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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Plant Sci.</journal-id>
<journal-title>Frontiers in Plant Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Plant Sci.</abbrev-journal-title>
<issn pub-type="epub">1664-462X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpls.2025.1629615</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Plant Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Association mapping and candidate gene identification for drought tolerance in sorghum</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Min</surname>
<given-names>Huiting</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3068111/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Kang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Tiantian</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cheng</surname>
<given-names>Xinxiu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Habyarimana</surname>
<given-names>Ephrem</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Yongfei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hu</surname>
<given-names>Die</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Yi-Hong</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/106520/overview"/>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Lihua</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
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<aff id="aff1">
<sup>1</sup>
<institution>College of Agriculture, Anhui Science and Technology University</institution>, <addr-line>Chuzhou, Anhui</addr-line>,&#xa0;<country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>International Joint Research Center of Forage Bio-Breeding in Anhui Province</institution>, <addr-line>Chuzhou</addr-line>,&#xa0;<country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>The&#xa0;International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)</institution>, <addr-line>Hyderabad, Telangana</addr-line>,&#xa0;<country>India</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Biology, University of Louisiana at Lafayette</institution>, <addr-line>Lafayette, LA</addr-line>,&#xa0;<country>United States</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Guoquan Liu, The University of Queensland, Australia</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Sofie Pearson, The University of Queensland, Australia</p>
<p>Yongfu Tao, Chinese Academy of Agricultural Sciences, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Yi-Hong Wang, <email xlink:href="mailto:yihong.wang@louisiana.edu">yihong.wang@louisiana.edu</email>; Lihua Wang, <email xlink:href="mailto:wanglihuaerr@126.com">wanglihuaerr@126.com</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>25</day>
<month>07</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1629615</elocation-id>
<history>
<date date-type="received">
<day>22</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>06</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Min, Wang, Wang, Cheng, Habyarimana, Wang, Hu, Wang and Wang</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Min, Wang, Wang, Cheng, Habyarimana, Wang, Hu, Wang and Wang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Water is essential for plant growth, and drought is one of the most predominant constraints on crop yield. Sorghum is a well-known drought-tolerant crop model, and sorghum landraces possess novel alleles for local adaptation.</p>
</sec>
<sec>
<title>Methods</title>
<p>In this study, we evaluated a sorghum mini core panel of 239 landraces sampled globally for shoot and root growth under simulated drought conditions using 10% and 20% polyethylene glycol (PEG) in 2020 and 2024, and measured drought tolerance using the seedling tolerance coefficient (STC).</p>
</sec>
<sec>
<title>Results and discussion</title>
<p>Phenotypic analysis showed that more accessions produced more roots than longer roots when exposed to 10% PEG; however, at 20% PEG, more accessions produced longer roots than more roots, reflecting the adaptability of some accessions to drought stress. However, PEG reduced shoot growth in all accessions in both years. A genome-wide association study (GWAS) on 32 growth and 19 STC traits identified 22 loci, 19 of which were mapped to the STC traits, and 17 of these 19 were associated with STC of shoot weight. Eleven of the 22 loci were collocated with 23 previously identified mapped drought-related quantitative trait loci (QTLs); 15 of these 23 QTLs were mapped to green leaf area, total number of green leaves, or chlorophyll content. We also found 19 candidate genes for 12 of the 22 loci. Five of those genes showed either preferential or specific expression in the roots according to GeneAtlas v2. One candidate gene from a locus colocated with a previously mapped chlorophyll fluorescence QTL has been shown to increase chlorophyll fluorescence in maize in another study. The results of this study lay the foundation for further characterizing the sorghum mini core panel for novel drought-tolerant genes.</p>
</sec>
</abstract>
<kwd-group>
<kwd>sorghum</kwd>
<kwd>mini core</kwd>
<kwd>GWAS</kwd>
<kwd>SNPs</kwd>
<kwd>drought tolerance</kwd>
<kwd>candidate genes</kwd>
</kwd-group>
<counts>
<fig-count count="0"/>
<table-count count="4"/>
<equation-count count="2"/>
<ref-count count="76"/>
<page-count count="14"/>
<word-count count="5346"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Functional and Applied Plant Genomics</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Water is critical for plant growth and development. As with all crop plants, the growth of sorghum [<italic>Sorghum bicolor</italic> (L.) Moench] relies on an adequate water supply in the form of rainfall or irrigation well distributed throughout the growing season (<xref ref-type="bibr" rid="B3">Assefa et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B14">Eck and Musick, 1979</xref>). For example, a medium-to-late sorghum variety maturing between 110 and 130 days would require approximately 450 to 650 mm of water during the growing season, and for this reason, the average yield of dryland sorghum is approximately half that of irrigated sorghum (<xref ref-type="bibr" rid="B3">Assefa et&#xa0;al., 2010</xref>). Not surprisingly, the total water supply (available soil water at seedling emergence plus in-season precipitation) is significantly correlated with sorghum grain yield (<italic>r</italic>
<sup>2</sup> = 0.834), and for every centimeter increase of available soil water at seedling emergence and in-season precipitation, sorghum grain yield increases by 221 and 164 kg ha<sup>&#x2212;1</sup>, respectively (<xref ref-type="bibr" rid="B56">Stone and Schlegel, 2006</xref>). This indicates that soil water at seedling emergence is slightly more important for grain yield, probably because the early stages of plant growth (germination, emergence, and seedling establishment) are potentially the most vulnerable to drought stress (<xref ref-type="bibr" rid="B2">Abreha et&#xa0;al., 2022</xref>).</p>
<p>Despite yield reduction by drought, sorghum is considered more drought-resistant than many other crop plants (<xref ref-type="bibr" rid="B21">Hadebe et&#xa0;al., 2017</xref>) and shows a wide range of morphological, physiological, and biochemical adaptations in response to drought stress (<xref ref-type="bibr" rid="B33">Liu et&#xa0;al., 2024</xref>). When exposed to drought, older sorghum leaves are selectively killed, while the younger leaves remain physiologically functional as a result of osmotic adjustment in the younger leaves (<xref ref-type="bibr" rid="B6">Blum, 2005</xref>). Sorghum plants can have higher water use efficiency because they can reduce evapotranspiration more efficiently (<xref ref-type="bibr" rid="B59">Tolk and Howell, 2003</xref>). This is most likely because drought-tolerant sorghums tend to produce more epicuticular wax on their leaf surface compared to sensitive ones during drought stress (<xref ref-type="bibr" rid="B47">Sanjari et&#xa0;al., 2021</xref>). Further support comes from overexpressing a sorghum <italic>WINL1</italic>, which simultaneously increases total wax/cutin content and drought tolerance in <italic>Arabidopsis</italic> (<xref ref-type="bibr" rid="B4">Bao et&#xa0;al., 2017</xref>). Another reason may be that during drought, drought-tolerant sorghum plants show more leaf rolling than the susceptible lines, reducing the effective evapotranspiration area of the uppermost leaves by approximately 75% (<xref ref-type="bibr" rid="B36">Matthews et&#xa0;al., 1990</xref>). In addition to this leaf feature, sorghum plants tend to penetrate deeper into the subsoil (40&#x2013;135 cm) (<xref ref-type="bibr" rid="B48">Schittenhelm and Schroetter, 2014</xref>; <xref ref-type="bibr" rid="B50">Singh and Singh, 1995</xref>), and more roots are produced during drought (<xref ref-type="bibr" rid="B9">de Oliveira et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B43">Queiroz et&#xa0;al., 2019</xref>). A combination of these two factors may account for up to 90% of the total water used by sorghum (<xref ref-type="bibr" rid="B44">Rachidi et&#xa0;al., 1993</xref>). Therefore, this root feature (more and deeper roots) has been found to be a major contributor to drought tolerance in sorghum (<xref ref-type="bibr" rid="B69">Wright and Smith, 1983</xref>). At the physiological level, drought induces the large central vacuole to form small vesicles when the leaf water potential is at &#x2212;37 bars; this maintains tonoplast integrity and allows sorghum plants to withstand drought (<xref ref-type="bibr" rid="B18">Giles et&#xa0;al., 1976</xref>). It is not surprising that drought elicits extensive genetic (<xref ref-type="bibr" rid="B2">Abreha et&#xa0;al., 2022</xref>) and proteomic responses (<xref ref-type="bibr" rid="B29">Li et&#xa0;al., 2020</xref>) in sorghum.</p>
<p>Because of its importance, drought tolerance has been extensively mapped in sorghum. By searching drought tolerance-related traits in the Sorghum quantitative trait locus (QTL) Atlas (<xref ref-type="bibr" rid="B34">Mace et&#xa0;al., 2019</xref>), 817 loci were identified from 19 studies published before 2019. More recently, <xref ref-type="bibr" rid="B60">Tsehaye et&#xa0;al. (2024)</xref> mapped 32 drought-related quantitative trait nucleotides (QTNs) using an association mapping panel of 216 diverse accessions and 17,637 Single Nucleotide Polymorphism (SNP) markers, four of which colocated with previously mapped drought-related QTLs. <xref ref-type="bibr" rid="B16">Faye et&#xa0;al. (2022)</xref> mapped 16 pleiotropic associations for drought responses across water stress environments using an association mapping panel of 590 predominantly West African sorghum landraces and 130,709 SNPs. Crop landraces represent local adaptations of domesticated species and contribute novel alleles for adaptation to stressful environments (<xref ref-type="bibr" rid="B13">Dwivedi et&#xa0;al., 2016</xref>). Although larger panels (<xref ref-type="bibr" rid="B16">Faye et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B58">Tao et&#xa0;al., 2020</xref>, <xref ref-type="bibr" rid="B57">2021</xref>) have been used in a sorghum genome-wide association study (GWAS), we found that the sorghum mini core panel is effective in QTL mapping. In a previous study, we mapped and cloned a pleiotropic QTL gene for plant height, days to 50% flowering, biomass, juice yield, and juice sugar content (<xref ref-type="bibr" rid="B63">Upadhyaya et&#xa0;al., 2022</xref>) using the sorghum mini core collection of 242 global landraces (<xref ref-type="bibr" rid="B61">Upadhyaya et&#xa0;al., 2009</xref>). The mini core panel has since been used to map sorghum panicle architecture (<xref ref-type="bibr" rid="B65">Wang et&#xa0;al., 2021</xref>), sorghum plant color (<xref ref-type="bibr" rid="B64">Wang et&#xa0;al., 2024</xref>), callus induction and regeneration from mature sorghum seeds (<xref ref-type="bibr" rid="B70">Xu et&#xa0;al., 2025</xref>), and additional developmental and reproductive traits (<xref ref-type="bibr" rid="B62">Upadhyaya et&#xa0;al., 2024</xref>).</p>
<p>In this study, the objective was to map drought tolerance loci that are pleiotropic for more than one trait or stable across environments. Drought stress was imposed by polyethylene glycol (PEG), which is commonly used to simulate drought in sorghum (<xref ref-type="bibr" rid="B1">Abdel-Ghany et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B12">Dugas et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B24">Jafar et&#xa0;al., 2004</xref>; <xref ref-type="bibr" rid="B38">Pavli et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B43">Queiroz et&#xa0;al., 2019</xref>), on the sorghum mini core panel. To carry out the mapping, we evaluated seedling shoot/root length, shoot/root fresh/dry weight, germination rate with and without osmotic stress, and drought indices, which were calculated as the ratio of growth under stressed and control conditions in 2020 and 2024 and performed a GWAS on the traits as previously described (<xref ref-type="bibr" rid="B31">Li et&#xa0;al., 2018</xref>) using 6,094,317 SNP markers (<xref ref-type="bibr" rid="B63">Upadhyaya et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B65">Wang et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B70">Xu et&#xa0;al., 2025</xref>). We identified 17 QTLs for shoot fresh and dry weight and drought index, along with five QTLs for other traits. A suite of candidate genes landed on by or closest to linked SNPs was also identified.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="s2_1">
<title>Plant materials and osmotic stress assay</title>
<p>A mini core panel of 239 accessions (<xref ref-type="bibr" rid="B61">Upadhyaya et&#xa0;al., 2009</xref>) was used for this study. Uniform, full, and healthy seeds, free from mechanical damage or pest or disease infection, were used. The selected seeds were surface-sterilized with a 0.1% mercuric chloride (HgCl<sub>2</sub>) solution for 15 minutes and then rinsed thoroughly three times with sterile distilled water to remove any residual HgCl<sub>2</sub>. The sterilized seeds were treated with 10% and 20% polyethylene glycol (PEG-6000) solutions in 2020 (20_10 and 20_20, respectively) and with 10% PEG in 2024 (24_10) to simulate drought stress, with distilled water as the control. The 20% PEG treatment was not repeated in 2024 because it interfered with germination and subsequent seedling growth. Each treatment consisted of 30 seeds for each of the three replicates in each accession. Both the control and treatment seeds germinated on two pieces of special blotting paper (12 &#xd7; 12 cm) in a germination box and were incubated in a plant growth chamber at a constant temperature of 28&#xb0;C with a 16-hour light/8-hour dark photoperiod for 10 days. On the 10th day, 10 uniformly growing seedlings were selected from each treatment. Shoot length (SL) and root length (RL) were measured using a ruler to the nearest millimeter. Fresh weights of shoots and roots (SFW and RFW, respectively) were determined using an electronic balance with a precision of 0.0001g. The shoots and roots were then dried at 75&#xb0;C for 24 hours and cooled to room temperature, and their dry weights (SDW and RDW, respectively) were measured using the same balance. The germination rate (GR) was recorded for 2024.</p>
<p>The drought tolerance was assessed using the seedling tolerance coefficient (STC) (<xref ref-type="bibr" rid="B42">Qiu et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B73">Yu et&#xa0;al., 2021</xref>) and was calculated as follows:</p>
<disp-formula>
<mml:math display="block" id="M1">
<mml:mrow>
<mml:mtext>STC</mml:mtext>
<mml:mo>=</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mtext>Measured&#xa0;value&#xa0;under&#xa0;treatment</mml:mtext>
<mml:mo stretchy="false">/</mml:mo>
<mml:mtext>Measured&#xa0;value&#xa0;under&#xa0;control</mml:mtext>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>The STC calculated for each trait was denoted as RL<sub>STC</sub> for root length, while root length for the 10% or 20% PEG treatment conducted in 2020 was denoted as RLPEG20_10 and RLPEG20_20, respectively; the control was denoted as RL20. A list of all traits is provided in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S1</bold>
</xref>.</p>
</sec>
<sec id="s2_2">
<title>Association mapping</title>
<p>GWAS was conducted as described (<xref ref-type="bibr" rid="B31">Li et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B63">Upadhyaya et&#xa0;al., 2022</xref>, <xref ref-type="bibr" rid="B62">2024</xref>; <xref ref-type="bibr" rid="B65">Wang et&#xa0;al., 2021</xref>, <xref ref-type="bibr" rid="B64">2024</xref>; <xref ref-type="bibr" rid="B70">Xu et&#xa0;al., 2025</xref>). In short, GWAS for the 51 traits (listed together with all Manhattan plots in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure S1</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S1</bold>
</xref>) was performed using 6,094,317 SNPs. A kinship matrix (K) was generated with EMMAX (<xref ref-type="bibr" rid="B25">Kang et&#xa0;al., 2010</xref>), and a Q matrix was calculated using STRUCTURE 2.3.4 (<xref ref-type="bibr" rid="B39">Pritchard et&#xa0;al., 2000</xref>). Both matrices were used to perform GWAS in an Mixed Linear Model (MLM) model (<xref ref-type="bibr" rid="B71">Yu et&#xa0;al., 2006</xref>). The modified Bonferroni correction was used to determine association significance thresholds. At a nominal level of &#x3b1; = 0.05, the threshold <italic>p</italic>-value was 8.2 &#xd7; 10<sup>&#x2212;9</sup>, or a &#x2212;log<sub>10</sub>(<italic>p</italic>) value of 8.08. As in previous studies (<xref ref-type="bibr" rid="B63">Upadhyaya et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B62">2024</xref>), we also included markers with <italic>p</italic>-values below 10<sup>&#x2212;4</sup> (<xref ref-type="bibr" rid="B15">Famoso et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B76">Zhao et&#xa0;al., 2011</xref>) to account for associations of multiple markers at a locus across more than two traits to declare an association.</p>
</sec>
<sec id="s2_3">
<title>QTL colocalization and identification of candidate genes</title>
<p>As described by <xref ref-type="bibr" rid="B62">Upadhyaya et&#xa0;al. (2024)</xref>, to identify colocalizing QTLs mapped in this study based on physical location, previously mapped QTLs downloaded from the Sorghum QTL Atlas (<xref ref-type="bibr" rid="B34">Mace et&#xa0;al., 2019</xref>) and those by <xref ref-type="bibr" rid="B16">Faye et&#xa0;al. (2022)</xref> were used. The location of candidate genes was identified with the BTx623 reference sequence (whose complete genome is now available; <xref ref-type="bibr" rid="B68">Wei et&#xa0;al., 2024</xref>), <italic>S. bicolor</italic> v3.1.1 (<xref ref-type="bibr" rid="B37">McCormick et&#xa0;al., 2018</xref>) at Phytozome 13 (<xref ref-type="bibr" rid="B19">Goodstein et&#xa0;al., 2012</xref>). Genes, including linked SNP markers with <italic>p</italic>-values below 10<sup>&#x2212;4</sup>, were considered candidate genes based on previous studies that showed that linked markers can land on the causal genes (<xref ref-type="bibr" rid="B63">Upadhyaya et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B66">Wang et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B75">Zhang et&#xa0;al., 2023</xref>).</p>
</sec>
<sec id="s2_4">
<title>Statistical analysis</title>
<p>Pearson&#x2019;s correlation coefficient (<italic>r</italic>) was calculated using Excel&#x2019;s PEARSON function. Its significance was tested using a table of critical values. The assumptions of analysis of variance (ANOVA), i.e., data normality and variance homogeneity, were confirmed using the Kolmogorov&#x2013;Smirnov test (see <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S2</bold>
</xref>). ANOVA was performed using the SPSS V29.0 statistical software with a general linear model. The variance components generated from the ANOVA were used to calculate the broad-sense heritability (<italic>H</italic>
<sup>2</sup>) for the RL<sub>STC</sub>, RDW<sub>STC</sub>, RFW<sub>STC</sub>, SL<sub>STC</sub>, SDW<sub>STC</sub>, and SFW<sub>STC</sub> using the following formula:</p>
<disp-formula>
<mml:math display="block" id="M2">
<mml:mrow>
<mml:msup>
<mml:mi>H</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
<mml:mo>=</mml:mo>
<mml:mi>V</mml:mi>
<mml:mi>g</mml:mi>
<mml:mo stretchy="false">/</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>V</mml:mi>
<mml:mi>g</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>V</mml:mi>
<mml:mi>g</mml:mi>
<mml:mi>e</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>V</mml:mi>
<mml:mi>e</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>Vg</italic>, <italic>Vge</italic>, and <italic>Ve</italic> are genetic variance, the genotype &#xd7; environment interaction variance, and environmental variance, respectively (<xref ref-type="bibr" rid="B51">Smith et&#xa0;al., 1998</xref>; <xref ref-type="bibr" rid="B62">Upadhyaya et&#xa0;al., 2024</xref>).</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Phenotypic analysis</title>
<p>We analyzed phenotypic variation among replicates for each accession. We found that if ranked by minimal dispersion using standard deviation (SD) for SLPEG20_10, three of the top four accessions (IS12302, IS20697, and IS2382) were all caudatum, and one (IS30466) was caudatum-bicolor (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S3</bold>
</xref>). Pearson&#x2019;s correlation between the STC traits of SFW<sub>STC</sub>20_20 and SDW<sub>STC</sub>20_20 was highest (<italic>r</italic> = 0.95; <italic>r</italic> = 0.77) between SFW<sub>STC</sub>20_10 and SDW<sub>STC</sub>20_10 and was <italic>r</italic> = 0.82 between SFW<sub>STC</sub>24_10 and SDW<sub>STC</sub>24_10; all significant at <italic>p</italic> &lt; 0.001. We also observed a similar trend between RFW<sub>STC</sub> and RDW<sub>STC</sub> (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S4</bold>
</xref>). This was followed by SL<sub>STC</sub> and SFW<sub>STC</sub>, and SL<sub>STC</sub> and SDW<sub>STC</sub> (both 0.84, significant at <italic>p</italic> &lt; 0.001). We also found that SDW<sub>STC</sub>20_20 was highly and significantly correlated with RDW<sub>STC</sub>20_20, RFW<sub>STC</sub>20_20, and SL<sub>STC</sub>20_20 with <italic>r</italic> of 0.8, 0.77, and 0.84, respectively (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S4</bold>
</xref>). Interestingly, RDWPEG20_10 was more highly correlated with SL20, RL20, SFW20, RFW20, SDW20, and RDW20 than with RDWPEG20_20 (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S4</bold>
</xref>).</p>
<p>We found that 34%&#x2013;55% of the mini core panel produced more root biomass and longer roots during osmotic stress (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). At 10% PEG, more accessions produced more roots (47%&#x2013;55%) than longer roots (19%), and this trend was also observed in the 2024 data; however, at 20% PEG, more accessions produced longer roots (34%) than more roots (13%&#x2013;20%). On average, in 2020, the 10% PEG treatment reduced RL by 20%, and the 20% PEG treatment reduced RL by 72%. In 2024, when only 10% PEG was used, RL was reduced by 34% due to the treatment. When ranked by RL<sub>STC</sub>, none of the bottom 70 accessions produced longer roots in 2020 when treatment was increased from 10% to 20% PEG (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S5</bold>
</xref>). Furthermore, no accessions invested in shoot growth at 20% PEG, although a few random accessions (2%&#x2013;7%) did show increased shoot weight at 10% PEG in both years (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). This clearly demonstrates that osmotic stress greatly reduces shoot growth. Interestingly, all three root STC traits, RL<sub>STC</sub>, RDW<sub>STC</sub>, and RFW<sub>STC</sub>, had slightly lower broad-sense heritability than the shoot traits (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). This was most likely due to the non-genetic root response to osmotic stress, as the root was in direct contact with the stressor.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Number of mini core accessions with increased phenotypic values by PEG treatments*.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" colspan="2" align="center">Trait</th>
<th valign="top" align="center">Accessions (percentage)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="3" align="center">RL<sub>STC</sub>
</td>
<td valign="top" align="center">RL<sub>STC</sub>20-10</td>
<td valign="top" align="center">34 (19)</td>
</tr>
<tr>
<td valign="top" align="center">RL<sub>STC</sub>20-20</td>
<td valign="top" align="center">60 (34)</td>
</tr>
<tr>
<td valign="top" align="center">RL<sub>STC</sub>24_10</td>
<td valign="top" align="center">17 (10)</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">RDW<sub>STC</sub>
</td>
<td valign="top" align="center">RDW<sub>STC</sub>20-10</td>
<td valign="top" align="center">98 (55)</td>
</tr>
<tr>
<td valign="top" align="center">RDW<sub>STC</sub>20-20</td>
<td valign="top" align="center">23 (13)</td>
</tr>
<tr>
<td valign="top" align="center">RDW<sub>STC</sub>24_10</td>
<td valign="top" align="center">30 (17)</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">RFW<sub>STC</sub>
</td>
<td valign="top" align="center">RFW<sub>STC</sub>20-10</td>
<td valign="top" align="center">84 (47)</td>
</tr>
<tr>
<td valign="top" align="center">RFW<sub>STC</sub>20-20</td>
<td valign="top" align="center">35 (20)</td>
</tr>
<tr>
<td valign="top" align="center">RFW<sub>STC</sub>24_10</td>
<td valign="top" align="center">24 (13)</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">SL<sub>STC</sub>
</td>
<td valign="top" align="center">SL<sub>STC</sub>20-10</td>
<td valign="top" align="center">2 (1)</td>
</tr>
<tr>
<td valign="top" align="center">SL<sub>STC</sub>20-20</td>
<td valign="top" align="center">0 (0)</td>
</tr>
<tr>
<td valign="top" align="center">SL<sub>STC</sub>24_10</td>
<td valign="top" align="center">9 (5)</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">SDW<sub>STC</sub>
</td>
<td valign="top" align="center">SDW<sub>STC</sub>20-10</td>
<td valign="top" align="center">12 (7)</td>
</tr>
<tr>
<td valign="top" align="center">SDW<sub>STC</sub>20-20</td>
<td valign="top" align="center">0 (0)</td>
</tr>
<tr>
<td valign="top" align="center">SDW<sub>STC</sub>24_10</td>
<td valign="top" align="center">8 (4)</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">SFW<sub>STC</sub>
</td>
<td valign="top" align="center">SFW<sub>STC</sub>20-10</td>
<td valign="top" align="center">4 (2)</td>
</tr>
<tr>
<td valign="top" align="center">SFW<sub>STC</sub>20-20</td>
<td valign="top" align="center">0 (0)</td>
</tr>
<tr>
<td valign="top" align="center">SFW<sub>STC</sub>24_10</td>
<td valign="top" align="center">10 (6)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*10% (20_10) and 20% PEG (20_20) in 2020 and 10% in 2024. A total of 179 accessions with missing data points of no more than one were included in the accession count and percentage calculation. Values in parentheses are percentages.</p>
</fn>
<fn>
<p>STC, seedling tolerance coefficient; SL/RL, shoot/root length; SFW/RFW, shoot/root fresh weight; SDW/RDW, shoot/root dry weight; PEG, polyethylene glycol.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Broad-sense heritability (<italic>H</italic>
<sup>2</sup>) of the six seedling tolerance coefficient traits.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" colspan="2" align="center">Trait</th>
<th valign="top" align="center">
<italic>H</italic>
<sup>2</sup>
</th>
<th valign="top" align="center">Average</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="3" align="center">RDW<sub>STC</sub>
</td>
<td valign="top" align="center">RDW<sub>STC</sub>20-10</td>
<td valign="top" align="center">0.690558</td>
<td valign="top" rowspan="3" align="center">0.709377</td>
</tr>
<tr>
<td valign="top" align="center">RDW<sub>STC</sub>20-20</td>
<td valign="top" align="center">0.748958</td>
</tr>
<tr>
<td valign="top" align="center">RDW<sub>STC</sub>24_10</td>
<td valign="top" align="center">0.688615</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">RFW<sub>STC</sub>
</td>
<td valign="top" align="center">RFWSTC20-10</td>
<td valign="top" align="center">0.501197</td>
<td valign="top" rowspan="3" align="center">0.642634</td>
</tr>
<tr>
<td valign="top" align="center">RFWSTC20-20</td>
<td valign="top" align="center">0.737857</td>
</tr>
<tr>
<td valign="top" align="center">RFWSTC24_10</td>
<td valign="top" align="center">0.688847</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">RL<sub>STC</sub>
</td>
<td valign="top" align="center">RL<sub>STC</sub>20-10</td>
<td valign="top" align="center">0.754941</td>
<td valign="top" rowspan="3" align="center">0.702646</td>
</tr>
<tr>
<td valign="top" align="center">RL<sub>STC</sub>20-20</td>
<td valign="top" align="center">0.611755</td>
</tr>
<tr>
<td valign="top" align="center">RL<sub>STC</sub>24_10</td>
<td valign="top" align="center">0.741242</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">SDW<sub>STC</sub>
</td>
<td valign="top" align="center">SDW<sub>STC</sub>20-10</td>
<td valign="top" align="center">0.85714</td>
<td valign="top" rowspan="3" align="center">0.792949</td>
</tr>
<tr>
<td valign="top" align="center">SDW<sub>STC</sub>20-20</td>
<td valign="top" align="center">0.805177</td>
</tr>
<tr>
<td valign="top" align="center">SDW<sub>STC</sub>24_10</td>
<td valign="top" align="center">0.716529</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">SFW<sub>STC</sub>
</td>
<td valign="top" align="center">SFW<sub>STC</sub>20-10</td>
<td valign="top" align="center">0.907195</td>
<td valign="top" rowspan="3" align="center">0.813592</td>
</tr>
<tr>
<td valign="top" align="center">SFW<sub>STC</sub>20-20</td>
<td valign="top" align="center">0.765715</td>
</tr>
<tr>
<td valign="top" align="center">SFW<sub>STC</sub>24_10</td>
<td valign="top" align="center">0.767865</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="center">SL<sub>STC</sub>
</td>
<td valign="top" align="center">SL<sub>STC</sub>20-10</td>
<td valign="top" align="center">0.739947</td>
<td valign="top" rowspan="3" align="center">0.780708</td>
</tr>
<tr>
<td valign="top" align="center">SL<sub>STC</sub>20-20</td>
<td valign="top" align="center">0.746749</td>
</tr>
<tr>
<td valign="top" align="center">SL<sub>STC</sub>24_10</td>
<td valign="top" align="center">0.855427</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Based on RL<sub>STC</sub> and RDW<sub>STC</sub>, we identified one drought-tolerant (IS 30533) and one sensitive (IS 32439) accession. On average, the IS 32439 root length and dry weight were reduced by the PEG treatment by 64% and 71%, respectively, while in IS 30533, these were increased by 20% and 19%, respectively. Still, for IS 30533, shoot length and dry weight were decreased by 40% and 37%, respectively, by the treatment, while they were 65% and 60%, respectively, for IS 32439 (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S5</bold>
</xref>).</p>
</sec>
<sec id="s3_2">
<title>Association mapping</title>
<p>We applied the same criterion used in previous studies (<xref ref-type="bibr" rid="B63">Upadhyaya et&#xa0;al., 2022</xref>, <xref ref-type="bibr" rid="B62">2024</xref>; <xref ref-type="bibr" rid="B65">Wang et&#xa0;al., 2021</xref>) for trait mapping in the sorghum mini core panel, which defines a significant association as multiple SNPs linked to a trait within the same locus with a <italic>p</italic>-value &lt; 10<sup>&#x2212;4</sup>. In addition to identifying trait-specific loci, this study also focused on pleiotropic loci&#x2014;those associated with more than one trait. With this criterion, we identified 22 loci linked to 12 drought-related traits (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>; all 51 Manhattan plots are provided in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure S1</bold>
</xref>). SDW<sub>STC</sub> and SFW<sub>STC</sub> had the highest correlation coefficient (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S4</bold>
</xref>). Here, we report that 17 of the 22 mapped loci were pleiotropic for the two traits and that 19 of the 22 loci were mapped to the STC traits (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). Seven traits (RFW<sub>STC</sub>20_20, SL<sub>STC</sub>20_20, SDW<sub>STC</sub>20_20, SFW<sub>STC</sub>20_20, SFWPEG20_20, SDWPEG20_20, and SLPEG20_20) were all mapped to the 4&#x2013;1 locus. Loci 2&#x2013;1 and 4-2 (RFW<sub>STC</sub>20_20, SL<sub>STC</sub>20_20, SDW<sub>STC</sub>20_20, and SFW<sub>STC</sub>20_20) and 6&#x2013;1 and 6-2 (SDW<sub>STC</sub>20_20, SFW<sub>STC</sub>20_20, SDWPEG20_20, and SFWPEG20_20) were all pleiotropic for four traits, while all other loci were pleiotropic for two traits (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Drought tolerance-related loci mapped in the sorghum mini core panel and their colocation with previously mapped drought-related QTLs.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" colspan="4" align="center">QTLs mapped in this study</th>
<th valign="middle" colspan="4" align="center">Previously mapped QTLs</th>
</tr>
<tr>
<th valign="middle" align="center">ID</th>
<th valign="middle" align="center">Top SNPs</th>
<th valign="middle" colspan="2" align="center">Trait/&#x2212;log(<italic>p</italic>) value</th>
<th valign="middle" align="center">Location</th>
<th valign="middle" align="center">Trait</th>
<th valign="middle" align="center">Name</th>
<th valign="middle" align="center">Reference</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="4" align="center">1-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="4" align="center">1:7709494&#x2013;14555494<break/>1:7780218&#x2013;8980613<break/>1:7895113&#x2013;9046512<break/>1:8086604&#x2013;9156345<break/>1:8180004&#x2013;8187693</td>
<td valign="middle" rowspan="4" align="center">Total number of green leaves<break/>Plant height<break/>Biomass<break/>Fresh biomass<break/>Maturity</td>
<td valign="middle" rowspan="4" align="center">QTNGL1.2<break/>QHGHT1.58<break/>QBMAS1.9<break/>QFBMS1.51<break/>KN1</td>
<td valign="middle" rowspan="4" align="center">
<xref ref-type="bibr" rid="B45">Rama Reddy et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B52">Spindel et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B16">Faye et&#xa0;al., 2022</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">8175770</td>
<td valign="middle" align="center">6.092572476</td>
<td valign="middle" align="center">5.901292726</td>
</tr>
<tr>
<td valign="middle" align="center">8175846</td>
<td valign="middle" align="center">6.069833035</td>
<td valign="middle" align="center">6.328635272</td>
</tr>
<tr>
<td valign="middle" align="center">8181926</td>
<td valign="middle" align="center">6.734819235</td>
<td valign="middle" align="center">6.658063039</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">1-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">25423417</td>
<td valign="middle" align="center">6.696211597</td>
<td valign="middle" align="center">5.046218177</td>
</tr>
<tr>
<td valign="middle" align="center">25423421</td>
<td valign="middle" align="center">6.896639032</td>
<td valign="middle" align="center">5.274721862</td>
</tr>
<tr>
<td valign="middle" align="center">25423654</td>
<td valign="middle" align="center">6.351679731</td>
<td valign="middle" align="center">6.124947452</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">1-3</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SFWPEG20_20</td>
<td valign="middle" align="center">SLPEG20_20</td>
<td valign="middle" rowspan="4" align="center">1:60998392&#x2013;61246047</td>
<td valign="middle" rowspan="4" align="center">Biomass at 65% moisture</td>
<td valign="middle" rowspan="4" align="center">QBM651.10</td>
<td valign="middle" rowspan="4" align="center">
<xref ref-type="bibr" rid="B52">Spindel et&#xa0;al., 2018</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">61062232</td>
<td valign="middle" align="center">6.244060667</td>
<td valign="middle" align="center">7.240034659</td>
</tr>
<tr>
<td valign="middle" align="center">61067704</td>
<td valign="middle" align="center">6.244060667</td>
<td valign="middle" align="center">7.240034659</td>
</tr>
<tr>
<td valign="middle" align="center">61067917</td>
<td valign="middle" align="center">6.970580775</td>
<td valign="middle" align="center">7.951858174</td>
</tr>
<tr>
<td valign="middle" rowspan="8" align="center">2-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">RFW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SL<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="8" align="center">2:47479285&#x2013;50768059<break/>2:48465917&#x2013;51754692<break/>2:47540401&#x2013;57021411</td>
<td valign="middle" rowspan="8" align="center">Plant height<break/>Fresh biomass<break/>Green leaf area</td>
<td valign="middle" rowspan="8" align="center">QHGHT2.22<break/>QFBMS2.12<break/>QGLFA2.2</td>
<td valign="middle" rowspan="8" align="center">
<xref ref-type="bibr" rid="B52">Spindel et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B45">Rama Reddy et&#xa0;al., 2014</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">49420951</td>
<td valign="middle" align="center">4.487674263</td>
<td valign="middle" align="center">3.424231104</td>
</tr>
<tr>
<td valign="middle" align="center">49421672</td>
<td valign="middle" align="center">4.179738517</td>
<td valign="middle" align="center">3.309300367</td>
</tr>
<tr>
<td valign="middle" align="center">49422838</td>
<td valign="middle" align="center">6.213284552</td>
<td valign="middle" align="center">4.904262718</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
</tr>
<tr>
<td valign="middle" align="center">49420951</td>
<td valign="middle" align="center">6.415666917</td>
<td valign="middle" align="center">7.017774935</td>
</tr>
<tr>
<td valign="middle" align="center">49421672</td>
<td valign="middle" align="center">6.33486414</td>
<td valign="middle" align="center">6.889629854</td>
</tr>
<tr>
<td valign="middle" align="center">49422838</td>
<td valign="middle" align="center">7.220320153</td>
<td valign="middle" align="center">7.486824187</td>
</tr>
<tr>
<td valign="middle" rowspan="5" align="center">3-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="5" align="center"/>
<td valign="middle" rowspan="5" align="center"/>
<td valign="middle" rowspan="5" align="center"/>
<td valign="middle" rowspan="5" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">20274965</td>
<td valign="middle" align="center">7.283425462</td>
<td valign="middle" align="center">5.58199737</td>
</tr>
<tr>
<td valign="middle" align="center">20274987</td>
<td valign="middle" align="center">6.01480676</td>
<td valign="middle" align="center">4.077951971</td>
</tr>
<tr>
<td valign="middle" align="center">20274991</td>
<td valign="middle" align="center">6.494032608</td>
<td valign="middle" align="center">4.525464497</td>
</tr>
<tr>
<td valign="middle" align="center">20275019</td>
<td valign="middle" align="center">7.098582705</td>
<td valign="middle" align="center">5.276704707</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">3-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="4" align="center">3:51390526&#x2013;55538940<break/>3:51629032&#x2013;55604826<break/>3:53876527&#x2013;55222843<break/>3:53884338&#x2013;55533369<break/>3:54220793&#x2013;55419201</td>
<td valign="middle" rowspan="4" align="center">Green leaf area<break/>Total number of green leaves<break/>Total number of green leaves<break/>Green leaf area<break/>Green leaf area</td>
<td valign="middle" rowspan="4" align="center">QGLFA3.3<break/>QTNGL3.3<break/>QTNGL3.4<break/>QGLFA3.5<break/>QGLFA3.4</td>
<td valign="middle" rowspan="4" align="center">
<xref ref-type="bibr" rid="B45">Rama Reddy et&#xa0;al., 2014</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">54673890</td>
<td valign="middle" align="center">5.864308749</td>
<td valign="middle" align="center">5.34388905</td>
</tr>
<tr>
<td valign="middle" align="center">54673977</td>
<td valign="middle" align="center">5.864308749</td>
<td valign="middle" align="center">5.34388905</td>
</tr>
<tr>
<td valign="middle" align="center">54674484</td>
<td valign="middle" align="center">6.282688315</td>
<td valign="middle" align="center">5.576211248</td>
</tr>
<tr>
<td valign="middle" rowspan="16" align="center">4-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">RFW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SL<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="16" align="center">4:71001&#x2013;1548102</td>
<td valign="middle" rowspan="16" align="center">Green leaf area</td>
<td valign="middle" rowspan="16" align="center">QGLFA4.1</td>
<td valign="middle" rowspan="16" align="center">
<xref ref-type="bibr" rid="B53">Srinivas et&#xa0;al., 2009</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">335179</td>
<td valign="middle" align="center">7.178732257</td>
<td valign="middle" align="center">5.829212644</td>
</tr>
<tr>
<td valign="middle" align="center">340675</td>
<td valign="middle" align="center">7.223628346</td>
<td valign="middle" align="center">5.582475776</td>
</tr>
<tr>
<td valign="middle" align="center">340847</td>
<td valign="middle" align="center">7.223628346</td>
<td valign="middle" align="center">5.582475776</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
</tr>
<tr>
<td valign="middle" align="center">335179</td>
<td valign="middle" align="center">8.549496331</td>
<td valign="middle" align="center">7.423224934</td>
</tr>
<tr>
<td valign="middle" align="center">340675</td>
<td valign="middle" align="center">7.198161217</td>
<td valign="middle" align="center">6.672253247</td>
</tr>
<tr>
<td valign="middle" align="center">340847</td>
<td valign="middle" align="center">7.198161217</td>
<td valign="middle" align="center">6.672253247</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SFWPEG20_20</td>
<td valign="middle" align="center">SDWPEG20_20</td>
</tr>
<tr>
<td valign="middle" align="center">335179</td>
<td valign="middle" align="center">6.634126667</td>
<td valign="middle" align="center">7.679019892</td>
</tr>
<tr>
<td valign="middle" align="center">340675</td>
<td valign="middle" align="center">6.781339929</td>
<td valign="middle" align="center">7.46226058</td>
</tr>
<tr>
<td valign="middle" align="center">340847</td>
<td valign="middle" align="center">6.781339929</td>
<td valign="middle" align="center">7.46226058</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SLPEG20_20</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">335179</td>
<td valign="middle" align="center">6.284284665</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">340675</td>
<td valign="middle" align="center">7.312943179</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">340847</td>
<td valign="middle" align="center">7.312943179</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" rowspan="6" align="center">4-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">RFW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SL<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="6" align="center"/>
<td valign="middle" rowspan="6" align="center"/>
<td valign="middle" rowspan="6" align="center"/>
<td valign="middle" rowspan="6" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">7340159</td>
<td valign="middle" align="center">6.005381451</td>
<td valign="middle" align="center">5.955787394</td>
</tr>
<tr>
<td valign="middle" align="center">7340188</td>
<td valign="middle" align="center">6.146902096</td>
<td valign="middle" align="center">5.711189696</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
</tr>
<tr>
<td valign="middle" align="center">7340159</td>
<td valign="middle" align="center">6.043780556</td>
<td valign="middle" align="center">5.883865159</td>
</tr>
<tr>
<td valign="middle" align="center">7340188</td>
<td valign="middle" align="center">6.201848721</td>
<td valign="middle" align="center">5.807850664</td>
</tr>
<tr>
<td valign="middle" rowspan="7" align="center">5-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SLPEG20_20</td>
<td valign="middle" align="center">SLPEG20_10</td>
<td valign="middle" rowspan="7" align="center"/>
<td valign="middle" rowspan="7" align="center"/>
<td valign="middle" rowspan="7" align="center"/>
<td valign="middle" rowspan="7" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">14749135</td>
<td valign="middle" align="center">7.20588014</td>
<td valign="middle" align="center">4.310967245</td>
</tr>
<tr>
<td valign="middle" align="center">14764206</td>
<td valign="middle" align="center">7.031012426</td>
<td valign="middle" align="center">4.726055663</td>
</tr>
<tr>
<td valign="middle" align="center">14790465</td>
<td valign="middle" align="center">8.295266962</td>
<td valign="middle" align="center">6.3811091</td>
</tr>
<tr>
<td valign="middle" align="center">14817605</td>
<td valign="middle" align="center">7.741075943</td>
<td valign="middle" align="center">5.659760658</td>
</tr>
<tr>
<td valign="middle" align="center">14838313</td>
<td valign="middle" align="center">7.22546815</td>
<td valign="middle" align="center">4.465115849</td>
</tr>
<tr>
<td valign="middle" align="center">14851504</td>
<td valign="middle" align="center">8.017381333</td>
<td valign="middle" align="center">4.50832729</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">5-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">RFW20_20</td>
<td valign="middle" align="center">RFWPEG20_10</td>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">20946132</td>
<td valign="middle" align="center">9.032320539</td>
<td valign="middle" align="center">7.242243694</td>
</tr>
<tr>
<td valign="middle" align="center">20946153</td>
<td valign="middle" align="center">8.476547344</td>
<td valign="middle" align="center">7.418053564</td>
</tr>
<tr>
<td valign="middle" align="center">20946253</td>
<td valign="middle" align="center">7.053352114</td>
<td valign="middle" align="center">4.882369306</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">5-3</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="3" align="center"/>
<td valign="middle" rowspan="3" align="center"/>
<td valign="middle" rowspan="3" align="center"/>
<td valign="middle" rowspan="3" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">65929984</td>
<td valign="middle" align="center">6.29492177</td>
<td valign="middle" align="center">5.650168324</td>
</tr>
<tr>
<td valign="middle" align="center">65930108</td>
<td valign="middle" align="center">6.360960499</td>
<td valign="middle" align="center">5.719394472</td>
</tr>
<tr>
<td valign="middle" rowspan="8" align="center">6-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="8" align="center">6:1671780&#x2013;1714417</td>
<td valign="middle" rowspan="8" align="center">Chlorophyll fluorescence</td>
<td valign="middle" rowspan="8" align="center">QCHLF6.8</td>
<td valign="middle" rowspan="8" align="center">
<xref ref-type="bibr" rid="B17">Fiedler et&#xa0;al., 2014</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">1683157</td>
<td valign="middle" align="center">7.763763571</td>
<td valign="middle" align="center">8.047866994</td>
</tr>
<tr>
<td valign="middle" align="center">1683159</td>
<td valign="middle" align="center">6.743550697</td>
<td valign="middle" align="center">7.170180763</td>
</tr>
<tr>
<td valign="middle" align="center">1683181</td>
<td valign="middle" align="center">6.366959595</td>
<td valign="middle" align="center">6.854304226</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDWPEG20_20</td>
<td valign="middle" align="center">SFWPEG20_20</td>
</tr>
<tr>
<td valign="middle" align="center">1683157</td>
<td valign="middle" align="center">7.173383002</td>
<td valign="middle" align="center">7.300309843</td>
</tr>
<tr>
<td valign="middle" align="center">1683159</td>
<td valign="middle" align="center">6.10531889</td>
<td valign="middle" align="center">6.323799102</td>
</tr>
<tr>
<td valign="middle" align="center">1683181</td>
<td valign="middle" align="center">6.277580714</td>
<td valign="middle" align="center">6.560284309</td>
</tr>
<tr>
<td valign="middle" rowspan="10" align="center">6-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="10" align="center">6:46558064&#x2013;50652065</td>
<td valign="middle" rowspan="10" align="center">Green leaf area</td>
<td valign="middle" rowspan="10" align="center">QGLFA6.1</td>
<td valign="middle" rowspan="10" align="center">
<xref ref-type="bibr" rid="B53">Srinivas et&#xa0;al., 2009</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">46599990</td>
<td valign="middle" align="center">6.778232968</td>
<td valign="middle" align="center">7.258141677</td>
</tr>
<tr>
<td valign="middle" align="center">46602135</td>
<td valign="middle" align="center">6.799929522</td>
<td valign="middle" align="center">7.245531549</td>
</tr>
<tr>
<td valign="middle" align="center">46613461</td>
<td valign="middle" align="center">6.799929522</td>
<td valign="middle" align="center">7.245531549</td>
</tr>
<tr>
<td valign="middle" align="center">46613645</td>
<td valign="middle" align="center">7.177554732</td>
<td valign="middle" align="center">7.880833313</td>
</tr>
<tr>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDWPEG20_20</td>
<td valign="middle" align="center">SFWPEG20_20</td>
</tr>
<tr>
<td valign="middle" align="center">46599990</td>
<td valign="middle" align="center">6.256926186</td>
<td valign="middle" align="center">6.636795736</td>
</tr>
<tr>
<td valign="middle" align="center">46602135</td>
<td valign="middle" align="center">6.310414974</td>
<td valign="middle" align="center">6.652851601</td>
</tr>
<tr>
<td valign="middle" align="center">46613461</td>
<td valign="middle" align="center">6.310414974</td>
<td valign="middle" align="center">6.652851601</td>
</tr>
<tr>
<td valign="middle" align="center">46613645</td>
<td valign="middle" align="center">6.613541225</td>
<td valign="middle" align="center">7.212360472</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">7-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">GRCK2024</td>
<td valign="middle" align="center">GR<sub>STC</sub>24_10</td>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">25776380</td>
<td valign="middle" align="center">6.358062437</td>
<td valign="middle" align="center">4.281133202</td>
</tr>
<tr>
<td valign="middle" align="center">25777587</td>
<td valign="middle" align="center">7.526355067</td>
<td valign="middle" align="center">5.094466411</td>
</tr>
<tr>
<td valign="middle" align="center">25777916</td>
<td valign="middle" align="center">8.225453962</td>
<td valign="middle" align="center">5.262387727</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">7-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_10</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_10</td>
<td valign="middle" rowspan="3" align="center">7:39543566&#x2013;48379318</td>
<td valign="middle" rowspan="3" align="center">Chlorophyll content</td>
<td valign="middle" rowspan="3" align="center">QCHLC7.4</td>
<td valign="middle" rowspan="3" align="center">
<xref ref-type="bibr" rid="B17">Fiedler et&#xa0;al., 2014</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">45098852</td>
<td valign="middle" align="center">7.41519769</td>
<td valign="middle" align="center">7.515380775</td>
</tr>
<tr>
<td valign="middle" align="center">45098853</td>
<td valign="middle" align="center">6.190476311</td>
<td valign="middle" align="center">6.267296943</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">8-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">4718439</td>
<td valign="middle" align="center">10.14452745</td>
<td valign="middle" align="center">8.496081295</td>
</tr>
<tr>
<td valign="middle" align="center">4719344</td>
<td valign="middle" align="center">6.388117926</td>
<td valign="middle" align="center">5.886092378</td>
</tr>
<tr>
<td valign="middle" align="center">4726212</td>
<td valign="middle" align="center">7.220582719</td>
<td valign="middle" align="center">5.798288488</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">9-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">RFW20</td>
<td valign="middle" align="center">SFWPEG20_10</td>
<td valign="middle" rowspan="3" align="center"/>
<td valign="middle" rowspan="3" align="center"/>
<td valign="middle" rowspan="3" align="center"/>
<td valign="middle" rowspan="3" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">734720</td>
<td valign="middle" align="center">8.401017801</td>
<td valign="middle" align="center">6.275968976</td>
</tr>
<tr>
<td valign="middle" align="center">734771</td>
<td valign="middle" align="center">7.915613864</td>
<td valign="middle" align="center">4.374989053</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">9-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SFW<sub>STC</sub>24_10</td>
<td valign="middle" align="center">RFW<sub>STC</sub>24_10</td>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">9798734</td>
<td valign="middle" align="center">6.7147509</td>
<td valign="middle" align="center">5.255642033</td>
</tr>
<tr>
<td valign="middle" align="center">9799294</td>
<td valign="middle" align="center">7.039341044</td>
<td valign="middle" align="center">5.70565594</td>
</tr>
<tr>
<td valign="middle" align="center">9800202</td>
<td valign="middle" align="center">6.582200035</td>
<td valign="middle" align="center">5.26023082</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">9-3</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">RFW20_20</td>
<td valign="middle" align="center">SFWPEG20_10</td>
<td valign="middle" rowspan="3" align="center">9:55713786&#x2013;57908267<break/>9:55813801&#x2013;57991519<break/>9:56104114&#x2013;56610219</td>
<td valign="middle" rowspan="3" align="center">Green leaf area<break/>Total number of green leaves<break/>Chlorophyll fluorescence</td>
<td valign="middle" rowspan="3" align="center">QGLFA9.6<break/>QTNGL9.1<break/>QCHLF9.13</td>
<td valign="middle" rowspan="3" align="center">
<xref ref-type="bibr" rid="B46">Sabadin et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B45">Rama Reddy et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B17">Fiedler et&#xa0;al., 2014</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">56373379</td>
<td valign="middle" align="center">8.025536867</td>
<td valign="middle" align="center">4.280428888</td>
</tr>
<tr>
<td valign="middle" align="center">56374198</td>
<td valign="middle" align="center">6.378388946</td>
<td valign="middle" align="center">4.424347292</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">10-1</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_10</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_10</td>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
<td valign="middle" rowspan="4" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">27918593</td>
<td valign="middle" align="center">5.81835559</td>
<td valign="middle" align="center">7.428463949</td>
</tr>
<tr>
<td valign="middle" align="center">27918661</td>
<td valign="middle" align="center">6.036030639</td>
<td valign="middle" align="center">7.212369448</td>
</tr>
<tr>
<td valign="middle" align="center">27918667</td>
<td valign="middle" align="center">6.163314405</td>
<td valign="middle" align="center">6.67572531</td>
</tr>
<tr>
<td valign="middle" rowspan="6" align="center">10-2</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="6" align="center">10:41745111&#x2013;52246823</td>
<td valign="middle" rowspan="6" align="center">Green leaf area</td>
<td valign="middle" rowspan="6" align="center">QGLFA10.2</td>
<td valign="middle" rowspan="6" align="center">
<xref ref-type="bibr" rid="B23">Haussmann et&#xa0;al., 2002</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">44310626</td>
<td valign="middle" align="center">5.48809613</td>
<td valign="middle" align="center">6.205218693</td>
</tr>
<tr>
<td valign="middle" align="center">44329730</td>
<td valign="middle" align="center">5.897243312</td>
<td valign="middle" align="center">6.965896225</td>
</tr>
<tr>
<td valign="middle" align="center">44351912</td>
<td valign="middle" align="center">7.029334136</td>
<td valign="middle" align="center">7.536690866</td>
</tr>
<tr>
<td valign="middle" align="center">44366553</td>
<td valign="middle" align="center">6.232655998</td>
<td valign="middle" align="center">7.053328408</td>
</tr>
<tr>
<td valign="middle" align="center">44427299</td>
<td valign="middle" align="center">6.422957194</td>
<td valign="middle" align="center">7.224057245</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">10-3</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">SDW<sub>STC</sub>20_20</td>
<td valign="middle" align="center">SFW<sub>STC</sub>20_20</td>
<td valign="middle" rowspan="3" align="center">10:45658506&#x2013;51995783</td>
<td valign="middle" rowspan="3" align="center">Green leaf area</td>
<td valign="middle" rowspan="3" align="center">QGLFA10.3</td>
<td valign="middle" rowspan="3" align="center">
<xref ref-type="bibr" rid="B23">Haussmann et&#xa0;al., 2002</xref>
</td>
</tr>
<tr>
<td valign="middle" align="center">46853453</td>
<td valign="middle" align="center">6.405686191</td>
<td valign="middle" align="center">6.018533018</td>
</tr>
<tr>
<td valign="middle" align="center">46853558</td>
<td valign="middle" align="center">7.520008804</td>
<td valign="middle" align="center">7.200200734</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>See <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> notes for other abbreviations.</p>
</fn>
<fn>
<p>1&#x2013;1 etc.: the first digit indicates sorghum chromosome number, and the second the locus order number. QTL location before 2019 was from the Sorghum QTL Atlas (<xref ref-type="bibr" rid="B34">Mace et&#xa0;al., 2019</xref>).</p>
</fn>
<fn>
<p>GR, germination rate; CK, control.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<title>Colocation with previously mapped drought-related QTLs</title>
<p>Eleven (1-1, 1-3, 2-1, 3-3, 4-1, 6-1, 6-2, 7-2, 9-3, 10-2, and 10-3) of the 22 loci were colocated with 23 previously mapped QTLs (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). Among the 23 QTLs, 15 were associated with drought-related leaf features: nine (QGLFA2.2, QGLFA3.3, QGLFA3.5, QGLFA3.4, QGLFA4.1, QGLFA6.1, QGLFA9.6, QGLFA10.2, and QGLFA10.3) were associated with green leaf area, four (QTNGL1.2, QTNGL3.3, QTNGL3.4, and QTNGL9.1) were associated with the total number of green leaves, and two (QCHLF6.8 and QCHLF9.13) were associated with chlorophyll content (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). Among the 11 loci, 1&#x2013;1 and 3&#x2013;2 were each colocated with five QTLs, while 2&#x2013;1 and 9&#x2013;3 were each colocated with three QTLs; the rest were colocated with one QTL (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
</sec>
<sec id="s3_4">
<title>Candidate genes identified by linked SNPs</title>
<p>Candidate genes were identified because they had linked SNP markers that landed in coding, or 5&#x2032;/3&#x2032; regions, or were closest to the linked SNPs. Using these criteria, we found 19 candidate genesmacross 12 of the 22 loci (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). Five candidate genes &#x2013;a transporter (Sobic.001G323600) in locus 1-3, a UDP-glucosyl transferase (Sobic.004G087300) in locus 4-2, and three aldo/keto reductases (Sobic.006G096000, Sobic.006G096100, and Sobic.006G096200) in locus 6-2 &#x2013;showed consistently high expression in the roots based on data available from GeneAtlas v2 FPKM (<xref ref-type="bibr" rid="B37">McCormick et al., 2018</xref>). In addition, a nucleoporin gene&#xa0;(Sobic.006G011700) displayed shoot-specific expression (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S6</bold>
</xref>). Haplotypes based on the three SNPs (46613461, 46613645, and 46615325) located in the promoter and coding regions of Sobic.006G096100 in locus 6-2 showed that IS 30533 had TTC while IS 34239 had CCT at these positions (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S7</bold>
</xref>).</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Candidate genes identified in this study.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Locus</th>
<th valign="top" align="left">Top SNPs</th>
<th valign="top" align="left">Trait</th>
<th valign="top" align="left">Candidate gene</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1-1</td>
<td valign="top" align="left">8175770<break/>8175846<break/>8181926</td>
<td valign="top" align="left">SDW<sub>STC</sub>20_20<break/>SFW<sub>STC</sub>20_20</td>
<td valign="top" align="left">Sobic.001G106400 E3 ubiquitin-protein ligase FANCL<break/>Sobic.001G106200 HOMEOBOX PROTEIN KNOTTED-1-LIKE 1/KN1</td>
</tr>
<tr>
<td valign="top" align="left">1-3</td>
<td valign="top" align="left">61062232<break/>61067704<break/>61067917</td>
<td valign="top" align="left">SFWPEG20_20<break/>SLPEG20_20</td>
<td valign="top" align="left">Sobic.001G323600 Polyol transporter<break/>Sobic.001G323500 DUF789</td>
</tr>
<tr>
<td valign="top" align="left">2-1</td>
<td valign="top" align="left">49420951<break/>49421672<break/>49422838</td>
<td valign="top" align="left">RFW<sub>STC</sub>20_20<break/>SL<sub>STC</sub>20_20<break/>SDW<sub>STC</sub>20_20<break/>SFW<sub>STC</sub>20_20</td>
<td valign="top" align="left">Sobic.002G159900 chloroplastic phosphoenolpyruvate/phosphate translocator 1</td>
</tr>
<tr>
<td valign="top" align="left">4-1</td>
<td valign="top" align="left">335179<break/>340675<break/>340847</td>
<td valign="top" align="left">RFW<sub>STC</sub>20_20<break/>SL<sub>STC</sub>20_20<break/>SDW<sub>STC</sub>20_20<break/>SFW<sub>STC</sub>20_20<break/>SFWPEG20_20<break/>SDWPEG20_20<break/>SLPEG20_20</td>
<td valign="top" align="left">Sobic.004G004100 Pentatricopeptide (PPR) repeat-containing protein-like<break/>Sobic.004G004200 Regucalcin gene promoter region-related protein<break/>Sobic.004G003700 Myb_DNA-bind_4</td>
</tr>
<tr>
<td valign="top" align="left">4-2</td>
<td valign="top" align="left">7340159<break/>7340188</td>
<td valign="top" align="left">RFW<sub>STC</sub>20_20<break/>SL<sub>STC</sub>20_20<break/>SDW<sub>STC</sub>20_20<break/>SFW<sub>STC</sub>20_20</td>
<td valign="top" align="left">Sobic.004G087300 UDP-glucosyl transferase 73C</td>
</tr>
<tr>
<td valign="top" align="left">5-1</td>
<td valign="top" align="left">14749135<break/>14764206<break/>14790465<break/>14817605<break/>14838313<break/>14851504</td>
<td valign="top" align="left">SLPEG20_20<break/>SLPEG20_10</td>
<td valign="top" align="left">Sobic.005G094400</td>
</tr>
<tr>
<td valign="top" align="left">5-2</td>
<td valign="top" align="left">20946132<break/>20946153<break/>20946253</td>
<td valign="top" align="left">RFW20<break/>RFWPEG20_10</td>
<td valign="top" align="left">Sobic.005G108300 jasmonic acid-amino synthetase (JAR1)</td>
</tr>
<tr>
<td valign="top" align="left">6-1</td>
<td valign="top" align="left">1683157<break/>1683159<break/>1683181</td>
<td valign="top" align="left">SDW<sub>STC</sub>20_20<break/>SFW<sub>STC</sub>20_20<break/>SDWPEG20_20<break/>SFWPEG20_20</td>
<td valign="top" align="left">Sobic.006G011700 NUCLEOPORIN-RELATED</td>
</tr>
<tr>
<td valign="top" align="left">6-2</td>
<td valign="top" align="left">46599990<break/>46602135<break/>46613461<break/>46613645</td>
<td valign="top" align="left">SDW<sub>STC</sub>20_20<break/>SFW<sub>STC</sub>20_20<break/>SDWPEG20_20<break/>SFWPEG20_20</td>
<td valign="top" align="left">Sobic.006G096000 ALDO/KETO REDUCTASE Sobic.006G096100 ALDO/KETO REDUCTASE<break/>Sobic.006G096200 ALDO/KETO REDUCTASE</td>
</tr>
<tr>
<td valign="top" align="left">8-1</td>
<td valign="top" align="left">4718439<break/>4719344<break/>4726212</td>
<td valign="top" align="left">SDW<sub>STC</sub>20_20<break/>SFW<sub>STC</sub>20_20</td>
<td valign="top" align="left">Sobic.008G047900 HSP20-like chaperone<break/>Sobic.008G048000 Auxin responsive protein</td>
</tr>
<tr>
<td valign="top" align="left">9-2</td>
<td valign="top" align="left">9798734<break/>9799294<break/>9800202</td>
<td valign="top" align="left">SFW<sub>STC</sub>24_10<break/>RFW<sub>STC</sub>24_10</td>
<td valign="top" align="left">Sobic.009G075400 PROTEIN RALF-LIKE 4<break/>Sobic.009G075300 DUF1677</td>
</tr>
<tr>
<td valign="top" align="left">10-1</td>
<td valign="top" align="left">27918593<break/>27918661<break/>27918667</td>
<td valign="top" align="left">SDW<sub>STC</sub>20_10<break/>SFW<sub>STC</sub>20_10</td>
<td valign="top" align="left">Sobic.010G140600 BOLA-LIKE PROTEIN-RELATED</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>In this study, we evaluated a sorghum mini core panel for shoot and root growth under simulated drought conditions imposed by 10%/and 20% PEG. The results showed that certain accessions exhibited enhanced root growth&#x2014;through either increased root number or elongation&#x2014;under osmotic stress. A greater number of accessions produced more roots rather than longer roots when exposed to 10% PEG. However, at 20% PEG, more accessions exhibited longer roots than increased root number, reflecting the adaptability of some accessions to drought stress. These findings are consistent with those of previous studies (<xref ref-type="bibr" rid="B5">Bibi et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B9">de Oliveira et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B48">Schittenhelm and Schroetter, 2014</xref>; <xref ref-type="bibr" rid="B50">Singh and Singh, 1995</xref>). Based on the response of root length and dry weight (RL<sub>STC</sub> and RDW<sub>STC</sub>), IS 30533 was identified as the most drought-tolerant, while IS 32439 was the most sensitive accession. These accessions may be of particular interest for sorghum breeding programs targeting improved drought tolerance.</p>
<p>Drought stress significantly and negatively impacts sorghum growth (<xref ref-type="bibr" rid="B2">Abreha et&#xa0;al., 2022</xref>), especially shoot growth (<xref ref-type="bibr" rid="B24">Jafar et&#xa0;al., 2004</xref>), which was most significantly reduced by PEG treatments as measured by shoot fresh and dry weight STC (SDW<sub>STC</sub> and SFW<sub>STC</sub>) (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). This explains why among the 22 loci identified, 19 were mapped to the STC traits, which reflect the impact on growth, and 17 were mapped to SDW<sub>STC</sub> and SFW<sub>STC</sub>. Half of the mapped loci are also colocated with 23 previously mapped drought-related QTLs; 15 of these 23 QTLs were mapped to green leaf area, total number of green leaves, or chlorophyll content (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). We also found 19 candidate genes for 12 of the 22 loci. Five of those genes show either preferential or specific expression in the roots (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S6</bold>
</xref>). The relevance of some of these candidate genes to drought tolerance is explained in the following sections.</p>
<p>When exposed to drought stress, the immediate response must be to protect the cell. One candidate gene identified in locus 8&#x2013;1 encodes Hsp20, which has been found to be induced by drought stress in sorghum (<xref ref-type="bibr" rid="B1">Abdel-Ghany et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B74">Zhang et&#xa0;al., 2024</xref>). As a small heat shock protein, Hsp20, may form a complex with a variety of non-native proteins to form a first line of defense against protein aggregation during stress (<xref ref-type="bibr" rid="B22">Haslbeck and Vierling, 2015</xref>). Drought also induces transporters for various solutes (<xref ref-type="bibr" rid="B10">Dong et al., 2014</xref>), and we found one polyol transporter in locus 1-3 and a chloroplastic phosphoenolpyruvate/phosphate translocator (PPT) in locus 2-1. a polyol transporter is an H<sup>+</sup>-dependent plasma membrane carrier that transports mannitol and sorbitol, which protect cells against osmotic stress (<xref ref-type="bibr" rid="B49">Shen et al., 1999</xref>) and are induced in grapevines by drought (<xref ref-type="bibr" rid="B8">Conde et al., 2015</xref>). PPT imports phosphoenolpyruvate (PEP) to the plastid from the cytosol. A loss-of-function mutant of PPT1 in <italic>Arabidopsis</italic> results in stunted roots (<xref ref-type="bibr" rid="B54">Staehr et al., 2014</xref>), potentially compromising the ability of roots to cope with drought. Regarding transporters, we identified in locus 6 -1 a nucleoporin that is the main transport channel between the cytoplasm and the nucleoplasm, and a maize nucleoporin, <italic>ZmNUP58</italic>, has been shown to play an important role in the stress response of maize. <italic>ZmNUP58</italic> overexpression in maize significantly promotes both chlorophyll content and activities of antioxidant enzymes under drought conditions (<xref ref-type="bibr" rid="B32">Liu et&#xa0;al., 2022</xref>). Coincidentally, a chlorophyll fluorescence QTL (QCHLF6.8) (<xref ref-type="bibr" rid="B17">Fiedler et&#xa0;al., 2014</xref>) is also colocated in this locus (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>), demonstrating the effectiveness of drought QTL mapping using the mini core panel in this study. In sorghum, the stay-green trait contributes to the adaptation to post-flowering drought conditions (<xref ref-type="bibr" rid="B2">Abreha et&#xa0;al., 2022</xref>). Since drought reduces sorghum leaf chlorophyll content (<xref ref-type="bibr" rid="B26">Kapanigowda et&#xa0;al., 2013</xref>), increased chlorophyll content during drought is a sign of drought tolerance (<xref ref-type="bibr" rid="B27">Kassahun et&#xa0;al., 2010</xref>). For this reason, we found at least five QTL clusters from six studies in which stay-green loci overlap with chlorophyll content loci: one each on chromosomes 2 and 10, and three on chromosome 3 (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S8</bold>
</xref>).</p>
<p>Sorghum also exhibits physiological and biochemical resistance to drought by scavenging reactive oxygen species (ROS) and changing the activity of its antioxidant enzymes (<xref ref-type="bibr" rid="B33">Liu et&#xa0;al., 2024</xref>). For ROS scavenging, a BolA protein identified in locus 10 -1 may play a negative role in ROS scavenging, as a mutation in <italic>Arabidopsis BolA</italic> causes the plant to produce longer roots and to scavenge ROS, implying an increased capacity to extract deeper soil water (<xref ref-type="bibr" rid="B41">Qin et al., 2015</xref>). Another example of a ROS scavenger (<xref ref-type="bibr" rid="B72">Yu et al., 2020</xref>) is the three aldo-keto reductases (AKR) in locus 6-2, which are mostly expressed in the roots (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table S6</bold>
</xref>). In tomatoes, the majority of <italic>AKR</italic> genes are induced by drought treatments, and silencing <italic>AKR</italic> expression reduces drought tolerance due to low proline content and high malondialdehyde content, indicating <italic>AKR</italic>s&#x2019; positive role in regulating drought tolerance in tomatoes (<xref ref-type="bibr" rid="B20">Guan et&#xa0;al., 2023</xref>). So is the E3 ubiquitin-protein ligase in locus 1-1. A rice U-box E3 ubiquitin ligase (<italic>OsPUB67</italic>) was significantly induced by drought, and its overexpression enhances the reactive oxygen species scavenging ability and stomatal closure, which improves drought tolerance (<xref ref-type="bibr" rid="B40">Qin et al., 2020</xref>). For antioxidant activities, we found a UDP-glucosyl transferase (UGT) in locus 4-2. Overexpressing two <italic>Arabidopsis</italic> UGTs, <italic>UGT79B2</italic> and <italic>UGT79B3</italic>, increases drought tolerance thanks to increased anthocyanin accumulation and enhanced antioxidant activity in coping with drought (<xref ref-type="bibr" rid="B30">Li et al., 2017</xref>), and similar results have also been reported in rice (<xref ref-type="bibr" rid="B11">Dong et al., 2020</xref>).</p>
<p>The last candidate gene to be described is <italic>jasmonic acid-amino synthetase1</italic> (<italic>JAR1</italic>) in locus 5-2. Jasmonic acid (JA) is of central importance in drought stress responses (<xref ref-type="bibr" rid="B67">Wasternack, 2014</xref>). <italic>JAR1</italic> is involved in conjugating JA to Ile, the bioactive form of JA (<xref ref-type="bibr" rid="B55">Staswick and Tiryaki, 2004</xref>). <italic>JAR1</italic> plays a major role in JA signaling (<xref ref-type="bibr" rid="B28">Kazan and Manners, 2008</xref>), and its expression is upregulated in the early stages of drought and decreased upon persistent drought (<xref ref-type="bibr" rid="B7">Chen et&#xa0;al., 2019</xref>). Overexpressing <italic>JAR1</italic> reduces water loss during drought, while its mutation lowers JA&#x2013;Ile content and causes hypersensitivity to drought (<xref ref-type="bibr" rid="B35">Mahmud et&#xa0;al., 2022</xref>).</p>
<p>In conclusion, we evaluated a sorghum mini core panel for tolerance to drought simulated by PEG. We confirmed results from previous studies that sorghum plants produced more roots than longer roots at 10% PEG, but at 20% PEG, they produced longer roots than more roots, and PEG reduced shoot growth in all accessions in both years. GWAS identified 22 loci, 19 of which were mapped to the STC traits, and 17 of the 19 were mapped to the STC of shoot weight. Eleven of the 22 loci were colocated with 15 QTLs that had been previously mapped to green leaf area, the total number of green leaves, or chlorophyll content. Of the 19 candidate genes from the 12 loci mapped, five showed either preferential or specific expression in the roots according to GeneAtlas v2. One of the candidate genes from locus 6-1, colocated with a previously mapped chlorophyll fluorescence QTL, was found to increase chlorophyll fluorescence in another study. Sorghum leaf chlorophyll content is closely associated with drought tolerance. IS 30533 was the most tolerant accession, and IS 32439 was the most sensitive accession. The results from this study will facilitate sorghum marker-assisted breeding for drought tolerance.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>.</p>
</sec>
<sec id="s6" sec-type="author-contributions">
<title>Author contributions</title>
<p>HM: Data curation, Writing &#x2013; review &amp; editing. KW: Data curation, Writing &#x2013; review &amp; editing. TW: Data curation, Writing &#x2013; review &amp; editing. XC: Data curation, Writing &#x2013; review &amp; editing. EH: Software, Writing &#x2013; review &amp; editing. YW: Writing &#x2013; review &amp; editing, Data curation. DH: Writing &#x2013; review &amp; editing, Data curation. YW: Software, Writing &#x2013; original draft, Methodology. LW: Software, Writing &#x2013; original draft, Methodology.</p>
</sec>
<sec id="s7" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by the National Natural Science Foundation of China (32372134), PhD Stable Talent Funding (No. NXWD202401), and the Chuzhou &#x201c;Star of Innovation and Entrepreneurship&#x201d; Industrial Innovation Team.</p>
</sec>
<sec id="s8" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s9" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fpls.2025.1629615/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpls.2025.1629615/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Image1.pdf" id="SF1" mimetype="application/pdf"/>
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<supplementary-material xlink:href="Table2.xlsx" id="SM2" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="Table3.xlsx" id="SM3" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="Table4.xlsx" id="SM4" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="Table5.xlsx" id="SM5" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="Table6.xlsx" id="SM6" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="Table7.xlsx" id="SM7" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
<supplementary-material xlink:href="Table8.xlsx" id="SM8" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
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