The effect of chromosome structure upon meiotic homologous and homoeologous recombinations in Triticeae

The tribe Triticeae contains about 500 diploid and polyploid taxa, among which are important crops, such as wheat, barley and rye. The phylogenetic relationships, genome compo-sition and chromosomal architecture, were already reported in the pioneer genetic studies on these species, given their implications in breeding-related programs. Hexaploid wheat, driven by its high capacity to develop cytogenetic stocks, has always been at the forefront of these studies. Cytogenetic stocks have been widely used in the identification of homoeologous relationships between the chromosomes of wheat and related species, which has provided valuable information on genome evolution with implications in the transfer of useful agronomical traits into crops. Meiotic recombination is non-randomly distributed in the Triticeae species, and crossovers are formed in the distal half of the chromosomes. Also of interest for crops improvement is the possibility of being able to modulate the intraspecific and interspecific recombination landscape to increase its frequency in crossover-poor regions. Structural changes may help in this task. In fact, chromosome truncation increases the recombination frequency in the adjacent intercalary region. However, structural changes also have a negative effect upon recombination. Gross chromosome rearrangements produced in the evolution usually suppress meiotic recombination between non-syntenic homoeologs. Thus, the chromosome structural organization of related genomes is of great interest in designing strategies of the introgression of useful genes into crops

Del color de los ojos al interior del genoma. Nuevas tecnologías aplicadas a la educación: una experiencia en la enseñanza de la Genética

Depto. de Genética, Fisiología y MicrobiologíaFac. de Ciencias BiológicasFALSEsubmitte

Contribution of Structural Chromosome Mutants to the Study of Meiosis in Plants

Dissection of the molecular mechanisms underlying the transition through the complex events of the meiotic process requires the use of gene mutants or RNAi-mediated gene silencing. A considerable number of meiotic mutants have been isolated in plant species such as Arabidopsis thaliana, maize or rice. However, structural chromosome mutants are also important for the identification of the role developed by different chromosome domains in the meiotic process. This review summarizes the contribution of studies carried out in plants using structural chromosome variations. Meiotic events concerning the search of the homologous partner, the control of number and distribution of chiasmata, the mechanism of pairing correction, and chromosome segregation are considered

Forcing the shift of the crossover site to proximal regions in wheat chromosomes

Crossovers are not uniformly distributed along chromosomes in wheat. They take place preferentially in distal positions. The effect of the chromosomal architecture on crossover positioning has been analyzed from the chiasmate bonds at metaphase I formed by the truncated arms of 51 terminal deletion lines of eight wheat chromosomes. Chromosome 4A and the B genome chromosomes, in their standard or truncated conformation, and their arms, were identified by C-banding. Chromosomes studied show a similar chiasma distribution. Reduction of the size of the truncated arms is accompanied by a gradual decrease of the chiasma frequency in chromosome arms 1BL, 3BS, 3BL, 4BL, 5BS, 5BL, 6BL, 7BS, 7BL and 4AL. In chromosome arm 1BS, most chiasmata are concentrated in the distal half of the satellite and, in 4AS, in the distal 24 %. The arms 2BS, 2BL and 6BS do not show a simple decreasing gradient of the recombination rate, the chiasma frequency increases in subdistal intervals compared to more distal regions. Although terminal deletions usually induce an increase of chiasma frequency in intercalary regions, the level of intact chromosome arms is maintained in only a few deletion lines. Truncated arms containing only the 20 % proximal of the intact arm do not form chiasmata. The relationships of chiasma positioning with chromatin structure and genome organization is discussed

Analytical Methodology of Meiosis in Autopolyploid and Allopolyploid Plants

Meiosis is the cellular process responsible for producing gametes with half the genetic content of the parent cells. Integral parts of the process in most diploid organisms include the recognition, pairing, synapsis, and recombination of homologous chromosomes, which are prerequisites for balanced segregation of half-bivalents during meiosis I. In polyploids, the presence of more than two sets of chromosomes adds to the basic meiotic program of their diploid progenitors the possibility of interactions between more than two chromosomes and the formation of multivalents, which has implications on chromosome segregations and fertility. The mode of how chromosomes behave in meiosis in competitive situations has been the aim of many studies in polyploid species, some of which are considered here. But polyploids are also of interest in the study of meiosis because some of them tolerate the loss of chromosome segments or complete chromosomes as well as the addition of chromosomes from related species. Deletions allow to assess the effect of specific chromosome segments on meiotic behavior. Introgression lines are excellent materials to monitor the behavior of a given chromosome in the genetic background of the recipient species. We focus on this approach here as based on studies carried out in bread wheat, which is commonly used as a model species for meiosis studies. In addition to highlighting the relevance of the use of materials derived from polyploids in the study of meiosis, cytogenetics tools such as fluorescence in situ hybridization and the immunolabeling of proteins interacting with DNA are also emphasized

Genomic and Meiotic Changes Accompanying Polyploidization

Hybridization and polyploidy have been considered as significant evolutionary forces in adaptation and speciation, especially among plants. Interspecific gene flow generates novel genetic variants adaptable to different environments, but it is also a gene introgression mechanism in crops to increase their agronomical yield. An estimate of 9% of interspecific hybridization has been reported although the frequency varies among taxa. Homoploid hybrid speciation is rare compared to allopolyploidy. Chromosome doubling after hybridization is the result of cellular defects produced mainly during meiosis. Unreduced gametes, which are formed at an average frequency of 2.52% across species, are the result of altered spindle organization or orientation, disturbed kinetochore functioning, abnormal cytokinesis, or loss of any meiotic division. Meiotic changes and their genetic basis, leading to the cytological diploidization of allopolyploids, are just beginning to be understood especially in wheat. However, the nature and mode of action of homoeologous recombination suppressor genes are poorly understood in other allopolyploids. The merger of two independent genomes causes a deep modification of their architecture, gene expression, and molecular interactions leading to the phenotype. We provide an overview of genomic changes and transcriptomic modifications that particularly occur at the early stages of allopolyploid formatio

Del color de los ojos al interior del genoma. Nuevas tecnologías aplicadas a la educación: una experiencia en la enseñanza de la Genética

Depto. de Genética, Fisiología y MicrobiologíaFac. de Ciencias BiológicasFALSEsubmitte

BioEmprende: Biología para el empleo

El proyecto pretende fomentar acciones encaminadas a la inserción en el mercado laboral, dar visibilidad a los convenios firmados y prácticas en empresas, acceso directo a redes de empleo internacionales y potenciar a bioemprendedores

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)