35 research outputs found

    Genome analysis identified novel candidate genes for ascochyta blight resistance in chickpea using whole genome re-sequencing data

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    Ascochyta blight (AB) is a fungal disease that can significantly reduce chickpea production in Australia and other regions of the world. In this study, 69 chickpea genotypes were sequenced using whole genome re-sequencing (WGRS) methods. They included 48 Australian varieties differing in their resistance ranking to AB, 16 advanced breeding lines from the Australian chickpea breeding program, four landraces, and one accession representing the wild chickpea species Cicer reticulatum. More than 800,000 single nucleotide polymorphisms (SNPs) were identified. Population structure analysis revealed relatively narrow genetic diversity amongst recently released Australian varieties and two groups of varieties separated by the level of AB resistance. Several regions of the chickpea genome were under positive selection based on Tajimaā€™s D test. Both Fst genome- scan and genome-wide association studies (GWAS) identified a 100 kb region (AB4.1) on chromosome 4 that was significantly associated with AB resistance. The AB4.1 region co-located to a large QTL interval of 7 Mbāˆ¼30 Mb identified previously in three different mapping populations which were genotyped at relatively low density with SSR or SNP markers. The AB4.1 region was validated by GWAS in an additional collection of 132 advanced breeding lines from the Australian chickpea breeding program, genotyped with approximately 144,000 SNPs. The reduced level of nucleotide diversity and long extent of linkage disequilibrium also suggested the AB4.1 region may have gone through selective sweeps probably caused by selection of the AB resistance trait in breeding. In total, 12 predicted genes were located in the AB4.1 QTL region, including those annotated as: NBS-LRR receptor-like kinase, wall-associated kinase, zinc finger protein, and serine/threonine protein kinases. One significant SNP located in the conserved catalytic domain of a NBS-LRR receptor-like kinase led to amino acid substitution. Transcriptional analysis using qPCR showed that some predicted genes were significantly induced in resistant lines after inoculation compared to non-inoculated plants. This study demonstrates the power of combining WGRS data with relatively simple traits to rapidly develop ā€œfunctional makersā€ for marker-assisted selection and genomic selection.Yongle Li, Pradeep Ruperao, Jacqueline Batley, David Edwards, Jenny Davidson, Kristy Hobson and Tim Sutto

    The Progression in Developing Genomic Resources for Crop Improvement

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    Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis technique

    Trait associations in the pangenome of pigeon pea ( Cajanus cajan )

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    Pigeon pea (Cajanus cajan) is an important orphan crop mainly grown by smallholder farmers inIndia and Africa. Here, we present the first pigeon pea pangenome based on 89 accessionsmainly from India and the Philippines, showing that there is significant genetic diversity inPhilippine individuals that is not present in Indian individuals. Annotation of variable genessuggests that they are associated with self-fertilization and response to disease. We identified225 SNPs associated with nine agronomically important traits over three locations and twodifferent time points, with SNPs associated with genes for transcription factors and kinases.These results will lead the way to an improved pigeon pea breeding programme

    Genome-wide analysis of the calmodulin-binding transcription activator (CAMTA) gene family in Sesamum indicum L., and its role in abiotic stress tolerance traits

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    Calmodulin-binding transcription activator (CAMTA) is one of the key transcription factor families possessing calcium receptors (calmodulins, CaM). It modulates the expression levels of genes associated with ontogeny and various biotic and abiotic stress factors. The CAMTA family genes were known to be involved in different abiotic stress in several crop species. However, their functional relevance in sesame remains unexplored. To understand the role of CAMTA in stress tolerance in sesame, we performed a genome-wide analysis to identify the members of the SiCAMTA gene family. We have identified and reported here the five SiCAMTA genes localized on four chromosomes within the sesame genome. In silico analysis of the putative 2-kilobase (kb) promoter regions for these five SiCAMTA genes showed that phytohormone and stress response-related cis-elements were predominated in SiCAMTA2 and SiCAMTA5. Also, we studied its modulated expression levels, with special reference to drought and waterlogging stress. It revealed that the SiCAMTA5 and SiCAMTA2 genes were the most responsive to the studied stress factors. The target prediction and network analysis suggested that SiCAMTAs could bind the CGCG cis element in the target gene promoters and predicted 1202 SiCAMTA target genes in the sesame genome, including abiotic stress-responsive genes viz. LEA, PIP1ā€“2, PPO1, SAP, ARF17, and GA3OX1. These findings were validated using qPCR analysis for five CAMTA and 10 CAMTA target genes and establish a foundation for future functional research of SiCAMTA genes towards sesame stress tolerance

    Prioritization of candidate genes in "QTL-hotspot" region for drought tolerance in chickpea (Cicer arietinum L.)

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    A combination of two approaches, namely QTL analysis and gene enrichment analysis were used to identify candidate genes in the "QTL-hotspot" region for drought tolerance present on the Ca4 pseudomolecule in chickpea. In the first approach, a high-density bin map was developed using 53,223 single nucleotide polymorphisms (SNPs) identified in the recombinant inbred line (RIL) population of ICC 4958 (drought tolerant) and ICC 1882 (drought sensitive) cross. QTL analysis using recombination bins as markers along with the phenotyping data for 17 drought tolerance related traits obtained over 1-5 seasons and 1-5 locations split the "QTL-hotspot" region into two subregions namely "QTL-hotspot_a" (15 genes) and "QTL-hotspot_b" (11 genes). In the second approach, gene enrichment analysis using significant marker trait associations based on SNPs from the Ca4 pseudomolecule with the above mentioned phenotyping data, and the candidate genes from the refined "QTL-hotspot" region showed enrichment for 23 genes. Twelve genes were found common in both approaches. Functional validation using quantitative real-time PCR (qRT-PCR) indicated four promising candidate genes having functional implications on the effect of "QTL-hotspot" for drought tolerance in chickpea.Sandip M Kale, Deepa Jaganathan, Pradeep Ruperao, Charles Chen, Ramu Punna, Himabindu Kudapa, Mahendar Thudi, Manish Roorkiwal, Mohan AVSK Katta, Dadakhalandar Doddamani, Vanika Garg, P B Kavi Kishor, Pooran M Gaur, Henry T Nguyen, Jacqueline Batley, David Edwards, Tim Sutton and Rajeev K Varshne

    Double-digest restriction-associated DNA sequencing-based genotyping and its applications in sesame germplasm management

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    Sesame (Sesamum indicum L.) is an ancient oilseed crop belonging to the family Pedaliaceae and a globally cultivated crop for its use as oil and food. In this study, 2496 sesame accessions, being conserved at the National Genebank of ICAR-National Bureau of Plant Genetic Resources (NBPGR), were genotyped using genomics-assisted double-digest restriction-associated DNA sequencing (ddRAD-seq) approach. A total of 64,910 filtered single-nucleotide polymorphisms (SNPs) were utilized to assess the genome-scale diversity. Applications of this genome-scale information (reduced representation using restriction enzymes) are demonstrated through the development of a molecular core collection (CC) representing maximal SNP diversity. This information is also applied in developing a mid-density panel (MDP) comprising 2515 hyper-variable SNPs, representing almost equally the genic and non-genic regions. The sesame CC comprising 384 accessions, a representative set of accessions with maximal diversity, was identified using multiple criteria such as k-mer (subsequence of length ā€œkā€ in a sequence read) diversity, observed heterozygosity, CoreHunter3, GenoCore, and genetic differentiation. The coreset constituted around 15% of the total accessions studied, and this small subset had captured >60% SNP diversity of the entire population. In the coreset, the admixture analysis shows reduced genetic complexity, increased nucleotide diversity (Ļ€), and is geographically distributed without any repetitiveness in the CC germplasm. Within the CC, India-originated accessions exhibit higher diversity (as expected based on the center of diversity concept), than those accessions that were procured from various other countries. The identified CC set and the MDP will be a valuable resource for genomics-assisted accelerated sesame improvement program

    Constructing improved chickpea genome assemblies using skimGBS

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    Chickpea (Cicer arietinum L.) is the second most important grain legume after soybean and plays an important role in food security. The application of genomics provides the potential to increase the productivity and resilience of this important crop. We have developed a novel strategy to assess and improve the chickpea reference genomes. The quality of both chickpea desi and kabuli draft genomes were assessed using sequence data from flow cytometry isolated chromosomes to identify misplaced contigs. Using SNPs derived from whole genome sequence data of ICC 4958 x PI 489777, and skim sequence-based genotyping of this population, we could validate and correct the draft assembly. In addition to placing the misplaced sequence regions into corresponding chromosome positions, most of the previously unplaced contig sequences have now been incorporated into the pseudomolecules of the improved version. The total chromosome sequence length has increased from 124.38 Mb and 347.24 Mb to 375.06 Mb and 423.28 Mb for the desi and kabuli genomes respectively. Both genomes have been re-annotated. A total of 33,473 genes from kabuli and 31,419 genes from desi were predicted. Both improved genomes are available at http://cicer.info

    Sorghum Pan-Genome Explores the Functional Utility for Genomic-Assisted Breeding to Accelerate the Genetic Gain

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    Sorghum (Sorghum bicolor L.) is a staple food crops in the arid and rainfed production ecologies. Sorghum plays a critical role in resilient farming and is projected as a smart crop to overcome the food and nutritional insecurity in the developing world. The development and characterisation of the sorghum pan-genome will provide insight into genome diversity and functionality, supporting sorghum improvement. We built a sorghum pan-genome using reference genomes as well as 354 genetically diverse sorghum accessions belonging to different races. We explored the structural and functional characteristics of the pan-genome and explain its utility in supporting genetic gain. The newly-developed pan-genome has a total of 35,719 genes, a core genome of 16,821 genes and an average of 32,795 genes in each cultivar. The variable genes are enriched with environment responsive genes and classify the sorghum accessions according to their race.We show that 53%of genes display presence-absence variation, and some of these variable genes are predicted to be functionally associated with drought adaptation traits. Using more than two million SNPs from the pan-genome, association analysis identified 398 SNPs significantly associated with important agronomic traits, of which, 92 were in genes. Drought gene expression analysis identified 1,788 genes that are functionally linked to different conditions, of which 79 were absent from the reference genome assembly. This study provides comprehensive genomic diversity resources in sorghum which can be used in genome assisted crop improvement

    Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources

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    Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs

    Exploring the sorghum race level diversity utilizing 272 sorghum accessions genomic resources

    Get PDF
    Due to evolutionary divergence, sorghum race populations exhibit significant genetic and morphological variation. A k-mer-based sorghum race sequence comparison identified the conserved k-mers of all 272 accessions from sorghum and the race-specific genetic signatures identified the gene variability in 10,321 genes (PAVs). To understand sorghum race structure, diversity and domestication, a deep learning-based variant calling approach was employed in a set of genotypic data derived from a diverse panel of 272 sorghum accessions. The data resulted in 1.7 million high-quality genome-wide SNPs and identified selective signature (both positive and negative) regions through a genome-wide scan with different (iHS and XP-EHH) statistical methods. We discovered 2,370 genes associated with selection signatures including 179 selective sweep regions distributed over 10 chromosomes. Co-localization of these regions undergoing selective pressure with previously reported QTLs and genes revealed that the signatures of selection could be related to the domestication of important agronomic traits such as biomass and plant height. The developed k-mer signatures will be useful in the future to identify the sorghum race and for trait and SNP markers for assisting in plant breeding programs
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