Dissecting new genetic components of salinity tolerance in two-row spring barley at the vegetative and reproductive stages

Soil salinity imposes an agricultural and economic burden that may be alleviated by identifying the components of salinity tolerance in barley, a major crop and the most salt tolerant cereal. To improve our understanding of these components, we evaluated a diversity panel of 377 two-row spring barley cultivars during both the vegetative, in a controlled environment, and the reproductive stages, in the field. In the controlled environment, a high-throughput phenotyping platform was used to assess the growth-related traits under both control and saline conditions. In the field, the agronomic traits were measured from plots irrigated with either fresh or saline water. Association mapping for the different components of salinity tolerance enabled us to detect previously known associations, such as HvHKT1;5. Using an "interaction model", which took into account the interaction between treatment (control and salt) and genetic markers, we identified several loci associated with yield components related to salinity tolerance. We also observed that the two developmental stages did not share genetic regions associated with the components of salinity tolerance, suggesting that different mechanisms play distinct roles throughout the barley life cycle. Our association analysis revealed that genetically defined regions containing known flowering genes (Vrn-H3, Vrn-H1, and HvNAM-1) were responsive to salt stress. We identified a salt-responsive locus (7H, 128.35 cM) that was associated with grain number per ear, and suggest a gene encoding a vacuolar H+-translocating pyrophosphatase, HVP1, as a candidate. We also found a new QTL on chromosome 3H (139.22 cM), which was significant for ear number per plant, and a locus on chromosome 2H (141.87 cM), previously identified using a nested association mapping population, which associated with a yield component and interacted with salinity stress. Our study is the first to evaluate a barley diversity panel for salinity stress under both controlled and field conditions, allowing us to identify contributions from new components of salinity tolerance which could be used for marker-assisted selection when breeding for marginal and saline regions

The Genome Sequence of the Wild Tomato Solanum pimpinellifolium Provides Insights Into Salinity Tolerance

Solanum pimpinellifolium, a wild relative of cultivated tomato, offers a wealth of breeding potential for desirable traits such as tolerance to abiotic and biotic stresses. Here, we report the genome assembly and annotation of S. pimpinellifolium ‘LA0480.’ Moreover, we present phenotypic data from one field experiment that demonstrate a greater salinity tolerance for fruit- and yield-related traits in S. pimpinellifolium compared with cultivated tomato. The ‘LA0480’ genome assembly size (811 Mb) and the number of annotated genes (25,970) are within the range observed for other sequenced tomato species. We developed and utilized the Dragon Eukaryotic Analyses Platform (DEAP) to functionally annotate the ‘LA0480’ protein-coding genes. Additionally, we used DEAP to compare protein function between S. pimpinellifolium and cultivated tomato. Our data suggest enrichment in genes involved in biotic and abiotic stress responses. To understand the genomic basis for these differences in S. pimpinellifolium and S. lycopersicum, we analyzed 15 genes that have previously been shown to mediate salinity tolerance in plants. We show that S. pimpinellifolium has a higher copy number of the inositol-3-phosphate synthase and phosphatase genes, which are both key enzymes in the production of inositol and its derivatives. Moreover, our analysis indicates that changes occurring in the inositol phosphate pathway may contribute to the observed higher salinity tolerance in ‘LA0480.’ Altogether, our work provides essential resources to understand and unlock the genetic and breeding potential of S. pimpinellifolium, and to discover the genomic basis underlying its environmental robustness

Population genomics and haplotype analysis in spelt and bread wheat identifies a gene regulating glume color

The cloning of agriculturally important genes is often complicated by haplotype variation across crop cultivars. Access to pan-genome information greatly facilitates the assessment of structural variations and rapid candidate gene identification. Here, we identified the red glume 1 (Rg-B1) gene using association genetics and haplotype analyses in ten reference grade wheat genomes. Glume color is an important trait to characterize wheat cultivars. Red glumes are frequent among Central European spelt, a dominant wheat subspecies in Europe before the 20th century. We used genotyping-by-sequencing to characterize a global diversity panel of 267 spelt accessions, which provided evidence for two independent introductions of spelt into Europe. A single region at the Rg-B1 locus on chromosome 1BS was associated with glume color in the diversity panel. Haplotype comparisons across ten high-quality wheat genomes revealed a MYB transcription factor as candidate gene. We found extensive haplotype variation across the ten cultivars, with a particular group of MYB alleles that was conserved in red glume wheat cultivars. Genetic mapping and transient infiltration experiments allowed us to validate this particular MYB transcription factor variants. Our study demonstrates the value of multiple high-quality genomes to rapidly resolve copy number and haplotype variations in regions controlling agriculturally important traits

MVAPP – Multivariate analysis application for streamlined data analysis and curation

The revised and peer-reviewed version of this paper was published Open Access in Plant Physiology on May 2019 - please cite > DOI: https://doi.org/10.1104/pp.19.00235<br><br>Modern phenotyping enables the measurement of many phenotypic traits simultaneously, yielding vast amounts of quantitative data that is hard to manage and analyze. This type of data, when adequately examined, could reveal genotype-to-phenotype relationships and meaningful relationships between individual measured traits. Efficient data mining is currently challenging for experimental biologists, as many researchers are limited by their ability to curate, integrate and explore these complex outputs. Additionally, data transparency, accessibility and reproducibility have become important considerations for scientific publication. Thus, the need for a streamlined pipeline for curating phenotypic data is now more pressing than in the past. To address that need, we developed an open-source online platform for multivariate analysis, MVApp, which allows interactive data curation, in-depth data analysis and customized visualization. MVApp was developed in R using the Shiny framework, combining several functional R modules into a comprehensive toolkit that can be used without any prior knowledge of R, programming or advanced statistics. MVApp aims to enhance data transparency, standardize and facilitate phenotypic data curation and increase statistical literacy among the scientific community. Given that contributions from users in this open-source environment is encouraged, MVApp can be continuously updated and expanded to facilitate the analysis of high-throughput phenotyping outputs

MVApp - poster

The poster representing some analyses available on the MVApp platform - http://mvapp.kaust.edu.sa/MVApp. The paper describing the MVApp in more detail is available in pre-print as "Julkowska, Magdalena; Saade, Stephanie; Agarwal, Gaurav; Gao, Ge; Pailles, Yveline; Morton, Mitchell; Awlia, Mariam; Tester, Mark (2018): MVAPP – Multivariate analysis application for streamlined data analysis and curation. figshare. Paper. doi: <a href="https://doi.org/10.6084/m9.figshare.6291461.v1">https://doi.org/10.6084/m9.figshare.6291461.v1</a>

Fonio millet genome unlocks African orphan crop diversity for agriculture in a changing climate

Sustainable food production in the context of climate change necessitates diversification of agriculture and a more efficient utilization of plant genetic resources. Fonio millet (Digitaria exilis) is an orphan African cereal crop with a great potential for dryland agriculture. Here, we establish high-quality genomic resources to facilitate fonio improvement through molecular breeding. These include a chromosome-scale reference assembly and deep re-sequencing of 183 cultivated and wild Digitaria accessions, enabling insights into genetic diversity, population structure, and domestication. Fonio diversity is shaped by climatic, geographic, and ethnolinguistic factors. Two genes associated with seed size and shattering showed signatures of selection. Most known domestication genes from other cereal models however have not experienced strong selection in fonio, providing direct targets to rapidly improve this crop for agriculture in hot and dry environments