Reading at MolecPlantBreed

AlphaFold2 revolutionized structural biology with the ability to predict protein structures with exceptionally high accuracy. Its implementation, however, lacks the code and data required to train new models. These are necessary to (1) tackle new tasks, like protein–ligand complex structure prediction, (2) investigate the process by which the model learns and (3) assess the model’s capacity to generalize to unseen regions of fold space. Here we report OpenFold, a fast, memory efficient and trainable implementation of AlphaFold2. We train OpenFold from scratch, matching the accuracy of AlphaFold2. Having established parity, we find that OpenFold is remarkably robust at generalizing even when the size and diversity of its training set is deliberately limited, including near-complete elisions of classes of secondary structure elements. By analyzing intermediate structures produced during training, we also gain insights into the hierarchical manner in which OpenFold learns to fold. In sum, our studies demonstrate the power and utility of OpenFold, which we believe will prove to be a crucial resource for the protein modeling community. OpenFold is a trainable open-source implementation of AlphaFold2. It is fast and memory efficient, and the code and training data are available under a permissive license.

Human wellbeing depends on ecosystem services, highlighting the need for improving the ecosystem-service multifunctionality of food and feed production systems. We study Swiss agricultural grasslands to assess how employing and combining three widespread aspects of grassland management and their interactions can enhance 22 plot-level ecosystem service indicators, as well as ecosystem-service multifunctionality. The three management aspects we assess are i) organic production system, ii) an eco-scheme prescribing extensive management (without fertilization), and iii) harvest type (pasture vs. meadow). While organic production system and interactions between the three management aspects play a minor role, the main effects of eco-scheme and harvest type considerably shape single services. Moreover, the eco-scheme ‘extensive management’ and the harvest type ‘pasture’ enhance plot-scale ecosystem-service multifunctionality, mostly through facilitating cultural services at the expense of provisioning services. These changes in ecosystem-service supply occur mainly via changes in land-use intensity, i.e., reduced fertilizer input and harvest frequency. In conclusion, diversifying grassland management where this is currently homogeneous across farms and landscapes depicts an important first step to improve landscape-scale multifunctionality for sustainable grassland systems. To meet societal ecosystem services demand, the three studied management aspects can be systematically combined to increase ecosystem services that are in short supply. Sustainable agricultural policies need to be practically assessed. Here, the authors assess how management practices affect ecosystem services in Swiss agricultural grasslands showing that organic farming has a lesser impact than the eco-scheme and the use as pasture or meadow.

Although originally primarily a system for functional biology, Arabidopsis thaliana has, owing to its broad geographical distribution and adaptation to diverse environments, developed into a powerful model in population genomics. Here we present chromosome-level genome assemblies of 69 accessions from a global species range. We found that genomic colinearity is very conserved, even among geographically and genetically distant accessions. Along chromosome arms, megabase-scale rearrangements are rare and typically present only in a single accession. This indicates that the karyotype is quasi-fixed and that rearrangements in chromosome arms are counter-selected. Centromeric regions display higher structural dynamics, and divergences in core centromeres account for most of the genome size variations. Pan-genome analyses uncovered 32,986 distinct gene families, 60% being present in all accessions and 40% appearing to be dispensable, including 18% private to a single accession, indicating unexplored genic diversity. These 69 new Arabidopsis thaliana genome assemblies will empower future genetic research. A pan-genome of Arabidopsis thaliana constructed using chromosome-level genome assemblies of 69 diverse accessions reveals a conserved genome structure throughout the global species range.

Sugarcane, the world’s most harvested crop by tonnage, has shaped global history, trade and geopolitics, and is currently responsible for 80% of sugar production worldwide1. While traditional sugarcane breeding methods have effectively generated cultivars adapted to new environments and pathogens, sugar yield improvements have recently plateaued2. The cessation of yield gains may be due to limited genetic diversity within breeding populations, long breeding cycles and the complexity of its genome, the latter preventing breeders from taking advantage of the recent explosion of whole-genome sequencing that has benefited many other crops. Thus, modern sugarcane hybrids are the last remaining major crop without a reference-quality genome. Here we take a major step towards advancing sugarcane biotechnology by generating a polyploid reference genome for R570, a typical modern cultivar derived from interspecific hybridization between the domesticated species (Saccharum officinarum) and the wild species (Saccharum spontaneum). In contrast to the existing single haplotype (‘monoploid’) representation of R570, our 8.7 billion base assembly contains a complete representation of unique DNA sequences across the approximately 12 chromosome copies in this polyploid genome. Using this highly contiguous genome assembly, we filled a previously unsized gap within an R570 physical genetic map to describe the likely causal genes underlying the single-copy Bru1 brown rust resistance locus. This polyploid genome assembly with fine-grain descriptions of genome architecture and molecular targets for biotechnology will help accelerate molecular and transgenic breeding and adaptation of sugarcane to future environmental conditions. We build a polyploid reference genome for hybrid sugarcane cultivar R570, improving on its current ‘mosaic monoploid’ representation, enabling fine-grain description of genome architecture and the exploration of candidate genes underlying the Bru1 brown rust resistance locus.

Pesticide risk reduction is a priority in European agricultural policies, but how to reach these targets remains an open question. Against this background, a novel approach for transforming pest management practices is currently gaining momentum in Europe: pesticide-free, non-organic production systems. These involve the non-use of pesticides in parts of crop rotations or entire crop rotations but do not comply with other organic farming regulations. Here we present insights into the first real-world examples of such systems, in Switzerland and Germany. In both countries, pesticide-free production was initiated jointly by farmers and downstream actors some years ago. This was followed by the launch of public support schemes in 2023. We discuss the functioning and impacts of these examples, as well as farmers’ adoption behaviour. Compared with organic production, the reviewed pesticide-free production schemes are more flexible and have lower adoption hurdles for farmers, as well as lower yield losses. These characteristics facilitate the large-scale adoption of pesticide-free production systems. Moreover, pesticide-free can become a clear-cut and simple production standard. Pesticide-free production can thus be a disruptive approach to create a tangible ‘third way’ between conventional and organic production. However, there are various adoption barriers and pesticide-free production would not currently be profitable without support in most cases. In this Perspective, Finger and Möhring discuss the emergence of pesticide-free crop production systems in Europe in the context of real-world examples and highlight the barriers to adoption of this cropping strategy.

Stripe rust is a devastating disease of wheat worldwide. Chinese wheat cultivar Lanhangxuan 121 (LHX121), selected from an advanced line L92-47 population that had been subjected to space mutation breeding displayed a consistently higher level of resistance to stipe rust than its parent in multiple field environments. The aim of this research was to establish the number and types of resistance genes in parental lines L92-47 and LHX121 using separate segregating populations. The first population developed from a cross between LHX121 and susceptible cultivar Xinong 822 comprised 278 F2:3 lines. The second validation population comprised 301 F2:3 lines from a cross between L92-47 and susceptible cultivar Xinong 979. Lines of two population were evaluated for stripe rust response at three sites during the 2018–2020 cropping season. Affymetrix 660 K SNP arrays were used to genotype the lines and parents. Inclusive composite interval mapping detected QTL QYrLHX.nwafu-2BS, QYrLHX.nwafu-3BS, and QYrLHX.nwafu-5BS for resistance in all three environments. Based on previous studies and pedigree information, QYrLHX.nwafu-2BS and QYrLHX.nwafu-3BS were likely to be Yr27 and Yr30 that are present in the L92-47 parent. QYrLHX.nwafu-5BS (YrL121) detected only in LHX121 was mapped to a 7.60 cM interval and explained 10.67–22.57% of the phenotypic variation. Compared to stripe rust resistance genes previously mapped to chromosome 5B, YrL121 might be a new adult plant resistance QTL. Furthermore, there were a number of variations signals using 35 K SNP array and differentially expressed genes using RNA-seq between L92-47 and LHX121 in the YrL121 region, indicating that they probably impair the presence and/or function of YrL121.

Genetic monitoring of populations currently attracts interest in the context of the Convention on Biological Diversity but needs long-term planning and investments. However, genetic diversity has been largely neglected in biodiversity monitoring, and when addressed, it is treated separately, detached from other conservation issues, such as habitat alteration due to climate change. We report an accounting of efforts to monitor population genetic diversity in Europe (genetic monitoring effort, GME), the evaluation of which can help guide future capacity building and collaboration towards areas most in need of expanded monitoring. Overlaying GME with areas where the ranges of selected species of conservation interest approach current and future climate niche limits helps identify whether GME coincides with anticipated climate change effects on biodiversity. Our analysis suggests that country area, financial resources and conservation policy influence GME, high values of which only partially match species’ joint patterns of limits to suitable climatic conditions. Populations at trailing climatic niche margins probably hold genetic diversity that is important for adaptation to changing climate. Our results illuminate the need in Europe for expanded investment in genetic monitoring across climate gradients occupied by focal species, a need arguably greatest in southeastern European countries. This need could be met in part by expanding the European Union’s Birds and Habitats Directives to fully address the conservation and monitoring of genetic diversity. Comparing data on genetic monitoring efforts across Europe with the distributions of areas at species’ climatic niche margins, the authors show that monitoring efforts should be expanded to populations at trailing niche margins to include genetic variation that may prove important for adaptation to ongoing climate warming.

Advancements in genome sequencing have facilitated whole-genome characterization of numerous plant species, providing an abundance of genotypic data for genomic analysis. Genomic selection and neural networks (NNs), particularly deep learning, have bee

The terms “New Genomic Techniques” (NGTs) or “Genome Editing” refer to various methods that allow finding, cleaving, and repairing specific sequences …

Large language models (LLMs), such as ChatGPT, have taken the world by storm. However, LLMs are not limited to human language and can be used to analy…

Applying deep learning in population genomics is challenging because of computational issues and lack of interpretable models. Here, we propose GenNet, a novel open-source deep learning framework for predicting phenotypes from genetic variants. In this framework, interpretable and memory-efficient neural network architectures are constructed by embedding biologically knowledge from public databases, resulting in neural networks that contain only biologically plausible connections. We applied the framework to seventeen phenotypes and found well-replicated genes such as HERC2 and OCA2 for hair and eye color, and novel genes such as ZNF773 and PCNT for schizophrenia. Additionally, the framework identified ubiquitin mediated proteolysis, endocrine system and viral infectious diseases as most predictive biological pathways for schizophrenia. GenNet is a freely available, end-to-end deep learning framework that allows researchers to develop and use interpretable neural networks to obtain novel insights into the genetic architecture of complex traits and diseases. van Hilten and colleagues present GenNet, a deep-learning framework for predicting phenotype from genetic data. This framework generates interpretable neural networks that provide insight into the genetic basis of complex traits and diseases.

Some of the AI-designed gene editors could be more versatile than those found in nature.

Plant nuclei exhibit near-infrared autofluorescence, which has the inherent capacity to be harnessed for dynamic analyses of cellular nuclei across diverse plant species. This autofluorescence

Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000–610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred ~30.5 thousand years ago, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica. Chromosome-level genome assemblies of allotetraploid Coffea arabica and representatives of its diploid progenitors, Coffea eugenioides and Coffea canephora, provide insights into Arabica’s diversification history.

Main conclusion A novel electroporation method for genome editing was performed using plant tissue samples by direct RNPs-introduction in carnation. Abstract Genome editing is becoming a very useful tool in plant breeding. In this study, a novel electroporation method was performed for genome editing using plant tissue samples. The objective was to create a flower color mutant using the pink-flowered carnation ‘Kane Ainou 1-go’. For this purpose, a ribonucleoprotein consisting of guide RNA and clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 9 (Cas9) was introduced into the stem tissue to induce mutations in the anthocyanidin synthase (ANS) gene, which is involved in anthocyanin biosynthesis. As the ANS of ‘Kane Ainou 1-go’ has not been previously isolated, we initially isolated the ANS gene from ‘Kane Ainou 1-go’ for characterization. Southern hybridization analysis confirmed that the ANS gene was present in the genome as a two-allele gene with a pair of homologous sequences (ANS-1 and 2); these sequences were used as the target for genome editing. Genome editing was performed by introducing #2_single-guide RNA into the stem tissue using the ribonucleoprotein. This molecule was used because it exhibited the highest efficiency in an analysis of cleavage activity against the target sequence in vitro. Cleaved amplified polymorphic sequence analysis of genomic DNA extracted from 85 regenerated individuals after genome editing was performed. The results indicated that mutations in the ANS gene may have been introduced into two lines. Cloning of the ANS gene in these two lines confirmed the introduction of a single nucleotide substitution mutation for ANS-1 in both lines, and a single amino acid substitution in one line. We discussed the possibility of color change by the amino acid substitution, and also the future applications of this technology.

Draft genomes generated from Oxford Nanopore Technologies (ONT) long reads are known to have a higher error rate. Although existing genome polishers can enhance their quality, the error rate (including mismatches, indels and switching errors between paternal and maternal haplotypes) can be significant. Here, we develop two polishers, hypo-short and hypo-hybrid to address this issue. Hypo-short utilizes Illumina short reads to polish an ONT-based draft assembly, resulting in a high-quality assembly with low error rates and switching errors. Expanding on this, hypo-hybrid incorporates ONT long reads to further refine the assembly into a diploid representation. Leveraging on hypo-hybrid, we have created a diploid genome assembly pipeline called hypo-assembler. Hypo-assembler automates the generation of highly accurate, contiguous and nearly complete diploid assemblies using ONT long reads, Illumina short reads and optionally Hi-C reads. Notably, our solution even allows for the production of telomere-to-telomere diploid genomes with additional manual steps. As a proof of concept, we successfully assembled a fully phased telomere-to-telomere diploid genome of HG00733, achieving a quality value exceeding 50. This work introduces two polishers for refining the draft genome generated from nanopore long reads, as well as an assembler pipeline for producing telomere-to-telomere diploid genome with low error rate.

Plant genome sequences catalogue genes and the genetic elements that regulate their expression. Such inventories further research aims as diverse as mapping the molecular basis of trait diversity in domesticated plants or inquiries into the origin of evolutionary innovations in flowering plants mill …

Polyploidization is a major driver of genome diversification and environmental adaptation. However, the merger of different genomes may result in genomic conflicts, raising a major question regarding how genetic diversity is interpreted and regulated to enable environmental plasticity. By analyzing the genome-wide binding of 191 trans-factors in allopolyploid wheat, we identified like heterochromatin protein 1 (LHP1) as a master regulator of subgenome-diversified genes. Transcriptomic and epigenomic analyses of LHP1 mutants reveal its role in buffering the expression of subgenome-diversified defense genes by controlling H3K27me3 homeostasis. Stripe rust infection releases latent subgenomic variations by eliminating H3K27me3-related repression. The simultaneous inactivation of LHP1 homoeologs by CRISPR–Cas9 confers robust stripe rust resistance in wheat seedlings. The conditional repression of subgenome-diversified defenses ensures developmental plasticity to external changes, while also promoting neutral-to-non-neutral selection transitions and adaptive evolution. These findings establish an LHP1-mediated buffering system at the intersection of genotypes, environments, and phenotypes in polyploid wheat. Manipulating the epigenetic buffering capacity offers a tool to harness cryptic subgenomic variations for crop improvement. The regulation of genetic diversity resulting from polyploidization and its impact on environmental adaptability remain unclear. Here, the authors show that LHP1-mediated epigenetic buffering of subgenome diversity and defense responses confers genome plasticity and adaptability in allopolyploid wheat.