This book addresses a question fundamental to any discussion of grammatical theory and grammatical variation: to what extent can principles of grammar be explained through language use? The book ...argues that there is a profound correspondence between performance data and the fixed conventions of grammars. Preferences and patterns found in the one, the book shows, are reflected in constraints and variation patterns in the other. The theoretical consequences of the proposed ‘performance-grammar correspondence hypothesis’ are far-reaching — for current grammatical formalisms, for the innateness hypothesis, and for psycholinguistic models of performance and learning. Drawing on empirical generalizations and insights from language typology, generative grammar, psycholinguistics, and historical linguistics, this book demonstrates that the assumption that grammars are immune to performance is false. It presents detailed empirical case studies and arguments for an alternative theory in which performance has shaped the conventions of grammars and thus the variation patterns found in the world’s languages. The innateness of language, the book argues, resides primarily in the mechanisms human beings have for processing and learning it.
CRISPR-Cas nucleoproteins target foreign DNA via base pairing with a crRNA. However, a quantitative description of protein binding and nuclease activation at off-target DNA sequences remains elusive. ...Here, we describe a chip-hybridized association-mapping platform (CHAMP) that repurposes next-generation sequencing chips to simultaneously measure the interactions between proteins and ∼107 unique DNA sequences. Using CHAMP, we provide the first comprehensive survey of DNA recognition by a type I-E CRISPR-Cas (Cascade) complex and Cas3 nuclease. Analysis of mutated target sequences and human genomic DNA reveal that Cascade recognizes an extended protospacer adjacent motif (PAM). Cascade recognizes DNA with a surprising 3-nt periodicity. The identity of the PAM and the PAM-proximal nucleotides control Cas3 recruitment by releasing the Cse1 subunit. These findings are used to develop a model for the biophysical constraints governing off-target DNA binding. CHAMP provides a framework for high-throughput, quantitative analysis of protein-DNA interactions on synthetic and genomic DNA.
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•CHAMP enables massively parallel profiling of protein-nucleic acid interactions•CHAMP was used to measure off-target DNA binding by a CRISPR-Cas complex•Cascade decodes extended PAMs and binds DNA with a 3-nt periodicity•Cas3 binding is dependent on the PAM and PAM-proximal crRNA-DNA mismatches
Discarded next-gen sequencing chips provide a platform for analyzing protein-DNA interactions that reveals a novel proofreading mechanism used by the Cascade/Cas3 complex.
A lack of tools to precisely control gene expression has limited our ability to evaluate relationships between expression levels and phenotypes. Here, we describe an approach to titrate expression of ...human genes using CRISPR interference and series of single-guide RNAs (sgRNAs) with systematically modulated activities. We used large-scale measurements across multiple cell models to characterize activities of sgRNAs containing mismatches to their target sites and derived rules governing mismatched sgRNA activity using deep learning. These rules enabled us to synthesize a compact sgRNA library to titrate expression of ~2,400 genes essential for robust cell growth and to construct an in silico sgRNA library spanning the human genome. Staging cells along a continuum of gene expression levels combined with single-cell RNA-seq readout revealed sharp transitions in cellular behaviors at gene-specific expression thresholds. Our work provides a general tool to control gene expression, with applications ranging from tuning biochemical pathways to identifying suppressors for diseases of dysregulated gene expression.
Synthetic DNA is rapidly emerging as a durable, high-density information storage platform. A major challenge for DNA-based information encoding strategies is the high rate of errors that arise during ...DNA synthesis and sequencing. Here, we describe the HEDGES (Hash Encoded, Decoded by Greedy Exhaustive Search) error-correcting code that repairs all three basic types of DNA errors: insertions, deletions, and substitutions. HEDGES also converts unresolved or compound errors into substitutions, restoring synchronization for correction via a standard Reed–Solomon outer code that is interleaved across strands. Moreover, HEDGES can incorporate a broad class of user-defined sequence constraints, such as avoiding excess repeats, or too high or too low windowed guanine–cytosine (GC) content. We test our code both via in silico simulations and with synthesized DNA. From its measured performance, we develop a statistical model applicable to much larger datasets. Predicted performance indicates the possibility of error-free recovery of petabyte- and exabyte-scale data from DNA degraded with as much as 10% errors. As the cost of DNA synthesis and sequencing continues to drop, we anticipate that HEDGES will find applications in large-scale error-free information encoding.
Many large-scale, high-throughput experiments use DNA barcodes, short DNA sequences prepended to DNA libraries, for identification of individuals in pooled biomolecule populations. However, DNA ...synthesis and sequencing errors confound the correct interpretation of observed barcodes and can lead to significant data loss or spurious results. Widely used error-correcting codes borrowed from computer science (e.g., Hamming, Levenshtein codes) do not properly account for insertions and deletions (indels) in DNA barcodes, even though deletions are the most common type of synthesis error. Here, we present and experimentally validate filled/truncated right end edit (FREE) barcodes, which correct substitution, insertion, and deletion errors, even when these errors alter the barcode length. FREE barcodes are designed with experimental considerations in mind, including balanced guanine-cytosine (GC) content, minimal homopolymer runs, and reduced internal hairpin propensity. We generate and include lists of barcodeswith different lengths and error correction levels thatmay be useful in diverse high-throughput applications, including >10⁶ single-error–correcting 16-mers that strike a balance between decoding accuracy, barcode length, and library size. Moreover, concatenating two or more FREE codes into a single barcode increases the available barcode space combinatorially, generating lists with >1015 errorcorrecting barcodes. The included software for creating barcode libraries and decoding sequenced barcodes is efficient and designed to be user-friendly for the general biology community.
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