A multiple alignment workflow shows the effect of repeat masking and parameter tuning on alignment in plants

Abstract

Alignments of multiple genomes are a cornerstone of comparative genomics, but generating these alignments remains technically challenging and often impractical. We developed the msa_pipeline workflow (https://bitbucket.org/bucklerlab/msa_pipeline) to allow practical and sensitive multiple alignment of diverged plant genomes and calculation of conservation scores with minimal user inputs. As high repeat content and genomic divergence are substantial challenges in plant genome alignment, we also explored the effect of different masking approaches and parameters of the LAST aligner using genome assemblies of 33 grass species. Compared with conventional masking with RepeatMasker, a masking approach based on k-mers (nucleotide sequences of k length) increased the alignment rate of coding sequence and noncoding functional regions by 25 and 14%, respectively. We further found that default alignment parameters generally perform well, but parameter tuning can increase the alignment rate for noncoding functional regions by over 52% compared with default LAST settings. Finally, by increasing alignment sensitivity from the default baseline, parameter tuning can increase the number of noncoding sites that can be scored for conservation by over 76%. Overall, tuning of masking and alignment parameters can generate optimized multiple alignments to drive biological discovery in plants.