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      Evolution of sex‐biased genes in Drosophila species with neo‐sex chromosomes: Potential contribution to reducing the sexual conflict

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          Abstract

          An advantage of sex chromosomes may be the potential to reduce sexual conflict because they provide a basis for selection to operate separately on females and males. However, evaluating the relationship between sex chromosomes and sexual conflict is challenging owing to the difficulty in measuring sexual conflict and substantial divergence between species with and without sex chromosomes. We therefore examined sex‐biased gene expression as a proxy for sexual conflict in three sets of Drosophila species with and without young sex chromosomes, the so‐called neo‐sex chromosomes. In all sets, we detected more sex‐biased genes in the species with neo‐sex chromosomes than in the species without neo‐sex chromosomes in larvae, pupae, and adult somatic tissues but not in gonads. In particular, many unbiased genes became either female‐ or male‐biased after linkage to the neo‐sex chromosomes in larvae, despite the low sexual dimorphism. For example, genes involved in metabolism, a key determinant for the rate of development in many animals, were enriched in the genes that acquired sex‐biased expression on the neo‐sex chromosomes at the larval stage. These genes may be targets of sexually antagonistic selection (i.e., large size and rapid development are selected for in females but selected against in males). These results indicate that acquiring neo‐sex chromosomes may have contributed to a reduction in sexual conflict, particularly at the larval stage, in Drosophila..

          Abstract

          In theory, having sex chromosomes is advantageous to reduce sexual conflict. Our analyses revealed that many genes have acquired the sex‐biased expression on the neo‐sex chromosomes particularly at the larval stage. Our study indicates that cryptic sexual conflict at the preadult stages cannot be ignored, and some of these conflicts may have been resolved by acquiring sex‐biased expression after the emergence of neo‐sex chromosomes in Drosophila.

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          Most cited references54

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

              Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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                Author and article information

                Contributors
                manozawa@tmu.ac.jp
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                23 July 2024
                July 2024
                : 14
                : 7 ( doiID: 10.1002/ece3.v14.7 )
                : e11701
                Affiliations
                [ 1 ] Department of Biological Sciences Tokyo Metropolitan University Hachioji Japan
                [ 2 ] Research Center for Genomics and Bioinformatics Tokyo Metropolitan University Hachioji Japan
                Author notes
                [*] [* ] Correspondence

                Masafumi Nozawa, Department of Biological Sciences, Tokyo Metropolitan University, Hachioji 192‐0397, Tokyo, Japan.

                Email: manozawa@ 123456tmu.ac.jp

                Author information
                https://orcid.org/0000-0003-1580-8312
                Article
                ECE311701 ECE-2024-03-00449.R1
                10.1002/ece3.11701
                11266434
                39050657
                d836812c-218e-4239-ac4a-639861400e36
                © 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 June 2024
                : 02 March 2024
                : 21 June 2024
                Page count
                Figures: 7, Tables: 3, Pages: 13, Words: 8700
                Funding
                Funded by: Japan Society for the Promotion of Science , doi 10.13039/501100001691;
                Award ID: 17H05015
                Award ID: 15K14585
                Award ID: 16H06279
                Award ID: 21H02539
                Award ID: 221S0002
                Award ID: 25711023
                Categories
                Evolutionary Ecology
                Genetics
                Genomics
                Research Article
                Research Article
                Custom metadata
                2.0
                July 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.5 mode:remove_FC converted:24.07.2024

                Evolutionary Biology
                drosophila,neo‐sex chromosome,sex‐biased gene expression,sexual conflict,sexual selection,sexual size dimorphism

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