Complementary techniques that deepen information content and minimize reagent costs are required to realize the full potential of massively parallel sequencing. Here, we describe a resequencing approach that directs focus to genomic regions of high interest by combining hybridization-based purification of multi-megabase regions with sequencing on the Illumina Genome Analyzer (GA). The capture matrix is created by a microarray on which probes can be programmed as desired to target any non-repeat portion of the genome, while the method requires only a basic familiarity with microarray hybridization. We present a detailed protocol suitable for 1-2 microg of input genomic DNA and highlight key design tips in which high specificity (>65% of reads stem from enriched exons) and high sensitivity (98% targeted base pair coverage) can be achieved. We have successfully applied this to the enrichment of coding regions, in both human and mouse, ranging from 0.5 to 4 Mb in length. From genomic DNA library production to base-called sequences, this procedure takes approximately 9-10 d inclusive of array captures and one Illumina flow cell run.
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http://dx.doi.org/10.1038/nprot.2009.68 | DOI Listing |
Am J Physiol Endocrinol Metab
January 2025
Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, 97239.
Maternal obesity puts the offspring at high risk of developing obesity and cardio-metabolic diseases in adulthood. Here, we utilized a mouse model of maternal high-fat diet (HFD)-induced obesity that recapitulates metabolic perturbations seen in humans. We show increased adiposity in the offspring of HFD-fed mothers (Off-HFD) when compared to the offspring regular diet-fed mothers (Off-RD).
View Article and Find Full Text PDFDetermining whether an ipsilateral breast carcinoma recurrence is a true recurrence or a new primary remains challenging based solely on clinicopathologic features. Algorithms based on these features have estimated that up to 68% of recurrences might be new primaries. However, few studies have analyzed the clonal relationship between primary and secondary carcinomas to establish the true nature of recurrences.
View Article and Find Full Text PDFNature
January 2025
Program of Mathematical Genomics, Department of Systems Biology, Columbia University, New York, NY, USA.
Transcriptional regulation, which involves a complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate to unseen cell types and conditions. Here we introduce GET (general expression transformer), an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types.
View Article and Find Full Text PDFCell Syst
December 2024
The Edison Family Center for Genome Sciences & Systems Biology, Saint Louis, MO 63110, USA; Department of Genetics, Saint Louis, MO 63110, USA. Electronic address:
Deep learning is a promising strategy for modeling cis-regulatory elements. However, models trained on genomic sequences often fail to explain why the same transcription factor can activate or repress transcription in different contexts. To address this limitation, we developed an active learning approach to train models that distinguish between enhancers and silencers composed of binding sites for the photoreceptor transcription factor cone-rod homeobox (CRX).
View Article and Find Full Text PDFGigascience
January 2025
Department of Genetics and Genomic Sciences, Department of Artificial Intelligence and Human Health, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Background: Cancer mutations are often assumed to alter proteins, thus promoting tumorigenesis. However, how mutations affect protein expression-in addition to gene expression-has rarely been systematically investigated. This is significant as mRNA and protein levels frequently show only moderate correlation, driven by factors such as translation efficiency and protein degradation.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!