Biology subjects

Cockram, J.

Publications and source records attributed to Cockram, J..

4 recordsLinked to original sources

bioRxiv2022

A global pangenome for the wheat fungal pathogen Pyrenophora tritici-repentis and prediction of effector protein structural homology

The adaptive potential of plant fungal pathogens is largely governed by the gene content of a species, comprised of core and ancillary genes across the pathogen isolate repertoire. To approximate the complete gene repertoire of a globally significant crop fungal pathogen, a pan genomic analysis was undertaken for Pyrenophora tritici-repentis (Ptr), the causal agent of tan (or yellow) spot disease in wheat. In this study, fifteen new Ptr genomes were sequenced, assembled and annotated, including isolates from three races not previously sequenced. Together with eleven previously published Ptr genomes, a pangenome for twenty-six Ptr isolates from Australia, Europe, North Africa and America, representing nearly all known races, revealed a conserved core-gene content of 57% and presents a new Ptr resource for searching natural homologues using remote protein structural homology. Here, we identify for the first time a nonsynonymous mutation in the Ptr effector gene ToxB, multiple copies of toxb, a distant natural Pyrenophora homologue of a known Parastagonopora nodorum effector, and clear genomic break points for the ToxA effector horizontal transfer region. This comprehensive genomic analysis of Ptr races includes nine isolates sequenced via long read technologies. Accordingly, these resources provide a more complete representation of the species, and serve as a resource to monitor variations potentially involved in pathogenicity. Author NotesAll supporting data, code and protocols have been provided within the article or through supplementary data files. Five supplementary data files and fifteen supplementary figures are available with the online version of this article. Impact StatementOur Pyrenophora tritici-repentis (Ptr) pangenome study provides resources and analyses for the identification of pathogen virulence factors, of high importance to microbial research. Key findings include: 1) Analysis of eleven new sequenced (with three new races not previously available) and previously published isolates, 26 genomes in total, representing the near complete Ptr race set for known effector production collected from Australia, Europe, North Africa and the Americas. 2) We show that although Ptr has low core gene conservation, the whole genome divergence of other wheat pathogens was greater. 3) The new PacBio sequenced genomes provide unambiguous genomic break points for the large ToxA effector horizontal transfer region, which is only present in ToxA producing races. 4) A new web-based Ptr resource for searching in silico remote protein structural homology is presented, and a distant natural Pyrenophora protein homologue of a known effector from another wheat pathogen is identified for the first time. Data SummaryThe sources and genomic sequences used throughout this study have been deposited in the National Centre for Biotechnology Information (NCBI), under the assembly accession numbers provided in Tables 1 and 2 (available in the online version of this article). The new M4 resource for protein structural homology is freely available through the BackPhyre web-portal URL, http://www.sbg.bio.ic.ac.uk/phyre2/. O_TBL View this table: org.highwire.dtl.DTLVardef@c6b2deorg.highwire.dtl.DTLVardef@1091da1org.highwire.dtl.DTLVardef@17860a4org.highwire.dtl.DTLVardef@10d4aaorg.highwire.dtl.DTLVardef@fa258f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONSummary statistics for our four PacBio sequenced Ptr genome assemblies, compared with those of two previously published Ptr assemblies. C_TABLECAPTION C_TBL O_TBL View this table: org.highwire.dtl.DTLVardef@b7d0cforg.highwire.dtl.DTLVardef@1ee01e6org.highwire.dtl.DTLVardef@becc09org.highwire.dtl.DTLVardef@456c7corg.highwire.dtl.DTLVardef@1d55799_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 2.C_FLOATNO O_TABLECAPTIONIllumina sequenced genome assemblies of 11 new Ptr isolates. Table shows isolate source, race and de novo assembly statistics. C_TABLECAPTION C_TBL

genomics↗

bioRxiv2021

Genetic resistance to yellow rust infection of the wheat ear is controlled by genes controlling foliar resistance and flowering time

Yellow rust (YR), or stripe rust, is a fungal infection of wheat (Triticum aestivum L.) caused by the pathogen Puccinia striiformis Westend f. sp. tritici (Pst). While much research has focused on YR infection of wheat leaves, we are not aware of reports investigating the genetic control of YR resistance in other wheat structures, such as the ears. Here we use an eight-founder population to undertake genetic analysis of glume YR infection in wheat ears. Five quantitative trait loci (QTL) were identified, each explaining between ~3-7% of the phenotypic variation. Of these, three (QYrg.niab-2D.2, QYrg.niab-4D.1 and QYrg.niab-5A.1) co-located with QTL for leaf YR resistance previously identified in the same population, with evidence suggesting QYrg.niab-5A.1 may correspond to the adult plant resistance locus Yr34 which originates from T. monococcum ssp. monococcum and that resistance at QYrg.niab-2D.2 may be conferred by chromosomal introgression from a wheat relative. Additional leaf YR resistance QTL previously identified in the population were not detected as controlling glume resistance, with the remaining two glume YR QTL linked to genetic loci controlling flowering time. The first of these, QYrg.niab-2D.1, mapped to the major flowering time locus Photoperiod-D1 (Ppd-D1), with the early-flowering allele from the MAGIC founder Soissons conferring reduced glume YR resistance. The second, QYrg.niab-4A.1, was identified in one trial only, and was located close to a flowering time QTL. This indicates earlier flowering results in increased glume YR susceptibility, likely due to exposure of tissues during environmental conditions more favourable for Pst infection. Collectively, our results provide first insights into the genetic control of YR resistance in glumes, controlled by subsets of QTL for leaf YR resistance and flowering time. This work provides specific genetic targets for the control of YR resistance in both the leaves and the glumes, and may be especially relevant in Pst-prone agricultural environments where earlier flowering is favoured. Core ideasO_LIPuccinia striiformis Westend f. sp. tritici (Pst) causes yellow rust (YR) in wheat leaves and ears. C_LIO_LIWe present the first reports for the genetic control of YR on the wheat ear. C_LIO_LIEar YR infection is controlled by subsets of QTL controlling leaf resistance and flowering time. C_LIO_LIThe findings are relevant to wheat breeding for Pst-prone environments. C_LI

genetics↗

bioRxiv2020

Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley

The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However in many cases, the underlying alleles and genomic regions that have underpinned this success remain unknown. This is due, in part, to the difficulty in generating sufficient phenotypic data on large numbers of historical varieties to allow such analyses to be undertaken. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using the age of a variety as a surrogate for yield. Using environmental genome-wide association scans (EnvGWAS) on variety age in two of the worlds most important crops, wheat and barley, we found strong signals of selection across the genomes of our target crops. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure in wheat and barley over the past century, we used the same genotypic data to derive eigenvectors for deployment in EigenGWAS. This resulted in the detection of seven major chromosomal introgressions that contributed to adaptation in wheat. The deployment of both EigenGWAS and EnvGWAS based on variety age avoids costly phenotyping and will facilitate the identification of genomic tracts that have been under selection during plant breeding in underutilized historical cultivar collections. Our results not only demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions that have been under selection but to also guide future plant breeding strategies to maximise the rate of genetic gain and adaptation in crop improvement programs. Significance Statement100 years of plant breeding have greatly improved crop adaptation, resilience, and productivity. Generating the trait data required for these studies is prohibitively expensive and can be impossible on large historical traits. This study reports using variety age and eigenvectors of the genomic relationship matrix as surrogate traits in GWAS to locate the genomic regions that have undergone selection during varietal development in wheat and barley. In several cases these were confirmed as associated with yield and other selected traits. The success and the simplicity of the approach means it can easily be extended to other crops with a recent recorded history of plant breeding and available genomic resources.

genetics↗

bioRxiv2020

Limited haplotype diversity underlies polygenic trait architecture across 70 years of wheat breeding

BackgroundBreeding has helped improve bread wheat yield significantly over the last century. Understanding the potential for future crop improvement depends on relating segregating genetic variation to agronomic traits. ResultsWe bred NIAB Diverse MAGIC population, comprising over 500 recombinant inbred lines, descended from sixteen bread wheat varieties released between 1935-2004. We sequenced the founders exomes and promotors by capture. Despite being highly representative of North-West European wheat and capturing 73% of global polymorphism, we found 89% of genes contained no more than three haplotypes. We sequenced each line with 0.3x coverage whole-genome sequencing, and imputed 1.1M high-quality SNPs that were over 99% concordant with array genotypes. Imputation accuracy remained high at coverage as low as 0.076x, with or without the use of founder genomes as reference panels. We created a genotype-phenotype map for 47 traits over two years. We found 136 genome-wide significant associations, concentrated at 42 genetic loci with large and often pleiotropic effects. Outside of these loci most traits are polygenic, as revealed by multi-locus shrinkage modelling. ConclusionsHistorically, wheat breeding has reshuffled a limited palette of haplotypes; continued improvement will require selection at dozens of loci of diminishing effect, as most of the major loci we mapped are known. Breeding to optimise one trait generates correlated trait changes, exemplified by the negative trade-off between yield and protein content, unless selection and recombination can break critical unfavourable trait-trait associations. Finally, low coverage whole genome sequencing of bread wheat populations is an economical and accurate genotyping strategy.

genomics↗