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651 results for “Legume”
Symbiotic Transcriptome profiling of candidate genes in model legume Arachis hypogaea using Next Generation Sequencing Technology (NGS)
GEO Series GSE98997. Arachis hypogaea. 18 samples. Type: Expression profiling by high throughput sequencing.
DNA barcode trnH-psbA is a promising candidate for efficient identification of forage legumes and grasses
<p><strong>Objective</strong></p> <p>Grasslands are widespread ecosystems that fulfil many functions. Plant species richness (PSR) is known to have beneficial effects on such functions and monitoring PSR is crucial for tracking the effects of land use and agricultural management on these ecosystems. Unfortunately, traditional morphology-based methods are labor-intensive and cannot be adapted for high-throughput assessments.</p> <p>DNA barcoding could aid increasing the throughput of PSR assessments in grasslands. In this proof-of-concept work, we aimed at determining which of three plant DNA barcodes (<em>rbcLa</em>, <em>matK</em> and <em>trnH-psbA</em>) best discriminates 16 key grass and legume species common in temperate sub-alpine grasslands.</p> <p><strong>Results</strong></p> <p>Barcode <em>trnH-psbA</em> had a 100% correct assignment rate (CAR) in the five analyzed legumes, followed by <em>rbcLa </em>(93.3%) and <em>matK</em> (55.6%). Barcode <em>trnH-psbA</em> had a 100% CAR in the grasses <em>Cynosurus cristatus</em>, <em>Dactylis glomerata</em> and <em>Trisetum flavescens</em>. However, the closely related <em>Festuca, Lolium </em>and <em>Poa</em> species were not always correctly identified, which led to an overall CAR in grasses of 66.7 %, 50.0% and 46.4% for<em> trnH-psbA</em>, <em>matK</em> and <em>rbcLa</em>, respectively. Barcode <em>trnH-psbA</em> is thus the most promising candidate for PSR assessments in permanent grasslands and could greatly support plant biodiversity monitoring on a larger scale.</p> <p><strong>Content of data file</strong></p> <p>This data file contains all raw data obtained during the study. The full information on the project can be found on the BOLD database (<a href="http://www.boldsystems.org/index.php/Public_SearchTerms">http://www.boldsystems.org/index.php/Public_SearchTerms</a>) using the search term SWFRG</p>
Data from: Shared genes but not shared genetic variation: legume colonization by two belowground symbionts
Mutualisms between hosts and multiple symbionts can generate diffuse coevolution if genetic covariance exists between host traits governing multiple interactions. Rhizobia and arbuscular mycorrhizal fungi (AMF) both interact with legume hosts, providing complementary nutrients (nitrogen and phosphorous). Molecular approaches have revealed extensive pleiotropy in the plant genetic pathways required for colonization of both symbionts; however, a quantitative genetic approach is required to understand whether this pleiotropy shapes evolution in natural populations. In a greenhouse experiment with 75 families of Chamaecrista fasciculata grown in two phosphorous environments (fertilized and unfertilized), positive covariance between nodule number and plant aboveground biomass within and across environments indicates selection for increased allocation to rhizobia. Genetic variation for host restriction of AMF colonization in response to P suggests that this aspect of context-dependency can evolve in host populations, and that selection in this mutualism varies with P. Despite the existence of gene-level pleiotropy during rhizobium and AMF infection, we find no evidence for genetic covariance in symbiont colonization or its response to phosphorous - suggesting that genetic variation at other, non-pleiotropic loci govern variation in colonization and thus that these traits likely evolve independently in plant populations.
Data from: Competitive Indices in cereal and legume mixtures in a South Asian environment
The assessment of competitive performance of mixture components is important for maximizing benefits of intercropping systems. This field study tested binary mixtures of two cereals (sorghum and pearl millet) and three forage legumes (cowpea, cluster bean and soybean), along with their sole crops on competitive indices. Sorghum-cowpea binary mixture resulted in a lower green forage yield of sorghum and cowpea by 9% and 36% respectively, but overall biomass production was increased by 30% and 117% compared to their sole crop equivalents. Partial land equivalent ratios (LER) of all component crops were higher than 0.50, indicating better land use efficiency, except of soybean in binary mixtures with cowpea and cluster bean. However, the highest LER was of sorghum-cowpea (1.55), followed by sorghum-soybean (1.48) and pearl millet-soybean (1.48) binary mixtures. Pearl millet dominated sorghum and all legumes, while cowpea remained a superior competitor among legumes as per aggressivity value index. The highest crowding ratio was exhibited by pearl millet in binary mixture with cluster bean indicating its higher competitive ability incomparison to other mixture components. Observed yield loss data indicated that pearl millet was the most resistant crop to yield loss in all binary mixtures, while soybean had the highest yield reduction. In a short term, the highest area-time equivalent ratio for sorghum-cowpea binary mixture indicated the maximum advantage for this binary mixture compared to other binary mixtures.
Scheme 4 from: Bruneau A, Queiroz LP, Ringelberg JJ, Borges LM, Bortoluzzi RLC, Brown GK, Cardoso DBOS, Clark RP, Conceição AS, Cota MMT, Demeulenaere E, Duno de Stefano R, Ebinger JE, Ferm J, Fonseca-Cortés A, Gagnon E, Grether R, Guerra E, Haston E, Herendeen PS, Hernández HM, Hopkins HCF, Huamantupa-Chuquimaco I, Hughes CE, Ickert-Bond SM, Iganci J, Koenen EJM, Lewis GP, Lima HC, Lima AG, Luckow M, Marazzi B, Maslin BR, Morales M, Morim MP, Murphy DJ, O'Donnell SA, Oliveira FG, Oliveira ACS, Rando JG, Ribeiro PG, Ribeiro CL, Santos FS, Seigler DS, Silva GS, Simon MF, Soares MVB, Terra V (2024) Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. PhytoKeys 240: 1-552. https://doi.org/10.3897/phytokeys.240.101716
Scheme 4
Scheme 3 from: Bruneau A, Queiroz LP, Ringelberg JJ, Borges LM, Bortoluzzi RLC, Brown GK, Cardoso DBOS, Clark RP, Conceição AS, Cota MMT, Demeulenaere E, Duno de Stefano R, Ebinger JE, Ferm J, Fonseca-Cortés A, Gagnon E, Grether R, Guerra E, Haston E, Herendeen PS, Hernández HM, Hopkins HCF, Huamantupa-Chuquimaco I, Hughes CE, Ickert-Bond SM, Iganci J, Koenen EJM, Lewis GP, Lima HC, Lima AG, Luckow M, Marazzi B, Maslin BR, Morales M, Morim MP, Murphy DJ, O'Donnell SA, Oliveira FG, Oliveira ACS, Rando JG, Ribeiro PG, Ribeiro CL, Santos FS, Seigler DS, Silva GS, Simon MF, Soares MVB, Terra V (2024) Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. PhytoKeys 240: 1-552. https://doi.org/10.3897/phytokeys.240.101716
Scheme 3
Scheme 2 from: Bruneau A, Queiroz LP, Ringelberg JJ, Borges LM, Bortoluzzi RLC, Brown GK, Cardoso DBOS, Clark RP, Conceição AS, Cota MMT, Demeulenaere E, Duno de Stefano R, Ebinger JE, Ferm J, Fonseca-Cortés A, Gagnon E, Grether R, Guerra E, Haston E, Herendeen PS, Hernández HM, Hopkins HCF, Huamantupa-Chuquimaco I, Hughes CE, Ickert-Bond SM, Iganci J, Koenen EJM, Lewis GP, Lima HC, Lima AG, Luckow M, Marazzi B, Maslin BR, Morales M, Morim MP, Murphy DJ, O'Donnell SA, Oliveira FG, Oliveira ACS, Rando JG, Ribeiro PG, Ribeiro CL, Santos FS, Seigler DS, Silva GS, Simon MF, Soares MVB, Terra V (2024) Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. PhytoKeys 240: 1-552. https://doi.org/10.3897/phytokeys.240.101716
Scheme 2
Scheme 1 from: Bruneau A, Queiroz LP, Ringelberg JJ, Borges LM, Bortoluzzi RLC, Brown GK, Cardoso DBOS, Clark RP, Conceição AS, Cota MMT, Demeulenaere E, Duno de Stefano R, Ebinger JE, Ferm J, Fonseca-Cortés A, Gagnon E, Grether R, Guerra E, Haston E, Herendeen PS, Hernández HM, Hopkins HCF, Huamantupa-Chuquimaco I, Hughes CE, Ickert-Bond SM, Iganci J, Koenen EJM, Lewis GP, Lima HC, Lima AG, Luckow M, Marazzi B, Maslin BR, Morales M, Morim MP, Murphy DJ, O'Donnell SA, Oliveira FG, Oliveira ACS, Rando JG, Ribeiro PG, Ribeiro CL, Santos FS, Seigler DS, Silva GS, Simon MF, Soares MVB, Terra V (2024) Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. PhytoKeys 240: 1-552. https://doi.org/10.3897/phytokeys.240.101716
Scheme 1
Scheme 7 from: Bruneau A, Queiroz LP, Ringelberg JJ, Borges LM, Bortoluzzi RLC, Brown GK, Cardoso DBOS, Clark RP, Conceição AS, Cota MMT, Demeulenaere E, Duno de Stefano R, Ebinger JE, Ferm J, Fonseca-Cortés A, Gagnon E, Grether R, Guerra E, Haston E, Herendeen PS, Hernández HM, Hopkins HCF, Huamantupa-Chuquimaco I, Hughes CE, Ickert-Bond SM, Iganci J, Koenen EJM, Lewis GP, Lima HC, Lima AG, Luckow M, Marazzi B, Maslin BR, Morales M, Morim MP, Murphy DJ, O'Donnell SA, Oliveira FG, Oliveira ACS, Rando JG, Ribeiro PG, Ribeiro CL, Santos FS, Seigler DS, Silva GS, Simon MF, Soares MVB, Terra V (2024) Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. PhytoKeys 240: 1-552. https://doi.org/10.3897/phytokeys.240.101716
Scheme 7
Scheme 6 from: Bruneau A, Queiroz LP, Ringelberg JJ, Borges LM, Bortoluzzi RLC, Brown GK, Cardoso DBOS, Clark RP, Conceição AS, Cota MMT, Demeulenaere E, Duno de Stefano R, Ebinger JE, Ferm J, Fonseca-Cortés A, Gagnon E, Grether R, Guerra E, Haston E, Herendeen PS, Hernández HM, Hopkins HCF, Huamantupa-Chuquimaco I, Hughes CE, Ickert-Bond SM, Iganci J, Koenen EJM, Lewis GP, Lima HC, Lima AG, Luckow M, Marazzi B, Maslin BR, Morales M, Morim MP, Murphy DJ, O'Donnell SA, Oliveira FG, Oliveira ACS, Rando JG, Ribeiro PG, Ribeiro CL, Santos FS, Seigler DS, Silva GS, Simon MF, Soares MVB, Terra V (2024) Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. PhytoKeys 240: 1-552. https://doi.org/10.3897/phytokeys.240.101716
Scheme 6
Scheme 5 from: Bruneau A, Queiroz LP, Ringelberg JJ, Borges LM, Bortoluzzi RLC, Brown GK, Cardoso DBOS, Clark RP, Conceição AS, Cota MMT, Demeulenaere E, Duno de Stefano R, Ebinger JE, Ferm J, Fonseca-Cortés A, Gagnon E, Grether R, Guerra E, Haston E, Herendeen PS, Hernández HM, Hopkins HCF, Huamantupa-Chuquimaco I, Hughes CE, Ickert-Bond SM, Iganci J, Koenen EJM, Lewis GP, Lima HC, Lima AG, Luckow M, Marazzi B, Maslin BR, Morales M, Morim MP, Murphy DJ, O'Donnell SA, Oliveira FG, Oliveira ACS, Rando JG, Ribeiro PG, Ribeiro CL, Santos FS, Seigler DS, Silva GS, Simon MF, Soares MVB, Terra V (2024) Advances in Legume Systematics 14. Classification of Caesalpinioideae. Part 2: Higher-level classification. PhytoKeys 240: 1-552. https://doi.org/10.3897/phytokeys.240.101716
Scheme 5
Figure 1 from: Cannon P, Buddie A, Bridge P, de Neergaard E, Lübeck M, Askar M (2012) Lectera, a new genus of the Plectosphaerellaceae for the legume pathogen Volutella colletotrichoides. MycoKeys 3: 23-36. https://doi.org/10.3897/mycokeys.3.3065
Figure 1 - ML ITS phyogram showing the phylogenetic position of Lectera species.
Figure 3 from: Cannon P, Buddie A, Bridge P, de Neergaard E, Lübeck M, Askar M (2012) Lectera, a new genus of the Plectosphaerellaceae for the legume pathogen Volutella colletotrichoides. MycoKeys 3: 23-36. https://doi.org/10.3897/mycokeys.3.3065
Figure 3 - ML tree of GAPDH sequences, of a subset of the strains used for the ITS sequence set.
Figure 34 from: Prathapan KD (2016) Revision of the legume-feeding leaf beetle genus Madurasia Jacoby, including a new species description (Coleoptera, Chrysomelidae, Galerucinae, Galerucini). In: Jolivet P, Santiago-Blay J, Schmitt M (Eds) Research on Chrysomelidae 6. ZooKeys 597: 57–79. https://doi.org/10.3897/zookeys.597.7520
Figure 34 - Distribution of Madurasia andamanica sp. n. on the Andaman Islands.
Acute Effects of Legume-enriched Meals Compared to Western Diet Meals on Postprandial Metabolism in Participants with Increased Cardiometabolic Risk
ClinicalTrials.gov study NCT06270901. IPD Sharing: NO. Countries: 1. Publications: 0.
Effects of Legume Consumption on Adiponectin and Inflammatory Markers Among Adults
ClinicalTrials.gov study NCT01906086. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impacts of Fermented Pea- and Legume-based Product on Gut Microbiota and Health
ClinicalTrials.gov study NCT06743828. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effects of a Legume-rich Diet in the Context of the Planetary Health Diet Compared to a Western-oriented Dietary Pattern in Participants with Increased Cardiometabolic Risk
ClinicalTrials.gov study NCT06700954. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Optimizing Online Purchasing of Fruits, Vegetables, and Legumes for Low-Income Families
ClinicalTrials.gov study NCT07071753. IPD Sharing: NO. Countries: 0. Publications: 0.
Prevalence of Sensitization to Legumes in a Region From Southern France (Légumineuses)
ClinicalTrials.gov study NCT03686891. IPD Sharing: NO. Countries: 1. Publications: 0.
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