Biology subjects

Ramirez Gonzalez, R. H.

Publications and source records attributed to Ramirez Gonzalez, R. H..

5 recordsLinked to original sources

bioRxiv2026

Natural and breeding selection converge on overlapping haplotypes with divergent directions and outcomes in wheat

Understanding how natural and breeding selection interact to shape crop genomes is essential for improving resilience under climate change. Here, we applied a k-mer-based, alignment-free haplotype assignment approach to whole-genome resequencing data from 827 wheat landraces representing seven geographic groups and 208 modern cultivars. We identified haplotypes associated with local adaptation that were enriched in specific agroecological regions, many of which were derived from wild-relative introgressions. Comparative analyses revealed that natural and breeding selection largely targeted overlapping haplotype sets, but often drove them in opposite directions. Notably, haplotypes conferring adaptive advantages were frequently associated with negative regulation of agronomic traits, explaining their reduced prevalence among breeding-selected haplotypes. These results reveal the genomic basis of trade-offs between environmental adaptation and productivity and offer a framework for exploiting adaptive diversity in wheat improvement.

plant biology↗

bioRxiv2025

KCFtools: Rapid alignment-free method for introgression screening and GWAS using k-mer profiles

MotivationIn the era of multiple genome references, researchers often align sequencing reads against distinct assemblies or even multiple references simultaneously. This enables applications such as the detection of introgressed segments or highly variable genomic regions, which are especially prevalent in large-genome crop species such as lettuce or wheat. However, these applications come at the cost of increased computational burden, inconsistencies in mapping methods, and reduced reproducibility across studies. To address these limitations, we developed KCFtools, a Java-based toolkit that identifies the presence and absence of k-mers in non-overlapping genomic or transcriptomic windows by comparing query and reference genomes. This alignment-free approach enables the efficient computation of an identity score for each window, thereby facilitating robust detection of introgressed or variable regions across genomes. ResultsWe systematically evaluated the performance and accuracy of the k-mer-based method implemented in KCFtools, benchmarking it against conventional SNP-based introgression detection pipelines. Our results demonstrate that KCFtools effectively captures introgressed segments and structurally diverse regions, even in species with fragmented or highly divergent reference genomes. In addition, we extended KCFtools to generate genotype matrices from k-mer variation tables. These matrices are compatible with Genome-Wide Association Studies (GWAS) software and allow the identification of loci associated with phenotypic traits. We showcase the utility of this approach by detecting known and novel associations for downy mildew resistance in lettuce, underscoring the pipelines potential for high-resolution, reference-agnostic population genetic analysis. Availabilityhttps://github.com/sivasubramanics/kcftools Contactc.s.sivasubramani@gmail.com

bioinformatics↗

bioRxiv2023

Recognition of Necrosis and Ethylene-inducing like peptides confers disease resistance in Brassica napus and is modulated by BSK1 in Arabidopsis

Brassicas are important crops susceptible to significant losses caused by disease: thus, breeding resistant lines can mitigate the effects of pathogens. MAMPs (microbe-associated molecular patterns) are conserved molecules of pathogens that elicit host defence responses known as pattern-triggered immunity (PTI). Necrosis & Ethylene-inducing peptide 1-like proteins (NLPs) are MAMPs found in a wide range of phytopathogens, including major disease-causing fungal species. We studied the response to the BcNEP2 from Botrytis cinerea as a representative NLP in Brassica napus to improve our understanding of recognition mechanisms that could enable the development of disease-resistant crops. To genetically map regions responsible for NLP recognition, we used an associative transcriptomics (AT) approach using diverse B. napus accessions and bulk segregant analysis (BSA) on DNA pools created from a bi-parental cross of NLP-responsive (Ningyou1) and non-responsive (Ningyou7) lines. In silico mapping with AT identified two peaks associated with NLP recognition on chromosomes A04 and C05 whereas the BSA narrowed it down to a main peak on A04. BSA delimited the region associated with NLP-responsiveness to 3 Mbp, containing [~]245 genes on the Darmor-bzh reference genome. Variants detected in the region were used for KASP marker design and four KASP markers were identified co-segregating with the phenotype. The same pipeline was performed with the ZS11 genome, and the highest associated region was confirmed on chromosome A04. Comparative BLAST analysis revealed there were unannotated clusters of RLP homologs on ZS11 chromosome A04. To reduce the number of candidate genes responsible for NLP recognition, RNA-Seq data was used to detect the unannotated expressed putative genes. Screening the BSA Ning1x7 population demonstrated a highly significant association between NLP-recognition and resistance to Botrytis cinerea. Also, the lines non-responsive to NLP had significantly greater response to the bacterial MAMP flg22. Additionally, BnaA01g02190D, a homologue of Arabidopsis AtBSK1 (At4g35230) BR-SIGNALLING KINASE1, was associated with a high BcNEP2-induced ROS response phenotype. We show that in Arabidopsis, Atbsk1 mutants had significantly lower response to BcNEP2 and increased susceptibility to B. cinerea (p-value=1.12e-14***). Overall, the results define the genomic location for NLP-recognition on the B. napus genome and demonstrate that NLP recognition has a positive contribution to disease resistance which can have practical application in crop improvement.

plant biology↗

bioRxiv2019

A co-expression network in hexaploid wheat reveals mostly balanced expression and lack of significant gene loss of homeologous meiotic genes upon polyploidization

Polyploidization has played an important role in plant evolution. However, upon polyploidization the process of meiosis must adapt to ensure the proper segregation of increased numbers of chromosomes to produce balanced gametes. It has been suggested that meiotic gene (MG) duplicates return to a single copy following whole genome duplication to stabilise the polyploid genome. Therefore, upon the polyploidization of wheat, a hexaploid species with three related (homeologous) genomes, the stabilization process may have involved rapid changes in content and expression of MGs on homeologous chromosomes (homeologs). To examine this hypothesis, sets of candidate MGs were identified in wheat using co-expression network analysis and orthology informed approaches. In total, 130 RNA-Seq samples from a range of tissues including wheat meiotic anthers were used to define co-expressed modules of genes. Three modules were significantly correlated with meiotic tissue samples but not with other tissue types. These modules were enriched for GO terms related to cell cycle, DNA replication and chromatin modification, and contained orthologs of known MGs. Overall 74.4 % of genes within these meiosis-related modules had three homeologous copies which was similar to other tissue-related modules. Amongst wheat MGs identified by orthology, rather than co-expression, the majority (93.7 %) were either retained in hexaploid wheat at the same number of copies (78.4 %) or increased in copy number (15.3%) compared to ancestral wheat species. Furthermore, genes within meiosis-related modules showed more balanced expression levels between homeologs than genes in non-meiosis-related modules. Taken together our results do not support extensive gene loss nor changes in homeolog expression of MGs upon wheat polyploidization. The construction of the MG co-expression network allowed identification of hub genes and provided key targets for future studies.\n\nAuthor summaryAll flowering plants have undergone a polyploidization event(s) during their evolutionary history. One of the biggest challenges faced by a newly-formed polyploid is meiosis, an essential event for sexual reproduction and fertility. This process must adapt to discriminate between multiple related chromosomes and to ensure their proper segregation to produce fertile gametes. The meiotic mechanisms responsible for the stabilisation of the extant polyploids remain poorly understood except in wheat, where there is now a better understanding of these processes. It has been proposed that meiotic adaptation in established polyploids could involve meiotic gene loss following the event of polyploidization. To test this hypothesis in hexaploid wheat, we have computationally predicted sets of hexaploid wheat meiotic genes based on expression data from different tissue types, including meiotic anther tissue, and orthology informed approaches. We have calculated homeolog expression patterns and number of gene copies for the predicted meiotic genes and compared them with proper control gene sets. Our findings did not support any significant meiotic gene loss upon wheat polyploidization. Furthermore, wheat meiotic genes showed more balanced expression levels between homeologs than non-meiotic genes.

bioinformatics↗

bioRxiv2016

An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations.

Advances in genome sequencing and assembly technologies are generating many high quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimised data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents more than 78% of the genome with a scaffold N50 of 88.8kbp that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNAseq and PacBio full-length cDNAs to identify 104,091 high confidence protein-coding genes and 10,156 non-coding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop. [Supplemental material is available for this article.]

genomics↗