Elucidating the genetic basis of biomass accumulation and radiation use efficiency in spring wheat and its role in yield potential

One of the major challenges for plant scientists is increasing wheat (Triticum aestivum) yield potential (YP). A significant bottleneck for increasing YP is achieving increased biomass through optimization of radiation use efficiency (RUE) along the crop cycle. Exotic material such as landraces and synthetic wheat has been incorporated into breeding programmes in an attempt to alleviate this; however, their contribution to YP is still unclear. To understand the genetic basis of biomass accumulation and RUE, we applied genome‐wide association study (GWAS) to a panel of 150 elite spring wheat genotypes including many landrace and synthetically derived lines. The panel was evaluated for 31 traits over 2 years under optimal growing conditions and genotyped using the 35K wheat breeders array. Marker‐trait association identified 94 SNPs significantly associated with yield, agronomic and phenology‐related traits along with RUE and final biomass (BM_PM) at various growth stages that explained 7%–17% of phenotypic variation. Common SNP markers were identified for grain yield, BM_PM and RUE on chromosomes 5A and 7A. Additionally, landrace and synthetic derivative lines showed higher thousand grain weight (TGW), BM_PM and RUE but lower grain number (GM2) and harvest index (HI). Our work demonstrates the use of exotic material as a valuable resource to increase YP. It also provides markers for use in marker‐assisted breeding to systematically increase BM_PM, RUE and TGW and avoid the TGW/GM2 and BM_PM/HI trade‐off. Thus, achieving greater genetic gains in elite germplasm while also highlighting genomic regions and candidate genes for further study.     

Rapid identification and interpretation of gene–environment associations using the new R.SamBada landscape genomics pipeline

sam βada is a genome–environment association software, designed to search for signatures of local adaptation. However, pre‐ and postprocessing of data can be labour‐intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r ‐package providing a pipeline for landscape genomic analysis based on sam βada , spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).     

Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis

Maize (Zea mays mays) oil is a rich source of polyunsaturated fatty acids (FAs) and energy, making it a valuable resource for human food, animal feed, and bio‐energy. Although this trait has been studied via conventional genome‐wide association study (GWAS), the single nucleotide polymorphism (SNP)‐trait associations generated by GWAS may miss the underlying associations when traits are based on many genes, each with small effects that can be overshadowed by genetic background and environmental variation. Detecting these SNPs statistically is also limited by the levels set for false discovery rate. A complementary pathways analysis that emphasizes the cumulative aspects of SNP‐trait associations, rather than just the significance of single SNPs, was performed to understand the balance of lipid metabolism, conversion, and catabolism in this study. This pathway analysis indicated that acyl‐lipid pathways, including biosynthesis of wax esters, sphingolipids, phospholipids and flavonoids, along with FA and triacylglycerol (TAG) biosynthesis, were important for increasing oil and FA content. The allelic variation found among the genes involved in many degradation pathways, and many biosynthesis pathways leading from FAs and carbon partitioning pathways, was critical for determining final FA content, changing FA ratios and, ultimately, to final oil content. The pathways and pathway networks identified in this study, and especially the acyl‐lipid associated pathways identified beyond what had been found with GWAS alone, provide a real opportunity to precisely and efficiently manipulate high‐oil maize genetic improvement.     

Genetic and genomic resources of sorghum to connect genotype with phenotype in contrasting environments

With the recent development of genomic resources and high‐throughput phenotyping platforms, the 21st century is primed for major breakthroughs in the discovery, understanding and utilization of plant genetic variation. Significant advances in agriculture remain at the forefront to increase crop production and quality to satisfy the global food demand in a changing climate all while reducing the environmental impacts of the world's food production. Sorghum, a resilient C₄ grain and grass important for food and energy production, is being extensively dissected genetically and phenomically to help connect the relationship between genetic and phenotypic variation. Unlike genetically modified crops such as corn or soybean, sorghum improvement has relied heavily on public research; thus, many of the genetic resources serve a dual purpose for both academic and commercial pursuits. Genetic and genomic resources not only provide the foundation to identify and understand the genes underlying variation, but also serve as novel sources of genetic and phenotypic diversity in plant breeding programs. To better disseminate the collective information of this community, we discuss: (i) the genomic resources of sorghum that are at the disposal of the research community; (ii) the suite of sorghum traits as potential targets for increasing productivity in contrasting environments; and (iii) the prospective approaches and technologies that will help to dissect the genotype–phenotype relationship as well as those that will apply foundational knowledge for sorghum improvement.     

Functional mapping of N deficiency‐induced response in wheat yield‐component traits by implementing high‐throughput phenotyping

As overfertilization leads to environmental concerns and the cost of N fertilizer increases, the issue of how to select crop cultivars that can produce high yields on N‐deficient soils has become crucially important. However, little information is known about the genetic mechanisms by which crops respond to environmental changes induced by N signaling. Here, we dissected the genetic architecture of N‐induced phenotypic plasticity in bread wheat (Triticum aestivum L.) by integrating functional mapping and semiautomatic high‐throughput phenotyping data of yield‐related canopy architecture. We identified a set of quantitative trait loci (QTLs) that determined the pattern and magnitude of how wheat cultivars responded to low N stress from normal N supply throughout the wheat life cycle. This analysis highlighted the phenological landscape of genetic effects exerted by individual QTLs, as well as their interactions with N‐induced signals and with canopy measurement angles. This information may shed light on our mechanistic understanding of plant adaptation and provide valuable information for the breeding of N‐deficiency tolerant wheat varieties.     

Genetic association with high‐resolution climate data reveals selection footprints in the genomes of barley landraces across the Iberian Peninsula

Landraces are local populations of crop plants adapted to a particular environment. Extant landraces are surviving genetic archives, keeping signatures of the selection processes experienced by them until settling in their current niches. This study intends to establish relationships between genetic diversity of barley (Hordeum vulgare L.) landraces collected in Spain and the climate of their collection sites. A high‐resolution climatic data set (5 × 5 km spatial, 1‐day temporal grid) was computed from over 2,000 temperature and 7,000 precipitation stations across peninsular Spain. This data set, spanning the period 1981–2010, was used to derive agroclimatic variables meaningful for cereal production at the collection sites of 135 barley landraces. Variables summarize temperature, precipitation, evapotranspiration, potential vernalization and frost probability at different times of the year and time scales (season and month). SNP genotyping of the landraces was carried out combining Illumina Infinium assays and genotyping‐by‐sequencing, yielding 9,920 biallelic markers (7,479 with position on the barley reference genome). The association of these SNPs with agroclimatic variables was analysed at two levels of genetic diversity, with and without taking into account population structure. The whole data sets and analysis pipelines are documented and available at https://eead-csic-compbio.github.io/barley-agroclimatic-association . We found differential adaptation of the germplasm groups identified to be dominated by reactions to cold temperature and late‐season frost occurrence, as well as to water availability. Several significant associations pointing at specific adaptations to agroclimatic features related to temperature and water availability were observed, and candidate genes underlying some of the main regions are proposed.     

粤东亚热带森林群落树种组成对苔藓植物分布的影响

为探究森林群落树种组成对苔藓植物分布的影响,利用多元统计方法研究粤东亚热带地区苔藓植物的组成和分布对林分类型的响应。根据森林乔木层的树种组成划分为翻白叶树(Pterospermum heterophyllum)、木荷(Schima superba)+米锥(Castanopsis carlesii)和米锥3种森林类型。结果表明,3种森林类型中苔类(liverworts)和藓类(mosses)植物群落组成特征总体上存在显著差异;双齿裂萼苔(Chiloscyphus latifolius)和细指苔(Kurzia gonyotricha)在3种类型林分中的重要值变化指示了苔类植物群落的差异。3种类型林分中,均以东亚拟鳞叶藓(Pseudotaxiphyllum pohliaecarpum)为优势种。不同林分中藓类植物种类组成主要表现为亚优种分布的不同。这表明森林群落树种组成作为重要的生物因子,对林内苔藓植物的分布和种类组成有重要影响。     

Predicting the success of an invader: Niche shift versus niche conservatism

Invasive species can encounter environments different from their source populations, which may trigger rapid adaptive changes after introduction (niche shift hypothesis). To test this hypothesis, we investigated whether postintroduction evolution is correlated with contrasting environmental conditions between the European invasive and source ranges in the Asian tiger mosquito Aedes albopictus. The comparison of environmental niches occupied in European and source population ranges revealed more than 96% overlap between invasive and source niches, supporting niche conservatism. However, we found evidence for postintroduction genetic evolution by reanalyzing a published ddRADseq genomic dataset from 90 European invasive populations using genotype–environment association (GEA) methods and generalized dissimilarity modeling (GDM). Three loci, among which a putative heat‐shock protein, exhibited significant allelic turnover along the gradient of winter precipitation that could be associated with ongoing range expansion. Wing morphometric traits weakly correlated with environmental gradients within Europe, but wing size differed between invasive and source populations located in different climatic areas. Niche similarities between source and invasive ranges might have facilitated the establishment of populations. Nonetheless, we found evidence for environmental‐induced adaptive changes after introduction. The ability to rapidly evolve observed in invasive populations (genetic shift) together with a large proportion of unfilled potential suitable areas (80%) pave the way to further spread of Ae. albopictus in Europe.