REXTAL: Regional Extension of Assemblies Using Linked-Reads

Abstract

It is currently impossible to get complete de-novo assembly of segmentally duplicated genome regions using genome-wide short-read datasets. Here, we devise a new computational method called Regional Extension of Assemblies Using Linked-Reads (REXTAL) for improved region-specific assembly of segmental duplication-containing DNA, leveraging genomic short-read datasets generated from large DNA molecules partitioned and barcoded using the "Gel Bead in Emulsion" (GEM) microfluidic method (Zheng et al., 2016). We show that using REXTAL, it is possible to extend assembly of single-copy diploid DNA into adjacent, otherwise inaccessible subtelomere segmental duplication regions and other subtelomeric gap regions. Moreover, REXTAL is computationally more efficient for the directed assembly of such regions from multiple genomes (e.g., for the comparison of structural variation) than genome-wide assembly approaches.

Keywords: 10X sequencing; Linked-read sequencing; Subtelomere; assembly; genome gaps; segmental duplication; structural variation.

Figure 1.

Conceptual description of GEM microfluidic method. Circle (blue, magenta) represents gel beads. Each bead contains many copies of a 16-base barcode (Rectangles inside the circle) unique to that bead. Each partition gets one gel bead. The 10 curve lines inside the large square (represents partition) represent molecules of length approximately 50 kb–100 kb. The green and orange ovals represent short reads of length 150 bases which are obtained from these molecules (curve lines).

Figure 2.

A: Flowchart. B: Details of Reads Selection algorithm is shown inside dotted box

Figure 3.

Four different chromosomes with different characteristics. The blue rectangle represents single copy region and the magenta rectangle represents segmental duplication region.

Figure 4

A: Alignment of 2p 500kb as query with assembled scaffolds of 2p for range 10–70 as subject in BLAST. B: Alignment of 19p 1-copy 300kb as query with assembled scaffolds of 19p 1-copy for range 3–70 as subject in BLAST. C: Alignment of 10p 1-copy 300kb as query with assembled scaffolds of 10p 1-copy for range 3–70 as subject in BLAST. D: Alignments of two 1-copy regions of 5p as query with assembled scaffolds of 5p 1-copy regions for range 3–70 as subject in BLAST.

Figure 5.

Top magenta rectangle represents the query sequence. A: Partially overlapped local alignment regions and gaps in coverage of the query sequence. B: Considering partially overlapped local alignment regions as sequence contigs and each sequence contig region (C) is followed by one sequence gap (G). Dotted blue lines represent starting position and ending position of gap.

Figure 6.

Algorithm to calculate LAF.

Figure 7.

A: Alignment of 2p with assembled scaffolds of 2p for range 10–60 of REXTAL. B: Alignment of 2p as query with assembled scaffolds of 2p extracted from genome-wide assembly. C: Alignment of 19p with assembled scaffolds of 19p 1-copy for range 3–70 of REXTAL. D: Alignment of 19p with assembled scaffolds of 19p 1-copy region extracted from genome-wide assembly. E: Alignment of 10p with assembled scaffolds of 10p 1-copy for range 3–70 of REXTAL. F: Alignment of 10p with assembled scaffolds of 10p 1-copy region extracted from genome-wide assembly. G: Alignment of 5p with assembled scaffolds of 5p 1-copy regions for range 3–70 of REXTAL. H: Alignment of 5p with assembled scaffolds of 5p 1-copy regions extracted from genome-wide assembly.

Figure 8.

A: Alignment of 19p segmental duplication region with assembled scaffolds of 19p 1-copy for range 3–70 of REXTAL. B: Alignment of 19p segmental duplication region with assembled scaffolds of 19p 1-copy region extracted from genome-wide assembly. C: Alignment of 10p segmental duplication region with assembled scaffolds of 10p 1-copy for range 3–70 of REXTAL. D: Alignment of 10p segmental duplication region with assembled scaffolds of 10p 1-copy region extracted from genome-wide assembly.