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Large-scale analysis reveals that the genome features of simple sequence repeats are generally conserved at the family level in insects.

ABSTRACT: Simple sequence repeats (SSR), also called microsatellites, have been widely used as genetic markers, and have been extensively studied in some model insects. At present, the genomes of more than 100 insect species are available. However, the features of SSRs in most insect genomes remain largely unknown.We identified 15.01 million SSRs across 136 insect genomes. The number of identified SSRs was positively associated with genome size in insects, but the frequency and density per megabase of genomes were not. Most insect SSRs (56.2-93.1%) were perfect (no mismatch). Imperfect (at least one mismatch) SSRs (average length 22-73 bp) were longer than perfect SSRs (16-30 bp). The most abundant insect SSRs were the di- and trinucleotide types, which accounted for 27.2% and 22.0% of all SSRs, respectively. On average, 59.1%, 36.8%, and 3.7% of insect SSRs were located in intergenic, intronic, and exonic regions, respectively. The percentages of various types of SSRs were similar among insects from the same family. However, they were dissimilar among insects from different families within orders. We carried out a phylogenetic analysis using the SSR frequencies. Species from the same family were generally clustered together in the evolutionary tree. However, insects from the same order but not in the same family did not cluster together. These results indicated that although SSRs undergo rapid expansions and contractions in different populations of the same species, the general genomic features of insect SSRs remain conserved at the family level.Millions of insect SSRs were identified and their genome features were analyzed. Most insect SSRs were perfect and were located in intergenic regions. We presented evidence that the variance of insect SSRs accumulated after the differentiation of insect families.

SUBMITTER: Ding S

PROVIDER: S-EPMC5674736 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Large-scale analysis reveals that the genome features of simple sequence repeats are generally conserved at the family level in insects.

Ding Simin S Wang Shuping S He Kang K Jiang Mingxing M Li Fei F

BMC genomics 20171106 1

<h4>Background</h4>Simple sequence repeats (SSR), also called microsatellites, have been widely used as genetic markers, and have been extensively studied in some model insects. At present, the genomes of more than 100 insect species are available. However, the features of SSRs in most insect genomes remain largely unknown.<h4>Results</h4>We identified 15.01 million SSRs across 136 insect genomes. The number of identified SSRs was positively associated with genome size in insects, but the freque ...[more]

PMID: 29110701

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Project description:BackgroundSimple Sequence Repeats (SSRs) are short tandem repeats of nucleotide sequences. It has been shown that SSRs are associated with human diseases and are of medical relevance. Accordingly, a variety of computational methods have been proposed to mine SSRs from genomes. Conventional methods rely on a high-quality complete genome to identify SSRs. However, the sequenced genome often misses several highly repetitive regions. Moreover, many non-model species have no entire genomes. With the recent advances of next-generation sequencing (NGS) techniques, large-scale sequence reads for any species can be rapidly generated using NGS. In this context, a number of methods have been proposed to identify thousands of SSR loci within large amounts of reads for non-model species. While the most commonly used NGS platforms (e.g., Illumina platform) on the market generally provide short paired-end reads, merging overlapping paired-end reads has become a common way prior to the identification of SSR loci. This has posed a big data analysis challenge for traditional stand-alone tools to merge short read pairs and identify SSRs from large-scale data.ResultsIn this study, we present a new Hadoop-based software program, termed BigFiRSt, to address this problem using cutting-edge big data technology. BigFiRSt consists of two major modules, BigFLASH and BigPERF, implemented based on two state-of-the-art stand-alone tools, FLASH and PERF, respectively. BigFLASH and BigPERF address the problem of merging short read pairs and mining SSRs in the big data manner, respectively. Comprehensive benchmarking experiments show that BigFiRSt can dramatically reduce the execution times of fast read pairs merging and SSRs mining from very large-scale DNA sequence data.ConclusionsThe excellent performance of BigFiRSt mainly resorts to the Big Data Hadoop technology to merge read pairs and mine SSRs in parallel and distributed computing on clusters. We anticipate BigFiRSt will be a valuable tool in the coming biological Big Data era.

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Large-scale analysis reveals that the genome features of simple sequence repeats are generally conserved at the family level in insects.

Publications

Large-scale analysis reveals that the genome features of simple sequence repeats are generally conserved at the family level in insects.

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