Final grain production and quality in durum wheat are affected by biotic and abiotic stresses. The association mapping (AM) approach is useful for dissecting the genetic control of quantitative traits, with the aim of increasing final wheat production under stress conditions. In this study, we used AM analyses to detect quantitative trait loci (QTL) underlying agronomic and quality traits in a collection of 294 elite durum wheat lines from CIMMYT (International Maize and Wheat Improvement Center), grown under different water regimes over four growing seasons. Thirty-seven significant marker-trait associations (MTAs) were detected for sedimentation volume (SV) and thousand kernel weight (TKW), located on chromosomes 1B and 2A, respectively. The QTL loci found were then confirmed with several AM analyses, which revealed 12 sedimentation index (SDS) MTAs and two additional loci for SV (4A) and yellow rust (1B). A candidate gene analysis of the identified genomic regions detected a cluster of 25 genes encoding blue copper proteins in chromosome 1B, with homoeologs in the two durum wheat subgenomes, and an ubiquinone biosynthesis O-methyltransferase gene. On chromosome 2A, several genes related to photosynthetic processes and metabolic pathways were found in proximity to the markers associated with TKW. These results are of potential use for subsequent application in marker-assisted durum wheat-breeding programs.
In this study, 129 wheat genotypes from globally diverse origins were genotyped using DArTseq (SilicoDArT and SNP) markers. After filtering markers for quality-filtering, 14,270 SilicoDArTs and 6484 SNPs were retained and used for genetic diversity, population structure and linkage disequilibrium analyses. The highest number of SilicoDArT and SNP markers mapped on genome A and B compared to genome D. In both marker types, polymorphism information content (PIC) values ranged from 0.1 to 0.5, while > 0.80% of SilicoDArTs and > 0.44% SNPs showed PIC value more than median (0.25%). Un-weighted Neighbor Joining cluster analysis and Bayesian-based model population structure grouped wheat genotypes into three and four clusters, respectively. Principal component analysis and discriminant analysis of principal component results showed highly match with cluster and population structure analysis. Linkage disequilibrium (LD) was more extensive in both marker types, while graphical display of LD decay for both marker types showed that LD declined in the region close to 15 kbp, where r2-values corresponded to r2 = 0.16. Overall, our genetic diversity analysis showed high level of variation in studied wheat genotypes, even though there was no relationship between wheat grouping and origins. This might be attributed to admixture level that occurred during long-term natural selection of wheat genotypes in different parts of the world. Highly diverse wheat genotypes used in this study may possess unique genes and are useful sources in breeding programs to improve grain yield and quality.
The aim of this study was the identification of molecular markers for the Pc39 gene in cultivated oat (Avena sativa L.). Pc39 is a major race-specific crown rust resistance gene originally found in an Israeli accession of the wild hexaploid Avena sterilis. The effectiveness of this gene in Europe has decreased in recent years, but is still relatively high and breeding programs would benefit from the availability of molecular markers to aid in its mapping and deployment. The complexity of the oat genome poses a significant obstacle to genetic research. No oat rust resistance genes have yet been cloned, and even the number of relevant molecular markers is very limited. Here, genotyping of a segregating population derived from a cross ‘Celer’ (Pc39)/STH9210 (susceptible) was conducted using RAPD- and SRAP-PCR-based methods, as well as microarray-based DArT™ and next-generation sequencing DArTseq™ techniques. Markers associated with Pc39 were placed on the hexaploid oat consensus linkage group Mrg11 at 3.7–6.7 cM. Six new PCR-based markers were developed to allow identification of the resistant Pc39 allele. These tightly linked markers will be useful in marker-assisted selection, with the closest, SCAR_3456624, being within 0.37 cM of Pc39. The newly developed markers could find applications in the fine mapping or positional cloning of this gene. Moreover, easy-to-use PCR-based markers linked to Pc39 could facilitate the utilization of this gene in oat breeding programs, especially as a component of crown rust resistance gene pyramids.
Pea (Pisum sativum) is one of the most important temperate grain legumes in the world, and its production is severely constrained by the pea aphid (Acyrthosiphon pisum). Wild relatives, such as P. fulvum, are valuable sources of allelic diversity to improve the genetic resistance of cultivated pea species against A. pisum attack. To unravel the genetic control underlying resistance to the pea aphid attack, a quantitative trait loci (QTL) analysis was performed using the previously developed high density integrated genetic linkage map originated from an intraspecific recombinant inbred line (RIL) population (P. fulvum: IFPI3260 × IFPI3251).
RESULTS
We accurately evaluated specific resistance responses to pea aphid that allowed the identification, for the first time, of genomic regions that control plant damage and aphid reproduction. Eight QTLs associated with tolerance to pea aphid were identified in LGs I, II, III, IV and V, which individually explained from 17.0% to 51.2% of the phenotypic variation depending on the trait scored, and as a whole from 17.0% to 88.6%. The high density integrated genetic linkage map also allowed the identification of potential candidate genes co‐located with the QTLs identified.
Human-mediated transport of species outside their natural range is a rapidly growing threat to biodiversity, particularly for island ecosystems that have evolved in isolation. The genetic structure underpinning island populations will largely determine their response to increased transport and thus help to inform biosecurity management. However, this information is severely lacking for some groups, such as the soil fauna. We therefore analysed the phylogeographic structure of an indigenous and an invasive springtail species (Collembola: Poduromorpha), each distributed across multiple remote sub-Antarctic islands, where human activity is currently intensifying. For both species, we generated a genome-wide SNP data set and additionally analysed all available COI barcodes. Genetic differentiation in the indigenous springtail Tullbergia bisetosa is substantial among (and, to a lesser degree, within) islands, reflecting low dispersal and historic population fragmentation, while COI patterns reveal ancestral signatures of postglacial recolonization. This pronounced geographic structure demonstrates the key role of allopatric divergence in shaping the region’s diversity and highlights the vulnerability of indigenous populations to genetic homogenization via human transport. For the invasive species Hypogastrura viatica, nuclear genetic structure is much less apparent, particularly for islands linked by regular shipping, while diverged COI haplotypes indicate multiple independent introductions to each island. Thus, human transport has likely facilitated this species’ persistence since its initial colonization, through the ongoing introduction and inter-island spread of genetic variation. These findings highlight the different evolutionary consequences of human transport for indigenous and invasive soil species. Crucially, both outcomes demonstrate the need for improved intraregional biosecurity among remote island systems, where the policy focus to date has been on external introductions.
Bi-allelic Single Nucleotide Polymorphism (SNP) markers are widely used in population genetic studies. In most studies, sequences either side of the SNPs remain unused, although these sequences contain information beyond that used in population genetic studies. In this study, we show how these sequence tags either side of a single nucleotide polymorphism can be used for comparative genome analysis. We used DArTseq (Diversity Array Technology) derived SNP data for a non-model Australian native freshwater fish, Macquaria ambigua, to identify genes linked to SNP associated sequence tags, and to discover homologies with evolutionarily conserved genes and genomic regions. We concatenated 6,776 SNP sequence tags to create a hypothetical genome (representing 0.1–0.3% of the actual genome), which we used to find sequence homologies with 12 model fish species using the Ensembl genome browser with stringent filtering parameters. We identified sequence homologies for 17 evolutionarily conserved genes (cd9b, plk2b, rhot1b, sh3pxd2aa, si:ch211-148f13.1, si:dkey-166d12.2, zgc:66447, atp8a2, clvs2, lyst, mkln1, mnd1, piga, pik3ca, plagl2, rnf6, sec63) along with an ancestral evolutionarily conserved syntenic block (euteleostomi Block_210). Our analysis also revealed repetitive sequences covering approximately 12% of the hypothetical genome where DNA transposon, LTR and non-LTR retrotransposons were most abundant. A hierarchical pattern of the number of sequence homologies with phylogenetically close species validated the approach for repeatability. This new approach of using SNP associated sequence tags for comparative genome analysis may provide insight into the genome evolution of non-model species where whole genome sequences are unavailable.
Macrobrachium (Bate, 1868) is a large and cosmopolitan crustacean genus of high economic importance worldwide. We investigated the morphological and molecular identification of freshwater prawns of the genus Macrobrachium in South, South West, and Littoral regions of Cameroon. A total of 1,566 specimens were examined morphologically using a key described by Konan (Diversité morphologique et génétique des crevettes des genres Atya Leach, 1816 et Macrobrachium Bate, 1868 de Côte d’Ivoire, 2009, Université d’Abobo Adjamé, Côte d’Ivoire), leading to the identification of seven species of Macrobrachium: M. vollenhovenii (Herklots, 1857); M. macrobrachion (Herklots, 1851); M. sollaudii (De Man, 1912); M. dux (Lenz, 1910); M. chevalieri (Roux, 1935); M. felicinum (Holthuis, 1949); and an undescribed Macrobrachium species M.sp. To validate the genetic basis of the identified species, 94 individuals representing the species were selected and subjected to genetic characterization using 1,814 DArT markers. The admixture analysis revealed four groups: M. vollenhovenii and M. macrobrachion; M. chevalieri; M. felicinum and M.sp; and M. dux and M. sollaudii. But, the principal component analysis (PCA) separated M.sp and M. felicinum to create additional group (i.e., five groups). Based on these findings, M. vollenhovenii and M. macrobrachion may be conspecific, as well as M. dux and M. sollaudii, while M. felicinum and M.sp seems to be different species, suggesting a potential conflict between the morphological identification key and the genetic basis underlying speciation and species allocation for Macrobrachium. These results are valuable in informing breeding design and genetic resource conservation programs for Macrobrachium in Africa.
Understanding the genetic diversity of Aegilops biuncialis, a valuable source of agronomical useful genes, may significantly facilitate the introgression breeding of wheat. The genetic diversity and population structure of 86 Ae. biuncialis genotypes were investigated by 32700 DArT markers with the simultaneous application of three statistical methods— neighbor-joining clustering, Principal Coordinate Analysis, and the Bayesian approach to classification. The collection of Ae. biuncialis accessions was divided into five groups that correlated well with their eco-geographic habitat: A (North Africa), B (mainly from Balkans), C (Kosovo and Near East), D (Turkey, Crimea, and Peloponnese), and E (Azerbaijan and the Levant region). The diversity between the Ae. biuncialis accessions for a phenological trait (heading time), which is of decisive importance in the adaptation of plants to different eco-geographical environments, was studied over 3 years. A comparison of the intraspecific variation in the heading time trait by means of analysis of variance and principal component analysis revealed four phenotypic categories showing association with the genetic structure and geographic distribution, except for minor differences. The detailed exploration of genetic and phenologic divergence provides an insight into the adaptation capacity of Ae. biuncialis, identifying promising genotypes that could be utilized for wheat improvement.
Yellow rust (YR) or stripe rust, caused by Puccinia striformis f. sp tritici Eriks (Pst), is a major challenge to resistance breeding in wheat. A genome wide association study (GWAS) was performed using 22,415 single nucleotide polymorphism (SNP) markers and 591 haplotypes to identify genomic regions associated with resistance to YR in a subset panel of 419 pre-breeding lines (PBLs) developed at International Center for Maize and Wheat Improvement (CIMMYT). The 419 PBLs were derived from an initial set of 984 PBLs generated by a three-way crossing scheme (exotic/elite1//elite2) among 25 best elites and 244 exotics (synthetics, landraces) from CIMMYT’s germplasm bank. For the study, 419 PBLs were characterized with 22,415 high-quality DArTseq-SNPs and phenotyped for severity of YR disease at five locations in Mexico. A population structure was evident in the panel with three distinct subpopulations, and a genome-wide linkage disequilibrium (LD) decay of 2.5 cM was obtained. Across all five locations, 14 SNPs and 7 haplotype blocks were significantly (P < 0.001) associated with the disease severity explaining 6.0 to 14.1% and 7.9 to 19.9% of variation, respectively. Based on average LD decay of 2.5 cM, identified 14 SNP–trait associations were delimited to seven quantitative trait loci in total. Seven SNPs were part of the two haplotype blocks on chromosome 2A identified in haplotypes-based GWAS. In silico analysis of the identified SNPs showed hits with interesting candidate genes, which are related to pathogenic process or known to regulate induction of genes related to pathogenesis such as those coding for glunolactone oxidase, quinate O-hydroxycinnamoyl transferase, or two-component histidine kinase. The two-component histidine kinase, for example, acts as a sensor in the perception of phytohormones ethylene and cytokinin. Ethylene plays a very important role in regulation of multiple metabolic processes of plants, including induction of defense mechanisms mediated by jasmonate. The SNPs linked to the promising genes identified in the study can be used for marker-assisted selection.
The haploid fungus Pseudocercospora fijiensis causes black Sigatoka in banana and is chiefly controlled by extensive fungicide applications, threatening occupational health and the environment. The 14α-Demethylase Inhibitors (DMIs) are important disease control fungicides, but they lose sensitivity in a rather gradual fashion, suggesting an underlying polygenic genetic mechanism. In spite of this, evidence found thus far suggests that P. fijiensis cyp51 gene mutations are the main responsible factor for sensitivity loss in the field. To better understand the mechanisms involved in DMI resistance, in this study we constructed a genetic map using DArTseq markers on two F1 populations generated by crossing two different DMI resistant strains with a sensitive strain. Analysis of the inheritance of DMI resistance in the F1 populations revealed two major and discrete DMI-sensitivity groups. This is an indicative of a single major responsible gene. Using the DMI-sensitivity scorings of both F1 populations and the generation of genetic linkage maps, the sensitivity causal factor was located in a single genetic region. Full agreement was found for genetic markers in either population, underlining the robustness of the approach. The two maps indicated a similar genetic region where the Pfcyp51 gene is found. Sequence analyses of the Pfcyp51 gene of the F1 populations also revealed a matching bimodal distribution with the DMI resistant. Amino acid substitutions in P. fijiensis CYP51 enzyme of the resistant progeny were previously correlated with the loss of DMI sensitivity. In addition, the resistant progeny inherited a Pfcyp51 gene promoter insertion, composed of a repeat element with a palindromic core, also previously correlated with increased gene expression. This genetic approach confirms that Pfcyp51 is the single explanatory gene for reduced sensitivity to DMI fungicides in the analysed P. fijiensis strains. Our study is the first genetic analysis to map the underlying genetic factors for reduced DMI efficacy.