| Trees have shaped many terrestrial ecosystems,providing important sustainable resources for diverse industries worldwide.Tree growth is an integrative dynamic process exhibiting in continuous growth of height and circumference.The process involves the activities of the shoot apical meristem and vascular cambium.Tree growth is a result of cell expansion and division in the apical and cambial meristems,which reflects the cumulative effects of the relevant genes through a long period of time.However,plant growth rate varies through the growing process,and the growth rhythm is affected by many biological and ambient factors,such as water utilization,nutrient absorption,phenology,photosynthesis,and biotic/abiotic stresses,etc.This study presents an applicable strategy for elucidating the genetic mechanism underlying a long-term biological process by using plant growth as an example.The main results in this study were as follows:(1)With the sequenced individual as maternal parent,we build a large F1 full-sib mapping population of S.suchowensis.The field trial includes 338 randomly selected progenies from the mapping population.Each progeny was repeated with nine clonal ramets,resulting a total of3,342 plants in field test.We measured the plant growth 14 times during the growing process,resulting in a total of 105 time spans covering the different measurements.Plotting the phenotypic data of stem height(SH)and ground diameter(GD)derived “S-shaped curves”,and the growth rhythm showed a dynamic pattern of “slow-fast-slow”.Statistics on growth rates in continuous time spans showed that turning point “from slow to fast” in SH growth appeared at T1(Apr.14,2018),while turning point “from fast to slow” in SH growth appeared at T7(Jul.13,2018).As for GD,the corresponding turning points appeared at T1 and T9(Aug.12,2018).The Pearson's correlation revealed significantly positive correlations between SH and GD through the growing process.It also showed that the pair-wise correlation for SH and GD gradually decreased with the development of plants,suggesting the early-fast growing plants would slow down at the late developmental stages,and/or the early-slow growing plants might catch up with the development of plants.Therefore,growth rhythm varied among the examined progeny during the growing process.(2)We mapped QTLs controlling SH and GD growth in the 105 time spans.For SH,two“consistent QTLs”(qtl-4-1 and qtl-4-2)and three “temporary QTLs”(qtl-4-3,qtl-10,and qtl-15)were detected.For GD,two “consistent QTLs”(qtl-4-1 and qtl-4-2)and four“temporary QTLs”(qtl-4-3,qtl-8,qtl-13,and qtl-14)were detected.The time-sequential QTL analyses showed that effects of the detected QTLs varied across the growing process.The two consistent QTLs qtl-4-1,qtl-4-2,together with the temporary QTL qtl-4-3,were found to have a pleiotropic effect on SH and GD,and exhibited similar functional pattern on SH and GD.Confidence intervals of the two consistent QTLs were positioned at two discrete regions on LG IV,with qtl-4-1 spans from 10.3 c M to 27.6 c M,and qtl-4-2 spans from 32.9 c M to 51.9 c M.(3)We reported a chromosome-scale assembly of S.suchowensis generated by combining Pac Bio sequencing with Hi-C technologies.The obtained genome assemblies covered a total length of 356?Mb,with 36,937 putative protein-encoding genes.By applying Hi-C data,339.67?Mb(95.29%)of the assembled sequences were allocated to the 19 chromosomes of haploid willow.The pseudo-molecule of chromosome IV covers 17.42 Mb and consists of 1,769 genes.Aligning the flanking SSR markers of the two QTLs to S.suchowensis genome sequence located qtl-4-1 to a 3.3 Mb physical interval with 307 genes and two mi RNAs(novel_mi R856 a and novel_mi R166c),and qtl-4-2 to a 2.9 Mb physical interval with 240 genes and two mi RNAs(novel_mi R6151 a and novel_mi R6151b),separately.(4)The time-sequential transcriptome sequences were mapped to the S.suchowensis reference genome to obtain the m RNA expression levels.Subsequently,the gene expression patterns were built with transcriptomic data of leaf and cambium tissues by using the weighted gene correlation network analysis(WGCNA).WGCNA identified 24 co-expressed module eigengenes(MEs)separately with leaf and cambium transcriptomic data.Based on correlation between the derived MEs of leaf tissue and growth rates of SH and GD at significance P < 0.05,we identified significantly correlated MEs.As for the derived MEs of leaf tissue,LME8(contains1,410 unigenes)was found to significantly correlate with growth rates of SH;whereas three MEs,LME3(contains 159 unigenes),LME6(contains 1,532 unigenes),and LME12(contains 805unigenes),were found to significantly correlate with growth rates of GD through the growing process.As for the derived MEs of cambium tissue,CME4(contains 652 unigenes),CME14(contains 1,076 unigenes),CME19(contains 1,496 unigenes)and CME22(contains 108unigenes)were found to significantly correlate with growth rates of SH;whereas CME2(contains 1,817 unigenes)and CME8(contains 785 unigenes)were found to significantly correlate with growth rates of GD through the growing process.(5)Combined with the target genomic interval,a total of 113 genes in the candidate MEs significantly correlated with growth rates of SH and GD were located in physical intervals of qtl-4-1 and qtl-4-2.Specifically,examination of gene distribution detected 14,7,5,10,7,1,8,10,and 13 unigenes in LME8,LME3,LME6,LME12,CME4,CME14,CME19,CME2 and CME8 located in the physical interval of qtl-4-1,respectively;and there are 22,5,4,7,5,2,1,4,and 10 unigenes in LME8,LME3,LME12,CME4,CME14,CME19,CME22,CME2 and CME8 located in the physical interval of qtl-4-2,respectively.To further narrow down the candidate genes in the confidence interval of the two consistent QTLs,we compared the correlation between growth rate and gene expression level between the contrasting genotypes.Comparing genes expression level between the contrasting genotypes revealed expression pattern of EVM0017394,EVM0039247,EVM0001136 and EVM0021205,which were all from the leaf transcriptome,matched the growth rhythm of SH between the contrasting genotypes.There were four genes(EVM0002073 from leaf transcriptome,EVM0016825,EVM0001027 and EVM0005286 from cambium transcriptome)with expression pattern matching the growth rhythm of GD between the contrasting genotypes.Therefore,our findings suggest that height growth involves the activities of leaf tissue,and no evidence of cambium activity contributing to height growth was observed;whereas growth of circumference mainly related to the activities of vascular cambium,and activities of leaf tissue also contributes to circumference growth.Further functional examination of the eight candidate major genes showed that they mainly involved in plant growth and developmental process,such as phytohormone signaling transport,transcription factors,and various enzymes participating in primary and secondary growth processes.(6)Mi RNAs play significant role in regulating development of plants.In this paper,we performed time-sequential small RNA sequencing to predict the conserved and novel mi RNAs contained in S.suchowensis,and calculated the mi RNA expression of leaves and cambium tissues in the two contrasting genotypes during the growing process.With reference to the technical route of identifying candidate genes related to growth rhythm traits from the time-sequential transcriptomes,we planned to discover candidated mi RNAs involved in the growth and development of forest trees.However,this study showed no evidence that the major effect QTLs underlying growth performance of S.suchowensis associate with regulation of mi RNAs.In this study,we performed a time-sequential study to uncover the genetic factors underlying the dynamic growth of a woody plant,which provides unprecedented information to help us to understand the dynamic growth of plants.Moreover,we presented an applicable strategy for dissecting genetic factors underlying long-term biological process. |
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