Resolving Multicopy Duplications de novo Using Polyploid Phasing

Abstract

While the rise of single-molecule sequencing systems has enabled an unprecedented rise in the ability to assemble complex regions of the genome, long segmental duplications in the genome still remain a challenging frontier in assembly. Segmental duplications are at the same time both gene rich and prone to large structural rearrangements, making the resolution of their sequences important in medical and evolutionary studies. Duplicated sequences that are collapsed in mammalian de novo assemblies are rarely identical; after a sequence is duplicated, it begins to acquire paralog specific variants. In this paper, we study the problem of resolving the variations in multicopy long-segmental duplications by developing and utilizing algorithms for polyploid phasing. We develop two algorithms: the first one is targeted at maximizing the likelihood of observing the reads given the underlying haplotypes using discrete matrix completion. The second algorithm is based on correlation clustering and exploits an assumption, which is often satisfied in these duplications, that each paralog has a sizable number of paralog-specific variants. We develop a detailed simulation methodology, and demonstrate the superior performance of the proposed algorithms on an array of simulated datasets. We measure the likelihood score as well as reconstruction accuracy, i.e., what fraction of the reads are clustered correctly. In both the performance metrics, we find that our algorithms dominate existing algorithms on more than 93% of the datasets. While the discrete matrix completion performs better on likelihood score, the correlation clustering algorithm performs better on reconstruction accuracy due to the stronger regularization inherent in the algorithm. We also show that our correlation-clustering algorithm can reconstruct on an average 7.0 haplotypes in 10-copy duplication data-sets whereas existing algorithms reconstruct less than 1 copy on average.

Multi-platform discovery of haplotype-resolved structural variation in human genomes

“…The sequence structure of such variation is still not resolved and novel methods will need to be developed to sequence-resolve CNVs (M. J. Chaisson et al 2017). Of note, there is a pressing need to reduce the FDR of SV calling to below the current standard of 5% because forward validation of all potentially disease-relevant events will be impractical at this threshold.…”

Haplotype Threading: Accurate Polyploid Phasing from Long Reads

“…More recent advances have not proven to be useful for whole-genome singleindividual haplotyping, like PolyHarsh [13], a Gibbs sampling method that is also based on the MEC model and has only been shown to work on very small artificial examples, TriPoly [14] that infers haplotypes from trio data and thus requires family data, and SDA [15]. The latter provides two algorithms based on a discrete matrix completion approach and correlation clustering, respectively, and is used to resolve segmental duplications of higher ploidy during genome assembly.…”

A haplotype-aware de novo assembly of related individuals using pedigree graph

“…The next step for this work involves producing assemblies alongside the process of graphbased phasing on pedigrees. This task may also involve phasing repeat regions, which we plan to perform using polyploid phasing as described by Chaisson et al (2017). The general idea of our phasing approach can be even applied to polyploid genomes, with some gain in computation time.…”