%0 Journal Article %J Science %D 2020 %T Cell type-specific genetic regulation of gene expression across human tissues. %A Kim-Hellmuth, Sarah %A Aguet, François %A Oliva, Meritxell %A Muñoz-Aguirre, Manuel %A Kasela, Silva %A Wucher, Valentin %A Castel, Stephane E %A Hamel, Andrew R %A Viñuela, Ana %A Roberts, Amy L %A Mangul, Serghei %A Wen, Xiaoquan %A Wang, Gao %A Barbeira, Alvaro N %A Garrido-Martín, Diego %A Nadel, Brian B %A Zou, Yuxin %A Bonazzola, Rodrigo %A Quan, Jie %A Brown, Andrew %A Martinez-Perez, Angel %A Soria, José Manuel %A Getz, Gad %A Dermitzakis, Emmanouil T %A Small, Kerrin S %A Stephens, Matthew %A Xi, Hualin S %A Im, Hae Kyung %A Guigo, Roderic %A Segrè, Ayellet V %A Stranger, Barbara E %A Ardlie, Kristin G %A Lappalainen, Tuuli %K Cells %K Gene Expression Regulation %K Humans %K Organ Specificity %K Quantitative Trait Loci %K RNA, Long Noncoding %K Transcriptome %X

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type-interaction QTLs for seven cell types and show that cell type-interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type-interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.

%B Science %V 369 %8 2020 09 11 %G eng %N 6509 %1 https://www.ncbi.nlm.nih.gov/pubmed/32913075?dopt=Abstract %R 10.1126/science.aaz8528 %0 Journal Article %J Science %D 2020 %T Transcriptomic signatures across human tissues identify functional rare genetic variation. %A Ferraro, Nicole M %A Strober, Benjamin J %A Einson, Jonah %A Abell, Nathan S %A Aguet, François %A Barbeira, Alvaro N %A Brandt, Margot %A Bucan, Maja %A Castel, Stephane E %A Davis, Joe R %A Greenwald, Emily %A Hess, Gaelen T %A Hilliard, Austin T %A Kember, Rachel L %A Kotis, Bence %A Park, YoSon %A Peloso, Gina %A Ramdas, Shweta %A Scott, Alexandra J %A Smail, Craig %A Tsang, Emily K %A Zekavat, Seyedeh M %A Ziosi, Marcello %A Ardlie, Kristin G %A Assimes, Themistocles L %A Bassik, Michael C %A Brown, Christopher D %A Correa, Adolfo %A Hall, Ira %A Im, Hae Kyung %A Li, Xin %A Natarajan, Pradeep %A Lappalainen, Tuuli %A Mohammadi, Pejman %A Montgomery, Stephen B %A Battle, Alexis %K Genetic Variation %K Genome, Human %K Humans %K Multifactorial Inheritance %K Organ Specificity %K Transcriptome %X

Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.

%B Science %V 369 %8 2020 09 11 %G eng %N 6509 %1 https://www.ncbi.nlm.nih.gov/pubmed/32913073?dopt=Abstract %R 10.1126/science.aaz5900 %0 Journal Article %J Genome Biol %D 2018 %T Cell type-specific CLIP reveals that NOVA regulates cytoskeleton interactions in motoneurons. %A Yuan, Yuan %A Xie, Shirley %A Darnell, Jennifer C %A Darnell, Andrew J %A Saito, Yuhki %A Phatnani, Hemali %A Murphy, Elisabeth A %A Zhang, Chaolin %A Maniatis, Tom %A Darnell, Robert B %K Alternative Splicing %K Amino Acid Sequence %K Animals %K Cercopithecus aethiops %K Chromosomes, Artificial, Bacterial %K COS Cells %K Cross-Linking Reagents %K Cytoskeleton %K Dendrites %K Exons %K Immunoprecipitation %K Lipoylation %K Mice %K Mice, Transgenic %K Motor Neurons %K Nerve Tissue Proteins %K NIH 3T3 Cells %K Pseudopodia %K RNA %K RNA-Binding Proteins %K Septins %K Transcriptome %X

BACKGROUND: Alternative RNA processing plays an essential role in shaping cell identity and connectivity in the central nervous system. This is believed to involve differential regulation of RNA processing in various cell types. However, in vivo study of cell type-specific post-transcriptional regulation has been a challenge. Here, we describe a sensitive and stringent method combining genetics and CLIP (crosslinking and immunoprecipitation) to globally identify regulatory interactions between NOVA and RNA in the mouse spinal cord motoneurons.

RESULTS: We developed a means of undertaking motoneuron-specific CLIP to explore motoneuron-specific protein-RNA interactions relative to studies of the whole spinal cord in mouse. This allowed us to pinpoint differential RNA regulation specific to motoneurons, revealing a major role for NOVA in regulating cytoskeleton interactions in motoneurons. In particular, NOVA specifically promotes the palmitoylated isoform of the cytoskeleton protein Septin 8 in motoneurons, which enhances dendritic arborization.

CONCLUSIONS: Our study demonstrates that cell type-specific RNA regulation is important for fine tuning motoneuron physiology and highlights the value of defining RNA processing regulation at single cell type resolution.

%B Genome Biol %V 19 %P 117 %8 2018 08 15 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/30111345?dopt=Abstract %R 10.1186/s13059-018-1493-2 %0 Journal Article %J Genome Res %D 2018 %T Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line. %A Nattestad, Maria %A Goodwin, Sara %A Ng, Karen %A Baslan, Timour %A Sedlazeck, Fritz J %A Rescheneder, Philipp %A Garvin, Tyler %A Fang, Han %A Gurtowski, James %A Hutton, Elizabeth %A Tseng, Elizabeth %A Chin, Chen-Shan %A Beck, Timothy %A Sundaravadanam, Yogi %A Kramer, Melissa %A Antoniou, Eric %A McPherson, John D %A Hicks, James %A McCombie, W Richard %A Schatz, Michael C %K Breast Neoplasms %K Female %K Gene Amplification %K Gene Rearrangement %K Genome, Human %K Genomic Structural Variation %K High-Throughput Nucleotide Sequencing %K Humans %K MCF-7 Cells %K Oncogenes %K Receptor, ErbB-2 %K Repetitive Sequences, Nucleic Acid %K Transcriptome %X

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important oncogene (also known as ), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

%B Genome Res %V 28 %P 1126-1135 %8 2018 08 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/29954844?dopt=Abstract %R 10.1101/gr.231100.117 %0 Journal Article %J Nat Methods %D 2017 %T Simultaneous epitope and transcriptome measurement in single cells. %A Stoeckius, Marlon %A Hafemeister, Christoph %A Stephenson, William %A Houck-Loomis, Brian %A Chattopadhyay, Pratip K %A Swerdlow, Harold %A Satija, Rahul %A Smibert, Peter %K Epitope Mapping %K Epitopes %K Gene Expression Profiling %K High-Throughput Nucleotide Sequencing %K Sequence Analysis, RNA %K Tissue Array Analysis %K Transcriptome %X

High-throughput single-cell RNA sequencing has transformed our understanding of complex cell populations, but it does not provide phenotypic information such as cell-surface protein levels. Here, we describe cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), a method in which oligonucleotide-labeled antibodies are used to integrate cellular protein and transcriptome measurements into an efficient, single-cell readout. CITE-seq is compatible with existing single-cell sequencing approaches and scales readily with throughput increases.

%B Nat Methods %V 14 %P 865-868 %8 2017 Sep %G eng %N 9 %1 https://www.ncbi.nlm.nih.gov/pubmed/28759029?dopt=Abstract %R 10.1038/nmeth.4380