Abstract

The genome of the cold-adapted diatom Fragilariopsis cylindrus is characterized by highly diverged haplotypes that intersperse its homozygous genome. Here, we describe how a combination of PacBio DNA and Illumina RNA sequencing can be used to resolve this complex genomic landscape locally into the highly diverged haplotypes, and how to map various environmentally controlled transcripts onto individual haplotypes. We assembled PacBio sequence data with the FALCON assembler and created a haplotype resolved annotation of the assembly using annotations of a Sanger sequenced F. cylindrus genome. RNA-seq datasets from six different growth conditions were used to resolve allele-specifc gene expression in F. cylindrus. This approach enables to study differential expression of alleles in a complex genomic landscape and provides a useful tool to study how diverged haplotypes in diploid organisms are used for adaptation and evolution to highly variable environments.

Highlights

  • Background & SummaryHow extreme and highly variable environmental conditions impact the evolution and adaptation of eukaryotic organisms has not been extensively studied, yet

  • Our recent work on the diploid polar diatom Fragilariopsis cylindrus[1], which has successfully adapted to the sea-ice environment of the Southern Ocean, showed that approximately 25% of its diploid genome is characterized by highly diverged haplotypes that are interspersed throughout its otherwise homozygous genome

  • Alleles from these diverged haplotypes were differentially expressed across variable environmental conditions

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Summary

Introduction

Background & SummaryHow extreme and highly variable environmental conditions impact the evolution and adaptation of eukaryotic organisms has not been extensively studied, yet. To resolve the exact location of these diverged haplotype contigs, we used the diploid aware FALCON assembler[4] for long PacBio sequence reads (Data Citation 1). RNA-seq datasets from six different experimental treatments were created, using samples from (1) optimal growth, (2) freezing temperatures, (3) elevated temperatures, (4) elevated carbon dioxide, (5) iron starvation, and (6) prolonged darkness (Table 1) (Data Citation 2).

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