References
  1. Li, N; Liu, H.; Sun, J.; Zheng, H.; Wang, J.; Yang, L.; Zhao, H.; Zou, D. Transcriptome analysis of two contrasting rice cultivars during alkaline stress. Sci. Rep. 2018 , 8, 9586. https://doi.org/10.1038/s41598-018-27940-x.
  2. Filippi, P.; Jones, E.J.; Ginns, B.J.; Whelan, B.M.; Roth, G.W.; Bishop, T.F.A. Mapping the depth-to-soil pH constraint, and the relationship with cotton and grain yield at the within-field scale. Agronomy 2019 , 9, 251. https://doi.org/10.3390/agronomy9050251.
  3. Loeppert, R.H.; Suarez, D.L. Carbonate and gypsum. In Methods of Soil Analysis. Part 3 Chemical Methods, 5.3 , Sparks, D.L.; Page, A.L.; Helmke, P.A.; Loeppert, R.H.; Soltanpour, P. N.; Tabatabai, M. A.; Johnston, C. T.; Sumner, M.E., Eds.; Publisher: Soil Science Society of America and American Society of Agronomy, Madison, USA,1996 ; chapter 15, pp. 437-474, ISBN 978-089-118-825-4.
  4. Al-Busaidi, A.; Cookson, P. Salinity – pH relationships in calcareous soils of Oman. J. Sci Res. Agric. Marine Sci. 2003 , 8, 41 - 46.
  5. Terés, J.; Busoms, S.; Perez Martín, L.; Luís‐Villarroya, A.; Flis, P.; Álvarez‐Fernández, A.; Tolrà, R.; Salt, D.E.; Poschenrieder, C. Soil carbonate drives local adaptation in Arabidopsis thaliana . Plant Cell Environ. 2019 , 42, 2384–98. https://doi.org/10.1111/pce.13567.
  6. Hui, X.; Luo, L.; Wang, S.; Cao, H.; Huang, M.; Shi, M.; Malhi, S.S.; Wang, Z. Critical concentration of available soil phosphorus for grain yield and zinc nutrition of winter wheat in a zinc-deficient calcareous soil. Plant Soil 2019 , 444, 315-330, https://doi.org/10.1007/s11104-019-04273-w.
  7. Dreyer, M.; Wichmann, M.; Rischen, M.; Gorlach, B.M.; Ehmke, A.; Pitmann, B.; Mühling, K.H. Ammonium-driven nitrification plays a key role in increasing Mn availability in calcareous soils. J. Plant Nutr. Soil Sci. 2020 , 183, 389-396, https://doi.org/10.1002/jpln.201900131.
  8. Felle, H.H. pH: signal and messenger in plant cells. Plant Biol.2001 , 3, 577-591. https://doi.org/10.1055/s-2001-19372
  9. Lee, J.A.; Woolhouse, H.W. Root growth and dark fixation of carbon dioxide in calcicoles and calcifuges. New Phytol. 1969 , 68, 247-255, https://doi.org/10.1111/j.1469-8137.1969.tb06437.x.
  10. Sagervanshi, A.; Naeem, A.; Kaiser,H.; Pitann, B.; Mühling, K.H. Early growth reduction in Vicia faba L. under alkali salt stress is mainly caused by excess bicarbonate and related to citrate and malate over accumulation. Environ. Exp. Bot. 2021 , 192, 104636, https://doi.org/10.1016/j.envexpbot.2021.104636.
  11. Parvaiz, A.; Ozturk, M.; Sharma, S.; Gucel. S. Effect of sodium carbonate-induced salinity-alkalinity on some key osmoprotectants, protein profile, antioxidant enzymes, and lipid peroxidation in two mulberry (Morus alba L.) cultivars. J. Plant Interact.2014 , 9, 460–67, https://doi.org/10.1080/17429145.2013.855271.
  12. Sarkar, B.; Hasanuzzaman, M.; Adak, M.K. Insights into the role of iron supplementation in conferring bicarbonate-mediated alkaline stress tolerance in maize. J. Soil Sci. Plant Nutr. 2022 , 22, 2719-2734, https://doi.org/10.1007/s42729-022-00839-3.
  13. Zou, C.L.; Wang, Y.B.; Wang, B.; Liu, D.; Liu, L.; Li, C.F. Effects of alkali stress on dry matter accumulation, root morphology, ion balance, free polyamines, and organic acids of sugar beet. Acta Physiol. Plant. 2021 , 43, 13,
  14. Cao, Y.; Song, H. and Zhang, L., 2022. New Insight into Plant Saline-Alkali Tolerance Mechanisms and Application to Breeding. IJMS, 2022 , 23, 16048. https://doi.org/10.3390/ijms232416048
  15. Zhang, H..; Liu, X-L.; Zhang, R-X.; Yuan, H-Y.; Wang, M-M.; Yang, H-Y.; Ma, H-Y.; Liu, D.; Jiang, C.J.; Liang, Z-W. Root Damage under Alkaline Stress Is Associated with Reactive Oxygen Species Accumulation in Rice (Oryza sativa L.). Front. Plant Sci.2017 , 8, 1–12, https://doi.org/10.3389/fpls.2017.01580.
  16. Waters, B.M.; Amundsen, K.; Graef, G. Gene expression profiling of iron deficiency chlorosis sensitive and tolerant soybean indicates key roles for phenylpropanoids under alkalinity stress. Front. Plant Sci.2018 , 9, 10, https://doi.org/10.3389/fpls.2018.00010..
  17. Duan, X.; Yu, Y.; Duanmu, H.; Chen, C.; Sun, X.; Cao, L.; Li, Q.; Ding, X.; Liu, B.; Zhu, Y. GsSLAH3, a Glycine soja slow type anion channel homolog, positively modulates plant bicarbonate stress tolerance. Physiol. Plant. 2018 , 164, 145-162, https://doi.org/10.1111/ppl.12683.
  18. Mehari TG, Xu Y, Umer MJ, Shiraku ML, Hou Y, Wang Y, Yu S, Zhang X, Wang K, Cai X, Zhou Z, Liu F. Multi-omics-based identification and functional characterization of GhA06G1257 proves its potential role in drought stress tolerance in Gossypium hirsutum. Front. Plant Sci. 2021 ,12, 746771, https:/doi.org/10.3389/fpls.2021.746771.
  19. Li, Z.; Xu, Y. Bulk segregation analysis in the NGS era: a review of its teenage years. Plant J.  2022 , 109, 1355-1374, .
  20. Busoms, S. Terés, J.; Huang, X-Y.; Bomlies, K.; Danku, J.; Douglas, A.; Weigel, D.; Poschenrieder, C.; Salt, D.E. Salinity is an agent of divergent selection driving local adaptation of Arabidopsis to coastal habitats. Plant Physiol. 2015 , 168, 915-929. https://doi.org/10.1104/pp.15.00427
  21. Scholl, R.L.; May, S.T.; Ware, D.H. Seed and molecular resources for Arabidopsis. Plant Physiol. 2000 , 124, 1477-1480. https://doi.org/10.1104/pp.124.4.1477.
  22. Schneider, C.A. Rasband, W.S.; Eliceiri, K.W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 2012, 9, 671-5. https://doi.org/10.1038/nmeth.2089.
  23. Joshi N.A.; Fass JN. Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files (Version 1.33) [Software].2011. Available at https://github.com/najoshi/sickle.
  24. McKenna, A., et al.; DePristo, M.A., 2010. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome research, 2010 , 20, 1297-1303. doi: 10.1101/gr.107524.110.
  25. Wilm, A.; Aw, P.P.K.; Bertrand, D.; Yeo, G.H.T.; Ong, S.H.; Wong, C.H.; Khor, C.C.; Petric, R.; Hibberd, M.L.; Nagarajan, N. LoFreq: a sequence-quality aware, ultra-sensitive variant caller for uncovering cell-population heterogeneity from high-throughput sequencing datasets. Nucleic acids research, 2012 , 40, 11189-11201. https://doi.org/10.1093/nar/gks918.
  26. Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics, 2011 , 27, 2987-2993. https://doi.org/10.1093/bioinformatics/btr509
  27. Edwards, M.D.; Gifford, D.K. High-resolution genetic mapping with pooled sequencing. BMC Bioinform. 2012 , 13 (Suppl 6), S8. https://doi.org/10.1186/1471-2105-13-S6-S8.
  28. Busoms, S.; Paajanen, P.; Marburger, S.; Bray, S.; Huang, X.Y.; Poschenrieder, C.; Yant; Salt, D.E. Fluctuating selection on migrant adaptive sodium transporter alleles in coastal Arabidopsis thaliana . PNAS, 2018 , 115, E12443-E12452. https://doi.org/10.1073/pnas.1816964115
  29. Danecek, P., et al.; McVean, G. 1000 Genomes Project Analysis Group. 2011. The variant call format and VCFtools . Bioinformatics, 2011 , 27 , 2156-2158. https://doi.org/10.1093/bioinformatics/btr330.
  30. Cingolani, P. Variant Annotation and Functional Prediction: SnpEff. In: Ng, C., Piscuoglio, S. (eds) Variant Calling. Methods in Molecular Biology, 2022 , vol. 2493. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2293-3_19.
  31. Benjamini, Y.; Yekutieli, D. 2001, The control of the false discovery rate in multiple testing under dependency. Ann. Stat. 2001 , 29, 1165-1188. https://doi.org/10.1214/aos/1013699998.
  32. Tian, T.; Liu, Y.; Yan, H.; You, Q.; Yi, X.; Du, Z.; Xu, W.; Su, Z. agriGOv2.0: a GO analysis for the agricultural community, 2017 update. Nucleic Acids Res. 2017 , 45, W122-W129. https://doi.org/10.1093/nar/gkx382.
  33. Thanati, F.; Karatzas, E.; Baltoumas, F.; Stravopodis, D.J.; Eliopoulos, A.; Pavolpoulos, G. FLAME: a web tool for functional and literature enrichment analysis of multiple gene lists. Biol. (Basel)2021 , 10:665. https://doi.org/10.3390/biology10070665.
  34. Szklarczyk, D.; Gable, A.L.; Lyon, D.; Junge, A.; Wyder, S.; Huerta-Cepas, J.; Simonovic, M.; Doncheva, N.T.; Morris, H.; Bork, P.; Jensen, L.J.; von Mering, C. String v11: protein-protein association networks with increased coverage, supporting functional discovery in genome –wide experimental datasets. Nucleic Acids Res. 2019 , 47, D607-D613. https://doi.org/10.1093/nar/gky1131.
  35. Castilla, A.R.; Méndez-Vigo, B.; Marcer, A.; Martínez-Minaya, J.; Conessa, D.; Picó, F.X.; Alonso-Blanco, C. Ecological, genetic and evolutionary drivers of regional genetic differentiation inArabidopsis thaliana. BMC Evol. Biol. 2020 , 20, 71, https://doi.org/10.1186/s12862-020-01635-2
  36. Pérez‑Martín, L.; Busoms, S.; Almira, M.J.; Azagury, N.; Terés, J.; Tolrà, R.; Poschenrieder, C.; Barceló, J. Evolution of salt tolerance in Arabidopsis thaliana on siliceous soils does not confer tolerance to saline calcareous soils. Plant Soil 2022 , 476, 455–475, https://doi.org/10.1007/s11104-022-05439-9
  37. Busoms, S.; Terés, J.; Yant, L.; Poschenrieder, C.; Salt, D.E. Adaptation to coastal soils through pleiotropic boosting of ion and stress hormone concentrations in wild Arabidopsis thaliana . New Phytol. 2021 , 232, 208-220, https://doi.org/10.1111/nph.17569
  38. Pérez-Martín, L.; Busoms, S.; Tolrà, R.; Poschenrieder, C. Transcriptomics reveals fast changes in salicylate and jasmonate signaling pathways in shoots of carbonate-tolerant Arabidopsis thaliana under bicarbonate exposure. Int. J. Mol. Sci.,2021 , 22, 1226.
  39. Li, Q.; Yang, A.; Zhang, W-H. Efficient acquisition of iron confers greater tolerance to saline-alkaline stress in rice (Oryza sativa L.). J. Exp. Bot. 2016 ,67, 6431–6444. https://doi.org/10.1093/jxb/erw407
  40. Sivitz, A.B.: Hermand, V.; Curie, C.; Vert, G. Arabidopsis bHLH100 and bHLH101 control iron homeostasis via a FIT-independent pathway. PLoS One. 2012 , 7, e44843. https://doi.org/10.1371/journal.pone.0044843
  41. Kiba, T.; Kudo, T.; Kojima, M.; Sakakibara, H. Hormonal control of nitrogen acquisition: roles of auxin, abscisic acid, and cytokinin. J. Exp. Bot. 2011 , 62, 1399-1409. https://doi.org/10.1093/jxb/erq410
  42. Xia, A.; Wu, Y. Joint interactions of carbon and nitrogen metabolism dominated by bicarbonate and nitrogen in Orychophragmus violaceus and Brassica napus under simulated karst habitats. BMC Plant Biol. 2022 , 22, 1-13. https://doi.org/10.1186/s12870-022-03646-1
  43. Salomé, P.A.; Bomblies, K.; Fitz, J.; Laitinen, R.A.E.; Warthmann, N.; Yant, L.; Weigel, D. The recombination landscape in Arabidopsis thaliana F2 populations. Heredity, 2012 , 108, 447-455. https://doi.org/10.1038/hdy.2011.95
  44. Benowicz, A.; Stoehr, M.; Hamann, A.; Yanchuk, A.D. Estimation of the F2 generation segregation variance and relationships among growth, frost damage, and bud break in coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) wide-crosses. Annals of Forest Science, 2020 , 77, 1-13. https://doi.org/10.1007/s13595-020-0925-9
  45. Bartlett, M.E.; Whipple, C.J. Protein change in plant evolution: tracing one thread connecting molecular and phenotypic diversity. Front. Plant Sci., 2013 , 4, 382, https://doi.org/10.3389/fpls.2013.00382
  46. Castilla, A.R.; Méndez-Vigo, B.; Marcer, A.; Martínez-Minaya, J.; Conessa, D.; Picó, F.X.; Alonso-Blanco, C. Ecological, genetic and evolutionary drivers of regional genetic differentiation inArabidopsis thaliana. BMC Evol. Biol. 2020 , 20, 71, https://doi.org/10.1186/s12862-020-01635-2
  47. Monroe, J.G., Srikant, T., Carbonell-Bejerano, P. et al.  Mutation bias reflects natural selection in Arabidopsis thaliana . Nature, 2022 , 602, 101–105. https://doi.org/10.1038/s41586-021-04269-6
  48. Ye, S.; Yan, L.; Ma, X.; Chen, Y.; Wu, L.; Ma, T.; Zhao, L.; Yi, B.; Ma, C.; Tu, J.; Shen, J. Combined BSA-Seq based mapping and RNA-Seq profiling reveal candidate genes associated with plant architecture inBrassica napus . Int. J. Mol. Sci.  2022 , 23, 2472. https://doi.org/10.3390/ijms23052472
  49. Derakhshani, B.; Ayalew, H.; Mishina, K.; Tanaka, T.; Kawahara, Y.; Jafary, H.; Oono, Y. Comparative analysis of root transcriptome reveals candidate genes and expression divergence of homoeologous genes in response to water stress in wheat. Plants,2020 , 9596. https://doi.org/10.3390/plants9050596
  50. Guo, Z.; Cai, L.; Chen, Z.; Wang, R.; Zhang, L.; Guan, S.; Zhang, S.; Ma, W.; Liu, C.; Pan, G. Identification of candidate genes controlling chilling tolerance of rice in the cold region at the booting stage by BSA-Seq and RNA-Seq.  R. Soc. Open Sci., 2020 , 7.201081. http://dx.doi.org/10.1098/rsos.201081
  51. Bernal, A.J.; Yoo, C-M.; Mutwil, M.; Jensen, J. K.; Hou, G.; Blaukopf, C.; Sorensen, I.; Blancaflor, E. B.; Scheller, H. V.; Willats, W.G.T. Functional analysis of the cellulose synthase-like genes CSLD1, CSLD2, and CSLD4 in tip-growing Arabidopsis cells. Plant Physiol.2008 , 148, 1238–1253. https://doi.org/10.1104/pp.108.121939
  52. Yin, L.; Verhertbruggen, Y.; Oikawa, A.; Manisseri, C.; Knierim, B.; Prak, L.; Krüger Jensen, J.; Knox, J.P.; Auer, M.; Willats, W.G.T.; Scheller, H.V. The cooperative activities of CSLD2, CSLD3, and CSLD5 are required for normal Arabidopsis development. Mol. Plant2011 , 4, 1024-1037. https://doi.org/10.1093/mp/ssr02
  53. Lee, K.; Lehmann, M.; Paul, M.V; Wang, L.; Luckner, M.; Wanner, G.; Geigenberger, P.; Leister, D.; Kleine, T. Lack of FIBRILLIN6 inArabidopsis thaliana affects light acclimation and sulfate metabolism. New Phytol. 2020 , 225, 1715-1731. https://doi.org/10.1111/nph.16246
  54. Hayashi, K.; Arai, K.; Tanaka, Y.; Hira, H.; Guo, R.; Hu, Y.; Ge, C.; Zhao, Y.; Kasahara, H.; Fukui, K. The main oxidative inactivation pathway of the plant hormone auxin. Nat. Commun. 2021 , 12, 6752, https://doi.org/10.1038/s41467-021-27020-1
  55. Lakehal, A.; Dob, A.; Novák, O.; Bellini, C. A DAO1-mediated circuit controls auxin and jasmonate crosstalk robustness during adventitious root initiation in Arabidopsis. Int. J. Mol. Sci. 2019 , 20, 4428, https://doi.org/10.3390/ijms20184428
  56. Werner, A.K.; Sparkes, I.A.; Witte, C-P. Identification, biochemical characterization, and subcellular localization of allantoate amidohydrolasr¡es from Arbidopsis and soybean. Plant Physiol.2008 , 146, 418-430 https://doi.org/10.1104/pp.107.110809
  57. Lescano, C.I.; Martini, C.; González, C.A.; Desimone, Allantoin accumulation by allantoinase downregulation and transport by ureide permease 5 confers salt stress tolerance to Arabidopsis plants. Plant Mol. Biol. 2016 , 91, 581-595, https://doi.org/10.1007/s11103-016-0490-7
  58. Chung, H.S.; Howe, G.A. A critical role for the TIFY motif in repression of jasmonate signaling by a stabilized splice variant of the JASMONATE ZIM-domain protein JAZ10 in Arabidopsis. Plant Cell,2009 , 21, 131-145. https://doi.org/10.1105/tpc.108.064097
  59. Sun, Q.; Wang, G.; Zhang, X.; Zhang, X.; Qiao, P.; Long, L.; Yuan, Y. and Cai, Y., 2017. Genome-wide identification of the TIFY gene family in three cultivated Gossypium species and the expression of JAZ genes.  Sci. Rep.  2017 , 7, 1-9. https://doi.org/10.1038/srep42418
  60. Lei, G.J.; Zhu, X.F.; Wang, Z.W.; Dong, F.; Dong, N.Y.; Zheng, S.J. Abscisic acid alleviates iron deficiency by promoting root iron reutilization and transport from root to shoot in Arabidopsis. Plan Cell Environ. 2014 , 37, 852-863. https://doi.org/10.1111/pce.12203
  61. Ruan, Y.L.; Jin, Y.; Yang, Y.J.; Li, G.J.; Boyer, J.S. Sugar input, metabolism, and signaling mediated by invertase: roles in development, yield potential, and response to drought and heat. Mol. Plant,2010 , 3, 942-955. https://doi.org/10.1093/mp/ssq044