Genomic resources in plant breeding for sustainable agriculture.

Climate change during the last 40 years has had a serious impact on agriculture and threatens global food and nutritional security. From over half a million plant species, cereals and legumes are the most important for food and nutritional security. Although systematic plant breeding has a relatively short history, conventional breeding coupled with advances in technology and crop management strategies has increased crop yields by 56 % globally between 1965-85, referred to as the Green Revolution. Nevertheless, increased demand for food, feed, fiber, and fuel necessitates the need to break existing yield barriers in many crop plants. In the first decade of the 21st century we witnessed rapid discovery, transformative technological development and declining costs of genomics technologies. In the second decade, the field turned towards making sense of the vast amount of genomic information and subsequently moved towards accurately predicting gene-to-phenotype associations and tailoring plants for climate resilience and global food security. In this review we focus on genomic resources, genome and germplasm sequencing, sequencing-based trait mapping, and genomics-assisted breeding approaches aimed at developing biotic stress resistant, abiotic stress tolerant and high nutrition varieties in six major cereals (rice, maize, wheat, barley, sorghum and pearl millet), and six major legumes (soybean, groundnut, cowpea, common bean, chickpea and pigeonpea). We further provide a perspective and way forward to use genomic breeding approaches including marker-assisted selection, marker-assisted backcrossing, haplotype based breeding and genomic prediction approaches coupled with machine learning and artificial intelligence, to speed breeding approaches. The overall goal is to accelerate genetic gains and deliver climate resilient and high nutrition crop varieties for sustainable agriculture.

Assessment and site-specific manipulation of DNA (hydroxy-)methylation during mouse corticogenesis.

Dynamic changes in DNA (hydroxy-)methylation are fundamental for stem cell differentiation. However, the signature of these epigenetic marks in specific cell types during corticogenesis is unknown. Moreover, site-specific manipulation of cytosine modifications is needed to reveal the significance and function of these changes. Here, we report the first assessment of (hydroxy-)methylation in neural stem cells, neurogenic progenitors, and newborn neurons during mammalian corticogenesis. We found that gain in hydroxymethylation and loss in methylation occur sequentially at specific cellular transitions during neurogenic commitment. We also found that these changes predominantly occur within enhancers of neurogenic genes up-regulated during neurogenesis and target of pioneer transcription factors. We further optimized the use of dCas9-Tet1 manipulation of (hydroxy-)methylation, locus-specifically, in vivo, showing the biological relevance of our observations for Dchs1, a regulator of corticogenesis involved in developmental malformations and cognitive impairment. Together, our data reveal the dynamics of cytosine modifications in lineage-related cell types, whereby methylation is reduced and hydroxymethylation gained during the neurogenic lineage concurrently with up-regulation of pioneer transcription factors and activation of enhancers for neurogenic genes.

Development of a D genome specific marker resource for diploid and hexaploid wheat.

BACKGROUND: Mapping and map-based cloning of genes that control agriculturally and economically important traits remain great challenges for plants with complex highly repetitive genomes such as those within the grass tribe, Triticeae. Mapping limitations in the Triticeae are primarily due to low frequencies of polymorphic gene markers and poor genetic recombination in certain genetic regions. Although the abundance of repetitive sequence may pose common problems in genome analysis and sequence assembly of large and complex genomes, they provide repeat junction markers with random and unbiased distribution throughout chromosomes. Hence, development of a high-throughput mapping technology that combine both gene-based and repeat junction-based markers is needed to generate maps that have better coverage of the entire genome. RESULTS: In this study, the available genomics resource of the diploid Aegilop tauschii, the D genome donor of bread wheat, were used to develop genome specific markers that can be applied for mapping in modern hexaploid wheat. A NimbleGen array containing both gene-based and repeat junction probe sequences derived from Ae. tauschii was developed and used to map the Chinese Spring nullisomic-tetrasomic lines and deletion bin lines of the D genome chromosomes. Based on these mapping data, we have now anchored 5,171 repeat junction probes and 10,892 gene probes, corresponding to 5,070 gene markers, to the delineated deletion bins of the D genome. The order of the gene-based markers within the deletion bins of the Chinese Spring can be inferred based on their positions on the Ae. tauschii genetic map. Analysis of the probe sequences against the Chinese Spring chromosome sequence assembly database facilitated mapping of the NimbleGen probes to the sequence contigs and allowed assignment or ordering of these sequence contigs within the deletion bins. The accumulated length of anchored sequence contigs is about 155 Mb, representing ~ 3.2 % of the D genome. A specific database was developed to allow user to search or BLAST against the probe sequence information and to directly download PCR primers for mapping specific genetic loci. CONCLUSIONS: In bread wheat, aneuploid stocks have been extensively used to assign markers linked with genes/traits to chromosomes, chromosome arms, and their specific bins. Through this study, we added thousands of markers to the existing wheat chromosome bin map, representing a significant step forward in providing a resource to navigate the wheat genome. The database website ( http://probes.pw.usda.gov/ATRJM/ ) provides easy access and efficient utilization of the data. The resources developed herein can aid map-based cloning of traits of interest and the sequencing of the D genome of hexaploid wheat.