Detection and validation of stay-green QTL in post-rainy sorghum involving widely adapted cultivar,M35-1 and a popular stay-green genotype B35

Background

Sorghum [Sorghum bicolor (L.) Moench] is an important dry-land cereal of the world providing food, fodder, feed and fuel. Stay-green (delayed-leaf senescence) is a key attribute in sorghum determining its adaptation to terminal drought stress. The objective of this study was to validate sorghum stay-green quantitative trait loci (QTL) identified in the past, and to identify new QTL in the genetic background of a post-rainy adapted genotype M35-1.

Results

A genetic linkage map based on 245 F₉ Recombinant Inbred Lines (RILs) derived from a cross between M35-1 (more senescent) and B35 (less senescent) with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers was used. The phenotypic data collected for three consecutive post-rainy crop seasons on the RIL population (M35-1 × B35) was used for QTL analysis. Sixty-one QTL were identified for various measures of stay-green trait and each trait was controlled by one to ten QTL. The phenotypic variation explained by each QTL ranged from 3.8 to 18.7%. Co-localization of QTL for more than five traits was observed on two linkage groups i.e. on SBI-09-3 flanked by S18 and Xgap206 markers and, on SBI-03 flanked by XnhsbSFCILP67 and Xtxp31. QTL identified in this study were stable across environments and corresponded to sorghum stay-green and grain yield QTL reported previously. Of the 60 genic SSRs mapped, 14 were closely linked with QTL for ten traits. A genic marker, XnhsbSFCILP67 (Sb03g028240) encoding Indole-3-acetic acid-amido synthetase GH3.5, was co-located with QTL for GLB, GLM, PGLM and GLAM on SBI-03. Genes underlying key enzymes of chlorophyll metabolism were also found in the stay-green QTL regions.

Conclusions

We validated important stay-green QTL reported in the past in sorghum and detected new QTL influencing the stay-green related traits consistently. Stg2, Stg3 and StgB were prominent in their expression. Collectively, the QTL/markers identified are likely candidates for subsequent verification for their involvement in stay-green phenotype using NILs and to develop drought tolerant sorghum varieties through marker-assisted breeding for terminal drought tolerance in sorghum.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-909) contains supplementary material, which is available to authorized users.     

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.     

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 QTL for sugar-related traits in a sweet × grain sorghum (<Emphasis Type="Italic">Sorghum bicolor</Emphasis> L. Moench) recombinant inbred population

QTL for stem sugar-related and other agronomic traits were identified in a converted sweet (R9188) × grain (R9403463-2-1) sorghum population. QTL analyses were conducted using phenotypic data for 11 traits measured in two field experiments and a genetic map comprising 228 SSR and AFLP markers grouped into 16 linkage groups, of which 11 could be assigned to the 10 sorghum chromosomes (SBI-01 to SBI-10). QTL were identified for all traits and were generally co-located to five locations (SBI-01, SBI-03, SBI-05, SBI-06 and SBI-10). QTL alleles from R9188 were detected for increased sucrose content and sugar content on SBI-01, SBI-05 and SBI-06. R9188 also contributed QTL alleles for increased Brix on SBI-05 and SBI-06, and increased sugar content on SBI-03. QTL alleles from R9403463-2-1 were found for increased sucrose content and sucrose yield on SBI-10, and increased glucose content on SBI-07. QTL alleles for increased height, later flowering and greater total dry matter yield were located on SBI-01 of R9403463-2-1, and SBI-06 of R9188. QTL alleles for increased grain yield from both R9403463-2-1 and R9188 were found on SBI-03. As an increase in stem sugars is an important objective in sweet sorghum breeding, the QTL identified in this study could be further investigated for use in marker-assisted selection of sweet sorghum.     

Identification of quantitative trait loci (QTL) for fruit-quality traits and number of weeks of flowering in the cultivated strawberry

Fruit quality and repeat flowering are two major foci of several strawberry breeding programs. The identification of quantitative trait loci (QTL) and molecular markers linked to these traits could improve breeding efficiency. In this work, an F₁ population derived from the cross ‘Delmarvel’ × ‘Selva’ was used to develop a genetic linkage map for QTL analyses of fruit-quality traits and number of weeks of flowering. Some QTL for fruit-quality traits were identified on the same homoeologous groups found in previous studies, supporting trait association in multiple genetic backgrounds and utility in multiple breeding programs. None of the QTL for soluble solids colocated with a QTL for titratable acids, and, although the total soluble solid contents were significantly and positively correlated with titratable acids, the correlation coefficient value of 0.2452 and independence of QTL indicate that selection for high soluble solids can be practiced independently of selection for low acidity. One genomic region associated with the total number of weeks of flowering was identified quantitatively on LG IV-S-1. The most significant marker, FxaACAO2I8C-145S, explained 43.3 % of the phenotypic variation. The repeat-flowering trait, scored qualitatively, mapped to the same region as the QTL. Dominance of the repeat-flowering allele was demonstrated by the determination that the repeat-flowering parent was heterozygous. This genomic region appears to be the same region identified in multiple mapping populations and testing environments. Markers linked in multiple populations and testing environments to fruit-quality traits and repeat flowering should be tested widely for use in marker-assisted breeding.     

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.     

Confirming quantitative trait loci for aflatoxin resistance from Mp313E in different genetic backgrounds

The fungus Aspergillus flavus (Link:Fr) causes ear rot of maize (Zea mays L.) and produces the toxic metabolic product aflatoxin. One particularly effective method of controlling the fungus is via host plant resistance, but while several resistant breeding lines have been identified, transferring the resistance genes from these lines into elite cultivars has been less effective than needed. A high number of genes involved with resistance, each with a small effect, and some only found under certain environmental conditions, has hampered resistance breeding. The identification of markers linked to genomic regions associated with resistance would aid in this effort. The goals of this study were to identify and characterize quantitative trait loci (QTL) conferring resistance to aflatoxin accumulation from resistant maize donor Mp313E in a background of the susceptible inbred line Va35; to compare them to the QTL identified from Mp313E in a background of B73; and to test the stability of the QTL identified in Mp313E × Va35 in multiple environments by remapping the phenotypic tails of the Mp313E × Va35 mapping population in new locations. Twenty different QTL were found in this study, 11 of which were also found in different environments using the phenotypic tail subset mapping population, and five of which were likely the same as those reported in the Mp313E × B73 mapping population. This indicates that many of the QTL are stable over the environments and genetic backgrounds tested, which will make them more valuable in breeding efforts.     

Analysis of an intraspecific RIL population uncovers genomic segments harbouring multiple QTL for seed relevant traits in lentil (<Emphasis Type="Italic">Lens culinaris</Emphasis> L.)

Improving seed related traits remains key objective in lentil breeding. In recent years, genomic resources have shown great promise to accelerate crop improvement. However, limited genomic resources in lentil greatly restrict the use of genomics assisted breeding. The present investigation aims to build an intraspecific genetic linkage map and identify the QTL associated with important seed relevant traits using 94 recombinant inbreds (WA 8649090 × Precoz). A total of 288 polymorphic DNA markers including simple sequence repeat (SSR), inter simple sequence repeat (ISSR) and random amplified polymorphic DNA (RAPD) were assayed on mapping population. The resultant genetic linkage map comprised 220 loci spanning 604.2 cM of the lentil genome, with average inter-marker distance of 2.74 cM. QTL mapping in this RIL population uncovered a total of 18 QTL encompassing nine major and nine minor QTL. All major QTL were detected for seed related traits viz., seed diameter (SD), seed thickness (ST), seed weight (SW) and seed plumpness (SP) across two locations. A considerable proportion of the phenotypic variation (PV) was accounted to these QTL. For instance, one major QTL on LG5 controlling SW (QTL 15) explained 50% PV in one location, while the same QTL accounted for 34.18% PV in other location. Importantly, the genomic region containing multiple QTL for different seed traits was mapped to a 17-cM region on LG5. The genomic region harbouring QTL for multiple traits opens up exciting opportunities for genomics assisted improvement of lentil.     

Characterization,development and mapping of Unigene-derived microsatellite markers in sorghum [<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench]

Molecular variation within known genes controlling specific functions provide candidate gene-based markers which are tightly linked with the trait of interest. Unigene-derived microsatellite markers, with their unique identity and positions, offer the advantage of unraveling variation in the expressed component of the genome. We characterized ≥12-bp-long microsatellite loci from 13,899 unique sequences of sorghum [Sorghum bicolor (L.) Moench] available in the NCBI unigene database for their abundance and possible use in sorghum breeding. Analysis of 12,464 unigenes (≥200-bp) using MISA software identified 14,082 simple sequence repeats (SSRs) in 7,370 unigenes, from which 1,519 unigene SSR markers were developed. The average frequency of SSR was 1 per1.6 kb and 1.0 per 1.1 unigene; hexamers followed by trimers were found in abundance, of which 33.3% AT-rich and CCG repeats were the most abundant. Of the 302 unigene SSRs tested, 60 (19.8%) were polymorphic between the two parents, M35-1 and B35 of a recombinant inbred line (RIL) mapping population. A mapping population consisting of 500 RILs was developed using the above two parents, and a subset of random 245 RILs was used for genotyping with polymorphic SSRs. We developed a linkage map containing 231 markers, of which 228 (174 genomic and 54 genic) were microsatellites and three were morphological markers. Markers were distributed over 21 linkage groups, and spanned a genetic distance of 1235.5 cM. This map includes 81 new SSRs, of which 35 (21 unigene and 14 genomic) were developed in the present study and 46 from other studies. The order of the SSR markers mapped in the present study was confirmed physically by BLAST search against the whole-genome shotgun sequence of sorghum. Many unigene sequences used for marker development in this study include genes coding for important regulatory proteins and functional proteins that are involved in stress-related metabolism. The unigene SSR markers used together with other SSR markers to construct the sorghum genetic map will have applications in studies on comparative mapping, functional diversity analysis and association mapping, and for quantitative trait loci detection for drought and other agronomically important traits in sorghum.     

Targeted mapping of quantitative trait locus regions for rhizomatousness in chromosome SBI-01 and analysis of overwintering in a Sorghum bicolor × S. propinquum population

While rhizome formation is intimately associated with perennialism and the derived benefit of sustainability, the introduction of this trait into temperate-zone adapted Sorghum cultivars requires precise knowledge of the genetics conditioning this trait in order to minimize the risk of weediness (e.g., Johnsongrass, S. halepense) while maximizing the productivity of perennial sorghum. As an incremental step towards dissecting the genetics of perennialism, a segregating F4 heterogeneous inbred family derived from a cross between S. bicolor and S. propinquum was phenotyped in both field and greenhouse environments for traits related to over-wintering and rhizome formation. An unseasonably cold winter in 2011 provided high selection pressure, and hence 74.8 % of the population did not survive. This severe selection pressure for cold tolerance allowed the resolution of two previously unidentified over-wintering quantitative trait locus (QTL) and more powerful correlation models than previously reported. Conflicting with previous reports, a maximum of 33 % of over-wintering variation could be explained by above-ground shoot formation from rhizomes; however, every over-wintering plant exhibited rhizome growth. Thus, while rhizome formation is required for over-wintering, other factors also determine survival in this interspecific population. The fine mapping of a previously reported rhizome QTL on sorghum chromosome SBI-01 was conducted by targeting this genomic region with additional simple sequence repeat markers. Fine mapping reduced the 2-LOD rhizome QTL interval from ~59 to ~14.5 Mb, which represents a 75 % reduction in physical distance and a 53 % reduction in the number of putative genes in the locus.     

Identification of genomic regions that affect grain-mould incidence and other traits of agronomic importance in sorghum

Grain-mould is a major problem in grain sorghum utilization as mouldy grain has a reduced quality due to the deterioration of the endosperm and reduced embryo viability. Here, our objective was to use genome mapping to improve knowledge of genetic variation and co-variation for grain-mould incidence and other inter-related agronomic traits. Grain-mould incidence, kernel-milling hardness, grain density, plant height, panicle peduncle length, foliar-disease incidence, and plant color were measured on 125 F₅ genotypes derived from a cross of Sureño and RTx430. Quantitative trait loci were detected by means of 130 mapped markers (44 microsatellites, 85 AFLPs, one morphological-trait locus) distributed among ten linkage groups covering 970 cM. One to five QTLs affected each trait, with the exception of grain density for which no QTLs were detected. Grain-mould incidence was affected by five QTLs each accounting for between 10 and 23% of the phenotypic variance. The effects and relative positions of QTLs for grain-mould incidence were in accordance with the QTL distribution of several inter-related agronomic traits (e.g., plant height, peduncle length) and with the correlation between these phenotypic traits and grain-mould incidence. The detection of QTLs for grain-mould incidence was dependent on the environment, which is consistent with heritibility estimates that show strong environmental and genotype × environment effects. Several genomic regions affected multiple traits including one region that affected grain-mould incidence, plant height, panicle peduncle length, and grain-milling hardness, and a second region that influenced grain-mould (in four environments) and plant height. One genomic region, which harbors loci for plant color, influenced the severity of foliar disease symptoms and the incidence of grain-mould in one environment. Collectively QTLs detected in the present population explained between 10% and 55% of the phenotypic variance observed for a given trait.     

Genetic dissection of drought tolerance in chickpea (Cicer arietinum L.)

Key message

Analysis of phenotypic data for 20 drought tolerance traits in 1–7 seasons at 1–5 locations together with genetic mapping data for two mapping populations provided 9 QTL clusters of which one present on CaLG04 has a high potential to enhance drought tolerance in chickpea improvement.

Abstract

Chickpea (Cicer arietinum L.) is the second most important grain legume cultivated by resource poor farmers in the arid and semi-arid regions of the world. Drought is one of the major constraints leading up to 50 % production losses in chickpea. In order to dissect the complex nature of drought tolerance and to use genomics tools for enhancing yield of chickpea under drought conditions, two mapping populations—ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261) segregating for drought tolerance-related root traits were phenotyped for a total of 20 drought component traits in 1–7 seasons at 1–5 locations in India. Individual genetic maps comprising 241 loci and 168 loci for ICCRIL03 and ICCRIL04, respectively, and a consensus genetic map comprising 352 loci were constructed (http://cmap.icrisat.ac.in/cmap/sm/cp/varshney/). Analysis of extensive genotypic and precise phenotypic data revealed 45 robust main-effect QTLs (M-QTLs) explaining up to 58.20 % phenotypic variation and 973 epistatic QTLs (E-QTLs) explaining up to 92.19 % phenotypic variation for several target traits. Nine QTL clusters containing QTLs for several drought tolerance traits have been identified that can be targeted for molecular breeding. Among these clusters, one cluster harboring 48 % robust M-QTLs for 12 traits and explaining about 58.20 % phenotypic variation present on CaLG04 has been referred as “QTL-hotspot”. This genomic region contains seven SSR markers (ICCM0249, NCPGR127, TAA170, NCPGR21, TR11, GA24 and STMS11). Introgression of this region into elite cultivars is expected to enhance drought tolerance in chickpea.     

Mapping of shoot fly tolerance loci in sorghum using SSR markers

Sorghum (Sorghum bicolor (L.) Moench) is one of the most important crops in the semiarid regions of the world. One of the important biotic constraints to sorghum production in India is the shoot fly which attacks sorghum at the seedling stage. Identification of the genomic regions containing quantitative trait loci (QTLs) for resistance to shoot fly and the linked markers can facilitate sorghum improvement programmes through marker-assisted selection. A simple sequence repeat (SSR) marker- based skeleton linkage map of two linkage groups of sorghum was constructed in a population of 135 recombinant inbred lines (RIL) derived from a cross between IS18551 (resistant to shoot fly) and 296B (susceptible to shoot fly). A total of 14 SSR markers, seven each on linkage groups A and C were mapped. Using data of different shoot fly resistance component traits, one QTL which is common for glossiness, oviposition and dead hearts was detected following composite interval mapping (CIM) on linkage group A. The phenotypic variation explained by this QTL ranged from 3.8%–6.3%. Besides the QTL detected by CIM, two more QTLs were detected following multi-trait composite interval mapping (MCIM), one each on linkage groups A and C for the combinations of traits which were correlated with each other. Results of the present study are novel as we could find out the QTLs governing more than one trait (pleiotropic QTLs). The identification of pleiotropic QTLs will help in improvement of more than one trait at a time with the help of the same linked markers. For all the QTLs, the resistant parent IS18551 contributed resistant alleles.     

Genetic Mapping of Quantitative Trait Loci Underlying Flowering Time in Chrysanthemum (Chrysanthemum morifolium)

Flowering time is an important trait in chrysanthemum, but its genetic basis remains poorly understood. An intra-specific mapping population bred from the cross between the autumn-flowering cultivar ‘Yuhualuoying’ and the summer-flowering ‘Aoyunhanxiao’ was used to determine the number and relative effect of QTL segregating for five measures of flowering time. From flowering time data recorded over two consecutive seasons, 35 additive QTL were detected, each explaining between 5.8% and 22.7% of the overall phenotypic variance. Of these, 13 were detected in both years. Nine genomic regions harboring QTL for at least two of the five traits were identified. Ten pairs of loci epistatically determined the flowering time, but their contribution to the overall phenotypic variance was less than for the additive QTL. The results suggest that flowering time in chrysanthemum is principally governed by main effect QTL but that epistasis also contributes to the genetic architecture of the trait, and the major QTL identified herein are useful in our ongoing efforts to streamline the improvement of chrysanthemum via the use of molecular methodology.     

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.     

大豆遗传图谱的构建和若干农艺性状的QTL定位分析

大豆许多重要农艺性状都是由微效多基因控制的数量性状,对这些数量性状进行QTL定位是大豆数量性状遗传研究领域的一个重要内容.本研究利用栽培大豆科新3号为父本、中黄20为母本杂交得到含192个单株的F2分离群体,构建了含122 个SSR标记、覆盖1719.6cM、由33个连锁群组成的连锁遗传图谱.利用复合区间作图法,对该群体的株高、主茎节数、单株粒重和蛋白质含量等农艺性状的调查数据进行QTL分析,共找到两个株高QTL,贡献率分别为9.15%和6.08%;两个主茎节数QTL,贡献率分别为10. 1%和8.6%;一个蛋白质含量QTL,贡献率为9.8%;一个单株粒重QTL,贡献率为11.4% .通过遗传作图共找到与所定位的4个农艺性状QTL连锁的6个SSR标记,这些标记可以应用于大豆种质资源的分子标记辅助选择,从而为大豆分子标记辅助育种提供理论依据.     

QTL mapping of potato chip color and tuber traits within an autotetraploid family

Cultivated potato (Solanum tuberosum L.) is a highly heterozygous autotetraploid crop species, and this creates challenges for traditional line development and molecular breeding. Recent availability of a single-nucleotide polymorphism (SNP) array with 8303 features and software packages for linkage and association mapping in autotetraploid species present new opportunities for the identification of genomic regions that contribute to high-value traits in cultivated potato. A biparental tetraploid potato population was evaluated across three field seasons and storage trials in order to identify quantitative trait loci (QTL) for multiple tuber traits including fried chip color after 5.5–7.2 °C storage. Tetra-allelic dosage information was used to construct a genetic linkage map that covered 1041 cM and contained 2095 SNP markers with a median marker interval of 0.4 cM. A total of 41 QTL were identified for flower color, tuber yield, tuber number per plant, tuber weight, tuber size, and chip color after various storage regimes. Moderate effect QTL for chip color at 3 months were identified that co-localized with candidate genes vacuolar invertase (VInv), invertase inhibitor (INH2), and apoplastic invertase (Inv _ap -b). A separate QTL for chip color after 6 months of storage was identified in the short arm of chromosome 2, and this locus may contribute to variation in senescent sweetening resistance. QTL for tuber weight, length, and width co-localized with a known QTL for plant maturity on chromosome 5. Genome-wide association mapping using a polyploid model detected the tuber size QTL and identified a number of candidate SNPs, but was unable to detect markers significantly associated with chip color.     

Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population

A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.     

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