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SCIENCE CHINA Life Sciences, Volume 62, Issue 4: 467-488(2019) https://doi.org/10.1007/s11427-018-9458-0

Characterization and evolutionary dynamics of complex regions in eukaryotic genomes

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  • ReceivedOct 1, 2018
  • AcceptedNov 5, 2018
  • PublishedFeb 22, 2019

Abstract

Complex regions in eukaryotic genomes are typically characterized by duplications of chromosomal stretches that often include one or more genes repeated in a tandem array or in relatively close proximity. Nevertheless, the repetitive nature of these regions, together with the often high sequence identity among repeats, have made complex regions particularly recalcitrant to proper molecular characterization, often being misassembled or completely absent in genome assemblies. This limitation has prevented accurate functional and evolutionary analyses of these regions. This is becoming increasingly relevant as evidence continues to support a central role for complex genomic regions in explaining human disease, developmental innovations, and ecological adaptations across phyla. With the advent of long-read sequencing technologies and suitable assemblers, the development of algorithms that can accommodate sample heterozygosity, and the adoption of a pangenomic-like view of these regions, accurate reconstructions of complex regions are now within reach. These reconstructions will finally allow for accurate functional and evolutionary studies of complex genomic regions, underlying the generation of genotype-phenotype maps of unprecedented resolution.


Funded by

a National Science Foundation Grant(MCB-1157876)


Acknowledgment

This work was supported by a National Science Foundation Grant (MCB-1157876) to J.M.R.


Interest statement

The author(s) declare that they have no conflict of interest.


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  • Figure 1

    The Sdic multigene family of D. melanogaster. A, Each Sdic repeat is composed of three parts: a defective version of a TE; a truncated version of the parental gene AnxB10 (AnxB10-like); and the transcriptional unit Sdic (Nurminsky et al., 1998; Ponce and Hartl, 2006; Ranz et al., 2003). Sdic combines one stretch derived from AnxB10, contributing to the promoter region only, and three discontinued stretches from sw that donate to the transcribed region of Sdic. The first exon (*) derives from previously intronic sw sequence. This structure is quite similar across repeats with the exception of the most 3′ fourth of each transcriptional unit. B, The organization of the Sdic region across different releases of the genome assembly for the reference strain ISO-1 as in FlyBase. Sdic CN increased from four to seven in the latest release of the genome assembly. C, Reconstruction of the Sdic region using a genome assembly scaffolded with PacBio sequencing data (Berlin et al., 2015; Clifton et al., 2017). Sdic CN decreased from seven to six compared to the reference assembly. The different Sdic copies are only color-coded in the most reliable reconstruction of the region, denoting the differences they harbor at the nucleotide level.

  • Table 1   Modern genome sequencing technologies

    Sequencing system

    Sequencingmechanism

    Read lengths

    Single pass Error rate

    Sequencing output

    Advantages

    Disadvantages

    Sanger

    ABI 3730xl

    Sanger sequencing

    900 bp

    ~0.001%

    2.76 Mb/run

    Highest accuracy

    Short reads; very low throughput

    Roche

    454 GS-FLX

    Pyrosequencing

    up to 1000 bp

    ~1.0%

    0.7 Gb/run

    High accuracy;longest SGS reads

    Short reads; low throughput; very high cost

    Life Technologies

    SOLiD 5500xl

    Ligation and two-base coding

    75 bp (fragment)

    75 bp + 35 bp (paired-end)

    up to 60 bp + 60 bp (mate-paired)

    <0.1%

    160 Gb/run

    Highest SGSaccuracy

    Very short reads; high cost; poor ability to resolve repetitive regions

    Illumina

    HiSeq 4000

    MiSeq (v3 kit)

    NextSeq 550

    Sequencing by synthesis

    150 bp ×2

    300 bp ×2

    150 bp ×2

    ~0.1%

    1.3–1.5 Tb/flow cell

    13.2–15 Gb/flow cell

    100–120 Gb/flow cell

    High accuracy; high throughput; lowest cost

    Very short reads; poor ability to resolverepetitive regions

    Tru-Seq Synthetic Long Reads

    Sequencing by synthesis

    150 bp ×2

    ~10 kb synthetic reads

    ~0.1%

    Dependent on Illumina system

    Provides better alignment of short reads to repeats

    Poor ability to resolve highly similar repeats

    Pacific Biosciences

    Sequel

    Single Molecule Real-Time (SMRT) sequencing

    ~20 kb average

    >100 kb max

    10%–15%

    5–10 Gb/SMRT cell

    Longer reads

    Lowest accuracy

    Oxford Nanopore

    MinION

    Nanoporesequencing

    10–20 kb average

    ~900 kb max

    5%–15%

    10–20 Gb/flow cell

    Longest reads

    Low accuracy

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