Large differences in gene expression responses to drought and heat stress between elite barley cultivar scarlett and a spanish landrace

23 Pags.- 6 Tabls.- 8 Figs. Copyright © 2017 Cantalapiedra, García-Pereira, Gracia, Igartua, Casas and Contreras-Moreira. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forms is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Drought causes important losses in crop production every season. Improvement for drought tolerance could take advantage of the diversity held in germplasm collections, much of which has not been incorporated yet into modern breeding. Spanish landraces constitute a promising resource for barley breeding, as they were widely grown until last century and still show good yielding ability under stress. Here, we study the transcriptome expression landscape in two genotypes, an outstanding Spanish landrace-derived inbred line (SBCC073) and a modern cultivar (Scarlett). Gene expression of adult plants after prolonged stresses, either drought or drought combined with heat, was monitored. Transcriptome of mature leaves presented little changes under severe drought, whereas abundant gene expression changes were observed under combined mild drought and heat. Developing inflorescences of SBCC073 exhibited mostly unaltered gene expression, whereas numerous changes were found in the same tissues for Scarlett. Genotypic differences in physiological traits and gene expression patterns confirmed the different behavior of landrace SBCC073 and cultivar Scarlett under abiotic stress, suggesting that they responded to stress following different strategies. A comparison with related studies in barley, addressing gene expression responses to drought, revealed common biological processes, but moderate agreement regarding individual differentially expressed transcripts. Special emphasis was put in the search of co-expressed genes and underlying common regulatory motifs. Overall, 11 transcription factors were identified, and one of them matched cis-regulatory motifs discovered upstream of co-expressed genes involved in those responses.This work was funded by DGA - Obra Social La Caixa [grant number GA-LC-059-2011] and by the Spanish Ministry of Economy and Competitiveness [projects AGL2010-21929, RFP-2012-00015-00-00 AGL2013-48756-R and AGL2016-80967-R]. Carlos P. Cantalapiedra is funded by [grant BES-2011-045905 linked to project AGL2010-21929].Peer reviewe

A cluster of nucleotide-binding site-leucine-rich repeat genes resides in a barley powdery mildew resistance quantitative trait loci on 7HL

Powdery mildew causes severe yield losses in barley production worldwide. Although many resistance genes have been described, only a few have already been cloned. A strong QTL (quantitative trait locus) conferring resistance to a wide array of powdery mildew isolates was identified in a Spanish barley landrace on the long arm of chromosome 7H. Previous studies narrowed down the QTL position, but were unable to identify candidate genes or physically locate the resistance. In this study, the exome of three recombinant lines from a high-resolution mapping population was sequenced and analyzed, narrowing the position of the resistance down to a single physical contig. Closer inspection of the region revealed a cluster of closely related NBS-LRR (nucleotide-binding site–leucine-rich repeat containing protein) genes. Large differences were found between the resistant lines and the reference genome of cultivar Morex, in the form of PAV (presence-absence variation) in the composition of the NBS-LRR cluster. Finally, a template-guided assembly was performed and subsequent expression analysis revealed that one of the new assembled candidate genes is transcribed. In summary, the results suggest that NBS-LRR genes, absent from the reference and the susceptible genotypes, could be functional and responsible for the powdery mildew resistance. The procedure followed is an example of the use of NGS (next-generation sequencing) tools to tackle the challenges of gene cloning when the target gene is absent from the reference genome

Resequencing the Vrs1 gene in Spanish barley landraces revealed reversion of six-rowed to two-rowed spike

Six-rowed spike 1 (Vrs1) is a gene of major importance for barley breeding and germplasm management as it is the main gene determining spike row-type (2-rowed vs. 6-rowed). This is a widely used DUS trait, and has been often associated to phenotypic traits beyond spike type. Comprehensive re-sequencing Vrs1 revealed three two-rowed alleles (Vrs1.b2; Vrs1.b3; Vrs1.t1) and four six-rowed (vrs1.a1; vrs1.a2; vrs1.a3; vrs1.a4) in the natural population. However, the current knowledge about Vrs1 alleles and its distribution among Spanish barley subpopulations is still underexploited. We analyzed the gene in a panel of 215 genotypes, made of Spanish landraces and European cultivars. Among 143 six-rowed accessions, 57 had the vrs1.a1 allele, 83 were vrs1.a2, and three showed the vrs1.a3 allele. Vrs1.b3 was found in most two-rowed accessions, and a new allele was observed in 7 out of 50 two-rowed Spanish landraces. This allele, named Vrs1.b5, contains a ‘T’ insertion in exon 2, originally proposed as the causal mutation giving rise to the six-row vrs1.a2 allele, but has an additional upstream deletion that results in the change of 15 amino acids and a potentially functional protein. We conclude that eight Vrs1 alleles (Vrs1.b2, Vrs1.b3, Vrs1.b5, Vrs1.t1, vrs1.a1, vrs1.a2, vrs1.a3, vrs1.a4) discriminate two and six-rowed barleys. The markers described will be useful for DUS identification, plant breeders, and other crop scientists.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness grants AGL2010-21929, AGL2013-48756-R, RFP2012-00015-00-00, RTA2012-00033-C03-02, and EUI2009-04075 (national code for Plant-KBBE project ExpResBar). CPC was funded by the Spanish Ministry of Economy, Industry and Competitiveness grant no. BES-2011-045905 (linked to project AGL2010-21929). TK and SS were supported by a research fund by the Ministry of Agriculture, Forestry, and Fisheries of Japan (Genomics for Agricultural Innovation grants no. TRS1002). SS was supported by a Grant-in-Aid from the Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellow for Research Abroad and a Grant-in-Aid for Young Scientists (B) (no. 16 K18635)

eggNOG 6.0: enabling comparative genomics across 12 535 organisms

The eggNOG (evolutionary gene genealogy Non-supervised Orthologous Groups) database is a bioinformatics resource providing orthology data and comprehensive functional information for organisms from all domains of life. Here, we present a major update of the database and website (version 6.0), which increases the number of covered organisms to 12 535 reference species, expands functional annotations, and implements new functionality. In total, eggNOG 6.0 provides a hierarchy of over 17M orthologous groups (OGs) computed at 1601 taxonomic levels, spanning 10 756 bacterial, 457 archaeal and 1322 eukaryotic organisms. OGs have been thoroughly annotated using recent knowledge from functional databases, including KEGG, Gene Ontology, UniProtKB, BiGG, CAZy, CARD, PFAM and SMART. eggNOG also offers phylogenetic trees for all OGs, maximising utility and versatility for end users while allowing researchers to investigate the evolutionary history of speciation and duplication events as well as the phylogenetic distribution of functional terms within each OG. Furthermore, the eggNOG 6.0 website contains new functionality to mine orthology and functional data with ease, including the possibility of generating phylogenetic profiles for multiple OGs across species or identifying single-copy OGs at custom taxonomic levels. eggNOG 6.0 is available at http://eggnog6.embl.de

Candidate genes underlying QTL for flowering time and their interactions in a wide spring barley (Hordeum vulgare L.) cross

Response to vernalization and photoperiod are the main determinants controlling the time to flowering in temperate cereals. While the individual genes that determine a plant's response to these environmental signals are well characterized, the combinatorial effect on flowering time of allelic variants for multiple genes remains unresolved. This study investigated the genetic control of flowering-time in a biparental population of spring barley, derived from a wide cross between a late-flowering European and an early-flowering North-American cultivar. While the major flowering time genes are not segregating in the Beka × Logan cross, large variation in flowering was observed. We identified five QTL, with both parents found to contribute early alleles. The catalog of QTL discovered aligns with several candidate genes affecting flowering time in barley. The combination of particular alleles at HvCEN, HvELF3 and HvFT1 in Logan are responsible for the earliness of this cultivar. Interestingly, earliness for flowering could be further enhanced, with Beka found to contribute three early alleles, including a QTL co-locating with a HvFD-like gene, suggesting that there are diverse aspects of the flowering-time pathway that have been manipulated in these two cultivars. Epistatic interactions between flowering-time QTL or candidate genes were observed in field data and confirmed under controlled conditions. The results of this study link photoperiod-dependent flowering-time genes with earliness per se genes into a single model, thus providing a unique framework that can be used by geneticists and breeders to optimize flowering time in barley.This work was supported by the Spanish Ministry of Economy and Competitiveness (grant numbers AGL2010-21929 and AGL2013-48756-R), the Spanish Ministry of Economy and Competitiveness, the Agencia Estatal de Investigación, and the European Regional Development Fund (grant number AGL2016–80967-R), and Government of Aragon (Research Group A08_20R)

eggNOG 6.0: enabling comparative genomics across 12 535 organisms

6 Pág.The eggNOG (evolutionary gene genealogy Non-supervised Orthologous Groups) database is a bioinformatics resource providing orthology data and comprehensive functional information for organisms from all domains of life. Here, we present a major update of the database and website (version 6.0), which increases the number of covered organisms to 12 535 reference species, expands functional annotations, and implements new functionality. In total, eggNOG 6.0 provides a hierarchy of over 17M orthologous groups (OGs) computed at 1601 taxonomic levels, spanning 10 756 bacterial, 457 archaeal and 1322 eukaryotic organisms. OGs have been thoroughly annotated using recent knowledge from functional databases, including KEGG, Gene Ontology, UniProtKB, BiGG, CAZy, CARD, PFAM and SMART. eggNOG also offers phylogenetic trees for all OGs, maximising utility and versatility for end users while allowing researchers to investigate the evolutionary history of speciation and duplication events as well as the phylogenetic distribution of functional terms within each OG. Furthermore, the eggNOG 6.0 website contains new functionality to mine orthology and functional data with ease, including the possibility of generating phylogenetic profiles for multiple OGs across species or identifying single-copy OGs at custom taxonomic levels. eggNOG 6.0 is available at http://eggnog6.embl.de.National Programme for Fostering Excellence in Scientific and Technical Research [PGC2018-098073-A-I00 MCIU/AEI/FEDER, UE to J.H.-C., J.G.-L.]; Chan Zuckerberg Initiative DAF [2020-218584]; Silicon Valley Community Foundation (to J.B. and J.H.C.); Severo Ochoa Centres of Excellence Programme from the State Research Agency (AEI) of Spain [SEV-2016–0672 (2017–2021) to C.P.C.]; Research Technical Support Staff Aid [PTA2019-017593-I/AEI/10.13039/501100011033 to A.H.P.]; Novo Nordisk Foundation [NNF14CC0001 to R.K., L.J.J.]; SIB Swiss Institute of Bioinformatics (to D.S. and C.vM.). Funding for open access charge: Institutional CSIC and EMBL agreements.Peer reviewe

Towards the biogeography of prokaryotic genes

Funding was provided by the European Union’s Horizon 2020 Research and Innovation Programme (grant 686070: DD-DeCaF to P.B.) and Marie Skłodowska-Curie Actions (grant 713673 to A.R.d.R.), the European Research Council (ERC) MicrobioS (ERC-AdG-669830 to P.B.), JTC project jumpAR (01KI1706 to P.B.), a BMBF Grant (grant 031L0181A: LAMarCK to P.B.), the European Molecular Biology Laboratory (P.B.), the ETH and Helmut Horten Foundation (S.S.), the National Key R&D Program of China (grant 2020YFA0712403 to X.-M.Z.), (grant 61932008 to X.-M.Z.; grant 61772368 to X.-M.Z.; grant 31950410544 to L.P.C.), the Shanghai Municipal Science and Technology Major Project (grant 2018SHZDZX01 to X.-M.Z. and L.P.C.) and Zhangjiang Lab (X.-M.Z. and L.P.C.), the International Development Research Centre (grant 109304, EMBARK under the JPI AMR framework; to L.P.C.), la Caixa Foundation (grant 100010434, fellowship code LCF/BQ/DI18/11660009 to A.R.d.R.), the Severo Ochoa Program for Centres of Excellence in R&D from the Agencia Estatal de Investigación of Spain (grant SEV-2016-0672 (2017–2021) to C.P.C.), the Ministerio de Ciencia, Innovación y Universidades (grant PGC2018-098073-A-I00 MCIU/AEI/FEDER to J.H.-C. and J.G.-L.), the Innovation Fund Denmark (grant 4203-00005B, PNM), the Biotechnology and Biological Sciences research Council (BBSrC) Gut MicroInstitute Strategic Programmebes and Health BB/r012490/1 and its constituent project BBS/e/F/000Pr10355 (F.H.). R.A. is a member of the Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences.Peer reviewe

eggNOG-mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale

Centro de Biotecnología y Genómica de Plantas (CBGP)Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows for: 1) de novo gene prediction from raw contigs, 2) built-in pairwise orthology prediction, 3) fast protein domain discovery, and 4) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.This research was supported by the National Programme for Fostering Excellence in Scientific and Technical Research (Grant No. PGC2018-098073-A-I00 MCIU/AEI/FEDER, UE, to J.H.C.) and the Severo Ochoa Centres of Excellence Programme (Grant No. SEV-2016-0672 (2017–2021) to C.P.C.) from the State Research Agency (AEI) of Spain, as well as a Research Technical Support Staff Aid (PTA2019-017593-I/AEI/10.13039/501100011033 to A.H.P.); European Research Council grant MicroBioS (ERC-2014-AdG)—GA669830 (to P.B.). Cloud computing is supported by BMBF (de.NBI network #031A537B).Peer reviewed5 Pág