Effective Machine-Learning Assembly For Next-Generation Sequencing With Very Low Coverage

Abstract

9In short-read DNA sequencing experiments, the read coverage is a key parameter to successfully assemble the reads and reconstruct the sequence of the input DNA. When coverage is very low, the original sequence reconstruction from the reads can be difficult because of the occurrence of uncovered gaps. Reference guided assembly can then improve these assemblies. However, when the available reference is phylogenetically distant from the sequencing reads, the mapping rate of the reads can be extremely low. Some recent improvements in read mapping approaches aim at modifying the reference according to the reads dynamically. Such approaches can significantly improve the alignment rate of the reads onto distant references but the processing of insertions and deletions remains challenging. Here, we introduce a dynamic programming algorithm to update the reference sequence according to previously aligned reads. Substitutions, insertions and deletions are performed in the reference sequence dynamically. We evaluate this approach to assemble a western-grey kangaroo mitochondrial amplicon. Our results show that more reads can be aligned and that this method produces assemblies of length comparable to the truth while limiting error rate when classic approaches fail to recover the correct length. Our method allows us to assemble the first full mitochondrial genome for the western-grey kangaroo. Finally, we discuss how the core algorithm of this method could be improved and combined with other approaches to analyse larger genomic sequences. 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26De novo assembly algorithms classically use graph, de Bruijn or overlap-layout-consensus, to join short 27 sequencing reads into longer contigs. However, when the short-reads coverage is very low, only short 28 contigs can be reconstructed because of the occurrence of uncovered gaps in the sequence (Miller et al., 29 2010). In this case, the availability of a reference sequence can be beneficial to connect and order these 30 contigs, an approach known as reference-guided assembly or homology-guided assembly (Rausch et al., 31 2009; Lischer and Shimizu, 2017). The reads are mapped onto this reference and a contig is constructed 32 by taking the consensus of the short-reads at each position. However, some gaps in the mapping of 33 the reads onto the reference may remain if the available reference is too distant phylogenetically from 34 the sequence the short-reads originate from. This is because the short-reads that cannot, or can only 35 partially, be mapped to the distant reference are discarded or trimmed. The information contained in the 36 discarded or trimmed sequences of the reads is therefore lost. Hence, improvements in the alignments of 37 the reads to the reference that are able to take advantage of this unexploited information should improve 38 the assemblies. 39Iterative referencing proposes to align all the reads to the reference and then update the reference 40 sequence by calling the consensus of the reads. Once the ref...