Biology subjects

Press, W. H.

Publications and source records attributed to Press, W. H..

4 recordsLinked to original sources

bioRxiv2025

Population Models with Phenotypic Diversity and Fluctuating Environment Illustrate Parameter Regimes of Adaptation vs. Extinction

A species may survive long-term environmental fluctuations by maintaining a sufficient phenotypic variability to span the changes. Bet-hedging and adaptive mutatability (or mutator strains) are among possible mechanisms. We construct simple population dynamics models for these strategies in a unified framework, with a stochastic environment model and a specifiable environmental carrying capacity, identifying different parameter regimes: Quantitatively, how much hedging is needed or what mutation rate is required? How much selection burden re wild-type is tolerable for the strategy to work? Is the diverse population susceptible to invasion by a reverting wild type better adapted in the short run, but producing an extinction outcome in the long run? We give answers that are quantitative in the context of the specific idealized models, but that can also be qualitatively illuminating to more realistic cases.

evolutionary biology↗

bioRxiv2022

Fast trimer statistics facilitate accurate decoding of large random DNA barcode sets even at large sequencing error rates.

Predefined sets of short DNA sequences are commonly used as barcodes to identify individual biomolecules in pooled populations. Such use requires either sufficiently small DNA error rates, or else an error-correction methodology. Most existing DNA error-correcting codes (ECCs) correct only one or two errors per barcode in sets of typically [lsim] 104 barcodes. We here consider the use of random barcodes of sufficient length that they remain accurately decodable even with {gtrsim} 6 errors and even at 10% or 20% nucleotide error rates. We show that length 34 nt is sufficient even with {gtrsim} 106 barcodes. The obvious objection to this scheme is that it requires comparing every read to every possible barcode by a slow Levenshtein or Needleman-Wunsch comparison. We show that several orders of magnitude speedup can be achieved by (i) a fast triage method that compares only trimer (three consecutive nucleotide) occurence statistics, precomputed in linear time for both reads and barcodes, and (ii) the massive parallelism available on todays even commodity-grade GPUs. With 106 barcodes of length 34 and 10% DNA errors (substitutions and indels) we achieve in simulation 99.9% precision (decode accuracy) with 98.8% recall (read acceptance rate). Similarly high precision with somewhat smaller recall is achievable even with 20% DNA errors. The amortized computation cost on a commodity workstation with two GPUs (2022 capability and price) is estimated as between US$ 0.15 and US$ 0.60 per million decoded reads.

bioinformatics↗

bioRxiv2019

Massively parallel kinetic profiling of natural and engineered CRISPR nucleases

Engineered Streptococcus pyogenes (Sp) Cas9s and Acidaminococcus sp. (As) Cas12a (formerly Cpf1) improve cleavage specificity in human cells. However, the fidelity, enzymatic mechanisms, and cleavage products of emerging CRISPR nucleases have not been profiled systematically across partially mispaired off-target DNA sequences. Here, we describe NucleaSeq-- nuclease digestion and deep sequencing--a massively parallel platform that measures cleavage kinetics and captures the time-resolved identities of cleaved products for more than ten thousand DNA targets that include mismatches, insertions, and deletions relative to the guide RNA. The binding specificity of each enzyme is measured on the same DNA library via the chip-hybridized association mapping platform (CHAMP). Using this integrated cleavage and binding platform, we profile four SpCas9 variants and AsCas12a. Engineered Cas9s retain wtCas9-like off-target binding but increase cleavage specificity; Cas9-HF1 shows the most dramatic increase in cleavage specificity. Surprisingly, wtCas12a--reported as a more specific nuclease in cells--has cleavage specificity similar to wtCas9 in vitro. Initial cleavage position and subsequent end-trimming vary across nucleases, guide RNA sequences, and position and base identity of mispairs in target DNAs. Using these large datasets, we develop a biophysical model that reveals mechanistic insights into off-target cleavage activities by these nucleases. More broadly, NucleaSeq enables rapid, quantitative, and systematic comparison of the specificities and cleavage products of engineered and natural nucleases.

molecular biology↗

bioRxiv2018

Error-correcting DNA barcodes for high-throughput sequencing

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 and Levenshtein codes) do not properly account for insertions and deletions in DNA barcodes, even though deletions are the most common type of synthesis error. Here, we present and experimentally validate FREE (Filled/truncated Right End Edit) 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 GC content, minimal homopolymer runs, and reduced internal hairpin propensity. We generate and include lists of barcodes with different lengths and error-correction levels that may 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 error-correcting 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.\n\nSIGNIFICANCE STATEMENTModern high-throughput biological assays study pooled populations of individual members by labeling each member with a unique DNA sequence called a \"barcode.\" DNA barcodes are frequently corrupted by DNA synthesis and sequencing errors, leading to significant data loss and incorrect data interpretation. Here, we describe a novel error-correction strategy to improve the efficiency and statistical power of DNA barcodes. To our knowledge, this is the first report of an error-correcting method that accurately handles insertions and deletions in DNA barcodes, the most common type of error encountered during DNA synthesis and sequencing, resulting in order-of-magnitude increases in accuracy, efficiency, and signal-to-noise. The accompanying software package makes deployment of these barcodes effortless for the broader experimental scientist community.

molecular biology↗