Ecological Genetics and Genomics最新文献

Parasitic plant Striga gesneroides reduces cowpea productivity in sub-Saharan Africa, leading to substantial yield losses. This weed is the major reason for land abandonment by many farmers. While various methods have been proposed for managing Striga invasion and parasitism, host-plant resistance remains the most effective and affordable option for small-scale farmers in the sub-region. This study aims to expedite the improvement of Striga resistance breeding through marker-assisted selection by identifying genomic regions and candidate genes associated with Striga resistance indicator traits using association mapping. A panel of 188 cowpea accessions assembled from five gene banks in West Africa were phenotyped for two years under Striga-infested and non-infested research conditions. These accessions were equally genotyped using the medium-density genotyping of the Diversity Arrays Technology sequencing (DArTseq) platform to obtain marker information. High broad-sense heritability estimates were observed for Striga resistance status (SRS), number of Striga per plot (NSPlot), and Pod weight (PW) while low heritability estimates were observed for fodder weight (FW) and Plant Aspect (PASP). Twenty-four SNP markers were identified across SRS, NSPlot, FW, PASP, and PW under Striga-infested conditions. Under non-infested conditions, 17 SNPs were identified across FW, PASP, and PW. Gene annotation of the significant SNPs revealed candidate genes such as ubiquitin ligase activity, cell wall reinforcement protein, and pathogenesis-related protein. These genes function in plant growth regulation, development, and defense mechanisms. This study offers valuable insights for marker selection, validation, and deployment in cowpea improvement for Striga resistance in SSA.

During an investigations on Monosporascus cannonballus, the causal agent of root rot and vine decline of melons, in 1999, a previously unknown rhizosphere fungus was encountered in the desert soils of southern California. The fungus, herein named Desertella arida Stanghellini & Mohammadi sp. nov., was associated with roots of diverse plants including brassica (Sahara mustard (Brassica tournefortii), shepherd's purse (Capsella bursa-pastoris)) and plantain (Plantago ovata Forsk). The fungus forms extensive multinucleate, septate hyphae (6–17 μm in diameter) bearing hundreds of large spherical to pear-shaped unicellular asexual spores (50–120 μm in diameter), either singly or in large clusters. The spores are beige to cream-colored, thin-walled, and contain a dense, granular cytoplasm. Further investigation on the distribution of D. arida in soils of desert habitats in the southwestern USA led to the discovery of a second fungus belonging to a different species herein named Desertella americanense Mohammadi & Stanghellini sp. nov., in California, Arizona, Nevada, and Utah. The two species are morphologically similar. Spores from both fungi in native soil survived heat treatment up to 100 °C. Both species are culturable and colonized roots of monocots and dicots forming abundant hyphae and spores as early as 10 days post-inoculation. Desertella arida significantly enhanced shoot growth in broccoli, lettuce, Plantago ovata and flax. In conclusion, we discovered two desert-dwelling ascomycete fungi that were associated with the roots of native plant species in southern California. They were culturable on a synthetic medium, heat-tolerant and promoted growth on several crop species. These fungi appeared to exist in other neighboring states such as Arizona and Nevada.

Vigna is a genus of approximately 100 wild species found in tropical and sub-tropical region. The three varieties of green gram (Vigna radiata L.) (VBN3, VBN6 & CO8) was widely cultivated in Tamil Nadu. Soil salinity is a significant issue in food production because excessive salt concentrations in soil inhibit plant development, delaying maturity and reducing crop yield or causing wilting. In the present study, we investigate the effective screening of saline tolerance in green gram, carried out the mechanism of physiological, biochemical and genetic variation using molecular markers of salinity stress of green gram under different concentration of NaCl (control, 50, 100, 150 and 200 mM). The result shows that, the salinity stress significantly reduced the physiological, biochemical and plant growth characteristics. Besides, the gene-targeted like Start Codon Targeted (SCoT) and CAAT box derived polymorphism (CBDP) markers were used to examine the genetic variability under saline stress of green gram. Herein, the SCoT and CBDP primers produced 54 and 90 polymorphic bands with an average of 5.7 and 7.8 bands per primer, respectively. The Analysis of Molecular Variance (AMOVA) and Principal Coordinate Analysis (PCoA) revealed genetic diversity within species was greater than between them, indicating that all of the saline-treated samples from the three varieties displayed genetic variation. The present study concludes that the increased concentration of NaCl reduced the plant growth and significantly affects the physiological, biochemical and genetic variation.

By prioritizing high yields in ideal conditions, traditional breeding might miss out that genotypes with superior yield and stability. Thus,this study seeks to identify stable genotypes that offer more predictable and reliable yields; under both stress and resourceful environments, leading to not only greater food security but financial stability as well. Incorporating both fixed (AMMI&GGI) and random effects models (BLUP & MTSI), not only leveraged theoretical but also empirical comparisons-weakness of each model is covered by all 4 models-to select elites hybrids Maize. Furthermore, a multi-environment trial assessed 41 hybrids across 4 research stations in 2 winter seasons using RCB design. Likewise, compiled cutting-edge statistical methods for GEI analyses from the “metan” package (R-Software), selected hybrids with consistent performance with meticulous analysis. AMMI(Additive Main effects and Multiplicative Interaction)analysis revealed that of significant (p ≤ 0.05) effects of genotype, environment, & genotype-environment interaction (GEI), explaining yield variance with interaction effects were captured by 3 interaction principal components (IPCs). Moreover,GEI graphics of AMMI biplots elucidates four hybrids(MRM-4062, Super-22, PAC-744, and Gen-4118) with high yield stability and above-average performance. Additionally, eight hybrids (4118, 4558, 5454, NMH1258, PAC 746, PAC 745 Gold, and SUPER 9090) exhibited superior yield, regardless of their stability. Nepalgunj exhibited the lowest GEI value. Conversely, Rampur displayed an above-average GEI, indicating a strong ability to modulate varieties performance. Besides this, GGE biplot revealed two potential mega-environments based on yield similarities. Nine high-yielding hybrids (SUPPER 6768, SUPPER 9396, PAC750, MBS5622, PAC745 Gold, MRM4065, NMH8392, Gen-4118, and Gen-4558) were identified as vertex hybrids, signifying their superior performance across wide environments. Even supposing, mixed effects model, both the best linear unbiased prediction (BLUP) weighted with average absolute score standardized by yields (WAASBY) models, Gen-4118 ranked highest in terms of average yield, followed by NMH-8392, TMH2858, and others, and Multi-Trait Stability Index (MTSI) identified SUPPER-9090 as the most stable and high-yielding genotype, followed by NMH4040, Super-22, Gen-4118, MBS-1144, and NMH1255. In a nutshell, Gen-4118, Super-9090, MRM-4062, NMH1258, NMH-8392, TMH2858, PAC 746, PAC 745 Gold emerge as the highest-yielding and most consistently high-performinghybrids, offering promise for commercial farming across diverse environments. Clearly,this study has potential to mitigate risks for farmers (economic burden, crop failure) and bolster food security/climate resilience. What's more, it paves the way for future research on cold tolerance genes for even greater crop improvement.

Mucuna pruriens, a widely available but underutilized legume in India, stands out for its nutritional and medicinal potential. Understanding the genetic diversity of M. pruriens is vital for its conservation and utilization in breeding programs aimed at enhancing its nutritional and agronomic traits. In this regard, molecular markers like ISSRs offer a reliable and informative tool for assessing genetic diversity. In the present study, 23 M. pruriens accessions from northeastern India were evaluated using ISSR markers, revealing high levels of polymorphism and significant genetic diversity. A total of 512 amplicons were generated across 33 ISSR primers, with an average polymorphic percentage of 98.05 %. PIC values ranged from 0.22 to 0.50, indicating substantial genetic variation within the accessions. Supplementary indicators such as EMR and MI were employed to evaluate the marker system's efficacy. EMR ranged from 6 to 22, averaging 14.95, while MI ranged from 2.64 to 9.02, averaging 6.04, with a positive correlation observed between EMR and MI. Cluster analysis based on Jaccard's similarity coefficient classified the accessions into two major groups, with the northeastern Indian accessions displaying higher diversity compared to those from other regions of India. Interestingly, geographical proximity did not consistently correlate with genetic similarity, suggesting complex patterns of gene flow and historical germplasm exchange. Overall, this study provides valuable insights into the genetic diversity of M. pruriens and highlights the importance of conserving and utilizing this underutilized legume for addressing global food security challenges.

In the present study, multi-environmental trials were performed on 19 newly developed barley genotypes at five test regions across the warm climate in Iran for two consecutive years. The results of additive main effects and multiplicative interaction (AMMI), GGE biplot (GGE) model, and several BLUP-based stability parameters and integrated models (WAASB and WAASBY) were used to reveal GEI patterns and identify superior genotypes with stable grain yield across test environments. Statistical analyses revealed that grain yield was influenced by significant environments (E), genotypes (G), and GEI effects. Among AMMI-, BLUP-, and grain mean-based stability parameters, the harmonic means of genotypic values (HMGV), relative performance of genotypic value (RPGV), and harmonic mean of RPGV parameters indicated a dynamic concept of stability. Moreover, results of GGE biplot analysis identified three mega-environments with different winner genotypes in test environments. Regardless of the different years, the Ahvaz, Darab, and Moghan regions were identified as Type-II environments due to their highest discrimination power and representative ability. The grouping pattern considerably followed the ranking of genotypes in GGE biplot analysis and WAASB model. In conclusion, our results revealed that genotypes G9 and G10 had grain yield higher than the reference genotype and relative stability in specific environments with favorable environmental conditions. Genotype G5 had general adaptability and stability across all test environments. This genotype can be recommended for cultivation in a wide range of environments in the warm climate of Iran.

Fungal endophytes exhibit a broad diversity and are found universally associated with all plant species, playing a vital role in enhancing the host plant's resilience against both biotic and abiotic stressors. In this investigation conducted in Mumbai, India, the Illumina MiSeq sequencing platform was employed to study the endophytic fungal diversity of the common mangrove, Acanthus ilicifolius and its rhizosphere utilizing the amplification of the fungal ribosomal ITS2 region. The results revealed the creation of 307 Operational Taxonomic Units (OTUs) from a total of 663,600 sequencing reads, clustered at a 97 percent similarity level. Evaluation using Simpson and Shannon indices indicated that the highest community diversity was observed in stem tissue compared to root and leaf samples. The total OTUs were categorized into five phyla, 41 orders, 89 families, and 133 genera, with Ascomycota being the predominant phylum at 76.9% relative abundance, followed by Basidiomycota at 22.87%. The most abundant genera in the soil were Malassezia (35%) and Aspergillus (29.5%), while Vishniacozyma (61%) dominated in leaf samples. Unlike stem and root, no single genus dominated these tissues. The findings demonstrated significant distinctions between the fungal endophytic communities in plant tissues and the fungal microbiome in the soil. Notably, the endophyte fungi community in roots exhibited a closer resemblance to stem samples than to leaf samples. FunGuild analysis also revealed characteristic communities in different samples indicating specific functions of these genera. Overall, this study provides novel insights into the intricate composition of endophytic fungi within the tissues of A. ilicifolius and its rhizosphere.

In the current study, sixteen basil genotypes in India were analyzed over three years using the AMMI stability model. The study years explained the bulk of the variation in all nine variables. The vast amount of data required for this inquiry hinders plant breeding processes. For basil's two most critical features, ursolic acid and essential oil yield, we found that genotypes 6, 11, and 12 were the best and most consistent options for practically every analyzed property. Furthermore, there were substantial + ve and -ve correlations among the major characteristics that drove stable line selection. Trait associations and stability-related factors both influence stable genotype selection in basil. Based on the results, genotypes 6, 11, and 12 may be recommended for large-area cultivation.

Morada Nova breed has a low effective herd, and its white variety is in risk of extinction in Brazilian semi-arid region. This study aimed to evaluate white Morada Nova sheep’s genetic variability and population structure in four flocks. These are the only flocks in the world. The assessed parameters of pedigree integrity and a genealogy record of 219 animals. 44.74 % did not have pedigree information on their mother or father, and 50.47 % did not have available information on their grandparents. 52.97 % had a pedigree in their first ancestry (obtained through the average of known parents), 23.74 % in the second, 13.58 % in the third, and 5.33 % in the fourth. The effective size was 10.7, considering the complete equivalent generation. The effective number of founding animals (fe) and ancestors (fa) was 10, indicating the effective participation of all founding animals in the population over the generations, reducing losses of genetic variability. Out of all the ancestors, only 3 explained 50 % of the population’s genetic variability, reflecting the low values of fa and fe. The population’s average inbreeding and kinship coefficients were 2.61 and 4.54. The F statistics of Wright, Fis, Fst, and Fit, were −0.012, 0.016, and 0.003. The genetic conservation index (GCI) had an average of 2.01 ± 1.29, with minimum and maximum values of 1.0 and 6.38, respectively. Approximately, 71 % of the population had GCI below 2.0, while only 5.9 % of sheep had an GCI bigger than 5.0. This indicates the absence of sub-structures inf the population. There is no population subdivision, considering the genealogical structure of the evaluated flocks. The inbreeding and kinship coefficient values are controlled and serve as a starting point for establishing a future management plan for the genetic variability of the flock. It is recommended to use strategies to increase the effective population size, to meet the minimum number recommended by FAO and to promote the conservation and genetic improvement of the breed.

The scope of the present review is to highlight and discuss the application of genomic selection to the improvement of dairy cattle productivity in the face of climate change. The field of genomics is conceived as the scientific study of a species' genome's structure and function using several nucleotide sequences. Genomic selection is the selection of a population based on estimated genomic breeding values. It has been applied as an invaluable tool for increasing the rate of genetic gain with reduced generation intervals while maintaining a good level of selection accuracy. Moreover, it has been widely used for the selection of superior animals with great accuracy at an early age, resulting in enhanced productivity in dairy cattle populations. Genomic selection is particularly efficient in improving low-heritability traits related to the efficiency of feed conversion, reproduction, adaptation to changing production environments, and resistance to various disease transmitting pathogens and vectors. Genomic selection implementation requires careful model selection, and one of the popular models is best linear unbiased prediction (BLUP). Most studies have shown that pure breeds' genomic evaluation can be utilized to improve productivity, efficiency, and genetics by providing a large reference population for dairy cows with high milk production. Research concentrating on the use of genomic selection on Bos indicus cattle is required to assess its effect on the productivity of tropical cattle breeds, as the majority of research studies have been carried out using Bos taurus cattle.