Biology subjects

Cockram, J.

Publications and source records attributed to Cockram, J..

9 recordsLinked to original sources

bioRxiv2025

The barley ear row-number allele ancestral to the six-row allele vrs1.a1 is found in wild barley from the Fertile Crescent

Barley (Hordeum vulgare L.) exhibits two main inflorescence phenotypes: the wild-type two-row form in which only the central spikelet at each rachis node is fertile, and the six-row form, where mutations in the homeobox gene Six-rowed spike 1 (VRS1) confer fertility to all three spikelets. While the six-row alleles vrs1.a2 and vrs1.a3 arose independently from point mutations in the ancestral Vrs1.b2 and Vrs1.b3 alleles, the origin of the hypothesised wild-type Vrs1.b1 allele ancestral to vrs1.a1 is unclear. To explore the origin and exploitation of VRS1 alleles, we re-sequenced VRS1 in 98 cultivars, 170 landraces and 69 wild barley accessions, identifying 39 haplotypes. Sequence analysis confirmed vrs1.a1 as the most commonly used six-row allele in European cultivars. Subsequent analysis of the landrace and wild barley data identified three occurrences of the haplotype consistent with a vrs1.b1 allele, all from wild barley. These wild barley accessions originated from the eastern Fertile Crescent (Iran) and the Caspian Sea region, suggesting vrs1.a1 arose via mutation of Vrs1.b1 within barleys domestication centre - unlike vrs1.a2 and vrs1.a3, which originated in the Western Mediterranean and East Asia cultivated barley genepools, respectively. In addition, we identified ten novel VRS1 amino acid changes in wild barley accessions, which given the pleiotropic effects of VRS1 on traits such as leaf size, vein number and tiller number, may be of interest for future functional investigation. Overall, this study provides insights into the evolution, domestication and utilisation of genetic variation at VRS1, a key gene influencing barley architecture and agricultural performance.

molecular biology↗

bioRxiv2025

Wheat responds to lack of root hairs with recruitment of bacteria harboring P mineralization genes and increased arbuscular mycorrhizal fungi arbuscularisation

Understanding how crops recruit bacterial and fungal partners for phosphorus (P) nutrition remains incomplete, particularly regarding temporal shifts between P-cycling bacteria and arbuscular mycorrhizal fungi (AMF). We investigated these dynamics using the wheat root hair mutant short root hair 1 (srh1), which is impaired in root hair elongation and may be more dependent on microbial P acquisition compared to the wildtype. We profiled the P-cycling bacterial microbiome and AMF colonization across development and at booting under P-depleted conditions. Before AMF establishment, the root hair mutant rhizosphere was enriched in bacterial organic P-mineralization genes. After AMF colonization increased in both genotypes, this enrichment disappeared, indicating a temporal shift from bacterial to fungal P acquisition. Growing the root hair mutant in P-depleted conditions to booting, when P uptake is highest in wheat, did not induce the mutant to recruit its bacterial P-cycling microbiome. Instead, AMF arbuscule formation was enriched. Collectively, our results reveal a temporal transition in wheat from bacterial to AMF-mediated P nutrition and highlight the compensatory role of the microbiome in plants lacking root hair elongation.

microbiology↗

bioRxiv2025

Barley BODYGUARD controls cuticular specialisations regulated by SHINE transcription factors

The outer epidermis of land plants secretes a cuticular layer, a hydrophobic diffusion barrier which minimises water loss into the atmosphere and protects from pests, ultraviolet light and organ fusion. Cuticles typically comprise a polyester cutin matrix embedded and overlaid with cuticular waxes, but their exact chemical make-up, structure and functions can vary widely depending on the tissue and species. Barley shows two such cuticular specialisations: (1) deposition of a thick {beta}-diketone-rich wax bloom on multiple organs at reproductive stage, common in other Poeceae species and linked to yield; and, (2) secretion of a sticky layer on the grain fruit (caryopsis) pericarp cuticle which adheres to inner floral hulls, leading to barleys distinctive covered grain used in animal feed and malting. Two SHINE/WAX-INDUCER transcription factors in barley, HvWIN1 and NUD, promote the wax bloom and hull to caryopsis adhesion, respectively, yet little is understood about other genes involved. Leveraging near-isogenic lines of wax-deficient mutants, we identify the barley BODYGUARD1 (HvBDG1) gene encoding an /{beta}-hydrolase essential for leaf cuticular integrity and wax bloom deposition. Modelling of functional and defective alleles suggests that HvBDG1 N-terminal region control of protein flexibility is important for HvBDG1 function. In addition to their role in controlling barley epicuticular wax deposition, we show that both HvBDG1 and HvWIN1 are essential for strong hull to caryopsis adhesion. Along with NUD, these gene products differentially contribute to ultrastructural changes on the pericarp associated with a cuticular building programme driven by NUD and HvWIN1 regulation of cuticle metabolism and transport and cell wall-related genes, and correlate with shifts in pericarp surface chemistry. We also show that the previously asserted grain-specific role of NUD should be revised, as our findings reveal that it is essential for maintaining leaf cuticle integrity. Our analyses in barley suggest that NUD and HvWIN1 control cuticular specialisations and cuticle integrity in part via promotion of HvBDG1 expression, while HvWIN1 and NUD likely act independently from each other. Lastly, mining tetraploid wheat mutant populations followed by crossing to combine mutated homoeologues demonstrated that BDG1 and WIN1 orthologues also control wax bloom in wheat. Taken together, our work greatly expands the genetic networks and molecular activities important for cuticle development in cereals and the underlying mechanisms for both shared and species-specific cuticular specialisations.

plant biology↗

bioRxiv2025

pyRootHair: Machine Learning Accelerated Software for High-Throughput Phenotyping of Plant Root Hair Traits

1Root hairs play a key role in plant nutrient and water uptake. Historically, root hair traits have been largely quantified manually. As such, this process has been laborious and low-throughput. However, given their importance for plant health and development, high-throughput quantification of root hair morphology could help underpin rapid advances in the genetic understanding of these traits. With recent increases in the accessibility and availability of artificial intelligence (AI) and machine learning techniques, the development of tools to automate plant phenotyping processes has been greatly accelerated. Here, we present pyRootHair, a high-throughput, AI-powered software application to automate root hair trait extraction from images of plant roots grown on agar plates. pyRootHair is capable of batch processing over 600 images per hour without manual input from the end user. In this study, we deploy pyRootHair on a panel of 24 diverse wheat cultivars and uncover a large, previously unresolved amount of variation in many root hair traits. We show that the overall root hair profile falls under two distinct shape categories, and that different root hair traits often correlate with each other. We also demonstrate that pyRootHair can be deployed on a range of plant species, including arabidopsis (Arabidopsis thaliana), brachypodium (Brachypodium distachyon), medicago (Medicago truncatula), oat (Avena sativa), rice (Oryza sativa), teff (Eragostis tef) and tomato (Solanum lycopersicum). The application of pyRootHair enables users to rapidly screen large numbers of plant germplasm resources for variation in root hair morphology, supporting high-resolution measurements and high-throughput data analysis. This facilitates downstream investigation of the impacts of root hair genetic control and morphological variaton on plant performance.

bioinformatics↗

bioRxiv2022

Multi-trait ensemble genomic prediction and simulations of recurrent selection highlight importance of complex trait genetic architecture in long-term genetic gains in wheat

Cereal crop breeders have achieved considerable genetic gain in genetically complex traits, such as grain yield, while maintaining genetic diversity. However, focus on selection for yield has negatively impacted other important traits. To better understand selection within a breeding context, and how it might be optimised, we analysed genotypic and phenotypic data from a diverse, 16-founder wheat multi-parent advanced generation inter-cross (MAGIC) population. Compared to single-trait models, multi-trait ensemble genomic prediction models increased prediction accuracy for almost 90% of traits, improving grain yield prediction accuracy by 3-52%. For complex traits, non-parametric models (Random Forest) also outperformed simplified, additive models (LASSO), increasing grain yield prediction accuracy by 10-36%. Simulations of recurrent genomic selection then showed that sustained greater forward prediction accuracy optimised long-term genetic gains. Simulations of selection on grain yield found indirect responses in related traits, which involved optimisation of antagonistic trait relationships. We found multi-trait selection indices could be used to optimise undesirable relationships, such as the trade-off between grain yield and protein content, or combine traits of interest, such as yield and weed competitive ability. Simulations of phenotypic selection found that including Random Forest rather than LASSO genetic models, and multi-trait rather than single-trait models as the true genetic model, accelerated and extended long-term genetic gain whilst maintaining genetic diversity. These results suggest important roles of pleiotropy and epistasis in the wider context of wheat breeding programmes and provide insights into mechanisms for continued genetic gain in a limited genepool and optimisation of multiple traits for crop improvement.

genetics↗

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↗