Identification and validation of genomic regions that affect shoot fly resistance in sorghum [<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench]

Shoot fly is one of the most important pests affecting the sorghum production. The identification of quantitative trait loci (QTL) affecting shoot fly resistance enables to understand the underlying genetic mechanisms and genetic basis of complex interactions among the component traits. The aim of the present study was to detect QTL for shoot fly resistance and the associated traits using a population of 210 RILs of the cross 27B (susceptible) × IS2122 (resistant). RIL population was phenotyped in eight environments for shoot fly resistance (deadheart percentage), and in three environments for the component traits, such as glossiness, seedling vigor and trichome density. Linkage map was constructed with 149 marker loci comprising 127 genomic-microsatellite, 21 genic-microsatellite and one morphological marker. QTL analysis was performed by using MQM approach. 25 QTL (five each for leaf glossiness and seedling vigor, 10 for deadhearts, two for adaxial trichome density and three for abaxial trichome density) were detected in individual and across environments. The LOD and R ² (%) values of QTL ranged from 2.44 to 24.1 and 4.3 to 44.1%, respectively. For most of the QTLs, the resistant parent, IS2122 contributed alleles for resistance; while at two QTL regions, the susceptible parent 27B also contributed for resistance traits. Three genomic regions affected multiple traits, suggesting the phenomenon of pleiotrophy or tight linkage. Stable QTL were identified for the traits across different environments, and genetic backgrounds by comparing the QTL in the study with previously reported QTL in sorghum. For majority of the QTLs, possible candidate genes were identified. The QTLs identified will enable marker assisted breeding for shoot fly resistance in sorghum.     

Identification of quantitative trait loci for resistance to shoot fly in sorghum [<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench]

The shoot fly is one of the most destructive insect pests of sorghum at the seedling stage. Deployment of cultivars with improved shoot fly resistance would be facilitated by the use of molecular markers linked to QTL. The objective of this study was to dissect the genetic basis of resistance into QTL, using replicated phenotypic data sets obtained from four test environments, and a 162 microsatellite marker-based linkage map constructed using 168 RILs of the cross 296B (susceptible) × IS18551 (resistant). Considering five component traits and four environments, a total of 29 QTL were detected by multiple QTL mapping (MQM) viz., four each for leaf glossiness and seedling vigor, seven for oviposition, six for deadhearts, two for adaxial trichome density and six for abaxial trichome density. The LOD and R ² (%) values of QTL ranged from 2.6 to 15.0 and 5.0 to 33%, respectively. For most of the QTL, IS18551 contributed resistance alleles; however, at six QTL, alleles from 296B also contributed to resistance. QTL of the related component traits were co-localized, suggesting pleiotropy or tight linkage of genes. The new morphological marker Trit for trichome type was associated with the major QTL for component traits of resistance. Interestingly, QTL identified in this study correspond to QTL/genes for insect resistance at the syntenic maize genomic regions, suggesting the conservation of insect resistance loci between these crops. For majority of the QTL, possible candidate genes lie within or very near the ascribed confidence intervals in sorghum. Finally, the QTL identified in the study should provide a foundation for marker-assisted selection (MAS) programs for improving shoot fly resistance in sorghum.     

Genomic diversity among sorghum genotypes with resistance to sorghum shoot fly, Atherigona soccata

Host plant resistance is one of the important components for management of sorghum shoot fly, Atherigona soccata. The levels of resistance in cultivated germplasm are low to moderate, and therefore, it is important to identify sorghum genotypes with diverse mechanisms of resistance based on physico-chemical and or molecular markers. We assessed the genetic diversity of 15 sorghum genotypes with different levels of resistance/susceptibility to shoot fly, A. soccata using 93 sorghum simple sequence repeat (SSR) primer pairs and simultaneously characterized for 15 morpho-biochemical traits associated with shoot fly resistance. Of these 93 SSR primer pairs, amplification products from 79, thought to correspond to single-copy loci distributed across all ten sorghum chromosome pairs, showed good polymorphism across the 15 sorghum genotypes. The polymorphic information content (PIC) values of these 79 SSR markers ranged from 0.06 to 0.86. The Principal Coordinate Analyses (PCoA) and cluster analyses based on dissimilarity matrices derived from SSR based allelic variation (Neighbor-Joining distance) and variation in 15 morpho-biochemical traits (based on Gower??s distance), revealed grouping of most susceptible genotypes in single cluster. The improved breeding lines grouped with resistant or susceptible genotypes, based on shared pedigree. Based on these results, three resistant accessions viz., IS 1054, IS 1057 and IS 4664 were found diverse to IS 18551, which is widely used as shoot fly resistance donor. These diverse sources, after further characterization for resistance mechanisms, can be used in breeding programs for improving shoot fly resistance.     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

Leaf surface chemistry of sorghum seedlings influencing expression of resistance to sorghum shoot fly, Atherigona soccata

Sorghum shoot fly, Atherigona soccata is one of the serious constraints to sorghum production, and host plant resistance is an important component for controlling this pest. We studied the expression of resistance to A. soccata in a diverse array of sorghum genotypes in relation to composition of leaf surface chemicals during the seedling stage. The sorghum genotypes IS 1054, IS 1057, IS 2146, IS 4664, IS 2312, IS 2205, SFCR 125, SFCR 151, ICSV 700, and IS 18551 exhibited antixenosis for oviposition, and suffered less deadhearts due to sorghum shoot fly, A. soccata. Compounds undecane 5- methyl, decane 4- methyl, hexane 2, 4- methyl, pentadecane 8- hexyl, and dodecane 2, 6, 11- trimethyl, present on the leaf surface of sorghum seedlings, were associated with susceptibility to shoot fly; while 4, 4- dimethyl cyclooctene was associated with resistance to shoot fly. The compounds associated with resistance/susceptibility to shoot fly, can be used as marker traits to select for resistance as well as for diversifying and increasing the levels of resistance to this pest. The role of biochemical compounds for developing sorghum varieties with resistance to shoot fly, A. soccata has been discussed.     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

Identification of a major quantitative trait locus conditioning resistance to greenbug biotype E in sorghum PI 550610 using simple sequence repeat markers

Greenbug, Schizaphis graminum (Rondani), represents the most important pest insect of sorghum, Sorghum bicolor (L.) Moench, in the Great Plains of the United States. Biotype E is the most widespread and dominant type not only in sorghum and wheat, Triticum aestivum L., fields, but also on many noncultivated grass species. This study was designed to determine sorghum accession PI 550610 resistance to greenbug biotype E, to map the resistance quantitative trait loci (QTLs) by using an established simple sequence repeat (SSR) linkage map and to identify SSR markers closely linked to the major resistance QTLs. In greenhouse screening tests, seedlings of PI 550610 showed strong resistance to the greenbug at a level similar to resistant accession PI550607. For QTL mapping, one F2 population containing 277 progeny and one population containing 233 F2:3 families derived from Westland A line x PI 550610 were used to genotype 132 polymorphic SSR markers and to phenotype seedling resistance to greenbug feeding. Phenotypic evaluation of sorghum seedling damage at 7, 12, 17, and 21 d postinfestation in the F2:3 families revealed that resistance variation was normally distributed. Single marker analysis indicated 16 SSRs spread over five chromosomes were significant for greenbug resistance. Composite interval and multiple interval mapping procedures indicated that a major QTL resided in the interval of 6.8 cM between SSR markers Xtxp358 and Xtxp289 on SBI-09. The results will be valuable in the development of new greenbug biotype E resistant sorghum cultivars and for the further characterization of major genes by map-based cloning.     

QTL analysis of ergot resistance in sorghum

Sorghum ergot, caused predominantly by Claviceps africana Frederickson, Mantle, de Milliano, is a significant threat to the sorghum industry worldwide. The objectives of this study were firstly, to identify molecular markers linked to ergot resistance and to two pollen traits, pollen quantity (PQ) and pollen viability (PV), and secondly, to assess the relationship between the two pollen traits and ergot resistance in sorghum. A genetic linkage map of sorghum RIL population R931945-2-2 x IS 8525 (resistance source) was constructed using 303 markers including 36 SSR, 117 AFLPtrade mark, 148 DArTtrade mark and two morphological trait loci. Composite interval mapping identified nine, five, and four QTL linked to molecular markers for percentage ergot infection (PCERGOT), PQ and PV, respectively, at a LOD >2.0. Co-location/linkage of QTL were identified on four chromosomes while other QTL for the three traits mapped independently, indicating that both pollen and non pollen-based mechanisms of ergot resistance were operating in this sorghum population. Of the nine QTL identified for PCERGOT, five were identified using the overall data set while four were specific to the group data sets defined by temperature and humidity. QTL identified on SBI-02 and SBI-06 were further validated in additional populations. This is the first report of QTL associated with ergot resistance in sorghum. The markers reported herein could be used for marker-assisted selection for this important disease of sorghum.     

Molecular mapping of QTLs for resistance to the greenbug <Emphasis Type="Italic">Schizaphis graminum</Emphasis> (Rondani) in <Emphasis Type="Italic">Sorghum bicolor</Emphasis> (Moench)

Sorghum is a worldwide important cereal crop and widely cultivated for grain and forage production. Greenbug, Schizaphis graminum (Rondani) is one of the major insect pests of sorghum and can cause serious damage to sorghum plants, particularly in the US Great Plains. Identification of chromosomal regions responsible for greenbug resistance will facilitate both map-based cloning and marker-assisted breeding. Thus, a mapping experiment was conducted to dissect sorghum genetic resistance to greenbug biotype I into genomic regions. Two hundred and seventy-seven (277) F(2) progeny and their F(2:3) families from a cross between Westland A line (susceptible parent) and PI550610 (resistant parent) combined with 118 polymorphic simple sequence repeat (SSR) markers were used to map the greenbug resistance QTLs. Composite interval mapping (CIM) and multiple interval mapping (MIM) revealed two QTLs on sorghum chromosome nine (SBI-09) consistently conditioned the resistance of host plant to the greenbug. The two QTLs were designated as QSsgr-09-01 (major QTL) and QSsgr-09-02 (minor QTL), accounting for approximately 55-80%, and 1-6% of the phenotypic variation for the resistance to greenbug feeding, respectively. These resistance QTLs appeared to have additive and partially dominant effects. The markers Xtxp358, Xtxp289, Xtxp67 and Xtxp230 closely flanked the respective QTLs, and can be used in high-throughput marker-assisted selections (MAS) for breeding new resistant parents and producing commercial hybrids.     

Genetic mapping of QTLs associated with greenbug resistance and tolerance in Sorghum bicolor

Ninety three recombinant inbreds of Sorghum bicolor (L. Moench) were derived from a cross between two sorghum lines GBIK and Redlan. This population was used to identify quantitative trait loci (QTLs) for resistance and tolerance to greenbug (Schizaphids graminum Rondani) Biotypes I and K. One hundred and thirteen loci (38 SSRs and 75 RAPDs) were mapped in 12 linkage groups covering 1,530 cM. In general, nine QTLs were detected affecting both resistance and tolerance to greenbug (GB) Biotypes I and K. The phenotypic variance explained by each QTL ranged from 5.6% to 38.4%. Four SSRs and one RAPD marker were associated with the expression of all resistance and tolerance traits. These markers appear to be linked to biotype non-specific resistance and tolerance genes. Four additional markers were associated with biotype-specific resistance or tolerance traits. The detection of more than one locus for each biotype supports the hypothesis that several regions, which represent different genes, control the expression of resistance and tolerance to greenbug in sorghum. The results can be used for marker-assisted selection and the breeding of greenbug-tolerant sorghum cultivars.     

Quantitative Trait Loci Mapping of Leaf Morphological Traits and Chlorophyll Content in Cultivated Tetraploid Cotton

Genetic mapping provides a powerful tool for quantitative trait loci （QTL） analysis at the molecular level. A simple sequence repeat （SSR） genetic map containing 590 markers and a BCI population from two cultivated tetraploid cotton （Gossypium hirsutum L.） cultivars, namely TM-1 and Hai 7124 （G. barbadense L.）, were used to map and analyze QTL using the composite interval mapping （CIM） method. Thirty one QTLs, 10 for lobe length, 13 for lobe width, six for lobe angle, and two for leaf chlorophyll content, were detected on 15 chromosomes or linkage groups at logarithm of odds （LOD）≥2.0, of which 15 were found for leaf morphology at LOD≥3.0. The genetic effects of the QTL were estimated. These results are fundamental for marker-assisted selection （MAS） of these traits in tetraploid cotton breeding.     

QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat

In bread wheat, single-locus and two-locus QTL analyses were conducted for seven yield and yield contributing traits using two different mapping populations (P I and P II). Single-locus QTL analyses involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated yield traits to detect the pleiotropic QTLs. Two-locus analyses were conducted to detect main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions (QE and QQE). Only a solitary QTL for spikelets per spike was common between the above two populations. HomoeoQTLs were also detected, suggesting the presence of triplicate QTLs in bread wheat. Relatively fewer QTLs were detected in P I than in P II. This may be partly due to low density of marker loci on P I framework map (173) than in P II (521) and partly due to more divergent parents used for developing P II. Six QTLs were important which were pleiotropic/coincident involving more than one trait and were also consistent over environments. These QTLs could be utilized efficiently for marker assisted selection (MAS).     

Mapping of QTLs governing agronomic and yield traits in chickpea

Chickpea is one of the most important leguminous cool season food crops, cultivated prevalently in South Asia and Middle East. The main objective of this study was to identify quantitative trait loci (QTLs) associated with seven agronomic and yield traits in two recombinant inbred line populations of chickpea derived from the crosses JG62 × Vijay (JV population) and Vijay × ICC4958 (VI population) from at least three environments. Single locus QTL analysis involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated traits to detect pleiotropic QTLs. Two-locus analysis was conducted to identify the main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions. Through CIM analysis, a total of 106 significant QTLs (41 in JV and 65 in VI populations) were identified for the seven traits, of which one QTL each for plant height and days to maturity was common in both the populations. Six pleiotropic QTLs that were consistent over the environments were also identified. LG2 in JV and LG1a in VI contained at least one QTL for each trait. Hence, concentrating on these LGs in molecular breeding programs is most likely to bring simultaneous improvement in these traits.     

QTL for fibre-related traits in grain × sweet sorghum as a tool for the enhancement of sorghum as a biomass crop

Compared to maize and temperate grasses, sorghum has received less attention in terms of improving cell wall components. The objectives of this study were to identify quantitative trait loci (QTL) with main effects, epistatic and pleiotropic effects along with QTL × environment (QE) interactions controlling fibre-related traits in sorghum. Neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), cellulose, hemicellulose, fresh leaf mass, stripped stalk mass, dry stalk mass, fresh biomass and dry biomass were analysed from a population of 188 grain × sweet sorghum recombinant inbred lines. A genetic map consisting of 157 DNA markers was constructed, and QTL were detected using composite interval mapping (CIM). CIM detected more than 5 additive QTL per trait explaining 7.1–24.7% of the phenotypic variation. Abundant co-localization of these QTL was observed across all chromosomes, and the highest cluster was identified on chromosome 6. Searching for candidate genes using the confidence interval of our QTL clusters reveals that these clusters might comprise a set of genes that are tightly linked. Some QTL showed multiple effects; however, the allele for each trait was favouring the parent with the increasing effect. QE interactions were observed for QTL showing multiple effects. Additive × additive interaction was observed for 7 out of 10 traits, indicating the importance of epistatic analysis. However, the phenotypic variation explained by digenic interactions was lower compared to the individual QTL. Our results indicate that various genetic components contribute to fibre-related traits and should be considered during the enhancement of sorghum for lignocellulosic biomass.     

Constructing a genetic linkage map and mapping quantitative trait loci for skeletal traits in Japanese flounder

A genetic linkage map of Japanese flounder was constructed using 165 doubled haploids (DHs) derived from a single female. A total of 574 genomic microsatellites (type II SSRs) and expressed sequence tag (EST)-derived markers (EST-SSRs) were mapped to 24 linkage groups. The length of linkage map was estimated as 1270.9 centiMorgans (cM), with an average distance between markers of 2.2 cM. The EST-SSRs were used together with type II SSR markers to construct the Japanese flounder genetic linkage map which will facilitate identify quantitative trait locus (QTL) controlling important economic traits in Japanese flounder. Thus, twelve skeletal traits at 2 years of age were measured for all DHs. Forty-one QTLs were detected on 14 linkage groups and totally account for a small proportion of phenotypic variation (4.5 to 17.3%). Most of QTLs detected distribute on linkage groups 5 (9 QTLs), 8 (9 QTLs), 9 (5 QTLs) and 20 (4 QTLs), in which, some QTLs perform the pleiotropy.     

Quantitative trait loci for yield and related traits in the wheat population Ning7840 × Clark

Grain yield and associated agronomic traits are important factors in wheat (Triticum aestivum L.) improvement. Knowledge regarding the number, genomic location, and effect of quantitative trait loci (QTL) would facilitate marker-assisted selection and the development of cultivars with desirable characteristics. Our objectives were to identify QTLs directly and indirectly affecting grain yield expression. A population of 132 F₁₂ recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese facultative wheat Ning7840 and the US soft red winter wheat Clark. Phenotypic data were collected for 15 yield and other agronomic traits in the RILs and parental lines from three locations in Oklahoma from 2001 to 2003. Twenty-nine linkage groups, consisting of 363 AFLP and 47 SSR markers, were identified. Using composite interval mapping (CIM) analysis, 10, 16, 30, and 14 QTLs were detected for yield, yield components, plant adaptation (shattering and lodging resistance, heading date, and plant height), and spike morphology traits, respectively. The QTL effects ranged from 7 to 23%. Marker alleles from Clark were associated with a positive effect for the majority of QTLs for yield and yield components, but gene dispersion was the rule rather than the exception for this RIL population. Often, QTLs were detected in proximal positions for different traits. Consistent, co-localized QTLs were identified in linkage groups 1AL, 1B, 4B, 5A, 6A, and 7A, and less consistent but unique QTLs were identified on 2BL, 2BS, 2DL, and 6B. Results of this study provide a benchmark for future efforts on QTL identification for yield traits.     

Mapping QTL for grain yield and other agronomic traits in post-rainy sorghum [Sorghum bicolor (L.) Moench]

Sorghum, a cereal of economic importance ensures food and fodder security for millions of rural families in the semi-arid tropics. The objective of the present study was to identify and validate quantitative trait loci (QTL) for grain yield and other agronomic traits using replicated phenotypic data sets from three post-rainy dry sorghum crop seasons involving a mapping population with 245 F₉ recombinant inbred lines derived from a cross of M35-1 × B35. A genetic linkage map was constructed with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers. The QTL analysis for 11 traits following composite interval mapping identified 91 QTL with 5–12 QTL for each trait. QTL detected in the population individually explained phenotypic variation between 2.5 and 30.3 % for a given trait and six major genomic regions with QTL effect on multiple traits were identified. Stable QTL across seasons were identified. Of the 60 genic markers mapped, 21 were found at QTL peak or tightly linked with QTL. A gene-based marker XnhsbSFCILP67 (Sb03g028240) on SBI-03, encoding indole-3-acetic acid-amido synthetase GH3.5, was found to be involved in QTL for seven traits. The QTL-linked markers identified for 11 agronomic traits may assist in fine mapping, map-based gene isolation and also for improving post-rainy sorghum through marker-assisted breeding.     

Mapping of quantitative trait loci (QTLs) for oil yield using SSRs and gene-based markers in African oil palm (<Emphasis Type="Italic">Elaeis guineensis</Emphasis> Jacq.)

The identification of quantitative trait loci (QTLs) based on anchor markers, especially candidate genes that control a trait of interest, has been noted to increase the power of QTL detection. Since these markers can be scored as co-dominant data, they are also valuable for comparing and integrating the QTL linkage maps from diverse mapping populations. To estimate the position and effects of QTLs linked to oil yield traits in African oil palm, co-dominant microsatellites (SSR) and candidate gene-based sequence polymorphisms were applied to construct a linkage map for a progeny showing large differences in oil yield components. The progeny was genotyped for 97 SSR markers, 93 gene-linked markers, and 12 non-gene-linked SNP markers. From these, 190 segregating loci could be arranged into 31 linkage groups while 12 markers remained unmapped. Using the single marker linkage, interval mapping and multiple QTL methods, 16 putative QTLs on seven linkage groups affecting important oil yield related traits such as fresh fruit bunch yield (FFB), ratio of oil per fruit (OF), oil per bunch (OB), fruit per bunch (FB) and wet mesocarp per fruit (WMF) could be identified in the segregating population with estimated values for explained variance ranging from 12.4 % to 54.5 %. Markers designed from some candidate genes involved in lipid biosynthesis were found to be mapped near significant QTLs for various economic yield traits. Associations between QTLs and potential candidate genes are discussed.     

A QTL study on late leaf spot and rust revealed one major QTL for molecular breeding for rust resistance in groundnut (Arachis hypogaea L.)

Late leaf spot (LLS) and rust are two major foliar diseases of groundnut (Arachis hypogaea L.) that often occur together leading to 50–70% yield loss in the crop. A total of 268 recombinant inbred lines of a mapping population TAG 24 × GPBD 4 segregating for LLS and rust were used to undertake quantitative trait locus (QTL) analysis. Phenotyping of the population was carried out under artificial disease epiphytotics. Positive correlations between different stages, high to very high heritability and independent nature of inheritance between both the diseases were observed. Parental genotypes were screened with 1,089 simple sequence repeat (SSR) markers, of which 67 (6.15%) were found polymorphic. Segregation data obtained for these markers facilitated development of partial linkage map (14 linkage groups) with 56 SSR loci. Composite interval mapping (CIM) undertaken on genotyping and phenotyping data yielded 11 QTLs for LLS (explaining 1.70–6.50% phenotypic variation) in three environments and 12 QTLs for rust (explaining 1.70–55.20% phenotypic variation). Interestingly a major QTL associated with rust (QTL_rust01), contributing 6.90–55.20% variation, was identified by both CIM and single marker analysis (SMA). A candidate SSR marker (IPAHM 103) linked with this QTL was validated using a wide range of resistant/susceptible breeding lines as well as progeny lines of another mapping population (TG 26 × GPBD 4). Therefore, this marker should be useful for introgressing the major QTL for rust in desired lines/varieties of groundnut through marker-assisted backcrossing.     

Identification of QTLs for eight agronomically important traits using an ultra-high-density map based on SNPs generated from high-throughput sequencing in sorghum under contrasting photoperiods

The productivity of sorghum is mainly determined by agronomically important traits. The genetic bases of these traits have historically been dissected and analysed through quantitative trait locus (QTL) mapping based on linkage maps with low-throughput molecular markers, which is one of the factors that hinder precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, an ultra-high-density linkage map based on high-quality single nucleotide polymorphisms (SNPs) generated from low-coverage sequences (~0.07 genome sequence) in a sorghum recombinant inbred line (RIL) population was constructed through new sequencing technology. This map consisted of 3418 bin markers and spanned 1591.4 cM of genome size with an average distance of 0.5 cM between adjacent bins. QTL analysis was performed and a total of 57 major QTLs were detected for eight agronomically important traits under two contrasting photoperiods. The phenotypic variation explained by individual QTLs varied from 3.40% to 33.82%. The high accuracy and quality of this map was evidenced by the finding that genes underlying two cloned QTLs, Dw3 for plant height (chromosome 7) and Ma1 for flowering time (chromosome 6), were localized to the correct genomic regions. The close associations between two genomic regions on chromosomes 6 and 7 with multiple traits suggested the existence of pleiotropy or tight linkage. Several major QTLs for heading date, plant height, numbers of nodes, stem diameter, panicle neck length, and flag leaf width were detected consistently under both photoperiods, providing useful information for understanding the genetic mechanisms of the agronomically important traits responsible for the change of photoperiod.