Two consensus quantitative trait loci clusters controlling anthesis–silking interval, ear setting and grain yield might be related with drought tolerance in maize

Unravelling the molecular basis of drought tolerance will provide novel opportunities for improving crop yield under water-limited conditions. The present study was conducted to identify quantitative trait loci (QTLs) controlling anthesis–silking interval (ASI), ear setting percentage (ESP) and grain yield (GY). The mapping population included 234 F₂ plants derived from the cross X178 (drought tolerant) × B73 (drought susceptible). The corresponding F_2:3 progenies, along with their parents, were evaluated for the above-mentioned traits under both well-watered and water-stressed field conditions in three different trials carried out in central and southern China. Interval mapping and composite interval mapping identified 45 and 65 QTLs for the investigated traits, respectively. Two QTL clusters influencing ASI and ESP on chromosomes 1 (bin 1.03) and 9 (bins 9.03–9.05) were identified in more than two environments, showing sizeable additive effects and contribution to phenotypic variance; these two QTL clusters influenced GY only in one environment. No significant interaction was detected between the two genomic regions. A comparative analysis of these two QTL clusters with the QTLs controlling maize drought tolerance previously described in three mapping populations confirmed and extended their relevance for marker-assisted breeding to improve maize production under water-limited conditions.     

Exploring Potential of Pearl Millet Germplasm Association Panel for Association Mapping of Drought Tolerance Traits

A pearl millet inbred germplasm association panel (PMiGAP) comprising 250 inbred lines, representative of cultivated germplasm from Africa and Asia, elite improved open-pollinated cultivars, hybrid parental inbreds and inbred mapping population parents, was recently established. This study presents the first report of genetic diversity in PMiGAP and its exploitation for association mapping of drought tolerance traits. For diversity and genetic structure analysis, PMiGAP was genotyped with 37 SSR and CISP markers representing all seven linkage groups. For association analysis, it was phenotyped for yield and yield components and morpho-physiological traits under both well-watered and drought conditions, and genotyped with SNPs and InDels from seventeen genes underlying a major validated drought tolerance (DT) QTL. The average gene diversity in PMiGAP was 0.54. The STRUCTURE analysis revealed six subpopulations within PMiGAP. Significant associations were obtained for 22 SNPs and 3 InDels from 13 genes under different treatments. Seven SNPs associations from 5 genes were common under irrigated and one of the drought stress treatments. Most significantly, an important SNP in putative acetyl CoA carboxylase gene showed constitutive association with grain yield, grain harvest index and panicle yield under all treatments. An InDel in putative chlorophyll a/b binding protein gene was significantly associated with both stay-green and grain yield traits under drought stress. This can be used as a functional marker for selecting high yielding genotypes with ‘stay green’ phenotype under drought stress. The present study identified useful marker-trait associations of important agronomics traits under irrigated and drought stress conditions with genes underlying a major validated DT-QTL in pearl millet. Results suggest that PMiGAP is a useful panel for association mapping. Expression patterns of genes also shed light on some physiological mechanisms underlying pearl millet drought tolerance.     

Quantitative trait loci associated with constitutive traits control water use in pearl millet [Pennisetum glaucum (L.) R. Br.]

There is substantial genetic variation for drought adaption in pearl millet in terms of traits controlling plant water use. It is important to understand genomic regions responsible for these traits. Here, F₇ recombinant inbred lines were used to identify quantitative trait loci (QTL) and allelic interactions for traits affecting plant water use, and their relevance is discussed for crop productivity in water‐limited environments. Four QTL contributed to increased transpiration rate under high vapour pressure deficit (VPD) conditions, all with alleles from drought‐sensitive parent ICMB 841. Of these four QTL, a major QTL (35.7%) was mapped on linkage group (LG) 6. The alleles for 863B at this QTL decreased transpiration rate and this QTL co‐mapped to a previously detected LG 6 QTL, with alleles from 863B for grain weight and panicle harvest index across severe terminal drought stress environments. This provided additional support for a link between water saving from a lower transpiration rate under high VPD and drought tolerance. 863B alleles in this same genomic region also increased shoot weight, leaf area and total transpiration under well‐watered conditions. One unexpected outcome was reduced transpiration under high VPD (15%) from the interaction of two alleles for high VPD transpiration (LG 6 (B), 40.7) and specific leaf mass and biomass (LG 7 (A), 35.3), (A, allele from ICMB 841, B, allele from 863B, marker position). The LG 6 QTL appears to combine alleles for growth potential, beneficial for non‐stress conditions, and for saving water under high evaporative demand, beneficial under stressful conditions. Mapping QTL for water‐use traits, and assessing their interactions offers considerable potential for improving pearl millet adaptation to specific stress conditions through physiology‐informed marker‐assisted selection.     

Quantitative trait loci influencing drought tolerance in grain sorghum (Sorghum bicolor L. Moench)

Drought is a major constraint in sorghum production worldwide. Drought-stress in sorghum has been characterized at both pre-flowering and post-flowering stages resulting in a drastic reduction in grain yield. In the case of post-flowering drought stress, lodging further aggravates the problem resulting in total loss of crop yield in mechanized agriculture. The present study was conducted to identify quantitative trait loci (QTLs) controlling post-flowering drought tolerance (stay green), pre-flowering drought tolerance and lodging tolerance in sorghum using an F₇ recombinant inbred line (RIL) population derived from the cross SC56×Tx7000. The RIL lines, along with parents, were evaluated for the above traits in multiple environments. With the help of a restriction fragment length polymorphism (RFLP) map, which spans 1,355 cM and consists of 144 loci, nine QTLs, located over seven linkage groups were detected for stay green in several environments using the method of composite interval mapping. Comparison of the QTL locations with the published results indicated that three QTLs located on linkage groups A, G and J were consistent. This is considered significant since the stay green line SC56 used in our investigation is from a different source compared to B35 that was used in all the earlier investigations. Comparative mapping has shown that two stay green QTLs identified in this study corresponded to stay green QTL regions in maize. These genomic regions were also reported to be congruent with other drought-related agronomic and physiological traits in maize and rice, suggesting that these syntenic regions might be hosting a cluster of genes with pleiotropic effects implicated in several drought tolerance mechanisms in these grass species. In addition, three and four major QTLs responsible for lodging tolerance and pre-flowering drought tolerance, respectively, were detected. This investigation clearly revealed the important and consistent stay green QTLs in a different stay green source that can logically be targeted for positional cloning. The identification of QTLs and markers for pre-flowering drought tolerance and lodging tolerance will help plant breeders in manipulating and pyramiding those traits along with stay green to improve drought tolerance in sorghum. Received: 2 June 2000 / Accepted: 15 November 2000     

Mapping QTLs for Plant Phenology and Production Traits Using Indica Rice (Oryza sativa L.) Lines Adapted to Rainfed Environment

Drought is a major abiotic stress limiting rice production and yield stability in rainfed ecosystems. Identifying quantitative trait loci (QTL) for rice yield and yield components under water limited environments will help to develop drought resilient cultivars using marker assisted breeding (MAB) strategy. A total of 232 recombinant inbred lines of IR62266/Norungan were used to map QTLs for plant phenology and production traits under rainfed condition in target population of environments. A total of 79 QTLs for plant phenology and production traits with phenotypic variation ranging from 4.4 to 72.8% were detected under non-stress and drought stress conditions across two locations. Consistent QTLs for phenology and production traits were detected across experiments and water regimes. The QTL region, RM204-RM197-RM217 on chromosome 6 was linked to days to 50% flowering and grain yield per plant under both rainfed and irrigated conditions. The same genomic region, RM585-RM204-RM197 was also linked to harvest index under rainfed condition with positive alleles from Norungan, a local landrace. QTLs for plant production and drought resistance traits co-located near RM585-RM204-RM197-RM217 region on chromosome 6 in several rice genotypes. Thus with further fine mapping, this region may be useful as a candidate QTL for MAB, map-based cloning of genes and functional genomics studies for rainfed rice improvement.     

Mapping and characterisation of QTL × E interactions for traits determining grain and stover yield in pearl millet

A mapping population of 104 F(3) lines of pearl millet, derived from a cross between two inbred lines H 77/833-2 x PRLT 2/89-33, was evaluated, as testcrosses on a common tester, for traits determining grain and stover yield in seven different field trials, distributed over 3 years and two seasons. The total genetic variation was partitioned into effects due to season (S), genotype (G), genotype x season interaction (G x S), and genotype x environment-within-season interaction [G x E(S)]. QTLs were determined for traits for their G, G x S, and G x E(S) effects, to assess the magnitude and the nature (cross over/non-crossover) of environmental interaction effects on individual QTLs. QTLs for some traits were associated with G effects only, while others were associated with the effects of both G and G x S and/or G, G x S and G x E(S) effects. The major G x S QTLs detected were for flowering time (on LG 4 and LG 6), and mapped to the same intervals as G x S QTLs for several other traits (including stover yield, harvest index, biomass yield and panicle number m(-2)). All three QTLs detected for grain yield were unaffected by G x S interaction however. All three QTLs for stover yield (mapping on LG 2, LG 4 and LG 6) and one of the three QTLs for grain yield (mapping on LG 4) were also free of QTL x E(S) interactions. The grain yield QTLs that were affected by QTL x E(S) interactions (mapping on LG 2 and LG 6), appeared to be linked to parallel QTL x E(S) interactions of the QTLs for panicle number m(-2) on (LG 2) and of QTLs for both panicle number m(-2) and harvest index (LG 6). In general, QTL x E(S) interactions were more frequently observed for component traits of grain and stover yield, than for grain or stover yield per se.     

Mapping QTLs associated with drought resistance in sorghum (Sorghum bicolor L. Moench)

Drought is a major abiotic stress factor limiting crop production. Identification of genetic factors involved in plant responses to drought stress will provide a solid foundation to improve drought resistance. Sorghum is well adapted to hot dry environments and regarded as a model for studying drought resistance among the grasses. Significant progress in genome mapping of this crop has also been made. In sorghum, rapid premature leaf death generally occurs when water is limited during the grain filling period. Premature leaf senescence, in turn, leads to charcoal rot, stalk lodging, and significant yield loss. More than 80% of commercial sorghum hybrids in the United States are grown under non-irrigated conditions and although most of them have pre-flowering drought resistance, many do not have any significant post-flowering drought resistance. Stay-green is one form of drought resistance mechanism, which gives sorghum resistance to premature senescence under soil moisture stress during the post-flowering period. Quantitative trait locus (QTL) studies with recombinant inbred lines (RILs) and near-isogenic lines (NILs) identified several genomic regions associated with resistance to pre-flowering and post-flowering drought stress. We have identified four genomic regions associated with the stay-green trait using a RIL population developed from B35 × Tx7000. These four major stay-green QTLs were consistently identified in all field trials and accounted for 53.5% of the phenotypic variance. We review the progress in mapping stay-green QTLs as a component of drought resistance in sorghum. The molecular genetic dissection of the QTLs affecting stay-green will provide further opportunities to elucidate the underlying physiological mechanisms involved in drought resistance in sorghum and other grasses.     

Grain yield responses to moisture regimes in a rice population: association among traits and genetic markers

Drought is a major constraint to rice (Oryza sativa L.) production in rainfed and poorly irrigated environments. Identifying genomic regions influencing the response of yield and its components to water deficits will aid our understanding of the genetic mechanism of drought tolerance (DT) of rice and the development of DT varieties. Grain yield (GY) and its components of a recombinant inbred population developed from a lowland rice and an upland rice were investigated under different water levels in 2003 and 2004 in a rainout DT screening facility. Correlation and path analysis indicated that spikelet fertility (SF) was particularly important for grain yield with direct effect (P=0.60) under drought stress, while spikelet number per panicle (SN) contributed the most to grain yield (P=0.41) under well-watered condition. A total of 32 quantitative trait loci (QTLs) for grain yield and its components were identified. The phenotypic variation explained by individual QTLs varied from 1.29% to 14.76%. Several main effect QTLs affecting SF, 1,000-grain weight (TGW), panicle number (PN), and SN were mapped to the same regions on chromosome 4 and 8. These QTLs were detected consistently across 2 years and under both water levels in this study. Several digenic interactions among yield components were also detected. The identification of genomic regions associated with GY and its components under stress will be useful to improve drought tolerance of rice by marker-aided approaches.G. H. Zou and H. W. Mei contribute equally to this work.     

Quantitative trait loci associated with drought tolerance at reproductive stage in rice

Drought is a major constraint to rice (Oryza sativa) yield and its stability in rainfed and poorly irrigated environments. Identifying genomic regions influencing the response of yield and its components to water deficits will aid in our understanding of the genetics of drought tolerance and development of more drought tolerant cultivars. Quantitative trait loci (QTL) for grain yield and its components and other agronomic traits were identified using a subset of 154 doubled haploid lines derived from a cross between two rice cultivars, CT9993-510 to 1-M and IR62266-42 to 6-2. Drought stress treatments were managed by use of a line source sprinkler irrigation system, which provided a linearly decreasing level of irrigation coinciding with the sensitive reproductive growth stages. The research was conducted at the Ubon Rice Research Center, Ubon, Thailand. A total of 77 QTL were identified for grain yield and its components under varying levels of water stress. Out of the total of 77 QTL, the number of QTL per trait were: 7-grain yield (GY); 8-biological yield (BY); 6-harvest index (HI); 5-d to flowering after initiation of irrigation gradient (DFAIG); 10-total spikelet number (TSN); 7-percent spikelet sterility (PSS); 23-panicle number (PN); and 11-plant height (PH). The phenotypic variation explained by individual QTL ranged from 7.5% to 55.7%. Under well-watered conditions, we observed a high genetic association for BY, HI, DFAIG, PSS, TSN, PH, and GY. However, only BY and HI were found to be significantly associated with GY under drought treatments. QTL flanked by markers RG104 to RM231, EMP2_2 to RM127, and G2132 to RZ598 on chromosomes 3, 4, and 8 were associated with GY, HI, DFAIG, BY, PSS, and PN under drought treatments. The aggregate effects of these QTL on chromosomes 3, 4, and 8 resulted in higher grain yield. These QTL will be useful for rainfed rice improvement, and will also contribute to our understanding of the genetic control of GY under drought conditions at the sensitive reproductive stage. Close linkage or pleiotropy may be responsible for the coincidence of QTL detected in this experiment. Digenic interactions between QTL main effects for GY, BY, HI, and PSS were observed under irrigation treatments. Most (but not all) DH lines have the same response in measure of productivity when the intensity of water deficit was increased, but no QTL by irrigation treatment interaction was detected. The identification of genomic regions associated with GY and its components under drought stress will be useful for marker-based approaches to improve GY and its stability for farmers in drought-prone rice environments.     

Mapping QTLs for seed yield and drought susceptibility index in soy-bean（Glycine max L.） across different environments

Drought stress has long been a major constraint in maintaining yield stability of soybean （Glycine max （L.） Merr.） in rainfed ecosystems. The identification of consistent quantitative trait loci （QTL） involving seed yield per plant （YP） and drought susceptibility index （DSI） in a population across different environments would therefore be important in molecular marker-assisted breeding of soybean cultivars suitable for rainfed regions. The YP of a recombinant line population of 184 F2：7：11 lines from a cross of Kefengl and Nannong1138-2 was studied under water-stressed （WS） and well-watered （WW） conditions in field （F） and greenhouse （G） trials, and DSI for yield was calculated in two trials. Nineteen QTLs associated with YP-WS and YP-WW, and 10 QTLs associated with DSI, were identi- fied. Comparison of these QTL locations with previous findings showed that the majority of these regions control one or more traits re- lated to yield and other agronomic traits. One QTL on molecular linkage group （MLG） K for YP-F, and two QTLs on MLG C2 for YP-G, remained constant across different water regimes. The regions on MLG C2 for YP-WW-F and MLG H for YP-WS-F had a pleiotropic effect on DSI-F, and MLG A1 for YP-WS-G had a pleiotropic effect on DSI-G. The identification of consistent QTLs for YP and DSI across different environments will significantly improve the efficiency of selecting for drought tolerance in soybean.     

Linkages and Interactions Analysis of Major Effect Drought Grain Yield QTLs in Rice

Quantitative trait loci conferring high grain yield under drought in rice are important genomic resources for climate resilient breeding. Major and consistent drought grain yield QTLs usually co-locate with flowering and/or plant height QTLs, which could be due to either linkage or pleiotropy. Five mapping populations used for the identification of major and consistent drought grain yield QTLs underwent multiple-trait, multiple-interval mapping test (MT-MIM) to estimate the significance of pleiotropy effects. Results indicated towards possible linkages between the drought grain yield QTLs with co-locating flowering and/or plant height QTLs. Linkages of days to flowering and plant height were eliminated through a marker-assisted breeding approach. Drought grain yield QTLs also showed interaction effects with flowering QTLs. Drought responsiveness of the flowering locus on chromosome 3 (qDTY_3.2) has been revealed through allelic analysis. Considering linkage and interaction effects associated with drought QTLs, a comprehensive marker-assisted breeding strategy was followed to develop rice genotypes with improved grain yield under drought stress.     

Quantitative trait loci for yield and correlated traits under high and low soil nitrogen conditions in tropical maize

The first objective of this study was to map and characterize quantitative trait loci (QTL) for grain yield (GY) and for secondary traits under varying nitrogen (N) supply. To achieve this objective, a segregating F_2:3 population previously developed for QTL mapping under water-limited conditions was used. The population was evaluated in Mexico under low N conditions in the dry winter season and under low and high N conditions in the wet summer season. From eight QTLs identified for GY under low N conditions, two were also detected under high N conditions. Five QTLs were stable across the two low N environments and five co-localized with QTLs identified for the anthesis-silking interval (ASI) or for the number of ears per plant (ENO) under low N conditions. The percentage of the phenotypic variance expressed by all QTLs for ASI and ENO was quite different when evaluated under low N conditions during the dry winter (40% for ASI and 22% for ENO) and the wet summer seasons (22% for ASI and 46% for ENO). The results suggest optimizing different breeding strategies based on selection index depending on the growing season. Good QTL colocalization was observed for ASI (four QTLs) and ENO (three QTLs) when looking at QTL identified under low N and water-limited conditions in the same population. The results suggest that that both secondary traits can be used in breeding programs for simultaneous improvement of maize against low N and drought stresses.     

Genetic dissection of cotton physiological responses to arid conditions and their inter-relationships with productivity

Testing of the extent to which different complex traits share common genetic control provides a means to distinguish associations that are truly diagnostic of genetic potential for improved adaptation to abiotic stress, from incidental phenotypic correlations. In two generations of progeny from a cross between Gossypium hirsutum and Gossypium barbadense, quantitative trait loci (QTL) mapping was used to evaluate correspondence in genetic control of selected physiological measures and productivity under water‐limited and well‐watered environments, respectively. A total of 33 QTLs were detected for five physiological variables [osmotic potential (OP), carbon isotope ratio (δ¹³C; indicator of water use efficiency), canopy temperature, chlorophyll a and b], and 46 QTLs for five measures of crop productivity [dry matter, seed cotton yield (SC), harvest index, boll weight, and boll number]. QTL likelihood intervals for high SC and low OP corresponded in three genomic regions, two of which mapped to homoeologous locations on the two subgenomes of tetraploid cotton. QTLs for δ¹³C showed only incidental association with productivity, indicating that high water use efficiency can be associated with either high or low productivity. Different cotton species have evolved different alleles related to physiological responses and productivity under water deficit, which may permit the development of genotypes that are better‐adapted to arid conditions.     

Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis

An F_4:5 population of 490 recombinant inbred lines (RILs) from the cross Apo/^2*Swarna was used to detect quantitative trait loci (QTL) with large effects on grain yield under drought stress using bulk-segregant analysis (BSA). Swarna is an important rainfed lowland rice variety grown on millions of hectares in Asia, but is highly susceptible to drought and aerobic soil conditions. Apo is an aerobic-adapted variety with moderate tolerance to drought. Two rice microsatellite (RM) markers, RM324, and RM416, located on chromosomes 2 and 3, respectively, were shown via BSA to be strongly associated with yield under lowland drought stress. The effects of these QTL were tested in a total of eight hydrological environments over a period of 3 years. The QTL linked to RM416 (DTY _3.1 ) had a large effect on grain yield under severe lowland drought stress, explaining about 31% of genetic variance for the trait (P < 0.0001). It also explained considerable variance for yield under mild stress in lowland conditions and aerobic environments. To our knowledge this is the first reported QTL that has a large effect on yield in both lowland drought and aerobic environments. The QTL linked to RM324 (DTY _2.1 ) had a highly significant effect on grain yield in lowland drought stress (R ² = 13–16%) and in two aerobic trials. The effect of these QTL on grain yield was verified to be not mainly due to phenology differences. Effects of DTY _3.1 on yield under stress have been observed in several other rice mapping populations studied at IRRI. Results of this study indicate that BSA is an effective method of identifying QTL alleles with large effects on rice yield under severe drought stress. The Apo alleles for these large-effect QTL for grain yield under drought and aerobic conditions may be immediately exploited in marker-assisted-breeding to improve the drought tolerance of Swarna.     

QTLs affecting morph-physiological traits related to drought tolerance detected in overlapping introgression lines of rice (Oryza sativa L.)

Plant photosynthetic traits such as net photosynthetic rate (P_n), stomata conductance (g_s), transpiration rate (T_r), and intercellular CO₂ concentration (C_i), are known to relate to drought tolerance in plants, but the genetic basis of these traits remains largely uncharacterized because of the difficulty in phenotyping physiological traits in a large mapping population. In this study, a set of 55 overlapping introgression lines (ILs) in the Teqing (indica) background were used to genetically dissect several morph-physiological traits and their relationship with grain yield under water stress and non-stress conditions. These traits included specific leaf weight (SLW), chlorophyll content (CC), leaf stomata frequency (SF), P_n, g_s, T_r, and C_i. A total of 40 QTLs affecting the measured traits were identified and mapped to 21 genomic regions in the rice genome. Clustered QTLs affecting P_n, g_s, T_r, and C_i in the same genomic regions suggest common genetic bases for the physiological traits. Low or no phenotypic correlations between leaf morphological traits and photosynthetic traits and between morph-physiological traits and grain yield (GY) appeared to be due to inconsistence in QTL effect for clustered QTLs, unlinked QTLs affecting different traits, and to possible epistasis that could not be adequately addressed in this study. Our results indicate that improving drought tolerant (DT) of rice by selecting any single secondary traits is not expected to be effective and the identified QTLs for GY and related morph-physiological traits should be carefully confirmed before to be used for improving DT in rice by MAS.     

Genomic dissection of drought resistance in durum wheat × wild emmer wheat recombinant inbreed line population

Drought is the major factor limiting wheat productivity worldwide. The gene pool of wild emmer wheat, Triticum turgidum ssp. dicoccoides , harbours a rich allelic repertoire for morpho-physiological traits conferring drought resistance. The genetic and physiological bases of drought responses were studied here in a tetraploid wheat population of 152 recombinant inbreed lines (RILs), derived from a cross between durum wheat (cv. Langdon) and wild emmer (acc# G18-16), under contrasting water availabilities. Wide genetic variation was found among RILs for all studied traits. A total of 110 quantitative trait loci (QTLs) were mapped for 11 traits, with LOD score range of 3.0–35.4. Several QTLs showed environmental specificity, accounting for productivity and related traits under water-limited (20 QTLs) or well-watered conditions (15 QTLs), and in terms of drought susceptibility index (22 QTLs). Major genomic regions controlling productivity and related traits were identified on chromosomes 2B, 4A, 5A and 7B. QTLs for productivity were associated with QTLs for drought-adaptive traits, suggesting the involvement of several strategies in wheat adaptation to drought stress. Fifteen pairs of QTLs for the same trait were mapped to seemingly homoeologous positions, reflecting synteny between the A and B genomes. The identified QTLs may facilitate the use of wild alleles for improvement of drought resistance in elite wheat cultivars.     

Molecular mapping of genomic regions harbouring QTLs for root and yield traits in sorghum (Sorghum bicolor L. Moench)

Root system is a vital part of plants for absorbing soil moisture and nutrients and it influences the drought tolerance. Identification of the genomic regions harbouring quantitative trait loci (QTLs) for root and yield traits, and the linked markers can facilitate sorghum improvement through marker-assisted selection (MAS) besides the deeper understanding of the plant response to drought stress. A population of 184 recombinant inbred lines (RILs), derived from E36-1 × SPV570, along with parents were phenotyped for component traits of yield in field and root traits in an above ground rhizotron. High estimates of heritability and genetic advance for all the root traits and for most of the yield traits, presents high scope for improvement of these traits by simple selection. A linkage map constructed with 104 marker loci comprising 50 EST-SSRs, 34 non-genic nuclear SSRs and 20 SNPs, and QTL analysis was performed using composite interval mapping (CIM) approach. A total of eight and 20 QTLs were mapped for root and yield related traits respectively. The QTLs for root volume, root fresh weight and root dry weight were found co-localized on SBI-04, supported by a positive correlation among these traits. Hence, these traits can be improved using the same linked markers. The lack of overlap between the QTLs of component traits of root and yield suggested that these two sets of parameters are independent in their influence and the possibility of combining these two traits might enhance productivity of sorghum under receding moisture condition.     

QTL studies reveal little relevance of chilling-related seedling traits for yield in maize

Prolonged low temperature phases and short-term cold spells often occur in spring during the crucial stages of early maize (Zea mays L.) development. The effect of low temperature-induced growth retardation at the seedling stage on final yield is poorly studied. Therefore, the aim was to identify genomic regions associated with morpho-physiological traits at flowering and harvest stage and their relationship to previously identified quantitative trait loci (QTLs) for photosynthesis and morpho-physiological traits from the same plants at seedling stage. Flowering time, plant height and shoot biomass components at harvest were measured in a dent mapping population for cold tolerance studies, which was sown in the Swiss Midlands in early and late spring in two consecutive years. Early-sown plants exhibited chilling stress during seedling stage, whereas late-sown plants grew under favorable conditions. Significant QTLs, which were stable across environments, were found for plant height and for the time of flowering. The QTLs for flowering were frequently co-localized with QTLs for plant height or ear dry weight. The comparison with QTLs detected at seedling stage revealed only few common QTLs. A pleiotropic effect was found on chromosome 3 which revealed that a good photosynthetic performance of the seedling under warm conditions had a beneficial effect on plant height and partially on biomass at harvest. However, a high chilling tolerance of the seedling seemingly had an insignificant or small negative effect on the yield.     

The detection of QTLs in barley associated with endosperm hardness, grain density, grain size and malting quality using rapid phenotyping tools

Using a barley mapping population, ‘Vlamingh’ × ‘Buloke’ (V × B), whole grain analyses were undertaken for physical seed traits and malting quality. Grain density and size were predicted by digital image analysis (DIA), while malt extract and protein content were predicted using near infrared (NIR) analysis. Validation of DIA and NIR algorithms confirmed that data for QTL analysis was highly correlated (R ² > 0.82), with high RPD values (the ratio of the standard error of prediction to the standard deviation, 2.31–9.06). Endosperm hardness was measured on this mapping population using the single kernel characterisation system. Grain density and endosperm hardness were significantly inter-correlated in all three environments (r > 0.22, P < 0.001); however, other grain components were found to interact with the traits. QTL for these traits were also found on different genomic regions, for example, grain density QTLs were found on chromosomes 2H and 6H, whereas endosperm hardness QTLs were found on 1H, 5H, and 7H. In this study, the majority of the genomic regions associated with grain texture were also coincident with QTLs for grain size, yield, flowering date and/or plant development genes. This study highlights the complexity of genomic regions associated with the variation of endosperm hardness and grain density, and their relationships with grain size traits, agronomic-related traits, and plant development loci.