Genomic evidence for homoploid hybrid speciation between ancestors of two different genera

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Abstract

Homoploid hybrid speciation (HHS) has been increasingly recognized as occurring widely during species diversification of both plants and animals. However, previous studies on HHS have mostly focused on closely-related species while it has been rarely reported or tested between ancestors of different genera. Here, we explore the likely HHS origin of Carpinus sect. Distegocarpus between sect. Carpinus and Ostrya in the family Betulaceae. We generate a chromosome-level reference genome for C. viminea of sect. Carpinus and re-sequence genomes of 44 individuals from the genera Carpinus and Ostrya. Our integrated analyses of all genomic data suggest that sect. Distegocarpus, which has three species, likely originates through HHS during the early divergence between Carpinus and Ostrya. Our study highlights the likelihood of an HHS event between ancestors of the extant genera during their initial divergences, which may have led to reticulate phylogenies at higher taxonomic levels.

Abstract

Carpinus fangiana exhibits intermediate morphology between C. viminea and Ostrya rehderiana. Here, the authors report that Carpinus sect. Distegocarpus likely originate through homoploid hybrid speciation (HHS) during the early divergence between Carpinus and Ostrya through genomic analyses.

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Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin (2009)

Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk

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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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The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

Aaron McKenna, Matthew Hanna, Eric Banks … (2010)

Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

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Author and article information

Contributors

Jianquan Liu:

ORCID: http://orcid.org/0000-0002-4237-7418

liujq@nwipb.ac.cn

Journal

Journal ID (nlm-ta): Nat Commun

Journal ID (iso-abbrev): Nat Commun

Title: Nature Communications

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2041-1723

Publication date (Electronic): 13 April 2022

Publication date PMC-release: 13 April 2022

Publication date Collection: 2022

Volume: 13

Electronic Location Identifier: 1987

Affiliations

[1 ]GRID grid.13291.38, ISNI 0000 0001 0807 1581, State Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, , Sichuan University, ; Chengdu, Sichuan China

[2 ]GRID grid.32566.34, ISNI 0000 0000 8571 0482, State Key Laboratory of Grassland Agro-Ecosystem, College of Ecology, , Lanzhou University, ; Lanzhou, Gansu China

Author information

Zefu Wang http://orcid.org/0000-0002-5440-4188

Jialiang Li http://orcid.org/0000-0003-1700-131X

Zhiyang Zhang http://orcid.org/0000-0002-9466-9439

Jianquan Liu http://orcid.org/0000-0002-4237-7418

Article

Publisher ID: 29643

DOI: 10.1038/s41467-022-29643-4

PMC ID: 9008057

PubMed ID: 35418567

SO-VID: 0c5ff004-4155-4a85-831a-af6327408920

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 1 July 2021

Date accepted : 25 March 2022

Funding

Funded by: This work was supported equally by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB31000000), the National Natural Science Foundation of China (grant numbers 31590821) and the National Key Research and Development Program of China (2017YFC0505203), and also by Fundamental Research Funds for the Central Universities (SCU2019D013 and 2020SCUNL207), and National High-Level Talents Special Support Plan (10 Thousand of People Plan).

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ScienceOpen disciplines: Uncategorized

Keywords: evolutionary genetics,evolutionary biology,ecological genetics,plant evolution

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ScienceOpen disciplines: Uncategorized

Keywords: evolutionary genetics, evolutionary biology, ecological genetics, plant evolution

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Genomic evidence for homoploid hybrid speciation between ancestors of two different genera

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Most cited references 69

Fast and accurate short read alignment with Burrows–Wheeler transform

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

The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

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Cited by 14

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