Biology subjects

Guarracino, A.

Publications and source records attributed to Guarracino, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Epigenetic control and inheritance of rDNA arrays

Ribosomal RNA (rRNA) genes exist in multiple copies arranged in tandem arrays known as ribosomal DNA (rDNA). The total number of gene copies is variable, and the mechanisms buffering this copy number variation remain unresolved. We surveyed the number, distribution, and activity of rDNA arrays at the level of individual chromosomes across multiple human and primate genomes. Each individual possessed a unique fingerprint of copy number distribution and activity of rDNA arrays. In some cases, entire rDNA arrays were transcriptionally silent. Silent rDNA arrays showed reduced association with the nucleolus and decreased interchromosomal interactions, indicating that the nucleolar organizer function of rDNA depends on transcriptional activity. Methyl-sequencing of flow-sorted chromosomes, combined with long read sequencing, showed epigenetic modification of rDNA promoter and coding region by DNA methylation. Silent arrays were in a closed chromatin state, as indicated by the accessibility profiles derived from Fiber-seq. Removing DNA methylation restored the transcriptional activity of silent arrays. Array activity status remained stable through the iPS cell re-programming. Family trio analysis demonstrated that the inactive rDNA haplotype can be traced to one of the parental genomes, suggesting that the epigenetic state of rDNA arrays may be heritable. We propose that the dosage of rRNA genes is epigenetically regulated by DNA methylation, and these methylation patterns specify nucleolar organizer function and can propagate transgenerationally.

genomics↗

bioRxiv2024

A familial, telomere-to-telomere reference for human de novo mutation and recombination from a four-generation pedigree

Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assess de novo mutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5 de novo single-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6 de novo indels or structural variants (SVs) originating from tandem repeats, 7.7 centromeric de novo SVs and SNVs, and 12.4 de novo Y chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documenting de novo SVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% of de novo SNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map ([~]3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations and de novo SVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available "truth set" of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.

genomics↗

bioRxiv2024

Complete sequencing of ape genomes

We present haplotype-resolved reference genomes and comparative analyses of six ape species, namely: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan, and siamang. We achieve chromosome-level contiguity with unparalleled sequence accuracy (<1 error in 500,000 base pairs), completely sequencing 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, providing more in-depth evolutionary insights. Comparative analyses, including human, allow us to investigate the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference. This includes newly minted gene families within lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes, and subterminal heterochromatin. This resource should serve as a definitive baseline for all future evolutionary studies of humans and our closest living ape relatives.

genomics↗

bioRxiv2024

Cluster efficient pangenome graph construction with nf-core/pangenome

MotivationPangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time. ResultsTo overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-cores best practices. Leveraging biocontainers ensures portability and seamless deployment in HPC environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 E. coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. Availabilitynf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/1.1.2/docs/usage. Contactsimon.heumos@qbic.uni-tuebingen.de, sven.nahnsen@qbic.uni-tuebingen.de

bioinformatics↗

bioRxiv2024

Gapless assembly of complete human and plant chromosomes using only nanopore sequencing

The combination of ultra-long Oxford Nanopore (ONT) sequencing reads with long, accurate PacBio HiFi reads has enabled the completion of a human genome and spurred similar efforts to complete the genomes of many other species. However, this approach for complete, "telomere-to-telomere" genome assembly relies on multiple sequencing platforms, limiting its accessibility. ONT "Duplex" sequencing reads, where both strands of the DNA are read to improve quality, promise high per-base accuracy. To evaluate this new data type, we generated ONT Duplex data for three widely-studied genomes: human HG002, Solanum lycopersicum Heinz 1706 (tomato), and Zea mays B73 (maize). For the diploid, heterozygous HG002 genome, we also used "Pore-C chromatin contact mapping to completely phase the haplotypes. We found the accuracy of Duplex data to be similar to HiFi sequencing, but with read lengths tens of kilobases longer, and the Pore-C data to be compatible with existing diploid assembly algorithms. This combination of read length and accuracy enables the construction of a high-quality initial assembly, which can then be further resolved using the ultra-long reads, and finally phased into chromosome-scale haplotypes with Pore-C. The resulting assemblies have a base accuracy exceeding 99.999% (Q50) and near-perfect continuity, with most chromosomes assembled as single contigs. We conclude that ONT sequencing is a viable alternative to HiFi sequencing for de novo genome assembly, and has the potential to provide a single-instrument solution for the reconstruction of complete genomes.

bioinformatics↗

bioRxiv2024

Genetic Modulation of Protein Expression in Rat Brain

Genetic variations in protein expression are implicated in a broad spectrum of common diseases and complex traits. However, the fundamental genetic architecture and variation of protein expression have received comparatively less attention than either mRNA or classical phenotypes. In this study, we systematically quantified proteins in the brains of a large family of rats using tandem mass tag (TMT)-based quantitative mass-spectrometry (MS) technology. We identified and quantified a comprehensive proteome of 8,119 proteins from Spontaneously Hypertensive (SHR/Olalpcv), Brown Norway with polydactyly-luxate (BN-Lx/Cub), and 29 of their fully inbred HXB/BXH progeny. Differential expression (DE) analysis identified 597 proteins with significant differences in expression between the parental strains (fold change > 2 and FDR < 0.01). We characterized 95 variant peptides by proteogenomics approach and discovered 464 proteins linked to strong cis-acting quantitative trait loci (pQTLs, FDR < 0.05). We also explored the linkage of pQTLs with behavioral phenotypes in rats and examined the sex-specific pQTLs to reveal both distinct and shared cis-pQTLs between sexes. Furthermore, by creating a novel view of the rat pangenome, we improved the ability to pinpoint candidate genes underlying pQTL. Finally, we explored the connection between the pQTLs in rat and human disorders, underscoring the translational potential of our findings. Collectively, this work demonstrates the value of large and systematic proteo-genetic datasets in understanding protein modulation in the brain and its functional linkage to complex central nervous system (CNS) traits.

genetics↗

bioRxiv2024

Global diversity, recurrent evolution, and recent selection on amylase structural haplotypes in humans

The adoption of agriculture, first documented [~]12,000 years ago in the Fertile Crescent, triggered a rapid shift toward starch-rich diets in human populations. Amylase genes facilitate starch digestion and increased salivary amylase copy number has been observed in some modern human populations with high starch intake, though evidence of recent selection is lacking. Here, using 52 long-read diploid assemblies and short read data from [~]5,600 contemporary and ancient humans, we resolve the diversity, evolutionary history, and selective impact of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in populations with agricultural subsistence compared to fishing, hunting, and pastoral groups. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each exhibit multiple duplications/deletions with mutation rates >10,000-fold the SNP mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome graph-based approach to infer structural haplotypes across thousands of humans, we identify extensively duplicated haplotypes present at higher frequencies in modern day populations with traditionally agricultural diets. Leveraging 533 ancient human genomes we find that duplication-containing haplotypes (i.e. haplotypes with more amylase gene copies than the ancestral haplotype) have increased in frequency more than seven-fold over the last 12,000 years providing evidence for recent selection in West Eurasians. Together, our study highlights the potential impacts of the agricultural revolution on human genomes and the importance of long-read sequencing in identifying signatures of selection at structurally complex loci.

evolutionary biology↗

bioRxiv2024

Pangenome reconstruction in rats enhances genotype-phenotype mapping and novel variant discovery

The HXB/BXH family of recombinant inbred rat strains is a unique genetic resource that has been extensively phenotyped over 25 years, resulting in a vast dataset of quantitative molecular and physiological phenotypes. We built a pangenome graph from 10x Genomics Linked-Read data for 31 recombinant inbred rats to study genetic variation and association mapping. The pangenome includes 0.2Gb of sequence that is not present the reference mRatBN7.2, confirming the capture of substantial additional variation. We validated variants in challenging regions, including complex structural variants resolving into multiple haplotypes. Phenome-wide association analysis of validated SNPs uncovered variants associated with glucose/insulin levels and hippocampal gene expression. We propose an interaction between Pirl1l1, chromogranin expression, TNF- levels, and insulin regulation. This study demonstrates the utility of linked-read pangenomes for comprehensive variant detection and mapping phenotypic diversity in a widely used rat genetic reference panel.

genomics↗

bioRxiv2023

The complete human diploid reference genome of RPE-1 identifies the phased epigenetic landscapes from multi-omics data

Comparative analysis of recent human genome assemblies highlights profound sequence divergence that peaks within polymorphic loci such as centromeres. This raises the question about the adequacy of relying on human reference genomes to accurately analyze sequencing data derived from experimental cell lines. Here, we generated the complete diploid genome assembly for the human retinal epithelial cells (RPE-1), a widely used non-cancer laboratory cell line with a stable karyotype, to use as matched reference for multi-omics sequencing data analysis. Our RPE1v1.0 assembly presents completely phased haplotypes and chromosome-level scaffolds that span centromeres with ultra-high base accuracy (>QV60). We mapped the haplotype-specific genomic variation specific to this cell line including t(Xq;10q), a stable 73.18 Mb duplication of chromosome 10 translocated onto the microdeleted chromosome X telomere t(Xq;10q). Polymorphisms between haplotypes of the same genome reveals genetic and epigenetic variation for all chromosomes, especially at centromeres. The RPE-1 assembly as matched reference genome improves mapping quality of multi-omics reads originating from RPE-1 cells with drastic reduction in alignments mismatches compared to using the most complete human reference to date (CHM13). Leveraging the accuracy achieved using a matched reference, we were able to identify the kinetochore sites at base pair resolution and show unprecedented variation between haplotypes. This work showcases the use of matched reference genomes for multi-omics analyses and serves as the foundation for a call to comprehensively assemble experimentally relevant cell lines for widespread application. HighlightsO_LIWe generated the complete phased genome assembly of one of the most widely used non-cancer cell lines (RPE-1) with a stable diploid karyotype C_LIO_LIWe used this genome as a matched reference to analyze sequencing data from RPE-1 C_LIO_LIMapping to the RPE1v1.0 genome improves alignment quality, faithful assignment of reads to each haplotype, and epigenome peak calling accuracy uncovering inter-haplotype variation C_LIO_LIUse of the matched reference genome enables epigenetic precision in identifying for the first time the kinetochore site at base pair resolution for each haplotype C_LIO_LIThe RPE-1 genome represents a new telomere-to-telomere (T2T) human diploid reference for the scientific community that will advance genetic and epigenetic research across fields using this cell line C_LI

genomics↗

bioRxiv2023

Pangenome graph layout by Path-Guided Stochastic Gradient Descent

MotivationThe increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genomic similarity and diversity between multiple genomes. In order to understand them, we need to see them. For visualization, we need a human readable graph layout: A graph embedding in low (e.g. two) dimensional depictions. Due to a pangenome graphs potential excessive size, this is a significant challenge. ResultsIn response, we introduce a novel graph layout algorithm: the Path-Guided Stochastic Gradient Descent (PG-SGD). PG-SGD uses the genomes, represented in the pangenome graph as paths, as an embedded positional system to sample genomic distances between pairs of nodes. This avoids the quadratic cost seen in previous versions of graph drawing by Stochastic Gradient Descent (SGD). We show that our implementation efficiently computes the low dimensional layouts of gigabase-scale pangenome graphs, unveiling their biological features. AvailabilityWe integrated PG-SGD in ODGI which is released as free software under the MIT open source license. Source code is available at https://github.com/pangenome/odgi. Contactegarris5@uthsc.edu

bioinformatics↗

bioRxiv2023

A reference-unbiased super-pangenome of the North American wild grape species (Vitis spp.) reveals genus-wide association with adaptive traits

Capturing the genetic diversity of wild relatives is crucial for improving crops because wild species are valuable sources of agronomic traits that are essential to enhance the sustainability and adaptability of domesticated cultivars. Genetic diversity across a genus can be captured in super-pangenomes, which provide a framework for interpreting genomic variations. Here we report the sequencing, assembly, and annotation of nine wild North American grape genomes, which were phased and scaffolded at chromosome scale. We generate a reference-unbiased super-pangenome using pairwise whole-genome alignment methods, revealing the extent of the genomic diversity among wild grape species from sequence to gene level. The pangenome graph captures genomic variation between haplotypes within a species and across the different species, and it accurately assesses the similarity of hybrids to their parents. The species selected to build the pangenome are a great representation of the genus, as illustrated by capturing known allelic variants in the sex-determining region and for Pierces disease resistance loci. Using pangenome-wide association analysis, we demonstrate the utility of the super-pangenome by effectively mapping short-reads from genus-wide samples and identifying loci associated with salt tolerance in natural populations of grapes. This study highlights how a reference-unbiased super-pangenome can reveal the genetic basis of adaptive traits from wild relatives and accelerate crop breeding research.

genomics↗

bioRxiv2023

Building pangenome graphs

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder (PGGB), a pipeline for constructing pangenome graphs without bias or exclusion. PGGB uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.

bioinformatics↗

bioRxiv2022

The complete sequence of a human Y chromosome

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure including long palindromes, tandem repeats, and segmental duplications1-3. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished4, 5. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029 base pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, revealing the complete ampliconic structures of TSPY, DAZ, and RBMY gene families; 41 additional protein-coding genes, mostly from the TSPY family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a prior assembly of the CHM13 genome4 and mapped available population variation, clinical variants, and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

genomics↗

bioRxiv2022

Recombination between heterologous human acrocentric chromosomes

The short arms of the human acrocentric chromosomes 13, 14, 15, 21, and 22 share large homologous regions, including the ribosomal DNA repeats and extended segmental duplications (Floutsakou et al. 2013; van Sluis et al. 2019). While the complete assembly of these regions in the Telomere-to-Telomere consortiums CHM13 provided a model of their homology (Nurk et al. 2022), it remained unclear if these patterns were ancestral or maintained by ongoing recombination exchange. Here, we show that acrocentric chromosomes contain pseudo-homologous regions (PHRs) indicative of recombination between non-homologs. Considering an all-to-all comparison of the high-quality human pangenome from the Human Pangenome Reference Consortium (HPRC) (Liao et al. 2022), we find that contigs from all of the acrocentric short arms form a community similar to those formed by single chromosomes or the sex chromosome pair. A variation graph (Garrison et al. 2018) constructed from centromere-spanning acrocentric contigs indicates the presence of regions where most contigs appear nearly identical between heterologous CHM13 acrocentrics. Except on chromosome 15, we observe faster decay of linkage disequilibrium in the PHRs than in the corresponding short and long arms, indicating higher rates of recombination (N. Li and Stephens 2003; Huttley et al. 1999). The PHRs include sequences previously shown to lie at the breakpoint of Robertsonian translocations (Jarmuz-Szymczak et al. 2014), and we show that their arrangement is compatible with crossover in inverted duplications on chromosomes 13, 14, and 21. The ubiquity of signals of recombination between heterologous chromosomes seen in the HPRC draft pangenomes acrocentric assemblies suggests that these shared sequences form the basis for recurrent Robertsonian translocations, providing sequence and population-based confirmation of hypotheses first developed cytogenetically fifty years ago (Hamerton et al. 1975).

genomics↗

bioRxiv2022

A Draft Human Pangenome Reference

The Human Pangenome Reference Consortium (HPRC) presents a first draft human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals. These assemblies cover more than 99% of the expected sequence and are more than 99% accurate at the structural and base-pair levels. Based on alignments of the assemblies, we generated a draft pangenome that captures known variants and haplotypes, reveals novel alleles at structurally complex loci, and adds 119 million base pairs of euchromatic polymorphic sequence and 1,529 gene duplications relative to the existing reference, GRCh38. Roughly 90 million of the additional base pairs derive from structural variation. Using our draft pangenome to analyze short-read data reduces errors when discovering small variants by 34% and boosts the detected structural variants per haplotype by 104% compared to GRCh38-based workflows, and by 34% compared to using previous diversity sets of genome assemblies.

genomics↗

bioRxiv2022

Optimal gap-affine alignment in O(s) space

MotivationPairwise sequence alignment remains a fundamental problem in computational biology and bioinformatics. Recent advances in genomics and sequencing technologies demand faster and scalable algorithms that can cope with the ever-increasing sequence lengths. Classical pairwise alignment algorithms based on dynamic programming are strongly limited by quadratic requirements in time and memory. The recently proposed wavefront alignment algorithm (WFA) introduced an efficient algorithm to perform exact gap-affine alignment in O(ns) time, where s is the optimal score and n is the sequence length. Notwithstanding these bounds, WFAs O(s2) memory requirements become computationally impractical for genome-scale alignments, leading to a need for further improvement. ResultsIn this paper, we present the bidirectional WFA algorithm (BiWFA), the first gap-affine algorithm capable of computing optimal alignments in O(s) memory while retaining WFAs time complexity of O(ns). As a result, this work improves the lowest known memory bound O(n) to compute gap-affine alignments. In practice, our implementation never requires more than a few hundred MBs aligning noisy Oxford Nanopore Technologies reads up to 1 Mbp long while maintaining competitive execution times. AvailabilityAll code is publicly available at https://github.com/smarco/BiWFA-paper Contactsantiagomsola@gmail.com

bioinformatics↗

bioRxiv2022

Automated assembly of high-quality diploid human reference genomes

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has greatly benefited society1, 2. However, it still has many gaps and errors, and does not represent a biological human genome since it is a blend of multiple individuals3, 4. Recently, a high-quality telomere-to-telomere reference genome, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a duplicate genome, and is thus nearly homozygous5. To address these limitations, the Human Pangenome Reference Consortium (HPRC) recently formed with the goal of creating a collection of high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversity6. Here, in our first scientific report, we determined which combination of current genome sequencing and automated assembly approaches yields the most complete, accurate, and cost-effective diploid genome assemblies with minimal manual curation. Approaches that used highly accurate long reads and parent-child data to sort haplotypes during assembly outperformed those that did not. Developing a combination of all the top performing methods, we generated our first high- quality diploid reference assembly, containing only [~]4 gaps (range 0-12) per chromosome, most within + 1% of CHM13s length. Nearly 1/4th of protein coding genes have synonymous amino acid changes between haplotypes, and centromeric regions showed the highest density of variation. Our findings serve as a foundation for assembling near-complete diploid human genomes at the scale required for constructing a human pangenome reference that captures all genetic variation from single nucleotides to large structural rearrangements.

genomics↗

bioRxiv2022

Unbiased pangenome graphs

MotivationPangenome variation graphs model the mutual alignment of collections of DNA sequences. A set of pairwise alignments implies a variation graph, but there are no scalable methods to generate such a graph from these alignments. Existing related approaches depend on a single reference, a specific ordering of genomes, or a de Bruijn model based on a fixed k-mer length. A scalable, self-contained method to build pangenome graphs without such limitations would be a key step in pangenome construction and manipulation pipelines. ResultsWe design the seqwish algorithm, which builds a variation graph from a set of sequences and alignments between them. We first transform the alignment set into an implicit interval tree. To build up the variation graph, we query this tree-based representation of the alignments to reduce transitive matches into single DNA segments in a sequence graph. By recording the mapping from input sequence to output graph, we can trace the original paths through this graph, yielding a pangenome variation graph. We present an implementation that operates in external memory, using disk-backed data structures and lock-free parallel methods to drive the core graph induction step. We demonstrate that our method scales to very large graph induction problems by applying it to build pangenome graphs for several species. Availabilityseqwish is published as free software under the MIT open source license. Source code and documentation are available at https://github.com/ekg/seqwish. seqwish can be installed via Bioconda https://bioconda.github.io/recipes/seqwish/README.html or GNU Guix https://github.com/ekg/guix-genomics/blob/master/seqwish.scm. Contactegarris5@uthsc.edu

bioinformatics↗