Patterns of molecular and phenotypic diversity in pearl millet [Pennisetum glaucum (L.) R. Br.] from West and Central Africa and their relation to geographical and environmental parameters

<p>Abstract</p> <p>Background</p> <p>The distribution area of pearl millet in West and Central Africa (WCA) harbours a wide range of climatic and environmental conditions as well as diverse farmer preferences and pearl millet utilization habits which have the potential to lead to local adaptation and thereby to population structure. The objectives of our research were to (i) assess the geographical distribution of genetic diversity in pearl millet inbreds derived from landraces, (ii) assess the population structure of pearl millet from WCA, and (iii) identify those geographical parameters and environmental factors from the location at which landraces were sampled, as well as those phenotypic traits that may have affected or led to this population structure. Our study was based on a set of 145 inbred lines derived from 122 different pearl millet landraces from WCA.</p> <p>Results</p> <p>Five sub-groups were detected within the entire germplasm set by STRUCTURE. We observed that the phenotypic traits flowering time, relative response to photoperiod, and panicle length were significantly associated with population structure but not the environmental factors which are expected to influence these traits in natural populations such as latitude, temperature, or precipitation.</p> <p>Conclusions</p> <p>Our results suggested that for pearl millet natural selection is compared to artificial selection less important in shaping populations.</p

Natural variation in Arabidopsis shoot branching plasticity in response to nitrate supply affects fitness.

The capacity of organisms to tune their development in response to environmental cues is pervasive in nature. This phenotypic plasticity is particularly striking in plants, enabled by their modular and continuous development. A good example is the activation of lateral shoot branches in Arabidopsis, which develop from axillary meristems at the base of leaves. The activity and elongation of lateral shoots depends on the integration of many signals both external (e.g. light, nutrient supply) and internal (e.g. the phytohormones auxin, strigolactone and cytokinin). Here, we characterise natural variation in plasticity of shoot branching in response to nitrate supply using two diverse panels of Arabidopsis lines. We find extensive variation in nitrate sensitivity across these lines, suggesting a genetic basis for variation in branching plasticity. High plasticity is associated with extreme branching phenotypes such that lines with the most branches on high nitrate have the fewest under nitrate deficient conditions. Conversely, low plasticity is associated with a constitutively moderate level of branching. Furthermore, variation in plasticity is associated with alternative life histories with the low plasticity lines flowering significantly earlier than high plasticity lines. In Arabidopsis, branching is highly correlated with fruit yield, and thus low plasticity lines produce more fruit than high plasticity lines under nitrate deficient conditions, whereas highly plastic lines produce more fruit under high nitrate conditions. Low and high plasticity, associated with early and late flowering respectively, can therefore be interpreted alternative escape vs mitigate strategies to low N environments. The genetic architecture of these traits appears to be highly complex, with only a small proportion of the estimated genetic variance detected in association mapping

Genetic dissection of photoperiod response based on GWAS of pre-anthesis phase duration in spring barley

Heading time is a complex trait, and natural variation in photoperiod responses is a major factor controlling time to heading, adaptation and grain yield. In barley, previous heading time studies have been mainly conducted under field conditions to measure total days to heading. We followed a novel approach and studied the natural variation of time to heading in a world-wide spring barley collection (218 accessions), comprising of 95 photoperiod-sensitive (Ppd-H1) and 123 accessions with reduced photoperiod sensitivity (ppd-H1) to long-day (LD) through dissecting pre-anthesis development into four major stages and sub-phases. The study was conducted under greenhouse (GH) conditions (LD; 16/8 h; ∼20/∼16°C day/night). Genotyping was performed using a genome-wide high density 9K single nucleotide polymorphisms (SNPs) chip which assayed 7842 SNPs. We used the barley physical map to identify candidate genes underlying genome-wide association scans (GWAS). GWAS for pre-anthesis stages/sub-phases in each photoperiod group provided great power for partitioning genetic effects on floral initiation and heading time. In addition to major genes known to regulate heading time under field conditions, several novel QTL with medium to high effects, including new QTL having major effects on developmental stages/sub-phases were found to be associated in this study. For example, highly associated SNPs tagged the physical regions around HvCO1 (barley CONSTANS1) and BFL (BARLEY FLORICAULA/LEAFY) genes. Based upon our GWAS analysis, we propose a new genetic network model for each photoperiod group, which includes several newly identified genes, such as several HvCO-like genes, belonging to different heading time pathways in barley

Shifting the limits in wheat research and breeding using a fully annotated reference genome

Introduction: Wheat (Triticum aestivum L.) is the most widely cultivated crop on Earth, contributing about a fifth of the total calories consumed by humans. Consequently, wheat yields and production affect the global economy, and failed harvests can lead to social unrest. Breeders continuously strive to develop improved varieties by fine-tuning genetically complex yield and end-use quality parameters while maintaining stable yields and adapting the crop to regionally specific biotic and abiotic stresses. Rationale: Breeding efforts are limited by insufficient knowledge and understanding of wheat biology and the molecular basis of central agronomic traits. To meet the demands of human population growth, there is an urgent need for wheat research and breeding to accelerate genetic gain as well as to increase and protect wheat yield and quality traits. In other plant and animal species, access to a fully annotated and ordered genome sequence, including regulatory sequences and genome-diversity information, has promoted the development of systematic and more time-efficient approaches for the selection and understanding of important traits. Wheat has lagged behind, primarily owing to the challenges of assembling a genome that is more than five times as large as the human genome, polyploid, and complex, containing more than 85% repetitive DNA. To provide a foundation for improvement through molecular breeding, in 2005, the International Wheat Genome Sequencing Consortium set out to deliver a high-quality annotated reference genome sequence of bread wheat. Results: An annotated reference sequence representing the hexaploid bread wheat genome in the form of 21 chromosome-like sequence assemblies has now been delivered, giving access to 107,891 high-confidence genes, including their genomic context of regulatory sequences. This assembly enabled the discovery of tissue- and developmental stage–related gene coexpression networks using a transcriptome atlas representing all stages of wheat development. The dynamics of change in complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. Aspects of the future value of the annotated assembly for molecular breeding and research were exemplarily illustrated by resolving the genetic basis of a quantitative trait locus conferring resistance to abiotic stress and insect damage as well as by serving as the basis for genome editing of the flowering-time trait. Conclusion: This annotated reference sequence of wheat is a resource that can now drive disruptive innovation in wheat improvement, as this community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding. Importantly, the bioinformatics capacity developed for model-organism genomes will facilitate a better understanding of the wheat genome as a result of the high-quality chromosome-based genome assembly. By necessity, breeders work with the genome at the whole chromosome level, as each new cross involves the modification of genome-wide gene networks that control the expression of complex traits such as yield. With the annotated and ordered reference genome sequence in place, researchers and breeders can now easily access sequence-level information to precisely define the necessary changes in the genomes for breeding programs. This will be realized through the implementation of new DNA marker platforms and targeted breeding technologies, including genome editing

Genetic diversity and population structure in a legacy collection of spring barley landraces adapted to a wide range of climates.

Global environmental change and increasing human population emphasize the urgent need for higher yielding and better adapted crop plants. One strategy to achieve this aim is to exploit the wealth of so called landraces of crop species, representing diverse traditional domesticated populations of locally adapted genotypes. In this study, we investigated a comprehensive set of 1485 spring barley landraces (Lrc1485) adapted to a wide range of climates, which were selected from one of the largest genebanks worldwide. The landraces originated from 5° to 62.5° N and 16° to 71° E. The whole collection was genotyped using 42 SSR markers to assess the genetic diversity and population structure. With an average allelic richness of 5.74 and 372 alleles, Lrc1485 harbours considerably more genetic diversity than the most polymorphic current GWAS panel for barley. Ten major clusters defined most of the population structure based on geographical origin, row type of the ear and caryopsis type - and were assigned to specific climate zones. The legacy core reference set Lrc648 established in this study will provide a long-lasting resource and a very valuable tool for the scientific community. Lrc648 is best suited for multi-environmental field testing to identify candidate genes underlying quantitative traits but also for allele mining approaches

Genome-wide association studies for agronomical traits in a world wide spring barley collection

Abstract Background Genome-wide association studies (GWAS) based on linkage disequilibrium (LD) provide a promising tool for the detection and fine mapping of quantitative trait loci (QTL) underlying complex agronomic traits. In this study we explored the genetic basis of variation for the traits heading date, plant height, thousand grain weight, starch content and crude protein content in a diverse collection of 224 spring barleys of worldwide origin. The whole panel was genotyped with a customized oligonucleotide pool assay containing 1536 SNPs using Illumina's GoldenGate technology resulting in 957 successful SNPs covering all chromosomes. The morphological trait "row type" (two-rowed spike vs. six-rowed spike) was used to confirm the high level of selectivity and sensitivity of the approach. This study describes the detection of QTL for the above mentioned agronomic traits by GWAS. Results Population structure in the panel was investigated by various methods and six subgroups that are mainly based on their spike morphology and region of origin. We explored the patterns of linkage disequilibrium (LD) among the whole panel for all seven barley chromosomes. Average LD was observed to decay below a critical level (r2-value 0.2) within a map distance of 5-10 cM. Phenotypic variation within the panel was reasonably large for all the traits. The heritabilities calculated for each trait over multi-environment experiments ranged between 0.90-0.95. Different statistical models were tested to control spurious LD caused by population structure and to calculate the P-value of marker-trait associations. Using a mixed linear model with kinship for controlling spurious LD effects, we found a total of 171 significant marker trait associations, which delineate into 107 QTL regions. Across all traits these can be grouped into 57 novel QTL and 50 QTL that are congruent with previously mapped QTL positions. Conclusions Our results demonstrate that the described diverse barley panel can be efficiently used for GWAS of various quantitative traits, provided that population structure is appropriately taken into account. The observed significant marker trait associations provide a refined insight into the genetic architecture of important agronomic traits in barley. However, individual QTL account only for a small portion of phenotypic variation, which may be due to insufficient marker coverage and/or the elimination of rare alleles prior to analysis. The fact that the combined SNP effects fall short of explaining the complete phenotypic variance may support the hypothesis that the expression of a quantitative trait is caused by a large number of very small effects that escape detection. Notwithstanding these limitations, the integration of GWAS with biparental linkage mapping and an ever increasing body of genomic sequence information will facilitate the systematic isolation of agronomically important genes and subsequent analysis of their allelic diversity.</p

Structure analysis for 1485 barley landraces.

<p><b>a)</b> mean Log probability values (LnP(D)) plotted as function of <i>K</i> (number of clusters); <b>b)</b> Delta <i>K</i> vs. <i>K</i> plotted as proposed by <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0116164#pone.0116164-Thiel1" target="_blank">[44]</a>. The graph indicates the maximum change at <i>K</i> = 4.</p

Comparison of diversity statistics for different panels.

<p>Genobar, Lrc1485, Lrc648, Lrc648r (648 randomly selected lines of Lrc1485 as additional validation), Lrc648 two-rowed sub-panel, and Lrc648 six-rowed sub-panel. ^atwo way comparisons: Genobar <i>vs</i> Lrc1485, Genobar <i>vs</i> Lrc648, Genobar <i>vs</i> Lrc648 (304 two-rowed accessions) and Genobar <i>vs</i> Lrc648 (344 six-rowed accessions) and Genobar <i>vs</i> Lrc648r.</p><p>Comparison of diversity statistics for different panels.</p