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Maximilian Haeussler

University of California, Santa Cruz

ORCID: 0000-0001-8721-8253

Publishes on Single-cell and spatial transcriptomics, Genomics and Phylogenetic Studies, RNA and protein synthesis mechanisms. 161 papers and 31.1k citations.

161Publications
31.1kTotal Citations
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Top publicationsby citations

CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens
Jean‐Paul Concordet, Maximilian Haeussler|Nucleic Acids Research|2018
Cited by 2.5kOpen Access

CRISPOR.org is a web tool for genome editing experiments with the CRISPR-Cas9 system. It finds guide RNAs in an input sequence and ranks them according to different scores that evaluate potential off-targets in the genome of interest and predict on-target activity. The list of genomes is continuously expanded, with more 150 genomes added in the last two years. CRISPOR tries to provide a comprehensive solution from selection, cloning and expression of guide RNA as well as providing primers needed for testing guide activity and potential off-targets. Recent developments include batch design for genome-wide CRISPR and saturation screens, creating custom oligonucleotides for guide cloning and the design of next generation sequencing primers to test for off-target mutations. CRISPOR is available from http://crispor.org, including the full source code of the website and a stand-alone, command-line version.

Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR
Cited by 1.9kOpen Access

BACKGROUND: The success of the CRISPR/Cas9 genome editing technique depends on the choice of the guide RNA sequence, which is facilitated by various websites. Despite the importance and popularity of these algorithms, it is unclear to which extent their predictions are in agreement with actual measurements. RESULTS: We conduct the first independent evaluation of CRISPR/Cas9 predictions. To this end, we collect data from eight SpCas9 off-target studies and compare them with the sites predicted by popular algorithms. We identify problems in one implementation but found that sequence-based off-target predictions are very reliable, identifying most off-targets with mutation rates superior to 0.1 %, while the number of false positives can be largely reduced with a cutoff on the off-target score. We also evaluate on-target efficiency prediction algorithms against available datasets. The correlation between the predictions and the guide activity varied considerably, especially for zebrafish. Together with novel data from our labs, we find that the optimal on-target efficiency prediction model strongly depends on whether the guide RNA is expressed from a U6 promoter or transcribed in vitro. We further demonstrate that the best predictions can significantly reduce the time spent on guide screening. CONCLUSIONS: To make these guidelines easily accessible to anyone planning a CRISPR genome editing experiment, we built a new website ( http://crispor.org ) that predicts off-targets and helps select and clone efficient guide sequences for more than 120 genomes using different Cas9 proteins and the eight efficiency scoring systems evaluated here.

The UCSC Genome Browser database: 2019 update
Maximilian Haeussler, Ann S. Zweig, Cath Tyner et al.|Nucleic Acids Research|2018
Cited by 1.1kOpen Access

The UCSC Genome Browser (https://genome.ucsc.edu) is a graphical viewer for exploring genome annotations. For almost two decades, the Browser has provided visualization tools for genetics and molecular biology and continues to add new data and features. This year, we added a new tool that lets users interactively arrange existing graphing tracks into new groups. Other software additions include new formats for chromosome interactions, a ChIP-Seq peak display for track hubs and improved support for HGVS. On the annotation side, we have added gnomAD, TCGA expression, RefSeq Functional elements, GTEx eQTLs, CRISPR Guides, SNPpedia and created a 30-way primate alignment on the human genome. Nine assemblies now have RefSeq-mapped gene models.

Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex
Cited by 1k

Systematic analyses of spatiotemporal gene expression trajectories during organogenesis have been challenging because diverse cell types at different stages of maturation and differentiation coexist in the emerging tissues. We identified discrete cell types as well as temporally and spatially restricted trajectories of radial glia maturation and neurogenesis in developing human telencephalon. These lineage-specific trajectories reveal the expression of neurogenic transcription factors in early radial glia and enriched activation of mammalian target of rapamycin signaling in outer radial glia. Across cortical areas, modest transcriptional differences among radial glia cascade into robust typological distinctions among maturing neurons. Together, our results support a mixed model of topographical, typological, and temporal hierarchies governing cell-type diversity in the developing human telencephalon, including distinct excitatory lineages emerging in rostral and caudal cerebral cortex.

Single-cell genomics identifies cell type–specific molecular changes in autism
Cited by 1kOpen Access

Despite the clinical and genetic heterogeneity of autism, bulk gene expression studies show that changes in the neocortex of autism patients converge on common genes and pathways. However, direct assessment of specific cell types in the brain affected by autism has not been feasible until recently. We used single-nucleus RNA sequencing of cortical tissue from patients with autism to identify autism-associated transcriptomic changes in specific cell types. We found that synaptic signaling of upper-layer excitatory neurons and the molecular state of microglia are preferentially affected in autism. Moreover, our results show that dysregulation of specific groups of genes in cortico-cortical projection neurons correlates with clinical severity of autism. These findings suggest that molecular changes in upper-layer cortical circuits are linked to behavioral manifestations of autism.

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