Chloroplast acquisition without the gene transfer in kleptoplastic sea slugs, 
      <i>Plakobranchus ocellatus</i>

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Abstract

Some sea slugs sequester chloroplasts from algal food in their intestinal cells and photosynthesize for months. This phenomenon, kleptoplasty, poses a question of how the chloroplast retains its activity without the algal nucleus. There have been debates on the horizontal transfer of algal genes to the animal nucleus. To settle the arguments, this study reported the genome of a kleptoplastic sea slug, Plakobranchus ocellatus, and found no evidence of photosynthetic genes encoded on the nucleus. Nevertheless, it was confirmed that light illumination prolongs the life of mollusk under starvation. These data presented a paradigm that a complex adaptive trait, as typified by photosynthesis, can be transferred between eukaryotic kingdoms by a unique organelle transmission without nuclear gene transfer. Our phylogenomic analysis showed that genes for proteolysis and immunity undergo gene expansion and are up-regulated in chloroplast-enriched tissue, suggesting that these molluskan genes are involved in the phenotype acquisition without horizontal gene transfer.

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Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2022)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

Kazutaka Katoh, Daron Standley (2013)

We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.

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RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

Alexandros Stamatakis (2014)

Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.

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Author and article information

Contributors

Taro Maeda:

ORCID: https://orcid.org/0000-0003-4185-0135

Shuji Shigenobu:

ORCID: https://orcid.org/0000-0003-4640-2323

Kristin Tessmar-Raible: Role: Reviewing Editor

Christian S Hardtke: Role: Senior Editor

Journal

Journal ID (nlm-ta): eLife

Journal ID (iso-abbrev): Elife

Journal ID (publisher-id): eLife

Title: eLife

Publisher: eLife Sciences Publications, Ltd

ISSN (Electronic): 2050-084X

Publication date (Electronic, pub): 27 April 2021

Publication date Collection: 2021

Volume: 10

Electronic Location Identifier: e60176

Affiliations

[1 ]National Institute for Basic Biology OkazakiJapan

[2 ]Sesoko Station, Tropical Biosphere Research Center, University of the Ryukyu OkinawaJapan

[3 ]Japan Agency for Marine-Earth Science and Technology YokosukaJapan

[4 ]National Institute of Genetics ShizuokaJapan

[5 ]The University of Tokyo TokyoJapan

[6 ]Marine Biological Laboratory, Hiroshima University HiroshimaJapan

[7 ]Kyoto Prefectural University KyotoJapan

[8 ]Okinawa Institute of Science and Technology Graduate University OkinawaJapan

[9 ]Research Center for Experimental Modeling of Human Disease, Kanazawa University KanazawaJapan

[10 ]SOKENDAI, the Graduate University for Advanced Studies OkazakiJapan

[11 ]Kitasato University TokyoJapan

[12 ]Setsunan Universiy HirakataJapan

University of Vienna Austria

University of Lausanne Switzerland

University of Vienna Austria

Sun Yat-sen University Cancer Center China

Author notes

[†]

Ryukoku University, Otsu, Japan.

Author information

Taro Maeda https://orcid.org/0000-0003-4185-0135

Atsushi Toyoda http://orcid.org/0000-0002-0728-7548

Nori Satoh http://orcid.org/0000-0002-4480-3572

Jun Minagawa http://orcid.org/0000-0002-3028-3203

Shuji Shigenobu https://orcid.org/0000-0003-4640-2323

Article

Publisher ID: 60176

DOI: 10.7554/eLife.60176

PMC ID: 8079154

PubMed ID: 33902812

SO-VID: 0a3dcb7e-8b1c-45af-ac8b-82caac400ee0

License:

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.