Transcription factors (TFs) play crucial roles in the regulation of photosynthesis; elucidating these roles will facilitate our understanding of photosynthesis and thus accelerate its improvement for enhancing crop yield. Promoter analysis of 52 nuclear-encoded Populus tomentosa Carr. genes involved in the Calvin-Benson-Bassham (CBB) cycle revealed 706 motifs and 326 potentially interacting TFs. A backward elimination random forest (BWERF) algorithm reduced the number of TFs to 40, involved in a three-layer gene regulatory network (GRN) including 46 photosynthesis genes (bottom layer), 25 TFs (second layer) and 15 TFs (top layer). Phenotype-genotype association identified 248 single-nucleotide polymorphisms (SNPs) within 72 genes associated with 11 photosynthesis traits. Of the regulatory pairs identified by the BWERF (202 pairs), 77 TF-target combinations harbored SNPs associated with the same trait, supporting similar mechanisms of phenotype modulation. We used expression quantitative trait nucleotide (eQTN) analysis to identify causal SNPs affecting gene expression, identifying 1851 eQTN signals for 50 eGenes (genes whose expressions are regulated by eQTNs). Distribution patterns identified 14 eQTNs from seven TFs associated with eight expression levels of their downstream targets (defined in the GRN), whereas seven TF-target pairs were also identified by phenotype-genotype associations. To further validate the roles of TFs at the metabolic level, we selected 6764 SNPs from 55 genes (identified by GRN-association or GRN-eQTN pairs or both) for metabolic association, identifying variants within 10 TFs affecting metabolic processes underlying the CBB cycle. Our study provides new insights into the photosynthesis pathway in poplar and may facilitate understanding of processes underlying photosynthesis improvement.
It is speculated that the changes in seawater temperature may cause population migration of the North Sea Mackerel and Herring fisheries. To assess the situation and propose some remedies which can help improving the economy, the paper establish a series of models. The paper set a revenue-cost model to figure out the maximum sailing distance and area by willingness of fishermen to define how migration of mackerel and herring influence the net profit of companies. The longer distance brings the larger total cost, the smaller total revenue, and the smaller net profit. The paper establish the total cost-time model which divide to fixed assets, wage, and fuel fare and the total revenue-time model which is influenced by freshness, to define the maximum sailing distance. Combining with the prediction of fisheries, it is clearly that fisheries will migrate out of the willingness area completely 78 years later. To avoid the awful condition of fishing, suggest fishermen take some strategies to reduce the loss of fish migration. According to the Barycenter method, consider Anstruther, Eyemouth and Buckie as the best three city for fisheries by using the administrative division of Scotland and the prediction of fisheries. Or fishermen can buy a certain percent advanced equipment according to the maximum net profit model.
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.
MicroRNAs (miRNAs) function as key regulators of complex traits, but how genetic alterations in miRNA biogenesis genes (miRBGs) affect quantitative variation has not been elucidated. We conducted transcript analyses and association genetics to investigate how miRBGs, miRNA genes (MIRNAs) and their respective targets contribute to secondary growth in a natural population of 435 Populus tomentosa individuals. This analysis identified 29 843 common single-nucleotide polymorphisms (SNPs; frequency > 0.10) within 682 genes (80 miRBGs, 152 MIRNAs, and 457 miRNA targets). Single-SNP association analysis found SNPs in 234 candidate genes exhibited significant additive/dominant effects on phenotypes. Among these, specific candidates that associated with the same traits produced 791 miRBG-MIRNA-target combinations, suggesting possible genetic miRBG-MIRNA and MIRNA-target interactions, providing an important clue for the regulatory mechanisms of miRBGs. Multi-SNP association found 4672 epistatic pairs involving 578 genes that showed significant associations with traits and identified 106 miRBG-MIRNA-target combinations. Two multi-hierarchical networks were constructed based on correlations of miRBG-miRNA and miRNA-target expression to further probe the mechanisms of trait diversity underlying changes in miRBGs. Our study opens avenues for the investigation of miRNA function in perennial plants and underscored miRBGs as potentially modulating quantitative variation in traits.
Wood formation is an excellent model system for quantitative trait analysis due to the strong associations between the transcriptional and metabolic traits that contribute to this complex process. Investigating the genetic architecture and regulatory mechanisms underlying wood formation will enhance our understanding of the quantitative genetics and genomics of complex phenotypic variation. Genome-wide association studies (GWAS) represent an ideal statistical strategy for dissecting the genetic basis of complex quantitative traits. However, elucidating the molecular mechanisms underlying many favorable loci that contribute to wood formation and optimizing GWAS design remain challenging in this omics era. In this review, we summarize the recent progress in GWAS-based functional genomics of wood property traits in major timber species such as Eucalyptus, Populus, and various coniferous species. We discusses several appropriate statistical methods and experimental designs for extensive GWAS in a given undomesticated tree population, such as omics-wide association study (OWAS) and high-throughput phenotyping technologies. We also explain why more attention should be paid to rare allelic variations and major structural variations. Finally, we explore the potential use of GWAS for the molecular breeding of trees. Such studies will help provide an integrated understanding of complex quantitative traits and should enable the molecular design of new cultivars.
Summary Lignin provides structural support in perennial woody plants and is a complex phenolic polymer derived from phenylpropanoid pathway. Lignin biosynthesis is regulated by coordinated networks involving transcription factors ( TF s), micro RNA s (mi RNA s) and long noncoding RNA s (lnc RNA s). However, the genetic networks underlying the lignin biosynthesis pathway for tree growth and wood properties remain unknown. Here, we used association genetics (additive, dominant and epistasis) and expression quantitative trait nucleotide ( eQTN ) mapping to decipher the genetic networks for tree growth and wood properties in 435 unrelated individuals of Populus tomentosa . We detected 124 significant associations ( P ≤ 6.89E‐05) for 10 growth and wood property traits using 30 265 single nucleotide polymorphisms from 203 lignin biosynthetic genes, 81 TF genes, 36 mi RNA genes and 71 lnc RNA loci, implying their common roles in wood formation. Epistasis analysis uncovered 745 significant pairwise interactions, which helped to construct proposed genetic networks of lignin biosynthesis pathway and found that these regulators might affect phenotypes by linking two lignin biosynthetic genes. eQTN s were used to interpret how causal genes contributed to phenotypes. Lastly, we investigated the possible functions of the genes encoding 4‐coumarate: CoA ligase and cinnamate‐4‐hydroxylase in wood traits using epistasis, eQTN mapping and enzymatic activity assays. Our study provides new insights into the lignin biosynthesis pathway in poplar and enables the novel genetic factors as biomarkers for facilitating genetic improvement of trees.
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