Development of core collections in soybean on the basis of seed size

Core collections display a large fraction of the diversity contained in large collections in smaller germplasm panels. We used historical data (1973–2015) collected at the World Vegetable Center, Taiwan, for developing soybean (Glycine max L. Merr.) core collections representing the diversity of the whole collection of 7853 accessions held by the Center. The collection was split into two groups on the basis of the 100 seed weight: large seeded (>25 g or equal to 25 g) and small seeded (<25 g). The large-seeded group (vegetable soybean/edamame) comprised 456 accessions, while the small-seeded group contained 7397 accessions. Within these two groups, we developed core collections based on seven quantitative and 14 qualitative traits collected during the autumn season, resulting in a core collection of 112 large-seeded vegetable soybean accessions and 1480 accessions for the small-seeded types

Unravelling the secret of seedbased gels in water: the nanoscale 3D network formation

Chia (Salvia hispanica) and basil (Ocimum basilicum) seeds have the intrinsic ability to form a hydrogel concomitant with moisture-retention, slow releasing capability and proposed health benefits such as curbing diabetes and obesity by delaying digestion process. However, the underlying mode of gelation at nanoscopic level is not clearly explained or explored. The present study elucidates and corroborates the hypothesis that the gelling behavior of such seeds is due to their nanoscale 3D-network formation. The preliminary study revealed the influence of several conditions like polarity, pH and hydrophilicity/ hydrophobicity on fiber extrusion from the seeds which leads to gelation. Optical microscopic analysis clearly demonstrated bundles of fibers emanating from the seed coat while in contact with water, and live growth of fibers to form 3D network. Scanning electron microscope (SEM) and transmission electron microscope (TEM) studies confirmed 3D network formation with fiber diameters ranging from 20 to 50 nm

Regulation of Stat5 by FAK and PAK1 in Oncogenic FLT3 and KIT driven Leukemogenesis

Oncogenic mutations of FLT3 and KIT receptors are associated with poor survival in patients with acute myeloid leukemia (AML) and myeloproliferative neoplasms (MPN) and currently available drugs are largely ineffective. Although Stat5 has been implicated in regulating several myeloid and lymphoid malignancies, how precisely Stat5 regulates leukemogenesis, including its nuclear translocation to induce gene transcription is poorly understood. In leukemic cells, we show constitutive activation of focal adhesion kinase (FAK), whose inhibition represses leukemogenesis. Downstream of FAK, activation of Rac1 is regulated by RacGEF Tiam1, whose inhibition prolongs the survival of leukemic mice. Inhibition of the Rac1 effector PAK1 prolongs the survival of leukemic mice in part by inhibiting the nuclear translocation of Stat5. These results reveal a leukemic pathway involving FAK/Tiam1/Rac1/PAK1 and demonstrate an essential role for these signaling molecules in regulating the nuclear translocation of Stat5 in leukemogenesis

Genetic approaches for assessment of phosphorus use efficiency in groundnut (Arachis hypogaea L.)

Production of phosphorus efficient genotypes can reduce environmental pollution. Identification of P-efficient groundnut genotypes is a need of the hour to sustain in P-deficient soils. The pot experiment showed significant differences between genotypes (G) and treatments (T) for all the traits and G × T interaction for majority of traits. The G × T × Y interaction effects were also significant for all the traits except leaf P% (LP%), leaf acid phosphatase (LAP) and root dry weight (RDW). In lysimeter experiment, the effect of G, T and G × T were significant for leaf dry weight (LDW), stem dry weight (SDW), total transpiration (TT) and transpiration efficiency (TE). For traits, LDW, SDW, TT, TE, ICGV 00351 and ICGS 76; for SDW, TT, ICGV 02266 are best performers under both P-sufficient and deficient conditions. Based on P-efficiency indices and surrogate traits of P-uptake, ICGV’s 02266, 05155, 00308, 06040 and 06146 were considered as efficient P-responding genotypes. From GGE biplot, ICGV 06146 under P-deficient and TAG 24 under both P-sufficient and deficient conditions are portrayed as best performer. ICGV 06146 was identified as stable pod yielder and a promising genotype for P-deficient soils. The genotypes identified in this study can be used as a parent in developing mapping population to decipher the genetics and to devleop groundnut breeding lines suitable to P-deficient soils

Genome-Wide SNP Discovery and Mapping QTLs for Seed Iron and Zinc Concentrations in Chickpea (Cicer arietinum L.)

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 F2 : 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 F2 : 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

Class IA PI3Kinase Regulatory Subunit, p85α, Mediates Mast Cell Development through Regulation of Growth and Survival Related Genes

Stem cell factor (SCF) mediated KIT receptor activation plays a pivotal role in mast cell growth, maturation and survival. However, the signaling events downstream from KIT are poorly understood. Mast cells express multiple regulatory subunits of class 1A PI3Kinase (PI3K) including p85α, p85β, p50α, and p55α. While it is known that PI3K plays an essential role in mast cells; the precise mechanism by which these regulatory subunits impact specific mast cell functions including growth, survival and cycling are not known. We show that loss of p85α impairs the growth, survival and cycling of mast cell progenitors (MCp). To delineate the molecular mechanism (s) by which p85α regulates mast cell growth, survival and cycling, we performed microarray analyses to compare the gene expression profile of MCps derived from WT and p85α-deficient mice in response to SCF stimulation. We identified 151 unique genes exhibiting altered expression in p85α-deficient cells in response to SCF stimulation compared to WT cells. Functional categorization based on DAVID bioinformatics tool and Ingenuity Pathway Analysis (IPA) software relates the altered genes due to lack of p85α to transcription, cell cycle, cell survival, cell adhesion, cell differentiation, and signal transduction. Our results suggest that p85α is involved in mast cell development through regulation of expression of growth, survival and cell cycle related genes

Author Correction: Towards an arthritis flare-responsive drug delivery system

In the original version of this Article, financial support was not fully acknowledged. The PDF and HTML versions of the Article have now been corrected to include support from the National Football League Players Association

Plexin-B2 Negatively Regulates Macrophage Motility, Rac, and Cdc42 Activation

Plexins are cell surface receptors widely studied in the nervous system, where they mediate migration and morphogenesis though the Rho family of small GTPases. More recently, plexins have been implicated in immune processes including cell-cell interaction, immune activation, migration, and cytokine production. Plexin-B2 facilitates ligand induced cell guidance and migration in the nervous system, and induces cytoskeletal changes in overexpression assays through RhoGTPase. The function of Plexin-B2 in the immune system is unknown. This report shows that Plexin-B2 is highly expressed on cells of the innate immune system in the mouse, including macrophages, conventional dendritic cells, and plasmacytoid dendritic cells. However, Plexin-B2 does not appear to regulate the production of proinflammatory cytokines, phagocytosis of a variety of targets, or directional migration towards chemoattractants or extracellular matrix in mouse macrophages. Instead, Plxnb2−/− macrophages have greater cellular motility than wild type in the unstimulated state that is accompanied by more active, GTP-bound Rac and Cdc42. Additionally, Plxnb2−/− macrophages demonstrate faster in vitro wound closure activity. Studies have shown that a closely related family member, Plexin-B1, binds to active Rac and sequesters it from downstream signaling. The interaction of Plexin-B2 with Rac has only been previously confirmed in yeast and bacterial overexpression assays. The data presented here show that Plexin-B2 functions in mouse macrophages as a negative regulator of the GTPases Rac and Cdc42 and as a negative regulator of basal cell motility and wound healing