Transcriptome profiling and validation of gene based single nucleotide polymorphisms (SNPs) in sorghum genotypes with contrasting responses to cold stress

Primer sequences for validation of bi-allelic variant calls. (DOCX 15 kb

Comparisons of De Novo Transcriptome Assemblers in Diploid and Polyploid Species Using Peanut (Arachis spp.) RNA-Seq Data

The narrow genetic base and limited genetic information on Arachis species have hindered the process of marker-assisted selection of peanut cultivars. However, recent developments in sequencing technologies have expanded opportunities to exploit genetic resources, and at lower cost. To use the genetic information for Arachis species available at the transcriptome level, it is important to have a good quality reference transcriptome. The available Tifrunner 454 FLEX transcriptome sequences have an assembly with 37,000 contigs and low N50 values of 500-751 bp. Therefore, we generated de novo transcriptome assemblies, with about 38 million reads in the tetraploid cultivar OLin, and 16 million reads in each of the diploids, A. duranensis K38901 and A. ipaënsis KGBSPSc30076 using three different de novo assemblers, Trinity, SOAPdenovo-Trans and TransAByss. All these assemblers can use single kmer analysis, and the latter two also permit multiple kmer analysis. Assemblies generated for all three samples had N50 values ranging from 1278-1641 bp in Arachis hypogaea (AABB), 1401-1492 bp in Arachis duranensis (AA), and 1107-1342 bp in Arachis ipaënsis (BB). Comparison with legume ESTs and protein databases suggests that assemblies generated had more than 40% full length transcripts with good continuity. Also, on mapping the raw reads to each of the assemblies generated, Trinity had a high success rate in assembling sequences compared to both TransAByss and SOAPdenovo-Trans. De novo assembly of OLin had a greater number of contigs (67,098) and longer contig length (N50 = 1,641) compared to the Tifrunner TSA. Despite having shorter read length (2 × 50) than the Tifrunner 454FLEX TSA, de novo assembly of OLin proved superior in comparison. Assemblies generated to represent different genome combinations may serve as a valuable resource for the peanut research community

Molecular tools enabling pennycress (\u3ci\u3eThlaspi arvense\u3c/i\u3e) as a model plant and oilseed cash cover crop

Thlapsi arvense L. (pennycress) is being developed as a profitable oilseed cover crop for the winter fallow period throughout the temperate regions of the world, controlling soil erosion and nutrients run-off on otherwise barren farmland. We demonstrate that pennycress can serve as a user-friendly model system akin to Arabidopsis that is well-suited for both laboratory and field experimentation. We sequenced the diploid genome of the spring-type Spring 32-10 inbred line (1C DNA content of 539 Mb; 2n = 14), identifying variation that may explain phenotypic differences with winter-type pennycress, as well as predominantly a one-to-one correspondence with Arabidopsis genes, which makes translational research straightforward. We developed an Agrobacterium-mediated floral dip transformation method (0.5% transformation efficiency) and introduced CRISPR-Cas9 constructs to produce indel mutations in the putative FATTY ACID ELONGATION1 (FAE1) gene, thereby abolishing erucic acid production and creating an edible seed oil comparable to that of canola. We also stably transformed pennycress with the Euonymus alatus diacylglycerol acetyltransferase (EaDAcT) gene, producing low-viscosity acetyltriacylglycerol- containing seed oil suitable as a diesel-engine drop-in fuel. Adoption of pennycress as a model system will accelerate oilseed-crop translational research and facilitate pennycress’ rapid domestication to meet the growing sustainable food and fuel demands

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. Methods To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. Findings During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. Interpretation Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world

Genome-wide association analysis of seedling traits in diverse Sorghum germplasm under thermal stress

Abstract Background Climate variability due to fluctuation in temperature is a worldwide concern that imperils crop production. The need to understand how the germplasm variation in major crops can be utilized to aid in discovering and developing breeding lines that can withstand and adapt to temperature fluctuations is more necessary than ever. Here, we analyzed the genetic variation associated with responses to thermal stresses in a sorghum association panel (SAP) representing major races and working groups to identify single nucleotide polymorphisms (SNPs) that are associated with resilience to temperature stress in a major cereal crop. Results The SAP exhibited extensive variation for seedling traits under cold and heat stress. Genome-wide analyses identified 30 SNPs that were strongly associated with traits measured at seedling stage under cold stress and tagged genes that act as regulators of anthocyanin expression and soluble carbohydrate metabolism. Meanwhile, 12 SNPs were significantly associated with seedling traits under heat stress and these SNPs tagged genes that function in sugar metabolism, and ion transport pathways. Evaluation of co-expression networks for genes near the significantly associated SNPs indicated complex gene interactions for cold and heat stresses in sorghum. We focused and validated the expression of four genes in the network of Sb06g025040 , a basic-helix-loop-helix ( bHLH ) transcription factor that was proposed to be involved in purple color pigmentation of leaf, and observed that genes in this network were upregulated during cold stress in a moderately tolerant line as compared to the more sensitive line. Conclusion This study facilitated the tagging of genome regions associated with variation in seedling traits of sorghum under cold and heat stress. These findings show the potential of genotype information for development of temperature resilient sorghum cultivars and further characterization of genes and their networks responsible for adaptation to thermal stresses. Knowledge on the gene networks from this research can be extended to the other cereal crops to better understand the genetic basis of resilience to temperature fluctuations during plant developmental stages

Pilea sohayakiensis Kitam.

原著和名: ソハヤキミヅ科名: イラクサ科 = Urticaceae採集地: 和歌山県 東牟婁郡 熊野川町 小口〜畝畑 (紀伊 東牟婁郡 熊野川町 小口〜畝畑 )採集日: 1980/9/22採集者: 萩庭丈壽整理番号: JH007931国立科学博物館整理番号: TNS-VS-95793

Transcriptomic Resources for the Medicinal Legume \u3ci\u3eMucuna pruriens\u3c/i\u3e: \u3ci\u3ede novo\u3c/i\u3e Transcriptome Assembly, Annotation, Identification and Validation of EST-SSR Markers

Background: The medicinal legume Mucuna pruriens (L.) DC. has attracted attention worldwide as a source of the anti-Parkinson’s drug L-Dopa. It is also a popular green manure cover crop that offers many agronomic benefits including high protein content, nitrogen fixation and soil nutrients. The plant currently lacks genomic resources and there is limited knowledge on gene expression, metabolic pathways, and genetics of secondary metabolite production. Here, we present transcriptomic resources for M. pruriens, including a de novo transcriptome assembly and annotation, as well as differential transcript expression analyses between root, leaf, and pod tissues. We also develop microsatellite markers and analyze genetic diversity and population structure within a set of Indian germplasm accessions. Results: One-hundred ninety-one million two hundred thirty-three thousand two hundred forty-two bp cleaned reads were assembled into 67,561 transcripts with mean length of 626 bp and N50 of 987 bp. Assembled sequences were annotated using BLASTX against public databases with over 80% of transcripts annotated. We identified 7,493 simple sequence repeat (SSR) motifs, including 787 polymorphic repeats between the parents of a mapping population. 134 SSRs from expressed sequenced tags (ESTs) were screened against 23 M. pruriens accessions from India, with 52 EST-SSRs retained after quality control. Population structure analysis using a Bayesian framework implemented in fastSTRUCTURE showed nearly similar groupings as with distance-based (neighbor-joining) and principal component analyses, with most of the accessions clustering per geographical origins. Pair-wise comparison of transcript expression in leaves, roots and pods identified 4,387 differentially expressed transcripts with the highest number occurring between roots and leaves. Differentially expressed transcripts were enriched with transcription factors and transcripts annotated as belonging to secondary metabolite pathways. Conclusions: The M. pruriens transcriptomic resources generated in this study provide foundational resources for gene discovery and development of molecular markers. Polymorphic SSRs identified can be used for genetic diversity, marker-trait analyses, and development of functional markers for crop improvement. The results of differential expression studies can be used to investigate genes involved in L-Dopa synthesis and other key metabolic pathways in M. pruriens

Genetic Diversity of Field Pennycress (Thlaspi arvense) Reveals Untapped Variability and Paths Toward Selection for Domestication

Evaluation of genetic diversity within wild populations is an essential process for improvement and domestication of new crop species. This process involves evaluation of population structure and individual accessions based on genetic markers, growth habits, and geographic collection area. In this study, accessions of field pennycress were analyzed to identify population structure and variation in germplasm available for breeding. A total of 9157 genome-wide single nucleotide polymorphisms (SNPs) were identified among the 121 accessions analyzed, and linkage disequilibrium based pruning resulted in 3497 SNPs. Bayesian cluster analysis was implemented in STRUCTURE v2.3.4 to identify four population groups. These groups were confirmed based on principal components analysis and geographic origins. Pairwise diversity among accessions was evaluated and revealed considerable genetic variation. Notably, a subset of accessions from Armenia with exceptional genetic variation was identified. This survey is the first to report significant genetic diversity among pennycress accessions and explain some of the phenotypic differences previously observed in the germplasm. Understanding variation in pennycress accessions will be a crucial step for selection, breeding, and domestication of a new cash cover crop for cold climates

Additional file 3: of Genome-wide association analysis of seedling traits in diverse Sorghum germplasm under thermal stress

Validation of SNPs in nine sorghum lines to determine the haplotypes for cold tolerance. (XLSX 10 kb