Biparental Recombinant Inbred Line Research Articles

Development and validation of Kompetitive allele‐specific PCR (KASP) markers for bacterial blight resistant locus BB‐13 in Upland cotton (Gossypium hirsutum L.)

AbstractCotton bacterial blight (CBB), caused by the pathogen Xanthomonas citri subsp. malvacearum (Xcm), can inflict significant damage to cotton (Gossypium hirsutum L.) production. Previously, we identified and mapped the broad‐spectrum CBB‐resistant locus BB‐13 on the long arm of chromosome D02 using array‐based single nucleotide polymorphisms (SNPs). In the current study, linked SNPs were converted into easily assayable Kompetitive Allele‐Specific PCR (KASP) markers to enable efficient detection and marker‐assisted selection of alleles at the BB‐13 locus. The KASP marker's efficiency in detecting the BB‐13 resistant gene was validated using an Upland cotton diversity panel of 72 accessions phenotyped with Xcm race 18. The KASP marker NCBB‐KASP4, derived from the CottonSNP63K array‐based marker i25755Gh that is closely associated with BB‐13, predicted the CBB response phenotypes with an error rate of 4.17% in the diversity panel. Additionally, two independent biparental recombinant inbred line populations segregating for resistance to Xcm race 18 were used for KASP marker validation and to test their utility in detecting the presence of the BB‐13 locus in the resistant accession CABD3CABCH‐1‐89. NCBB‐KASP4, validated across breeding populations and broad germplasm, is a reliable KASP marker for detection and testing of BB‐13 locus in cotton. Further, diagnostic array‐based SNP marker i25755Gh's allele pattern and the potential CBB response is described for 875 Gossypium accessions. These SNP‐based phenotypic predictions for 875 accessions along with disease response phenotypes to Xcm race 18 for 253 accessions provide a reference for CBB resistance in diverse cotton germplasm in the United States.

Recombination Hotspots in Soybean [Glycine Max (L.) Merr.

Recombination allows for the exchange of genetic material between two parents which plant breeders exploit to make improved cultivars. This recombination is not distributed evenly across the chromosome. Recombination mostly occurs in euchromatic regions of the genome and even then, recombination is focused into clusters of crossovers termed recombination hotspots. Understanding the distribution of these hotspots along with the sequence motifs associated with them may lead to methods that enable breeders to better exploit recombination in breeding. To map recombination hotspots and identify sequence motifs associated with hotspots in soybean [Glycine max (L.) Merr.], two bi-parental recombinant inbred lines populations were genotyped with the SoySNP50k Illumina Infinium assay. A total of 451 recombination hotspots were identified in the two populations. Despite being half-sib populations, only 18 hotspots were in common between the two populations. While pericentromeric regions did exhibit extreme suppression of recombination, twenty-seven percent of the detected hotspots were located in the pericentromeric regions of the chromosomes. Two genomic motifs associated with hotspots are similar to human, dog, rice, wheat, drosophila, and arabidopsis. These motifs were a CCN repeat motif and a poly-A motif. Genomic regions spanning other hotspots were significantly enriched with the tourist family of mini-inverted-repeat transposable elements that resides in less than 0.34% of the soybean genome. The characterization of recombination hotspots in these two large soybean bi-parental populations demonstrates that hotspots do occur throughout the soybean genome and are enriched for specific motifs but their locations may not be conserved between different populations.

Discovery and Validation of Grain Shape Loci in U.S. Rice Germplasm Through Haplotype Characterization.

Rice grain shape is a major determinant of rice market value and the end-use. We mapped quantitative trait loci (QTL) for grain shape traits in a bi-parental recombinant inbred line population (Trenasse/Jupiter) and discovered two major grain length QTLs—qGL3.1 and qGL7.1. Previously, a major grain shape gene GS3 was reported in the qGL3.1 region and grain length gene GL7 was reported to be encompassing qGL7.1 locus. The re-sequencing SNP data on the International Rice Research Institute (IRRI) 3K Rice Genome Project (RGP) panel were obtained from the IRRI SNP-Seek database for both genes and haplotype diversity was characterized for each gene in this diverse panel. United States rice germplasm was not well represented in the IRRI 3K RGP database. Therefore, a minimum SNP set was identified for each gene that could differentiate all the characterized haplotypes. These haplotypes in the 3K RGP panel were screened across 323 elite U.S. genotypes using the minimum SNP set. The screening of haplotypes and phenotype association confirmed the role of GS3 under qGL3.1. However, screening of the GL7 haplotypes in the U.S. germplasm panel showed that GL7 did not play a role in qGL7.1, and in addition, GL7.1 did not segregate in the Trenasse/Jupiter RIL population. This concluded that qGL7.1 is a novel QTL discovered on chr7 for grain shape in the Trenasse/Jupiter RIL population. A high-throughput KASP-based SNP marker for each locus (GS3 and qGL7.1) was identified and validated in elite U.S. rice germplasm to be used in an applied rice breeding program.

QTL Analysis for Bread Wheat Seed Size, Shape and Color Characteristics Estimated by Digital Image Processing

The size, shape, and color of wheat seeds are important traits that are associated with yield and flour quality (size, shape), nutritional value, and pre-harvest sprouting (coat color). These traits are under multigenic control, and to dissect their molecular and genetic basis, quantitative trait loci (QTL) analysis is used. We evaluated 114 recombinant inbred lines (RILs) in a bi-parental RIL mapping population (the International Triticeae Mapping Initiative, ITMI/MP) grown in 2014 season. We used digital image analysis for seed phenotyping and obtained data for seven traits describing seed size and shape and 48 traits of seed coat color. We identified 212 additive and 34 pairs of epistatic QTLs on all the chromosomes of wheat genome except chromosomes 1A and 5D. Many QTLs were overlapping. We demonstrated that the overlap between QTL regions was low for seed size/shape traits and high for coat color traits. Using the literature and KEGG data, we identified sets of genes in Arabidopsis and rice from the networks controlling seed size and color. Further, we identified 29 and 14 candidate genes for seed size-related loci and for loci associated with seed coat color, respectively.

Identification of QTLs Associated With Agronomic Traits in Tobacco via a Biparental Population and an Eight-Way MAGIC Population.

Agronomic traits such as plant height (PH), leaf number (LN), leaf length (LL), and leaf width (LW), which are closely related to yield and quality, are important in tobacco (Nicotiana tabacum L.). To identify quantitative trait loci (QTLs) associated with agronomic traits in tobacco, 209 recombinant inbred lines (RILs) and 537 multiparent advanced generation intercross (MAGIC) lines were developed. The biparental RIL and MAGIC lines were genotyped using a 430 K single-nucleotide polymorphism (SNP) chip assay, and their agronomic traits were repeatedly evaluated under different conditions. A total of 43 QTLs associated with agronomic traits were identified through a combination of linkage mapping (LM) and association mapping (AM) methods. Among these 43 QTLs, three major QTLs, namely qPH13-3, qPH17-1, and qLW20-1, were repeatedly identified by the use of various genetically diverse populations across different environments. The candidate genes for these major QTLs were subsequently predicted. Validation and utilization of the major QTL qLW20-1 for the improvement of LW in tobacco were investigated. These results could be applied to molecular marker-assisted selection (MAS) for breeding important agronomic traits in tobacco.

The downside of metabolic diversity: Postingestive rearrangements by specialized insects

Deploying toxins in complex mixtures is thought to be advantageous and is observed during antagonistic interactions in nature. Toxin mixtures are widely utilized in medicine and pest control, as they are thought to slow the evolution of detoxification counterresponses in the targeted organisms. Here we show that caterpillars rearrange key constituents of two distinct plant defense pathways to postingestively disable the defensive properties of both pathways. Specifically, phenolic esters of quinic acid, chlorogenic acids (CAs), potent herbivore and ultraviolet (UV) defenses, are reesterified to decorate particular sugars of 17-hydroxygeranyllinalool diterpene glycosides (HGL-DTGs) and prevent their respective anti–herbivore defense functions. This was discovered through the employment of comparative metabolomics of the leaves of Nicotiana attenuata and the frass of this native tobacco’s specialist herbivore, Manduca sexta larvae. Feeding caterpillars on leaves of transgenic plants abrogated in each of the two pathways, separately and together, revealed that one of the fully characterized frass conjugates, caffeoylated HGL-DTG, originated from ingested CA and HGL-DTGs and that both had negative effects on the defensive function of the other compound class, as revealed by rates of larval mass gain. This negative defensive synergy was further explored in 183 N. attenuata natural accessions, which revealed a strong negative covariance between the two defense pathways. Further mapping analyses in a biparental recombinant inbred line (RIL) population imputed quantitative trait loci (QTLs) for the two pathways at distinct genomic locations. The postingestive repurposing of defense metabolism constituents reveals a downside of deploying toxins in mixtures, a downside which plants in nature have evolved to counter.

An Integrated Linkage Map of Three Recombinant Inbred Populations of Pea (Pisum sativum L.).

Biparental recombinant inbred line (RIL) populations are sets of genetically stable lines and have a simple population structure that facilitates the dissection of the genetics of interesting traits. On the other hand, populations derived from multiparent intercrosses combine both greater diversity and higher numbers of recombination events than RILs. Here, we describe a simple population structure: a three-way recombinant inbred population combination. This structure was easy to produce and was a compromise between biparental and multiparent populations. We show that this structure had advantages when analyzing cultivar crosses, and could achieve a mapping resolution of a few genes.

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.

The genetics and physiology of seed dormancy, a crucial trait in common bean domestication

BackgroundPhysical seed dormancy is an important trait in legume domestication. Although seed dormancy is beneficial in wild ecosystems, it is generally considered to be an undesirable trait in crops due to reduction in yield and / or quality. The physiological mechanism and underlying genetic factor(s) of seed dormancy is largely unknown in several legume species. Here we employed an integrative approach to understand the mechanisms controlling physical seed dormancy in common bean (Phaseolus vulgaris L.).ResultsUsing an innovative CT scan imaging system, we were able to track water movements inside the seed coat. We found that water uptake initiates from the bean seed lens. Using a scanning electron microscopy (SEM) we further identified several micro-cracks on the lens surface of non-dormant bean genotypes. Bulked segregant analysis (BSA) was conducted on a bi-parental RIL (recombinant inbred line) population, segregating for seed dormancy. This analysis revealed that the seed water uptake is associated with a single major QTL on Pv03. The QTL region was fine-mapped to a 118 Kb interval possessing 11 genes. Coding sequence analysis of candidate genes revealed a 5-bp insertion in an ortholog of pectin acetylesterase 8 that causes a frame shift, loss-of-function mutation in non-dormant genotype. Gene expression analysis of the candidate genes in the seed coat of contrasting genotypes indicated 21-fold lower expression of pectin acetylesterase 8 in non-dormant genotype. An analysis of mutational polymorphism was conducted among wild and domesticated beans. Although all the wild beans possessed the functional allele of pectin acetylesterase 8, the majority (77%) of domesticated beans had the non-functional allele suggesting that this variant was under strong selection pressure through domestication.ConclusionsIn this study, we identified the physiological mechanism of physical seed dormancy and have identified a candidate allele causing variation in this trait. Our findings suggest that a 5-bp insertion in an ortholog of pectin acetylesterase 8 is likely a major causative mutation underlying the loss of seed dormancy during domestication. Although the results of current study provide strong evidences for the role of pectin acetylesterase 8 in seed dormancy, further confirmations seem necessary by employing transgenic approaches.

Multi-Trait Regressor Stacking Increased Genomic Prediction Accuracy of Sorghum Grain Composition

Genomic prediction has enabled plant breeders to estimate breeding values of unobserved genotypes and environments. The use of genomic prediction will be extremely valuable for compositional traits for which phenotyping is labor-intensive and destructive for most accurate results. We studied the potential of Bayesian multi-output regressor stacking (BMORS) model in improving prediction performance over single trait single environment (STSE) models using a grain sorghum diversity panel (GSDP) and a biparental recombinant inbred lines (RILs) population. A total of five highly correlated grain composition traits—amylose, fat, gross energy, protein and starch, with genomic heritability ranging from 0.24 to 0.59 in the GSDP and 0.69 to 0.83 in the RILs were studied. Average prediction accuracies from the STSE model were within a range of 0.4 to 0.6 for all traits across both populations except amylose (0.25) in the GSDP. Prediction accuracy for BMORS increased by 41% and 32% on average over STSE in the GSDP and RILs, respectively. Prediction of whole environments by training with remaining environments in BMORS resulted in moderate to high prediction accuracy. Our results show regression stacking methods such as BMORS have potential to accurately predict unobserved individuals and environments, and implementation of such models can accelerate genetic gain.

Enhancing Upland cotton for drought resilience, productivity, and fiber quality: comparative evaluation and genetic dissection.

To provision the world sustainably, modern society must increase overall crop production, while conserving and preserving natural resources. Producing more with diminishing water resources is an especially daunting endeavor. Toward the goal of genetically improving drought resilience of cultivated Upland cotton (Gossypium hirsutum L.), this study addresses the genetics of differential yield components referred to as productivity and fiber quality traits under regular-water versus low-water (LW) field conditions. We used ten traits to assess water stress deficit, which included six productivity and four fiber quality traits on two recombinant inbred line (RIL) populations from reciprocally crossed cultivars, Phytogen 72 and Stoneville 474. To facilitate genetic inferences, we genotyped RILs with the CottonSNP63K array, assembled high-density linkage maps of over 7000 SNPs and then analyzed quantitative trait variations. Analysis of variance revealed significant differences for all traits (p < 0.05) in these RIL populations. Although the LW irrigation regime significantly reduced all traits, except lint percent, the RILs exhibited a broad phenotypic spectrum of heritable differences across the water regimes. Transgressive segregation occurred among the RILs, suggesting the possibility of genetic gain through phenotypic selection for drought resilience and perhaps through marker-based selection. Analyses revealed more than 150 quantitative trait loci (QTLs) associated with productivity and fiber quality traits (p < 0.005) on different genomic regions of the cotton genome. The multiple-QTL models analysis with LOD > 3.0 detected 21 QTLs associated with productivity and 22 QTLs associated with fiber quality. For fiber traits, strong clustering and QTL associations occurred in c08 and its homolog c24 as well as c10, c14, and c21. Using contemporary genome sequence assemblies and bioinformatically related information, the identification of genomic regions associated with responses to plant stress/drought elevates the possibility of using marker-assisted and omics-based selection to enhance breeding for drought resilient cultivars and identifying candidate genes and networks. RILs with different responses to drought indicated that it is possible to maintain high fiber quality under LW conditions or reduce the of LW impact on quality. The heritable variation among elite bi-parental RILs for productivity and quality under field drought conditions, and their association of QTLs, and thus specific genomic regions, indicate opportunities for breeding-based gains in water resource conservation, i.e., enhancing cotton's agricultural sustainability.

Genetic variability, genotype × environment interaction and correlation analysis for grain iron and zinc contents in recombinant inbred line population of pearl millet [Pennisetum glaucum (L). R.

Micronutrient malnutrition is one of the major health problem, especially iron (Fe) and zinc (Zn) deficiencies that are widespread coupled with inadequate food supply in the developing world. Pearl millet grains are a good source of Fe and Zn elements making it a potential staple crop for overcoming hidden-hunger and micronutrient deficiencies. Breeding pearl millet with high levels of grain Zn and Fe contents represents a major opportunity to enhance the intake of these minerals for poor and malnourished people. A precise understanding of the genetic variability, correlation of mineral nutrients, genotype × environment (G × E) interaction is important for developing improved lines with high Fe and Zn content. To get fair estimates, we used a bi-parental recombinant inbred lines (RIL) mapping population representing F2 phenotypic variance. A total of 317 RILs were evaluated for grain iron and zinc content in two seasons, Summer 2016 (E1) and Summer 2017 (E2). The result from the analysis of variance exhibited a large variability for grain Fe and Zn content across the two environments. The G × E for high grain Fe were significant at P 0.01. The mean performance across the two environments data for grain Fe ranged from 22.9 to 154.5 mg kg-1 (ppm) and Zn content ranged from 19.3 to 121 mg kg-1. The correlation coefficient for grain Fe and Zn was 0.9, and 0.8 and across the two (E1 and E2) environments. The value of correlation coefficient (0.9) was found to be highly significant at P 0.01 level, that indicated good opportunities for simultaneous genetic improvement of both iron and zinc contents in pearl millet.

Earliness per se variation in Argentine bread wheat varieties and mapping of QTLs in a recombinant inbred line population

The occurrence of flowering time in wheat is affected not only by the vernalization and photoperiod response, but also by earliness per se (EPS). The effects of this trait facilitate the fine tunning of the life cycle for regional adaptation within mega environments. To contribute to the knowledge of the wheat germplasm grown in Argentina and to the understanding of the genetic basis underlying variation in EPS, this study aimed to characterize EPS in a set of modern local bread wheat varieties and to develop a biparental recombinant inbred line (RIL) population based on parental contrasting for EPS. The variation observed in flowering time, which was measured under satisfied vernalization and photoperiod demands and assignment of chromosomic regions by QTL analysis, constitutes the first genetic dissection of EPS control in Argentine wheat adapted materials, providing valuable information for regional adaptation in breeding programs. Based on EPS variation analysis, Baguette Premium 11 (late-heading variety) and BioINTA 2001 (early-heading variety) were selected to develop the mapping population. Six QTLs for EPS were detected in the biparental RIL population and QTL QEps.imj-5D1, in chromosome 5D, showed the greatest effect on EPS and is the first QTL to be reported in this chromosome.

Genotyping-by-sequencing based genetic mapping reveals large number of epistatic interactions for stem rot resistance in groundnut.

Genetic mapping identified large number of epistatic interactions indicating the complex genetic architecture for stem rot disease resistance. Groundnut (Arachis hypogaea) is an important global crop commodity and serves as a major source of cooking oil, diverse confectionery preparations and livestock feed. Stem rot disease caused by Sclerotium rolfsii is the most devastating disease of groundnut and can cause up to 100% yield loss. Genomic-assisted breeding (GAB) has potential for accelerated development of stem rot resistance varieties in short period with more precision. In this context, linkage analysis and quantitative trait locus (QTL) mapping for resistance to stem rot disease was performed in a bi-parental recombinant inbred line population developed from TG37A (susceptible) × NRCG-CS85 (resistant) comprising of 270 individuals. Genotyping-by-sequencing approach was deployed to generate single nucleotide polymorphism (SNP) genotyping data leading to development of a genetic map with 585 SNP loci spanning map distance of 2430cM. QTL analysis using multi-season phenotyping and genotyping data could not detect any major main-effect QTL but identified 44 major epistatic QTLs with phenotypic variation explained ranging from 14.32 to 67.95%. Large number interactions indicate the complexity of genetic architecture of resistance to stem rot disease. A QTL of physical map length 5.2Mb identified on B04 comprising 170 different genes especially leucine reach repeats, zinc finger motifs and ethyleneresponsive factors, etc., was identified. The identified genomic regions and candidate genes will further validate and facilitate marker development to deploy GAB for developing stem rot disease resistance groundnut varieties.

Genetic Mapping of Foliar and Tassel Heat Stress Tolerance in Maize

The frequency of heat stress events is expected to increase, further complicating the challenge of feeding a growing population. A better understanding of the genetic and molecular mechanisms of heat stress tolerance in maize (Zea mays L.) would facilitate the development of heat‐tolerant cultivars. To address this knowledge gap, we evaluated two biparental recombinant inbred line (RIL) populations (B73 × NC350 and B73 × CML103) for leaf and tassel heat tolerance traits. Two foliar traits, leaf firing and leaf blotching, were evaluated at three vegetative growth stages. In B73 × NC350, two tassel traits, tassel blasting and reduction in spikelet size, were scored at flowering. We detected 22 quantitative trait loci (QTL), 15 in B73 × NC350 and seven in B73 × CML103. We previously observed that the development of leaf firing was differentiable between parents, and indeed, the different manifestations of the leaf firing trait were not significantly correlated and QTL did not co‐localize. Leaf firing and leaf blotching traits were correlated at some vegetative growth stages, and most QTL did not co‐localize. Quantitative trait loci number and position for traits measured at multiple vegetative stages were generally consistent. There was a single QTL for tassel blasting on chromosome 5. Heat‐induced plant death segregated in B73 × CML103 and a major QTL was detected on chromosome 3, explaining 26.2% of phenotypic variance. Our study indicates that complex genetic mechanisms underlie the heat stress response in maize.

Haplotype-based allele mining in the Japan-MAGIC rice population

Multi-parent advanced generation inter-cross (MAGIC) lines have broader genetic variation than bi-parental recombinant inbred lines. Genome-wide association study (GWAS) using high number of DNA polymorphisms such as single-nucleotide polymorphisms (SNPs) is a popular tool for allele mining in MAGIC populations, in which the associations of phenotypes with SNPs are investigated; however, the effects of haplotypes from multiple founders on phenotypes are not considered. Here, we describe an improved method of allele mining using the newly developed Japan-MAGIC (JAM) population, which is derived from eight high-yielding rice cultivars in Japan. To obtain information on the haplotypes in the JAM lines, we predicted the haplotype blocks in the whole chromosomes using 16,345 SNPs identified via genotyping-by-sequencing analysis. Using haplotype-based GWAS, we clearly detected the loci controlling the glutinous endosperm and culm length traits. Information on the alleles of the eight founders, which was based on the effects of mutations revealed by the analysis of next-generation sequencing data, was used to narrow down the candidate genes and reveal the associations between alleles and phenotypes. The haplotype-based allele mining (HAM) proposed in this study is a promising approach to the detection of allelic variation in genes controlling agronomic traits in MAGIC populations.

A novel aphid resistance locus in cowpea identified by combining SSR and SNP markers

AbstractThe utility of combining simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) marker genotyping was determined for genetically mapping a novel aphid (Aphis craccivora) resistance locus in cowpea breeding line SARC 1‐57‐2 and for introgressing the resistance into elite cultivars by marker‐assisted backcrossing (MABC). The locus was tagged with codominant SSR marker CP 171F/172R with a recombination fraction of 5.91% in an F2 population from ‘Apagbaala’ x SARC 1‐57‐2. A SNP‐genotyped biparental recombinant inbred line population was genotyped for CP 171F/172R, which was mapped to position 11.5 cM on linkage group (LG) 10 (physical position 30.514 Mb on chromosome Vu10). Using CP 171F/172R for foreground selection and a KASP‐SNP‐based marker panel for background selection in MABC, the resistance from SARC 1‐57‐2 was introduced into elite susceptible cultivar ‘Zaayura’. Five BC4F3 lines of improved ‘Zaayura’ that were isogenic except for the resistance locus region had phenotypes similar to SARC 1‐57‐2. This study identified a novel aphid resistance locus and demonstrated the effectiveness of integrating SSR and SNP markers for trait mapping and marker‐assisted breeding.

Effect of qGN4.1 QTL for Grain Number per Panicle in Genetic Backgrounds of Twelve Different Mega Varieties of Rice

BackgroundRice is a major source of food, particularly for the growing Asian population; hence, the utilization of genes for enhancing its yield potential is important for ensuring food security. Earlier, we have mapped a major quantitative trait loci (QTL) for the grain number per panicle, qGN4.1, using biparental recombinant inbred line (RIL) populations involving a new plant type Indica rice genotype Pusa 1266. Later, three independent studies have confirmed the presence of a major QTL for spikelet number by three different names (SPIKE, GPS and LSCHL4) in the same chromosomal region, and have implicated the overexpression of Nal1 gene as the causal factor for high spikelet number. However, the effect of qGN4.1 in different rice genetic backgrounds and expression levels of the underlying candidate genes is not known.ResultsHere, we report the effect of qGN4.1 QTL in the genetic backgrounds of 12 different high-yielding mega varieties of rice, introgressed by marker assisted-backcross breeding (MABB) using two QTL positive markers for foreground selection and two QTL negative flanking markers for recombinant selection together with phenotypic selection for the recovery of recipient parent genetic background. Analysis of the performance of BC2F3 plants showed a significant increase in the average number of well-filled grains per panicle in all the backgrounds, ranging from 21.6 in CSR 30-GN4.1 to 147.6 in Samba Mahsuri-GN4.1. Furthermore, qGN4.1 caused a significant increase in flag leaf width and panicle branching in most backgrounds. We identified BC3F3qGN4.1 near-isogenic lines (NILs) with 92.0–98.0% similarity to the respective recipient parent by background analysis using a 50 K rice SNP genotyping chip. Three of the NILs, namely Pusa Basmati 1121-GN4.1, Samba Mahsuri-GN4.1 and Swarna-GN4.1, showed a significant yield superiority to their recipient parents. Analysis of differential gene expression revealed that high grain number in these QTL-NILs was unlikely due to the overexpression of Nal1 gene (LOC_Os04g52479). Instead, another tightly linked gene (LOC_Os04g52590) coding for a protein kinase domain-containing protein was consistently overexpressed in the high grain number NILs.ConclusionWe have successfully introgressed the qGN4.1 QTL for high grain number per panicle into 12 different mega varieties of rice using marker-assisted backcross breeding. The advanced near-isogenic lines are promising for the development of even higher yielding versions of these high-yielding mega varieties of rice.

Quantitative Trait Loci Mapping of Agronomic and Yield Traits in Two Grain Sorghum Biparental Families

The animal industry is a major sector of agriculture in the southeastern United States, but a large deficit exists in regional feed grains needed to support the industry. An increase in production of sorghum [Sorghum bicolor (L.) Moench], a water‐ and nutrient‐use‐efficient cereal, on marginal lands could lead to an alternative crop option for growers and reduce the current grain deficit. Quantitative trait locus (QTL) mapping of grain yield components in two sorghum biparental recombinant inbred line (RIL) populations was performed to better understand the genetic basis of grain yield and characterize these traits in a marginal environment. A more robust knowledge of the genetics underlying these complex traits could provide insights into molecular breeding strategies that aim to increase genetic gain. Specific yield traits investigated were grain number per primary panicle (GNP), 1000‐grain weight (TGW), and grain yield per primary panicle (YPP). Two‐year phenotyping in the South Carolina coastal plain revealed greater than threefold variation for both GNP and YPP, whereas TGW variation was just above twofold in both RIL families. There were 16 total yield trait QTL identified across both populations. Of the 16, eight QTL colocated with previously published QTL for yield‐related traits, including a QTL on chromosome 1 that was significant for all three grain yield components. A novel QTL for TGW was identified on chromosome 5 that explained &gt;21% of the phenotypic variance observed in one RIL population. This QTL and the seven additional novel QTL identified in this study provide new targets for grain yield improvement in sorghum.

QTL detection for flowering time in faba bean and the responses to ambient temperature and photoperiod

Faba bean (Vicia faba L.) is a grain legume primarily used for animal feed and human food grown in a range of environments, globally. Time of flowering in faba bean is critical for adaptation to specific environments and is controlled largely by factors such as ambient temperature and photoperiod. The aim of this study was to investigate the genetic control of flowering time and the responses of flowering time to ambient temperature and photoperiod in faba bean. A bi-parental recombinant inbred line population (Icarus × Ascot) was evaluated over three years in field trials and three different controlled environments with varying temperatures and photoperiods. QTL analysis identified eight regions of co-localised QTLs associated with days to flowering, thermal time to flowering and node of first flower; on Chr-I.A/III/V, Chr-I.B.3, Chr-III.1, Chr-III.2, Chr-V.1 and Chr-V.2. Two of the detected regions are common with previously detected QTLs, up to two more are possibly common and the remaining four appear to be novel. For the first time, the associations of these QTLs with ambient temperature and photoperiod response were described. Candidate genes for some of the QTLs were identified using the associations with ambient temperature and photoperiod response together with knowledge extended from other legumes that have a syntenic relationship with faba bean.