[1]
|
Pan Y, Birdsey RA, Phillips OL, Jackson RB. 2013. The structure, distribution, and biomass of the World's forests. Anual Review of Ecology, Evolution, and Systematics 44:593−622 doi: 10.1146/annurev-ecolsys-110512-135914
CrossRef Google Scholar
|
[2]
|
Wei H. 2021. Inaugural Editorial. Forestry Research 1:1 doi: 10.48130/FR-2021-0001
CrossRef Google Scholar
|
[3]
|
Plomion C, Bastien C, Bogeat-Triboulot MB, Bouffier L, Déjardin A, et al. 2016. Forest tree genomics: 10 achievements from the past 10 years and future prospects. Annals of Forest Science 73:77−103 doi: 10.1007/s13595-015-0488-3
CrossRef Google Scholar
|
[4]
|
Allona I, Kirst M, Boerjan W, Strauss S, Sederoff R. 2019. Editorial: Forest Genomics and Biotechnology. Frontiers in Plant Science 10:1187 doi: 10.3389/fpls.2019.01187
CrossRef Google Scholar
|
[5]
|
Schultz JA, Coleman HD. 2021. Pectin and xylan biosynthesis in poplar: Implications and opportunities for biofuels production. Frontiers in Plant Science 12:712083 doi: 10.3389/fpls.2021.712083
CrossRef Google Scholar
|
[6]
|
Cairns MA, Brown S, Helmer EH, Baumgardner GA. 1997. Root biomass allocation in the world's upland forests. Oecologia 111:1−11 doi: 10.1007/s004420050201
CrossRef Google Scholar
|
[7]
|
Houghton RA, Hall F, Goetz SJ. 2009. Importance of biomass in the global carbon cycle. Biogeosciences 114:G00E03
Google Scholar
|
[8]
|
de Vries L, Guevara-Rozo S, Cho M, Liu LY, Renneckar S, et al. 2021. Tailoring renewable materials via plant biotechnology. Biotechnology For Biofuels 14:167 doi: 10.1186/s13068-021-02010-z
CrossRef Google Scholar
|
[9]
|
Fukuda H, Komamine A. 1980. Establishment of an experimental system for the study of tracheary element differentiation from single cells isolated from the mesophyll of Zinnia elegans. Plant Physiology 65:57−60 doi: 10.1104/pp.65.1.57
CrossRef Google Scholar
|
[10]
|
Kubo M, Udagawa M, Nishikubo N, Horiguchi G, Yamaguchi M, et al. 2005. Transcription switches for protoxylem and metaxylem vessel formation. Genes & Development 19:1855−60 doi: 10.1101/gad.1331305
CrossRef Google Scholar
|
[11]
|
Wang D, Chen Y, Li W, Li Q, Lu M, et al. 2021. Vascular Cambium: The Source of Wood Formation. Frontiers in Plant Science 12:700928 doi: 10.3389/fpls.2021.700928
CrossRef Google Scholar
|
[12]
|
Ko JH, Kim WC, Kim JY, Ahn SJ, Han KH. 2012. MYB46-mediated transcriptional regulation of secondary wall biosynthesis. Molecular Plant 5:961−63 doi: 10.1093/mp/sss076
CrossRef Google Scholar
|
[13]
|
Zhu Y, Li L. 2021. Multi-layered regulation of plant cell wall thickening. Plant and Cell Physiology 62:1867−73 doi: 10.1093/pcp/pcab152
CrossRef Google Scholar
|
[14]
|
Xu C, Shen Y, He F, Fu X, Yu H, et al. 2019. Auxin-mediated Aux/IAA-ARF-HB signaling cascade regulates secondary xylem development in Populus. New Phtologist 222:752−67 doi: 10.1111/nph.15658
CrossRef Google Scholar
|
[15]
|
Shi D, Lebovka I, López-Salmerón V, Sanchez P, Greb T. 2019. Bifacial cambium stem cells generate xylem and phloem during radial plant growth. Development 146:dev171355 doi: 10.1242/dev.171355
CrossRef Google Scholar
|
[16]
|
Smetana O, Mäkilä R, Lyu M, Amiryousefi A, Sanchez Rodriguez F, et al. 2019. High levels of auxin signalling define the stem-cell organizer of the vascular cambium. Nature 565:485−89 doi: 10.1038/s41586-018-0837-0
CrossRef Google Scholar
|
[17]
|
Chiang MH, Greb T. 2019. How to organize bidirectional tissue production. Current Opinion in Plant Biology 51:15−21 doi: 10.1016/j.pbi.2019.03.003
CrossRef Google Scholar
|
[18]
|
Wenzel CL, Schuetz M, Yu Q, Mattsson J. 2007. Dynamics of MONOPTEROS and PIN-FORMED1 expression during leaf vein pattern formation in Arabidopsis thaliana. The Plant Journal 49:387−98 doi: 10.1111/j.1365-313X.2006.02977.x
CrossRef Google Scholar
|
[19]
|
De Rybel B, Adibi M, Breda AS, Wendrich JR, Smit ME, et al. 2014. Plant development. Integration of growth and patterning during vascular tissue formation in Arabidopsis. Science 345:1255215 doi: 10.1126/science.1255215
CrossRef Google Scholar
|
[20]
|
Ohashi-Ito K, Saegusa M, Iwamoto K, Oda Y, Katayama H, et al. 2014. A bHLH complex activates vascular cell division via cytokinin action in root apical meristem. Current Biology 24:2053−58 doi: 10.1016/j.cub.2014.07.050
CrossRef Google Scholar
|
[21]
|
Smet W, Sevilem I, de Luis Balaguer MA, Wybouw B, Mor E, et al. 2019. DOF2.1 controls cytokinin-dependent vascular cell proliferation downstream of TMO5/LHW. Current Biology 29:520−9.e6 doi: 10.1016/j.cub.2018.12.041
CrossRef Google Scholar
|
[22]
|
Hardtke CS, Berleth T. 1998. The Arabidopsis gene MONOPTEROS encodes a transcription factor mediating embryo axis formation and vascular development. The EMBO Journal 17:1405−11 doi: 10.1093/emboj/17.5.1405
CrossRef Google Scholar
|
[23]
|
Chen Y, Tong S, Jiang Y, Ai F, Feng Y, et al. 2021. Transcriptional landscape of highly lignified poplar stems at single-cell resolution. Genome Biology 22:319 doi: 10.1186/s13059-021-02537-2
CrossRef Google Scholar
|
[24]
|
Li H, Dai X, Huang X, Xu M, Wang Q, et al. 2021. Single-cell RNA sequencing reveals a high-resolution cell atlas of xylem in Populus. Journal of Integrative Plant Biology 63:1906−21 doi: 10.1111/jipb.13159
CrossRef Google Scholar
|
[25]
|
Chen A, Liao S, Cheng M, Ma K, Wu L, et al. 2022. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185:1777−92 e21 doi: 10.1016/j.cell.2022.04.003
CrossRef Google Scholar
|
[26]
|
Cao HX, Vu GTH, Gailing O. 2022. From Genome sequencing to CRISPR-based genome editing for climate-resilient forest trees. International Journal of Molecular Sciences 23:966 doi: 10.3390/ijms23020966
CrossRef Google Scholar
|
[27]
|
Pak S, Li C. 2022. Progress and challenges in applying CRISPR/Cas techniques to the genome editing of trees. Forestry Research 2:6 doi: 10.48130/FR-2022-0006
CrossRef Google Scholar
|
[28]
|
Fan D, Liu T, Li C, Jiao B, Li S, et al. 2015. Efficient CRISPR/Cas9-mediated targeted mutagenesis in Populus in the first generation. Scientific Reports 5:12217 doi: 10.1038/srep12217
CrossRef Google Scholar
|
[29]
|
van Zeijl A, Wardhani TAK, Seifi Kalhor M, Rutten L, Bu F, et al. 2018. CRISPR/Cas9-mediated mutagenesis of four putative symbiosis genes of the tropical tree Parasponia andersonii reveals novel phenotypes. Frontiers in Plant Science 9:284 doi: 10.3389/fpls.2018.00284
CrossRef Google Scholar
|
[30]
|
Dai Y, Hu G, Dupas A, Medina L, Blandels N, et al. 2020. Implementing the CRISPR/Cas9 technology in Eucalyptus hairy roots using wood-related genes. International Journal of Molecular Sciences 21:3408 doi: 10.3390/ijms21103408
CrossRef Google Scholar
|
[31]
|
Dai X, Yang X, Wang C, Fan Y, Xin S, et al. 2021. CRISPR/Cas9-mediated genome editing in Hevea brasiliensis. Industrial Crops And Products 164:113418 doi: 10.1016/j.indcrop.2021.113418
CrossRef Google Scholar
|
[32]
|
Fan Y, Xin S, Dai X, Yang X, Huang H, et al. 2020. Efficient genome editing of rubber tree (Hevea brasiliensis) protoplasts using CRISPR/Cas9 ribonucleoproteins. Industrial Crops And Products 146:112146 doi: 10.1016/j.indcrop.2020.112146
CrossRef Google Scholar
|
[33]
|
Poovaiah C, Phillips L, Geddes B, Reeves C, Sorieul M, Thorlby G. 2021. Genome editing with CRISPR/Cas9 in Pinus radiata (D. Don). BMC Plant Biology 21:363 doi: 10.1186/s12870-021-03143-x
CrossRef Google Scholar
|
[34]
|
Pavese V, Moglia A, Corredoira E, Martínez MT, Torello Marinoni D, et al. 2021. First report of CRISPR/Cas9 gene editing in Castanea sativa Mill. Frontiers in Plant Science 12:728516 doi: 10.3389/fpls.2021.728516
CrossRef Google Scholar
|
[35]
|
Pramanik D, Shelake RM, Kim MJ, Kim JY. 2021. CRISPR-mediated engineering across the central dogma in plant biology for basic research and crop improvement. Molecular Plant 14:127−50 doi: 10.1016/j.molp.2020.11.002
CrossRef Google Scholar
|
[36]
|
Hassan MM, Zhang Y, Yuan G, De K, Chen JG, et al. 2021. Construct design for CRISPR/Cas-based genome editing in plants. Trends in Plant Science 26:1133−52 doi: 10.1016/j.tplants.2021.06.015
CrossRef Google Scholar
|
[37]
|
Nidhi S, Anand U, Oleksak P, Tripathi P, Lal JA, et al. 2021. Novel CRISPR–cas systems: An updated review of the current achievements, applications, and future research perspectives. International Journal of Molecular Sciences 22:3327 doi: 10.3390/ijms22073327
CrossRef Google Scholar
|
[38]
|
Lu Y, Tian Y, Shen R, Yao Q, Wang M, et al. 2020. Targeted, efficient sequence insertion and replacement in rice. Nature Biotechnology 38:1402−7 doi: 10.1038/s41587-020-0581-5
CrossRef Google Scholar
|
[39]
|
Li S, Li J, He Y, Xu M, Zhang J, et al. 2019. Precise gene replacement in rice by RNA transcript-templated homologous recombination. Nature Biotechnology 37:445−50 doi: 10.1038/s41587-019-0065-7
CrossRef Google Scholar
|
[40]
|
Nishida K, Arazoe T, Yachie N, Banno S, Kakimoto M, et al. 2016. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science 353:aaf8729 doi: 10.1126/science.aaf8729
CrossRef Google Scholar
|
[41]
|
Anzalone AV, Randolph PB, Davis JR, Sousa AA, Koblan LW, et al. 2019. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature 576:149−57 doi: 10.1038/s41586-019-1711-4
CrossRef Google Scholar
|
[42]
|
Komor AC, Kim YB, Packer MS, Zuris JA, Liu DR. 2016. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533:420−24 doi: 10.1038/nature17946
CrossRef Google Scholar
|
[43]
|
Chanoca A, de Vries L, Boerjan W. 2019. Lignin engineering in forest trees. Frontiers in Plant Science 10:912 doi: 10.3389/fpls.2019.00912
CrossRef Google Scholar
|
[44]
|
Dort EN, Tanguay P, Hamelin RC. 2020. CRISPR/Cas9 gene editing: An unexplored frontier for forest pathology. Frontiers in Plant Science 11:1126 doi: 10.3389/fpls.2020.01126
CrossRef Google Scholar
|
[45]
|
Fang Q, Wang X, Wang H, Tang X, Liu C, et al. 2020. The poplar R2R3 MYB transcription factor PtrMYB94 coordinates with abscisic acid signaling to improve drought tolerance in plants. Tree Physiology 40:46−59 doi: 10.1093/treephys/tpz113
CrossRef Google Scholar
|
[46]
|
Su Y, Guo A, Huang Y, Wang Y, Hua J. 2020. GhCIPK6a increases salt tolerance in transgenic upland cotton by involving in ROS scavenging and MAPK signaling pathways. BMC Plant Biology 20:421 doi: 10.1186/s12870-020-02548-4
CrossRef Google Scholar
|
[47]
|
Xiu Y, Iqbal A, Zhu C, Wu G, Chang Y, et al. 2016. Improvement and transcriptome analysis of root architecture by overexpression of Fraxinus pennsylvanica DREB2A transcription factor in Robinia pseudoacacia L. 'Idaho'. Plant Biotechnology Journal 14:1456−69 doi: 10.1111/pbi.12509
CrossRef Google Scholar
|
[48]
|
Li R, Liu L, Dominic K, Wang T, Fan T, et al. 2018. Mulberry (Morus alba) MmSK gene enhances tolerance to drought stress in transgenic mulberry. Plant Physiology and Biochemistry 132:603−11 doi: 10.1016/j.plaphy.2018.10.007
CrossRef Google Scholar
|
[49]
|
Bewg WP, Ci D, Tsai CJ. 2018. Genome editing in trees: from multiple repair pathways to long-term stability. Frontiers in Plant Science 9:1732 doi: 10.3389/fpls.2018.01732
CrossRef Google Scholar
|
[50]
|
Polle A, Chen SL, Eckert C, Harfouche A. 2019. Engineering Drought Resistance in Forest Trees. Frontiers in Plant Science 9:1875 doi: 10.3389/fpls.2018.01875
CrossRef Google Scholar
|
[51]
|
Molla KA, Yang Y. 2019. CRISPR/Cas-mediated base editing: technical considerations and practical applications. Trends in Biotechnology 37:1121−42 doi: 10.1016/j.tibtech.2019.03.008
CrossRef Google Scholar
|
[52]
|
Gaudelli NM, Komor AC, Rees HA, Packer MS, Badran AH, et al. 2017. Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Nature 551:464−71 doi: 10.1038/nature24644
CrossRef Google Scholar
|
[53]
|
Zhao D, Li J, Li S, Xin X, Hu M, et al. 2021. Glycosylase base editors enable C-to-A and C-to-G base changes. Nature Biotechnology 39:35−40 doi: 10.1038/s41587-020-0592-2
CrossRef Google Scholar
|
[54]
|
Kurt IC, Zhou R, Iyer S, Garcia SP, Miller BR, et al. 2021. CRISPR C-to-G base editors for inducing targeted DNA transversions in human cells. Nature Biotechnology 39:41−6 doi: 10.1038/s41587-020-0609-x
CrossRef Google Scholar
|
[55]
|
Chen L, Park JE, Paa P, Rajakumar PD, Prekop HT, et al. 2021. Programmable C:G to G:C genome editing with CRISPR-Cas9-directed base excision repair proteins. Nature Communication 12:1348 doi: 10.1038/s41467-021-21559-9
CrossRef Google Scholar
|
[56]
|
Choi M, Yun JY, Kim JH, Kim JS, Kim ST. 2021. The efficacy of CRISPR-mediated cytosine base editing with the RPS5a promoter in Arabidopsis thaliana. Scientific Reports 11:8087 doi: 10.1038/s41598-021-87669-y
CrossRef Google Scholar
|
[57]
|
Molla KA, Sretenovic S, Bansal KC, Qi Y. 2021. Precise plant genome editing using base editors and prime editors. Nature Plants 7:1166−87 doi: 10.1038/s41477-021-00991-1
CrossRef Google Scholar
|
[58]
|
Gross A, Schoendube J, Zimmermann S, Steeb M, Zengerle R, et al. 2015. Technologies for single-cell isolation. International Journal of Molecular Sciences 16:16897−919 doi: 10.3390/ijms160816897
CrossRef Google Scholar
|
[59]
|
Zilionis R, Nainys J, Veres A, Savova V, Zemmour D, et al. 2017. Single-cell barcoding and sequencing using droplet microfluidics. Nature Protocols 12:44−73 doi: 10.1038/nprot.2016.154
CrossRef Google Scholar
|
[60]
|
Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, et al. 2015. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161:1187−201 doi: 10.1016/j.cell.2015.04.044
CrossRef Google Scholar
|
[61]
|
Zheng GXY, Terry JM, Belgrader P, Ryvkin P, Bent ZW, et al. 2017. Massively parallel digital transcriptional profiling of single cells. Nature Communications 8:14049 doi: 10.1038/ncomms14049
CrossRef Google Scholar
|
[62]
|
Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K, et al. 2015. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202−14 doi: 10.1016/j.cell.2015.05.002
CrossRef Google Scholar
|
[63]
|
Ryu KH, Huang L, Kang HM, Schiefelbein J. 2019. Single-cell RNA sequencing resolves molecular relationships among individual plant cells. Plant Physiology 179:1444−56 doi: 10.1104/pp.18.01482
CrossRef Google Scholar
|
[64]
|
Zhang T, Xu Z, Shang G, Wang J. 2019. A single-cell RNA sequencing profiles the developmental landscape of Arabidopsis root. Molecular Plant 12:648−60 doi: 10.1016/j.molp.2019.04.004
CrossRef Google Scholar
|
[65]
|
Shulse CN, Cole BJ, Ciobanu D, Lin J, Yoshinaga Y, et al. 2019. High-throughput single-cell transcriptome profiling of plant cell types. Cell Reports 27:2241−2247.E4 doi: 10.1016/j.celrep.2019.04.054
CrossRef Google Scholar
|
[66]
|
Denyer T, Ma X, Klesen S, Scacchi E, Nieselt K, et al. 2019. Spatiotemporal developmental trajectories in the Arabidopsis root revealed using high-throughput single-cell RNA sequencing. Developmental Cell 48:840−852.E5 doi: 10.1016/j.devcel.2019.02.022
CrossRef Google Scholar
|
[67]
|
Jean-Baptiste K, McFaline-Figueroa JL, Alexandre CM, Dorrity MW, Saunders L, et al. 2019. Dynamics of gene expression in single root cells of Arabidopsis thaliana. The Plant Cell 31:993−1011 doi: 10.1105/tpc.18.00785
CrossRef Google Scholar
|
[68]
|
Shahan R, Hsu CW, Nolan TM, Cole BJ, Taylor IW, et al. 2022. A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants. Developmental Cell 57:543−560.e9 doi: 10.1016/j.devcel.2022.01.008
CrossRef Google Scholar
|
[69]
|
Zhang T, Chen Y, Liu Y, Lin W, Wang J. 2021. Single-cell transcriptome atlas and chromatin accessibility landscape reveal differentiation trajectories in the rice root. Nature Communications 12:2053 doi: 10.1038/s41467-021-22352-4
CrossRef Google Scholar
|
[70]
|
Liu Q, Liang Z, Feng D, Jiang S, Wang Y, et al. 2021. Transcriptional landscape of rice roots at the single-cell resolution. Molecular Plant 14:384−94 doi: 10.1016/j.molp.2020.12.014
CrossRef Google Scholar
|
[71]
|
Zhang T, Chen Y, Wang J. 2021. A single-cell analysis of the Arabidopsis vegetative shoot apex. Developmental Cell 56:1056−74 doi: 10.1016/j.devcel.2021.02.021
CrossRef Google Scholar
|
[72]
|
Song Q, Ando A, Jiang N, Ikeda Y, Chen ZJ. 2020. Single-cell RNA-seq analysis reveals ploidy-dependent and cell-specific transcriptome changes in Arabidopsis female gametophytes. Genome Biology 21:178 doi: 10.1186/s13059-020-02094-0
CrossRef Google Scholar
|
[73]
|
Nelms B, Walbot V. 2019. Defining the developmental program leading to meiosis in maize. Science 364:52−56 doi: 10.1126/science.aav6428
CrossRef Google Scholar
|
[74]
|
Satterlee JW, Strable J, Scanlon MJ. 2020. Plant stem-cell organization and differentiation at single-cell resolution. PNAS 117:33689−99 doi: 10.1073/pnas.2018788117
CrossRef Google Scholar
|
[75]
|
Xu X, Crow M, Rice BR, Li F, Harris B, et al. 2021. Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery. Developmental Cell 56:557−568.E6 doi: 10.1016/j.devcel.2020.12.015
CrossRef Google Scholar
|
[76]
|
Kim JY, Symeonidi E, Pang TY, Denyer T, Weidauer D, et al. 2021. Distinct identities of leaf phloem cells revealed by single cell transcriptomics. The Plant Cell 33:511−30 doi: 10.1093/plcell/koaa060
CrossRef Google Scholar
|
[77]
|
Serrano-Ron L, Perez-Garcia P, Sanchez-Corrionero A, Gude I, Cabrera J, et al. 2021. Reconstruction of lateral root formation through single-cell RNA sequencing reveals order of tissue initiation. Molecular Plant 14:1362−78 doi: 10.1016/j.molp.2021.05.028
CrossRef Google Scholar
|
[78]
|
Liu Z, Zhou Y, Guo J, Li J, Tian Z, et al. 2020. Global dynamic molecular profiling of stomatal lineage cell development by single-cell RNA sequencing. Molecular Plant 13:1178−93 doi: 10.1016/j.molp.2020.06.010
CrossRef Google Scholar
|
[79]
|
Liu H, Hu D, Du P, Wang L, Liang X, et al. 2021. Single-cell RNA-seq describes the transcriptome landscape and identifies critical transcription factors in the leaf blade of the allotetraploid peanut (Arachis hypogaea L.). Plant Biotechnology Journal 19:2261−76 doi: 10.1111/pbi.13656
CrossRef Google Scholar
|
[80]
|
Gala HP, Lanctot A, Jean-Baptiste K, Guiziou S, Chu JC, et al. 2021. A single-cell view of the transcriptome during lateral root initiation in Arabidopsis thaliana. The Plant Cell 33:2197−220 doi: 10.1093/plcell/koab101
CrossRef Google Scholar
|
[81]
|
Lopez-Anido CB, Vatén A, Smoot NK, Sharma N, Guo V, et al. 2021. Single-cell resolution of lineage trajectories in the Arabidopsis stomatal lineage and developing leaf. Developmental Cell 56:1043−1055.E4 doi: 10.1016/j.devcel.2021.03.014
CrossRef Google Scholar
|
[82]
|
Birnbaum K, Shasha DE, Wang JY, Jung JW, Lambert GM, et al. 2003. A gene expression map of the Arabidopsis root. Science 302:1956−60 doi: 10.1126/science.1090022
CrossRef Google Scholar
|
[83]
|
Farmer A, Thibivilliers S, Ryu KH, Schiefelbein J, Libault M. 2021. Single-nucleus RNA and ATAC sequencing reveals the impact of chromatin accessibility on gene expression in Arabidopsis roots at the single-cell level. Molecular Plant 14:372−83 doi: 10.1016/j.molp.2021.01.001
CrossRef Google Scholar
|
[84]
|
Deal RB, Henikoff S. 2010. A simple method for gene expression and chromatin profiling of individual cell types within a tissue. Developmental Cell 18:1030−40 doi: 10.1016/j.devcel.2010.05.013
CrossRef Google Scholar
|
[85]
|
Reynoso MA, Pauluzzi GC, Kajala K, Cabanlit S, Velasco J, et al. 2018. Nuclear transcriptomes at high resolution using retooled INTACT. Plant Physiology 176:270−81 doi: 10.1104/pp.17.00688
CrossRef Google Scholar
|
[86]
|
Palovaara J, Weijers D. 2019. Adapting INTACT to analyse cell-type-specific transcriptomes and nucleocytoplasmic mRNA dynamics in the Arabidopsis embryo. Plant Reproduction 32:113−21 doi: 10.1007/s00497-018-0347-0
CrossRef Google Scholar
|
[87]
|
Del Toro-De León G, Köhler C. 2019. Endosperm-specific transcriptome analysis by applying the INTACT system. Plant Reproduction 32:55−61 doi: 10.1007/s00497-018-00356-3
CrossRef Google Scholar
|
[88]
|
Pirrello J, Deluche C, Frangne N, Gévaudant F, Maza E, et al. 2018. Transcriptome profiling of sorted endoreduplicated nuclei from tomato fruits: how the global shift in expression ascribed to DNA ploidy influences RNA-Seq data normalization and interpretation. The Plant Journal 93:387−98 doi: 10.1111/tpj.13783
CrossRef Google Scholar
|
[89]
|
Conde D, Triozzi PM, Balmant KM, Doty AL, Miranda M, et al. 2021. A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus Populus. PLoS One 16:e0251149 doi: 10.1371/journal.pone.0251149
CrossRef Google Scholar
|
[90]
|
Turco GM, Rodriguez-Medina J, Siebert S, Han D, Valderrama-Gómez MÁ, et al. 2019. Molecular mechanisms driving switch behavior in xylem cell differentiation. Cell Reports 28:342−351.E4 doi: 10.1016/j.celrep.2019.06.041
CrossRef Google Scholar
|
[91]
|
Giacomello S, Salmén F, Terebieniec BK, Vickovic S, Navarro JF, et al. 2017. Spatially resolved transcriptome profiling in model plant species. Nature Plants 3:17061 doi: 10.1038/nplants.2017.61
CrossRef Google Scholar
|
[92]
|
Giacomello S, Lundeberg J. 2018. Preparation of plant tissue to enable Spatial Transcriptomics profiling using barcoded microarrays. Nature Protocols 13:2425−46 doi: 10.1038/s41596-018-0046-1
CrossRef Google Scholar
|
[93]
|
Dunwell JM. 2010. Haploids in flowering plants: origins and exploitation. Plant Biotechnology Journal 8:377−424 doi: 10.1111/j.1467-7652.2009.00498.x
CrossRef Google Scholar
|
[94]
|
Coe EH Jr . 1959. A line of maize with high haploid frequency. The American Naturalist 93:381−2 doi: 10.1086/282098
CrossRef Google Scholar
|
[95]
|
Jain SM, Sopory SK, Veilleux R. 1996. In Vitro Haploid Production in Higher Plants: Volume 2: Applications. Springer Science & Business Media
|
[96]
|
Maluszynski M, Kasha K, Forster B, Szarejko I (eds.). 2003. Doubled haploid production in crop plants: anual. New York: Springer Science & Business Media
|
[97]
|
Xu L, Najeeb U, Tang G, Gu H, Zhang G, et al. 2007. Haploid and doubled haploid technology. Advances in Botanical Research 45:181−216 doi: 10.1016/S0065-2296(07)45007-8
CrossRef Google Scholar
|
[98]
|
Piosik Ł, Zenkteler E, Zenkteler M. 2016. Development of haploid embryos and plants of Lactuca sativa induced by distant pollination with Helianthus annuus and H. tuberosus. Euphytica 208:439−51 doi: 10.1007/s10681-015-1578-x
CrossRef Google Scholar
|
[99]
|
Godbole M, Murthy HN. 2012. In vitro production of haploids via parthenogenesis in culinary melon (Cucumis melo var. acidulus). Indian Journal of Biotechnology 11:495−97
Google Scholar
|
[100]
|
Soleimani A. 2012. Production of haploid lines from parthenogenetic Iranian melon plants obtained of irradiated pollen (Cucumis melo L.). International Research Journal of Applied and Basic Sciences 3:1585−89
Google Scholar
|
[101]
|
Deng Y, Tang B, Zhou X, Fu W, Tao L, et al. 2020. Direct regeneration of haploid or doubled haploid plantlets in cucumber (Cucumis sativus L.) through ovary culture. Plant Cell, Tissue and Organ Culture (PCTOC) 142:253−68 doi: 10.1007/s11240-020-01839-w
CrossRef Google Scholar
|
[102]
|
Zayachkovskaya T, Domblides E, Zayachkovsky V, Kan L, Domblides A, et al. 2021. Production of Gynogenic Plants of Red Beet (Beta vulgaris L.) in Unpollinated Ovule Culture In Vitro. Plants 10:2703 doi: 10.3390/plants10122703
CrossRef Google Scholar
|
[103]
|
Castillo AM, Valero-Rubira I, Allué S, Costar MA, Vallés MP. 2021. Bread Wheat Doubled Haploid Production by Anther Culture. Methods in Molecular Biology 2287:227−44 doi: 10.1007/978-1-0716-1315-3_11
CrossRef Google Scholar
|
[104]
|
Kurtar ES, Seymen M. 2021. Gynogenesis in Cucurbita Species. Methods in Molecular Biology 2289:123−33 doi: 10.1007/978-1-0716-1331-3_8
CrossRef Google Scholar
|
[105]
|
Galán-Ávila A, García-Fortea E, Prohens J, Herraiz FJ. 2021. Microgametophyte Development in Cannabis sativa L. and First Androgenesis Induction Through Microspore Embryogenesis. Frontiers in Plant Science 12:669424 doi: 10.3389/fpls.2021.669424
CrossRef Google Scholar
|
[106]
|
Kang X, Wei H. 2022. Breeding polyploid Populus: progress and perspective. Forestry Research 2:4 doi: 10.48130/FR-2022-0004
CrossRef Google Scholar
|
[107]
|
Winton LL, Einspahr DW. 1968. The use of heat-treated pollen for aspen haploid production. Forest Science406−7
Google Scholar
|
[108]
|
Stettler R, Bawa K. 1971. Experimental induction of haploid parthenogenesis in black cottonwood (Populus trichocarpa T. & G. ex Hook.). Silvae Genetica 20:15−25
Google Scholar
|
[109]
|
Illies Z. 1974. Induction of haploid parthenogenesis in aspen by postpollination treatment with Toluidine-blue. Silvae Genetica 23:221−26
Google Scholar
|
[110]
|
Wu K, Xu M. 1984. Induction of matrilinear haploid plants from unpollinated ovaries of poplar invitro. Kexue Tongbao 29:141−42
Google Scholar
|
[111]
|
Li Y, Huang S, Zhang J, Bu F, Lin T, et al. 2016. A protocol of homozygous haploid callus induction from endosperm of Taxus chinensis Rehd. var. mairei. SpringerPlus 5:1−9 doi: 10.1186/s40064-016-2320-4
CrossRef Google Scholar
|
[112]
|
Li Y, Wei H, Yang J, Du K, Li J, et al. 2020. High-quality de novo assembly of the Eucommia ulmoides haploid genome provides new insights into evolution and rubber biosynthesis. Horticulture Research 7:183 doi: 10.1038/s41438-020-00406-w
CrossRef Google Scholar
|
[113]
|
Wang C, Chu Z, Sun C. 1975. The induction of pollen plants of Populus. Acta Botanica Sinica 17:56−62
Google Scholar
|
[114]
|
Deutsch F, Kumlehn J, Ziegenhagen B, Fladung M. 2004. Stable haploid poplar callus lines from immature pollen culture. Physiologia Plantarum 120:613−22 doi: 10.1111/j.0031-9317.2004.0266.x
CrossRef Google Scholar
|
[115]
|
Li Y, Li H, Chen Z, Ji L, Ye M, et al. 2013. Haploid plants from anther cultures of poplar (Populus × beijingensis). Plant Cell, Tissue and Organ Culture (PCTOC) 114:39−48 doi: 10.1007/s11240-013-0303-5
CrossRef Google Scholar
|
[116]
|
Yang J, Li K, Li C, Li J, Zhao B, et al. 2018. In vitro anther culture and Agrobacterium-mediated transformation of the AP1 gene from Salix integra Linn. in haploid poplar (Populus simonii × P. nigra). Journal of Forestry Research 29:321−30 doi: 10.1007/s11676-017-0453-0
CrossRef Google Scholar
|
[117]
|
Ravi M, Chan SWL. 2010. Haploid plants produced by centromere-mediated genome elimination. Nature 464:615−18 doi: 10.1038/nature08842
CrossRef Google Scholar
|
[118]
|
Kelliher T, Starr D, Su X, Tang G, Chen Z, et al. 2019. One-step genome editing of elite crop germplasm during haploid induction. Nature Biotechnology 37:287−92 doi: 10.1038/s41587-019-0038-x
CrossRef Google Scholar
|
[119]
|
Wang N, Gent JI, Dawe RK. 2021. Haploid induction by a maize cenh3 null mutant. Science Advances 7:eabe2299 doi: 10.1126/sciadv.abe2299
CrossRef Google Scholar
|
[120]
|
Castellanos-Hernández OA, Rodríguez-Sahagún A, Acevedo-Hernández GJ, Herrera-Estrella LR. 2011. Genetic Transformation of Forest Trees. In Genetic Transformation, ed. Alvarez M. Rijeka: IntechOpen. pp. 191−214. http://doi.org/10.5772/24354
|
[121]
|
Song G, Prieto H, Orbovic V. 2019. Agrobacterium-Mediated Transformation of Tree Fruit Crops: Methods, Progress, and Challenges. Frontiers in Plant Science 10:266 doi: 10.3389/fpls.2019.00226
CrossRef Google Scholar
|
[122]
|
Giri CC, Shyamkumar B, Anjaneyulu C. 2004. Progress in tissue culture, genetic transformation and applications of biotechnology to trees: an overview. Trees 18:115−35 doi: 10.1007/s00468-003-0287-6
CrossRef Google Scholar
|
[123]
|
Fillatti JJ, Sellmer J, Mccown B, Haissig B, Comai L. 1987. Agrobacterium Mediated Transformation and Regeneration of Populus. Molecular and General Genetics MGG 206:192−9 doi: 10.1007/BF00333574
CrossRef Google Scholar
|
[124]
|
Huang Y, Diner AM, Karnosky DF. 1991. Agrobacterium rhizogenes-mediated genetic transformation and regeneration of a conifer: Larix decidua. In Vitro Cellular & Developmental Biology - Plant 27:201−7 doi: 10.1007/BF02632217
CrossRef Google Scholar
|
[125]
|
Bruegmann T, Polak O, Deecke K, Nietsch J, Fladung M. 2019. Poplar Transformation. In Transgenic Plants, Methods in Molecular Biology, eds. Kumar S, Barone P, Smith M. vol 1864. New York: Humana Press. pp. 165–77 https://doi.org/10.1007/978-1-4939-8778-8_12
|
[126]
|
Litz RE, Padilla G. 2012. Genetic Transformation of Fruit Trees. In Genomics of Tree Crops, eds. Schnell R, Priyadarshan P. New York: Springer. pp. 117−53. https://doi.org/10.1007/978-1-4614-0920-5_5
|
[127]
|
Jayashree R, Rekha K, Venkatachalam P, Uratsu SL, Dandekar AM, et al. 2003. Genetic transformation and regeneration of rubber tree (Hevea brasiliensis Muell. Arg) transgenic plants with a constitutive version of an anti-oxidative stress superoxide dismutase gene. Plant Cell Reports 22:201−9 doi: 10.1007/s00299-003-0666-x
CrossRef Google Scholar
|
[128]
|
Tang W, Newton RJ. 2003. Genetic transformation of conifers and its application in forest biotechnology. Plant Cell Reports 22:1−15 doi: 10.1007/s00299-003-0670-1
CrossRef Google Scholar
|
[129]
|
Cervera M, Navarro A, Navarro L, Peña L. 2008. Production of transgenic adult plants from clementine mandarin by enhancing cell competence for transformation and regeneration. Tree Physiology 28:55−66 doi: 10.1093/treephys/28.1.55
CrossRef Google Scholar
|
[130]
|
Dong JZ, Jia SR. 1991. High efficiency plant regeneration from cotyledons of watermelon (Citrullus vulgaris Schrad). Plant Cell Reports 9:559−62 doi: 10.1007/BF00232331
CrossRef Google Scholar
|
[131]
|
Baker BS, Bhatia SK. 1993. Factors effecting adventitious shoot regeneration from leaf explants of quince (Cydonia oblonga). Plant Cell, Tissue and Organ Culture 35:273−77 doi: 10.1007/BF00037281
CrossRef Google Scholar
|
[132]
|
Becerra D, Forero A, Góngora GA. 2004. Age and physiological condition of donor plants affect in vitro morphogenesis in leaf explants of Passiflora edulis f. flavicarpa. Plant Cell, Tissue and Organ Culture 79:87−90 doi: 10.1023/B:TICU.0000049440.10767.29
CrossRef Google Scholar
|
[133]
|
Zhang T, Lian H, Tang H, Dolezal K, Zhou C, et al. 2015. An intrinsic microRNA timer regulates progressive decline in shoot regenerative capacity in plants. The Plant Cell 27:349−60 doi: 10.1105/tpc.114.135186
CrossRef Google Scholar
|
[134]
|
Raspor M, Motyka V, Kaleri AR, Ninković S, Tubić L, et al. 2021. Integrating the roles for cytokinin and auxin in de novo shoot organogenesis: from hormone uptake to signaling outputs. International Journal of Molecular Sciences 22:8554 doi: 10.3390/ijms22168554
CrossRef Google Scholar
|
[135]
|
Hill K, Schaller GE. 2013. Enhancing plant regeneration in tissue culture: a molecular approach through manipulation of cytokinin sensitivity. Plant Signaling and Behavior 8:e25709 doi: 10.4161/psb.25709
CrossRef Google Scholar
|
[136]
|
Yang J, Zhao B, Kim YB, Zhou C, Li C, et al. 2013. Agrobacterium tumefaciens-mediated transformation of Phellodendron amurense Rupr. using mature-seed explants. Molecular Biology Reports 40:281−88 doi: 10.1007/s11033-012-2059-0
CrossRef Google Scholar
|
[137]
|
Yang J, Zhao S, Zhao B, Li C. 2018. Overexpression of TaLEA3 induces rapid stomatal closure under drought stress in Phellodendron amurense Rupr. Plant Science 277:100−9 doi: 10.1016/j.plantsci.2018.09.022
CrossRef Google Scholar
|
[138]
|
Yang J, Zhou C, Zhao B, Jin C, Zhang T, et al. 2011. Rapid direct adventitious shoot organogenesis and plant regeneration from mature seed explants of Phellodendron amurense Rupr. Journal of Medicinal Plant Research 5:4560−65
Google Scholar
|
[139]
|
Yang J, Yi J, Yang C, Li CJTP. 2013. Agrobacterium tumefaciens-mediated genetic transformation of Salix matsudana Koidz. using mature seeds. Tree Physiology 33:628−39 doi: 10.1093/treephys/tpt038
CrossRef Google Scholar
|
[140]
|
Yang J, Chen Z, Wu S, Cui Y, Zhang L, et al. 2015. Overexpression of the Tamarix hispida ThMT3 gene increases copper tolerance and adventitious root induction in Salix matsudana Koidz. Plant Cell, Tissue and Organ Culture 121:469−79 doi: 10.1007/s11240-015-0717-3
CrossRef Google Scholar
|
[141]
|
Teixeira da Silva JA, Malabadi RB. 2012. Factors affecting somatic embryogenesis in conifers. Journal of Forestry Research 23:503−15 doi: 10.1007/s11676-012-0266-0
CrossRef Google Scholar
|
[142]
|
Hazubska-Przyby T, Bojarczuk K. 2016. Tree somatic embryogenesis in science and forestry. Dendrobiology 76:105−16 doi: 10.12657/denbio.076.010
CrossRef Google Scholar
|
[143]
|
Ikeuchi M, Ogawa Y, Iwase A, Sugimoto K. 2016. Plant regeneration: cellular origins and molecular mechanisms. Development 143:1442−51 doi: 10.1242/dev.134668
CrossRef Google Scholar
|
[144]
|
Duan H, Maren NA, Ranney TG, Liu WJOPR. 2022. New opportunities for using WUS/BBM and GRF-GIF genes to enhance genetic transformation of ornamental plants. Ornamental Plant Research 2:4 doi: 10.48130/OPR-2022-0004
CrossRef Google Scholar
|
[145]
|
Lowe K, Wu E, Wang N, Hoerster G, Hastings C, et al. 2016. Morphogenic regulators Baby boom and Wuschel improve monocot transformation. The Plant Cell 28:1998−2015 doi: 10.1105/tpc.16.00124
CrossRef Google Scholar
|
[146]
|
Debernardi JM, Tricoli DM, Ercoli MF, Hayta S, Ronald P, et al. 2020. A GRF-GIF chimeric protein improves the regeneration efficiency of transgenic plants. Nature Biotechnology 38:1274−79 doi: 10.1038/s41587-020-0703-0
CrossRef Google Scholar
|
[147]
|
Liu B, Zhang J, Yang Z, Matsui A, Seki M, et al. 2018. PtWOX11 acts as master regulator conducting the expression of key transcription factors to induce de novo shoot organogenesis in poplar. Plant Molecular Biology 98:389−406 doi: 10.1007/s11103-018-0786-x
CrossRef Google Scholar
|
[148]
|
Chen J, Tomes S, Gleave AP, Hall W, Luo Z, et al. 2022. Significant improvement of apple (Malus domestica Borkh.) transgenic plant production by pre-transformation with a Baby boom transcription factor. Horticulture Research 9:uhab014 doi: 10.1093/hr/uhab014
CrossRef Google Scholar
|
[149]
|
Xu L, Huang H. 2014. Genetic and epigenetic controls of plant regeneration. Current Topics In Developmental Biology 108:1−33 doi: 10.1016/B978-0-12-391498-9.00009-7
CrossRef Google Scholar
|
[150]
|
Nagle M, Déjardin A, Pilate G, Strauss SH. 2018. Opportunities for Innovation in Genetic Transformation of Forest Trees. Frontiers in Plant Science 9:1443 doi: 10.3389/fpls.2018.01443
CrossRef Google Scholar
|
[151]
|
Luo G, Palmgren M. 2021. GRF-GIF Chimeras Boost Plant Regeneration. Trends in Plant Science 26:201−4 doi: 10.1016/j.tplants.2020.12.001
CrossRef Google Scholar
|
[152]
|
Ellison EE, Nagalakshmi U, Gamo ME, Huang PJ, Dinesh-Kumar S, et al. 2020. Multiplexed heritable gene editing using RNA viruses and mobile single guide RNAs. Nature Plants 6:620−24 doi: 10.1038/s41477-020-0670-y
CrossRef Google Scholar
|
[153]
|
Ji X, Yang B, Wang D. 2020. Achieving plant genome editing while bypassing tissue culture. Trends in Plant Science 25:427−29 doi: 10.1016/j.tplants.2020.02.011
CrossRef Google Scholar
|
[154]
|
Yang J, Lan L, Jin Y, Yu N, Wang D, et al. 2022. Mechanisms underlying legume-rhizobium symbioses. Journal of Integrative Plant Biology 64:244−67 doi: 10.1111/jipb.13207
CrossRef Google Scholar
|
[155]
|
Leary JK, Singleton PW, Borthakur D. 2004. Canopy nodulation of the endemic tree legume Acacia koa in the mesic forests of Hawaii. Ecology 85:3151−75 doi: 10.1890/03-3168
CrossRef Google Scholar
|
[156]
|
Honda MDH, Borthakur D. 2020. Mimosine facilitates metallic cation uptake by plants through formation of mimosine-cation complexes. Plant Molecular Biology 102:431−45 doi: 10.1007/s11103-019-00956-1
CrossRef Google Scholar
|
[157]
|
Borthakur D, Soedarjo M, Fox PM, Webb DT. 2003. The mid genes of Rhizobium sp strain TAL1145 are required for degradation of mimosine into 3-hydroxy-4-pyridone and are inducible by mimosine. Microbiology 149:537−46 doi: 10.1099/mic.0.25954-0
CrossRef Google Scholar
|
[158]
|
Negi VS, Bingham JP, Li QX, Borthakur D. 2013. midD-encoded 'rhizomimosinase' from Rhizobium sp. strain TAL1145 is a C-N lyase that catabolizes L-mimosine into 3-hydroxy-4-pyridone, pyruvate and ammonia. Amino Acids 44:1537−47 doi: 10.1007/s00726-013-1479-z
CrossRef Google Scholar
|
[159]
|
Awaya JD, Fox PM, Borthakur D. 2005. pyd genes of Rhizobium sp. strain TAL1145 are required for degradation of 3-hydroxy-4-pyridone, an aromatic intermediate in mimosine metabolism. Journal of Bacteriology 187:4480−7 doi: 10.1128/JB.187.13.4480-4487.2005
CrossRef Google Scholar
|
[160]
|
Soedarjo M, Borthakur D. 1998. Mimosine, a toxin produced by the tree-legume Leucaena provides a nodulation competition advantage to mimosine-degrading Rhizobium strains. Soil Biology and Biochemistry 30:1605−13 doi: 10.1016/S0038-0717(97)00180-6
CrossRef Google Scholar
|
[161]
|
Soedarjo M, Hemscheidt TK, Borthakur D. 1994. Mimosine, a toxin present in leguminous trees (Leucaena spp.), induces a mimosine-degrading enzyme activity in some Rhizobium strains. Applied and Environmental Microbiology 60:4268−72 doi: 10.1128/aem.60.12.4268-4272.1994
CrossRef Google Scholar
|
[162]
|
Tuskan GA, Difazio S, Jansson S, Bohlmann J, Grigoriev I, et al. 2006. The genome of black cottonwood, Populus trichocarpa (Torr. & Gray). Science 313:1596−604 doi: 10.1126/science.1128691
CrossRef Google Scholar
|
[163]
|
Marks RA, Hotaling S, Frandsen PB, VanBuren R. 2021. Representation and participation across 20 years of plant genome sequencing. Nature Plants 7:1571−78 doi: 10.1038/s41477-021-01031-8
CrossRef Google Scholar
|
[164]
|
Wenger AM, Peluso P, Rowell WJ, Chang PC, Hall RJ, et al. 2019. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nature Biotechnology 37:1155−62 doi: 10.1038/s41587-019-0217-9
CrossRef Google Scholar
|
[165]
|
Neale DB, Zimin AV, Zaman S, Scott AD, Shrestha B, et al. 2022. Assembled and annotated 26.5 Gbp coast redwood genome: a resource for estimating evolutionary adaptive potential and investigating hexaploid origin. G3 Genes|Genomes|Genetics 12:jkab380 doi: 10.1093/g3journal/jkab380
CrossRef Google Scholar
|
[166]
|
Wang C, Liu C, Roqueiro D, Grimm D, Schwab R, et al. 2015. Genome-wide analysis of local chromatin packing in Arabidopsis thaliana. Genome Research 25:246−56 doi: 10.1101/gr.170332.113
CrossRef Google Scholar
|
[167]
|
Michael TP, Bryant D, Gutierrez R, Borisjuk N, Chu P, et al. 2017. Comprehensive definition of genome features in Spirodela polyrhiza by high-depth physical mapping and short-read DNA sequencing strategies. The Plant Journal 89:617−35 doi: 10.1111/tpj.13400
CrossRef Google Scholar
|
[168]
|
Niu S, Li J, Bo W, Yang W, Zuccolo A, et al. 2022. The Chinese pine genome and methylome unveil key features of conifer evolution. Cell 185:204−217.E14 doi: 10.1016/j.cell.2021.12.006
CrossRef Google Scholar
|
[169]
|
Cazzolla Gatti R, Reich PB, Gamarra JGP, Crowther T, Hui C, et al. 2022. The number of tree species on Earth. PNAS 119:.e2115329119 doi: 10.1073/pnas.2115329119
CrossRef Google Scholar
|
[170]
|
Chen H, Zeng Y, Yang Y, Huang L, Tang B, et al. 2020. Allele-aware chromosome-level genome assembly and efficient transgene-free genome editing for the autotetraploid cultivated alfalfa. Nature Communications 11:2494 doi: 10.1038/s41467-020-16338-x
CrossRef Google Scholar
|
[171]
|
Koren S, Rhie A, Walenz BP, Dilthey AT, Bickhart DM, et al. 2018. De novo assembly of haplotype-resolved genomes with trio binning. Nature Biotechnology 36:1174−82 doi: 10.1038/nbt.4277
CrossRef Google Scholar
|
[172]
|
Zhang X, Zhang S, Zhao Q, Ming R, Tang H. 2019. Assembly of allele-aware, chromosomal-scale autopolyploid genomes based on Hi-C data. Nature Plants 5:833−45 doi: 10.1038/s41477-019-0487-8
CrossRef Google Scholar
|
[173]
|
Kronenberg ZN, Rhie A, Koren S, Concepcion GT, Peluso P, et al. 2021. Extended haplotype-phasing of long-read de novo genome assemblies using Hi-C. Nature Communications 12:1935 doi: 10.1038/s41467-020-20536-y
CrossRef Google Scholar
|
[174]
|
Zhang Q, Qi Y, Pan H, Tang H, Wang G, et al. 2022. Genomic insights into the recent chromosome reduction of autopolyploid sugarcane Saccharum spontaneum. Nature Genetics 54:885−96 doi: 10.1038/s41588-022-01084-1
CrossRef Google Scholar
|
[175]
|
Sun H, Jiao W, Krause K, Campoy JA, Goel M, et al. 2022. Chromosome-scale and haplotype-resolved genome assembly of a tetraploid potato cultivar. Nature Genetics 54:342−48 doi: 10.1038/s41588-022-01015-0
CrossRef Google Scholar
|
[176]
|
Zhang S, Li R, Zhang L, Chen S, Xie M, et al. 2020. New insights into Arabidopsis transcriptome complexity revealed by direct sequencing of native RNAs. Nucleic Acids Research 48:7700−11 doi: 10.1093/nar/gkaa588
CrossRef Google Scholar
|
[177]
|
Ji X, Li P, Fuscoe JC, Chen G, Xiao W, et al. 2020. A comprehensive rat transcriptome built from large scale RNA-seq-based annotation. Nucleic Acids Research 48:8320−31 doi: 10.1093/nar/gkaa638
CrossRef Google Scholar
|
[178]
|
Liu H, Wang X, Wang G, Cui P, Wu S, et al. 2021. The nearly complete genome of Ginkgo biloba illuminates gymnosperm evolution. Nature Plant 7:748−56 doi: 10.1038/s41477-021-00933-x
CrossRef Google Scholar
|
[179]
|
Cooke JEK, Eriksson ME, Junttila O. 2012. The dynamic nature of bud dormancy in trees: environmental control and molecular mechanisms. Plant, Cell & Environment 35:1707−28 doi: 10.1111/j.1365-3040.2012.02552.x
CrossRef Google Scholar
|
[180]
|
Triozzi PM, Ramos-Sánchez JM, Hernández-Verdeja T, Moreno-Cortés A, Allona I, et al. 2018. Photoperiodic regulation of shoot apical growth in poplar. Frontiers in Plant Science 9:1030 doi: 10.3389/fpls.2018.01030
CrossRef Google Scholar
|
[181]
|
Lloret A, Badenes ML, Ríos G. 2018. Modulation of dormancy and growth responses in reproductive buds of temperate trees. Frontiers in Plant Science 9:1368 doi: 10.3389/fpls.2018.01368
CrossRef Google Scholar
|
[182]
|
Brunner AM, Evans LM, Hsu CY, Sheng X. 2014. Vernalization and the chilling requirement to exit bud dormancy: shared or separate regulation. Frontiers in Plant Science 5:732 doi: 10.3389/fpls.2014.00732
CrossRef Google Scholar
|
[183]
|
Liu J, Sherif SM. 2019. Hormonal orchestration of bud dormancy cycle in deciduous woody perennials. Frontiers in Plant Science 10:1136 doi: 10.3389/fpls.2019.01136
CrossRef Google Scholar
|
[184]
|
Yang Q, Gao Y, Wu X, Moriguchi T, Bai S, et al. 2021. Bud endodormancy in deciduous fruit trees: advances and prospects. Horticulture Research 8:139 doi: 10.1038/s41438-021-00575-2
CrossRef Google Scholar
|
[185]
|
Maurya JP, Bhalerao RP. 2017. Photoperiod- and temperature-mediated control of growth cessation and dormancy in trees: a molecular perspective. Annals of Botany 120:351−60 doi: 10.1093/aob/mcx061
CrossRef Google Scholar
|
[186]
|
Maurya JP, Triozzi PM, Bhalerao RP, Perales M. 2018. Environmentally sensitive molecular switches drive poplar phenology. Frontiers in Plant Science 9:1873 doi: 10.3389/fpls.2018.01873
CrossRef Google Scholar
|
[187]
|
Rohde A, Bhalerao RP. 2007. Plant dormancy in the perennial context. Trends in Plant Science 12:217−23 doi: 10.1016/j.tplants.2007.03.012
CrossRef Google Scholar
|
[188]
|
Andersson A, Keskitalo J, Sjodin A, Bhalerao R, Sterky F, et al. 2004. A transcriptional timetable of autumn senescence. Genome Biology 5:R24
Google Scholar
|
[189]
|
Myburg AA, Grattapaglia D, Tuskan GA, Hellsten U, Hayes RD, et al. 2014. The genome of Eucalyptus grandis. Nature 510:356−62 doi: 10.1038/nature13308
CrossRef Google Scholar
|
[190]
|
Chen S, Wang Y, Yu L, Zheng T, Wang S, et al. 2021. Genome sequence and evolution of Betula platyphylla. Horticulture Research 8:37 doi: 10.1038/s41438-021-00481-7
CrossRef Google Scholar
|
[191]
|
Plomion C, Aury JM, Amselem J, Leroy T, Murat F, et al. 2018. Oak genome reveals facets of long lifespan. Nature Plants 4:440−52 doi: 10.1038/s41477-018-0172-3
CrossRef Google Scholar
|
[192]
|
Sollars ESA, Harper AL, Kelly LJ, Sambles CM, Ramirez-Gonzalez RH, et al. 2017. Genome sequence and genetic diversity of European ash trees. Nature 541:212−6 doi: 10.1038/nature20786
CrossRef Google Scholar
|
[193]
|
Nystedt B, Street NR, Wetterbom A, Zuccolo A, Lin YC, et al. 2013. The Norway spruce genome sequence and conifer genome evolution. Nature 497:579−84 doi: 10.1038/nature12211
CrossRef Google Scholar
|
[194]
|
Rohde A, Storme V, Jorge V, Gaudet M, Vitacolonna N, et al. 2011. Bud set in poplar - genetic dissection of a complex trait in natural and hybrid populations. New Phytologist 189:106−21 doi: 10.1111/j.1469-8137.2010.03469.x
CrossRef Google Scholar
|
[195]
|
Evans LM, Slavov GT, Rodgers-Melnick E, Martin J, Ranjan P, et al. 2014. Population genomics of Populus trichocarpa identifies signatures of selection and adaptive trait associations. Nature Genetics 46:1089−96 doi: 10.1038/ng.3075
CrossRef Google Scholar
|
[196]
|
Howe GT, Horvath DP, Dharmawardhana P, Priest HD, Mockler TC, et al. 2015. Extensive transcriptome changes during natural onset and release of vegetative bud dormancy in Populus. Frontiers in Plant Science 6:989 doi: 10.3389/fpls.2015.00989
CrossRef Google Scholar
|
[197]
|
Karlberg A, Englund M, Petterle A, Molnár G, Sjödin A, et al. 2010. Analysis of global changes in gene expression during activity-dormancy cycle in hybrid aspen apex. Plant Biotechnology 27:1−16 doi: 10.5511/plantbiotechnology.27.1
CrossRef Google Scholar
|
[198]
|
Ueno S, Klopp C, Leplé JC, Derory J, Noirot C, et al. 2013. Transcriptional profiling of bud dormancy induction and release in oak by next-generation sequencing. BMC Genomics 14:236 doi: 10.1186/1471-2164-14-236
CrossRef Google Scholar
|
[199]
|
Nose M, Kurita M, Tamura M, Matsushita M, Hiraoka Y, et al. 2020. Effects of day length- and temperature-regulated genes on annual transcriptome dynamics in Japanese cedar (Cryptomeria japonica D. Don), a gymnosperm indeterminate species. PloS One 15:e0229843 doi: 10.1371/journal.pone.0229843
CrossRef Google Scholar
|
[200]
|
Wu K, Duan X, Zhu Z, Sang Z, Zhang Y, et al. 2021. Transcriptomic analysis reveals the positive role of abscisic acid in endodormancy maintenance of leaf buds of Magnolia wufengensis. Frontiers in Plant Science 12:742504 doi: 10.3389/fpls.2021.742504
CrossRef Google Scholar
|
[201]
|
Ruttink T, Arend M, Morreel K, Storme V, Rombauts S, et al. 2007. A molecular timetable for apical bud formation and dormancy induction in poplar. The Plant Cell 19:2370−90 doi: 10.1105/tpc.107.052811
CrossRef Google Scholar
|
[202]
|
Lesur I, Le Provost G, Bento P, Da Silva C, Leplé JC, et al. 2015. The oak gene expression atlas: insights into Fagaceae genome evolution and the discovery of genes regulated during bud dormancy release. BMC Genomics 16:112 doi: 10.1186/s12864-015-1331-9
CrossRef Google Scholar
|
[203]
|
Santamaría ME, Rodríguez R, Cañal MJ, Toorop PE. 2011. Transcriptome analysis of chestnut (Castanea sativa) tree buds suggests a putative role for epigenetic control of bud dormancy. Annals of Botany 108:485−98 doi: 10.1093/aob/mcr185
CrossRef Google Scholar
|
[204]
|
Li W, Kang Y, Zhang Y, Zang Q, Qi L. 2021. Concerted control of the LaRAV1-LaCDKB1;3 module by temperature during dormancy release and reactivation of larch. Tree Physiology 41:1918−37 doi: 10.1093/treephys/tpab052
CrossRef Google Scholar
|
[205]
|
Hsu CY, Adams JP, No K, Liang H, Meilan R, et al. 2012. Overexpression of CONSTANS homologs CO1 and CO2 fails to alter normal reproductive onset and fall bud set in woody perennial poplar. PloS One 7:e45448-e doi: 10.1371/journal.pone.0045448
CrossRef Google Scholar
|
[206]
|
Yordanov YS, Ma C, Strauss SH, Busov VB. 2014. EARLY BUD-BREAK 1 (EBB1) is a regulator of release from seasonal dormancy in poplar trees. PNAS 111:10001−6 doi: 10.1073/pnas.1405621111
CrossRef Google Scholar
|
[207]
|
Singh RK, Maurya JP, Azeez A, Miskolczi P, Tylewicz S, et al. 2018. A genetic network mediating the control of bud break in hybrid aspen. Nature Communications 9:4173 doi: 10.1038/s41467-018-06696-y
CrossRef Google Scholar
|
[208]
|
Singh RK, Miskolczi P, Maurya JP, Bhalerao RP. 2019. A Tree ortholog of SHORT VEGETATIVE PHASE floral repressor mediates photoperiodic control of bud dormancy. Current Biology 29:128−33 doi: 10.1016/j.cub.2018.11.006
CrossRef Google Scholar
|
[209]
|
Conde D, Le Gac AL, Perales M, Dervinis C, Kirst M, et al. 2017. Chilling-responsive DEMETER-LIKE DNA demethylase mediates in poplar bud break. Plant, Cell & Environment 40:2236−49 doi: 10.1111/pce.13019
CrossRef Google Scholar
|
[210]
|
Azeez A, Zhao YC, Singh RK, Yordanov YS, Dash M, et al. 2021. EARLY BUD-BREAK 1 and EARLY BUD-BREAK 3 control resumption of poplar growth after winter dormancy. Nature Communications 12:1123 doi: 10.1038/s41467-021-21449-0
CrossRef Google Scholar
|
[211]
|
Anh Tuan P, Bai S, Saito T, Imai T, Ito A, et al. 2016. Involvement of EARLY BUD-BREAK, an AP2/ERF transcription factor gene, in bud break in Japanese pear (Pyrus pyrifolia Nakai) lateral flower buds: expression, histone modifications and possible target genes. Plant Cell Physiology 57:1038−47 doi: 10.1093/pcp/pcw041
CrossRef Google Scholar
|
[212]
|
Csorba T, Questa JI, Sun Q, Dean C. 2014. Antisense COOLAIR mediates the coordinated switching of chromatin states at FLC during vernalization. PNAS 111:16160−5 doi: 10.1073/pnas.1419030111
CrossRef Google Scholar
|
[213]
|
Johnsen Ø, Fossdal CG, Nagy N, Mølmann JA, Dæhlen OG, et al. 2005. Climatic adaptation in Picea abies progenies is affected by the temperature during zygotic embryogenesis and seed maturation. Plant, Cell & Environment 28:1090−102 doi: 10.1111/j.1365-3040.2005.01356.x
CrossRef Google Scholar
|
[214]
|
Yakovlev I, Fossdal CG, Skrøppa T, Olsen JE, Jahren AH, Johnsen Ø. 2012. An adaptive epigenetic memory in conifers with important implications for seed production. Seed Science Research 22:63−76 doi: 10.1017/S0960258511000535
CrossRef Google Scholar
|
[215]
|
Yakovlev IA, Fossdal CG, Johnsen Ø. 2010. MicroRNAs, the epigenetic memory and climatic adaptation in Norway spruce. New Phytologist 187:1154−69 doi: 10.1111/j.1469-8137.2010.03341.x
CrossRef Google Scholar
|
[216]
|
Yakovlev IA, Fossdal CG, Johnsen Ø, Junttila O, Skrøppa T. 2006. Analysis of gene expression during bud burst initiation in Norway spruce via ESTs from subtracted cDNA libraries. Tree Genetics & Genomes 2:39−52 doi: 10.1007/s11295-005-0031-z
CrossRef Google Scholar
|
[217]
|
Du Q, Lu W, Quan M, Xiao L, Song F, et al. 2018. Genome-wide association studies to improve wood properties: challenges and prospects. Frontiers in Plant Science 9:1912 doi: 10.3389/fpls.2018.01912
CrossRef Google Scholar
|
[218]
|
Resende RT, Resende MDV, Silva FF, Azevedo CF, Takahashi EK, et al. 2017. Regional heritability mapping and genome-wide association identify loci for complex growth, wood and disease resistance traits in Eucalyptus. New Phtologist 213:1287−300 doi: 10.1111/nph.14266
CrossRef Google Scholar
|
[219]
|
Lv C, Lu W, Quan M, Xiao L, Li L, et al. 2021. Pyramiding superior haplotypes and epistatic alleles to accelerate wood quality and yield improvement in poplar breeding. Industrial Crops and Products 171:113891 doi: 10.1016/j.indcrop.2021.113891
CrossRef Google Scholar
|
[220]
|
Bartholomé J, Mandrou E, Mabiala A, Jenkins J, Nabihoudine I, et al. 2015. High-resolution genetic maps of Eucalyptus improve Eucalyptus grandis genome assembly. New Phtologist 206:1283−96 doi: 10.1111/nph.13150
CrossRef Google Scholar
|
[221]
|
Wu Y, Close TJ, Lonardi S. 2011. Accurate construction of consensus genetic maps via integer linear programming. IEEE/ACM Transactions on Computational Biology and Bioinformatics 8:381−94 doi: 10.1109/TCBB.2010.35
CrossRef Google Scholar
|
[222]
|
Rastas P. 2017. Lep-MAP3: robust linkage mapping even for low-coverage whole genome sequencing data. Bioinformatics 33:3726−32 doi: 10.1093/bioinformatics/btx494
CrossRef Google Scholar
|
[223]
|
Qian Z, Zhang B, Chen H, Lu L, Duan M, et al. 2021. Identification of quantitative trait loci controlling the development of prickles in eggplant by genome re-sequencing analysis. Frontiers in Plant Science 12:731079 doi: 10.3389/fpls.2021.731079
CrossRef Google Scholar
|
[224]
|
Li Z, Xu Y. 2022. Bulk segregation analysis in the NGS era: a review of its teenage years. The Plant Journal 109:1355−74 doi: 10.1111/tpj.15646
CrossRef Google Scholar
|
[225]
|
Zhuo X, Zheng T, Li S, Zhang Z, Zhang M, et al. 2021. Identification of the PmWEEP locus controlling weeping traits in Prunus mume through an integrated genome-wide association study and quantitative trait locus mapping. Horticulture Research 8:131 doi: 10.1038/s41438-021-00573-4
CrossRef Google Scholar
|
[226]
|
Gattolin S, Cirilli M, Pacheco I, Ciacciulli A, Da Silva Linge C, et al. 2018. Deletion of the miR172 target site in a TOE-type gene is a strong candidate variant for dominant double-flower trait in Rosaceae. The Plant Journal 96:358−71 doi: 10.1111/tpj.14036
CrossRef Google Scholar
|
[227]
|
An Z, Zhao Y, Zhang X, Huang X, Hu Y, et al. 2019. A high-density genetic map and QTL mapping on growth and latex yield-related traits in Hevea brasiliensis Müll. Arg. Industrial Crops and Products 132:440−48 doi: 10.1016/j.indcrop.2019.03.002
CrossRef Google Scholar
|
[228]
|
Du Q, Gong C, Wang Q, Zhou D, Yang H, et al. 2016. Genetic architecture of growth traits in Populus revealed by integrated quantitative trait locus (QTL) analysis and association studies. New Phtologist 209:1067−82 doi: 10.1111/nph.13695
CrossRef Google Scholar
|
[229]
|
Du Q, Yang X, Xie J, Quan M, Xiao L, et al. 2019. Time-specific and pleiotropic quantitative trait loci coordinately modulate stem growth in Populus. Plant Biotechnology Journal 17:608−24 doi: 10.1111/pbi.13002
CrossRef Google Scholar
|
[230]
|
Porth I, Klapste J, Skyba O, Hannemann J, McKown AD, et al. 2013. Genome-wide association mapping for wood characteristics in Populus identifies an array of candidate single nucleotide polymorphisms. New Phytologist 200:710−26 doi: 10.1111/nph.12422
CrossRef Google Scholar
|
[231]
|
Fahrenkrog AM, Neves LG, Resende MFR Jr, Vazquez AI, de Los Campos G, et al. 2017. Genome-wide association study reveals putative regulators of bioenergy traits in Populus deltoides. New Phtologist 213:799−811 doi: 10.1111/nph.14154
CrossRef Google Scholar
|
[232]
|
Quan M, Liu X, Du Q, Xiao L, Lu W, et al. 2021. Genome-wide association studies reveal the coordinated regulatory networks underlying photosynthesis and wood formation in Populus. Journal of Experimental Botany 72:5372−89 doi: 10.1093/jxb/erab122
CrossRef Google Scholar
|
[233]
|
Müller BSF, de Almeida Filho JE, Lima BM, Garcia CC, Missiaggia A, et al. 2019. Independent and Joint-GWAS for growth traits in Eucalyptus by assembling genome-wide data for 3373 individuals across four breeding populations. New Phtologist 221:818−33 doi: 10.1111/nph.15449
CrossRef Google Scholar
|
[234]
|
De La Torre AR, Puiu D, Crepeau MW, Stevens K, Salzberg SL, et al. 2019. Genomic architecture of complex traits in loblolly pine. New Phtologist 221:1789−801 doi: 10.1111/nph.15535
CrossRef Google Scholar
|
[235]
|
Chen M, Fan W, Ji F, Hua H, Liu J, et al. 2021. Genome-wide identification of agronomically important genes in outcrossing crops using OutcrossSeq. Molecular Plant 14:556−70 doi: 10.1016/j.molp.2021.01.003
CrossRef Google Scholar
|
[236]
|
Gong C, Du Q, Xie J, Quan M, Chen B, et al. 2018. Dissection of insertion-deletion variants within differentially expressed genes involved in wood formation in Populus. Frontiers in Plant Science 8:2199 doi: 10.3389/fpls.2017.02199
CrossRef Google Scholar
|
[237]
|
Valenzuela CE, Ballesta P, Ahmar S, Fiaz S, Heidari P, et al. 2021. Haplotype- and SNP-based GWAS for growth and wood quality traits in Eucalyptus cladocalyx trees under arid conditions. Plants 10:148 doi: 10.3390/plants10010148
CrossRef Google Scholar
|
[238]
|
Ding X, Diao S, Luan Q, Wu HX, Zhang Y, et al. 2022. A transcriptome-based association study of growth, wood quality, and oleoresin traits in a slash pine breeding population. PloS Genetics 18:e1010017 doi: 10.1371/journal.pgen.1010017
CrossRef Google Scholar
|
[239]
|
Francisco FR, Aono AH, da Silva CC, Gonçalves PS, Scaloppi Junior EJ, et al. 2021. Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches. Frontiers in Plant Science 12:768589 doi: 10.3389/fpls.2021.768589
CrossRef Google Scholar
|
[240]
|
Sarić R, Nguyen VD, Burge T, Berkowitz O, Trtílek M, et al. 2022. Applications of hyperspectral imaging in plant phenotyping. Trends in Plant Science 27:301−15 doi: 10.1016/j.tplants.2021.12.003
CrossRef Google Scholar
|
[241]
|
Sawitri, Tani N, Na’iem M, Widiyatno, Indrioko S, et al. 2020. Potential of genome-wide association studies and genomic selection to improve productivity and quality of commercial timber species in tropical rainforest, a case study of Shorea platyclados. Forests 11:239 doi: 10.3390/f11020239
CrossRef Google Scholar
|
[242]
|
Chhatre VE, Fetter KC, Gougherty AV, Fitzpatrick MC, Soolanayakanahally RY, et al. 2019. Climatic niche predicts the landscape structure of locally adaptive standing genetic variation. bioRxiv Preprint doi: 10.1101/817411
CrossRef Google Scholar
|
[243]
|
Guzella TS, Dey S, Chelo IM, Pino-Querido A, Pereira VF, et al. 2018. Slower environmental change hinders adaptation from standing genetic variation. PLoS Genetics 14:e1007731 doi: 10.1371/journal.pgen.1007731
CrossRef Google Scholar
|
[244]
|
Filipe JC, Rymer PD, Byrne M, Hardy G, Mazanec R, et al. 2022. Signatures of natural selection in a foundation tree along Mediterranean climatic gradients. Molecular Ecology 31:1735−52 doi: 10.1111/mec.16351
CrossRef Google Scholar
|
[245]
|
Wang J, Ding J, Tan B, Robinson KM, Michelson IH, et al. 2018. A major locus controls local adaptation and adaptive life history variation in a perennial plant. Genome Biology 19:72 doi: 10.1186/s13059-018-1444-y
CrossRef Google Scholar
|
[246]
|
Gugger PF, Fitz-Gibbon ST, Albarrán-Lara A, Wright JW, Sork VL. 2021. Landscape genomics of Quercus lobata reveals genes involved in local climate adaptation at multiple spatial scales. Molecular Ecology 30:406−23 doi: 10.1111/mec.15731
CrossRef Google Scholar
|
[247]
|
Lu W, Xiao L, Quan M, Wang Q, El-Kassaby YA, et al. 2020. Linkage-linkage disequilibrium dissection of the epigenetic quantitative trait loci (epiQTLs) underlying growth and wood properties in Populus. New Phtologist 225:1218−33 doi: 10.1111/nph.16220
CrossRef Google Scholar
|
[248]
|
Ci D, Song Y, Du Q, Tian M, Han S, Zhang D. 2016. Variation in genomic methylation in natural populations of Populus simonii is associated with leaf shape and photosynthetic traits. Journal of Experimental Botany 67:723−37 doi: 10.1093/jxb/erv485
CrossRef Google Scholar
|
[249]
|
Ma K, Sun L, Cheng T, Pan H, Wang J, Zhang Q. 2018. Epigenetic Variance, Performing Cooperative Structure with Genetics, Is Associated with Leaf Shape Traits in Widely Distributed Populations of Ornamental Tree Prunus mume. Frontiers in Plant Science 9:41 doi: 10.3389/fpls.2018.00041
CrossRef Google Scholar
|
[250]
|
Ong-Abdullah M, Ordway JM, Jiang N, Ooi SE, Kok SY, et al. 2015. Loss of Karma transposon methylation underlies the mantled somaclonal variant of oil palm. Nature 525:533−7 doi: 10.1038/nature15365
CrossRef Google Scholar
|
[251]
|
Sáez-Laguna E, Guevara MÁ, Díaz LM, Sánchez-Gómez D, Collada C, et al. 2014. Epigenetic variability in the genetically uniform forest tree species Pinus pinea L. PLoS One 9:e103145 doi: 10.1371/journal.pone.0103145
CrossRef Google Scholar
|
[252]
|
Gugger PF, Fitz-Gibbon S, PellEgrini M, Sork VL. 2016. Species-wide patterns of DNA methylation variation in Quercus lobata and their association with climate gradients. Molecular Ecology 25:1665−80 doi: 10.1111/mec.13563
CrossRef Google Scholar
|
[253]
|
Xu G, Lyu J, Li Q, Liu H, Wang D, et al. 2020. Evolutionary and functional genomics of DNA methylation in maize domestication and improvement. Nature Communications 11:5539 doi: 10.1038/s41467-020-19333-4
CrossRef Google Scholar
|
[254]
|
Xu J, Chen G, Hermanson PJ, Xu Q, Sun C, et al. 2019. Population-level analysis reveals the widespread occurrence and phenotypic consequence of DNA methylation variation not tagged by genetic variation in maize. Genome Biology 20:243 doi: 10.1186/s13059-019-1859-0
CrossRef Google Scholar
|
[255]
|
Eichten SR, Briskine R, Song J, Li Q, Swanson-Wagner R, et al. 2013. Epigenetic and genetic influences on DNA methylation variation in maize populations. The Plant Cell 25:2783−97 doi: 10.1105/tpc.113.114793
CrossRef Google Scholar
|
[256]
|
Motte H, Vercauteren A, Depuydt S, Landschoot S, Geelen D, et al. 2014. Combining linkage and association mapping identifies RECEPTOR-LIKE PROTEIN KINASE1 as an essential Arabidopsis shoot regeneration gene. PNAS 111:8305−10 doi: 10.1073/pnas.1404978111
CrossRef Google Scholar
|
[257]
|
Willi Y, Kristensen TN, Sgrò CM, Weeks AR, Ørsted M, et al. 2022. Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species. PNAS 119:e2105076119 doi: 10.1073/pnas.2105076119
CrossRef Google Scholar
|
[258]
|
Wright S. 1943. Isolation by distance. Genetics 28:114−38 doi: 10.1093/genetics/28.2.114
CrossRef Google Scholar
|
[259]
|
Zhao W, Sun YQ, Pan J, Sullivan AR, Arnold ML, et al. 2020. Effects of landscapes and range expansion on population structure and local adaptation. New Phytologist 228:330−43 doi: 10.1111/nph.16619
CrossRef Google Scholar
|
[260]
|
Excoffier L, Foll M, Petit RJ. 2009. Genetic consequences of range expansions. Annual Review of Ecology Evolution and Systematics 40:481−501 doi: 10.1146/annurev.ecolsys.39.110707.173414
CrossRef Google Scholar
|
[261]
|
Orsini L, Vanoverbeke J, Swillen I, Mergeay J, De Meester L. 2013. Drivers of population genetic differentiation in the wild: isolation by dispersal limitation, isolation by adaptation and isolation by colonization. Molecular Ecology 22:5983−99 doi: 10.1111/mec.12561
CrossRef Google Scholar
|
[262]
|
Wang IJ, Bradburd GS. 2014. Isolation by environment. Molecular Ecology 23:5649−62 doi: 10.1111/mec.12938
CrossRef Google Scholar
|
[263]
|
Xia H, Wang B, Zhao W, Pan J, Mao J, et al. 2018. Combining mitochondrial and nuclear genome analyses to dissect the effects of colonization, environment, and geography on population structure in Pinus tabuliformis. Evolutionary Applications 11:1931−45 doi: 10.1111/eva.12697
CrossRef Google Scholar
|
[264]
|
Nadeau S, Meirmans PG, Aitken SN, Ritland K, Isabel N. 2016. The challenge of separating signatures of local adaptation from those of isolation by distance and colonization history: The case of two white pines. Ecology and Evolution 6:8649−64 doi: 10.1002/ece3.2550
CrossRef Google Scholar
|
[265]
|
Yeaman S, Hodgins KA, Lotterhos KE, Suren H, Nadeau S, et al. 2016. Convergent local adaptation to climate in distantly related conifers. Science 353:1431−33 doi: 10.1126/science.aaf7812
CrossRef Google Scholar
|
[266]
|
Chen J, Li L, Milesi P, Jansson G, Berlin M, et al. 2019. Genomic data provide new insights on the demographic history and the extent of recent material transfers in Norway spruce. Evolutionary Applications 12:1539−51 doi: 10.1111/eva.12801
CrossRef Google Scholar
|
[267]
|
Eckert AJ, Wegrzyn JL, Liechty JD, Lee JM, Cumbie WP, et al. 2013. The evolutionary genetics of the genes underlying phenotypic associations for loblolly pine (Pinus taeda, Pinaceae). Genetics 195:1353−72 doi: 10.1534/genetics.113.157198
CrossRef Google Scholar
|
[268]
|
Grivet D, Avia K, Vaattovaara A, Eckert AJ, Neale DB, et al. 2017. High rate of adaptive evolution in two widespread European pines. Molecular Ecology 26:6857−70 doi: 10.1111/mec.14402
CrossRef Google Scholar
|
[269]
|
Hall D, Olsson J, Zhao W, Kroon J, Wennström U, et al. 2021. Divergent pattern between phenotypic and genetic variation in Scots pine. Plant Communications 2:100139 doi: 10.1016/j.xplc.2020.100139
CrossRef Google Scholar
|
[270]
|
Rellstab C, Zoller S, Walthert L, Lesur I, Pluess AR, et al. 2016. Signatures of local adaptation in candidate genes of oaks (Quercus spp. ) with respect to present and future climatic conditions. Molecular Ecology 25:5907−24 doi: 10.1111/mec.13889
CrossRef Google Scholar
|
[271]
|
Jia KH, Zhao W, Maier PA, Hu XG, Jin YQ, et al. 2020. Landscape genomics predicts climate change-related genetic offset for the widespread Platycladus orientalis (Cupressaceae). Evolutionary Applications 13:665−76 doi: 10.1111/eva.12891
CrossRef Google Scholar
|
[272]
|
Guo J, Wang B, Liu Z, Mao J, Wang X, et al. 2022. Low genetic diversity and population connectivity fuelvulnerability to climate change for the Tertiary relict pinePinus bungeana. Journal of Systematics and Evolution 00:1−14 doi: 10.1111/jse.12821
CrossRef Google Scholar
|
[273]
|
Hoban S, Kelley JL, Lotterhos KE, Antolin MF, Bradburd G, et al. 2016. Finding the genomic basis of local adaptation: pitfalls, practical solutions, and future directions. The American Naturalist 188:379−97 doi: 10.1086/688018
CrossRef Google Scholar
|
[274]
|
Barton N, Hermisson J, Nordborg M. 2019. Population Genetics: Why structure matters. eLife 8:e45380 doi: 10.7554/eLife.45380
CrossRef Google Scholar
|
[275]
|
Gienapp P. 2020. Is gene mapping in wild populations useful for understanding and predicting adaptation to global change. Global Change Biolology 26:2737−49 doi: 10.1111/gcb.15058
CrossRef Google Scholar
|
[276]
|
Fitzpatrick MC, Keller SR. 2015. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. Ecology Letters 18:1−16 doi: 10.1111/ele.12376
CrossRef Google Scholar
|
[277]
|
Bay RA, Harrigan RJ, Underwood VL, Gibbs HL, Smith TB, Ruegg K. 2018. Genomic signals of selection predict climate-driven population declines in a migratory bird. Science 359:83−6 doi: 10.1126/science.aan4380
CrossRef Google Scholar
|
[278]
|
Gougherty AV, Keller SR, Fitzpatrick MC. 2021. Maladaptation, migration and extirpation fuel climate change risk in a forest tree species. Nature Climate Change 11:166−71 doi: 10.1038/s41558-020-00968-6
CrossRef Google Scholar
|
[279]
|
Láruson ÁJ, Fitzpatrick MC, Keller SR, Haller BC, Lotterhos KE. 2022. Seeing the Forest for the trees: Assessing genetic offset predictions from Gradient Forest. Evolutionary Applications 15:403−16 doi: 10.1111/eva.13354
CrossRef Google Scholar
|
[280]
|
Aitken SN, Whitlock MC. 2013. Assisted gene flow to facilitate local adaptation to climate change. Annual Review of Ecology Evolution and Systematics 44:367−88 doi: 10.1146/annurev-ecolsys-110512-135747
CrossRef Google Scholar
|
[281]
|
Ruotsalainen S. 2014. Increased forest production through forest tree breeding. Scandinavian Journal of Forest Research 29:49
Google Scholar
|
[282]
|
Butler BJ, Wear DN. 2013. Forest Ownership Dynamics of Southern Forests. In The Southern Forest Futures Project: Technical Report, eds. Wear DN, Greispp JG. USA: USDA Forest Service, Southern Research Station. pp.103−22
|
[283]
|
Meuwissen T, Hayes B, Goddard M. 2016. Genomic selection: A paradigm shift in animal breeding. Animal Frontiers 6:6−14 doi: 10.2527/af.2016-0002
CrossRef Google Scholar
|
[284]
|
Isik F. 2014. Genomic selection in forest tree breeding: the concept and an outlook to the future. New Forests 45:379−401 doi: 10.1007/s11056-014-9422-z
CrossRef Google Scholar
|
[285]
|
Caballero M, Lauer E, Bennett J, Zaman S, McEvoy S, et al. 2021. Toward genomic selection in Pinus taeda: Integrating resources to support array design in a complex conifer genome. Applications in Plant Sciences 2021:e11439 doi: 10.1002/aps3.11439
CrossRef Google Scholar
|
[286]
|
Jackson C, Christie N, Reynolds SM, Marais GC, Tii-Kuzu Y, et al. 2022. A genome-wide SNP genotyping resource for tropical pine tree species. Molecular Ecology Resources 22:695−710 doi: 10.1111/1755-0998.13484
CrossRef Google Scholar
|
[287]
|
Graham N, Telfer E, Frickey T, Slavov G, Ismael A, et al. 2022. Development and validation of a 36K SNP array for radiata pine (Pinus Radiata D. Don). Forests 13:176 doi: 10.3390/f13020176
CrossRef Google Scholar
|
[288]
|
Silva-Junior OB, Faria DA, Grattapaglia D. 2015. A flexible multi-species genome-wide 60K SNP chip developed from pooled resequencing of 240 Eucalyptus tree genomes across 12 species. New Phtologist 206:1527−40 doi: 10.1111/nph.13322
CrossRef Google Scholar
|
[289]
|
Grattapaglia D, Silva-Junior OB, Resende RT, Cappa EP, Müller BSF, et al. 2018. Quantitative genetics and genomics converge to accelerate forest tree breeding. Frontiers in Plant Science 9:1693 doi: 10.3389/fpls.2018.01693
CrossRef Google Scholar
|
[290]
|
Lebedev VG, Lebedeva TN, Chernodubov AI, Shestibratov K. 2020. Genomic selection for forest tree improvement: methods, achievements and perspectives. Forests 11:1190 doi: 10.3390/f11111190
CrossRef Google Scholar
|
[291]
|
Mphahlele MM, Isik F, Mostert-O’Neill MM, Reynolds SM, Hodge GR, et al. 2020. Expected benefits of genomic selection for growth and wood quality traits in Eucalyptus grandis. Tree Genetics & Genomes 16:49 doi: 10.1007/s11295-020-01443-1
CrossRef Google Scholar
|
[292]
|
Chamberland V, Robichaud F, Perron M, Gélinas N, Bousquet J, et al. 2020. Conventional versus genomic selection for white spruce improvement: a comparison of costs and benefits of plantations on Quebec public lands. Tree Genetics & Genomes 16:17 doi: 10.1007/s11295-019-1409-7
CrossRef Google Scholar
|
[293]
|
Telfer E, Graham N, Macdonald L, Li Y, Klápště J, et al. 2019. A high-density exome capture genotype-by-sequencing panel for forestry breeding in Pinus radiata. PLoS One 14:e0222640 doi: 10.1371/journal.pone.0222640
CrossRef Google Scholar
|
[294]
|
Wegrzyn JL, Liechty JD, Stevens KA, Wu LS, Loopstra CA, et al. 2014. Unique features of the loblolly pine (Pinus taeda L.) megagenome revealed through sequence annotation. Genetics 196:891−909 doi: 10.1534/genetics.113.159996
CrossRef Google Scholar
|
[295]
|
Li X, Gunasekara C, Guo Y, Zhang H, Lei L, et al. 2014. Pop's Pipes: poplar gene expression data analysis pipelines. Tree Genetics & Genomes 10:1093−101 doi: 10.1007/s11295-014-0745-x
CrossRef Google Scholar
|
[296]
|
Chen T, He HL, Church GM. 1999. Modeling gene expression with differential equations. Pacific Symposium on Biocomputing 1999:29−40 doi: 10.1007/s11295-019-1409-7
CrossRef Google Scholar
|
[297]
|
Ruklisa D, Brazma A, Viksna J. 2005. Reconstruction of gene regulatory networks under the finite state linear model. Genome Information 16:225−36 doi: 10.1371/journal.pone.0222640
CrossRef Google Scholar
|
[298]
|
Dojer N, Gambin A, Mizera A, Wilczyński B, Tiuryn J. 2006. Applying dynamic Bayesian networks to perturbed gene expression data. BMC Bioinformatics 7:249 doi: 10.1186/1471-2105-7-249
CrossRef Google Scholar
|
[299]
|
Louis M, Becskei A. 2002. Binary and graded responses in gene networks. Science's STKE 43:PE33 doi: 10.1126/stke.2002.143.pe33
CrossRef Google Scholar
|
[300]
|
Kauffman S. 1969. Homeostasis and differentiation in random genetic control networks. Nature 224:177−78 doi: 10.1038/224177a0
CrossRef Google Scholar
|
[301]
|
Chen BS, Chang CH, Wang YC, Wu CH, Lee HC. 2011. Robust model matching design methodology for a stochastic synthetic gene network. Mathematical Biosciences 230:23−36 doi: 10.1016/j.mbs.2010.12.007
CrossRef Google Scholar
|
[302]
|
Schäfer J, Strimmer K. 2005. An empirical Bayes approach to inferring large-scale gene association networks. Bioinformatics 21:754−64 doi: 10.1093/bioinformatics/bti062
CrossRef Google Scholar
|
[303]
|
Butte AJ, Kohane IS. 2000. Mutual information relevance networks: Functional genomic clustering using pairwise entropy measurements. Proceedings of Pacific Symposium on Biocomputing 5:418−29 doi: 10.1142/9789814447331_0040
CrossRef Google Scholar
|
[304]
|
Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, et al. 2006. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 7:S7 doi: 10.1186/1471-2105-7-S1-S7
CrossRef Google Scholar
|
[305]
|
Faith JJ, Hayete B, Thaden JT, Mogno I, Wierzbowski J, et al. 2007. Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biology 5:e0050008 doi: 10.1371/journal.pbio.0050008
CrossRef Google Scholar
|
[306]
|
Altay G, Emmert-Streib F. 2010. Inferring the conservative causal core of gene regulatory networks. BMC Systems Biology 4:132 doi: 10.1186/1752-0509-4-132
CrossRef Google Scholar
|
[307]
|
Luo W, Hankenson KD, Woolf PJ. 2008. Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual information. BMC Bioinformatics 9:467 doi: 10.1186/1471-2105-9-467
CrossRef Google Scholar
|
[308]
|
Lin YC, Li W, Sun YH, Kumari S, Wei H, et al. 2013. SND1 transcription factor-directed quantitative functional hierarchical genetic regulatory network in wood formation in Populus trichocarpa. The Plant Cell 25:4324−41 doi: 10.1105/tpc.113.117697
CrossRef Google Scholar
|
[309]
|
Wei M, Liu Q, Wang Z, Yang J, Li W, et al. 2020. PuHox52-mediated hierarchical multilayered gene regulatory network promotes adventitious root formation in Populus ussuriensis. New Phytologist 228:1369−85 doi: 10.1111/nph.16778
CrossRef Google Scholar
|
[310]
|
Wu W, Li J, Wang Q, Lv K, Du K, et al. 2021. Growth-regulating factor 5 (GRF5)-mediated gene regulatory network promotes leaf growth and expansion in poplar. New Phytologist 230:612−28 doi: 10.1111/nph.17179
CrossRef Google Scholar
|
[311]
|
Lu S, Li Q, Wei H, Chang MJ, Tunlaya-Anukit S, et al. 2013. Ptr-miR397a is a negative regulator of laccase genes affecting lignin content in Populus trichocarpa. Proceedings of the National Academy of Sciences The United States of America 110:10848−53 doi: 10.1073/pnas.1308936110
CrossRef Google Scholar
|
[312]
|
Lv K, Wu W, Wei H, Liu G. 2021. A systems biology approach identifies a regulator, BplERF1, of cold tolerance in Betula platyphylla. Forestry Research 1:11 doi: 10.48130/FR-2021-0011
CrossRef Google Scholar
|
[313]
|
Kumari S, Deng W, Gunasekara C, Chiang V, Chen HS, et al. 2016. Bottom-up GGM algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways or processes. BMC Bioinformatics 17:132 doi: 10.1186/s12859-016-0981-1
CrossRef Google Scholar
|
[314]
|
Deng W, Zhang K, Busov V, Wei H. 2017. Recursive random forest algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways. PloS ONE 12:e0171532 doi: 10.1371/journal.pone.0171532
CrossRef Google Scholar
|
[315]
|
Wei H. 2019. Construction of a hierarchical gene regulatory network centered around a transcription factor. Briefings in Bioinformatics 20:1021−31 doi: 10.1093/bib/bbx152
CrossRef Google Scholar
|
[316]
|
Nie J, Stewart R, Zhang H, Thomson JA, Ruan F, et al. 2011. TF-Cluster: a pipeline for identifying functionally coordinated transcription factors via network decomposition of the shared coexpression connectivity matrix (SCCM). BMC Systems Biology 5:53 doi: 10.1186/1752-0509-5-53
CrossRef Google Scholar
|
[317]
|
Ji X, Chen S, Li J, Deng W, Wei Z, et al. 2017. SSGA and MSGA: two seed-growing algorithms for constructing collaborative subnetworks. Scientific Reports 7:1446 doi: 10.1038/s41598-017-01556-z
CrossRef Google Scholar
|
[318]
|
Deng W. 2018. Algorithms for reconstruction of gene regulatory networks from high -throughput gene expression data. Thesis. Michigan Technological University, USA. 101 pp.
|