternative to the traditional GWAS. Author SummaryFinding genetic variants that confer an increased risk of developing a particular disease has long been a focus of modern genetics. Genome wide association studies (GWAS) have catalogued single nucleotide polymorphisms (SNPs) associated with a variety of complex diseases in humans, including obesity, but by and large have done so using increasingly large samples-- tens or even hundreds of thousands of individuals, whose phenotypes are thus often only superficially characterized. This, in turn, may hide the intricacies of the genetic influence on disease. GWAS findings are also usually study-population dependent. We found that genetic risk scores based on SNPs from large adult obesity studies are not predictive of the propensity to gain weight in very young children. However, using a small cohort of a few hundred children deeply characterized with growth trajectories between birth and two years, and leveraging such trajectories through novel functional data analysis (FDA) techniques, we were able to produce a strong childhood obesity genetic risk score.

genetics↗

bioRxiv2018

High inter- and intraspecific turnover of satellite repeats in great apes

BackgroundSatellite repeats are a structural component of centromeres and telomeres, and in some instances their divergence is known to drive speciation. Due to their highly repetitive nature, satellite sequences have been understudied and underrepresented in genome assemblies. To investigate their turnover in great apes, we studied satellite repeats in human, chimpanzee, bonobo, gorilla, and Sumatran and Bornean orangutans, using unassembled short and long sequencing reads.\n\nResultsThe density of satellite repeats, as identified from accurate short reads (Illumina), varied greatly among great ape genomes. These were dominated by a handful of abundant repeated motifs, frequently shared among species, which formed two groups: (1) the (AATGG)n repeat (critical for heat shock response) and its derivatives; and (2) subtelomeric 32-mers. Using the densities of abundant repeats, individuals could be classified into species. However clustering did not reproduce the accepted species phylogeny, suggesting rapid repeat evolution. Several abundant repeats were enriched in males vs. females; using existing Y chromosome assemblies or FIuorescent In Situ Hybridization, we validated location for some of them on the Y. Finally, applying a novel computational tool, we identified many satellite repeats completely embedded within long Oxford Nanopore and Pacific Biosciences reads. Such repeats were up to 59 kb in length and consisted of perfect repeats interspersed with other similar sequences.\n\nConclusionsOur results based on sequencing reads generated with three different technologies provide the first detailed characterization of great ape satellite repeats, and open new avenues for exploring their functions.

evolutionary biology↗

bioRxiv2017

Non-B DNA affects polymerization speed and error rate in sequencers and living cells

DNA conformation may deviate from the classical B-form in ~13% of the human genome. Non-B DNA regulates many cellular processes; however, its effects on DNA polymerization speed and accuracy have not been investigated genome-wide. Such an inquiry is critical for understanding neurological diseases and cancer genome instability. Here we present the first simultaneous examination of DNA polymerization kinetics and errors in the human genome sequenced with Single-Molecule-Real-Time technology. We show that polymerization speed differs between non-B and B-DNA: it decelerates at G-quadruplexes and fluctuates periodically at disease-causing tandem repeats. Analyzing polymerization kinetics profiles, we predict and validate experimentally non-B DNA formation for a novel motif. We demonstrate that several non-B motifs affect sequencing errors (e.g., G-quadruplexes increase error rates) and that sequencing errors are positively associated with polymerase slowdown. Finally, we show that highly divergent G4 motifs have pronounced polymerization slowdown and high sequencing error rates, suggesting similar mechanisms for sequencing errors and germline mutations.

genomics↗

bioRxiv2017

Infant Weight Gain Trajectories Linked To Oral Microbiome Composition

Gut and oral microbiome perturbations have been observed in obese adults and adolescents. Less is known about how weight gain in early childhood is influenced by gut, and particularly oral, microbiomes. Here we analyze the relationships among weight gain and gut and oral microbiomes in 226 two-year-olds who were followed during the first two years of life, as part of a larger study, with weight and length measured at seven time points. We used these data to identify children with rapid weight gain (a strong risk factor for childhood obesity), and to derive growth curves with novel Functional Data Analysis (FDA) techniques. The childrens oral and gut microbiomes were sampled at the end of the two-year period, and surveyed with 16S sequencing. First, we show that growth curves are associated negatively with diversity and positively with Firmicutes-to-Bacteroidetes ratio of the oral microbiome - a relationship that is also observed in children with rapid (vs. non-rapid) weight gain. We also demonstrate an association between the gut microbiome and child growth, but only when considering the effect of diet on the microbiome. Lastly, we identify several bacterial genera that are associated with child growth patterns. These results suggest that by the age of two, the oral microbiome may have already begun to establish patterns often seen in older obese individuals. They also suggest that the gut microbiome, while strongly influenced by diet, at age two does not harbor obesity signatures many researchers identified in later life stages.

genomics↗