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Drought is the most important yield limiting abiotic stress worldwide and could have negative effects on food security. This study was conducted to map yield and yield-contributing trait QTLs under drought stress by association mapping, and to in silico identify drought responsive genes and assay their expression profile. Association analysis was conducted using 181 SSR markers and nine phenotypic traits collected from a structured sorghum population consisting of 96 accessions evaluated under optimum and drought stressed conditions at Assiut University Experimental Farm, Assiut, Egypt. Genomic regions associated with major drought tolerance QTLs were annotated with NCBI and sorghum databases to identify drought responsive genes, which were further transcriptionally analyzed. Significant differences between optimum irrigation and drought-stressed conditions were observed in all measured phenotypic traits. Association analysis revealed 93 marker-trait associations between 71 SSR markers and the nine phenotypic traits with an R2 value ranging from 6.56 to 42.64%. A high degree of linkage disequilibrium (>52%) was identified among markers on different chromosomes, suggesting epistatic interaction. BLASTP annotation of QTL genomic sequences identified 86 gene homologs, from which fifteen genes are drought responsive. All fifteen genes were differentially expressed in drought tolerant and susceptible accessions and their expression levels were highly induced in response to drought stress. The results provide a powerful approach coupling association and in silico analyses to identify gene clusters having a common expression profile with similar function, pointing to an evolutionary mechanism to initiate a quantitative drought stress tolerance mechanism.

Charcoal rot disease, a root and stem disease caused by the soil-borne fungus Macrophomina phaseolina (Tassi) Goid., is a major biotic stress that limits sorghum productivity worldwide. Charcoal rot resistance-related parameters, e.g., pre-emergence damping-off%, post-emergence damping-off%, charcoal rot disease severity, and plant survival rates, were measured in a structured sorghum population consisting of 107 landraces. Analysis of variance of charcoal rot resistance-related parameters revealed significant variations in the response to M. phaseolina infection within evaluated accessions. Continuous phenotypic variations for resistance-related parameters were observed indicating a quantitative inheritance of resistance. The population was genotyped using 181 simple sequence repeat (SSR) markers. Association analysis identified 13 markers significantly associated with quantitative trait genes (QTLs) conferring resistance to charcoal rot disease with an R2 value ranging between 9.47 to 18.87%, nine of which are environment-specific loci. Several QTL-linked markers are significantly associated with more than one resistance-related parameter, suggesting that those QTLs might contain genes involved in the plant defense response. In silico analysis of four novel major QTLs identified 11 putative gene homologs that could be considered as candidate genes for resistance against charcoal rot disease. Cluster analysis using the genotypic data of 181 SSR markers from 107 sorghum accessions identified 12 main clusters. The results provide a basis for further functional characterization of charcoal rot disease resistance or defense genes in sorghum and for further dissection of their molecular mechanisms.

The molecular genetic basis of cotton fiber strength and fineness in crosses between Gossypium mustelinum and Gossypium hirsutum (Upland cotton) was dissected using 21 BC3F2 and 12 corresponding BC3F2:3 and BC3F2:4 families. The BC3F2 families were genotyped with simple sequence repeat markers from a G. hirsutum by G. mustelinum linkage map, and the three generations of BC3-derived families were phenotyped for fiber strength (STR) and fineness (Micronaire, MIC). A total of 42 quantitative trait loci (QTLs) were identified through one-way analysis of variance, including 15 QTLs for STR and 27 for MIC, with the percentage of variance explained by individual loci averaging 13.86 and 14.06%, respectively. Eighteen of the 42 QTLs were detected at least twice near the same markers in different generations/families or near linked markers in the same family, and 28 of the 42 QTLs were identified in both mixed model-based composite interval mapping and one-way variance analyses. Alleles from G. mustelinum increased STR for eight of 15 and reduced MIC for 15 of 27 QTLs. Significant among-family genotypic effects (P < 0.001) were detected in 13 and 10 loci for STR and MIC respectively, and five loci showed significant (P < 0.001) genotype × family interaction for MIC. These results support the hypothesis that fiber quality improvement for Upland cotton could be realized by introgressing G. mustelinum alleles although complexities due to the different effects of genetic background on introgressed chromatin might be faced. Building on prior work with G. barbadense, G. tomentosum, and G. darwinii, QTL mapping involving introgression of G. mustelinum alleles offers new allelic variation to Upland cotton germplasm.

Two hundred ninety­six Asian barley (Hordeum vulgare L.) accessions were assessed to detect QTLs underlying salt tolerance by association analysis using a 384 single nucleotide polymorphism (SNP) marker system. The experiment was laid out at the seedling stage in a hydroponic solution under control and 250 mM NaCl solution with three replications of four plants each. Salt tolerance was assessed by leaf injury score (LIS) and salt tolerance indices (STIs) of the number of leaves (NL), shoot length (SL), root length (RL), shoot dry weight (SDW) and root dry weight (RDW). LIS was scored from 1 to 5 according to the severity of necrosis and chlorosis observed on leaves. There was a wide variation in salt tolerance among Asian barley accessions. LIS and STI (SDW) were the most suitable traits for screening salt tolerance. Association was estimated between markers and traits to detect QTLs for LIS and STI (SDW). Seven significant QTLs were located on chromosomes 1H (2 QTLs), 2H (2 QTLs), 3H (1 QTL), 4H (1 QTL) and 5H (1 QTL). Five QTLs were asso­ ciated with LIS and 2 QTLs with STI (SDW). Two QTLs associated with LIS were newly identified on chromosomes 3H and 4H.

In recent years, sorghum (Sorghum bicolor (L.) Moench) has gained attention as a food, feed, and biofuel crop, but yield improvements have lagged behind those in other crops. Here, we investigated quantitative trait loci (QTLs) associated with yield and yield-related traits in sorghum. We measured eight morphological traits related to yield potential in an F2 and F2:3 population derived from a cross between African and Japanese sorghum landraces, and we developed a genetic linkage map of 137 sorghum genome-based simple sequence repeat markers. The total map length was 1,239.2 cM, with an average distance of 9.9 cM between adjacent markers. By using both single- and multiple-QTL approaches to identify the chromosomal regions controlling these traits, we identified a total of 52 QTLs associated with the eight traits (culm length, number of tillers, panicle length, culm diameter, leaf length, leaf width, grain weight/panicle, and 100-grain weight) using F2 phenotypic values while 25 QTLs were confirmed in the F2:3 population. The percentage phenotypic variation explained by individual QTLs ranged from 3.1 to 36.3 % in the F2 and 2.1 to 30.4 % in the F2:3 population. Most of the traits were significantly correlated with one another (P

Salinity is globally a major constraint for crop production. Breeding for salinity tolerance is an effective approach to improve crop production and productivity under saline conditions provided it is based on a good understanding of the genetic control of salinity tolerance. This study deals with mapping QTLs for salinity tolerance in durum wheat (Triticum durum) by association analysis using SSR markers. A total of 119 varieties were treated in 100 mM of NaCl solution and the salinity tolerance indices (STI) for several traits were calculated as parameters to assess salinity tolerance. Among the traits assessed, the increased proportion of dead leaves (%DL) was the most suitable parameter for assessment of salinity tolerance in durum varieties at early vegetative stages because of a broader range of variation among varieties and narrower range of variation within varieties compared to other traits. The QTL associated with salinity tolerance using %DL as a parameter was detected on chromosome 4B. An additional 11 QTLs associated with seven parameters using STI of other traits were detected on chromosomes 3A, 5A, 5B, 6A and 7A.

The pattern of the panicle is an important characteristic of sorghum that is used to identify race divisions and species values. The knowledge of the genetic basis of sorghum inflorescence architecture and its component traits can enhance the process of improvement in sorghum breeding. This study was undertaken to better understand the genetic basis of sorghum inflorescence architecture and its association with yield-related traits. We investigated 98 simple sequence repeat maps in the sorghum diversity research set (SDRS) of 107 landraces from the worldwide sorghum germplasm. A significant difference between accessions was observed for 14 measured traits. In several components of sorghum inflorescence architecture, we found that the significance and high correlations between pairs of traits revealed that these variations are dependent not only on the panicle length (PanL) but also on the total branch number, maximum length of the primary branch (MaxLBZ/MxLBZ) , rachis length (Rac), and panicle diameter (PanD) and width (Panw). Significant mean squares were obtained for almost all characters in the individual analysis and combined analysis of variance for each season and across two seasons, suggesting that, the components of inflorescence architecture and yield related traits were highly variable in SDRS population, therefore, would respond to selection for yield improvement. Molecular markers divided the germplasm into three sub-populations with different groups of inflorescence/panicle types (PanT) (broom, open and compact). The SDRS was composed of six different PanT that were associated with 14 inflorescence traits. Using different models of association analysis, 16 loci on 8 chromosomes were found to be significantly related to the patterns of observed panicle traits. Among these loci, four QTLs were responsible for length-based traits, and three QTLs were responsible for dimentional traits. Four QTLs were responsible for panicle feature such as PanT and shape, one QTL responsible for yield related trait such as grain weight. Two QTLs were responsible for branch-based traits, such as the total node number and branch number with −Log10 (P) values ranging from 1.5 to 7.6 as the threshold value. Several genomic regions affected multiple traits, including one region that affected PanL and MxLBZ/MaxLBZ. QTLs for different traits tended to be found in the same region on chromosome 4 and on chromosome 9. Additionally, QTL was involved on Chr-2, Chr-5, Chr-6 and Chr-10 as a novel QTL that controlled Rac, total node number, PanD and PanT. These results will serve as preliminary findings of QTLs for sorghum inflorescence architecture, and a further evaluation of the germplasm for these traits is in progress. Moreover, these findings can lead to the emergence of a new era of sorghum genomics, which are aimed at bridging the knowledge gap between genotype and phenotype in sorghum inflorescence architecture.

This study was conducted to identify quantitative trait loci (QTLs) for drought tolerance in sorghum (Sorghum bicolor (L.) Moench) by association mapping using a simple sequence repeat (SSR)-marker-based diversity research set. Genotypic data for 98 SSR marker loci on ten chromosomes were used for the association analysis. The experiment was conducted under control (well-watered) and drought stress conditions, and the phenotypic values of 23 morphological traits were recorded. Drought tolerance was assessed by using a leaf drying score as a parameter of the tolerance/susceptibility: scores were assigned on a scale from 1 (most tolerant) to 9 (most susceptible). Under the control conditions, 17 QTLs associated with 12 traits were identified on chromosomes 1, 2, 4, 8, 9, and 10, with −Log10 (P) ranging from 2.5 to 7.6 and explaining 9.5–57.5 % of the total phenotypic variance for the traits. Under the drought stress conditions, nine QTLs associated with 8 traits were identified on chromosomes 1, 2, 3, and 10 that explained 9–61.2 % of the total phenotypic variance for the traits, with −Log10 (P) ranging from 2.5 to 3.5. QTLs for some traits were detected only under the drought stress condition, suggesting that these traits are important in drought tolerance. These QTLs could be used to further dissect the genetic and physiological basis of drought tolerance in sorghum.

This study was undertaken to analyse the variation in panicle-related traits of 206 sorghum accessions collected from 27 Asian and African countries. Significant differences among the accessions were observed for 18 measured traits. First, we found that the patterns of the observed panicle-related traits reflected the distribution of the accessions of different origins. Second, the distribution of several components of inflorescence architecture in sorghum accessions influenced their yield components. Principal component analysis of the data showed a wide range of variations across the 206 sorghum accessions. Despite their geographical isolation, no distinct separation between the Asian and African accessions was observed. Correlation coefficient and path coefficient analysis indicated that panicle length (PanL), the total number of branches, rachis length (Rac) and panicle width had a positive direct effect on grain yield. Finally, we showed that the variation in the inflorescence architecture of sorghum accessions was dependent not only on the PanL, but also on the total number of branches, the maximum length of primary branches, Rac, panicle diameter and panicle width. Thus, there are major panicle determinants that are strongly associated with grain yield which should be considered in breeding programmes. These results will serve as a starting point for further evaluation of sorghum germplasm via quantitative trait loci analysis and may be useful for improving yield based on careful consideration of trait selection and inflorescence morphology.

Due to its critical importance in crop yield, the photoperiodic regulation of flowering time is considered an important trait in sorghum breeding programs. In this study, quantitative trait loci for flowering time were detected using an F(2) population derived from a cross between Kikuchi Zairai, a late-flowering cultivar originating from Japan and SC112, an early-flowering cultivar originating from Ethiopia. F(2) plants were grown with their parents under a natural day length and a 12 h day length. Two linkage maps were constructed using 213 simple sequence repeats markers. Nine quantitative trait loci controlling flowering time were identified in F(2) plants grown under a natural day length, whereas 7 QTLs were identified under a 12 h day length. Five QTLs controlling flowering time were shared under both of the day length conditions.

In mapping populations segregating for many loci, the large amount of variation among genotypes often masks small-effect quantitative trait loci (QTL). This problem can be reduced by development of populations with fewer chromosome segments segregating. Here, we report early QTL detection in reciprocal advanced backcross populations from crosses between elite Gossypium hirsutum L. ‘Acala Maxxa’ (GH) and G. barbadense L. ‘Pima S6’ (GB). A total of 297 BCF and BCF progeny rows—127 segregating for GB chromosome segments in GH background and 170 segregating for GH chromosome segments in GB background—were evaluated in three environments. Totals of 3186 and 3026 polymorphic single-nucleotide polymorphisms (SNPs) in GH and GB backgrounds, respectively, were identified and used for trait mapping. Small-effect QTL (

Association or linkage disequilibrium mapping is alternative to identify QTLs in plants. In this study we used SSR based sorghum diversity research set (SDRS) of 107 sorghum accessions. The representative set included a geographically diverse collection of accessions from 27 countries in Asia and Africa. For association analysis 98 sorghum SSR markers were selected from three previously published linkage maps. Phenotypic data was recorded for 26 morphological traits. Different association models were used to identify QTLs controlling major agronomic traits including both single QTL approaches as well as a multiple QTL approach. All models revealed loci having different strength of association with morphological traits. A total of 14 common significant SSR loci were identified by three different models of association analysis namely, single-QTL models with the effects of population structure, single-QTL models with the effects of population structure and familial relatedness, and multiple-QTL model with the effects of population structure. These loci were associated with 12 different morphological traits including days to heading, days to flowering, culm length, number of tillers, number of panicles and panicle length. Comparing results from different models may be an efficient way to detect reliable associations in the genome-wide association studies.

A wide range of variation in flowering time was observed within a diversity research set of 107 sorghum accessions ranging from 56 to 133 days. Accessions were classified into early medium and late flowering groups. 45 accessions were grown under three different environments of photoperiod (11, 12 and 15 h). Sorghum accessions gradually responded to the decreasing of day-length. The 12 h of photo- period could be considered as a threshold above which day-length delays the flowering time in sorghum. Association analysis was performed to identify the QTLs controlling flowering time and photoperiod sensitivity using 107 accessions of sorghum grown under natural condition and 45 accessions grown under controlled conditions. Four QTLs controlling flowering time were detected under natural condition of day-length at threshold 2.5 using K model. A total of seven flowering time loci were detected under controlled conditions of day-length. One QTL controlling photoperiod sensitivity was detected on chromosome 1 and one QTL controlling photoperiod insensitivity was detected on chromo- some 4.