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Biology subjects

Anand, D.

Publications and source records attributed to Anand, D..

2 recordsLinked to original sources

A novel method for systematic genetic analysis and visualization of phenotypic heterogeneity applied to orofacial clefts

Phenotypic heterogeneity is a hallmark of complex traits, and genetic studies may focus on the trait as a whole or on individual subgroups. For example, in orofacial clefting (OFC), three subtypes - cleft lip (CL), cleft lip and palate (CLP), and cleft palate (CP) have been studied separately and in combination. It is more challenging, however, to dissect the genetic architecture and describe how a given locus may be contributing to distinct subtypes of a trait. We developed a framework for quantifying and interpreting evidence of subtype-specific or shared genetic effects in complex traits. We applied this technique to create a \"cleft map\" of the association of 30 genetic loci with three OFC subtypes. In addition to new associations, we found loci with subtype-specific effects (e.g., GRHL3 (CP), WNT5A (CLP)), as well as loci associated with two or all three subtypes. We cross-referenced these results with mouse craniofacial gene expression datasets, which identified promising candidate genes. However, we found no strong correlation between OFC subtypes and expression patterns. In aggregate, the cleft map revealed neither subtype-specific nor shared genetic effects operate in isolation in OFC architecture. Our approach can be easily applied to any complex trait with distinct phenotypic subgroups.

genetics

PHASIS: A computational suite for de novo discovery and characterization of phased, siRNA-generating loci and their miRNA triggers

Phased, secondary siRNAs (phasiRNAs) are found widely in plants, from protein-coding transcripts and long, non-coding RNAs; animal piRNAs are also phased. Integrated methods characterizing \"PHAS\" loci are unavailable, and existing methods are quite limited and inefficient in handling large volumes of sequencing data. The PHASIS suite described here provides complete tools for the computational characterization of PHAS loci, with an emphasis on plants, in which these loci are numerous. Benchmarked comparisons demonstrate that PHASIS is sensitive, highly scalable and fast. Importantly, PHASIS eliminates the requirement of a sequenced genome and PARE/degradome data for discovery of phasiRNAs and their miRNA triggers.

bioinformatics