A genome-wide association study of lateral root number for Asian cotton (Gossypium arboreum L.)

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Abstract

Background

The lateral root is one of the most important organs that constitute the root architecture system in plants. It can directly affect the contact area between plants and soil and plays an important role in plant structural support and nutrient absorption. Optimizing root architecture systems can greatly increase crop yields. This study was designed to identify the molecular markers and candidate genes associated with lateral root development in cotton and to evaluate correlations with yield and disease traits.

Result

The number of lateral roots for 14-day old seedlings was recorded for 215 Gossypium arboreum accessions. A correlation analysis showed that the number of lateral roots positively correlates with the sympodial branch node and seed index traits, but negatively correlates with lint percentage. A Genome-wide association study (GWAS) identified 18 significant SNPs with 19 candidate genes associated with the lateral root number. Expression analysis identified three genes ( FLA12, WRKY29, and RBOHA) associated with lateral root development.

Conclusion

GWAS analysis identified key SNPs and candidate genes for lateral root number, and genes of FLA12, WRKY29, and RBOHA may play a pivotal role in lateral root development in Asian cotton.

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Most cited references 49

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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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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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ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

Kai Wang, Mingyao Li, Hakon Hakonarson (2010)

High-throughput sequencing platforms are generating massive amounts of genetic variation data for diverse genomes, but it remains a challenge to pinpoint a small subset of functionally important variants. To fill these unmet needs, we developed the ANNOVAR tool to annotate single nucleotide variants (SNVs) and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP. ANNOVAR can utilize annotation databases from the UCSC Genome Browser or any annotation data set conforming to Generic Feature Format version 3 (GFF3). We also illustrate a ‘variants reduction’ protocol on 4.7 million SNVs and indels from a human genome, including two causal mutations for Miller syndrome, a rare recessive disease. Through a stepwise procedure, we excluded variants that are unlikely to be causal, and identified 20 candidate genes including the causal gene. Using a desktop computer, ANNOVAR requires ∼4 min to perform gene-based annotation and ∼15 min to perform variants reduction on 4.7 million variants, making it practical to handle hundreds of human genomes in a day. ANNOVAR is freely available at http://www.openbioinformatics.org/annovar/ .

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Author and article information

Contributors

Xiongming DU: (View ORCID Profile)

Journal

Title: Journal of Cotton Research

Abbreviated Title: J Cotton Res

Publisher: Springer Science and Business Media LLC

ISSN (Electronic): 2523-3254

Publication date Created: December 2022

Publication date (Electronic): June 27 2022

Publication date (Print): December 2022

Volume: 5

Issue: 1

Article

DOI: 10.1186/s42397-022-00126-7

SO-VID: 9aea2d98-1082-4212-8f0e-a9a5671a8e4d

License:

https://creativecommons.org/licenses/by/4.0

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A genome-wide association study of lateral root number for Asian cotton (Gossypium arboreum L.)

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Abstract

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Genome Integrity

Most cited references 49

Fast and accurate short read alignment with Burrows–Wheeler transform

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

ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

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