Evidence map›Paper›PMID 38796435›Full record

ArticleBMC genomics2024

ACMGA: a reference-free multiple-genome alignment pipeline for plant species.

Huafeng Zhou, Xiaoquan Su, Baoxing Song

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Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Huafeng ZhouCollege of Computer Science and Technology, Qingdao University, Qingdao, Shandong, 266071, China.
Xiaoquan SuCollege of Computer Science and Technology, Qingdao University, Qingdao, Shandong, 266071, China. suxq@qdu.edu.cn.
Baoxing SongNational Key Laboratory of Wheat Improvement, Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong, 261325, China. baoxing.song@pku-iaas.edu.cn.

Funding

National Natural Science Foundation of China 31900486Shandong Provincial Natural Science Fund for Excellent Young Scientists Fund Program 2023HWYQ-109
6 · The paper itself

Abstract

backgroundThe short-read whole-genome sequencing (WGS) approach has been widely applied to investigate the genomic variation in the natural populations of many plant species. With the rapid advancements in long-read sequencing and genome assembly technologies, high-quality genome sequences are available for a group of varieties for many plant species. These genome sequences are expected to help researchers comprehensively investigate any type of genomic variants that are missed by the WGS technology. However, multiple genome alignment (MGA) tools designed by the human genome research community might be unsuitable for plant genomes.

resultsTo fill this gap, we developed the AnchorWave-Cactus Multiple Genome Alignment (ACMGA) pipeline, which improved the alignment of repeat elements and could identify long (> 50 bp) deletions or insertions (INDELs). We conducted MGA using ACMGA and Cactus for 8 Arabidopsis (Arabidopsis thaliana) and 26 Maize (Zea mays) de novo assembled genome sequences and compared them with the previously published short-read variant calling results. MGA identified more single nucleotide variants (SNVs) and long INDELs than did previously published WGS variant callings. Additionally, ACMGA detected significantly more SNVs and long INDELs in repetitive regions and the whole genome than did Cactus. Compared with the results of Cactus, the results of ACMGA were more similar to the previously published variants called using short-read. These two MGA pipelines identified numerous multi-allelic variants that were missed by the WGS variant calling pipeline.

conclusionsAligning de novo assembled genome sequences could identify more SNVs and INDELs than mapping short-read. ACMGA combines the advantages of AnchorWave and Cactus and offers a practical solution for plant MGA by integrating global alignment, a 2-piece-affine-gap cost strategy, and the progressive MGA algorithm.

Indexed as

ArabidopsisGenome, PlantZea maysGenomicsINDEL MutationPolymorphism, Single NucleotideSequence AlignmentSoftwareWhole Genome SequencingGenome comparisonMultiple genome alignmentPlant genome

Identifiers

PMID38796435
PMCPMC11127342

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.