Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding.

Inversions, a type of chromosomal structural variation, significantly influence plant adaptation and gene functions by impacting gene expression and recombination rates. However, compared with other structural variations, their roles in functional biology and crop improvement remain largely unexplored. In this review, we highlight technological and methodological advancements that have allowed a comprehensive understanding of inversion variants through the pangenome framework and machine learning algorithms. Genome editing is an efficient method for inducing or reversing inversion mutations in plants, providing an effective mechanism to modify local recombination rates. Given the potential of inversions in crop breeding, we anticipate increasing attention on inversions from the scientific community in future research and breeding applications.

Different DNA repair pathways are involved in single-strand break-induced genomic changes in plants.

In nature, single-strand breaks (SSBs) in DNA occur more frequently (by orders of magnitude) than double-strand breaks (DSBs). SSBs induced by the CRISPR/Cas9 nickase at a distance of 50-100 bp on opposite strands are highly mutagenic, leading to insertions/deletions (InDels), with insertions mainly occurring as direct tandem duplications. As short tandem repeats are overrepresented in plant genomes, this mechanism seems to be important for genome evolution. We investigated the distance at which paired 5'-overhanging SSBs are mutagenic and which DNA repair pathways are essential for insertion formation in Arabidopsis thaliana. We were able to detect InDel formation up to a distance of 250 bp, although with much reduced efficiency. Surprisingly, the loss of the classical nonhomologous end joining (NHEJ) pathway factors KU70 or DNA ligase 4 completely abolished tandem repeat formation. The microhomology-mediated NHEJ factor POLQ was required only for patch-like insertions, which are well-known from DSB repair as templated insertions from ectopic sites. As SSBs can also be repaired using homology, we furthermore asked whether the classical homologous recombination (HR) pathway is involved in this process in plants. The fact that RAD54 is not required for homology-mediated SSB repair demonstrates that the mechanisms for DSB- and SSB-induced HR differ in plants.

The Chicken Pan-Genome Reveals Gene Content Variation and a Promoter Region Deletion in IGF2BP1 Affecting Body Size.

Domestication and breeding have reshaped the genomic architecture of chicken, but the retention and loss of genomic elements during these evolutionary processes remain unclear. We present the first chicken pan-genome constructed using 664 individuals, which identified an additional approximately 66.5-Mb sequences that are absent from the reference genome (GRCg6a). The constructed pan-genome encoded 20,491 predicated protein-coding genes, of which higher expression levels are observed in conserved genes relative to dispensable genes. Presence/absence variation (PAV) analyses demonstrated that gene PAV in chicken was shaped by selection, genetic drift, and hybridization. PAV-based genome-wide association studies identified numerous candidate mutations related to growth, carcass composition, meat quality, or physiological traits. Among them, a deletion in the promoter region of IGF2BP1 affecting chicken body size is reported, which is supported by functional studies and extra samples. This is the first time to report the causal variant of chicken body size quantitative trait locus located at chromosome 27 which was repeatedly reported. Therefore, the chicken pan-genome is a useful resource for biological discovery and breeding. It improves our understanding of chicken genome diversity and provides materials to unveil the evolution history of chicken domestication.

Modelling of gene loss propensity in the pangenomes of three Brassica species suggests different mechanisms between polyploids and diploids.

Plant genomes demonstrate significant presence/absence variation (PAV) within a species; however, the factors that lead to this variation have not been studied systematically in Brassica across diploids and polyploids. Here, we developed pangenomes of polyploid Brassica napus and its two diploid progenitor genomes B. rapa and B. oleracea to infer how PAV may differ between diploids and polyploids. Modelling of gene loss suggests that loss propensity is primarily associated with transposable elements in the diploids while in B. napus, gene loss propensity is associated with homoeologous recombination. We use these results to gain insights into the different causes of gene loss, both in diploids and following polyploidization, and pave the way for the application of machine learning methods to understanding the underlying biological and physical causes of gene presence/absence.

Progress in single-access information systems for wheat and rice crop improvement.

Improving productivity of the staple crops wheat and rice is essential to feed the growing global population, particularly in the context of a changing climate. However, current rates of yield gain are insufficient to support the predicted population growth. New approaches are required to accelerate the breeding process, and many of these are driven by the application of large-scale crop data. To leverage the substantial volumes and types of data that can be applied for precision breeding, the wheat and rice research communities are working towards the development of integrated systems to access and standardize the dispersed, heterogeneous available data. Here, we outline the initiatives of the International Wheat Information System (WheatIS) and the International Rice Informatics Consortium (IRIC) to establish Web-based single-access systems and data mining tools to make the available resources more accessible, drive discovery and accelerate the production of new crop varieties. We discuss the progress of WheatIS and IRIC towards unifying specialized wheat and rice databases and building custom software platforms to manage and interrogate these data. Single-access crop information systems will strengthen scientific collaboration, optimize the use of public research funds and help achieve the required yield gains in the two most important global food crops.

Genotype-Environment mismatch of kelp forests under climate change.

Climate change is increasingly impacting ecosystems globally. Understanding adaptive genetic diversity and whether it will keep pace with projected climatic change is necessary to assess species' vulnerability and design efficient mitigation strategies such as assisted adaptation. Kelp forests are the foundations of temperate reefs globally but are declining in many regions due to climate stress. A lack of knowledge of kelp's adaptive genetic diversity hinders assessment of vulnerability under extant and future climates. Using 4245 single nucleotide polymorphisms (SNPs), we characterized patterns of neutral and putative adaptive genetic diversity for the dominant kelp in the southern hemisphere (Ecklonia radiata) from ~1000 km of coastline off Western Australia. Strong population structure and isolation-by-distance was underpinned by significant signatures of selection related to temperature and light. Gradient forest analysis of temperature-linked SNPs under selection revealed a strong association with mean annual temperature range, suggesting adaptation to local thermal environments. Critically, modelling revealed that predicted climate-mediated temperature changes will probably result in high genomic vulnerability via a mismatch between current and future predicted genotype-environment relationships such that kelp forests off Western Australia will need to significantly adapt to keep pace with projected climate change. Proactive management techniques such as assisted adaptation to boost resilience may be required to secure the future of these kelp forests and the immense ecological and economic values they support.

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat.

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High-throughput SNP arrays, or 'SNP chips', can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop-breeding activities.

Linkage mapping and QTL analysis of flowering time using ddRAD sequencing with genotype error correction in Brassica napus.

BACKGROUND: Brassica napus is an important oilseed crop cultivated worldwide. During domestication and breeding of B. napus, flowering time has been a target of selection because of its substantial impact on yield. Here we use double digest restriction-site associated DNA sequencing (ddRAD) to investigate the genetic basis of flowering in B. napus. An F2 mapping population was derived from a cross between an early-flowering spring type and a late-flowering winter type. RESULTS: Flowering time in the mapping population differed by up to 25 days between individuals. High genotype error rates persisted after initial quality controls, as suggested by a genotype discordance of ~ 12% between biological sequencing replicates. After genotype error correction, a linkage map spanning 3981.31 cM and compromising 14,630 single nucleotide polymorphisms (SNPs) was constructed. A quantitative trait locus (QTL) on chromosome C2 was detected, covering eight flowering time genes including FLC. CONCLUSIONS: These findings demonstrate the effectiveness of the ddRAD approach to sample the B. napus genome. Our results also suggest that ddRAD genotype error rates can be higher than expected in F2 populations. Quality filtering and genotype correction and imputation can substantially reduce these error rates and allow effective linkage mapping and QTL analysis.

Genetic and signalling pathways of dry fruit size: targets for genome editing-based crop improvement.

Fruit is seed-bearing structures specific to angiosperm that form from the gynoecium after flowering. Fruit size is an important fitness character for plant evolution and an agronomical trait for crop domestication/improvement. Despite the functional and economic importance of fruit size, the underlying genes and mechanisms are poorly understood, especially for dry fruit types. Improving our understanding of the genomic basis for fruit size opens the potential to apply gene-editing technology such as CRISPR/Cas to modulate fruit size in a range of species. This review examines the genes involved in the regulation of fruit size and identifies their genetic/signalling pathways, including the phytohormones, transcription and elongation factors, ubiquitin-proteasome and microRNA pathways, G-protein and receptor kinases signalling, arabinogalactan and RNA-binding proteins. Interestingly, different plant taxa have conserved functions for various fruit size regulators, suggesting that common genome edits across species may have similar outcomes. Many fruit size regulators identified to date are pleiotropic and affect other organs such as seeds, flowers and leaves, indicating a coordinated regulation. The relationships between fruit size and fruit number/seed number per fruit/seed size, as well as future research questions, are also discussed.

BioNanoAnalyst: a visualisation tool to assess genome assembly quality using BioNano data.

BACKGROUND: Reference genome assemblies are valuable, as they provide insights into gene content, genetic evolution and domestication. The higher the quality of a reference genome assembly the more accurate the downstream analysis will be. During the last few years, major efforts have been made towards improving the quality of genome assemblies. However, erroneous and incomplete assemblies are still common. Complementary to DNA sequencing technologies, optical mapping has advanced genomic studies by facilitating the production of genome scaffolds and assessing structural variation. However, there are few tools available to comprehensively examine misassemblies in reference genome sequences using optical map data. RESULTS: We present BioNanoAnalyst, a software package to examine genome assemblies based on restriction endonuclease cut sites and optical map data. A graphical user interface (GUI) allows users to assess reference genome sequences on different computer platforms without the requirement of programming knowledge. The zoom function makes visualisation convenient, while a GFF3 format output file gives an option to directly visualise questionable assembly regions by location and nucleotides following import into a local genome browser. CONCLUSIONS: BioNanoAnalyst is a tool to identify misassemblies in a reference genome sequence using optical map data. With the reported information, users can rapidly identify assembly errors and correct them using other software tools, which could facilitate an accurate downstream analysis.

Genotyping-by-sequencing approaches to characterize crop genomes: choosing the right tool for the right application.

In the last decade, the revolution in sequencing technologies has deeply impacted crop genotyping practice. New methods allowing rapid, high-throughput genotyping of entire crop populations have proliferated and opened the door to wider use of molecular tools in plant breeding. These new genotyping-by-sequencing (GBS) methods include over a dozen reduced-representation sequencing (RRS) approaches and at least four whole-genome resequencing (WGR) approaches. The diversity of methods available, each often producing different types of data at different cost, can make selection of the best-suited method seem a daunting task. We review the most common genotyping methods used today and compare their suitability for linkage mapping, genomewide association studies (GWAS), marker-assisted and genomic selection and genome assembly and improvement in crops with various genome sizes and complexity. Furthermore, we give an outline of bioinformatics tools for analysis of genotyping data. WGR is well suited to genotyping biparental cross populations with complex, small- to moderate-sized genomes and provides the lowest cost per marker data point. RRS approaches differ in their suitability for various tasks, but demonstrate similar costs per marker data point. These approaches are generally better suited for de novo applications and more cost-effective when genotyping populations with large genomes or high heterozygosity. We expect that although RRS approaches will remain the most cost-effective for some time, WGR will become more widespread for crop genotyping as sequencing costs continue to decrease.

Towards CRISPR/Cas crops - bringing together genomics and genome editing.

Contents 682 I. 682 II. 683 III. 684 IV. 685 V. 685 VI. 688 VII. 690 VIII. 694 694 References 694 SUMMARY: With the rapid increase in the global population and the impact of climate change on agriculture, there is a need for crops with higher yields and greater tolerance to abiotic stress. However, traditional crop improvement via genetic recombination or random mutagenesis is a laborious process and cannot keep pace with increasing crop demand. Genome editing technologies such as clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (CRISPR/Cas) allow targeted modification of almost any crop genome sequence to generate novel variation and accelerate breeding efforts. We expect a gradual shift in crop improvement away from traditional breeding towards cycles of targeted genome editing. Crop improvement using genome editing is not constrained by limited existing variation or the requirement to select alleles over multiple breeding generations. However, current applications of crop genome editing are limited by the lack of complete reference genomes, the sparse knowledge of potential modification targets, and the unclear legal status of edited crops. We argue that overcoming technical and social barriers to the application of genome editing will allow this technology to produce a new generation of high-yielding, climate ready crops.

Cross-species modeling of plant genomes at single nucleotide resolution using a pre-trained DNA language model.

Understanding the function and fitness effects of diverse plant genomes requires transferable models. Language models (LMs) pre-trained on large-scale biological sequences can learn evolutionary conservation, thus expected to offer better cross-species prediction through fine-tuning on limited labeled data compared to supervised deep learning models. We introduce PlantCaduceus, a plant DNA LM based on the Caduceus and Mamba architectures, pre-trained on a carefully curated dataset consisting of 16 diverse Angiosperm genomes. Fine-tuning PlantCaduceus on limited labeled Arabidopsis data for four tasks involving transcription and translation modeling demonstrated high transferability to maize that diverged 160 million years ago, outperforming the best baseline model by 1.45-fold to 7.23-fold. PlantCaduceus also enables genome-wide deleterious mutation identification without multiple sequence alignment (MSA). PlantCaduceus demonstrated a threefold enrichment of rare alleles in prioritized deleterious mutations compared to MSA-based methods and matched state-of-the-art protein LMs. PlantCaduceus is a versatile pre-trained DNA LM expected to accelerate plant genomics and crop breeding applications.

Duck pan-genome reveals two transposon insertions caused bodyweight enlarging and white plumage phenotype formation during evolution.

Structural variations (SVs) are a major source of domestication and improvement traits. We present the first duck pan-genome constructed using five genome assemblies capturing ∼40.98 Mb new sequences. This pan-genome together with high-depth sequencing data (∼46.5×) identified 101,041 SVs, of which substantial proportions were derived from transposable element (TE) activity. Many TE-derived SVs anchoring in a gene body or regulatory region are linked to duck's domestication and improvement. By combining quantitative genetics with molecular experiments, we, for the first time, unraveled a 6945 bp Gypsy insertion as a functional mutation of the major gene IGF2BP1 associated with duck bodyweight. This Gypsy insertion, to our knowledge, explains the largest effect on bodyweight among avian species (27.61% of phenotypic variation). In addition, we also examined another 6634 bp Gypsy insertion in MITF intron, which triggers a novel transcript of MITF, thereby contributing to the development of white plumage. Our findings highlight the importance of using a pan-genome as a reference in genomics studies and illuminate the impact of transposons in trait formation and livestock breeding.

Clonal Lineage Tracing with Somatic Delivery of Recordable Barcodes Reveals Migration Histories of Metastatic Prostate Cancer.

The patterns by which primary tumors spread to metastatic sites remain poorly understood. Here, we define patterns of metastatic seeding in prostate cancer (PCa) using a novel injection-based mouse model - EvoCaP (Evolution in Cancer of the Prostate), featuring aggressive metastatic cancer to bone, liver, lungs, and lymph nodes. To define migration histories between primary and metastatic sites, we used our EvoTraceR pipeline to track distinct tumor clones containing recordable barcodes. We detected widespread intratumoral heterogeneity from the primary tumor in metastatic seeding, with few clonal populations (CPs) instigating most migration. Metastasis-to-metastasis seeding was uncommon, as most cells remained confined within the tissue. Migration patterns in our model were congruent with human PCa seeding topologies. Our findings support the view of metastatic PCa as a systemic disease driven by waves of aggressive clones expanding their niche, infrequently overcoming constraints that otherwise keep them confined in the primary or metastatic site.

Utility of AlphaMissense predictions in Asparagine Synthetase deficiency variant classification.

AlphaMissense is a recently developed method that is designed to classify missense variants into pathogenic, benign, or ambiguous categories across the entire human proteome. Asparagine Synthetase Deficiency (ASNSD) is a developmental disorder associated with severe symptoms, including congenital microcephaly, seizures, and premature death. Diagnosing ASNSD relies on identifying mutations in the asparagine synthetase (ASNS) gene through DNA sequencing and determining whether these variants are pathogenic or benign. Pathogenic ASNS variants are predicted to disrupt the protein's structure and/or function, leading to asparagine depletion within cells and inhibition of cell growth. AlphaMissense offers a promising solution for the rapid classification of ASNS variants established by DNA sequencing and provides a community resource of pathogenicity scores and classifications for newly diagnosed ASNSD patients. Here, we assessed AlphaMissense's utility in ASNSD by benchmarking it against known critical residues in ASNS and evaluating its performance against a list of previously reported ASNSD-associated variants. We also present a pipeline to calculate AlphaMissense scores for any protein in the UniProt database. AlphaMissense accurately attributed a high average pathogenicity score to known critical residues within the two ASNS active sites and the connecting intramolecular tunnel. The program successfully categorized 78.9% of known ASNSD-associated missense variants as pathogenic. The remaining variants were primarily labeled as ambiguous, with a smaller proportion classified as benign. This study underscores the potential role of AlphaMissense in classifying ASNS variants in suspected cases of ASNSD, potentially providing clarity to patients and their families grappling with ongoing diagnostic uncertainty.

Teosinte Pollen Drive guides maize diversification and domestication by RNAi.

Meiotic drivers subvert Mendelian expectations by manipulating reproductive development to bias their own transmission. Chromosomal drive typically functions in asymmetric female meiosis, while gene drive is normally postmeiotic and typically found in males. Using single molecule and single-pollen genome sequencing, we describe Teosinte Pollen Drive, an instance of gene drive in hybrids between maize (Zea mays ssp. mays) and teosinte mexicana (Zea mays ssp. mexicana), that depends on RNA interference (RNAi). 22nt small RNAs from a non-coding RNA hairpin in mexicana depend on Dicer-Like 2 (Dcl2) and target Teosinte Drive Responder 1 (Tdr1), which encodes a lipase required for pollen viability. Dcl2, Tdr1, and the hairpin are in tight pseudolinkage on chromosome 5, but only when transmitted through the male. Introgression of mexicana into early cultivated maize is thought to have been critical to its geographical dispersal throughout the Americas, and a tightly linked inversion in mexicana spans a major domestication sweep in modern maize. A survey of maize landraces and sympatric populations of teosinte mexicana reveals correlated patterns of admixture among unlinked genes required for RNAi on at least 4 chromosomes that are also subject to gene drive in pollen from synthetic hybrids. Teosinte Pollen Drive likely played a major role in maize domestication and diversification, and offers an explanation for the widespread abundance of "self" small RNAs in the germlines of plants and animals.

Long-Read Sequencing Reveals Rapid Evolution of Immunity- and Cancer-Related Genes in Bats.

Bats are exceptional among mammals for their powered flight, extended lifespans, and robust immune systems and therefore have been of particular interest in comparative genomics. Using the Oxford Nanopore Technologies long-read platform, we sequenced the genomes of two bat species with key phylogenetic positions, the Jamaican fruit bat (Artibeus jamaicensis) and the Mesoamerican mustached bat (Pteronotus mesoamericanus), and carried out a comprehensive comparative genomic analysis with a diverse collection of bats and other mammals. The high-quality, long-read genome assemblies revealed a contraction of interferon (IFN)-α at the immunity-related type I IFN locus in bats, resulting in a shift in relative IFN-ω and IFN-α copy numbers. Contradicting previous hypotheses of constitutive expression of IFN-α being a feature of the bat immune system, three bat species lost all IFN-α genes. This shift to IFN-ω could contribute to the increased viral tolerance that has made bats a common reservoir for viruses that can be transmitted to humans. Antiviral genes stimulated by type I IFNs also showed evidence of rapid evolution, including a lineage-specific duplication of IFN-induced transmembrane genes and positive selection in IFIT2. In addition, 33 tumor suppressors and 6 DNA-repair genes showed signs of positive selection, perhaps contributing to increased longevity and reduced cancer rates in bats. The robust immune systems of bats rely on both bat-wide and lineage-specific evolution in the immune gene repertoire, suggesting diverse immune strategies. Our study provides new genomic resources for bats and sheds new light on the extraordinary molecular evolution in this critically important group of mammals.

A multiple alignment workflow shows the effect of repeat masking and parameter tuning on alignment in plants.

Alignments of multiple genomes are a cornerstone of comparative genomics, but generating these alignments remains technically challenging and often impractical. We developed the msa_pipeline workflow (https://bitbucket.org/bucklerlab/msa_pipeline) to allow practical and sensitive multiple alignment of diverged plant genomes and calculation of conservation scores with minimal user inputs. As high repeat content and genomic divergence are substantial challenges in plant genome alignment, we also explored the effect of different masking approaches and parameters of the LAST aligner using genome assemblies of 33 grass species. Compared with conventional masking with RepeatMasker, a masking approach based on k-mers (nucleotide sequences of k length) increased the alignment rate of coding sequence and noncoding functional regions by 25 and 14%, respectively. We further found that default alignment parameters generally perform well, but parameter tuning can increase the alignment rate for noncoding functional regions by over 52% compared with default LAST settings. Finally, by increasing alignment sensitivity from the default baseline, parameter tuning can increase the number of noncoding sites that can be scored for conservation by over 76%. Overall, tuning of masking and alignment parameters can generate optimized multiple alignments to drive biological discovery in plants.