المؤلفون: Phillips, Alyssa R, Seetharam, Arun S, Albert, Patrice S, AuBuchon-Elder, Taylor, Birchler, James A, Buckler, Edward S, Gillespie, Lynn J, Hufford, Matthew B, Llaca, Victor, Romay, Maria Cinta, Soreng, Robert J, Kellogg, Elizabeth A, Ross-Ibarra, Jeffrey

المصدر: G3 (Bethesda, Md.). 13(6)

مصطلحات موضوعية: Poa, Base Sequence, Genome, Plant Weeds, Molecular Sequence Annotation, Plant Breeding, Kentucky bluegrass, Poaceae, aneuploidy, genetic diversity, genome assembly, polyploidy, population structure, turfgrass, Human Genome, Genetics

الوصف: Poa pratensis, commonly known as Kentucky bluegrass, is a popular cool-season grass species used as turf in lawns and recreation areas globally. Despite its substantial economic value, a reference genome had not previously been assembled due to the genome's relatively large size and biological complexity that includes apomixis, polyploidy, and interspecific hybridization. We report here a fortuitous de novo assembly and annotation of a P. pratensis genome. Instead of sequencing the genome of a C4 grass, we accidentally sampled and sequenced tissue from a weedy P. pratensis whose stolon was intertwined with that of the C4 grass. The draft assembly consists of 6.09 Gbp with an N50 scaffold length of 65.1 Mbp, and a total of 118 scaffolds, generated using PacBio long reads and Bionano optical map technology. We annotated 256K gene models and found 58% of the genome to be composed of transposable elements. To demonstrate the applicability of the reference genome, we evaluated population structure and estimated genetic diversity in P. pratensis collected from three North American prairies, two in Manitoba, Canada and one in Colorado, USA. Our results support previous studies that found high genetic diversity and population structure within the species. The reference genome and annotation will be an important resource for turfgrass breeding and study of bluegrasses.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/4g95v5rxTest

المؤلفون: Morales, Nicolas, Anche, Mahlet T, Kaczmar, Nicholas S, Lepak, Nicholas, Ni, Pengzun, Romay, Maria Cinta, Santantonio, Nicholas, Buckler, Edward S, Gore, Michael A, Mueller, Lukas A, Robbins, Kelly R

المساهمون: Sillanpää, M, U.S. Department of Agriculture, Iowa Corn Promotion Board, Cornell University

المصدر: GENETICS ; volume 227, issue 1 ; ISSN 1943-2631

الوصف: Design randomizations and spatial corrections have increased understanding of genotypic, spatial, and residual effects in field experiments, but precisely measuring spatial heterogeneity in the field remains a challenge. To this end, our study evaluated approaches to improve spatial modeling using high-throughput phenotypes (HTP) via unoccupied aerial vehicle (UAV) imagery. The normalized difference vegetation index was measured by a multispectral MicaSense camera and processed using ImageBreed. Contrasting to baseline agronomic trait spatial correction and a baseline multitrait model, a two-stage approach was proposed. Using longitudinal normalized difference vegetation index data, plot level permanent environment effects estimated spatial patterns in the field throughout the growing season. Normalized difference vegetation index permanent environment were separated from additive genetic effects using 2D spline, separable autoregressive models, or random regression models. The Permanent environment were leveraged within agronomic trait genomic best linear unbiased prediction either modeling an empirical covariance for random effects, or by modeling fixed effects as an average of permanent environment across time or split among three growth phases. Modeling approaches were tested using simulation data and Genomes-to-Fields hybrid maize (Zea mays L.) field experiments in 2015, 2017, 2019, and 2020 for grain yield, grain moisture, and ear height. The two-stage approach improved heritability, model fit, and genotypic effect estimation compared to baseline models. Electrical conductance and elevation from a 2019 soil survey significantly improved model fit, while 2D spline permanent environment were most strongly correlated with the soil parameters. Simulation of field effects demonstrated improved specificity for random regression models. In summary, the use of longitudinal normalized difference vegetation index measurements increased experimental accuracy and understanding of field spatio-temporal ...

الإتاحة: https://doi.org/10.1093/genetics/iyae037Test
https://academic.oup.com/genetics/article-pdf/227/1/iyae037/57433105/iyae037.pdfTest

المؤلفون: Samayoa, Luis Fernando, Olukolu, Bode A, Yang, Chin Jian, Chen, Qiuyue, Stetter, Markus G, York, Alessandra M, de Jesus Sanchez-Gonzalez, Jose, Glaubitz, Jeffrey C, Bradbury, Peter J, Romay, Maria Cinta, Sun, Qi, Yang, Jinliang, Ross-Ibarra, Jeffrey, Buckler, Edward S, Doebley, John F, Holland, James B

المصدر: PLOS Genetics. 17(12)

مصطلحات موضوعية: Biological Sciences, Ecology, Evolutionary Biology, Genetics, Mental Health, Depression, Domestication, Genes, Plant, Genetic Variation, Inbreeding Depression, Phenotype, Plant Breeding, Plant Proteins, Quantitative Trait Loci, Selection, Genetic, Zea mays, Developmental Biology

الوصف: Inbreeding depression is the reduction in fitness and vigor resulting from mating of close relatives observed in many plant and animal species. The extent to which the genetic load of mutations contributing to inbreeding depression is due to large-effect mutations versus variants with very small individual effects is unknown and may be affected by population history. We compared the effects of outcrossing and self-fertilization on 18 traits in a landrace population of maize, which underwent a population bottleneck during domestication, and a neighboring population of its wild relative teosinte. Inbreeding depression was greater in maize than teosinte for 15 of 18 traits, congruent with the greater segregating genetic load in the maize population that we predicted from sequence data. Parental breeding values were highly consistent between outcross and selfed offspring, indicating that additive effects determine most of the genetic value even in the presence of strong inbreeding depression. We developed a novel linkage scan to identify quantitative trait loci (QTL) representing large-effect rare variants carried by only a single parent, which were more important in teosinte than maize. Teosinte also carried more putative juvenile-acting lethal variants identified by segregation distortion. These results suggest a mixture of mostly polygenic, small-effect partially recessive effects in linkage disequilibrium underlying inbreeding depression, with an additional contribution from rare larger-effect variants that was more important in teosinte but depleted in maize following the domestication bottleneck. Purging associated with the maize domestication bottleneck may have selected against some large effect variants, but polygenic load is harder to purge and overall segregating mutational burden increased in maize compared to teosinte.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/4xf7m376Test

المؤلفون: Chen, Qiuyue, Samayoa, Luis Fernando, Yang, Chin Jian, Bradbury, Peter J, Olukolu, Bode A, Neumeyer, Michael A, Romay, Maria Cinta, Sun, Qi, Lorant, Anne, Buckler, Edward S, Ross-Ibarra, Jeffrey, Holland, James B, Doebley, John F

المصدر: PLoS genetics. 16(5)

مصطلحات موضوعية: Zea mays, Genetics, Population, Gene Frequency, Quantitative Trait, Heritable, Genes, Plant, Quantitative Trait Loci, Gene Flow, Genetic Variation, Selection, Genetic, Domestication, Genetics, Developmental Biology

الوصف: The genetics of domestication has been extensively studied ever since the rediscovery of Mendel's law of inheritance and much has been learned about the genetic control of trait differences between crops and their ancestors. Here, we ask how domestication has altered genetic architecture by comparing the genetic architecture of 18 domestication traits in maize and its ancestor teosinte using matched populations. We observed a strongly reduced number of QTL for domestication traits in maize relative to teosinte, which is consistent with the previously reported depletion of additive variance by selection during domestication. We also observed more dominance in maize than teosinte, likely a consequence of selective removal of additive variants. We observed that large effect QTL have low minor allele frequency (MAF) in both maize and teosinte. Regions of the genome that are strongly differentiated between teosinte and maize (high FST) explain less quantitative variation in maize than teosinte, suggesting that, in these regions, allelic variants were brought to (or near) fixation during domestication. We also observed that genomic regions of high recombination explain a disproportionately large proportion of heritable variance both before and after domestication. Finally, we observed that about 75% of the additive variance in both teosinte and maize is "missing" in the sense that it cannot be ascribed to detectable QTL and only 25% of variance maps to specific QTL. This latter result suggests that morphological evolution during domestication is largely attributable to very large numbers of QTL of very small effect.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/8z87m5kpTest

المؤلفون: Chen, Qiuyue, Samayoa, Luis Fernando, Yang, Chin Jian, Olukolu, Bode A., York, Alessandra M., de Jesus Sanchez-Gonzalez, Jose, Xue, Wei, Glaubitz, Jeffrey C., Bradbury, Peter J., Romay, Maria Cinta, Sun, Qi, Buckler, Edward S., Holland, James B., Doebley, John F.

المصدر: Proceedings of the National Academy of Sciences of the United States of America, 2021 Oct . 118(43), 1-10.

الوصول الحر: https://www.jstor.org/stable/27093537Test

المؤلفون: Yi, Qiang, López-Malvar, Ana, Álvarez-Iglesias, Lorena, Romay, María Cinta, Revilla, Pedro

الوصف: Supplementary Table S1 Candidate genes associated with photosynthesis-related traits in a large maize association panel across three environments Supplementary Fig. S1 Manhattan plot and Quantile-quantile plot from a mixed linear model for photosynthesis-related traits in a large maize association population via single environment analysis. SNPs with p values ≥ the threshold of 1 × 10-4 were considered significantly associated with the trait. The different colors in the Manhattan plot represent the 10 different chromosomes of maize. Supplementary Fig. S2 Comparison of Leaf net photosynthesis (AN) among groups with the different number of favorable alleles carried in a large maize panel. The x-axis indicates groups 1, 2, 3, 4, and 5 with inbreds carrying 1, 2, 3, 4, and 5 favorable alleles in a large maize panel, respectively. The different upper letters above the mean lines denote significant differences at the probability of p = 0.05. The number of inbreds contained in the groups is presented below the mean lines. A total of 18 inbred lines, including EP32, GE129, NC250, Pa392, Oh43E, J47, Mo46, MS24, MS78, MS1, CH9, P39M96, A681, H29w, AusTRCF306303, AusTRCF305819, A665, and ND301, carried five favorable alleles for increasing Pn.

العلاقة: https://zenodo.org/record/7544747Test; https://doi.org/10.5281/zenodo.7544747Test; oai:zenodo.org:7544747

الإتاحة: https://doi.org/10.5281/zenodo.7544747Test
https://doi.org/10.5281/zenodo.7544746Test
https://zenodo.org/record/7544747Test

المؤلفون: Yi, Qiang, López Malvar, Ana, Álvarez Iglesias, Lorena, Romay, María Cinta, Revilla, Pedro

مصطلحات موضوعية: 3103 Agronomía

الوصف: High-yielding cultivars with high water use efficiency are a main target in maize breeding; yet, no comprehensive study about the genetic regulation of photosynthesis, or about the ranges of variability for gas exchange-related parameters in maize has been published. Here, a large maize panel of 731 inbred lines previously genotyped was evaluated to elucidate the genetic basis of photosynthesis-related parameters, measured 15–30 days after silking, across three years. Large phenotypic and genotypic variations were observed in this panel with dramatic fluctuations in heritability for various traits. We detected 27 minor Quantitative Trait Loci (QTL), comprising 39 significant trait-Single Nucleotide Polymorphisms (SNPs), located mostly on chromosomes 5 and 8. Most candidates genes were novel, though a few of them were functionally associated with the theory of source-to-sink translocation presented in previous studies. Genomic selection of favorable alleles to enhance photosynthesis, along with other tools, could be a practical, and a promising, approach in the future. Leaf net photosynthesis and stomatal conductance are the most promising targets for breeding programs. We did not find any marker associated with intrinsic water use efficiency, which highlights that developing maize cultivars with more efficient use of water by genomic selection is not straightforward; however, given the high heritability value for this trait, phenotypic selection could be implemented. ; Agencia Estatal de Investigación | Ref. PID2019-108127RB-I00 ; Agencia Estatal de Investigación | Ref. PCI2021-121912

العلاقة: info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-108127RB-I00/ES/MEJORA GENETICA DE MAIZ PARA RESILIENCIA, SOSTENIBILIDAD Y CALIDAD; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PCI2021-121912/ES/CAPITALIZATION OF MEDITERRANEAN MAIZE GERMPLASM FOR IMPROVING STRESS TOLERANCE; Agronomy, 13(3): 801 (2023); http://hdl.handle.net/11093/5138Test; https://www.mdpi.com/2073-4395/13/3/801Test

الإتاحة: https://doi.org/10.3390/agronomy13030801Test
http://hdl.handle.net/11093/5138Test
https://www.mdpi.com/2073-4395/13/3/801Test

المؤلفون: Lima, Dayane, Cristina, Aviles, Alejandro, Castro, Alpers, Ryan, Timothy, Mcfarland, Bridget, A, Kaeppler, Shawn, Ertl, David, Romay, Maria, Cinta, Gage, Joseph, L, Holland, James, Beissinger, Timothy, Bohn, Martin, Buckler, Edward, Edwards, Jode, Flint-Garcia, Sherry, Hirsch, Candice, N, Hood, Elizabeth, Hooker, David, C, Knoll, Joseph, E, Kolkman, Judith, M, Liu, Sanzhen, Mckay, John, Minyo, Richard, Moreta, Danilo, E, Murray, Seth, C, Nelson, Rebecca, Schnable, James, C, Sekhon, Rajandeep, S, Singh, Maninder, P, Thomison, Peter, Thompson, Addie, Tuinstra, Mitchell, Wallace, Jason, Washburn, Jacob, D, Weldekidan, Teclemariam, Wisser, Randall, J, Xu, Wenwei, de Leon, Natalia

المساهمون: University of Wisconsin-Madison, BASF Vegetable Seeds, BASF SE, Panama‑USA Commission for the Eradication and Prevention of Screwworm (COPEG), Iowa Corn Promotion Board (ICPB), Cornell University New York, North Carolina State University Raleigh (NC State), University of North Carolina System (UNC), USDA-ARS : Agricultural Research Service, Georg-August-University = Georg-August-Universität Göttingen, University of Illinois at Urbana-Champaign Urbana (UIUC), University of Illinois System, University of Minnesota Twin Cities (UMN), University of Minnesota System (UMN), Arkansas State University (A-State), University of Guelph, ARS Crop Genetics and Breeding Research Unit, United States Department of Agriculture (USDA), College of Agriculture and Life Sciences Cornell University (CALS), School of Integrative Plant Science CALS, Cornell University New York -Cornell University New York, Kansas State University, Colorado State University Fort Collins (CSU), Ohio State University Columbus (OSU), Texas A&M University–Commerce, University of Nebraska–Lincoln, University of Nebraska System, Clemson University, Michigan State University East Lansing, Michigan State University System, Purdue University West Lafayette, University of Georgia USA, University of Delaware Newark, Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Texas A&M University College Station, National Corn Growers Association, Iowa Corn Promotion Board, Georgia Corn Commission, Nebraska Corn Board, Ohio Corn Marketing Program, Corn Marketing Program of Michigan, Texas Corn Producers Board, University of Göttingen startup funds, USDA‑ARS, and USDA Germplasm Enhancement of Maize program.

المصدر: ISSN: 2730-6844.

مصطلحات موضوعية: Maize, Genotype by environment, Phenotype, Variable environments, Grain yield Objective, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics

الوصف: International audience ; Objectives This report provides information about the public release of the 2018-2019 Maize G X E project of the Genomes to Fields (G2F) Initiative datasets. G2F is an umbrella initiative that evaluates maize hybrids and inbred lines across multiple environments and makes available phenotypic, genotypic, environmental, and metadata information. The initiative understands the necessity to characterize and deploy public sources of genetic diversity to face the challenges for more sustainable agriculture in the context of variable environmental conditions. Data description Datasets include phenotypic, climatic, and soil measurements, metadata information, and inbred genotypic information for each combination of location and year. Collaborators in the G2F initiative collected data for each location and year; members of the group responsible for coordination and data processing combined all the collected information and removed obvious erroneous data. The collaborators received the data before the DOI release to verify and declare that the data generated in their own locations was accurate. ReadMe and description files are available for each dataset. Previous years of evaluation are already publicly available, with common hybrids present to connect across all locations and years evaluated since this project's inception.

العلاقة: hal-04175989; https://hal.inrae.fr/hal-04175989Test; https://hal.inrae.fr/hal-04175989/documentTest; https://hal.inrae.fr/hal-04175989/file/Lima-BMCGD-2023-CC-BY.pdfTest; WOS: 001001164200002

الإتاحة: https://doi.org/10.1186/s12863-023-01129-2Test
https://hal.inrae.fr/hal-04175989Test
https://hal.inrae.fr/hal-04175989/documentTest
https://hal.inrae.fr/hal-04175989/file/Lima-BMCGD-2023-CC-BY.pdfTest

المؤلفون: Lima, Dayane Cristina, Aviles, Alejandro Castro, Alpers, Ryan Timothy, Perkins, Alden, Schoemaker, Dylan L, Costa, Martin, Michel, Kathryn J., Kaeppler, Shawn, Ertl, David, Romay, Maria Cinta, Gage, Joseph L., Holland, James, Beissinger, Timothy, Bohn, Martin, Buckler, Edward, Edwards, Jode, Flint-Garcia, Sherry, Gore, Michael A., Hirsch, Candice N., Knoll, Joseph E., McKay, John, Minyo, Richard, Murray, Seth C., Schnable, James, Sekhon, Rajandeep S., Singh, Maninder P., Sparks, Erin E., Thomison, Peter, Thompson, Addie, Tuinstra, Mitchell, Wallace, Jason, Washburn, Jacob D., Weldekidan, Teclemariam, Xu, Wenwei, de Leon, Natalia

المصدر: BMC Research Notes ; volume 16, issue 1 ; ISSN 1756-0500

مصطلحات موضوعية: General Biochemistry, Genetics and Molecular Biology, General Medicine

الوصف: Objectives This release note describes the Maize GxE project datasets within the Genomes to Fields (G2F) Initiative. The Maize GxE project aims to understand genotype by environment (GxE) interactions and use the information collected to improve resource allocation efficiency and increase genotype predictability and stability, particularly in scenarios of variable environmental patterns. Hybrids and inbreds are evaluated across multiple environments and phenotypic, genotypic, environmental, and metadata information are made publicly available. Data description The datasets include phenotypic data of the hybrids and inbreds evaluated in 30 locations across the US and one location in Germany in 2020 and 2021, soil and climatic measurements and metadata information for all environments (combination of year and location), ReadMe, and description files for each data type. A set of common hybrids is present in each environment to connect with previous evaluations. Each environment had a collaborator responsible for collecting and submitting the data, the GxE coordination team combined all the collected information and removed obvious erroneous data. Collaborators received the combined data to use, verify and declare that the data generated in their own environments was accurate. Combined data is released to the public with minimal filtering to maintain fidelity to the original data.

الإتاحة: https://doi.org/10.1186/s13104-023-06430-yTest

المؤلفون: Lima, Dayane Cristina, Washburn, Jacob D., Varela, José Ignacio, Chen, Qiuyue, Gage, Joseph L., Romay, Maria Cinta, Holland, James, Ertl, David, Lopez-Cruz, Marco, Aguate, Fernando M., de los Campos, Gustavo, Kaeppler, Shawn, Beissinger, Timothy, Bohn, Martin, Buckler, Edward, Edwards, Jode, Flint-Garcia, Sherry, Gore, Michael A., Hirsch, Candice N., Knoll, Joseph E., McKay, John, Minyo, Richard, Murray, Seth C., Ortez, Osler A., Schnable, James C., Sekhon, Rajandeep S., Singh, Maninder P., Sparks, Erin E., Thompson, Addie, Tuinstra, Mitchell, Wallace, Jason, Weldekidan, Teclemariam, Xu, Wenwei, de Leon, Natalia

المصدر: BMC Research Notes ; volume 16, issue 1 ; ISSN 1756-0500

مصطلحات موضوعية: General Biochemistry, Genetics and Molecular Biology, General Medicine

الوصف: Objectives The Genomes to Fields (G2F) 2022 Maize Genotype by Environment (GxE) Prediction Competition aimed to develop models for predicting grain yield for the 2022 Maize GxE project field trials, leveraging the datasets previously generated by this project and other publicly available data. Data description This resource used data from the Maize GxE project within the G2F Initiative [1]. The dataset included phenotypic and genotypic data of the hybrids evaluated in 45 locations from 2014 to 2022. Also, soil, weather, environmental covariates data and metadata information for all environments (combination of year and location). Competitors also had access to ReadMe files which described all the files provided. The Maize GxE is a collaborative project and all the data generated becomes publicly available [2]. The dataset used in the 2022 Prediction Competition was curated and lightly filtered for quality and to ensure naming uniformity across years.

الإتاحة: https://doi.org/10.1186/s13104-023-06421-zTest