Key messageAnalysis 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.AbstractChickpea (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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-013-2230-6) contains supplementary material, which is available to authorized users.

With an aim of enhancing drought tolerance using a marker-assisted backcrossing (MABC) approach, we introgressed the "QTL-hotspot" region from ICC 4958 accession that harbors quantitative trait loci (QTLs) for several drought-tolerance related traits into three elite Indian chickpea (Cicer arietinum L.) cultivars: Pusa 372, Pusa 362, and DCP 92-3. Of eight simple sequence repeat (SSR) markers in the QTLhotspot region, two to three polymorphic markers were used for foreground selection with respective cross-combinations. A total of 47, 53, and 46 SSRs were used for background selection in case of introgression lines (ILs) developed in genetic backgrounds of Pusa 372, Pusa 362, and DCP 92-3, respectively. In total, 61 ILs (20 BC 3 F 3 in Pusa 372; 20 BC 2 F 3 in Pusa 362, and 21 BC 3 F 3 in DCP 92-3), with >90% recurrent parent genome recovery were developed. Six improved lines in different genetic backgrounds (e.g. BGM 10216 in Pusa 372; BG 3097 and BG 4005 in Pusa 362; IPC(L4-14), IPC(L4-16), and IPC(L19-1) in DCP 92-3) showed better performance than their respective recurrent parents. BGM 10216, with 16% yield gain over Pusa 372, has been released as Pusa Chickpea 10216 by the Central SubCommittees on Crop Standards, Notification and Release of Varieties of Agricultural Crops, Ministry of Agriculture and Farmers Welfare, Government of India, for commercial cultivation in India. In summary, this study reports introgression of the QTL-hotspot

Three bacteria, IC-59, IC-76A and IC-2002, isolated from the nodules of chickpea, were characterized for nodulation, nitrogen fixation, plant growth-promoting (PGP) and yield traits in five cultivars of chickpea such as BG256, RSG888, Subhra, K850 and ICCV2. All the bacteria produced cellulase, protease, β-1,3-glucanase, indole acetic acid, siderophore, hydro cyanic acid and 1-aminocyclopropane-1-carboxylate deaminase while none produced lipase and chitinase. The 16 S rDNA gene sequences of IC-59, IC-76A and IC-2002 were found to match closely with Rhizobium pusense, Paraburkholderia kururiensis and Stenotrophomonas maltophilia, respectively. The three bacteria nodulated all the cultivars of chickpea well, amplified nifH gene and fixed nitrogen. Under greenhouse conditions at 30 and 45 days after sowing, treatment of five cultivars of chickpea with bacterial cultures IC-59, IC-76A and IC-2002, enhanced the nodule number (up to 45%, 38% and 43%), nodule weight (up to 31%, 15% and 39%), shoot weight (11%, 16% and 14%) and root weight (37%, 48% and 62%), respectively, over the un-inoculated control. At crop maturity, IC-59, IC-76A and IC-2002 were found to enhance the shoot weight (16%, 40% and 26%), pod number (37%, 69% and 81%), pod weight (17%, 45% and 49%), seed number (21%, 31% and 39%) and seed weight (14%, 56% and 65%), respectively, over the un-inoculated control. Among the five cultivars, Subhra was found to enhance most of the PGP traits when treated with the three diazotrophic bacteria. It is concluded that the three diazotrophic bacteria could be potentially exploited for improving nodulation, nitrogen fixation, PGP and yields of chickpea.

Biofortification through plant breeding is a cost-effective and sustainable approach towards addressing micronutrient malnutrition prevailing across the globe. Screening cultivars for micronutrient content and identification of quantitative trait loci (QTLs)/genes and markers help in the development of biofortified varieties in chickpea ( Cicer arietinum L.). With the aim of identifying the genomic regions controlling seed Fe and Zn concentrations, the F 2:3 population derived from a cross between MNK-1 and Annigeri 1 was genotyped using genotyping by sequencing approach and evaluated for Fe and Zn concentration. An intraspecific genetic linkage map comprising 839 single nucleotide polymorphisms (SNPs) spanning a total distance of 1,088.04 cM with an average marker density of 1.30 cM was constructed. By integrating the linkage map data with the phenotypic data of the F 2:3 population, a total of 11 QTLs were detected for seed Fe concentration on CaLG03, CaLG04, and CaLG05, with phenotypic variation explained ranging from 7.2% ( CaqFe3.4 ) to 13.4% ( CaqFe4.2 ). For seed Zn concentration, eight QTLs were identified on CaLG04, CaLG05, and CaLG08. The QTLs individually explained phenotypic variations ranging between 5.7% ( CaqZn8.1 ) and 13.7% ( CaqZn4.3 ). Three QTLs for seed Fe and Zn concentrations ( CaqFe4.4, CaqFe4.5 , and CaqZn4.1 ) were colocated in the “ QTL-hotspot ” region on CaLG04 that harbors several drought tolerance-related QTLs. We identified genes in the QTL regions that encode iron–sulfur metabolism and zinc-dependent alcohol dehydrogenase activity on CaLG03, iron ion binding oxidoreductase on CaLG04, and zinc-induced facilitator-like protein and ZIP zinc/iron transport family protein on CaLG05. These genomic regions and the associated markers can be used in marker-assisted selection to increase seed Fe and Zn concentrations in agronomically superior chickpea varieties.

Exploring the natural genetic variability and its exploitation for improved Nitrogen Use Efficiency (NUE) in sorghum is one of the primary goals in the modern crop improvement programs. The integrated strategies include high-throughput phenotyping, next generation sequencing (NGS)-based genotyping technologies, and a priori selected candidate gene studies that help understand the detailed physiological and molecular mechanisms underpinning this complex trait. A set of sixty diverse sorghum genotypes was evaluated for different vegetative, reproductive, and yield traits related to NUE in the field (under three N regimes) for two seasons. Significant variations for different yield and related traits under 0 and 50% N confirmed the availability of native genetic variability in sorghum under low N regimes. Sorghum genotypes with distinct genetic background had interestingly similar NUE associated traits. The Genotyping-By-Sequencing based SNPs (>89 K) were used to study the population structure, and phylogenetic groupings identified three distinct groups. The information of grain N and stalk N content of the individuals covered on the phylogenetic groups indicated randomness in the distribution for adaptation under variable N regimes. This study identified promising sorghum genotypes with consistent performance under varying environments, with buffer capacity for yield under low N conditions. We also report better performing genotypes for varied production use—grain, stover, and dual-purpose sorghum having differential adaptation response to NUE traits. Expression profiling of NUE associated genes in shoot and root tissues of contrasting lines (PVK801 and HDW703) grown in varying N conditions revealed interesting outcomes. Root tissues of contrasting lines exhibited differential expression profiles for transporter genes [ammonium transporter (SbAMT), nitrate transporters (SbNRT)]; primary assimilatory (glutamine synthetase (SbGS), glutamate synthase (SbGOGAT[NADH], SbGOGAT[Fd]), assimilatory genes [nitrite reductase (SbNiR[NADH]3)]; and amino acid biosynthesis associated gene [glutamate dehydrogenase (SbGDH)]. Identification and expression profiling of contrasting sorghum genotypes in varying N dosages will provide new information to understand the response of NUE genes toward adaptation to the differential N regimes in sorghum. High NUE genotypes identified from this study could be potential candidates for in-depth molecular analysis and contribute toward the development of N efficient sorghum cultivars.