Loss of Function of an RNA Polymerase III Subunit Leads to Impaired Maize Kernel Development

Zhao, Hailiang; Qin, Yao; Xiao, Ziyi; Li, Qi; Pan, Zhenyuan; Gong, Dianming; Sun, Qin; Yang, Fang; Zhang, Zuxin; Cao, Xu; Qiu, Fazhan

doi:10.1104/pp.20.00502

Cited by 17 publications

(18 citation statements)

References 80 publications

(89 reference statements)

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“…Previous reports have shown that ZmNRPC2 controls seed development by regulating cell proliferation and endoreduplication in maize endosperm [ 22 ]. GL6 interacts with RNAPIII subunit C53 (NRPC4) and transcription factor class C1 (TFC1), regulating the expression of genes involved in rice grain development to promote cell proliferation in young panicles and grains [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

“…A partial loss of function of RNAPIII subunit NRPC7 leads to pleiotropic defects such as shorter siliques and roots, delay in flowering time, bumpy sepal texture, and irregular sepal shape [ 50 ]. NRPC2 regulates cell proliferation and endoreduplication to control endosperm development in maize [ 22 ]. The PLANTZ protein FL3 participates in the regulation of RNAPIII transcription machinery and regulates storage reserve filling in maize [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, a splice-site substitution of NRPC2 suppresses RNAPIII transcriptional activity, disrupting the proliferation and growth of tissue progenitor cells in the zebrafish digestive system [ 20 ]. The mutation of NRPC2 in mice reduces intestinal epithelial cell proliferation and impaired crypt development [ 21 ]; meanwhile, loss of NRPC2 function represses cell proliferation and endoreduplication in maize endosperm [ 22 ]. Despite these findings, we noticed that these mutants only occupy small parts of all subunits of RNAPIII, indicating the difficulty of isolating mutations in other RNAPIII subunits.…”

Section: Introductionmentioning

confidence: 99%

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Knockdown NRPC2, 3, 8, NRPABC1 and NRPABC2 Affects RNAPIII Activity and Disrupts Seed Development in Arabidopsis

Zhao

Qin

Xiao

et al. 2021

IJMS

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RNA polymerase III (RNAPIII) contains 17 subunits forming 4 functional domains that control the different stages of RNAPIII transcription and are dedicated to the synthesis of small RNAs such as 5S rRNA and tRNAs. Here, we identified 23 genes encoding these subunits in Arabidopsis (Arabidopsis thaliana) and further analyzed 5 subunits (NRPC2, NRPC3, NRPC8, NRPABC1, and NRPABC2) encoded by 6 genes with different expression patterns and belonging to different sub-complexes. The knockdown of these genes repressed the expression of 5S rRNA and tRNAs, causing seed developmental arrest at different stages. Among these knockdown mutants, RNA-seq analysis revealed 821 common differentially expressed genes (DEGs), significantly enriched in response to stress, abscisic acid, cytokinins, and the jasmonic acid signaling pathway. Weighted gene co-expression network analysis (WGCNA) revealed several hub genes involved in embryo development, carbohydrate metabolic and lipid metabolic processes. We identified numerous unique DEGs between the mutants belonging to pathways, including cell proliferation, ribosome biogenesis, cell death, and tRNA metabolic processes. Thus, NRPC2, NRPC3, NRPC8, NRPABC1, and NRPABC2 control seed development in Arabidopsis by influencing RNAPIII activity and, thus, hormone signaling. Reduced expression of these subunit genes causes an insufficient accumulation of the total RNAPIII, leading to the phenotypes observed following the genetic knockdown of these subunits.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Knockdown NRPC2, 3, 8, NRPABC1 and NRPABC2 Affects RNAPIII Activity and Disrupts Seed Development in Arabidopsis

Zhao

Qin

Xiao

et al. 2021

IJMS

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“…As such, potentially functional variants in protein-coding regions are assumed to be easier to detect (e.g., by association analyses) than variants that moderate gene expression [ 5 – 7 ]. Thus, missense and LOF variants are typically prioritised as putative causal variants for traits of interest (e.g., [ 8 – 11 ]).…”

Section: Introductionmentioning

confidence: 99%

Rare and population-specific functional variation across pig lines

et al. 2022

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Background It is expected that functional, mainly missense and loss-of-function (LOF), and regulatory variants are responsible for most phenotypic differences between breeds and genetic lines of livestock species that have undergone diverse selection histories. However, there is still limited knowledge about the existing missense and LOF variation in commercial livestock populations, in particular regarding population-specific variation and how it can affect applications such as across-breed genomic prediction. Methods We re-sequenced the whole genome of 7848 individuals from nine commercial pig lines (average sequencing coverage: 4.1×) and imputed whole-genome genotypes for 440,610 pedigree-related individuals. The called variants were categorized according to predicted functional annotation (from LOF to intergenic) and prevalence level (number of lines in which the variant segregated; from private to widespread). Variants in each category were examined in terms of their distribution along the genome, alternative allele frequency, per-site Wright’s fixation index (FST), individual load, and association to production traits. Results Of the 46 million called variants, 28% were private (called in only one line) and 21% were widespread (called in all nine lines). Genomic regions with a low recombination rate were enriched with private variants. Low-prevalence variants (called in one or a few lines only) were enriched for lower allele frequencies, lower FST, and putatively functional and regulatory roles (including LOF and deleterious missense variants). On average, individuals carried fewer private deleterious missense alleles than expected compared to alleles with other predicted consequences. Only a small subset of the low-prevalence variants had intermediate allele frequencies and explained small fractions of phenotypic variance (up to 3.2%) of production traits. The significant low-prevalence variants had higher per-site FST than the non-significant ones. These associated low-prevalence variants were tagged by other more widespread variants in high linkage disequilibrium, including intergenic variants. Conclusions Most low-prevalence variants have low minor allele frequencies and only a small subset of low-prevalence variants contributed detectable fractions of phenotypic variance of production traits. Accounting for low-prevalence variants is therefore unlikely to noticeably benefit across-breed analyses, such as the prediction of genomic breeding values in a population using reference populations of a different genetic background.

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“…As such, potentially functional variants in proteincoding regions are assumed to be easier to detect (e.g., by association analyses) than variants that moderate gene expression [5][6][7]. Thus, missense and LOF variants are typically prioritised as putative causal variants for the traits of interest (e.g., [8][9][10][11]).…”

Section: Introductionmentioning

confidence: 99%

Rare and population-specific functional variation across pig lines

Ros‐Freixedes

Valente

Chen

et al. 2022

Preprint

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BackgroundIt is expected that missense and loss-of-function (LOF) variants are responsible for phenotypic differences among breeds, genetic lines and varieties of livestock and crop species that have undergone diverse selection histories. However, there is still limited knowledge about the existing missense and LOF variation in livestock commercial populations, in particular regarding population-specific variation.MethodsWe performed whole-genome re-sequencing of 7,848 individuals from nine commercial pig breeding lines (average coverage: 4.1x) and imputed genotypes for 440,610 pedigree-related individuals. The variants were categorized according to predicted functional annotation (from loss-of-function to intergenic) and prevalence level (number of lines in which the variant segregated; from private to widespread). Variants in each category were examined in terms of distribution along the genome, minor allele frequency, Wright’s fixation index (FST), individual load, and association to production traits.ResultsOf the 46 million called variants, 28% were private (i.e., called in only one line) and 21% were widespread (i.e., called in all nine lines). Genomic regions with low recombination rate were enriched with private variants. Low-prevalence variants were enriched for lower allele frequencies, lower FST, and putatively functional and regulatory variants (including loss-of-function and deleterious missense). Only a small subset of low-prevalence variants was found at intermediate allele frequencies and had large estimated effects on production traits. Individuals on average carried less private deleterious missense alleles than expected compared to other predicted consequence types. A small subset of low-prevalence variants with intermediate allele frequencies and higher FST were detected as significantly associated to the production traits and explained small fractions of phenotypic variance (up to 3.2%). These associations were tagged by other more widespread variants, including intergenic variants.ConclusionsMost low-prevalence variants are kept at very low allele frequency and only a small subset contributed detectable fractions of phenotypic variance. Low-prevalence variants are therefore unlikely to hinder across-breed analyses, in particular when predicting genomic breeding values using reference populations of a different genetic background.

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Loss of Function of an RNA Polymerase III Subunit Leads to Impaired Maize Kernel Development

Cited by 17 publications

References 80 publications

Knockdown NRPC2, 3, 8, NRPABC1 and NRPABC2 Affects RNAPIII Activity and Disrupts Seed Development in Arabidopsis

Knockdown NRPC2, 3, 8, NRPABC1 and NRPABC2 Affects RNAPIII Activity and Disrupts Seed Development in Arabidopsis

Rare and population-specific functional variation across pig lines

Rare and population-specific functional variation across pig lines

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