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The domestication of wild emmer wheat led to the selection of modern durum wheat, grown mainly for pasta production. We describe the 10.45 gigabase (Gb) assembly of the genome of durum wheat cultivar Svevo. The assembly enabled genome-wide genetic diversity analyses revealing the changes imposed by thousands of years of empirical selection and breeding. Regions exhibiting strong signatures of genetic divergence associated with domestication and breeding were widespread in the genome with several major diversity losses in the pericentromeric regions. A locus on chromosome 5B carries a gene encoding a metal transporter ( TdHMA3-B1 ) with a non-functional variant causing high accumulation of cadmium in grain. The high-cadmium allele, widespread among durum cultivars but undetected in wild emmer accessions, increased in frequency from domesticated emmer to modern durum wheat. The rapid cloning of TdHMA3-B1 rescues a wild beneficial allele and demonstrates the practical use of the Svevo genome for wheat improvement. Genome assembly of durum wheat cultivar Svevo enables genome-wide genetic diversity analyses highlighting modifications imposed by thousands of years of empirical selection and breeding.

Wheat (Triticum spp.) is one of the founder crops that likely drove the Neolithic transition to sedentary agrarian societies in the Fertile Crescent more than 10,000 years ago. Identifying genetic modifications underlying wheat’s domestication requires knowledge about the genome of its allo-tetraploid progenitor, wild emmer (T. turgidum ssp. dicoccoides). We report a 10.1-gigabase assembly of the 14 chromosomes of wild tetraploid wheat, as well as analyses of gene content, genome architecture, and genetic diversity. With this fully assembled polyploid wheat genome, we identified the causal mutations in Brittle Rachis 1 (TtBtr1) genes controlling shattering, a key domestication trait. A study of genomic diversity among wild and domesticated accessions revealed genomic regions bearing the signature of selection under domestication. This reference assembly will serve as a resource for accelerating the genome-assisted improvement of modern wheat varieties.

There is an increasing awareness that as a result of structural variation, a reference sequence representing a genome of a single individual is unable to capture all of the gene repertoire found in the species. A large number of genes affected by presence/absence and copy number variation suggest that it may contribute to phenotypic and agronomic trait diversity. Here we show by analysis of the Brassica oleracea pangenome that nearly 20% of genes are affected by presence/absence variation. Several genes displaying presence/absence variation are annotated with functions related to major agronomic traits, including disease resistance, flowering time, glucosinolate metabolism and vitamin biosynthesis. Brassica oleracea is a single species that includes diverse crops such as cabbage, broccoli and Brussels sprouts. Here, the authors identify genes not captured in existing B. oleracea reference genomes by the assembly of a pangenome and show variations in gene content that may be related to important agronomic traits

A comprehensive transcriptome assembly of chickpea has been developed using 134.95 million Illumina single-end reads, 7.12 million single-end FLX/454 reads and 139,214 Sanger expressed sequence tags (ESTs) from >17 genotypes. This hybrid transcriptome assembly, referred to as C icer a rietinum T ranscriptome A ssembly version 2 (CaTA v2, available at http://data.comparative-legumes.org/transcriptomes/cicar/lista_cicar-201201), comprising 46,369 transcript assembly contigs (TACs) has an N50 length of 1,726 bp and a maximum contig size of 15,644 bp. Putative functions were determined for 32,869 (70.8%) of the TACs and gene ontology assignments were determined for 21,471 (46.3%). The new transcriptome assembly was compared with the previously available chickpea transcriptome assemblies as well as to the chickpea genome. Comparative analysis of CaTA v2 against transcriptomes of three legumes - Medicago , soybean and common bean, resulted in 27,771 TACs common to all three legumes indicating strong conservation of genes across legumes. CaTA v2 was also used for identification of simple sequence repeats (SSRs) and intron spanning regions (ISRs) for developing molecular markers. ISRs were identified by aligning TACs to the Medicago genome, and their putative mapping positions at chromosomal level were identified using transcript map of chickpea. Primer pairs were designed for 4,990 ISRs, each representing a single contig for which predicted positions are inferred and distributed across eight linkage groups. A subset of randomly selected ISRs representing all eight chickpea linkage groups were validated on five chickpea genotypes and showed 20% polymorphism with average polymorphic information content (PIC) of 0.27. In summary, the hybrid transcriptome assembly developed and novel markers identified can be used for a variety of applications such as gene discovery, marker-trait association, diversity analysis etc., to advance genetics research and breeding applications in chickpea and other related legumes.

Endophytic bacteria, recognized as eco-friendly biofertilizers, have demonstrated the potential to enhance crop growth and yield. While the plant growth-promoting effects of endophytic bacteria have been extensively studied, the impact of weed endophytes remains less explored. In this study, we aimed to isolate endophytic bacteria from native weeds and assess their plant growth-promoting abilities in rice under varying chemical fertilization. The evaluation encompassed measurements of mineral phosphate and potash solubilization, as well as indole-3-acetic acid (IAA) production activity by the selected isolates. Two promising strains, tentatively identified as Alcaligenes faecalis (BTCP01) from Eleusine indica (Goose grass) and Metabacillus indicus (BTDR03) from Cynodon dactylon (Bermuda grass) based on 16S rRNA gene phylogeny, exhibited noteworthy phosphate and potassium solubilization activity, respectively. BTCP01 demonstrated superior phosphate solubilizing activity, while BTDR03 exhibited the highest potassium (K) solubilizing activity. Both isolates synthesized IAA in the presence of L-tryptophan, with the detection of nifH and ipdC genes in their genomes. Application of isolates BTCP01 and BTDR03 through root dipping and spraying at the flowering stage significantly enhanced the agronomic performance of rice variety CV. BRRI dhan29. Notably, combining both strains with 50% of recommended N, P, and K fertilizer doses led to a substantial increase in rice grain yields compared to control plants receiving 100% of recommended doses. Taken together, our results indicate that weed endophytic bacterial strains BTCP01 and BTDR03 hold promise as biofertilizers, potentially reducing the dependency on chemical fertilizers by up to 50%, thereby fostering sustainable rice production.

The Brassicaceae (Cruciferae) family, owing to its remarkable species, genetic, and physiological diversity as well as its significant economic potential, has become a model for polyploidy and evolutionary studies. Utilizing extensive transcriptome pyrosequencing of diverse taxa, we established a resolved phytogeny of a subset of crucifer species. We elucidated the frequency, age, and phylogenetic position of polyploidy and lineage separation events that have marked the evolutionary history of the Brassicaceae. Besides the well-known ancient α (47 million years ago [Mya]) and β (124 Mya) paleopolyploidy events, several species were shown to have undergone a further more recent (~7 to 12 Mya) round of genome multiplication. We identified eight whole-genome duplications corresponding to at least five independent neo/mesopolyploidy events. Although the Brassicaceae family evolved from other eudicots at the beginning of the Cenozoic era of the Earth (60 Mya), major diversification occurred only during the Neogene period (0 to 23 Mya). Remarkably, the widespread species divergence, major polyploidy, and lineage separation events during Brassicaceae evolution are clustered in time around epoch transitions characterized by prolonged unstable climatic conditions. The synchronized diversification of Brassicaceae species suggests that polyploid events may have conferred higher adaptability and increased tolerance toward the drastically changing global environment, thus facilitating species radiation.

The Poaceae family, commonly known as the grass family, encompasses a diverse group of crops that play an essential role in providing food, fodder, biofuels, environmental conservation, and cultural value for both human and environmental well-being. Crops in Poaceae family are deeply intertwined with human societies, economies, and ecosystems, making it one of the most significant plant families in the world. As the major reservoirs of essential nutrients, seed grain of these crops has garnered substantial attention from researchers. Understanding the molecular and genetic processes that controls seed formation, development and maturation can provide insights for improving crop yield, nutritional quality, and stress tolerance. The diversity in photosynthetic pathways between C3 and C4 plants introduces intriguing variations in their physiological and biochemical processes, potentially affecting seed development. In this review, we explore recent studies performed with omics technologies, such as genomics, transcriptomics, proteomics and metabolomics that shed light on the mechanisms underlying seed development in wheat and maize, as representatives of C3 and C4 plants respectively, providing insights into their unique adaptations and strategies for reproductive success.

The ascomycete, Sclerotinia sclerotiorum , has a broad host range and causes yield loss in dicotyledonous crops world wide. Genomic diversity was determined in a population of 127 isolates obtained from individual canola ( Brassica napus ) fields in western Canada. Genotyping with 39 simple sequence repeat (SSR) markers revealed each isolate was a unique haplotype. Analysis of molecular variance showed 97% was due to isolate and 3% due to geographical location. Testing of mycelium compatibility among 133 isolates identified clones of mutually compatible isolates with 86–95% similar SSR haplotype, whereas incompatible isolates were highly diverse. In the Province of Manitoba, 61% of isolates were compatible forming clones and stings of pairwise compatible isolates not described before. In contrast, only 35% of isolates were compatible in Alberta without forming clones and strings, while 39% were compatible in Saskatchewan with a single clone, but no strings. These difference can be explained by wetter growing seasons and more susceptible crop species in Manitoba favouring frequent mycelium interaction and more life cycles over time, which might also explain similar differences observed in other geographical areas and host crops. Analysis of linkage disequilibrium rejected random recombination, consistent with a self-fertile fungus, restricted outcrossing due to mycelium incompatibility, and only a single annual opportunity for genomic recombination during meiosis in the ascospore stage between non-sister chromatids in the rare event nuclei from different isolates come together. More probable sources of genomic diversity is slippage during DNA replication and point mutation affecting single nucleotides that accumulate and likely increase mycelium incompatibility in a population over time. A phylogenetic tree based on SSR haplotype grouped isolates into 17 sub-populations. Aggressiveness was tested by inoculating one isolate from each sub-population onto B . napus lines with quantitative resistance. Analysis of variance was significant for isolate, line, and isolate by line interaction. These isolates represent the genomic and pathogenic diversity in western Canada, and are suitable for resistance screening in canola breeding programs.

Genomic prediction is a promising technology for advancing both plant and animal breeding, with many different prediction models evaluated in the literature. It has been suggested that the ability of powerful nonlinear models, such as deep neural networks, to capture complex epistatic effects between markers offers advantages for genomic prediction. However, these methods tend not to outperform classical linear methods, leaving it an open question why this capacity to model nonlinear effects does not seem to result in better predictive capability. In this work, we propose the theory that, because of a previously described principle called shortcut learning, deep neural networks tend to base their predictions on overall genetic relatedness rather than on the effects of particular markers such as epistatic effects. Using several datasets of crop plants [lentil (Lens culinaris Medik.), wheat (Triticum aestivum L.), and Brassica carinata A. Braun], we demonstrate the network's indifference to the values of the markers by showing that the same network, provided with only the locations of matches between markers for two individuals, is able to perform prediction to the same level of accuracy. Core Ideas The capacity of deep neural networks does not match performance in genomic prediction. Deep neural networks are not disadvantaged when they cannot access values of the markers. Deep neural networks likely attend primarily to genetic relatedness, not marker effects.

Background: CRISPR/Cas9 gene editing has become a revolutionary technique for crop improvement as it can facilitate fast and efficient genetic changes without the retention of transgene components in the final plant line. Lack of robust bioinformatics tools to facilitate the design of highly specific functional guide RNAs (gRNAs) and prediction of off-target sites in wheat is currently an obstacle to effective application of CRISPR technology to wheat improvement. Description: We have developed a web-based bioinformatics tool to design specific gRNAs for genome editing and transcriptional regulation of gene expression in wheat. A collaborative study between the Broad Institute and Microsoft Research used large-scale empirical evidence to devise algorithms (Doech et al., 2016, Nature Biotechnology 34, 184–191) for predicting the on-target activity and off-target potential of CRISPR/SpCas9 (Streptococcus pyogenes Cas9). We applied these prediction models to determine on-target specificity and potential off-target activity for individual gRNAs targeting specific loci in the wheat genome. The genome-wide gRNA mappings and the corresponding Doench scores predictive of the on-target and off-target activities were used to create a gRNA database which was used as a data source for the web application termed WheatCRISPR. Conclusion: The WheatCRISPR tool allows researchers to browse all possible gRNAs targeting a gene or sequence of interest and select effective gRNAs based on their predicted high on-target and low off-target activity scores, as well as other characteristics such as position within the targeted gene. It is publicly available at https://crispr.bioinfo.nrc.ca/WheatCrispr/.