JXB Advance Access originally published online on December 14, 2006
Journal of Experimental Botany 2007 58(2):327-338; doi:10.1093/jxb/erl225
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RESEARCH PAPER |
Sorghum stay-green QTL individually reduce post-flowering drought-induced leaf senescence
1Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas 77843, USA
2Molecular Genetics and Plant Genomics Laboratory, Department of Plant and Soil Science, Texas Tech University, Lubbock, Texas 79409-2122, USA
3Department of Primary Industries and Fisheries, Hermitage Research Station, Warwick, Queensland 4370, Australia
4Texas A&M University Agricultural Research and Extension Center, Lubbock, Texas 79401, USA
5Division of Plant Sciences and Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, Missouri 65211, USA
6Department of Horticultural Sciences and Institute for Plant Genomics and Biotechnology, Texas A&M University, College Station, Texas 77843, USA
7USDA-ARS, Southern Plains Agricultural Research Center, College Station Texas 77845, USA
* To whom correspondence should be addressed. E-mail: andrew.borrell{at}dpi.qld.gov.au
Received 23 December 2005; Accepted 9 October 2006
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Abstract |
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Sorghum is an important source of food, feed, and biofuel, especially in the semi-arid tropics because this cereal is well adapted to harsh, drought-prone environments. Post-flowering drought adaptation in sorghum is associated with the stay-green phenotype. Alleles that contribute to this complex trait have been mapped to four major QTL, Stg1–Stg4, using a population derived from BTx642 and RTx7000. Near-isogenic RTx7000 lines containing BTx642 DNA spanning one or more of the four stay-green QTL were constructed. The size and location of BTx642 DNA regions in each RTx7000 NIL were analysed using 62 DNA markers spanning the four stay-green QTL. RTx7000 NILs were identified that contained BTx642 DNA completely or partially spanning Stg1, Stg2, Stg3, or Stg4. NILs were also identified that contained sub-portions of each QTL and various combinations of the four major stay-green QTL. Physiological analysis of four RTx7000 NILs containing only Stg1, Stg2, Stg3, or Stg4 showed that BTx642 alleles in each of these loci could contribute to the stay-green phenotype. RTx7000 NILs containing BTx642 DNA corresponding to Stg2 retained more green leaf area at maturity under terminal drought conditions than RTx7000 or the other RTx7000 NILs. Under post-anthesis water deficit, a trend for delayed onset of leaf senescence compared with RTx7000 was also exhibited by the Stg2, Stg3, and Stg4 NILs, while significantly lower rates of leaf senescence in relation to RTx7000 were displayed by all of the Stg NILs to varying degrees, but particularly by the Stg2 NIL. Greener leaves at anthesis relative to RTx7000, indicated by higher SPAD values, were exhibited by the Stg1 and Stg4 NILs. The RTx7000 NILs created in this study provide the starting point for in-depth analysis of stay-green physiology, interaction among stay-green QTL and map-based cloning of the genes that underlie this trait.
Key words: Drought adaptation, NIL, sorghum, stay-green QTL
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Introduction |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionReferences |
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Sorghum [Sorghum bicolor (L.) Moench] is the fifth most important cereal crop world-wide (http://apps.fao.org/default.jsp) as well as an important source of feed, fibre, and biofuel (Doggett, 1988). Sorghum, like maize and sugarcane, carries out C4 photosynthesis, a specialization that makes these grasses well adapted to environments subject to high temperature and water limitation (Edwards et al., 2004). Sorghum is an important target of genome analysis among the C4 grasses because the sorghum genome is relatively small (
818 Mbp) (Price et al., 2005), the cultivated species is diploid (2n=20) and the sorghum germplasm is diverse (Dje et al., 2000; Menz et al., 2004; Casa et al., 2005). As a consequence, numerous sorghum genetic, physical, and comparative maps have been constructed (Tao et al., 1998; Boivin et al., 1999; Peng et al., 1999; Klein et al., 2000, 2003; Haussmann et al., 2002a; Menz et al., 2002; Bowers et al., 2003, 2005), a sorghum EST project (Pratt et al., 2005) and associated microarray analyses of sorghum gene expression have been carried out (Buchanan et al., 2005; Salzman et al., 2005), and a comprehensive analysis of sorghum chromosome architecture has been completed (Kim et al., 2005). This genome infrastructure has enabled map-based cloning of Rf1 (Klein et al., 2005) and analysis of genes that control other important sorghum traits (Lin et al., 1995; Pereira and Lee, 1995; Childs et al., 1997; Tao et al., 2003). Sorghum is better adapted to water-limiting environments compared with most other crops (see reviews by Doggett, 1988; Ludlow and Muchow, 1990; Mullet et al., 2001; Sanchez et al., 2002). This attribute is of great importance as the demand for food and water supplies increases due to world population growth (Khush, 1999; Gleick, 2003). Two distinct drought-stress responses have been identified in sorghum (Rosenow and Clark, 1981, 1995; Rosenow, 1983): a pre-flowering drought response that occurs prior to anthesis and a post-flowering drought response that is observed when water limitation occurs during the grain-filling stage. Symptoms of post-flowering drought-stress susceptibility include premature leaf and plant senescence, stalk lodging and charcoal rot, and a reduction in seed size (Rosenow and Clark, 1995). Sorghum genotypes that exhibit resistance to pre-flowering and/or post-flowering drought have been identified (see review by Rosenow and Clark, 1995). Genotypes resistant to post-flowering drought stress were called ‘stay-green’ types because these plants retain chlorophyll in their leaves and maintain the ability to carry out photosynthesis longer than ‘senescent’ genotypes under terminal drought conditions. This phenotype is distinct from ‘cosmetic’ stay-green, which is characterized by senescing leaves that retain chlorophyll but lose the capacity to carry out photosynthesis (see reviews by Thomas and Smart, 1993; Thomas and Howarth, 2000; Cha et al., 2002). The stay-green genotypes also exhibit reduced stalk lodging (Woodfin et al., 1998) and resistance to charcoal rot (Rosenow, 1983).
The physiological basis of the sorghum stay-green trait remains to be clarified. Stay-green genotypes have been found to contain higher cytokinin levels (McBee, 1984; Ambler et al., 1987) and more stem sugars (Duncan et al., 1981; McBee and Miller, 1982; Dahlberg, 1992) than senescent genotypes under certain conditions. In addition, stay-green hybrids assimilate more nitrogen and have higher specific leaf nitrogen than senescent hybrids, suggesting a link between nitrogen status and the stay-green trait (Borrell and Hammer, 2000; Borrell et al., 2001). However, it is unclear if these traits are a cause or a consequence of the stay-green trait, or are secondary traits that are associated with the general adaptation of stay-green genotypes to their agro-ecological zones. While the precise physiological basis of stay-green remains unclear, the positive impact of this trait on yield under terminal drought has been confirmed in several studies (Borrell et al., 2000b; Jordan et al., 2003). Moreover, this trait has little, if any, yield penalty when plants are grown under conditions where water is not limiting (Borrell et al., 2000b).
Several sorghum genotypes have been identified that exhibit the stay-green trait (BTx642, SC56, E36-1) (Rosenow, 1983; Kebede et al., 2001; Haussmann et al., 2002b). The genotype BTx642 (formerly B35) has been an especially useful source of stay-green for research (Tuinstra et al., 1997, 1998; Crasta et al., 1999; Subudhi et al., 2000; Tao et al., 2000; Xu et al., 2000) and the development of commercial hybrids (Henzell et al., 2001). BTx642 is derived from IS12555, a durra sorghum from Ethiopia. Genetic studies showed that the BTx642 genes conferring the stay-green trait act with varied levels of dominance (Walulu et al., 1994) or an additive fashion if the onset of senescence was analysed (van Oosterom et al., 1996). Several stay-green QTL mapping studies have been conducted using BTx642 as one of the parents (Tuinstra et al., 1996, 1997, 1998; Crasta et al., 1999; Subudhi et al., 2000; Tao et al., 2000; Xu et al., 2000). These studies identified four major QTL designated Stg1, Stg2, Stg3, and Stg4 and many additional minor QTL that can modulate expression of the stay-green trait. Stg1 and Stg2 were located on LG-03 and explained 20% and 30% of the phenotypic variability, respectively (Xu et al., 2000; Sanchez et al., 2002). Stg3 was located on LG-02 and Stg4 on LG-05, accounting for 16% and 10% of the phenotypic variance, respectively (Sanchez et al., 2002). The ranking of stay-green QTL based on their contribution to the stay-green phenotype in the BTx642 by RTx7000 population is Stg2>Stg1>Stg3>Stg4 (Xu et al., 2000). In relatively small RIL populations such as those that have been used for mapping stay-green, the influence of an individual QTL on expression of the phenotype can be difficult to quantify because (i) the experiments have limited statistical power to detect QTL (Beavis, 1994; Melchinger et al., 1998), (ii) detection may be influenced by GxE interactions and genetic background effects (Tuinstra et al., 1998), and (iii) the effects of the QTL that are detected tend to be biased upwards (Beavis, 1994; Melchinger et al., 1998).
A number of epistatic interactions among stay-green loci and between stay-green loci and genes in other regions of the sorghum genome have been identified (Subudhi et al., 2000). Near-isogenic lines (NILs) can be used to help clarify complex genetic interactions and phenotypes such as those associated with the stay-green trait. For example, 14 QTL were found to regulate flowering time in a cross of O. sativa japonica and O. sativa indica. Three flowering time QTL, Hd1, Hd3a, and Hd6 were fine mapped using NIL-derived material and the corresponding genes subsequently isolated using a map-based cloning approach (Paran and Zamir, 2003). Therefore, this approach was adopted to facilitate the physiological and genetic analysis of the genes that modulate the stay-green trait associated with BTx642. During the course of these studies, 34 RTx7000 NILs were developed by crossing BTx642 with the senescent genotype RTx7000 followed by subsequent introgression of one or more of the BTx642 stay-green QTL regions into the RTx7000 background. NILs containing Stg1, 2, 3, and 4 were identified and found to have enhanced stay-green related phenotypes relative to RTx7000.
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Materials and methods |
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Generation of RTx7000 NILs containing BTx642 DNA from the stay-green loci
Near-isogenic RTx7000 lines containing one or more of the Stg loci from BTx642 were constructed starting with a cross of BTx642 and RTx7000 followed by repeated backcrossing of F1 plants to RTx7000 either four (6000 NIL series) or six times (2000 NIL series) (Fig. 1).
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Progeny derived from each backcross were screened for one or more of the Stg loci using DNA markers that mapped within or near each locus (Fig. 2; DNA markers with arrows). For example, progeny containing BTx642 DNA spanning Stg1 were identified using the markers NPI414, Xtxs1114, and BNL15.20 (Fig. 2; markers in bold with arrows to the right). As a consequence several RTx7000 NILs were generated that contain a block of BTx642 DNA spanning Stg1 (Fig. 2, NILs 6078-1, 6086-3, 6102-23, 6100-7). Similarly, NILs containing BTx642 DNA corresponding to Stg2, Stg3, and/or Stg4 were generated using Xtxs584, RZ323, CSU58, A12-420 (Stg2), Xtxs1307, Xtxs1111, UMC5 (Stg3), and Xtxs713 (Stg4) (Fig. 2). Selection was continued until the BC4 or BC6 generation where the lines were selfed to create BC4F2–4 or BC6F2–4 lines.
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DNA extraction and DNA marker analysis
Genomic DNA of IS3620C, BTx623, BTx642, and RTx7000 was extracted from sorghum leaf tissue with a FastDNA kit using a FastPrep FP120 homogenizer according to the manufacturer's instructions (Qbiogene, Irvine, CA, USA). DNA was purified using a GENECLEAN Turbo kit (Qbiogene). AFLP template was prepared according to Vos et al. (1995), using the restriction enzymes EcoRI and MseI. DNA template preparation, amplification and visualization of amplified AFLP products were performed as described by Klein et al. (2000). The following EcoRI and MseI primer combinations were used for AFLP analysis: E-ACC+M-CGG, E-ACC+M-CTA, E-ACC+M-CTC, E-AGT+M-CTA, E-AGT+M-CTG, E-CTG+M-CAC, E-CTG+M-CCC, E-CTG+M-CTG, E-GAA+M-CAA, E-GAA+M-CAT, E-GAA+M-CCG, E-GAA+M-CTG, E-GGA+M-CAA, E-GGA+M-CAG, E-GGA+M-CTC, E-TAC+M-CTT, E-TGA+M-CCT, E-TGA+M-CTA, and E-TGA+M-CTG.
SSRs were amplified and analysed using fluorescent IRD-labelled primers obtained from Li-Cor (Lincoln, NE, USA) as described by Klein et al. (2000) or 5' HEX (IDT, Coralville, IA, USA) forward-labelled primers. PCR reaction conditions were identical for both primer substrates, except that the concentrations of forward and reverse primers were 2.5 pmol µl–1 for HEX-labelled primers and 1 pmol µl–1 for IRD-labelled primers. Data were analysed with Gene Scan version 3.7 Fragment Analysis Software (Applied Biosystems, Foster City, CA, USA) and peaks were scored manually using the Genotyper version 3.7 Fragment Analysis Software (Applied Biosystems). SSR primer sequences and amplification product sizes are listed at http://sorgblast2.tamu.edu/. Sixty-two of the 113 AFLP and SSR markers analysed mapped within one of the stay-green QTL. Markers outside these regions were also analysed to provide a random background survey of NIL genotypes.
Screening RTx7000 NILs for the stay-green phenotype
Four of the RTx7000 NILs contained BTx642 DNA spanning all, or a portion, of only Stg1, Stg2, Stg3, or Stg4. These NILs were targeted for further physiological analysis to determine if the BTx642 DNA introgressed into each of these NILs contained genes that would contribute to the stay-green trait independent of the other Stg loci.
Field experiments to characterize the NILs physiologically were conducted at the Hermitage Research Station (altitude 480 m, 28°10' S, 152°02' E) in Australia's north-eastern grain belt in two consecutive seasons: Experiment 1 (2004) and Experiment 2 (2005). Both experiments consisting of the Stg NILs and RTx7000 were grown at a rain-out shelter facility on a cracking and weakly self-mulching brownish-black clay (Talgai shallow phase; McKeown, 1978; Ug 5.14; Northcote, 1974). The experiment site has a slope of about 2% and the profile is moderately well drained. The experiment design was a randomized split block, with two density treatments (main plots) split by different genotypes (subplots). The experiments were replicated four times. Fertilizers were applied so that crop growth was not limited by nutrients in either treatment. Main plots were 3 mx12.5 m and subplots were 2 m (4 rows)x3 m. The main treatments were high density (20 plants m–2; HD) and low density (10 plants m–2, LD). Irrigation was applied to both treatments until 16 (Experiment 1) and 24 (Experiment 2) days before anthesis, after which time no more water was applied, creating a terminal water deficit. Terminal stress typifies the dry season of the semiarid tropics, where crops are usually grown solely on stored soil moisture in heavy soils, with the crop maturing progressively on a depleted soil moisture profile. The severity of drought was greater in Experiment 1 than in Experiment 2, due to earlier planting of the experiment in the 2004 season (11 December 2003) compared with the 2005 season (21 January 2005). Five of the six genotypes will be discussed in this paper: 6078-1 (Stg1 NIL), 2219-3 (Stg2 NIL), 2290-19 (Stg3 NIL), 6085-9 (Stg4 NIL), and RTx7000 (recurrent parent). The Stg4 NIL (6085-9) was grown only in Experiment 2.
Absolute rate of leaf senescence was calculated as the slope of the linear decline over time from anthesis to maturity (cm2 m–2 d–1). Relative rate of leaf senescence was calculated from the slope of the linear decline over time from anthesis to maturity of green leaf area, relative to green leaf area at anthesis, expressed as the loss of relative leaf area (%) d–1: [(1–GLAM/GLAA)x100]/days from anthesis to maturity, where GLAM is the green leaf area at maturity (cm2 m–2) and GLAA is the green leaf area at anthesis (cm2 m–2). In addition, leaf greenness, an integrated measure of the stay-green phenotype, was recorded on the leaf below the flag (FL-1) throughout the grain-filling period in the 2005 season. A Minolta chlorophyll meter (SPAD-502) was used to measure the greenness of FL-1 from four tagged plants in each plot at weekly intervals. Three measurements were taken down one side of the leaf at the base, centre and tip, approximately 1 cm from the leaf edge. Broken-stick functions were fitted to the individual plot data for the SPAD regression on time (d) and the following coefficients were determined:
- a=value of the asymptote (benchmark of leaf greenness at anthesis);
- b=slope of the first linear phase of the broken-stick function (fixed at zero);
- c=slope of the second linear phase of the broken-stick function (rate of decline in SPAD with senescence); and
- d=intersection of the two linear phases of the broken-stick function (onset of leaf senescence).
- b=slope of the first linear phase of the broken-stick function (fixed at zero);
Leaf greenness at maturity (SPADm) can be described mathematically by adapting ‘Equation 4’ from Borrell et al. (2000a), initially used to estimate green leaf area at maturity:
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Statistical analyses associated with phenotyping
The data were analysed using linear mixed models including fixed treatment terms (plant density, genotype, and their interaction) and random terms to reflect the blocking structure of the design (replicate, mainplot, subplot, and the appropriate interactions between these terms). In addition, the model accommodated error variance heterogeneity between the rain-out shelters.
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Results |
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Aligning stay-green loci mapped in BTx642/RTx7000 to the BTx623/IS3620C genetic map
Xu et al. (2000) utilized 98 F7 RIL lines derived from a cross of BTx642 and RTx7000 to map four major stay-green loci segregating in this population. The stay-green loci were located on a genetic map that spanned
837 cM based on the analysis of 162 RFLP markers (Xu et al., 2000). To assist further analysis of the stay-green loci identified by Xu et al. (2000), the regions of the sorghum genome spanning Stg1–Stg4 were located on the 1713 cM high density genetic map developed by Menz et al. (2002) based on 137 RILs derived from BTx623/IS3620C. There were several DNA markers located near or within the stay-green loci that were common to both genetic maps. For example, five DNA markers located near or within Stg1 and Stg2 on the BTx642/RTx7000 linkage map were located on LG-03 of the BTx623/IS3620C linkage map (Fig. 2; markers in bold; Xtxs584, Xtxs1175, Xtxs422, Xtxs1927, and BNL15.20). Similarly, several DNA markers spanning Stg3 and Stg4 on the BTx642/RTx7000 map were also located on the BTx623/IS3620C linkage map (Fig. 2, markers in bold; Xtxs1162, Xtxs1111, UMC5, UMC116, Xtxs713, and Xtxs387). Having aligned the two maps in the syntenic regions spanning Stg1–Stg4, additional information was collected to define the boundaries of each QTL on the BTx623/IS3620C map. The stay-green QTL were mapped in the BTx642/RTx7000 RIL population using phenotypic data collected from several geographical regions and in different years (Xu et al., 2000). As a consequence, the size and location of the stay-green loci mapped in the different studies varied to some extent (Xu et al., 2000). Due to this variation, a composite interval defined by all of the QTL studies was located on the BTx623/IS3620C map. The size and location of each stay-green QTL on the BTx623/IS3620C map was estimated based on DNA markers common to both maps, and the ratio of recombination observed between aligned regions of the two maps spanning the stay-green loci (Fig. 2; white regions labelled Stg1–Stg4). This analysis showed that each of the four stay-green loci spanned a maximum of 10–30 cM on the BTx623/IS3620C map.
Generation of RTx7000 NILs containing BTx642 DNA from the stay-green loci
Near-isogenic RTx7000 lines containing one or more of the Stg loci from BTx642 were constructed starting with a cross of BTx642 and RTx7000 followed by repeated backcrossing of F1 plants to RTx7000 either four (6000 NIL series) or six times (2000 NIL series) (Fig. 1). Thirty-four RTx7000 NILs were analysed using a total of 113 AFLP and SSR markers (Fig. 2). Sixty-two of the DNA markers used in the analysis were located either within or adjacent to each stay-green locus. This provided information on the size and location of the BTx642 DNA regions that had been introgressed into each RTx7000 NIL (Fig. 2, regions marked in white). Several NILs did not contain BTx642 DNA that overlapped with a stay-green QTL and were eliminated from further analysis. In addition, several NILs had similar BTx642 introgression patterns, therefore, only one example of each of these NILs is shown in Fig. 2 (see figure legend). The patterns of BTx642 introgression in the resulting 18 NILs are shown in Fig. 2. Four NILs contained BTx642 DNA that spanned Stg1 (Fig. 2, 6078-1, 6083-3, 6102-23, 6100-7). Among these NILs, 6078-1, designated a Stg1 NIL, contained BTx642 DNA spanning Stg1 but none of the other Stg loci. Nine NILs contained BTx642 DNA spanning nearly all or a subportion of the Stg2 QTL (Fig. 2). Stg2 NIL, 2219-3, contained BTx642 DNA that spanned most of the Stg2 locus (104.8 to 111.6–118 cM) plus a region flanking the Stg2 locus (65 cM to 104.8 cM) but none of the other Stg loci. A similar analysis identified 2290-19 as a Stg3 NIL and 6085-9 as a Stg4 NIL. Furthermore, several NILs were identified that contained BTx642 DNA that spanned all or a portion of two or more Stg loci (i.e. 6086-3=Stg1+Stg2; 6098-15=Stg2+Stg4). It was also noted that for a few NILs, DNA in some regions was heterozygous or heterogeneous (i.e. NIL 2230-5, Stg3 region) (Fig. 2; marked by 
width white bars).
Screening RTx7000 NILs for the stay-green phenotype
Rate of leaf senescence:
Genotypexdensity interactions were not significant at P=0.05 for the absolute rate of leaf senescence (aRATEsen) in Experiment 1 or 2 (Table 1). In Experiment 1, aRATEsen was higher (P <0.01) in RTx7000 (715 cm2 m–2 d–1) than in Stg2 (518 cm2 m–2 d–1) or Stg3 (578 cm2 m–2 d–1) NILs. In Experiment 2, aRATEsen was higher in RTx7000 (612 cm2 m–2 d–1) compared with all of the Stg NILs (Stg2=Stg3 >Stg4 >Stg1).
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No genotypexdensity interaction (P <0.05) was observed for the relative rate of leaf senescence (rRATEsen) in Experiment 1, although the interaction was significant (P <0.01) in Experiment 2. In Experiment 1, rRATEsen was less in the Stg2 NIL (2.01%) compared with RTx7000 (2.69%), and Stg1 (2.58%) and Stg3 (2.55%) NILs. In Experiment 2, rRATEsen was less in Stg2 (1.26%) and Stg4 (1.26%) NILs compared with the Stg3 NIL (1.38%) under HD, although none of the NILs was significantly different from RTx7000 (1.33%). However, under the LD treatment, rRATEsen was higher in RTx7000 (1.36%) than in Stg1 (1.14%) and Stg2 (1.18%) NILs.
Green leaf area at maturity (GLAM):
Genotype and density did not interact for GLAM in Experiment 1, although the interaction was significant (P <0.01) in Experiment 2 (Table 1). In Experiment 1, GLAM was higher in the Stg2 NIL (6644 cm2 m–2) compared with all other genotypes. There was, however, a trend for higher GLAM in Stg1 (2125 cm2 m–2) and Stg3 (2112 cm2 m–2) NILs compared with RTx7000 (1292 cm2 m–2). In Experiment 2, RTx7000 was no different than any other genotype in GLAM under HD (3732 cm2 m–2), although there was a trend for lower GLAM in Stg1 (3363 cm2 m–2) and Stg3 (2047 cm2 m–2) NILs, and higher GLAM in Stg2 (5765 cm2 m–2) and Stg4 (4652 cm2 m–2) NILs, relative to RTx7000. Under LD, GLAM was higher in Stg1 (8440 cm2 m–2) and Stg2 (7356 cm2 m–2) NILs compared with RTx7000 (2524 cm2 m–2), with a trend for higher GLAM also observed for Stg3 (3753 cm2 m–2) and Stg4 (4188 cm2 m–2) NILs.
Components of leaf greenness (Experiment 2 only):
The interactions between genotype and density were not significant at P=0.05 for any of the components of leaf greenness, hence only main effect data will be presented (Table 2; Fig. 3). SPAD at 67 d after anthesis (DAA) on FL-1 was higher in the Stg2 NIL (28.9) than in RTx7000 (17.3), although there was also a trend for higher leaf greenness in Stg1 (22.8) and Stg4 (22.1) NILs. Components of SPAD at 67 DAA (physiological maturity) were derived as coefficients of broken-stick functions fitted to regressions of SPAD on time (d) after anthesis (see Materials and methods for details). The observed SPAD values at 67 DAA were highly correlated (r2=0.98) with predicted SPAD values at 67 DAA (SPADm) calculated using broken-stick functions (Fig. 4). SPAD at anthesis (SPADa), the asymptote of the first linear phase of the broken-stick function (coefficient ‘a’), represents the initial benchmark of leaf nitrogen prior to the commencement of senescence. SPADa was higher in Stg1 (56.7) and Stg4 (56.0) NILs compared with RTx7000 (53.9), with a trend for higher SPADa in the Stg3 NIL (54.7). RTx7000 did not differ from any of the NILs in Ratesen (0.96 d–1), the rate of loss of SPAD d–1 following the onset of leaf senescence (coefficient ‘c’). However, there was a trend for lower rates of senescence in Stg1 (0.89 d–1) and Stg2 (0.76 d–1) NILs. In fact, the Ratesen observed in the Stg2 NIL (0.76 d–1) was significantly less than that observed for the Stg3 NIL (1.05 d–1) in this parameter. Similarly, RTx7000 (26.8 DAA) did not vary from the NILs in onset of leaf senescence (coefficient ‘d’), although a trend for delayed onset of senescence was observed in Stg2 (31.8 DAA), Stg3 (29.3 DAA), and Stg4 (28.5 DAA) NILs. SPADm was correlated with two of its components: coefficient ‘a’ (SPAD at anthesis, r=0.45, n=40, P <0.01) and coefficient ‘c’ (rate of loss of SPAD d–1, r= –0.75, n=40, P <0.001), but not with coefficient ‘d’ (onset of senescence, r=0.17, n=40).
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Discussion |
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TopAbstractIntroductionMaterials and methodsResultsDiscussionReferences |
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The long-term goal of this research is to understand the physiological basis of the sorghum stay-green trait and to identify the genes that contribute to this trait in different sorghum genotypes. Prior studies on the BTx642 source of stay-green identified numerous QTL that modulate expression of the trait (Tuinstra et al., 1997; Tao et al., 2000; Xu et al., 2000). Some of these QTL, such as Stg1–Stg4, are consistently expressed in a range of environments and in different genetic backgrounds (Tuinstra et al., 1997; Crasta et al., 1999; Subudhi et al., 2000; Xu et al., 2000). However, because the stay-green trait is expressed during grain-filling and involves leaf senescence, there are many secondary factors that can modulate this trait. For example, differences in flowering time and reproductive sink strength, in addition to variation in environmental factors, can influence expression of the stay-green trait (Rosenow and Clark, 1995). This complexity is consistent with our current understanding of the regulatory systems that modulate plant and leaf senescence now being revealed through genetic and genomic analyses (see reviews by Buchanan-Wollaston et al., 2003; Yoshida, 2003). As a consequence, an in-depth analysis of the genetic and physiological basis of the sorghum stay-green trait requires the generation of a series of near-isogenic ‘senescent’ lines containing one or more of the stay-green loci.
This report describes the development of 18 different RTx7000 BC4–6F2–4 NILs that contain introgressed regions of BTx642 DNA. Detailed genetic analysis of the RTx7000 NILs showed that these lines contain BTx642 DNA spanning all or a portion of the four major stay-green loci, Stg1–Stg4, previously identified in a cross of RTx7000 and BTx642 (Subudhi et al., 2000; Xu et al., 2000). Several of the RTx7000 NILs contained blocks of BTx642 DNA that partially or completely spanned a stay-green locus plus a variable amount of DNA flanking the target locus. The results of marker-assisted selection can be attributed to the stochastic nature of recombination and the limited availability of DNA markers at the start of this project. For example, the three DNA markers used for introgression of BTx642 DNA corresponding to Stg2 were derived from one edge of this QTL and DNA adjacent to the QTL. As a consequence, most of the RTx7000 NILs containing BTx642 corresponding to Stg2 spanned only a portion of this locus (Fig. 2). Similarly, only a single DNA marker, Xtxs713 was used to identify BTx642 DNA introgressions corresponding to Stg4 and therefore the resulting Stg4 NILs contained BTx642 DNA that spanned only a portion of this QTL (Fig. 2). Nevertheless, the subset of RTx7000 NILs containing BTx642 DNA that span different portions of each stay-green QTL will be useful for further delimiting these loci in follow up experiments.
RTx7000 NILs containing BTx642 DNA spanning only Stg1 (6078-1), Stg2 (2219-3), Stg3 (2290-19) or Stg4 (6085-9) were identified among the original set of 34 NILs constructed during this project. NIL 6078-1 contained BTx642 DNA that completely spans Stg1. However, 2219-3, 2290-19, and 6085-9 NILs contained BTx642 DNA that spanned most, but not all, of the associated QTL. Fortunately, physiological analysis of these four RTx7000 NILs showed that each of these NILs included BTx642 alleles that could contribute to the stay-green trait. While it is likely that the BTx642 alleles contributing to the observed phenotypes correspond to Stg1–Stg4, all of these NILs contain BTx642 DNA outside of the regions previously identified as containing the QTL. This is not unexpected, as the location of the QTL is inherently uncertain since it relies heavily on the stochastic process of recombination, particularly in small mapping populations. Thus the true location of a particular QTL may be outside of, but linked to, the region identified as its location. Fine mapping studies are underway to confirm these findings and eventually to clone the genes involved.
NIL 2219-3 that contains BTx642 DNA from Stg2 had the highest GLAM under terminal drought conditions among the NILs analysed relative to RTx7000 in both Experiments 1 and 2. Absolute and relative rates of leaf senescence were also lowest in Stg2 among the NILs analysed compared with RTx7000 in both experiments. In addition, measurements of leaf greenness with a chlorophyll meter showed a clear trend for delayed onset and reduced rate of leaf senescence in the Stg2 NIL relative to RTx7000. These results are consistent with prior analysis indicating that Stg2 has the largest influence on the expression of the stay-green phenotype among the four major Stg loci identified in the RTx7000/BTx642 population (Subudhi et al., 2000; Xu et al., 2000). Analysis of the stay-green NILs also indicates that all four stay-green loci derived from BTx642 can contribute to the stay-green phenotype in the absence of the other stay-green loci and other portions of the BTx642 genome. For example, NIL 6078-1 containing BTx642 DNA from Stg1, exhibited (relative to RTx7000) lower absolute and relative rates of leaf senescence in Experiment 2, a trend for higher GLAM in Experiments 1 and 2 (P <0.01, LD only), and higher SPAD at anthesis in Experiment 2. NIL 2290-19 containing BTx642 DNA from Stg3, exhibited (relative to RTx7000) lower absolute rates of leaf senescence in Experiments 1 and 2, a trend for higher GLAM in Experiments 1 and 2, and a trend for higher SPAD at anthesis and delayed onset of leaf senescence in Experiment 2. NIL 6085-9 containing BTx642 DNA from Stg4, was assessed only in Experiment 2; however, this NIL exhibited (relative to RTx7000) a lower absolute rate of leaf senescence, a trend for lower relative rate of leaf senescence, a trend for higher GLAM under LD and HD, higher SPAD at anthesis (P <0.01), and a trend for delayed onset of leaf senescence.
The trend for delayed onset of leaf senescence exhibited by the Stg2, Stg3, and Stg4 NILs in Experiment 2 supports earlier research by Borrell et al. (2000a) who found delayed onset of senescence in A35 hybrids (stay-green) compared with AQL39 hybrids (senescent) under a terminal water deficit. The lower rates of leaf senescence observed in the stay-green NILs, and in particular Stg2, also agree with earlier work by Borrell et al. (2000a). Furthermore, higher SPAD at anthesis in Stg1 and Stg4 NILs in Experiment 2 is consistent with previous studies showing higher specific leaf nitrogen at anthesis (Borrell and Hammer, 2000) and higher SPAD at anthesis (Borrell et al., 2001) in A35 hybrids compared with AQL39 hybrids under a terminal water deficit.
The strong positive correlation (r2=0.98) observed between SPAD measured at 67 DAA and SPAD predicted at 67 DAA (SPADm) suggests that the components of SPADm (SPADa, Durationsen and Ratesen) may provide insights into the functional basis of leaf senescence. The significant correlation (r= –0.75) between SPADm and rate of loss of SPAD (coefficient ‘c’) on the one hand, and the lack of correlation (r=0.17) between SPADm and the onset of leaf senescence (coefficient ‘d’) on the other, indicates that ‘rate’ rather than ‘onset’ of leaf senescence was the more important component of stay-green in this study.
Further physiological studies of these individual NILs will enable the mechanisms causing stay-green to be identified for each of the four genomic regions alone (Stg1, Stg2, Stg3, or Stg4). NILs containing various combinations of Stg1–Stg4 will also be studied, enabling the extent of gene interaction to be assessed for this trait. Ongoing fine-mapping studies should allow the key genes from each region to be identified.
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This research was supported by National Science Foundation Plant Genome Research Grant DBI-0321578 (PEK, RRK, and JEM), by the Texas Agricultural Experiment Station (PEK and JEM), by the USDA-ARS (RRK), by the Grains Research and Development Corporation Grant DAQ520 (AKB), and by the Queensland Department of Primary Industries and Fisheries (AKB and DRJ).
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