Biology subjects

Garrison, E.

Publications and source records attributed to Garrison, E..

At least 37 records · Page 2Linked to original sources

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

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

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

Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation

1AbstractsO_ST_ABSMotivationC_ST_ABSThe Jaccard similarity on k-mer sets has shown to be a convenient proxy for sequence identity. By avoiding expensive base-level alignments and comparing reduced sequence representations, tools such as MashMap can scale to massive numbers of pairwise comparisons while still providing useful similarity estimates. However, due to their reliance on minimizer winnowing, previous versions of MashMap were shown to be biased and inconsistent estimators of Jaccard similarity. This directly impacts downstream tools that rely on the accuracy of these estimates. ResultsTo address this, we propose the minmer winnowing scheme, which generalizes the minimizer scheme by use of a rolling minhash with multiple sampled k-mers per window. We show both theoretically and empirically that minmers yield an unbiased estimator of local Jaccard similarity, and we implement this scheme in an updated version of MashMap. The minmer-based implementation is over 10 times faster than the minimizer-based version under the default ANI threshold, making it well-suited for large-scale comparative genomics applications. AvailabilityMashMap3 is available at https://github.com/marbl/MashMap Contactblk6@rice.edu, adam.phillippy@nih.gov

bioinformatics↗

bioRxiv2023

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats

The seventh iteration of the reference genome assembly for Rattus norvegicus-- mRatBN7.2--corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared to its predecessor. Gene annotations are now more complete, significantly improving the mapping precision of genomic, transcriptomic, and proteomics data sets. We jointly analyzed 163 short-read whole genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined [~]20.0 million sequence variations, of which 18.7 thousand are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.

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

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

Virgin Birth: A genetic basis for facultative parthenogenesis

Sexual reproduction evolved 1-2 billion years ago and underlies the biodiversity of our planet. Nevertheless, devolution of sexual into asexual reproduction can occur across all phyla of the animal kingdom. The genetic basis for how parthenogenesis can arise is completely unknown. To understand the mechanism and benefits of parthenogenesis, we have sequenced the genome of the facultative parthenogen, Drosophila mercatorum, and compared its organisation and expression pattern during parthenogenetic or sexual reproduction. We identified three genes, desat2, Myc, and polo in parthenogenetic D. mercatorum that when mis-regulated in a non-parthenogenetic species, D. melanogaster, enable facultative parthenogenetic reproduction. This simple genetic switch leads us to propose that sporadic facultative parthenogenesis could evolve as an escape route preserving the genetic lineage in the face of sexual isolation.

evolutionary biology↗

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↗

bioRxiv2021

ODGI: understanding pangenome graphs

MotivationPangenome graphs provide a complete representation of the mutual alignment of collections of genomes. These models offer the opportunity to study the entire genomic diversity of a population, including structurally complex regions. Nevertheless, analyzing hundreds of gigabase-scale genomes using pangenome graphs is difficult as it is not well-supported by existing tools. Hence, fast and versatile software is required to ask advanced questions to such data in an efficient way. ResultsWe wrote ODGI, a novel suite of tools that implements scalable algorithms and has an efficient in-memory representation of DNA pangenome graphs in the form of variation graphs. ODGI supports pre-built graphs in the Graphical Fragment Assembly format. ODGI includes tools for detecting complex regions, extracting pangenomic loci, removing artifacts, exploratory analysis, manipulation, validation, and visualization. Its fast parallel execution facilitates routine pangenomic tasks, as well as pipelines that can quickly answer complex biological questions of gigabase-scale pangenome graphs. AvailabilityODGI is published as free software under the MIT open source license. Source code can be downloaded from https://github.com/pangenome/odgi and documentation is available at https://odgi.readthedocs.io. ODGI can be installed via Bioconda https://bioconda.github.io/recipes/odgi/README.html or GNU Guix https://github.com/pangenome/odgi/blob/master/guix.scm. Contactegarris5@uthsc.edu

genomics↗

bioRxiv2021

Chemical inhibition of pathological reactive astrocytes promotes neural protection

Disease, injury, and aging induce reactive astrocyte states with pathological functions1-4. In neurodegenerative diseases, inflammatory reactive astrocytes are abundant and contribute to progressive cell loss. Modulating the state or function of these reactive astrocytes thereby represents an attractive therapeutic goal5,6. Leveraging a cellular phenotypic screening platform, we show that chemical inhibitors of HDAC3 effectively block pathological astrocyte reactivity. Inhibition of HDAC3 reduces molecular and functional features of reactive astrocytes in vitro including inflammatory gene expression, cytokine secretion, and antigen presentation. Transcriptional and chromatin mapping studies show that HDAC3 inhibition mediates a switch between pro-inflammatory and anti-inflammatory states, which disarms the pathological functions of reactive astrocytes. Systemic administration of a blood-brain barrier penetrant chemical inhibitor of HDAC3, RGFP966, blocks reactive astrocyte formation and promotes axonal protection in vivo. Collectively, these results establish a platform for discovering chemical modulators of reactive astrocyte states, inform the mechanisms controlling astrocyte reactivity, and demonstrate the therapeutic potential of modulating astrocyte reactivity for neurodegenerative diseases.

neuroscience↗

bioRxiv2021

The complete sequence of a human genome

In 2001, Celera Genomics and the International Human Genome Sequencing Consortium published their initial drafts of the human genome, which revolutionized the field of genomics. While these drafts and the updates that followed effectively covered the euchromatic fraction of the genome, the heterochromatin and many other complex regions were left unfinished or erroneous. Addressing this remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium has finished the first truly complete 3.055 billion base pair (bp) sequence of a human genome, representing the largest improvement to the human reference genome since its initial release. The new T2T-CHM13 reference includes gapless assemblies for all 22 autosomes plus Chromosome X, corrects numerous errors, and introduces nearly 200 million bp of novel sequence containing 2,226 paralogous gene copies, 115 of which are predicted to be protein coding. The newly completed regions include all centromeric satellite arrays and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies for the first time.

genomics↗

bioRxiv2021

Vcflib and tools for processing the VCF variant call format

Since its introduction in 2011 the variant call format (VCF) has been widely adopted for processing DNA and RNA variants in practically all population studies -- as well as in somatic and germline mutation studies. VCF can present single nucleotide variants, multi-nucleotide variants, insertions and deletions, and simple structural variants called against a reference genome. Here we present over 125 useful and much used free and open source software tools and libraries, part of vcflib tools and bio-vcf. We also highlight cyvcf2, hts-nim and slivar tools. Application is typically in the comparison, filtering, normalisation, smoothing, annotation, statistics, visualisation and exporting of variants. Our tools run daily and invisibly in pipelines and countless shell scripts. Our tools are part of a wider bioinformatics ecosystem and we consider it very important to make these tools available as free and open source software to all bioinformaticians so they can be deployed through software distributions, such as Debian, GNU Guix and Bioconda. vcflib, for example, was installed over 40,000 times and bio-vcf was installed over 15,000 times through Bioconda by December 2020. We shortly discuss the design of VCF, lessons learnt, and how we can address more complex variation that can not easily be represented by the VCF format. All source code is published under free and open source software licenses and can be downloaded and installed from https://github.com/vcflib. Author summaryMost bioinformatics workflows deal with DNA/RNA variations that are typically represented in the variant call format (VCF) -- a file format that describes mutations (SNP and MNP), insertions and deletions (INDEL) against a reference genome. Here we present a wide range of free and open source software tools that are used in biomedical sequencing workflows around the world today.

bioinformatics↗

bioRxiv2021

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs

Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our novel toolchain can construct spliced pangenome graphs, map RNA-seq data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. This workflow improves accuracy over state-of-the-art RNA-seq mapping methods, and it can efficiently quantify haplotype-specific transcript expression without needing to characterize a samples haplotypes beforehand.

bioinformatics↗