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Genome-wide identification and comparative analysis of drought related genes in roots of two maize inbred lines with contrasting drought tolerance by RNA sequencing
HAO Lu-yang, LIU Xu-yang, ZHANG Xiao-jing, SUN Bao-cheng, LIU Cheng, ZHANG Deng-feng, TANG Huai-jun, LI Chun-hui, LI Yong-xiang, SHI Yun-su, XIE Xiao-qing, SONG Yan-chun, WANG Tian-yu, LI Yu
2020, 19 (2): 449-464.   DOI: 10.1016/S2095-3119(19)62660-2
Abstract174)      PDF in ScienceDirect      
Drought is one of the most important abiotic stresses affecting maize growth and development and therefore resulting in yield loss.  Thus it is essential to understand molecular mechanisms of drought stress responses in maize for drought tolerance improvement.  The root plays a critical role in plants sensing water deficit.  In the present study, two maize inbred lines, H082183, a drought-tolerant line, and Lv28, a drought-sensitive line, were grown in the field and treated with different water conditions (moderate drought, severe drought, and well-watered conditions) during vegetative stage.  The transcriptomes of their roots were investigated by RNA sequencing.  There were 1 428 and 512 drought-responsive genes (DRGs) in Lv28, 688 and 3 363 DRGs in H082183 under moderate drought and severe drought, respectively.  A total of 31 Gene Ontology (GO) terms were significantly over-represented in the two lines, 13 of which were enriched only in the DRGs of H082183.  Based on results of Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, “plant hormone signal transduction” and “starch and sucrose metabolism” were enriched in both of the two lines, while “phenylpropanoid biosynthesis” was only enriched in H082183.  Further analysis revealed the different expression patterns of genes related to abscisic acid (ABA) signal pathway, trehalose biosynthesis, reactive oxygen scavenging, and transcription factors might contribute to drought tolerance in maize.  Our results contribute to illustrating drought-responsive molecular mechanisms and providing gene resources for maize drought improvement.
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Simple nonlinear model for the relationship between maize yield and cumulative water amount
LIU Cheng SUN Bao-cheng, TANG Huai-jun, WANG Tian-yu LI Yu, ZHANG Deng-feng, XIE Xiao-qing, SHI Yun-su, SONG Yan-chun, YANG Xiao-hong, LI Jian-sheng
2017, 16 (04): 858-866.   DOI: 10.1016/S2095-3119(16)61493-4
Abstract794)      PDF in ScienceDirect      
Both the additive and multiplicative models of crop yield and water supply are polynomial equations, and the number of parameters increases linearly when the growing period is specified.  However, interactions among multiple parameters occasionally lead to unreasonable estimations of certain parameters, which were water sensitivity coefficients but with negative value.  Additionally, evapotranspiration must be measured as a model input.  To facilitate the application of these models and overcome the aforementioned shortcomings, a simple model with only three parameters was derived in this paper based on certain general quantitative relations of crop yield (Y) and water supply (W).  The new model, Y/YmWk/(Wk+whk), fits an S or a saturated curve of crop yield with the cumulative amount of water.  Three parameters are related to biological factors: the yield potential (Ym), the water requirement to achieve half of the yield potential (half-yield water requirement, wh), and the water sensitivity coefficient (k).  The model was validated with data from 24 maize lines obtained in the present study and 17 maize hybrids published by other authors.  The results showed that the model was well fit to the data, and the normal root of the mean square error (NRMSE) values were 2.8 to 17.8% (average 7.2%) for the 24 maize lines and 2.7 to 12.7% (average 7.4%) for the 17 maize varieties.  According to the present model, the maize water-sensitive stages in descending order were pollen shedding and silking, tasselling, jointing, initial grain ?lling, germination, middle grain ?lling, late grain ?lling, and end of grain ?lling.  This sequence was consistent with actual observations in the maize field.  The present model may be easily used to analyse the water use efficiency and drought tolerance of maize at specific stages.
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