Mining elite loci and candidate genes for root morphology-related traits at the seedling stage by genome-wide association studies in upland cotton(Gossypium hirsutum L.)

Root system architecture plays an essential role in water and nutrient acquisition in plants,and it is significantly involved in plant adaptations to various environmental stresses.In this study,a panel of 242 cotton accessions was collected to investigate six root morphological traits at the seedling stage,including main root length(MRL),root fresh weight(RFW),total root length(TRL),root surface area(RSA),root volume(RV),and root average diameter(AvgD).The correlation analysis of the six root morphological traits revealed strong positive correlations of TRL with RSA,as well as RV with RSA and AvgD,whereas a significant negative correlation was found between TRL and AvgD.Subsequently,a genome-wide association study(GWAS)was performed using the root phenotypic and genotypic data reported previously for the 242 accessions using 56,010 single nucleotide polymorphisms(SNPs)from the CottonSNP80K array.A total of 41 quantitative trait loci(QTLs)were identified,including nine for MRL,six for RFW,nine for TRL,12 for RSA,12 for RV and two for AvgD.Among them,eight QTLs were repeatedly detected in two or more traits.Integrating these results with a transcriptome analysis,we identified 17 candidate genes with high transcript values of transcripts per million(TPM)≥30 in the roots.Furthermore,we functionally verified the candidate gene GH_D05G2106,which encodes a WPP domain protein 2in root development.A virus-induced gene silencing(VIGS)assay showed that knocking down GH_D05G2106significantly inhibited root development in cotton,indicating its positive role in root system architecture formation.Collectively,these results provide a theoretical basis and candidate genes for future studies on cotton root developmental biology and root-related cotton breeding.

Identification of Quantitative Trait Loci for Anthesis-Silking Interval and Yield Components Under Drought Stress in Maize

A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the field under well-watered and drought-stressed regimes in Shanxi Province of China. The objectives of the study were to identify genetic segments responsible for the expression of anthesis-silking interval (ASI), ear setting and grain yield, and to examine if the quantitative trait loci (QTLs) for ASI or yield components can be used in marker-assisted selection (MAS) to improve grain yield under drought conditions. Results showed that under well-watered and drought-stressed regimes, three and two QTLs involved in the expression of ASI were detected on chromosomes 1, 2 and 3, and 2 and 5, respectively. Under well-watered regime, two QTLs for ear setting were detected on chromosomes 3 and 6, explaining about 19.9% of the phenotypic variance, and displayed additive and partial dominant effects, respectively. Under drought-stressed condition, four QTLs for ear setting were detected on chromosomes 3, 7 and 10, which were responsible for interpreting 60.4% of the phenotypic variance, and showed dominant or partial dominant effects. Under well-watered condition, four QTLs controlling grain yield were identified on chromosomes 3, 6 and 7, while five QTLs were identified under drought stress on chromosomes 1, 2, 4 and 8. The gene action was of additive or partial dominant effects, and each QTL could explain 7.3% to 22.0% of the phenotypic variance, respectively. Under drought conditions, ASI and ear setting percentage were highly correlated with grain yield, which can be used as secondary traits for grain yield selection. Based on linked markers detected and gene action analyzed, an MAS strategy for yield improvement under drought condition could be established, which consists of QTLs contributing to decreased ASI and to increased ear setting and grain yield, respectively.

Detection of Quantitative Trait Loci Associated with Several Internal Organ Traits and Teat Number Trait in a Pig Population

Quantitative trait loci （QTL） were detected for 8 internal organ traits, 3 carcass length traits, and teat number trait in 214 pigs in a resource population that included 180 F2 individuals. A total of 39 microsatellite markers were examined on SSC4, SSC6, SSC7, SSC8, and SSC13. The genetic traits included heart weight （HW）, lung weight （LW）, liver and gallbladder weight （LGW）, spleen weight （SPW）, stomach weight （STW）, small intestine weight （S1W）, large intestine weight （LIW）, kidney weight （KW）, carcass length to the first cervical vertebra （CL1）, carcass length to the first thoracic vertebra （CL2）, rib numbers （RNS）, and teat numbers （TNS）. Results indicated that, 3 highly significant QTL （P≤0.01 at chromosome-wise level） for HW （at 30 cM on SSC6）, RNS （at 115 cM on SSC7）, TNS （at 110 cM on SSC7）, and 6 significant QTL （P≤0.05 at chromosome-wise level） for LW （at 119 cM on SSC13）, LGW （at 94 cM on SSC6）, SPW （at 106 cM on SSC8）, SIW （0 cM on SSC4）, LIW （170 cM on SSC 4）, and TNS （at 95 cM on SSC6） were detected. The phenotypic variances for which these QTL were accounted ranged from 0.04 % to 14.06 %. Most of these QTL had not been previously reported.

Mapping QTLs for Panicle Traits Based on Rice RIL Population Derived from TD70 and Kasalath

Two hundred and forty recombinant inbred lines （RIL） derived from a cross TD70/Kasalath and its linkage map including 141 SSR markers were used to map QTLs controlling panicle length （PL）, total seeds per panicle （TSP） and grain density （GD） in 2010 and 2011. The results showed that a total of 23 QTLs controlling three panicle traits were detected on chromosomes 2, 3, 4, 6, 7, 8 and 10, respec- tively, including 5 QTLs controlling PL, 8 QTLs controlling TSP, 10 QTLs controlling GD, with the LOD value ranging between 2.5-9.3, and the QTLs explained the ob- served phenotypic by 4.0%-20.8%. The marker interval RM5699-RM424 on chro- mosome 2, RM489-RM1278 on chromosome 3, RM3367-RM1018 on chromosome 4, RM3343-RM412 on chromosome 6 were common marker intervals for TSP and GD; six QTLs （qPL3, qTSP4, qTSP6-2, qTSP7, qGD3-2 and qGDT） were detected in two years. Among these QTLs, the qPL3, qTSP6-2, qGD3-2 and qGD7 were major QTLs. All QTLs for PL mapped in the present study had been mapped QTLs previously by other research groups, 16 QTLs controlling TSP and GD were new ones which contributed the observed phenotypic variance range by 4%-9.5%. These results laid a founda^ion for further fine positioning or cloning these QTLs.

Detection of the Quantitative Trait Loci with AFLP and RFLP Markers for Phosphorus Uptake and Use Efficiency in Rice

To identify genetic factors underlying phosphorus (P) uptake and use efficiency under low_P stress in rice (Oryza sativa L.), 84 selected genotypes (recombinant inbred lines) and their parents (which differed in tolerance for low_P stress) “IR20” and IR55178_3B_9_3, were cultured in liquid medium supplemented with adequate and low P levels in a greenhouse. Plants were sampled after 6 weeks in culture for measurements of plant dry weight, P concentration, P uptake and P use efficiency under both P sufficient and stress conditions. A total of 179 molecular markers, including 26 RFLPs and 153 AFLPs, mapped on all 12 chromosomes of rice based on the 84 selected genotypes were used to detect the quantitative trait loci (QTLs) underlying tolerance for low_P stress. Three QTLs were detected on chromosomes 6, 7 and 12, respectively, for relative plant dry weight (RPDW) and relative P uptake (RPUP). One of the QTLs flanked by RG9 and RG241 on chromosome 12 had a major effect which explained about 50% of the variations in the two parameters across the population. The results coincided with the QTLs for low_P stress based on relative tillering ability from the same population from a cross between Nipponbare and Kasalath under soil condition. The identical major QTL for P uptake and plant growth under low_P stress in both liquid medium and soil strongly suggests that the ability of P uptake mainly controls rice tolerance for low_P stress.

Analysis of Quantitative Trait Loci for Starch Properties of Rice Based on an RIL Population

Rice (Oryza sativa L.) eating and cooking quality is mainly influenced by its starch properties. Mapping quantitative trait loci (QTL) for starch properties not only helps us understand their genetic basis leading to acceleration of quality improvement, but also helps us find possible genes participating in the synthesis of starch. A recombinant inbred line (RIL) population consisting of 107 lines, derived from an indica (Zaiyeqing 8, ZYQ 8) and a japonica (Jingxi 17, JX 17) rice, was used to investigate the genetic factors affecting starch quality parameters, such as apparent amylose content (AAC), gel consistency (GC), starch pasting viscosity parameters, gel textural properties, gelatinization temperature (GT) and starch retrogradation properties. A total of 44 QTLs covered chromosomes 2-6, 8, 9 and 11 were detected for the 22 traits, with at least one QTL and as many as four QTLs for each individual trait. The results indicated that two major genes were responsible for most starch property traits. The Wx gene that encodes granule bound starch synthase on chromosome 6 was significant for AAC, GC, starch pasting viscosity parameters, gel textural properties and starch retrogradation properties. The alk gene linked with Wx on chromosome 6 was significant for starch gelatinization temperature characteristics. All other QTLs were minor genes. One QTL on chromosome 9 flanked by RZ404 and G295 was significant for gel hardness (HD), gumminess (GUM), chewiness (CHEW), peak temperature of retrogradated starch (RTp), and percentage retrogradation (R%) and all these traits were not tested before.

Comparison and Analysis on DUS Screening Traits of Two Lavender Species

In this paper, based on the DUS testing of new Lavandula spp., the differences and correlations of main phenotypic traits between Lavandula angustifolia and L. heterophylla were observed and analyzed. The results showed that the plant morphological traits of L. angustifolia were better than that of L. heterophylla, moreover, L. angustifolia exhibited relatively high adaptive capacity to the environmental conditions in introduction areas of north China. For the inflorescence, the ornamental traits of L. heterophylla were totally superior to that of L. angustifolia, especially in flower color diversity. It had obvious differences in both quantitative traits and qualitative traits between the two species, and these traits remained relatively stable in the growth progress. The correlation coefficients among the traits of two species were high, and the trait matching numbers at the 1% significance level of L. angustifolia were slightly more than that of L. heterophylla.

Quantitative Trait Loci for Grain Chalkiness and Endosperm Transparency Detected in Three Recombinant Inbred Line Populations of Indica Rice

Quantitative trait loci（QTL） for percentage of chalky grain,degree of chalkiness,and endosperm transparency were detected using 3 recombinant inbred line populations derived from crosses between parental lines of commercial three-line hybrids of indica rice.Two of the populations showed great variations on heading date,and the other had a short range of heading date variation.A total of 40 QTLs were detected and fell into 15 regions of 10 chromosomes,of which 5 regions were detected for 1 or more same traits over different populations,2 were detected for different traits in different populations,3 were detected for 2 or all the 3 traits in a single population,and 5 were detected for a single trait in a single population.Most of these QTLs have been reported previously,but a region located on the long arm of chromosome 10 showing significant effects in all the 3 populations has not been reported before.It was shown that a number of gene cloned,including the Wx and Alk for the physiochemical property of rice grain,and GW2,GS3 and GW5 for grain weight and grain size,could have played important roles for the genetic control of grain chalkiness in rice,but there are many more QTLs exerting stable effects for rice chalkiness over different genetic backgrounds.It is worth paying more attentions to these regions which harbor QTL such as the qPCG5.2/qDC5.2/qET5.2 and qPCG10/qDC10/qET10 detected in our study.Our results also showed that the use of segregating populations having high-uniform heading date could greatly increase the efficiency of the identification of QTL responsible for traits that are subjected to great environmental influence.

Identification of quantitative trait loci for the dead leaf rate and the seedling dead rate under alkaline stress in rice

The quantitative trait loci （QTLs） for the dead leaf rate （DLR） and the dead seedling rate （DSR） at the different rice growing periods after transplanting under alkaline stress were identified using an F2：3 population, which included 200 individuals and lines derived from a cross between two japonica rice cultivars Gaochan 106 and Changbai 9 with microsatellite markers. The DLR detected at 20 days to 62 days after transplanting under alkaline stress showed continuous normal or near normal distributions in F3 lines, which was the quantitative trait controlled by multiple genes. The DSR showed a continuous distribution with 3 or 4 peaks and was the quantitative trait controlled by main and multiple genes when rice was grown for 62 days after transplanting under alkaline stress. Thirteen QTLs associated with DLR were detected at 20 days to 62 days after transplanting under alkaline stress. Among these, qDLR9-2 located in RM5786-RM160 on chromosome 9 was detected at 34 days, 41 days, 48 days, 55 days, and 62 days, respectively; qDLR4 located in RM3524-RM3866 on chromosome 4 was detected at 34 days, 41 days, and 48 days, respectively; qDLR7-1 located in RM3859-RM320 on chromosome 7 was detected at 20 days and 27 days; and qDLR6-2 in RM1340-RM5957 on chromosome 6 was detected at 55 days and 62 days, respectively. The alleles of both qDLR9-2 and qDLR4 were derived from alkaline sensitive parent ＂Gaochanl06＂. The alleles of both qDLR7-1 and qDLR6-2 were from alkaline tolerant parent Changbai 9. These gene actions showed dominance and over dominance primarily. Six QTLs associated with DSR were detected at 62 days after transplanting under alkaline stress. Among these, qDSR6-2 and qDSR8 were located in RM1340-RM5957 on chromosome 6 and in RM3752-RM404 on chromosome 8, respectively, which were associated with DSR and accounted for 20.32% and 18.86% of the observed phenotypic variation, respectively; qDSR11-2 and qDSR11-3 were located in RM536-RM479 and RM2596-RM286 on chromosome 11, respectively, which were associated with DSR explaining 25.85% and 15.41% of the observed phenotypic variation, respectively. The marker flanking distances of these QTLs were quite far except that of qDSR6-2, which should be researched further.

QTL Mapping for Stalk Related Traits in Maize (Zea mays L.) Under Different Densities

Stalk related traits, comprising plant height （PH）, ear height （EH）, internode number （IN）, average internode length （ALL）, stalk diameter （SD）, and ear height coefficient （EHC）, are significantly correlated with yield, density tolerance, and lodging resistance in maize. To investigate the genetic basis for stalk related traits, a doubled haploid （DH） population derived from a cross between NX531 and NX110 were evauluated under two densities over 2 yr. The additive quantitative trait loci （QTLs）, epistatic QTLs were detected using inclusive composite interval mapping and QTL-by-environment interaction were detected using mixed linear model. Differences between the two densities were significant for the six traits in the DH population. A linkage map that covered 1 721.19 cM with an average interval of 10.50 cM was constructed with 164 simple sequence repeat （SSR）. Two, two, seven, six, two, and eight additive QTLs for PH, IN, AIL, EH, SD, and EHC, respectively. The extend of their contribution to penotypic variation ranged from 10.10 to 31.93%. Seven QTLs were indentified simultaneously under both densities. One pair, two pairs and one pair of epistatic effects were detected for AIL, SD and EHC, respectively. No epistatic effects were detected for PH, EH, and IN. Nineteen QTLs with environment interactions were detected and their contribution to phenotypic variation ranged from 0.43 to 1.89%. Some QTLs were stably detected under different environments or genetic backgrounds comparing with previous studies. These QTLs could be useful for genetic improvement of stalk related traits in maize breeding.

Quantitative traits correlative analysis and growth comparison among different populations of bay scallop,Argopecten irradians

The shell traits and weight traits are measured in cultured populations of bay scallop, Argopecten irradians. The results of regression analysis show that the regression relationships for all the traits are significant (P<0.01). The correlative coefficients between body weight, as well as tissue weight with shell length, shell height and shell width are significant (P<0.05). But the correlative coefficients between the anterior and posterior auricle length with body weight as well as tissue weight are not significant (P>0.05). The multiple regression equation is obtained to estimate live body weight and tissue weight. The above traits except anterior and posterior auricle length are used for the growth and production comparison among three cultured populations, Duncan's new multiple range procedure analysis shows that all the traits in the Lingshuiqiao (LSQ) population are much more significant than those of the other two populations (P<0.01), and there is no significant difference between the Qipanmo (QPM) and Dalijia (DLJ) populations in all traits (P>0.05). The results indicate that the LSQ population has a higher growth rate and is expected to be more productive than the other two populations.

Strategies on Sample Size Determination and Qualitative and Quantitative Traits Integration to Construct Core Collection of Rice (Oryza sativa)

The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions （6.6%） could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits （QT1）, quantitative traits （QT2） and integrated qualitative and quantitative traits （QTT）, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections （225, 200, 175, 150, 125, 100, 75 and 50）. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.

Genetic bases of source-,sink-,and yield-related traits revealed by genome-wide association study in Xian rice

The source-sink relationship determines the ultimate grain yield.We investigated the genetic basis of the relationship between source and sink and yield potential in rice.In two environments,we identified quantitative trait loci(QTL)associated with sink capacity(total spikelet number per panicle and thousand-grain weight),source leaf(flag leaf length,flag leaf width and flag leaf area),source-sink relationship(total spikelet number to flag leaf area ratio)and yield-related traits(filled grain number per panicle,panicle number per plant,grain yield per plant,biomass per plant,and harvest index)by genome-wide association analysis using 272 Xian(indica)accessions.The panel showed substantial variation for all traits in the two environments and revealed complex phenotypic correlations.A total of 70 QTL influencing the 11 traits were identified using 469,377 high-quality SNP markers.Five QTL were detected consistently in four chromosomal regions in both environments.Five QTL clusters simultaneously affected source,sink,source–sink relationship,and grain yield traits,probably explaining the genetic basis of significant correlations of grain yield with source and sink traits.We selected 24 candidate genes in the four consistent QTL regions by identifying linkage disequilibrium(LD)blocks associated with significant SNPs and performing haplotype analysis.The genes included one cloned gene(NOG1)and three newly identified QTL(qHI6,qTGW7,and qFLA8).These results provide a theoretical basis for high-yield rice breeding by increasing and balancing source–sink relationships using marker-assisted selection.

Identification of QTLs for Yield-Related Traits in the Recombinant Inbred Line Population Derived from the Cross Between a Synthetic Hexaploid Wheat-Derived Variety Chuanmai 42 and a Chinese Elite Variety Chuannong 16

Synthetic hexaploid wheat （SHW） represents a valuable source of new resistances to a range of biotic and abiotic stresses. A recombinant inbred line （RIL） population with 127 recombinant inbred lines derived from a SHW-derived variety Chuanmai 42 crossing with a Chinese spring wheat variety Chuannong 16 was used to map QTLs for agronomic traits including grain yield, grains per square meter, thousand-kernel weight, spikes per square meter, grain number per spike, grains weight per spike, and biomass yield. The population was genotyped using 184 simple-sequence repeat （SSR） markers and 34 sequence-related amplified polymorphism （SRAP） markers. Of 76 QTLs （LOD〉2.5） identified, 42 were found to have a positive effect from Chuanmai 42. The QTL QGy.saas-4D.2 associated with grain yield on chromosome 4D was detected in four of the six environments and the combined analysis, and the mean yield, across six environments, of individuals carrying the Chuanmai 42 allele at this locus was 8.9% higher than that of those lines carrying the Chuannong 16 allele. Seven clusters of the yield-coincident QTLs were detected on 1A, 4A, 3B, 5B, 4D, and 7D.

Validation of qGSIO, a quantitative trait locus for grain size on the long arm of chromosome 10 in rice (Oryza sativa L.)

Grain size is a major determinant of grain weight and a trait having important impact on grain quality in rice. The objective of this study is to detect QTLs for grain size in rice and identify important QTLs that have not been well characterized before. The QTL mapping was first performed using three recombinant inbred line populations derived from indica rice crosses Teqing/IRBB lines, Zhenshan 97/Milyang 46, Xieqingzao/Milyang 46. Fourteen QTLs for grain length and 10 QTLs for grain width were detected, including seven shared by two populations and 17 found in one population. Three of the seven com- mon QTLs were found to coincide in position with those that have been cloned and the four others remained to be clarified. One of them, qGSIO located in the interval RM6100-RM228 on the long arm of chromosome 10, was validated using F2：3 populations and near isogenic lines derived from residual heterozygotes for the interval RM6100-RM228. The QTL was found to have a considerable effect on grain size and grain weight, and a small effect on grain number. This region was also previously detected for quality traits in rice in a number of studies, providing a good candidate for functional analysis and breeding utilization.

Quantitative Trait Loci Associated with Pollen Fertility under High Temperature Stress at Flowering Stage in Rice (Oryza sativa)

High temperature stress (HTS), an increasingly important problem in rice production, significantly reduces rice yield by reducing pollen fertility and seed setting rate. Breeding rice varieties with tolerance to HTS at the flowering stage is therefore essential for maintaining rice production as the climate continues to become warm. In this study, two quantitative trait loci (QTLs) underlying tolerance to HTS were identified using recombinant inbred lines derived from a cross between an HTS-tolerant rice cultivar 996 and a sensitive cultivar 4628. Pollen fertility was used as a heat-tolerance indicator for the lines subjected to HTS at the flowering stage in field experiments. Two QTLs that affected pollen fertility, qPF4 and qPF6, were detected between RM5687 and RM471 on chromosome 4, and between RM190 and RM225 on chromosome 6, by using the composite interval mapping (CIM) analysis. The two QTLs explained 15.1% and 9.31% of the total phenotypic variation in pollen fertility, and increased the pollen fertility of the plants subjected to HTS by 7.15% and 5.25%, respectively. The positive additive effects of the two QTLs were derived from the 996 alleles. The two major QTLs identified would be useful for further fine mapping and cloning of these genes and for molecular marker-assistant breeding of heat-tolerant rice varieties.

Detection of QTLs for Important Agronomic Traits and Analysis of Their Stabilities Using SSSLs in Rice

Single segment substitution lines （SSSLs） each with a single chromosome segment from a donor under the same genetic background as the recipient were developed in rice by advanced backcrossing and molecular marker-assisted selection. Using the SSSLs, the QTLs for the important agronomic traits in rice would be detected under different environmental conditions. Detection of the QTLs controlling 22 important traits in rice was done with 32 SSSLs by the randomized block design in 2-4 cropping seasons. 59 QTLs were detected and distributed on chromosomes 1, 2, 3, 4, 6, 7, 8, 10, and 11, of which 18 QTLs were detected more than twice. Only 30.5% of the QTLs were detected repeatedly in different cropping seasons. Most of the QTLs of important agronomic traits were of little additive effects and instability. The QTLs controlling the traits, such as grain weight, grain length, ratio of grain length to width, and heading date were relatively stable. The stable QTLs usually had larger additive effects and were less affected by environment. The QTLs for the important agronomic traits were detected using the SSSLs in rice with high resolution under different environmental conditions. The instability of the QTLs may be the basis of the variation of rice plants during growth and development. It would be the genetic basis for improving yield and quality in rice cultivars by farming methods.

QTL analysis of flag leaf in barley (Hordeum vulgare L.) for morphological traits and chlorophyll content

To understand genetic patterns of the morphological and physiological traits in flag leaf of barley, a double haploid （DH） population derived from the parents Yerong and Franklin was used to determine quantitative trait loci （QTL） controlling length, width, length/width, and chlorophyll content of flag leaves. A total of 9 QTLs showing significantly additive effect were detected in 8 intervals on 5 chromosomes. The variation of individual QTL ranged from 1.9% to 20.2%. For chlorophyll content expressed as SPAD value, 4 QTLs were identified on chromosomes 2H, 3H and 6H; for leaf length and width, 2 QTLs located on chromosomes 5H and 7H, and 2 QTLs located on chromosome 5H were detected; and for length/width, I QTL was detected on chromosome 7H. The identification of these QTLs associated with the properties of flag leaf is useful for barley improvement in breeding programs.

QTL analysis across multiple environments reveals promising chromosome regions associated with yield-related traits in maize under drought conditions

Drought is one of the most critical abiotic stresses influencing maize yield. Improving maize cultivars with drought tolerance using marker-assisted selection requires a better understanding of its genetic basis. In this study, a doubled haploid(DH) population consisting of 217 lines was created by crossing the inbred lines Han 21(drought-tolerant) and Ye 478(drought-sensitive). The population was genotyped with a 6 K SNP assay and 756 SNP(single nucleotide polymorphism) markers were used to construct a linkage map with a length of 1344 c M. Grain yield(GY), ear setting percentage(ESP), and anthesis–silking interval(ASI) were recorded in seven environments under well-watered(WW) and water-stressed(WS) regimes. High phenotypic variation was observed for all traits under both water regimes. Using the LSMEAN(least-squares mean) values from all environments for each trait, 18 QTL were detected, with 9 associated with the WW and 9 with the WS regime. Four chromosome regions,Chr. 3: 219.8–223.7 Mb, Chr. 5: 191.5–194.7 Mb, Chr. 7: 132.2–135.6 Mb, and Chr. 10: 88.2–89.4 Mb, harbored at least 2 QTL in each region, and QTL co-located in a region inherited favorable alleles from the same parent. A set of 64 drought-tolerant BC_3F_6 lines showed preferential accumulation of the favorable alleles in these four regions, supporting an association between the four regions and maize drought tolerance. QTL-by-environment interaction analysis revealed 28 ed QTL(environment-dependent QTL) associated with the WS regime and 22 associated with the WW regime for GY, ESP, and ASI. All WS QTL and55.6% of WW QTL were located in the ed QTL regions. The hotspot genomic regions identified in this work will support further fine mapping and marker-assisted breeding of drought-tolerant maize.

Quantitative trait loci analysis for root traits in synthetic hexaploid wheat under drought stress conditions

Synthetic hexaploid wheat(SHW),possesses numerous genes for drought that can help breeding for drought-tolerant wheat varieties.We evaluated 10 root traits at seedling stage in 111 F9 recombinant inbred lines derived from a F2 population of a SHW line(SHW-L1)and a common wheat line,under normal(NC)and polyethylene glycol-simulated drought stress conditions(DC).We mapped quantitative trait loci(QTLs)for root traits using an enriched high-density genetic map containing 120370 single nucleotide polymorphisms(SNPs),733 diversity arrays technology markers(DArT)and 119 simple sequence repeats(SSRs).With four replicates per treatment,we identified 19 QTLs for root traits under NC and DC,and 12 of them could be consistently detected with three or four replicates.Two novel QTLs for root fresh weight and root diameter under NC explained 9 and 15.7%of the phenotypic variation respectively,and six novel QTLs for root fresh weight,the ratio of root water loss,total root surface area,number of root tips,and number of root forks under DC explained 8.5–14%of the phenotypic variation.Here seven of eight novel QTLs could be consistently detected with more than three replicates.Results provide essential information for fine-mapping QTLs related to drought tolerance that will facilitate breeding drought-tolerant wheat cultivars.