Biology subjects

Castro, C. P.

Publications and source records attributed to Castro, C. P..

3 recordsLinked to original sources

bioRxiv2023

LRphase: an efficient method for assigning haplotype identity to long reads

MotivationUnderstanding the functional effects of sequence variation is among the primary goals of contemporary genomics. Individual human genomes contain millions of variants which are thought to contribute to phenotypic variability and differential disease risks at the population level. However, because variants rarely act in isolation, we cannot accurately predict functional effects without first considering the potential effects of other interacting variants on the same chromosome. This information can be obtained by phasing the read data from sequencing experiments. However, no standalone tools are available to simply phase reads based on known haplotypes. Here we present LRphase: a user-friendly utility for simple phasing of long sequencing reads. Availability and ImplementationLRphase is implemented in Python, and is freely available at https://github.com/Boyle-Lab/LRphase, under the MIT license. Version 1.1.0, described in this manuscript, is available through the pip and Bioconda repositories (e.g., "pip install lrphase==1.1.0"). Contactapboyle@umich.edu Supplementary InformationSupplementary methods are available as part of the online version of this publication.

bioinformatics↗

bioRxiv2022

Challenges in screening for de novo noncoding variants contributing to genetically complex phenotypes

Understanding the genetic basis for complex, heterogeneous disorders, such as autism spectrum disorder (ASD), is a persistent challenge in human medicine. Owing to their phenotypic complexity, the genetic mechanisms underlying these disorders may be highly variable across individual patients. Furthermore, much of their heritability is unexplained by known regulatory or coding variants. Indeed, there is evidence that much of the causal genetic variation stems from rare and de novo variants arising from ongoing mutation. These variants occur mostly in noncoding regions, likely affecting regulatory processes for genes linked to the phenotype of interest. However, because there is no uniform code for assessing regulatory function, it is difficult to separate these mutations into likely functional and nonfunctional subsets. This makes finding associations between complex diseases and potentially causal de novo single-nucleotide variants (dnSNVs) a difficult task. To date, all but one published study in this area has failed to find any significant associations between dnSNVs from ASD patients and any class of known regulatory elements. We sought to identify the underlying reasons for this and present strategies for overcoming these challenges. We show that, contrary to previous claims, the main reason for failure to find robust statistical enrichments is not the number of families sampled, but the quality and relevance to ASD of the annotations used to prioritize dnSNVs, and the reliability of the set of dnSNVs itself. We present a list of recommendations for designing future studies of this sort that will help researchers avoid common pitfalls.

genetics↗

bioRxiv2021

Cas9 targeted enrichment of mobile elements using nanopore sequencing

Mobile element insertions (MEIs) are highly repetitive genomic sequences that contribute to inter- and intra-individual genetic variation and can lead to genetic disorders. Targeted and whole-genome approaches using short-read sequencing have been developed to identify reference and non-reference MEIs; however, the read length hampers detection of these elements in complex genomic regions. Here, we pair Cas9 targeted nanopore sequencing with computational methodologies to capture active MEIs in human genomes. We demonstrate parallel enrichment for distinct classes of MEIs, averaging 44% of reads on targeted signals. We show an individual flow cell can recover a remarkable fraction of MEIs (97% L1Hs, 93% AluYb, 51% AluYa, 99% SVA_F, and 65% SVA_E). We identify twenty-one non-reference MEIs in GM12878 overlooked by modern, long-read analysis pipelines, primarily in repetitive genomic regions. This work introduces the utility of nanopore sequencing for MEI enrichment and lays the foundation for rapid discovery of elusive, repetitive genetic elements.

genetics↗