Genome-wide analysis of deletions in maize population reveals abundant genetic diversity and functional impact

Zhang, Xiao; Zhu, Yonghui; Kremling, Karl A.; Romay, M. Cinta; Bukowski, Robert; Sun, Qi; Buckler, Edward S.; Lü, Fei

doi:10.1007/s00122-021-03965-1

Cited by 9 publications

(7 citation statements)

References 91 publications

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“…However, little is known about intra‐wheat translocations and larger PAVs. GWAS is an efficient method for systematic identification of candidate genomic loci responsible for phenotypic variation (Kou et al., 2020; Zhang et al., 2015; Zhang et al., 2022; Zhou et al., 2015). However, GWAS has not previously been employed to reveal the genetic effects of SCVs in wheat, due to a lack of phenotype and corresponding SCV data for natural populations.…”

Section: Discussionmentioning

confidence: 99%

“…Zhang et al. (2022) also found that only a few genes were identified in both analyses of deletions and of SNPs for the same phenotypic traits, and most candidate genes were novel loci that could not be found in known large‐effect genes. SCVs can modulate phenotypes by altering gene expression in certain regions.…”

Section: Discussionmentioning

confidence: 99%

“…SVs affect more nucleotides than single nucleotide polymorphisms (SNPs) and have a larger or comparable effect (Abyzov et al., 2016). With the development of genome sequencing and assembly techniques, SV identification has been conducted in numerous plant species (Crow et al., 2020; Della Coletta et al., 2021; Girirajan et al., 2011; Kou et al., 2020; Sun et al., 2018; Tao et al., 2021; Walkowiak et al., 2020; Yang et al., 2019; Zhang et al., 2022; Zheng et al., 2011). These studies indicated that SVs are pervasive throughout the genome and play important roles in environmental adaptation, domestication, and trait architecture (Francia et al., 2016; Huang et al., 2021; Liu, Du, et al., 2020; Qian et al., 2016; Qin et al., 2021; Sutton et al., 2007; Würschum et al., 2015).…”

Section: Introductionmentioning

confidence: 99%

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Genome‐wide association study reveals structural chromosome variations with phenotypic effects in wheat (Triticum aestivum L.)

et al. 2022

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SUMMARY Structural chromosome variations (SCVs) are large‐scale genomic variations that can be detected by fluorescence in situ hybridization (FISH). SCVs have played important roles in the genome evolution of wheat (Triticum aestivum L.), but little is known about their genetic effects. In this study, a total of 543 wheat accessions from the Chinese wheat mini‐core collection and the Shanxi Province wheat collection were used for chromosome analysis using oligonucleotide probe multiplex FISH. A total of 139 SCVs including translocations, pericentric inversions, presence/absence variations (PAVs), and copy number variations (CNVs) in heterochromatin were identified at 230 loci. The distribution frequency of SCVs varied between ecological regions and between landraces and modern cultivars. Structural analysis using SCVs as markers clearly divided the landraces and modern cultivars into different groups. There are very clear instances illustrating alien introgression and wide application of foreign germplasms improved the chromosome diversity of Chinese modern wheat cultivars. A genome‐wide association study (GWAS) identified 29 SCVs associated with 12 phenotypic traits, and five (RT4AS•4AL‐1DS/1DL•1DS‐4AL, Mg2A‐3, Mr3B‐10, Mr7B‐13, and Mr4A‐7) of them were further validated using a doubled haploid population and advanced sib‐lines, implying the potential value of these SCVs. Importantly, the number of favored SCVs that were associated with agronomic trait improvement was significantly higher in modern cultivars compared to landraces, indicating positive selection in wheat breeding. This study demonstrates the significant effects of SCVs during wheat breeding and provides an efficient method of mining favored SCVs in wheat and other crops.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genome‐wide association study reveals structural chromosome variations with phenotypic effects in wheat (Triticum aestivum L.)

et al. 2022

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“…However, sometimes large fragment deletion is needed, such as knocking out relative longer regulation elements like non‐coding regions (Tan et al ., 2020 ) and changing genomic location of regulatory elements to create long‐distance trans‐regulatory modification (Fraser and Bickmore, 2007 ). Besides, genome deletion editing is also needed for studies of the effect of genome structural variation (SV) on biological phenotype (Zhang et al ., 2022 ) and the effect of gene copy number variation (gene dosage) on gene expression (Gamazon and Stranger, 2015 ). Paired sgRNAs‐based method can be used for programming genomic deletions via generating a pair of nearby DNA double‐strand breaks (DSBs) (Khosravi et al ., 2019 ; Zhu et al ., 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Targeted large fragment deletion in plants using paired crRNAs with type I CRISPR system

Li,

Huang,

Chen

et al. 2023

Plant Biotechnology Journal

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SummaryThe CRISPR‐Cas systems have been widely used as genome editing tools, with type II and V systems typically introducing small indels, and type I system mediating long‐range deletions. However, the precision of type I systems for large fragment deletion is still remained to be optimized. Here, we developed a compact Cascade‐Cas3 Dvu I‐C system with Cas11c for plant genome editing. The Dvu I‐C system was efficient to introduce controllable large fragment deletion up to at least 20 kb using paired crRNAs. The paired‐crRNAs design also improved the controllability of deletions for the type I‐E system. Dvu I‐C system was sensitive to spacer length and mismatch, which was benefit for target specificity. In addition, we showed that the Dvu I‐C system was efficient for generating stable transgenic lines in maize and rice with the editing efficiency up to 86.67%. Overall, Dvu I‐C system we developed here is powerful for achieving controllable large fragment deletions.

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“…In contrast to the human genome, where SVs affect a mere 1.5% of the genome when comparing two individuals [3,4], the plant genome is in flux-due to frequent genome duplications and the proliferation of transposable elements (TEs) [5], SVs can comprise up to 50% of the genome when comparing two individuals in one species [6][7][8]. A growing body of genomic analyses has shown the pivotal role of SVs in shaping plant phenotypic traits, with a broad scope from gene expression to environmental adaptation [9][10][11][12][13][14]. Meanwhile, quantitative trait locus (QTL) mapping has identified SVs as causative genetic variations controlling important agronomic traits of crops, such as flowering time in maize (e.g., Vgt1 [15], ZmCCT [16,17]), grain yield in rice (e.g., GW5 [18] and GL7 [19]), solid-stemmed architecture in wheat (e.g., TdDof [20]), and aroma volatiles in tomato (e.g., NSGT1 [21] and NSGT2 [9]), etc.…”

Section: Introductionmentioning

confidence: 99%

Structural variation discovery in wheat using PacBio high-fidelity sequencing

Zhang,

Kang

et al. 2023

Preprint

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BackgroundStructural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed because of their complex nature and the limitations of early genomic technologies. The recent advance in third-generation sequencing, particularly the PacBio high-fidelity (HiFi) sequencing technology, produces highly accurate long-reads and offers an unprecedented opportunity to characterize SVs’ structure and functionality. As HiFi sequencing is relatively new to population genomics, it is imperative to evaluate and optimize HiFi sequencing based SV detection before applying the technology at scale.ResultsWe sequenced wheat genomes using HiFi reads, followed by a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results showed that the accuracy of deletion discovery is markedly influenced by callers, which account for 87.73% of the variance, while both aligners (38.25%) and callers (49.32%) contributed substantially to the accuracy variance for insertions. Among the aligners, Winnowmap2 and NGMLR excelled in detecting deletions and insertions, respectively. For SV callers, SVIM achieved the best performance. We demonstrated that combining the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the effect of sequencing depth on the accuracy of SV detection, showing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery.ConclusionsThis study thoroughly evaluated SV discovery approaches using HiFi reads, establishing optimal workflows to investigate structural variations in the wheat genome. The notable accuracy of SV discovery from low-coverage HiFi sequencing indicates that skim HiFi sequencing is effective and preferable to characterize SVs at the population level. This study will help advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.

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Genome-wide analysis of deletions in maize population reveals abundant genetic diversity and functional impact

Cited by 9 publications

References 91 publications

Genome‐wide association study reveals structural chromosome variations with phenotypic effects in wheat (Triticum aestivum L.)

Genome‐wide association study reveals structural chromosome variations with phenotypic effects in wheat (Triticum aestivum L.)

Targeted large fragment deletion in plants using paired crRNAs with type I CRISPR system

Structural variation discovery in wheat using PacBio high-fidelity sequencing

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