Genetic variation in transcription factors and photosynthesis light-reaction genes regulates photosynthetic traits

Transcription factors (TFs) play crucial roles in regulating the production of the components required for photosynthesis; elucidating the mechanisms by which underlying genetic variation in TFs affects complex photosynthesis-related traits may improve our understanding of photosynthesis and identify ways to improve photosynthetic efficiency. Promoter analysis of 96 nuclear-encoded Populus tomentosa Carr. genes within this pathway revealed 47 motifs responsive to light, stress, hormones and organ-specific regulation, as well as 86 TFs that might bind these motifs. Using phenotype-genotype associations, we identified 244 single-nucleotide polymorphisms (SNPs) within 105 genes associated with 12 photosynthesis-related traits. Most (30.33%) of these SNPs were located in intronic regions and these SNPs explained 18.66% of the mean phenotypic variation in the photosynthesis-related traits. Additionally, expression quantitative trait loci (eQTL) mapping identified 216 eQTLs associated with 110 eGenes (genes regulated by eQTLs), explaining 14.12% of the variability of gene expression. The lead SNPs of 12.04% of the eQTLs also contributed to phenotypic variation. Among these, a SNP in zf-Dof 5.6 (G120_9287) affected photosynthesis by modulating the expression of a sub-regulatory network of eight other TFs, which in turn regulate 55 photosynthesis-related genes. Furthermore, epistasis analysis identified a large interacting network representing 732 SNP-SNP pairs, of which 354 were photosynthesis gene-TF pairs, emphasizing the important roles of TFs in affecting photosynthesis-related traits. We combined eQTL and epistasis analysis and found 32 TFs harboring eQTLs being epistatic to their targets (identified by eQTL analysis), of which 15 TFs were also associated with photosynthesis traits. We therefore constructed a schematic model of TFs involved in regulating the photosynthetic light reaction pathway. Taken together, our results provide insight into the genetic regulation of photosynthesis, and may drive progress in the marker-assisted selection of desirable P. tomentosa genotypes with more efficient photosynthesis.

[1]  Association , 1886, American Journal of Sociology.

[2]  C. Waddington.  Canalization of Development and the Inheritance of Acquired Characters , 1942, Nature.

[3]  C. Waddington,et al.  The strategy of the genes , 1957 .

[4]  G. A. Watterson.  On the number of segregating sites in genetical models without recombination. , 1975, Theoretical population biology.

[5]  M. Nei.  Molecular Evolutionary Genetics , 1987 .

[6]  D. Arnon.  The discovery of ferredoxin: the photosynthetic path. , 1988, Trends in biochemical sciences.

[7]  F. Tajima.  Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. , 1989, Genetics.

[8]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[9]  Cai-guo Xu,et al.  Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[10]  D. Levin,et al.  Genetic and phenotypic correlations in plants: a botanical test of Cheverud's conjecture , 1998, Heredity.

[11]  Henning Stahlberg,et al.  Structural biology: Proton-powered turbine of a plant motor , 2000, Nature.

[12]  P. Donnelly,et al.  Inference of population structure using multilocus genotype data. , 2000, Genetics.

[13]  O. Hardy,et al.  spagedi: a versatile computer program to analyse spatial genetic structure at the individual or population levels , 2002 .

[14]  Robert Eugene Blankenship.  Molecular mechanisms of photosynthesis , 2002 .

[15]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[16]  Matthew E. Hudson,et al.  Identification of Promoter Motifs Involved in the Network of Phytochrome A-Regulated Gene Expression by Combined Analysis of Genomic Sequence and Microarray Data1[w] , 2003, Plant Physiology.

[17]  J. Allen.  Cyclic, pseudocyclic and noncyclic photophosphorylation: new links in the chain. , 2003, Trends in plant science.

[18]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[19]  S. Yanagisawa,et al.  Metabolic engineering with Dof1 transcription factor in plants: Improved nitrogen assimilation and growth under low-nitrogen conditions. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[20]  W. G. Hill,et al.  Linkage disequilibrium in finite populations , 1968, Theoretical and Applied Genetics.

[21]  Xing Wang Deng,et al.  Conservation and Divergence of Light-Regulated Genome Expression Patterns during Seedling Development in Rice and Arabidopsis[W] , 2005, The Plant Cell Online.

[22]  Daniel Dvorkin,et al.  Detection of SNP epistasis effects of quantitative traits using an extended Kempthorne model. , 2006, Physiological genomics.

[23]  Higher order structure contributes to specific differences in redox potential and electron transfer efficiency of root and leaf ferredoxins. , 2006, Biochemistry.

[24]  J. Cairney,et al.  A simple and efficient method for isolating RNA from pine trees , 1993, Plant Molecular Biology Reporter.

[25]  Edward S. Buckler,et al.  TASSEL: software for association mapping of complex traits in diverse samples , 2007, Bioinform..

[26]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[27]  H. Maherali,et al.  Leaf hydraulic conductivity and photosynthesis are genetically correlated in an annual grass. , 2008, The New phytologist.

[28]  Li Ma,et al.  Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies , 2008, BMC Bioinformatics.

[29]  Jonathan Flint,et al.  Genetic architecture of quantitative traits in mice, flies, and humans. , 2009, Genome research.

[30]  G. Xue,et al.  Members of the Dof transcription factor family in Triticum aestivum are associated with light-mediated gene regulation , 2009, Functional & Integrative Genomics.

[31]  Siu-Ming Yiu,et al.  SOAP2: an improved ultrafast tool for short read alignment , 2009, Bioinform..

[32]  A. Munro,et al.  FdC1, a Novel Ferredoxin Protein Capable of Alternative Electron Partitioning, Increases in Conditions of Acceptor Limitation at Photosystem I* , 2010, The Journal of Biological Chemistry.

[33]  Q. Du,et al.  The actin multigene family in Populus: organization, expression and phylogenetic analysis , 2010, Molecular Genetics and Genomics.

[34]  Xin-Guang Zhu,et al.  Improving photosynthetic efficiency for greater yield. , 2010, Annual review of plant biology.

[35]  D. Kramer,et al.  Regulation of cyclic electron flow in C₃ plants: differential effects of limiting photosynthesis at ribulose-1,5-bisphosphate carboxylase/oxygenase and glyceraldehyde-3-phosphate dehydrogenase. , 2010, Plant, cell & environment.

[36]  C. Miyake.  Alternative electron flows (water-water cycle and cyclic electron flow around PSI) in photosynthesis: molecular mechanisms and physiological functions. , 2010, Plant & cell physiology.

[37]  G. Xue,et al.  TaNF-YB3 is involved in the regulation of photosynthesis genes in Triticum aestivum , 2011, Functional & Integrative Genomics.

[38]  Sujith Puthiyaveetil,et al.  A structural phylogenetic map for chloroplast photosynthesis. , 2011, Trends in plant science.

[39]  Gonçalo R. Abecasis,et al.  The variant call format and VCFtools , 2011, Bioinform..

[40]  D. Neale,et al.  Forest tree genomics: growing resources and applications , 2011, Nature Reviews Genetics.

[41]  T. Shah,et al.  Comparative LD mapping using single SNPs and haplotypes identifies QTL for plant height and biomass as secondary traits of drought tolerance in maize , 2011, Molecular Breeding.

[42]  P. Rigault,et al.  Association Genetics of Wood Physical Traits in the Conifer White Spruce and Relationships With Gene Expression , 2011, Genetics.

[43]  M. Hajirezaei,et al.  Expression of the Minor Isoform Pea Ferredoxin in Tobacco Alters Photosynthetic Electron Partitioning and Enhances Cyclic Electron Flow1[W] , 2012, Plant Physiology.

[44]  R. Gibbs,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:Epistasis dominates the genetic architecture of Drosophila quantitative traits , 2012 .

[45]  Q. Du,et al.  Genetic diversity and population structure of Chinese White poplar (Populus tomentosa) revealed by SSR markers. , 2012, The Journal of heredity.

[46]  Gary D Bader,et al.  A travel guide to Cytoscape plugins , 2012, Nature Methods.

[47]  D. Leister,et al.  PGRL1 is the elusive ferredoxin-plastoquinone reductase in photosynthetic cyclic electron flow. , 2013, Molecular cell.

[48]  G. Tuskan,et al.  Genome-wide association mapping for wood characteristics in Populus identifies an array of candidate single nucleotide polymorphisms. , 2013, The New phytologist.

[49]  Hui Zhang,et al.  Epistatic Effects on Abdominal Fat Content in Chickens: Results from a Genome-Wide SNP-SNP Interaction Analysis , 2013, PloS one.

[50]  Xiaohong Yang,et al.  Genome-wide association study dissects the genetic architecture of oil biosynthesis in maize kernels , 2012, Nature Genetics.

[51]  Q. Du,et al.  Allelic Variation in a Cellulose Synthase Gene (PtoCesA4) Associated with Growth and Wood Properties in Populus tomentosa , 2013, G3: Genes, Genomes, Genetics.

[52]  G. Tuskan,et al.  Populus trichocarpa cell wall chemistry and ultrastructure trait variation, genetic control and genetic correlations. , 2013, The New phytologist.

[53]  Lude Franke,et al.  From genome to function by studying eQTLs. , 2014, Biochimica et biophysica acta.

[54]  L. Rahman,et al.  Coordinated regulation of photosynthesis in rice increases yield and tolerance to environmental stress , 2014, Nature Communications.

[55]  M. Margis-Pinheiro,et al.  Possible roles of basic helix-loop-helix transcription factors in adaptation to drought. , 2014, Plant science : an international journal of experimental plant biology.

[56]  YANGXiao-hui,et al.  Variation in growth, leaf, and wood property traits of Chinese white poplar (Populus tomentosa), a major industrial tree species in Northern China , 2014 .

[57]  P. Visscher,et al.  Advantages and pitfalls in the application of mixed-model association methods , 2014, Nature Genetics.

[58]  Asha A. Nair,et al.  Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set , 2015, Nature Communications.

[59]  Q. Du,et al.  Identification of additive, dominant, and epistatic variation conferred by key genes in cellulose biosynthesis pathway in Populus tomentosa , 2014, DNA research : an international journal for rapid publication of reports on genes and genomes.

[60]  Transcript abundance patterns of PopulusC-repeat binding factor2 orthologs and genetic association of PsCBF2 allelic variation with physiological and biochemical traits in response to abiotic stress , 2015, Planta.

[61]  Hsien-Da Huang,et al.  PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants , 2015, Nucleic Acids Res..

[62]  David J. Arenillas,et al.  JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles , 2015, Nucleic Acids Res..

[63]  Q. Du,et al.  Association genetics and transcriptome analysis reveal a gibberellin-responsive pathway involved in regulating photosynthesis. , 2016, Journal of experimental botany.

[64]  Shizhong Xu,et al.  Genome-wide dissection of the maize ear genetic architecture using multiple populations. , 2016, The New phytologist.

[65]  Jianbing Yan,et al.  Distant eQTLs and Non-coding Sequences Play Critical Roles in Regulating Gene Expression and Quantitative Trait Variation in Maize. , 2017, Molecular plant.

[66]  M. MUHAGHEGH-DOLATABADY,et al.  Sequence Characterization in 3′-Flanking Region of Bovine TNF-α: Association with Milk Production Traits and Somatic Cell Score in Holstein Cattle of Iran , 2018 .