Biology subjects

Haussler, D.

Publications and source records attributed to Haussler, D..

52 records · Page 3Linked to original sources

bioRxiv2019

Progressive alignment with Cactus: a multiple-genome aligner for the thousand-genome era

Cactus, a reference-free multiple genome alignment program, has been shown to be highly accurate, but the existing implementation scales poorly with increasing numbers of genomes, and struggles in regions of highly duplicated sequence. We describe progressive extensions to Cactus that enable reference-free alignment of tens to thousands of large vertebrate genomes while maintaining high alignment quality. We show that Cactus is capable of scaling to hundreds of genomes and beyond by describing results from an alignment of over 600 amniote genomes, which is to our knowledge the largest multiple vertebrate genome alignment yet created. Further, we show improvements in orthology resolution leading to downstream improvements in annotation.

genomics↗

bioRxiv2019

Framework for determining accuracy of RNA sequencing data for gene expression profiling of single samples

BackgroundThe accuracy of gene expression as measured by RNA sequencing (RNA-Seq) is dependent on the amount of sequencing performed. However, some types of reads are not informative for determining this accuracy. Unmapped and non-exonic reads do not contribute to gene expression quantification. Duplicate reads can be the product of high gene expression or technical errors. FindingsWe surveyed bulk RNA-Seq datasets from 2179 tumors in 48 cohorts to determine the fractions of uninformative reads. Total sequence depth was 0.2-668 million reads (median (med.) 61 million; interquartile range (IQR) 53 million). Unmapped reads constitute 1-77% of all reads (med. 3%; IQR 3%); duplicate reads constitute 3-100% of mapped reads (med. 27%; IQR 30%); and non-exonic reads constitute 4-97% of mapped, non-duplicate reads (med. 25%; IQR 21%). Informative reads--Mapped, Exonic, Non-duplicate (MEND) reads--constitute 0-79% of total reads (med. 50%; IQR 31%). Further, we find that MEND read counts have a 0.22 Pearson correlation to the number of genes expressed above 1 Transcript Per Million, while total reads have a correlation of -0.05. ConclusionsSince the fraction of uninformative reads vary, we propose using only definitively informative reads, MEND reads, for the purposes of asserting the accuracy of gene expression measured in a bulk RNA-Seq experiment. We provide a Docker image containing 1) the existing required tools (RSeQC, sambamba and samblaster) and 2) a custom script. We recommend that all results, sensitivity studies and depth recommendations use MEND units.

genomics↗

bioRxiv2019

Efficient de novo assembly of eleven human genomes using PromethION sequencing and a novel nanopore toolkit

Present workflows for producing human genome assemblies from long-read technologies have cost and production time bottlenecks that prohibit efficient scaling to large cohorts. We demonstrate an optimized PromethION nanopore sequencing method for eleven human genomes. The sequencing, performed on one machine in nine days, achieved an average 63x coverage, 42 Kb read N50, 90% median read identity and 6.5x coverage in 100 Kb+ reads using just three flow cells per sample. To assemble these data we introduce new computational tools: Shasta - a de novo long read assembler, and MarginPolish & HELEN - a suite of nanopore assembly polishing algorithms. On a single commercial compute node Shasta can produce a complete human genome assembly in under six hours, and MarginPolish & HELEN can polish the result in just over a day, achieving 99.9% identity (QV30) for haploid samples from nanopore reads alone. We evaluate assembly performance for diploid, haploid and trio-binned human samples in terms of accuracy, cost, and time and demonstrate improvements relative to current state-of-the-art methods in all areas. We further show that addition of proximity ligation (Hi-C) sequencing yields near chromosome-level scaffolds for all eleven genomes.

bioinformatics↗

bioRxiv2019

ProTECT: Prediction of T-cell Epitopes for Cancer Therapy

Somatic mutations in cancers affecting protein coding genes can give rise to potentially therapeutic neoepitopes. These neoepitopes can guide Adoptive Cell Therapies (ACTs) and Peptide Vaccines (PVs) to selectively target tumor cells using autologous patient cytotoxic T-cells. Currently, researchers have to independently align their data, call somatic mutations and haplotype the patients HLA to use existing neoepitope prediction tools. We present ProTECT, a fully automated, reproducible, scalable, and efficient end-to-end analysis pipeline to identify and rank therapeutically relevant tumor neoepitopes in terms of immunogenicity starting directly from raw patient sequencing data, or from pre-processed data. The ProTECT pipeline encompasses alignment, HLA haplotyping, mutation calling (single nucleotide variants, short insertions and deletions, and gene fusions), peptide:MHC (pMHC) binding prediction, and ranking of final candidates. We demonstrate ProTECT on 326 samples from the TCGA Prostate Adenocarcinoma cohort, and compare it with published tools. ProTECT can be run on a standalone computer, a local cluster, or on a compute cloud using a Mesos backend. ProTECT is highly scalable and can process TCGA data in under 30 minutes per sample when run in large batches. ProTECT is freely available at https://www.github.com/BD2KGenomics/protect.

bioinformatics↗

bioRxiv2018

Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution

Direct comparisons of human and non-human primate brain tissue have the potential to reveal molecular pathways underlying remarkable specializations of the human brain. However, chimpanzee tissue is largely inaccessible during neocortical neurogenesis when differences in brain size first appear. To identify human-specific features of cortical development, we leveraged recent innovations that permit generating pluripotent stem cell-derived cerebral organoids from chimpanzee. First, we systematically evaluated the fidelity of organoid models to primary human and macaque cortex, finding organoid models preserve gene regulatory networks related to cell types and developmental processes but exhibit increased metabolic stress. Second, we identified 261 genes differentially expressed in human compared to chimpanzee organoids and macaque cortex. Many of these genes overlap with human-specific segmental duplications and a subset suggest increased PI3K/AKT/mTOR activation in human outer radial glia. Together, our findings establish a platform for systematic analysis of molecular changes contributing to human brain development and evolution.

developmental biology↗

bioRxiv2018

The UCSC Repeat Browser allows discovery and visualization of evolutionary conflict across repeat families

BackgroundNearly half the human genome consists of repeat elements, most of which are retrotransposons, and many of these sequences play important biological roles. However repeat elements pose several unique challenges to current bioinformatic analyses and visualization tools, as short repeat sequences can map to multiple genomic loci resulting in their misclassification and misinterpretation. In fact, sequence data mapping to repeat elements are often discarded from analysis pipelines. Therefore, there is a continued need for standardized tools and techniques to interpret genomic data of repeats. ResultsWe present the UCSC Repeat Browser, which consists of a complete set of human repeat reference sequences derived from the gold standard repeat database RepeatMasker. The UCSC Repeat Browser contains mapped annotations from the human genome to these references, and presents all of them as a comprehensive interface to facilitate work with repetitive elements. Furthermore, it provides processed tracks of multiple publicly available datasets of biological interest to the repeat community, including ChIP-SEQ datasets for KRAB Zinc Finger Proteins (KZNFs) - a family of proteins known to bind and repress certain classes of repeats. Here we show how the UCSC Repeat Browser in combination with these datasets, as well as RepeatMasker annotations in several non-human primates, can be used to trace the independent trajectories of species-specific evolutionary conflicts. ConclusionsThe UCSC Repeat Browser allows easy and intuitive visualization of genomic data on consensus repeat elements, circumventing the problem of multi-mapping, in which sequencing reads of repeat elements map to multiple locations on the human genome. By developing a reference consensus, multiple datasets and annotation tracks can easily be overlaid to reveal complex evolutionary histories of repeats in a single interactive window. Specifically, we use this approach to retrace the history of several primate specific LINE-1 families across apes, and discover several species-specific routes of evolution that correlate with the emergence and binding of KZNFs.

genomics↗

bioRxiv2018

KRAB Zinc Finger Proteins coordinate across evolutionary time scales to battle retroelements

KRAB Zinc Finger Proteins (KZNFs) are the largest and fastest evolving family of human transcription factors1,2. The evolution of this protein family is closely linked to the tempo of retrotransposable element (RTE) invasions, with specific KZNF family members demonstrated to transcriptionally repress specific families of RTEs3,4. The competing selective pressures between RTEs and the KZNFs results in evolutionary arms races whereby KZNFs evolve to recognize RTEs, while RTEs evolve to escape KZNF recognition5. Evolutionary analyses of the primate-specific RTE family L1PA and two of its KZNF binders, ZNF93 and ZNF649, reveal specific nucleotide and amino changes consistent with an arms race scenario. Our results suggest a model whereby ZNF649 and ZNF93 worked together to target independent motifs within the L1PA RTE lineage. L1PA elements eventually escaped the concerted action of this KZNF \"team\" over [~]30 million years through two distinct mechanisms: a slow accumulation of point mutations in the ZNF649 binding site and a rapid, massive deletion of the entire ZNF93 binding site.

evolutionary biology↗

bioRxiv2018

The UCSC Xena Platform for cancer genomics data visualization and interpretation

UCSC Xena is a visual exploration resource for both public and private omics data, supported through the web-based Xena Browser and multiple turn-key Xena Hubs. This unique archecture allows researchers to view their own data securely, using private Xena Hubs, simultaneously visualizing large public cancer genomics datasets, including TCGA and the GDC. Data integration occurs only within the Xena Browser, keeping private data private. Xena supports virtually any functional genomics data, including SNVs, INDELs, large structural variants, CNV, expression, DNA methylation, ATAC-seq signals, and phenotypic annotations. Browser features include the Visual Spreadsheet, survival analyses, powerful filtering and subgrouping, statistical analyses, genomic signatures, and bookmarks. Xena differentiates itself from other genomics tools, including its predecessor, the UCSC Cancer Genomics Browser, by its ability to easily and securely view public and private data, its high performance, its broad data type support, and many unique features.

cancer biology↗

bioRxiv2017

Structurally conserved primate lncRNAs are transiently expressed during human cortical differentiation and influence cell type specific genes

The cerebral cortex has expanded in size and complexity in primates, yet the underlying molecular mechanisms are obscure. We generated cortical organoids from human, chimpanzee, orangutan, and rhesus pluripotent stem cells and sequenced their transcriptomes at weekly time points for comparative analysis. We used transcript structure and expression conservation to discover thousands of expressed long non-coding RNAs (lncRNAs). Of 2,975 human, multi-exonic lncRNAs, 2,143 were structurally conserved to chimpanzee, 1,731 to orangutan, and 1,290 to rhesus. 386 human lncRNAs were transiently expressed (TrEx) and a similar expression pattern was often observed in great apes (46%) and rhesus (31%). Many TrEx lncRNAs were associated with neuroepithelium, radial glia, or Cajal-Retzius cells by single cell RNA-sequencing. 3/8 tested by ectopic expression showed [≥]2-fold effects on neural genes. This rich resource of primate expression data in early cortical development provides a framework for identifying new, potentially functional lncRNAs.

neuroscience↗

bioRxiv2017

Comparative Annotation Toolkit (CAT) - simultaneous clade and personal genome annotation

The recent introductions of low-cost, long-read, and read-cloud sequencing technologies coupled with intense efforts to develop efficient algorithms have made affordable, high-quality de novo sequence assembly a realistic proposition. The result is an explosion of new, ultra-contiguous genome assemblies. To compare these genomes we need robust methods for genome annotation. We describe the fully open source Comparative Annotation Toolkit (CAT), which provides a flexible way to simultaneously annotate entire clades and identify orthology relationships. We show that CAT can be used to improve annotations on the rat genome, annotate the great apes, annotate a diverse set of mammals, and annotate personal, diploid human genomes. We demonstrate the resulting discovery of novel genes, isoforms and structural variants, even in genomes as well studied as rat and the great apes, and how these annotations improve cross-species RNA expression experiments.

bioinformatics↗

bioRxiv2017

Combining accurate tumour genome simulation with crowd sourcing to benchmark somatic structural variant detection

BackgroundThe phenotypes of cancer cells are driven in part by somatic structural variants. Structural variants can initiate tumors, enhance their aggressiveness and provide unique therapeutic opportunities. Whole-genome sequencing of tumors can allow exhaustive identification of the specific structural variants present in an individual cancer, facilitating both clinical diagnostics and the discovery of novel mutagenic mechanisms. A plethora of somatic structural variant detection algorithms have been created to enable these discoveries, however there are no systematic benchmarks of them. Rigorous performance evaluation of somatic structural variant detection methods has been challenged by the lack of gold-standards, extensive resource requirements and difficulties arising from the need to share personal genomic information.\n\nResultsTo facilitate structural variant detection algorithm evaluations, we create a robust simulation framework for somatic structural variants by extending the BAMSurgeon algorithm. We then organize and enable a crowd-sourced benchmarking within the ICGC-TCGA DREAM Somatic Mutation Calling Challenge (SMC-DNA). We report here the results of structural variant benchmarking on three different tumors, comprising 204 submissions from 15 teams. In addition to ranking methods, we identify characteristic error-profiles of individual algorithms and general trends across them. Surprisingly, we find that ensembles of analysis pipelines do not always outperform the best individual method, indicating a need for new ways to aggregate somatic structural variant detection approaches.\n\nConclusionsThe synthetic tumors and somatic structural variant detection leaderboards remain available as a community benchmarking resource, and BAMSurgeon is available at https://github.com/adamewing/bamsurgeon.

bioinformatics↗

bioRxiv2017

Human-specific NOTCH-like genes in a region linked to neurodevelopmental disorders affect cortical neurogenesis

Genetic changes causing dramatic brain size expansion in human evolution have remained elusive. Notch signaling is essential for radial glia stem cell proliferation and a determinant of neuronal number in the mammalian cortex. We find three paralogs of human-specific NOTCH2NL are highly expressed in radial glia cells. Functional analysis reveals different alleles of NOTCH2NL have varying potencies to enhance Notch signaling by interacting directly with NOTCH receptors. Consistent with a role in Notch signaling, NOTCH2NL ectopic expression delays differentiation of neuronal progenitors, while deletion accelerates differentiation. NOTCH2NL genes provide the breakpoints in typical cases of 1q21.1 distal deletion/duplication syndrome, where duplications are associated with macrocephaly and autism, and deletions with microcephaly and schizophrenia. Thus, the emergence of hominin-specific NOTCH2NL genes may have contributed to the rapid evolution of the larger hominin neocortex accompanied by loss of genomic stability at the 1q21. 1 locus and a resulting recurrent neurodevelopmental disorder.

neuroscience↗

bioRxiv2017

Linear Assembly of a Human Y Centromere using Nanopore Long Reads

The human genome reference sequence remains incomplete due to the challenge of assembling long tracts of near-identical tandem repeats-in centromeric regions. To address this, we have implemented a nanopore sequencing strategy to generate high quality reads that span hundreds of kilobases of highly repetitive DNAs. Here, we use this advance to produce a sequence assembly and characterization of the centromeric region of a human Y chromosome.

genomics↗

bioRxiv2017

Genome Graphs

There is increasing recognition that a single, monoploid reference genome is a poor universal reference structure for human genetics, because it represents only a tiny fraction of human variation. Adding this missing variation results in a structure that can be described as a mathematical graph: a genome graph. We demonstrate that, in comparison to the existing reference genome (GRCh38), genome graphs can substantially improve the fractions of reads that map uniquely and perfectly. Furthermore, we show that this fundamental simplification of read mapping transforms the variant calling problem from one in which many non-reference variants must be discovered de-novo to one in which the vast majority of variants are simply re-identified within the graph. Using standard benchmarks as well as a novel reference-free evaluation, we show that a simplistic variant calling procedure on a genome graph can already call variants at least as well as, and in many cases better than, a state-of-the-art method on the linear human reference genome. We anticipate that graph-based references will supplant linear references in humans and in other applications where cohorts of sequenced individuals are available.

bioinformatics↗

bioRxiv2017

A Flow Procedure for the Linearization of Genome Sequence Graphs.

1Efforts to incorporate human genetic variation into the reference human genome have converged on the idea of a graph representation of genetic variation within a species, a genome sequence graph. A sequence graph represents a set of individual haploid reference genomes as paths in a single graph. When that set of reference genomes is sufficiently diverse, the sequence graph implicitly contains all frequent human genetic variations, including translocations, inversions, deletions, and insertions.\n\nIn representing a set of genomes as a sequence graph one encounters certain challenges. One of the most important is the problem of graph linearization, essential both for efficiency of storage and access, as well as for natural graph visualization and compatibility with other tools. The goal of graph linearization is to order nodes of the graph in such a way that operations such as access, traversal and visualization are as efficient and effective as possible.\n\nA new algorithm for the linearization of sequence graphs, called the flow procedure, is proposed in this paper. Comparative experimental evaluation of the flow procedure against other algorithms shows that it outperforms its rivals in the metrics most relevant to sequence graphs.

bioinformatics↗

bioRxiv2016

Cis-Compound Mutations are Prevalent in Triple Negative Breast Cancer and Can Drive Tumor Progression

About 16% of breast cancers fall into a clinically aggressive category designated triple negative (TNBC) due to a lack of ERBB2, estrogen receptor and progesterone receptor expression1-3. The mutational spectrum of TNBC has been characterized as part of The Cancer Genome Atlas (TCGA)4; however, snapshots of primary tumors cannot reveal the mechanisms by which TNBCs progress and spread. To address this limitation we initiated the Intensive Trial of OMics in Cancer (ITOMIC)-001, in which patients with metastatic TNBC undergo multiple biopsies over space and time5. Whole exome sequencing (WES) of 67 samples from 11 patients identified 426 genes containing multiple distinct single nucleotide variants (SNVs) within the same sample, instances we term Multiple SNVs affecting the Same Gene and Sample (MSSGS). We find that >90% of MSSGS result from cis-compound mutations (in which both SNVs affect the same allele), that MSSGS comprised of SNVs affecting adjacent nucleotides arise from single mutational events, and that most other MSSGS result from the sequential acquisition of SNVs. Some MSSGS drive cancer progression, as exemplified by a TNBC driven by FGFR2(S252W;Y375C). MSSGS are more prevalent in TNBC than other breast cancer subtypes and occur at higher-than-expected frequencies across TNBC samples within TCGA. MSSGS may denote genes that play as yet unrecognized roles in cancer progression.

clinical trials↗