Bi-parental Mapping Populations Research Articles

A GWAS identified a major QTL for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in a MAGIC population of Upland cotton and a meta-analysis of QTLs for Fusarium wilt resistance.

A major QTL conferring resistance to Fusarium wilt race 4 in a narrow region of chromosome D02 was identified in a MAGIC population of 550 RILs of Upland cotton. Numerous studies have been conducted to investigate the genetic basis of Fusarium wilt (FW, caused by Fusarium oxysporum f. sp. vasinfectum, FOV) resistance using bi-parental and association mapping populations in cotton. In this study, a multi-parent advanced generation inter-cross (MAGIC) population of 550 recombinant inbred lines (RILs), together with their 11 Upland cotton (Gossypium hirsutum) parents, was used to identify QTLs for FOV race 4 (FOV4) resistance. Among the parents, Acala Ultima, M-240 RNR, and Stoneville 474 were the most resistant, while Deltapine Acala 90, Coker 315, and Stoneville 825 were the most susceptible. Twenty-two MAGIC lines were consistently resistant to FOV4. Through a genome-wide association study (GWAS) based on 473,516 polymorphic SNPs, a major FOV4 resistance QTL within a narrow region on chromosomes D02 was detected, allowing identification of 14 candidate genes. Additionally, a meta-analysis of 133 published FW resistance QTLs showed a D subgenome and individual chromosome bias and no correlation between homeologous chromosome pairs. This study represents the first GWAS study using a largest genetic population and the most comprehensive meta-analysis for FW resistance in cotton. The results illustrated that 550 lines were not enough for high resolution mapping to pinpoint a candidate gene, and experimental errors in phenotyping cotton for FW resistance further compromised the accuracy and precision in QTL localization and identification of candidate genes. This study identified FOV4-resistant parents and MAGIC lines, and the first major QTL for FOV4 resistancein Upland cotton, providing useful information for developing FOV4-resistant cultivars and further genomic studies towards identification of causal genes for FOV4 resistance in cotton.

Combined GWAS and QTL mapping revealed candidate genes and SNP network controlling recovery and tolerance traits associated with drought tolerance in seedling winter wheat

To date, very little research on drought tolerance has been conducted at the seedling stage in winter wheat. In this study, two types of traits, namely tolerance and recovery traits, associated with drought tolerance were scored in biparental mapping population (BPP) and association mapping population (A-set). The results of this study revealed no or weak significant correlation between the two types of traits. Based on GWAS and QTL mapping analyses, all QTLs associated with recovery traits were completely different from those associated with tolerance traits except one QTL in each population that was found to be associated with one tolerance trait and one recovery trait. The analysis of SNP and gene networks confirmed the results of combined GWAS and QTL mapping. One SNP marker located on the 2B chromosome (S2B_26494801) was found to be associated with recovery traits in both populations. The results of this study provided new information on understanding and improving drought tolerance in winter wheat.

Insights into the Genomic Architecture of Seed and Pod Quality Traits in the U.S. Peanut Mini-Core Diversity Panel.

Traits such as seed weight, shelling percent, percent sound mature kernels, and seed dormancy determines the quality of peanut seed. Few QTL (quantitative trait loci) studies using biparental mapping populations have identified QTL for seed dormancy and seed grade traits. Here, we report a genome-wide association study (GWAS) to detect marker–trait associations for seed germination, dormancy, and seed grading traits in peanut. A total of 120 accessions from the U.S. peanut mini-core collection were evaluated for seed quality traits and genotyped using Axiom SNP (single nucleotide polymorphism) array for peanut. We observed significant variation in seed quality traits in different accessions and different botanical varieties. Through GWAS, we were able to identify multiple regions associated with sound mature kernels, seed weight, shelling percent, seed germination, and dormancy. Some of the genomic regions that were SNP associated with these traits aligned with previously known QTLs. For instance, QTL for seed dormancy has been reported on chromosome A05, and we also found SNP on the same chromosome associated with seed dormancy, explaining around 20% of phenotypic variation. In addition, we found novel genomic regions associated with seed grading, seed germination, and dormancy traits. SNP markers associated with seed quality and dormancy identified here can accelerate the selection process. Further, exploring the function of candidate genes identified in the vicinity of the associated marker will assist in understanding the complex genetic network that governs seed quality.

MIG-seq is an effective method for high-throughput genotyping in wheat (Triticum spp.)

MIG-seq (Multiplexed inter-simple sequence repeats genotyping by sequencing) has been developed as a low cost genotyping technology, although the number of polymorphisms obtained is assumed to be minimal, resulting in the low application of this technique to analyses of agricultural plants. We applied MIG-seq to 12 plant species that include various crops and investigated the relationship between genome size and the number of bases that can be stably sequenced. The genome size and the number of loci, which can be sequenced by MIG-seq, are positively correlated. This is due to the linkage between genome size and the number of simple sequence repeats (SSRs) through the genome. The applicability of MIG-seq to population structure analysis, linkage mapping, and quantitative trait loci (QTL) analysis in wheat, which has a relatively large genome, was further evaluated. The results of population structure analysis for tetraploid wheat showed the differences among collection sites and subspecies, which agreed with previous findings. Additionally, in wheat biparental mapping populations, over 3,000 SNPs/indels with low deficiency were detected using MIG-seq, and the QTL analysis was able to detect recognized flowering-related genes. These results revealed the effectiveness of MIG-seq for genomic analysis of agricultural plants with large genomes, including wheat.

Identification of QTLs Controlling Resistance to Anthracnose Disease in Water Yam (Dioscorea alata).

Anthracnose disease caused by a fungus Colletotrichum gloeosporioides is the primary cause of yield loss in water yam (Dioscorea alata), the widely cultivated species of yam. Resistance to yam anthracnose disease (YAD) is a prime target in breeding initiatives to develop durable-resistant cultivars for sustainable management of the disease in water yam cultivation. This study aimed at tagging quantitative trait loci (QTL) for anthracnose disease resistance in a bi-parental mapping population of D. alata. Parent genotypes and their recombinant progenies were genotyped using the Genotyping by Sequencing (GBS) platform and phenotyped in two crop cycles for two years. A high-density genetic linkage map was built with 3184 polymorphic Single Nucleotide Polymorphism (NSP) markers well distributed across the genome, covering 1460.94 cM total length. On average, 163 SNP markers were mapped per chromosome with 0.58 genetic distances between SNPs. Four QTL regions related to yam anthracnose disease resistance were identified on three chromosomes. The proportion of phenotypic variance explained by these QTLs ranged from 29.54 to 39.40%. The QTL regions identified showed genes that code for known plant defense responses such as GDSL-like Lipase/Acylhydrolase, Protein kinase domain, and F-box protein. The results from the present study provide valuable insight into the genetic architecture of anthracnose resistance in water yam. The candidate markers identified herewith form a relevant resource to apply marker-assisted selection as an alternative to a conventional labor-intensive screening for anthracnose resistance in water yam.

QTL mapping and colocalization analysis reveal novel candidate genes for multiple disease resistance in maize

AbstractUnpredictable pathogen pressures resulting from changing climatic patterns have required plant breeders to breed crop cultivars with durable resistance to multiple plant pathogens. The genetic basis of multiple disease resistance (MDR) is an important component in building durable resistance in crop plants. Maize (Zea mays L.) inbred NY22613, developed at Cornell University, has shown resistance to northern leaf blight (NLB), gray leaf spot (GLS), common rust, and Stewart's wilt (SW). In order to unravel the genetic basis of MDR in NY22613, quantitative trait locus (QTL) mapping and colocalization studies were conducted. A BC3S3 biparental mapping population (resistant inbred NY22613 and susceptible recurrent inbred Oh7B) was used to map the QTL responsible for disease resistance. The analysis revealed that 16 QTL were associated with NLB resistance, 17 QTL with GLS resistance, and 16 QTL with SW resistance. No QTL were colocalized for all three diseases. Three QTL were shared for NLB and GLS in chromosomes 7, 9, and 10 and one QTL was shared for GLS and SW in chromosome 2. These QTL contain the following genes that have been previously associated with disease resistance: Zm00001d002005 (lg1, liguleless1), Zm00001d024007, Zm00001d024008, LOC103642379, and LOC103641009. These regions also contain the following novel genes, which have not been associated with any function: LOC541757, Zm00001d044974, Zm00001d044975, and LOC109941121. To select individuals with MDR, a novel selection method was developed that combines phenotypic data, QTL data, and high‐density marker information in a cluster analysis designated as the high‐density marker phenotype (HEMP) QTL selection strategy.

Modeling allelic diversity of multiparent mapping populations affects detection of quantitative trait loci.

The search for quantitative trait loci that explain complex traits such as yield and drought tolerance has been ongoing in all crops. Methods such as biparental quantitative trait loci mapping and genome-wide association studies each have their own advantages and limitations. Multiparent advanced generation intercross populations contain more recombination events and genetic diversity than biparental mapping populations and are better able to estimate effect sizes of rare alleles than association mapping populations. Here, we discuss the results of using a multiparent advanced generation intercross population of doubled haploid maize lines created from 16 diverse founders to perform quantitative trait loci mapping. We compare 3 models that assume bi-allelic, founder, and ancestral haplotype allelic states for quantitative trait loci. The 3 methods have differing power to detect quantitative trait loci for a variety of agronomic traits. Although the founder approach finds the most quantitative trait loci, all methods are able to find unique quantitative trait loci, suggesting that each model has advantages for traits with different genetic architectures. A closer look at a well-characterized flowering time quantitative trait loci, qDTA8, which contains vgt1, highlights the strengths and weaknesses of each method and suggests a potential epistatic interaction. Overall, our results reinforce the importance of considering different approaches to analyzing genotypic datasets, and shows the limitations of binary SNP data for identifying multiallelic quantitative trait loci.

Genetic control of source-sink relationships in grain sorghum.

QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18Mb), 2 (2.52-11.43Mb) and 3 (1.32-3.95Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

High-Density Single Nucleotide Polymorphisms Genetic Map Construction and Quantitative Trait Locus Mapping of Color-Related Traits of Purple Sweet Potato [Ipomoea batatas (L.) Lam.

Flesh color (FC), skin color (SC), and anthocyanin content (AC) are three important traits being used for commodity evaluation in purple-fleshed sweet potato. However, to date, only a few reports are available on the inheritance of these traits. In this study, we used a biparental mapping population of 274 F1 progeny generated from a cross between a dark purple-fleshed (Xuzishu8) and white-fleshed (Meiguohong) sweet potato variety for genetic analyses. Correlation analysis showed a significant positive correlation among AC, SC, and FC. Medium-to-high heritability was observed for these traits. We detected single nucleotide polymorphisms (SNPs) by specific length amplified fragment sequencing (SLAF-seq) with the average sequencing depth of 51.72 and 25.76 for parents and progeny, respectively. Then we constructed an integrated genetic map consisting of 15 linkage groups (LGS) of sweet potato spanning on 2,233.66 cm with an average map distance of 0.71 cm between adjacent markers. Based on the linkage map, ten major quantitative trait loci (QTLs) associated to FC, SC, and AC were identified on LG12 between 0 and 64.97 cm distance, such as one QTL for SC and FC, respectively, which explained 36.3 and 45.9% of phenotypic variation; eight QTLs for AC, which explained 10.5–28.5% of the variation. These major QTLs were highly consistent and co-localized on LG12. Positive correlation, high heritability, and co-localization of QTLs on the same LG group confirm the significance of this study to establish a marker-assisted breeding program for sweet potato improvement.

Biparental Crossing and QTL Mapping for Validation of Genome-Wide Association Studies.

Association mapping (AM), also known as genome-wide association studies (GWAS), is increasingly being employed in crop plants for the identification of QTL/genes and marker-trait associations (MTAs) in natural populations. Large numbers of such associations have been identified for variety of traits in different crop plants. However, not many of these associations have been used practically in the crop improvement program due to lack of validation. Although there are different ways through which the results of AM/GWAS could be validated, the best approach is to develop a biparental population for the trait of interest. An overview of the steps involved in the validation of results of AM using biparental mapping population in plants is provided in this chapter.

Genomic regions associated with resistance to Fusarium wilt in castor identified through linkage and association mapping approaches.

Fusarium wilt, caused by Fusarium oxysporum f. sp. ricini, is the most destructive disease in castor. Host plant resistance is the best strategy for the management of wilt. Identification of molecular markers linked to wilt resistance will enhance the efficiency and effectiveness of breeding for wilt resistance. In the present study, genomic regions linked to wilt resistance were mapped using a bi-parental population of 185 F6-RILs and a genetically diverse panel of 300 germplasm accessions. Quantitative trait loci (QTL) analysis performed using a linkage map consisting of 1090 SNP markers identified a major QTL on chromosome 7 with an LOD score of 18.7, which explained 44% of the phenotypic variance. The association mapping performed using genotypic data from 3465 SNP loci revealed 69 significant associations (p< 1 × 10-4) for wilt resistance. The phenotypic variance explained by the individual SNPs ranged from 0.063 to 0.210. The QTL detected in the bi-parental mapping population was not identified in the association analysis. Thus, the results of this study indicate the possibility of vast gene diversity for Fusarium wilt resistance in castor.

Addressing Iron and Zinc Micronutrient Malnutrition Through Nutrigenomics in Pearl Millet: Advances and Prospects.

Iron (Fe) and zinc (Zn) micronutrient deficiencies are significant health concerns, particularly among the underprivileged and resource-poor people in the semi-arid tropics globally. Pearl millet is regarded as a climate-smart crop with low water and energy footprints. It thrives well under adverse agro-ecologies such as high temperatures and limited rainfall. Pearl millet is regarded as a nutri-cereal owing to health-promoting traits such as high grain Fe and Zn content, metabolizable energy, high antioxidant and polyphenols, high proportion of slowly digestible starches, dietary fibers, and favorable essential amino acid profile compared to many cereals. Higher genetic variability for grain Fe and Zn content has facilitated considerable progress in mapping and mining QTLs, alleles and genes underlying micronutrient metabolism. This has been made possible by developing efficient genetic and genomic resources in pearl millet over the last decade. These include genetic stocks such as bi-parental RIL mapping populations, association mapping panels, chromosome segment substitution lines (CSSLs) and TILLING populations. On the genomics side, considerable progress has been made in generating genomic markers, such as SSR marker repository development. This was followed by the development of a next-generation sequencing-based genome-wide SNP repository. The circa 1,000 genomes re-sequencing project played a significant role. A high-quality reference genome was made available by re-sequencing of world diversity panel, mapping population parents and hybrid parental lines. This mini-review attempts to provide information on the current developments on mapping Fe and Zn content in pearl millet and future outlook.

Identification and molecular mapping of a major quantitative trait locus underlying branch angle in soybean.

A major quantitative trait locus (QTL) modulating soybean (Glycine max) branch angle was identified by linkage analysis using two bi-parental mapping populations with and without pedigree from wild soybean (Glycine soja). Soybean branch angle is a critical architectural trait that affects many other traits of agronomic importance associated with the plant's productivity and grain yield and is thus a vital consideration in soybean breeding. However, the genetic basis for modulating this important trait in soybean and many other crops remain unknown. Previously, we developed a recombinant inbred line (RIL) population derived from a cross between a domesticated soybean (Glycine max) variety, Williams 82, and a wild soybean (Glycine soja) accession, PI 479,752, and observed drastic variation in plant architecture including branch angle among individual RILs. In this study, one of the RILs possessing extremely wide branch angle (WBA) was crossed with an elite soybean cultivar (LD00-3309) possessing narrow branch angle (NBA) to produce an F2 population composed of 147 plants and F2-derived F3 families for inheritance analysis and QTL mapping. We found that branch angle is controlled by a major QTL located on chromosome 19, designated qGmBa1 and that WBA-derived from the wild soybean accession-is dominant over NBA. This locus was also detected as a major one underlying branch angle by QTL mapping using a subset of the soybean nested association mapping (SoyNAM) population composed of 140 RILs, which were derived from a cross between a landrace, PI 437169B, possessing WBA and an elite variety, IA3023, possessing NBA. Molecular markers located in the QTL region defined by both mapping populations can be used for marker-assisted selection of branch angle in soybean breeding.

Genetic trade-offs underlie divergent life history strategies for local adaptation in white clover.

Local adaptation is common in plants, yet characterization of its underlying genetic basis is rare in herbaceous perennials. Moreover, while many plant species exhibit intraspecific chemical defence polymorphisms, their importance for local adaptation remains poorly understood. We examined the genetic architecture of local adaptation in a perennial, obligately-outcrossing herbaceous legume, white clover (Trifolium repens). This widespread species displays a well-studied chemical defence polymorphism for cyanogenesis (HCN release following tissue damage) and has evolved climate-associated cyanogenesis clines throughout its range. Two biparental F2 mapping populations, derived from three parents collected in environments spanning the U.S. latitudinal species range (Duluth, MN, St. Louis, MO and Gainesville, FL), were grown in triplicate for two years in reciprocal common garden experiments in the parental environments (6,012 total plants). Vegetative growth and reproductive fitness traits displayed trade-offs across reciprocal environments, indicating local adaptation. Genetic mapping of fitness traits revealed a genetic architecture characterized by allelic trade-offs between environments, with 100% and 80% of fitness QTL in the two mapping populations showing significant QTL×E interactions, consistent with antagonistic pleiotropy. Across the genome there were three hotspots of QTL colocalization. Unexpectedly, we found little evidence that the cyanogenesis polymorphism contributes to local adaptation. Instead, divergent life history strategies in reciprocal environments were major fitness determinants: selection favoured early investment in flowering at the cost of multiyear survival in the southernmost site versus delayed flowering and multiyear persistence in the northern environments. Our findings demonstrate that multilocus genetic trade-offs contribute to contrasting life history characteristics that allow for local adaptation in this outcrossing herbaceous perennial.

The Soybean High Density 'Forrest' by 'Williams 82' SNP-Based Genetic Linkage Map Identifies QTL and Candidate Genes for Seed Isoflavone Content.

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306); map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020); identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents.

Genomic Scan of Male Fertility Restoration Genes in a 'Gülzow' Type Hybrid Breeding System of Rye (Secale cereale L.).

Efficient and stable restoration of male fertility (Rf) is a prerequisite for large-scale hybrid seed production but remains an inherent issue in the predominant fertility control system of rye (Secale cereale L.). The ‘Gülzow’ (G)-type cytoplasmic male sterility (CMS) system in hybrid rye breeding exhibits a superior Rf. While having received little scientific attention, one major G-type Rf gene has been identified on 4RL (Rfg1) and two minor genes on 3R (Rfg2) and 6R (Rfg3) chromosomes. Here, we report a comprehensive investigation of the genetics underlying restoration of male fertility in a large G-type CMS breeding system using recent advents in rye genomic resources. This includes: (I) genome-wide association studies (GWAS) on G-type germplasm; (II) GWAS on a biparental mapping population; and (III) an RNA sequence study to investigate the expression of genes residing in Rf-associated regions in G-type rye hybrids. Our findings provide compelling evidence of a novel major G-type non-PPR Rf gene on the 3RL chromosome belonging to the mitochondrial transcription termination factor gene family. We provisionally denote the identified novel Rf gene on 3RL RfNOS1. The discovery made in this study is distinct from known P- and C-type systems in rye as well as recognized CMS systems in barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.). We believe this study constitutes a stepping stone towards understanding the restoration of male fertility in the G-type CMS system and potential resources for addressing the inherent issues of the P-type system.

Lens orientalis Contributes Quantitative Trait Loci and Candidate Genes Associated With Ascochyta Blight Resistance in Lentil.

Australian lentil production is affected by several major biotic constraints including Ascochyta blight (AB), caused by Ascochyta lentis, a devastating fungal disease. Cultivation of AB resistant cultivars, alongside agronomic management including fungicide application, is the current most economically viable control strategy. However, the breakdown of AB resistance in cultivars, such as Northfield and Nipper, suggests the need for introgression of new and diverse resistance genes. Successful introgression entails an understanding of the genetic basis of resistance. In this context, a biparental mapping population derived from a cross between a recently identified AB resistant accession ILWL 180 (Lens orientalis) and a susceptible cultivar ILL 6002 was produced. A genetic linkage map was constructed from single-nucleotide polymorphism markers generated using a genotyping-by-sequencing transcript approach. Genetic dissection of the mapping population revealed a major quantitative trait loci (QTL) region nested with three QTLs on linkage group 5 and explained 9.5–11.5 percent (%) of phenotypic variance for AB resistance. Another QTL was identified on LG2 with phenotypic variance of 9.6%. The identified QTL regions harbored putative candidate genes potentially associated with defense responses to A. lentis infection. The QTL analysis and the candidate gene information are expected to contribute to the development of diagnostic markers and enable marker-assisted resistance selection in lentil breeding programmes.

New PCR-specific markers for pollen fertility restoration QRfp-4R in rye (Secale cereale L.) with Pampa sterilizing cytoplasm

Pampa cytoplasmic male sterility phenomenon is used extensively in the rye hybrid breeding programs. It relies on sterilizing action of the cytoplasm resulting in non-viable pollen of female lines. The sterilizing effect is problematic for reversion, and efficient restores are needed. The most promising QTL is located on chromosome 4R, but other chromosomes may also code the trait. Advanced recombinant inbred lines formed bi-parental mapping population genotyped with DArTseq markers. Genetic mapping allowed the seven linkage groups to construct with numerous markers and represent all rye chromosomes. Single marker analysis and composite interval mapping were conducted to identify markers linked to the pollen fertility. Association mapping was used to detect additional markers associated with the trait. A highly significant QTL (QRfp-4R) that explained 42.3% of the phenotypic variation was mapped to the distal part of the long arm of the 4R chromosome. The markers localized in the QRfp-4R region achieve R2 association values up to 0.59. The homology of the 43 marker sequences to the loci responsible for fertility restoration in other species and transcription termination factor (mTERF) linked to Rf genes was established. Ten markers were successfully converted into PCR-specific conditions, and their segregation pattern was identical to that of unconverted DArTs.

On-field phenotypic evaluation of sunflower populations for broad-spectrum resistance to Verticillium leaf mottle and wilt

Sunflower Verticillium Wilt and Leaf Mottle (SVW), caused by Verticillium dahliae (Kleb.; Vd), is a soil-borne disease affecting sunflower worldwide. A single dominant locus, known as V1, was formerly effective in controlling North-American Vd races, whereas races from Argentina, Europe and an emerging race from USA overcome its resistance. This emphasizes the need for identifying broad-spectrum genetic resistance (BSR) sources. Here we characterize two sunflower mapping populations (MPs) for SVW resistance: a biparental MP and the association MP from the National Institute of Agricultural Technology (INTA), under field growing conditions. Nine field-trials (FTs) were conducted in highly infested fields in the most SVW-affected region of Argentina. Several disease descriptors (DDs), including incidence and severity, were scored across four phenological stages. Generalized linear models were fitted according to the nature of each variable, adjusting mean phenotypes for inbred lines across and within FTs. Comparison of these responses allowed the identification of novel BSR sources. Furthermore, we present the first report of SVW resistance heritability, with estimates ranging from 35 to 45% for DDs related to disease incidence and severity, respectively. This study constitutes the largest SVW resistance characterization reported to date in sunflower, identifying valuable genetic resources for BSR-breeding to cope with a pathogen of increasing importance worldwide.

Multi-Environment Quantitative Trait Loci Mapping for Grain Iron and Zinc Content Using Bi-parental Recombinant Inbred Line Mapping Population in Pearl Millet.

Pearl millet is a climate-resilient, nutritious crop with low input requirements that could provide economic returns in marginal agro-ecologies. In this study, we report quantitative trait loci (QTLs) for iron (Fe) and zinc (Zn) content from three distinct production environments. We generated a genetic linkage map using 210 F6 recombinant inbred line (RIL) population derived from the (PPMI 683 × PPMI 627) cross using genome-wide simple sequence repeats (SSRs). The molecular linkage map (seven linkage groups) of 151 loci was 3,273.1 cM length (Kosambi). The content of grain Fe in the RIL population ranged between 36 and 114 mg/Kg, and that of Zn from 20 to 106 mg/Kg across the 3 years (2014–2016) at over the three locations (Delhi, Dharwad, and Jodhpur). QTL analysis revealed a total of 22 QTLs for grain Fe and Zn, of which 14 were for Fe and eight were for Zn on three consecutive years at all locations. The observed phenotypic variance (R2) explained by different QTLs for grain Fe and Zn content ranged from 2.85 (QGFe.E3.2014–2016_Q3) to 19.66% (QGFe.E1.2014–2016_Q3) and from 2.93 (QGZn.E3.2014–2016_Q3) to 25. 95% (QGZn.E1.2014–2016_Q1), respectively. Two constitutive expressing QTLs for both Fe and Zn co-mapped in this population, one on LG 2 and second one on LG 3. Inside the QTLs candidate genes such as Ferritin gene, Al3+ Transporter, K+ Transporters, Zn2+ transporters and Mg2+ transporters were identified using bioinformatics approaches. The identified QTLs and candidate genes could be useful in pearl millet population improvement programs, seed, restorer parents, and marker-assisted selection programs.