Literature DB >> 29539638

Dysregulation of expression correlates with rare-allele burden and fitness loss in maize.

Karl A G Kremling1, Shu-Yun Chen2,3, Mei-Hsiu Su2, Nicholas K Lepak4, M Cinta Romay2, Kelly L Swarts1,5, Fei Lu2,6, Anne Lorant7, Peter J Bradbury4, Edward S Buckler1,2,4.   

Abstract

Here we report a multi-tissue gene expression resource that represents the genotypic and phenotypic diversity of modern inbred maize, and includes transcriptomes in an average of 255 lines in seven tissues. We mapped expression quantitative trait loci and characterized the contribution of rare genetic variants to extremes in gene expression. Some of the new mutations that arise in the maize genome can be deleterious; although selection acts to keep deleterious variants rare, their complete removal is impeded by genetic linkage to favourable loci and by finite population size. Modern maize breeders have systematically reduced the effects of this constant mutational pressure through artificial selection and self-fertilization, which have exposed rare recessive variants in elite inbred lines. However, the ongoing effect of these rare alleles on modern inbred maize is unknown. By analysing this gene expression resource and exploiting the extreme diversity and rapid linkage disequilibrium decay of maize, we characterize the effect of rare alleles and evolutionary history on the regulation of expression. Rare alleles are associated with the dysregulation of expression, and we correlate this dysregulation to seed-weight fitness. We find enrichment of ancestral rare variants among expression quantitative trait loci mapped in modern inbred lines, which suggests that historic bottlenecks have shaped regulation. Our results suggest that one path for further genetic improvement in agricultural species lies in purging the rare deleterious variants that have been associated with crop fitness.

Entities:  

Mesh:

Substances:

Year:  2018        PMID: 29539638     DOI: 10.1038/nature25966

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  36 in total

1.  Structure of linkage disequilibrium and phenotypic associations in the maize genome.

Authors:  D L Remington; J M Thornsberry; Y Matsuoka; L M Wilson; S R Whitt; J Doebley; S Kresovich; M M Goodman; E S Buckler
Journal:  Proc Natl Acad Sci U S A       Date:  2001-09-18       Impact factor: 11.205

2.  TASSEL: software for association mapping of complex traits in diverse samples.

Authors:  Peter J Bradbury; Zhiwu Zhang; Dallas E Kroon; Terry M Casstevens; Yogesh Ramdoss; Edward S Buckler
Journal:  Bioinformatics       Date:  2007-06-22       Impact factor: 6.937

3.  Recent demography drives changes in linked selection across the maize genome.

Authors:  Timothy M Beissinger; Li Wang; Kate Crosby; Arun Durvasula; Matthew B Hufford; Jeffrey Ross-Ibarra
Journal:  Nat Plants       Date:  2016-06-13       Impact factor: 15.793

4.  Regularization Paths for Generalized Linear Models via Coordinate Descent.

Authors:  Jerome Friedman; Trevor Hastie; Rob Tibshirani
Journal:  J Stat Softw       Date:  2010       Impact factor: 6.440

5.  Cassava haplotype map highlights fixation of deleterious mutations during clonal propagation.

Authors:  Punna Ramu; Williams Esuma; Robert Kawuki; Ismail Y Rabbi; Chiedozie Egesi; Jessen V Bredeson; Rebecca S Bart; Janu Verma; Edward S Buckler; Fei Lu
Journal:  Nat Genet       Date:  2017-04-17       Impact factor: 38.330

6.  A Bayesian framework to account for complex non-genetic factors in gene expression levels greatly increases power in eQTL studies.

Authors:  Oliver Stegle; Leopold Parts; Richard Durbin; John Winn
Journal:  PLoS Comput Biol       Date:  2010-05-06       Impact factor: 4.475

7.  Transcript profiling by 3'-untranslated region sequencing resolves expression of gene families.

Authors:  Andrea L Eveland; Donald R McCarty; Karen E Koch
Journal:  Plant Physiol       Date:  2007-11-16       Impact factor: 8.340

8.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583

9.  HTSeq--a Python framework to work with high-throughput sequencing data.

Authors:  Simon Anders; Paul Theodor Pyl; Wolfgang Huber
Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

10.  LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms.

Authors:  Daniel Money; Kyle Gardner; Zoë Migicovsky; Heidi Schwaninger; Gan-Yuan Zhong; Sean Myles
Journal:  G3 (Bethesda)       Date:  2015-09-15       Impact factor: 3.154

View more
  57 in total

1.  Comparative evolutionary genetics of deleterious load in sorghum and maize.

Authors:  Roberto Lozano; Elodie Gazave; Jhonathan P R Dos Santos; Markus G Stetter; Ravi Valluru; Nonoy Bandillo; Samuel B Fernandes; Patrick J Brown; Nadia Shakoor; Todd C Mockler; Elizabeth A Cooper; M Taylor Perkins; Edward S Buckler; Jeffrey Ross-Ibarra; Michael A Gore
Journal:  Nat Plants       Date:  2021-01-15       Impact factor: 15.793

2.  Evolutionarily informed deep learning methods for predicting relative transcript abundance from DNA sequence.

Authors:  Jacob D Washburn; Maria Katherine Mejia-Guerra; Guillaume Ramstein; Karl A Kremling; Ravi Valluru; Edward S Buckler; Hai Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2019-03-06       Impact factor: 11.205

3.  Adaptation and Phenotypic Diversification in Arabidopsis through Loss-of-Function Mutations in Protein-Coding Genes.

Authors:  Yong-Chao Xu; Xiao-Min Niu; Xin-Xin Li; Wenrong He; Jia-Fu Chen; Yu-Pan Zou; Qiong Wu; Yong E Zhang; Wolfgang Busch; Ya-Long Guo
Journal:  Plant Cell       Date:  2019-03-18       Impact factor: 11.277

4.  Metabolome-Scale Genome-Wide Association Studies Reveal Chemical Diversity and Genetic Control of Maize Specialized Metabolites.

Authors:  Shaoqun Zhou; Karl A Kremling; Nonoy Bandillo; Annett Richter; Ying K Zhang; Kevin R Ahern; Alexander B Artyukhin; Joshua X Hui; Gordon C Younkin; Frank C Schroeder; Edward S Buckler; Georg Jander
Journal:  Plant Cell       Date:  2019-03-28       Impact factor: 11.277

5.  Variation in Maize Chlorophyll Biosynthesis Alters Plant Architecture.

Authors:  Rajdeep S Khangura; Gurmukh S Johal; Brian P Dilkes
Journal:  Plant Physiol       Date:  2020-07-08       Impact factor: 8.340

Review 6.  Ten Years of the Maize Nested Association Mapping Population: Impact, Limitations, and Future Directions.

Authors:  Joseph L Gage; Brandon Monier; Anju Giri; Edward S Buckler
Journal:  Plant Cell       Date:  2020-05-12       Impact factor: 11.277

7.  Shared Genetic Control of Root System Architecture between Zea mays and Sorghum bicolor.

Authors:  Zihao Zheng; Stefan Hey; Talukder Jubery; Huyu Liu; Yu Yang; Lisa Coffey; Chenyong Miao; Brandi Sigmon; James C Schnable; Frank Hochholdinger; Baskar Ganapathysubramanian; Patrick S Schnable
Journal:  Plant Physiol       Date:  2019-11-18       Impact factor: 8.340

8.  Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions.

Authors:  Peng Zhou; Zhi Li; Erika Magnusson; Fabio Gomez Cano; Peter A Crisp; Jaclyn M Noshay; Erich Grotewold; Candice N Hirsch; Steven P Briggs; Nathan M Springer
Journal:  Plant Cell       Date:  2020-03-17       Impact factor: 11.277

9.  The Fate of Deleterious Variants in a Barley Genomic Prediction Population.

Authors:  Thomas J Y Kono; Chaochih Liu; Emily E Vonderharr; Daniel Koenig; Justin C Fay; Kevin P Smith; Peter L Morrell
Journal:  Genetics       Date:  2019-10-25       Impact factor: 4.562

10.  Haplotype structure in commercial maize breeding programs in relation to key founder lines.

Authors:  Stephanie M Coffman; Matthew B Hufford; Carson M Andorf; Thomas Lübberstedt
Journal:  Theor Appl Genet       Date:  2019-11-20       Impact factor: 5.699

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.