Genetic linkage analysis of stable QTLs in Gossypium hirsutum RIL population revealed function of GhCesA4 in fiber development.

INTRODUCTION: Upland cotton is an important allotetrapolyploid crop providing natural fibers for textile industry. Under the present high-level breeding and production conditions, further simultaneous improvement of fiber quality and yield is facing unprecedented challenges due to their complex negative correlations. OBJECTIVES: The study was to adequately identify quantitative trait loci (QTLs) and dissect how they orchestrate the formation of fiber quality and yield. METHODS: A high-density genetic map (HDGM) based on an intraspecific recombinant inbred line (RIL) population consisting of 231 individuals was used to identify QTLs and QTL clusters of fiber quality and yield traits. The weighted gene correlation network analysis (WGCNA) package in R software was utilized to identify WGCNA network and hub genes related to fiber development. Gene functions were verified via virus-induced gene silencing (VIGS) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 strategies. RESULTS: An HDGM consisting of 8045 markers was constructed spanning 4943.01 cM of cotton genome. A total of 295 QTLs were identified based on multi-environmental phenotypes. Among 139 stable QTLs, including 35 newly identified ones, seventy five were of fiber quality and 64 yield traits. A total of 33 QTL clusters harboring 74 QTLs were identified. Eleven candidate hub genes were identified via WGCNA using genes in all stable QTLs and QTL clusters. The relative expression profiles of these hub genes revealed their correlations with fiber development. VIGS and CRISPR/Cas9 edition revealed that the hub gene cellulose synthase 4 (GhCesA4, GH_D07G2262) positively regulate fiber length and fiber strength formation and negatively lint percentage. CONCLUSION: Multiple analyses demonstrate that the hub genes harbored in the QTLs orchestrate the fiber development. The hub gene GhCesA4 has opposite pleiotropic effects in regulating trait formation of fiber quality and yield. The results facilitate understanding the genetic basis of negative correlation between cotton fiber quality and yield.

Hub Genes in Stable QTLs Orchestrate the Accumulation of Cottonseed Oil in Upland Cotton via Catalyzing Key Steps of Lipid-Related Pathways.

Upland cotton is the fifth-largest oil crop in the world, with an average supply of nearly 20% of vegetable oil production. Cottonseed oil is also an ideal alternative raw material to be efficiently converted into biodiesel. However, the improvement in kernel oil content (KOC) of cottonseed has not received sufficient attention from researchers for a long time, due to the fact that the main product of cotton planting is fiber. Previous studies have tagged QTLs and identified individual candidate genes that regulate KOC of cottonseed. The regulatory mechanism of oil metabolism and accumulation of cottonseed are still elusive. In the current study, two high-density genetic maps (HDGMs), which were constructed based on a recombinant inbred line (RIL) population consisting of 231 individuals, were used to identify KOC QTLs. A total of forty-three stable QTLs were detected via these two HDGM strategies. Bioinformatic analysis of all the genes harbored in the marker intervals of the stable QTLs revealed that a total of fifty-one genes were involved in the pathways related to lipid biosynthesis. Functional analysis via coexpression network and RNA-seq revealed that the hub genes in the co-expression network that also catalyze the key steps of fatty acid synthesis, lipid metabolism and oil body formation pathways (ACX4, LACS4, KCR1, and SQD1) could jointly orchestrate oil accumulation in cottonseed. This study will strengthen our understanding of oil metabolism and accumulation in cottonseed and contribute to KOC improvement in cottonseed in the future, enhancing the security and stability of worldwide food supply.

Genome-Wide Analysis and Functional Characterization of LACS Gene Family Associated with Lipid Synthesis in Cotton (Gossypium spp.).

Cotton (Gossypium spp.) is the fifth largest oil crop in the world, and cottonseed provides abundant vegetable oil resources and industrial bioenergy fuels for people; therefore, it is of practical significance to increase the oil content of cotton seeds for improving the oil yield and economic benefits of planting cotton. Long-chain acyl-coenzyme A (CoA) synthetase (LACS) capable of catalyzing the formation of acyl-CoAs from free fatty acids has been proven to significantly participate in lipid metabolism, of which whole-genome identification and functional characterization of the gene family have not yet been comprehensively analyzed in cotton. In this study, a total of sixty-five LACS genes were confirmed in two diploid and two tetraploid Gossypium species, which were divided into six subgroups based on phylogenetic relationships with twenty-one other plants. An analysis of protein motif and genomic organizations displayed structural and functional conservation within the same group but diverged among the different group. Gene duplication relationship analysis illustrates the LACS gene family in large scale expansion through WGDs/segmental duplications. The overall Ka/Ks ratio indicated the intense purifying selection of LACS genes in four cotton species during evolution. The LACS genes promoter elements contain numerous light response cis-elements associated with fatty acids synthesis and catabolism. In addition, the expression of almost all GhLACS genes in high seed oil were higher compared to those in low seed oil. We proposed LACS gene models and shed light on their functional roles in lipid metabolism, demonstrating their engineering potential for modulating TAG synthesis in cotton, and the genetic engineering of cottonseed oil provides a theoretical basis.

Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates.

Extreme weather events threaten food security, yet global assessments of impacts caused by crop waterlogging are rare. Here we first develop a paradigm that distils common stress patterns across environments, genotypes and climate horizons. Second, we embed improved process-based understanding into a farming systems model to discern changes in global crop waterlogging under future climates. Third, we develop avenues for adapting cropping systems to waterlogging contextualised by environment. We find that yield penalties caused by waterlogging increase from 3-11% historically to 10-20% by 2080, with penalties reflecting a trade-off between the duration of waterlogging and the timing of waterlogging relative to crop stage. We document greater potential for waterlogging-tolerant genotypes in environments with longer temperate growing seasons (e.g., UK, France, Russia, China), compared with environments with higher annualised ratios of evapotranspiration to precipitation (e.g., Australia). Under future climates, altering sowing time and adoption of waterlogging-tolerant genotypes reduces yield penalties by 18%, while earlier sowing of winter genotypes alleviates waterlogging by 8%. We highlight the serendipitous outcome wherein waterlogging stress patterns under present conditions are likely to be similar to those in the future, suggesting that adaptations for future climates could be designed using stress patterns realised today.

Crop traits enabling yield gains under more frequent extreme climatic events.

Climate change (CC) in central China will change seasonal patterns of agricultural production through increasingly frequent extreme climatic events (ECEs). Breeding climate-resilient wheat (Triticum aestivum L.) genotypes may mitigate adverse effects of ECEs on crop productivity. To reveal crop traits conducive to long-term yield improvement in the target population of environments, we created 8,192 virtual genotypes with contrasting but realistic ranges of phenology, productivity and waterlogging tolerance. Using these virtual genotypes, we conducted a genotype (G) by environment (E) by management (M) factorial analysis (G×E×M) using locations distributed across the entire cereal cropping zone in mid-China. The G×E×M invoked locally-specific sowing dates under future climates that were premised on shared socioeconomic pathways SSP5-8.5, with a time horizon centred on 2080. Across the simulated adaptation landscape, productivity was primarily driven by yield components and phenology (average grain yield increase of 6-69% across sites with optimal combinations of these traits). When incident solar radiation was not limiting carbon assimilation, ideotypes with higher grain yields were characterised by earlier flowering, higher radiation-use efficiency and larger maximum kernel size. At sites with limited solar radiation, crops required longer growing periods to realise genetic yield potential, although higher radiation-use efficiency and larger maximum kernel size were again prospective traits enabling higher rates of yield gains. By 2080, extreme waterlogging stress in some regions of mid-China will impact substantially on productivity, with yield penalties of up to 1,010 kg ha-1. Ideotypes with optimal G×M could mitigate yield penalty caused by waterlogging by up to 15% under future climates. These results help distil promising crop trait by best management practice combinations that enable higher yields and robust adaptation to future climates and more frequent extreme climatic events, including flash flooding and soil waterlogging.

Detrimental effects of heat stress on grain weight and quality in rice (Oryza sativa L.) are aggravated by decreased relative humidity.

There is concern over the impact of global warming on rice production due increased heat stress, coupled with decreased relative humidity (RH). It is unknown how rice yield and quality are affected by heat stress and decreased RH during the grain filling stage. We conducted experiments in controlled growth chambers on six rice cultivars, varying in heat tolerance using 12 combinative treatments of three factors: two RH levels (75% and 85%), three temperature levels (the daily maximum temperature at 33 °C, 35 °C, and 37 °C), and two durations (8 d and 15 d after anthesis). Results showed that RH75% with temperature treatments significantly reduced grain weight, which was higher than RH85%. The same trend was also observed for both head rice rate and chalkiness. R168 was the most heat-tolerant cultivar, but it still had some differences in grain weight, head rice rate, and chalkiness between the two RH regimes. The lower RH was most detrimental at 35 °C, and to a lesser extent at 33 °C, but had a negligible effect at 37 °C. Our results provide a better understanding of temperature and RH's interaction effects on rice quality during the grain filling stage, suggesting that RH should be considered in heat tolerance screening and identification to facilitate rice breeding and genetic improvement.

iTRAQ-Based Quantitative Proteomics Analysis on Rice Anther Responding to High Temperature.

As one of the most important crops, rice provides the major food for more than half of the world population. However, its production is limited by many environmental factors, among which high temperature stress (HS) frequently occurs during anthesis and reduces its spikelet fertility. To explore the mechanism of HS tolerance in rice, we conducted a comparative proteomics analysis on the anthers between HS resistant and sensitive cultivars under different levels of high temperature. Under the same HS treatment, the resistant cultivar showed much higher spikelet fertility than the sensitive cultivar. Proteomic data showed that HS lead to the degradation of ribosomal proteins in the sensitive cultivar but not in the resistant one, which might result in the injury of protein biosynthetic machinery. In contrast, HS induced the increase of sHSP, ß-expansins and lipid transfer proteins in the resistant cultivar, which might contribute to its ability to tolerate HS. The results provide some new insights into the mechanism of rice HS response.

High Temperature Induced Glume Closure Resulted in Lower Fertility in Hybrid Rice Seed Production.

Predicted climate changes, in particular, the increased dimension and frequency of heat waves, are expected to affect crop growth in the future seriously. Hybrid rice relies on seed production from male sterile and restorer lines. Experiments were conducted over two consecutive years to compare the high temperature tolerance of parents of different hybrid rice combinations, in terms of fertility rate, flowering pattern, pollination and physiological parameters of the lodicule. Three male sterile lines and a broad compatibility restorer line (as pollen donor and conventional variety as well) were grown to heading stage and then treated with average daily temperatures of 26°C (range 23-30°C), 28°C (25-32°C), and 30°C (26-34°C), respectively, continued for 5-7 days each in a natural light phytotron which simulated the local typical high temperature weather in the field. The results indicated that male sterile lines were more sensitive to high temperature than the restorer line for fertility rate, and the sensitivity varied between varieties. The fertility rate of the restorer line was maintained at about 90% under the high temperature treatments, while it decreased in the male sterile lines by 23.3 and 48.1% at 28 and 30°C, respectively. The fertility rate of the most sensitive line declined by 70%, and the tolerant line declined by 34% at 30°C. Glume closure in the male sterile lines was a major reason for the reduced fertility rate under high temperature, which is closely correlated with carbohydrates content and the vascular bundle pattern in the lodicule. The present study identified a useful trait to select male sterile lines with high temperature tolerance for seed production.