Biology subjects

Niu, L.-J.

Publications and source records attributed to Niu, L.-J..

2 recordsLinked to original sources

bioRxiv2023

High-resolution diploid 3D genome reconstruction using Pore-C data

In diploid organisms, spatial variations between homologous chromosomes are essential to many biological phenomena. Currently, it is still challenging to efficiently reconstruct a high-quality diploid 3D human genome. Here, we introduce Dip3D, reconstructing the diploid 3D human genome using Pore-C data of one sample. Dip3D has solved multiple problems in genome-wide SNV calling and haplo-tagging caused by the high sequencing error rates in Pore-C type data. Dip3D capitalizes on the high-order chromosomal interaction characteristics, enabling robust haplotype imputation and intricate haplotype-specific 3D structure discovery. Dip3D outperforms previous methods in data utilization rate, contact matrix resolution, and completeness by one order of magnitude. Moreover, Dip3D allows capturing haplotype high-order interactions that are unseen in Hi-C type data. We demonstrated the identified haplotype substructures such as Topologically Associating Domains (TADs) in the constructed 3D human genome, and unraveled connections between genic haplotype-specific high-order interactions and imbalanced allelic expression.

genomics↗

bioRxiv2022

Falign: An effective alignment tool for long noisy 3C data

Fragmented long noisy reads (FLNRs), such as Pore-C, contain multiple fragments of varied length separated by restriction enzyme sites. Existing alignment tools have a low mapping rate for short fragments and find incorrect fragment boundaries, which affects the utilization of FLNRs for downstream studies. Here, we develop Falign, a sequence alignment method that is adapted to the nature of FLNRs. Falign adopts a two-phase approach to efficiently align both long and short fragments. Falign uses the restriction enzyme sites on the reference genome as boundaries, which avoids the problem of destroyed fragment boundaries on FLNRs. Falign employs a multiple-stage searching mechanism to effectively recover the alignments of FLNRs with multiple fragments and interchromosomal fragments. Experiments on simulated and experimental fragmented long noisy 3C datasets show that Falign can effectively recover the constructs of reads and the sampled loci of the fragments. Falign allows significantly higher data utilization for FLNRs.

bioinformatics↗