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      Genome-wide quantification of homeolog expression ratio revealed nonstochastic gene regulation in synthetic allopolyploid Arabidopsis

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          Abstract

          Genome duplication with hybridization, or allopolyploidization, occurs commonly in plants, and is considered to be a strong force for generating new species. However, genome-wide quantification of homeolog expression ratios was technically hindered because of the high homology between homeologous gene pairs. To quantify the homeolog expression ratio using RNA-seq obtained from polyploids, a new method named HomeoRoq was developed, in which the genomic origin of sequencing reads was estimated using mismatches between the read and each parental genome. To verify this method, we first assembled the two diploid parental genomes of Arabidopsis halleri subsp. gemmifera and Arabidopsis lyrata subsp. petraea ( Arabidopsis petraea subsp. umbrosa), then generated a synthetic allotetraploid, mimicking the natural allopolyploid Arabidopsis kamchatica. The quantified ratios corresponded well to those obtained by Pyrosequencing. We found that the ratios of homeologs before and after cold stress treatment were highly correlated ( r = 0.870). This highlights the presence of nonstochastic polyploid gene regulation despite previous research identifying stochastic variation in expression. Moreover, our new statistical test incorporating overdispersion identified 226 homeologs (1.11% of 20 369 expressed homeologs) with significant ratio changes, many of which were related to stress responses. HomeoRoq would contribute to the study of the genes responsible for polyploid-specific environmental responses.

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          Most cited references63

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          The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana.

          To take complete advantage of information on within-species polymorphism and divergence from close relatives, one needs to know the rate and the molecular spectrum of spontaneous mutations. To this end, we have searched for de novo spontaneous mutations in the complete nuclear genomes of five Arabidopsis thaliana mutation accumulation lines that had been maintained by single-seed descent for 30 generations. We identified and validated 99 base substitutions and 17 small and large insertions and deletions. Our results imply a spontaneous mutation rate of 7 x 10(-9) base substitutions per site per generation, the majority of which are G:C-->A:T transitions. We explain this very biased spectrum of base substitution mutations as a result of two main processes: deamination of methylated cytosines and ultraviolet light-induced mutagenesis.
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            Evolutionary changes in cis and trans gene regulation.

            Differences in gene expression are central to evolution. Such differences can arise from cis-regulatory changes that affect transcription initiation, transcription rate and/or transcript stability in an allele-specific manner, or from trans-regulatory changes that modify the activity or expression of factors that interact with cis-regulatory sequences. Both cis- and trans-regulatory changes contribute to divergent gene expression, but their respective contributions remain largely unknown. Here we examine the distribution of cis- and trans-regulatory changes underlying expression differences between closely related Drosophila species, D. melanogaster and D. simulans, and show functional cis-regulatory differences by comparing the relative abundance of species-specific transcripts in F1 hybrids. Differences in trans-regulatory activity were inferred by comparing the ratio of allelic expression in hybrids with the ratio of gene expression between species. Of 29 genes with interspecific expression differences, 28 had differences in cis-regulation, and these changes were sufficient to explain expression divergence for about half of the genes. Trans-regulatory differences affected 55% (16 of 29) of genes, and were always accompanied by cis-regulatory changes. These data indicate that interspecific expression differences are not caused by select trans-regulatory changes with widespread effects, but rather by many cis-acting changes spread throughout the genome.
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              Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data

              Motivation: Next-generation sequencing has become an important tool for genome-wide quantification of DNA and RNA. However, a major technical hurdle lies in the need to map short sequence reads back to their correct locations in a reference genome. Here, we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE). Results: We generated 16 million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these reads to the human genome we found that, at heterozygous SNPs, there was a significant bias toward higher mapping rates of the allele in the reference sequence, compared with the alternative allele. Masking known SNP positions in the genome sequence eliminated the reference bias but, surprisingly, did not lead to more reliable results overall. We find that even after masking, ∼5–10% of SNPs still have an inherent bias toward more effective mapping of one allele. Filtering out inherently biased SNPs removes 40% of the top signals of ASE. The remaining SNPs showing ASE are enriched in genes previously known to harbor cis-regulatory variation or known to show uniparental imprinting. Our results have implications for a variety of applications involving detection of alternate alleles from short-read sequence data. Availability: Scripts, written in Perl and R, for simulating short reads, masking SNP variation in a reference genome and analyzing the simulation output are available upon request from JFD. Raw short read data were deposited in GEO (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE18156. Contact: jdegner@uchicago.edu; marioni@uchicago.edu; gilad@uchicago.edu; pritch@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                April 2014
                13 January 2014
                13 January 2014
                : 42
                : 6
                : e46
                Affiliations
                1Department of Computer Science, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan and 2Institute of Evolutionary Biology and Environmental Studies and Institute of Plant Biology, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
                Author notes
                *To whom correspondence should be addressed. Tel: +81 3 5734 3526; Fax: +81 3 5734 3526; Email: sesejun@ 123456cs.titech.ac.jp
                Correspondence may also be addressed to Kentaro K. Shimizu. Tel: +41 44 635 67 40; Fax: +41 44 635 68 21; Email: kentaro.shimizu@ 123456ieu.uzh.ch

                These authors contributed equally to the paper as first authors.

                Article
                gkt1376
                10.1093/nar/gkt1376
                3973336
                24423873
                f821d30f-3831-4f6d-bcef-3e7de5208021
                © The Author(s) 2014. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 5 June 2013
                : 26 November 2013
                : 14 December 2013
                Page count
                Pages: 15
                Categories
                Methods Online

                Genetics
                Genetics

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