An expert panel was convened in September 2019 by The International Scientific Association for Probiotics and Prebiotics (ISAPP) to develop a definition for fermented foods and to describe their role in the human diet. Although these foods have been consumed for thousands of years, they are receiving increased attention among biologists, nutritionists, technologists, clinicians and consumers. Despite this interest, inconsistencies related to the use of the term ‘fermented’ led the panel to define fermented foods and beverages as “foods made through desired microbial growth and enzymatic conversions of food components”. This definition, encompassing the many varieties of fermented foods, is intended to clarify what is (and is not) a fermented food. The distinction between fermented foods and probiotics is further clarified. The panel also addressed the current state of knowledge on the safety, risks and health benefits, including an assessment of the nutritional attributes and a mechanistic rationale for how fermented foods could improve gastrointestinal and general health. The latest advancements in our understanding of the microbial ecology and systems biology of these foods were discussed. Finally, the panel reviewed how fermented foods are regulated and discussed efforts to include them as a separate category in national dietary guidelines. Although fermented foods have been consumed for thousands of years, a clear definition has been lacking. This Consensus Statement outlines a definition for the term ‘fermented foods’ as determined by an expert panel convened by the International Scientific Association for Probiotics and Prebiotics in September 2019. They have remained staples of human diets for centuries and are an increasingly popular food category. Yet, their emergent popularity in the past 20 years has led to numerous misunderstandings and questions. What constitutes fermentation? Do fermented foods necessarily contain live microorganisms? Are fermented foods the same as probiotic foods? Do microorganisms in fermented foods become established in the gut or influence the gut microbiota? Do fermented foods provide health benefits and, if so, how?Fermented foods and beverages accompanied and likely facilitated the transition from hunter-gatherer communities to sessile agricultural communities in the Neolithic revolution about 14,000 years agoAccordingly, the International Scientific Association for Probiotics and Prebiotics (ISAPP) organized a meeting of clinical and scientific experts in family medicine, microbiology, food science and technology, ecology, immunology, and microbial genetics held in September 2019 to develop a consensus report on fermented foods (a category that includes fermented beverages). The main goals of this Consensus Statement are to provide researchers, health-care providers, industry, regulators and consumers with a clear and concise definition of fermented foods, to differentiate between fermented foods and probiotics, and to summarize what is known about the health effects and safety of fermented foods. This Consensus Statement also discusses the mechanistic rationale for how fermented foods could improve gastrointestinal and systemic health, the advancements in knowledge on the microbial ecology and systems biology of those foods, and the current regulatory considerations and position of these foods in dietary guidelines.The consensus panel was organized under the auspices of ISAPP, which is a non-profit organization governed by a volunteer board of directors. Although funded by member companies, ISAPP’s activities are not stipulated by industry. The mission is to provide objective, science-based information on probiotics, prebiotics and related health topics. Panel members were identified and invited based on their subject matter expertise and experience. An outline was developed and each expert was asked to address specific topics. The panel discussed each issue until consensus was reached. Following the meeting, each panellist wrote relevant sections and the assembled draft was reviewed and approved by all authors. The authors thank members of the ISAPP board of directors who did not directly participate in this consensus panel but who reviewed, provided comments and approved this manuscript: G. Gibson, E. Quigley, S. Salminen, K. Scott and H. Szajewska.3. Fermentation-associated microorganisms usually out-compete potential pathogenic and spoilage organisms, further enhancing food safety and stability. In the absence of potable water, fermented beverages, such as beer, wine, sour milk and cereal gruels, provided a safe and transportable source of liquids4. These qualities, along with the fermentation-mediated transformation of perishable raw food materials into organoleptically satisfying products, led to their adoption by nearly every culture worldwide.Humans must have learned early in their history that fermentation provided many important advantages for managing precious food resources. Fermentation can improve the functional properties of agricultural crops and transform bland raw materials into nutritious, palatable or intoxicating products. Certainly, fermentation would have been regarded as one of the most effective ways to preserve foods owing, in part, to the formation of organic acids, alcohols, bacteriocins and other antimicrobial end-products as a result of fermentation microorganisms5. The consumption of fermented milk products, including cheese, pre-date human lactase persistence, suggesting that lactose removal might have been one of the initial aims of this process6. Similarly, the human attraction to flavour-potentiating nucleotides and amino acids that are enriched in certain fermented foods, such as soy sauce and miso, could have evolved as a result of the safety and nutritional benefits of those foods in early human diets7. The extended shelf-life of fermented foods and the removal of noxious plant compounds by fermentation still serve critical purposes in regions of the world that have low food security and poor access to refrigeration, electricity and clean water. Even in societies for which sanitation and preservation are not a problem, fermented foods constitute an important part of the human diet. It is estimated that more than 5,000 varieties of fermented foods (and beverages) are currently produced and consumed globally8.One particular example of how fermented foods and human culture co-evolved is through dairy fermentations11. Nonetheless, with the exception of yoghurt and other cultured dairy products, few well-designed, randomized controlled trials (RCTs) on the health benefits of the array of fermented foods have been published. Likewise, hypothesis-driven research describing the mechanisms of how fermented foods affect human physiology is limited. Defining these gaps can provide a basis for future research, including experiments aimed at understanding the potential health benefits of fermented foods.Beyond their importance to public health and food preservation and quality, current epidemiological evidence suggests that diets rich in fermented foods can reduce disease risk and enhance longevity, health, and quality of life12. Although this definition might be relevant for anaerobic lactic and ethanolic fermentations13 that occur in yoghurt, kimchi or wine, it does not apply to numerous other food fermentations. Fermentation as applied to foods and beverages has a much broader meaning and includes reactions and pathways that do not involve any of the criteria implicit in the strict biochemical definition. For example, aerobic metabolism is used by fungi responsible for koji, the starting material for soy sauce and miso, and in the manufacture of vinegar and kombucha by acetic acid bacteria (AAB)15. Accordingly, the panel proposes a broader definition that accounts for these variations in metabolic pathways. Thus, we define fermented foods and beverages as: “foods made through desired microbial growth and enzymatic conversions of food components”.Biochemists define fermentation as “an ATP-generating process in which organic compounds act as both donors and acceptors of electrons”The definition requires the activity of microorganisms. Although endogenous or exogenous enzymes from plants, animals or other sources might be present, the activities of those enzymes alone are insufficient for a food to be regarded as fermented. This definition is sufficiently broad to include not only the fermentations noted earlier but also to distinguish fermentation from its microbiological converse, namely food spoilage. Whereas both processes occur via microbial growth and enzymatic activity on food constituents, spoilage is clearly unintentional and fermentation is deliberate and controlled to generate the desirable attributes.This definition of fermented foods and beverages accommodates the many products made globally from diverse starting materials Box . The def16. Of note, some cured meat products  can be fermented or non-fermented.Some salad dressing, mustard and other condiments might include ingredients made by fermentation such as vinegar or sour cream. In our view, these foods would not satisfy the definition of a fermented food, even if they contained an appreciable amount of a fermented ingredient Box , nor wouBox 1 Fermented food classification based on the presence of live microorganismsFermentedLive microorganisms presentYoghurtSour creamKefirMost cheesesMisoNattoTempehNon-heated fermented vegetablesNon-heated salami, pepperoni and other fermented sausagesBoza, bushera and other fermented cerealsMost kombuchasSome beersLive microorganisms absentBreadHeat-treated or pasteurized fermented vegetables, sausage, soy sauce, vinegar and some kombuchasWine, most beers and distilled spiritsCoffee and chocolate beans (after roasting)Not fermentedChemically leavened breadFresh sausageVegetables pickled in brine and/or vinegarChemically produced soy sauceSalted or cured processed meats and fishBox 2 Key conclusions of this consensus paperFermented foods are defined as foods made through desired microbial growth and enzymatic conversions of food components.Microorganisms  determine the course and outcome of fermentation processes and contribute to the development of the characteristic properties of the final fermented food.Fermented food products should only be labelled as ‘containing probiotics’ when there is evidence that their live microbial components provide health benefits and the precise microbiological content is defined.A modern understanding of patterns of microbial community succession during the fermentation and ageing of fermented foods is being obtained through the application of metagenomics, metatranscriptomics and metabolomics.A better understanding of the health effects of fermented foods based on data available from population-based diet and health studies as well as new randomized controlled trials are needed to clarify the role of the consumption of fermented foods and of the live microorganisms they might contain in human health.When properly made, fermented foods and the bacteria and fungi responsible for their manufacture have a long history of safe use.Fermented foods could benefit health through the nutritive alteration of the ingredients, modulation of the immune system, the presence of bioactive compounds that affect intestinal and systemic function, or by modulating gut microbiota composition and activity.17, the term ‘probiotic’ should only be used when there is a demonstrated health benefit conferred by well-defined and characterized live microorganisms. The health benefit must, at least in part, be due to the live microorganisms and must extend beyond any nutritional benefit of the food matrix. For these reasons, the terms ‘fermented food’ and ‘probiotics’ cannot be used interchangeably , but these uncharacterized and unidentified strains, at unknown doses, would not qualify as probiotics. By contrast, if L. plantarum 299v, a genetically characterized strain with clinically demonstrated probiotic properties19, was present at an efficacious dose until the end of shelf-life and there were no indications for inhibitory interactions of the sauerkraut matrix, this sauerkraut would meet the minimum criteria for a probiotic fermented food. Such products could contain an appropriately worded claim, for example, “probiotic sauerkraut containing L. plantarum 299v might improve intestinal well-being”, provided that local regulatory requirements are satisfied 22. However, in our view, even if the fermented food contains one or more of those species, the label “contains probiotics” should only be used when the strains in the fermented food are defined to the strain level, the genome sequences are known and the strains are present at an appropriate number during product shelf-life , AAB, bacilli or other bacteria, yeasts, or filamentous fungi. These microorganisms were among the very first to be isolated and characterized by Pasteur, Lister and other early microbiologists40. LAB include the reclassified members of the Lactobacillaceae or Lactobacillus genus complex41 and numerous other taxa, including species of Lactococcus and Tetragenococcus associated with milk and soy sauce fermentations, respectively. Besides LAB, particular species of Bacillus and AAB are solely responsible for some fermented foods  or have important supporting roles as is the case for Staphylococcus, Enterococcus, Brevibacterium and Propionibacterium in sausage and cheese fermentations43. Among the fungi, ethanol-producing yeasts, usually species of Saccharomyces, are used for bread, beer, wine and various alcoholic fermentations. Interestingly, the domestication of Saccharomyces cerevisiae strains and their adaptation to a range of fermentation substrates and environments has led to the formation of distinct lineages associated with particular products45.LAB are a group of Gram-positive, non-spore forming, aerotolerant bacteria that are phylogenetically positioned within the Firmicutes phylum, predominantly in the order Lactobacillales. They are among the most important and widely used microorganisms in food fermentations, serving essential functions in fermented dairy, meat, cereal and vegetable products46. Penicillium, Aspergillus and Rhizopus are among the moulds commonly used for fermented dairy, meat and soy products and include proteinase, lipase and amylase-producing strains47. As described later, many food fermentations involve microbial communities consisting of multiple genera and taxa.Similar domestication events are also likely responsible for the widespread use of atoxigenic filamentous fungi49. Since the twentieth century, pure starter cultures have been developed to provide consistency and convenience and to accommodate large-scale industrial fermentations50. Typically, only one or two microbial strains  are necessary to initiate those fermentations51. Although technological performance properties remain one of the main criteria, the isolation and development of new strains increasingly relies on relevant genomic information and on the application of available molecular tools54.Considerable progress has been made towards understanding the function of individual microorganisms in fermented food production and then using that information to improve products and strains. Phylogenomic analyses have shown that, despite their general biochemical and physiological similarities, wine, beer and bread yeast strains evolved independently based on habitat and geography as well as through human-driven domestication55. Molecular approaches have shown that fermented foods are frequently dependent on complex, multi-kingdom, microbial communities functioning in concert via dynamic succession processes59. However, despite this complexity, the presence of a so-called core microbiota  are often apparent in a wide range of fermented foods64. Provided that the starting materials are generally the same, spontaneous fermentations (relying on autochthonous or resident microorganisms present in the ingredients and/or surrounding environment) typically result in products that contain very similar microorganisms (even the same species), regardless of provenance65. For example, fermentations of cabbage and other green leafy vegetables are all initiated by Leuconostoc mesenteroides followed by Lactiplantibacillus species and Levilactobacillus brevis, independent of whether the product is called sauerkraut (Europe and North America), kimchi (Korea), suan-cai (China) or sinki 66. This highly reproducible succession of fermentation microbiota in spontaneous vegetable fermentations, whereby the assembly of fermentation microbiota is limited by dispersal, reflects the stable association of these organisms with the raw materials als Fig. . Similarare Fig. . In the 68.The outcome of a food or beverage fermentation process depends on the microorganism-led conversion of substrates into metabolites that support the aroma and taste, appearance, preservation, and nutritional properties of the finished product. These characteristics are time-dependent and determined by the microbiota as well as by a range of physicochemical parameters, including temperature, pH, water activity, oxidation–reduction potential and substrate availability. How these intrinsic and extrinsic environmental parameters are ultimately managed can have profound effects on the final properties and characteristics of fermented foods69. Although fermented foods have long been studied as model systems to understand microbial ecology70, these latest efforts integrate broader ecological and evolutionary principles, including dispersal, selection, drift and diversification73. The contribution of these principles to community assembly in fermented foods is outlined in Fig. 74, determine a genetic basis for particular microorganisms to live in a fermented food environment75 and recreate the domestication processes that generated the industrial cultures used in fermentations77. Ultimately, findings from those studies will help to address product variation and quality issues that occur even when starter cultures are used. They might also lead to the identification of biomarkers to monitor these foods throughout production and to predict nutritional and health-impacting qualities.Systems and evolutionary biology approaches are now providing a rational basis for controlling or managing microbial diversity and community structure to achieve different fermentation processes78. Likewise, beverages containing 4% or more alcohol and pH values less than 4.5 are also considered microbiologically safe79. Many LAB, whether part of the autochthonous microbiota or added as starter cultures, are known to produce bacteriocins that inhibit undesirable bacteria, including Listeria, Staphylococcus and Clostridium80.Fermented foods that contain appreciable levels of fermentation-produced organic acids (>100 mM), combined with low water activity, salt, nitrite and other antimicrobials, have a long record of food safety81. Bitter cassava, for example, contains cyanogenic glycosides that must be removed by fermentation, soaking or other suitable processes to avoid acute toxicity when consumed82. During sourdough fermentations, some LAB facilitate the degradation of phytate, a cereal grain-associated compound that chelates divalent cations and prevents their absorption in the gastrointestinal tract83. Reducing phytate results in enhanced calcium, magnesium, iron and zinc bioavailability from these breads86. Sourdough fermentation is also hypothesized to reduce the concentration of other immune-reactive proteins, including the amylase-trypsin inhibitor in wheat, and could therefore be better tolerated than conventional breads by individuals with non-coeliac wheat intolerance or irritable bowel syndrome87.Food fermentations can also enhance food safety and nutritional quality by removing toxic or anti-nutritive compounds from the raw ingredients. For example, the removal of toxic compounds is a prominent feature of cereal, legume and tuber fermentations88. When properly made from safe and wholesome ingredients, fermented foods are rarely associated with gastroenteritis. Nonetheless, some cheeses and low-acid fermented foods can pose a safety risk if the food is contaminated with Listeria monocytogenes, Salmonella, Clostridium botulinum or other foodborne pathogens89. Although not a direct effect on safety, some microorganisms, including species of the Lactobacillaceae as well as Enterococcus and Staphylococcus associated with long-ripened cheeses, sausages and other fermented foods, can carry transmissible antibiotic-resistance genes92.For any food product, there are safety concerns associated with live pathogenic microorganisms as well as toxins or metabolic products that can produce harmful effects. With few exceptions, food-fermenting LAB, yeasts and filamentous fungi are non-pathogenic and do not produce toxins or harmful end-products93. In the absence of host-mediated detoxification systems, these amines can cause mild to more severe effects such as migraines94. Several strategies have been adopted to reduce or mitigate biogenic amine formation, including hygiene to minimize the occurrence of microorganisms producing these compounds and using decarboxylase-negative starter cultures96.The microbial metabolites of some fermented foods can, under certain circumstances, also present safety risks. Alcohol  and salt  are inherent constituents of some fermented foods and should be consumed in moderation. Histamine, tyramine and other biogenic amines are formed by some LAB via the decarboxylation of amino acids during the fermentation of cheese, meats, vegetables, soybeans and wineAspergillus and Penicillium from koji, cheese and other fermented foods98. Other microbial metabolites, including citrulline and reuterin, are precursors of the toxic compounds ethyl carbamate99 and acrolein100, respectively. Both occur in alcoholic beverages as well as in other fermented foods. However, their risks to human health from the exposure to fermented foods have not been established102.Mycotoxins are a potential concern for all fermented foods produced with filamentous fungi. However, domestication and careful strain selection have effectively eliminated mycotoxin-producing lineages of 103. However, except for yoghurt and cultured dairy products, few human clinical studies have been performed to verify their benefits104. Yoghurt consumption is associated with reductions in adiposity factors 105, type 2 diabetes mellitus and cardiovascular disease (see reviews107), among other positive indications108. Although much of this evidence is based on prospective or epidemiological studies, more than 20 RCTs with yoghurt and cultured milk products have been reported for both healthy individuals and patient population groups109. Likewise, milk kefir110, kimchi111, sauerkraut112, natto113, vinegar114 and sourdough bread115 have been investigated in at least one RCT. By contrast, evidence of health promotion for other fermented foods  is mostly limited to chemical analyses and animal and cell culture models24.Consumer interest in fermented foods has been driven in large part by their suggested nutritional benefits, and this interest has led to renewed popularity of these foods on nearly every continent116 and efforts should be made to avoid misleading or unwarranted conclusions117. It should be noted that additional challenges exist for cohort studies because dietary databases do not often include fermented foods as a category and critical aspects of those foods might not be reported .A better understanding of the health benefits of fermented foods will be obtained from harvesting information from existing population-based diet and health databases as well as with new RCTs. These studies should address the health outcomes arising from the intake of differentiated fermented food categories (including fermented dairy products and other fermented foods with living versus dead microorganisms), food types , and individual fermented food products with well-characterized strains and nutrient compositions. Large, placebo-controlled RCTs will need to account for the known limitations of these types of nutrition study, including blinding, sample size, diet control, dietary recall and adequate intervention times, as well as the challenges specific to fermented foods . To prevent the foods from being easily distinguished by study participants, placebo controls might need to be made to provide the same sensory attributes expected for the fermented foods being tested. Retrospective cohort or, preferably, prospective cohort studies that meet the Bradford Hill criteria should be usedKnowledge on the specific health-promoting properties of fermented foods provides a foundation to evaluate how those properties vary by food type, strain composition and production methods. Several routes for health promotion by fermented foods are proposed Fig. , includi118. Microorganisms reduce the concentrations of high-calorie monosaccharides and disaccharides  present in milk, meat and plants via catabolic pathways. Reductions in certain sugars could also reduce the glycaemic index120 and improve food tolerability 121. Fermentation can result in the hydrolysis of polysaccharides, proteins or fats, thereby increasing their digestion124. Other enzymatic transformations with important nutritional implications also occur, including detoxification reactions  and the removal of anti-nutritive factors 127. For polyphenol-containing foods, the conversion of phenolic compounds by lactobacilli128 increases the bioavailability of flavonoids, tannins and other bioactive compounds130. The biosynthesis of vitamins, amino acid derivatives, organic acids and cofactors can also occur during fermentation132, with effects at either local gastrointestinal or systemic sites. Some of these compounds are broadly distributed between fermented food types (such as lactic acid133 and acetic acid134), whereas others are common in certain foods  or limited to certain microorganisms with specific enzymatic activities .Microbial activity during food fermentations results in the enrichment and/or removal of compounds that affect the nutritional composition of the final food product144. Indeed, many of the LAB that dominate lactic acid-fermented foods possess intrinsic characteristics that promote their ability to survive gastric transit 145. Depending on individual dietary habits, fermented food-associated LAB can transiently constitute between 0.1% and 1% of the bacteria in the large intestine and a comparable proportion in the small intestine145. This percentage is based on current estimates of autochthonous microbiota in the gastrointestinal tract146 and the presence of up to 1011 LAB cells in a single serving of many fermented foods, such as yoghurt or kefir, that contain live and active microorganisms. Similarly, another study published in 2020 showed that food-associated LAB reached faecal metagenome abundances of >0.1%147. Although these microorganisms are unlikely to maintain long-term residence in the intestine, some fermented food microorganisms are known to be metabolically active in the gastrointestinal tract148, and short-term colonization could be sufficient to synthesize bioactive compounds, inhibit intestinal pathogens and mediate epithelial modulatory effects . Such interactions would be augmented by the repeated daily consumption of the fermented food. According to population-based studies and RCTs, fermented foods can also influence the composition of the gut microbiota153. Modulation of the gut microbiota can result from the living (or inactivated) microorganisms in those foods, the nutritional components and metabolites released as a result of fermentation, and changes these food constituents confer on the host immune system. These effects are likely dependent on inter-individual differences in host physiology and gut microbiota composition154.Multiple studies in humans have shown that microorganisms in fermented foods can survive gastric transit and reach the colon155, foods and beverages are the major conduit of contact between external antigens and the human body. The gastrointestinal tract is vulnerable to the initial pattern of microbial colonization during the first months of life156, potentially setting a critical window for microbial stimuli effects on the immune system. In one cross-sectional study, fermented food intake (fermented vegetables) during early childhood was associated with a reduced risk of childhood atopy158. In another epidemiological study, fermented food consumption combined with common daily-life exposure  also reduced the risk of childhood allergies158. The authors from the former study further reported that an anthroposophic lifestyle (low antibiotic use and vaccinations and high intake of fermented vegetables) was associated with differences in infant microbiome structure, including a higher abundance and diversity of LAB, and a higher concentration of acetate compared with infants from a traditional lifestyle159. Fermented food intake is also one of the synergistic factors associated with a farming upbringing, a lifestyle factor that has consistently been associated with reduced allergy and asthma risk (reviewed elsewhere160). These associations could indicate that a lack of fermented foods in modern, industrialized societies constitutes a substantial loss in exposure to non-harmful microorganisms important for immune system development and maintenance.As approximately 70% of the human immune system is located in the gastrointestinal tract161 have been shown to modulate immune responses in numerous animal models, RCTs or prospective studies on the human immune system have yet to be performed. It is expected that the modulation of the human immune system by fermented foods would be the result of the combined effects of compounds present in the starting ingredients and those formed during fermentation as well as of living and dead or inactivated microorganisms. Those fermentation-associated microorganisms and their cell components  are already known to be immune reactive according to animal model and in vitro studies164. Knowledge about other immune-modulating compounds, such as d-phenyllactic acid, produced by lactic acid bacteria in situ165, is still emerging. Ultimately, the precise molecular stimuli in fermented foods responsible for immunomodulation probably depend on the total composition of the product166.Although fermented foods such as milk kefir168. The use of microbial cultures is also regulated and includes criteria for establishing safety, such as the ‘Generally Recognized As Safe’ designation in the USA or the ‘Qualified Presumption of Safety’ list in Europe. The latter, for example, is a designation assigned by the European Food and Safety Authority to groups of microorganisms that, in general, do not raise safety concerns as components of foods, including fermented foods169. Strains developed by the use of recombinant DNA technology or those that are genetically modified have different regulatory controls. For example, in the USA, genetically modified strains must have a ‘Generally Recognized As Safe’ status, whereas in Europe, such products require Qualified Presumption of Safety status170.Guidelines that govern food fermentation are covered in international regulations and are mainly concerned with food safetyS. thermophilus and L. delbrueckii subsp. bulgaricus and that kefir is a fermented milk consisting of Lentilactobacillus kefiri and species of the genera Leuconostoc, Lactococcus and Acetobacter, in addition to lactose-fermenting yeasts (Kluyveromyces marxianus) and non-lactose-fermenting yeasts 171. Similar standards could emerge as the microorganisms present in other fermented foods are identified .The identification of core microbial components in fermented foods has the potential to lead to new regulations around the labelling of these foods. Regulations could be used to ensure that minimum requirements relating to the involvement of specific microbial taxa in the fermentation process are met. Only a few standards exist, mostly for cultured dairy products. For example, the Codex Alimentarius states that yoghurt should be made using a combination of 173. However, with few exceptions, fermented foods are generally absent as a recommended category in dietary guidelines175. The only country, to our knowledge, that has a specific guideline is India, which encourages pregnant women to consume fermented foods176. Other countries, including the USA and Canada, mention yoghurt and kefir in the dairy products section138, but there is no specific emphasis on fermented foods. Owing to the high levels of live, potentially health-promoting microorganisms in many fermented foods, these foods have been advocated for inclusion in dietary recommendations174. To advance this field, studies that collect dietary information should also track foods that contain live cultures. Adding granularity to dietary intake data so that fermented foods are not subsumed under other categories will enable researchers to better understand the role of these foods in health.Fermented foods are widely consumed around the world and have been estimated to account for approximately one-third of the human dietOne of the main goals of this panel was to bring scientific clarity to the rapidly growing field of fermented foods and beverages. We anticipate that the outcomes described in this report Box  could afAlthough consumers have become increasingly interested in fermented foods, it is unfortunate that, in our opinion, much information available on fermented foods in popular press magazines, websites and social media is exaggerated or inaccurate. For example, on the many internet and popular magazine lists of the ‘best super foods’, fermented foods are often ranked at the top. Such labels, while perhaps useful for marketing, do not convey accurate information for consumers regarding nutritional or other specific properties of fermented foods. Furthermore, as discussed earlier, fermented foods are frequently considered as probiotic foods, even when live microorganisms are absent in the final product and the health benefits have not been clinically demonstrated. This report clarifies these points for consumers and communicators.177. Food fermentation can also provide new strategies for industry to address contemporary socioeconomic and health challenges involving ageing, malnutrition and obesity178. Manufacturers who produce and market fermented foods can benefit from clear definitions and criteria for what constitutes probiotic fermented foods. In particular, we reaffirm the statement in Hill et al.17 that fermented foods are not equivalent to probiotic foods. Many fermented food products have no evidence that their live microbial component provides health benefits and the precise microbiological content is rarely defined. Without this level of characterization, they should not be labelled as “containing probiotics”. Some manufacturers supplement fermented foods with microorganisms after a heat treatment, perhaps to satisfy consumer interest in adding live microorganisms to their diet. These products, in our view, do not reflect the expected characteristics of fermented foods containing live microorganisms. In general, there is no expectation that fermented foods must contain live microorganisms. The most notable exception is for yoghurt, where, depending on the jurisdiction, specific requirements can exist. Industry is responsible for producing fermented foods following good manufacturing practices and should practice advertising and labelling that is truthful and informative and should be consistent with the criteria stipulated above.As noted previously, fermented foods and beverages were among the first processed foods. Bread, beer, wine and fermented dairy, soy and other products continue to represent a considerable portion of the total processed foods industry. This form of processing remains extremely important in many parts of the world, whereby fermented foods can enhance both food security and sustainability179. Similar arrangements also exist in other countries. Although the Protected Designation of Origin framework is designed to control product claims about geographical origins and production practices and not microbiological properties of foods, per se, these protections can dictate the type or nature of the cultures used in cheese, sausages, bread, vinegar and other fermented foods. Thus, for these products, governments can indirectly influence how fermented products are produced as well as the safety and quality properties. This process is especially relevant as industrialization and high-throughput production practices have been adopted even by traditional small-scale manufacturers180.In most jurisdictions, governments provide regulatory oversight of the safety and marketing of fermented foods, including advertising, product labelling and health benefit claims. In Europe, a broad range of fermented foods are made in accordance with so-called Protected Designation of Origin requirements that impose geographical, manufacturing and quality requirementsGovernment agencies are also responsible for providing accurate and informative nutritional labelling and for reviewing and approving health benefit claims. However, as already noted, most regulatory agencies have not considered the potential inclusion of fermented foods in dietary guidance programmes beyond their nutritional contribution to health. Nonetheless, as more clinical and epidemiological studies are reported, such efforts could be warranted.50. Many spontaneously fermented foods serve as a rich reservoir of potentially valuable strains183. Of particular interest is the possibility of predicting the quality attributes of fermented foods and beverages based on the initial microbial composition of the raw materials. Ultimately, the production of fermented foods and beverages with greater quality control will ensure the delivery of products that provide flavour, texture and health-related attributes.For more than a century, microbiologists have sought to identify and describe the relevant ‘microbial parts’ within fermented foods and beverages. Only in the past two decades have researchers from multiple scientific disciplines, including systems and molecular biology, microbial ecology, and bioinformatics, begun to understand how those parts are assembled to build microbial communities that are ultimately responsible for the attributes associated with fermented foods and beverages. Collectively, this research provides a rational basis for improving both the functional characteristics and nutritional properties of these foods. It could also be feasible to identify and introduce novel microbial species that can augment desirable traits


Neonatal hyperbilirubinemia is a common benign phenomenon, related to a variety of physiological, pathological, and genetic conditions of neonates . Since t*60(−3279T>G) and UGT1A1*6(−3156G>A) are situated in very close proximity (In this well-designed cross-sectional study, the genetic sequencing was fully performed in different parts of the UGT1A1 gene, which is related to Gilbert syndrome . Finallyroximity .An important concept in genetic polymorphism is linkage disequilibrium. It means that two genes are physically linked to each other, and alleles do not occur randomly with respect to each other .D′ value was high, in their analysis, two mutations were considered as one. For this reason, they have to decide to test this mutation together either or alone.In conclusion, due to the high likelihood of these two mutations moving together , the resAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


O. barthii), cultivated and landraces , and improved varieties derived through interspecific hybridizations. A total of 1,527 DNA samples were genotyped with 46,818 polymorphic single nucleotide polymorphisms (SNPs) using DArTseq. Various statistical analyses were performed on eleven datasets corresponding to 5 plants per accession individually and in a bulk (two sets), 10 plants individually and in a bulk (two sets), all 15 plants individually (one set), and a randomly sampled individual repeated six times (six sets). Overall, we arrived at broadly similar conclusions across 11 datasets in terms of SNP polymorphism, heterozygosity/heterogeneity, diversity indices, concordance among genetic dissimilarity matrices, population structure, and genetic differentiation; there were, however, a few discrepancies between some pairs of datasets. Detailed results of each sampling method, the concordance in their outputs, and the technical and cost implications of each method were discussed.To minimize the cost of sample preparation and genotyping, most genebank genomics studies in self-pollinating species are conducted on a single individual to represent an accession, which may be heterogeneous with larger than expected intra-accession genetic variation. Here, we compared various population genetics parameters among six DNA (leaf) sampling methods on 90 accessions representing a wild species ( Using limited numbers of accessions and/or agro-morphological traits and markers in different species, previous studies assessed intra-accession genetic diversity using morphological and isozymes5, amplified fragment length polymorphisms (AFLP)6, random amplified polymorphic DNA (RAPD)7, inter simple sequence repeat (ISSR)9, and simple sequence repeats (SSR) markers10. RAPD, AFLP, and ISSR markers are currently becoming obsolete for germplasm characterization for multiple reasons, including dominant inheritance, low reproducibility, low throughput for genotyping thousands of collections conserved at most genebanks, low marker density (genome coverage), poor resolution associated with the size-based fragment analysis system, and difficulty in merging multiple datasets generated by different collaborators or labs11. SSR markers are codominant and more reproducible, with better genome coverage than AFLP, RAPD and ISSRs; however, they are not well suited for large-sale characterization of genebank collections, primarily due to lower throughput, high genotyping cost, and difficulty in merging genotypic data generated by multiple collaborators or labs due to their ability in detecting multiple alleles, stuttering, and addition or omission of a nucleotide during polymerase chain reaction (± A) that causes ambiguity in automated fragment analysis systems using capillary DNA sequencers14.The levels and distributions of intra-accession (within-accession) genetic diversity in genebank collections provide invaluable information for diverse purposes, including (a) deciding the number of seeds (plants) per panicle (ear) and the number of panicles per accession (or variety) that should be sampled and conserved to capture given attributes; and (b) serving as baseline data for germplasm management and distribution as well as monitoring genetic variation and integrity during conservation and regeneration16. These include germplasm curation17; generation of high-density reference genotypic data18 and molecular passport data19; gene discovery using genomewide association studies and selective sweep analysis22; understanding the genetic profiles of the entire collection23; identifying redundant collections and creating subsets of genetically unique accessions for genetic and breeding studies25; and correcting mislabeled, taxonomically misclassified and/or misidentified collections27. Using GBS, for example, nearly 33% of the 22,626 barley accessions at the Leibniz Institute of Plant Genetics and Crop Plant Research’s 19 and 50% of the 1,143 accessions of a wild relative of wheat (Aegilops tauschii)17 were found to be potential duplicates.The availability of low-cost next-generation sequencing (NGS) technologies that generate high-density genome-wide SNPs is providing genetic resource scientists tremendous opportunities to enhance the quality, efficiency, and cost-effectiveness of genebank operationsOryza barthii A. Chev., O. glaberrima Steud. (African rice) and O. sativa L. (Asian rice) using DArTseq technology28. The DArTseq-based SNPs were highly useful for a wide range of purposes, including (1) understanding the genetic diversity, population structure, and genetic differentiation among African rice (Oryza glaberrima Steud.) collections, and developing core and minicore sets25; (2) developing species- and subspecies-diagnostic SNP markers to minimize misclassification, misidentification and mislabeling errors during germplasm acquisition and routine genebank operations26; (3) identifying candidate genes using selective sweep analysis21; and (4) comparing the extent of genetic variation and relatedness among various landraces and improved intraspecific and interspecific rice varieties developed by AfricaRice breeders with those developed by other institutions29. Based on the pilot study, we aim to genotype the entire rice collection conserved at AfricaRice using DArTseq and use the data to improve our germplasm curation. We will create subsets of the most genetically diverse accessions for further field evaluation, gene discovery, trait donor selection, and pre-breeding, which will ultimately promote the use of the collections in rice improvement. To reduce genotyping costs per accession, most molecular characterization studies in self-pollinating species are conducted by randomly sampling a single plant to represent an accession. This has been the case in our previous studies and other studies in rice31, barley19, and wild relatives of wheat17. Single plant samples have provided invaluable data for assessing inter-accession genetic diversity, relatedness and population structure in self-pollinating species, but are not suitable for measuring intra-accession diversity, which forms one of the bases of the current study. Furthermore, a single plant genotype data may be misleading when the extent of intra-accession diversity is greater than expected for different reasons, including a higher level of outcrossing33, phenotypic heterogeneity, seed admixture, pollen contamination and off-types, which is another basis for this study. For example, sorghum landraces and wild rice showed an outcrossing rates that varied from 5 to 40%32 and from 4 to 25%33, respectively. As a result, there is concern among the genetic resources scientists that results based on a single individual genotype may not be comparable with multiple plants per accession, genotyped either individually or in bulks17.Recently, our team at the AfricaRice center implemented a pilot study to characterize 4,115 rice accessions representing 35 refers to the genotyping of bulks of individuals using either plant tissue bulking or DNA pooling36. In outcrossing species, the bulking method has been commonly used for quick and economic genotyping of inbred lines, populations, and open-pollinated varieties for different purposes39. In selfing species, however, bulk segregant analysis has been used primarily for mapping genes and quantitative trait loci (QTL) associated with target traits of importance in breeding44. Some researchers have recommended bulking (pooling) method for characterizing multiple individuals per accession as the basis for evaluating genetic identity and diversity within accession in self-pollinating species17, but this method also has its limitations, including knowing the minimum number of individuals required in the bulk15, and the sensitivity of the genotyping platforms in detecting rare alleles due to allele dilution problems45. The alternative method of genotyping multiple plants per accession individually may be ideal for capturing rare alleles and estimating intra-accession genetic diversity but will increase the genotyping costs per accession multi-fold. The objectives of this study were, therefore, to: (1) assess intra-accession and inter-accession genetic diversity in 90 rice accessions, each represented by six leaf sampling methods ; (2) compare the concordance among the different sampling methods with respect to species  and genetic backgrounds of the germplasm (wild vs. landraces vs. improved); and (3) compare the outputs of the different datasets and assess if there were cases where one method provided obvious advantages over the others as well as the cost and technical implications of each method for large-scale germplasm curation and characterization in selfing species.Bulk segregant analysisO. barthii (18), landraces of cultivated species of O. glaberrima (21), O. sativa subsp. indica (19), O. sativa subsp. japonica (18), and improved interspecific varieties/genotypes derived from crosses between O. glaberrima and O. sativa (14) . Three DNA samples had over 70% missing data points and were excluded from the dataset. The genotype data of the remaining 1,527 samples were imputed using Random Forest46, which is implemented as “randomForest” in the R package47.This study was conducted using a total of 1,527 DNA samples from 90 accessions and varieties  that represented a wild 48 implemented in NTSYSpc v2.149. Because genotyping errors may account for about 1% of observed differences51, it is often difficult to consider SNPs with minor allele frequency < 0.01 as polymorphic sites. For that reason, we filtered the imputed genotype data using a minor allele frequency (MAF) of 0.01 and maximum heterozygosity of 0.50, which formed dataset Set-1 that consisted of 15 individual samples and two bulks. In this study, we used heterozygosity for simplicity to refer both to heterozygosity in the individuals (single plants) and heterogeneity in the bulks. Eleven additional subsets of data were created from Set-1 corresponding to all 15 plants individually (Set-2), a bulk of 5 plants (Set 3), another bulk of 10 plants (Set-4), and randomly selected individuals from Set-2 repeated 6-times (Set-5 to Set-10), 5 plants individually (Set 11) and 10 plants individually (Set 12).To evaluate the accuracy of the imputed SNPs in genetic diversity and population structure analyses, we first computed identity-by-state (IBS)-based genetic distance matrices from the 67,728 SNPs before and after imputation and compared the two distance matrices using the Mantel test25. Briefly, heterozygosity, IBS-based genetic distance matrices, and principal component analysis (PCA) were computed using TASSEL v.5.2.5852. The first two principal components (PCs) from the PCA were plotted for visual examination in XLSTAT 2012  using species/subspecies and predicted group memberships from phylogenetic and population structure analyses as categorical variables. The correlation between pairs of genetic distance matrices was computed using the Mantel test48 implemented in NTSYSpc v2.149. The HapMap format of each dataset was exported to PHYLIP interleaved format using TASSEL v.5.2.57, which was then converted to MEGA X53, STRUCTURE v.2.3.454 and ARLEQUIN v.3.5.2.255 formats using PGDSpider v.2.1.1.356. We used Molecular Evolutionary Genetics Analysis (MEGA) X to compute the pairwise maximum composite likelihood (MCL)-based genetic distance between DNA samples and accessions, for constructing phylogenetic trees using the neighbor-joining method, and for computing number of segregating sites (S), the proportion of polymorphic sites (Ps), Theta (θ), and nucleotide diversity (π). A site (SNP) was considered segregating if it had two or more nucleotides at that site; π refers to the average number of pairwise nucleotide differences between two sequences (samples), while θ was used as another estimator of diversity parameters based on the number of segregating sites in the samples. Phylo.io57 was used for comparing pairs of phylogenetic trees side-by-side as well as for computing Robinson-Foulds (RF) distance58 and number of subtree prune-and-regraft (SPR) distances60 between pairs of phylogenetic trees. For such purposes, Newick files were generated for each dataset using MEGA X and used as inputs into Phylo.io.Most of the statistical analyses were performed as described in previous studies54 as described in the previous studies61. DNA samples and accessions with membership probabilities > 60% were assigned to the same clusters (group), while those with probabilities < 60% in any group were assigned to a “mixed” group. Analysis of molecular variance (AMOVA)62 and FST-based pairwise genetic distance matrices63 were computed among and within groups using ARLEQUIN v.3.5.2.255. Accessions were assigned into 3–5 groups (populations) based on their species/subspecies, ecologies or group membership predicted from the phylogenetic and population structure analyses.Population structure was analyzed using the model-based method implemented in the software package STRUCTURE v.2.3.4Of the 67,728 SNPs used for genotyping the 1,527 DNA samples  and upland  ecologies had θ and/or π values ranging from 0.061 to 0.205 in at least one of the three datasets, which may be due to broader intra-accession diversity or to errors that might have occurred during genotyping and/or sample preparation . To determine the cause of such unexpectedly large intra-accession diversity within these accessions, we compared pairwise IBS-based genetic distance for the 15 individuals in Set-2. Figure As summarized in Fig. O. barthii (2), O. glaberrima (12), O. sativa (29); the latter includes indica (2), japonica (15) and interspecific genotypes (12). The 15 individuals from each of 4 other accessions were divided into two distinct but genetically similar sub-clusters.Figure O. barthii and O. glaberrima appeared nearly identical in the PCA plot because only 40% of the 46,818 SNPs were polymorphic within these two species as compared to 65% of the SNPs that were polymorphic among the O. sativa accessions.We observed nine accessions  that differed by at least 5% of the scored alleles based on π, θ and IBS-based genetic distance between pairs of individuals from within the accession; all these accessions except WAB0029281 each had 1–3 samples that did not cluster together with the other individuals originating from the same accession in the phylogenetic tree. The first five principal components from PCA performed in Set-2 accounted for 70.6% of the variation observed across the 1,347 individuals  and heterozygosity estimated per SNP ranged from 0.902 to 1.00 (mean of 0.965) across all datasets  the three groups predicted based on cluster analyses, PCA and the model-based population structure analyses (see below). Mantel correlations between datasets varied from 0.270 to 0.991 in O. glaberrima, from 0.878 to 0.999 in O. barthii, from 0.786 to 0.999 in indica, from 0.741 to 0.995 in japonica, and from 0.906 to 0.999 in interspecific improved genotypes. The lowest Mantel correlation coefficients were, therefore, observed within O. glaberrima, which is also evident from relatively inconsistent frequency distributions of the genetic distance matrices. When groups predicted based on the multivariate methods were considered, Mantel correlation coefficients among the distance matrices computed from all datasets were higher in the O. glaberrima/O. barthii group (0.945 ≤ r ≤ 1.000), followed by O. sativa adapted to the lowland (0.878 ≤ r ≤ 0.999) and upland (0.749 ≤ r ≤ 0.990) ecologies  and the upland (primarily japonica) ecologies were assigned into the second and third groups, respectively. The phylogenetic trees constructed from the other datasets revealed similar grouping patterns and are summarized in Supplementary Fig. O. barthii accession (WAB0028942) clustered together with O. glaberrima accessions, while another O. barthii accession (WAB0038213) clustered with O. glaberrima in Set-2, Set-11, and Set-12. Robinson-Foulds (RF) and SPR distances computed as measures of differences (disagreements) between pairs of the neighbor-joining phylogenies constructed from all datasets varied from 0.15 to 0.76 (RF) and from 7 to 37 (SPR)  or very great (> 0.250) genetic differentiation65, which varied from 0.154 to 0.819 between pairs of the 5 groups, from 0.261 to 0.827 between pairs of the four groups and from 0.453 to 0.785 between pairs of the three groups  and the number of groups used in the analyses , O. sativa (772) and O. glaberrima  with 26,073 physically mapped SNPs21, with each accession represented by a single plant after seed purification25. There are, however, concerns regarding the development of purified seed lots and/or use of a single individual to represent a genebank collection, especially in landraces and wild accessions. First, seed purification of thousands of accessions conserved at a given genebank incurs additional financial resources, personnel, time, and space. Since each accession can be then split into two or more new seed lots after purification, these additional resources are needed not only for purification but also for managing/maintaining the purified seed lots68. Second, most genebanks do not have clear strategies to manage the purified germplasm sets (seed lots). Third, the genotypic data generated from a single individual per accession with or without seed purification may not capture the genetic variation available within a given collection. Finally, genotyping of bulks of multiple individuals per accession for genomic studies in selfing species has been suggested17 but is not yet commonly used in inbreeding species, although is it commonly used for similar purposes in cross-pollinating species70. To the best of our knowledge, therefore, this is the first extensive and systematic study to generate well-designed empirical data for assessing the level and distribution of intra- and inter-accession genetic diversity across different leaf/DNA sampling methods in three rice species and different genetic backgrounds using genome-wide SNPs.In most genomics studies of self-pollinating species held in genebank collections, each accession is often represented by genotype data taken from a single randomly sampled individualO. glaberrima (see below) when analyses were done on a priori known groups.Overall, the various types of univariate and multivariate analyses performed in the present study revealed relatively consistent patterns of marker polymorphisms, heterozygosity, intra-accession, and inter-accession diversity indices, genetic dissimilarity, population structure, and genetic differentiation irrespective of the sampling methods. Of the 1,527 DNA samples used in the present study, (1) 96.5% of the single plant DNA samples originating from the same accession clustered together as expected and only 3.5% of the individuals clustered with other accessions; (2) the two bulks of 5 and 10 plants within an accession consistently clustered with the 15 single plant samples in 95.6% of the 90 accessions; (3) θ and π computed as measures of genetic diversity within each accession were smaller than 0.06 in 81 of the 90 accessions, which suggests greater than expected intra-accession diversity within 10% of the accessions; (4) there were highly comparable patterns of polymorphisms (98.8–99.9%) among all datasets irrespective of the sampling methods (Supplementary Table O. glaberrima (1 accession), O. barthii (2 accessions), and O. sativa adapted to the lowland (6 accessions) and upland (7 accessions) ecologies. Pairwise differences among the multiple individuals of these accessions have been summarized in Figs. 19. In a genomic study of barley genebank accessions using GBS, there were 32 accessions represented by 10 individuals each that revealed varying degrees of intra-accession diversity. About 34% of the 32 barley accessions showed very little intra-accession diversity, while 16% showed an intra-accession divergence that was equivalent to inter-accession diversity19. Using morphological and isozyme markers, intra-accessions genetic diversity has also been reported in another study of barley landraces conserved in genebanks for 10–72 years5. In most accessions, our results obtained from the two datasets corresponding to the 5 and 10 single plants were highly similar to those of the 15 individuals.Although our genotypic data for the 5–15 individuals per accession did not provide strong justification for compensating the 4–14-fold increase in sample preparation and genotyping costs compared to using a single plant, we observed some level of disagreement between datasets within some accessions, which included 45. O. glaberrima was the only exception that showed lower correlations between distance matrices computed from the 5–15 individuals in Set-2, Set-11 and Set-12 vs. the bulks of 5 and 10 plants in Set-3 and Set-4 (0.477 ≤ r ≤ 0.690), which may either be due to the genetic background of this species and/or an ascertainment bias in the SNPs. Although ascertainment bias is minimal with genotyping by sequencing technologies, it may arise when marker data is not obtained from a random sample of the polymorphisms71, which could occur in the current study due to the use of the O. sativa spp. japonica (cv. Nipponbare) reference genome for aligning marker sequences. Some level of ascertainment bias may have also been introduced by the Random Forest46 imputation method used in this study, as has been reported in another study in wheat72.To capture the larger intra-accession diversity observed within some of the accessions, we recommend a single bulk of either 5 or 10 individuals instead of genotyping 5–15 plants individually per accession; this is evident from the very high positive correlations (0.871 ≤ r ≤ 0.995) between distance matrices computed from Set-2, Set-3, Set-4, Set-11 and Set-12 , and mixing of samples are common problems in genebanks15 and have been reported in several species, including multiple Oryza species74, Dioscorea spp.75, Brassica spp 76. and Solanum spp.77. The percentage of mislabeled or misclassified samples reported in the literature is highly variable depending on sample size, the species, and the methods used for assessing the error rates, which varied from 3 to 21%77. In one of our recent studies, we found that 3.1% of 3,134 of accessions from four rice species were either mislabeled or misclassified26, which can easily be checked using a subset of the diagnostic SNPs that we developed in the previous study. Misclassification and mislabeling not only restrict the effective use of the germplasm for various purposes but also provide an erroneous estimate of intra-accession and inter-accession genetic diversity; in such cases, the presence of larger intra-accession genetic diversity can be an indication of errors rather than genetics/biological.Overall, the different DNA sampling methods revealed very consistent patterns of genetic relationships, population structures, and genetic differentiation irrespective of species, genetic background, and predicted group memberships Fig. . Howeverees Fig. . The mis80, all of which are of little relevance in characterizing genebank collections. In germplasm characterization, phylogenetic trees are primarily used to understand the broader pattern of evolutionary relationships; the level of genetic divergence; the definition of groups (populations or sub-populations); the selection of subsets of accessions that capture the genetic variation of a given group; and the identification of potential duplicates. In such cases, it is often difficult for genetic resource scientists to determine the true historical relationships between any groups of accessions other than using the bootstrapping method for assessing the accuracy or confidence in phylogenetic trees81. Although some studies advocate for bootstrapping, other studies believe that bootstrap values are a poor measure of repeatability82 depending on (1) the methods used for computing similarity/dissimilarity matrices; (2) the algorithm/methodology implemented in constructing the phylogenetic trees and for assessing disagreements between pairs of trees80, and (3) the lack of clear-cut threshold bootstrap values (which vary from 70 to 100%) that is used to judge whether a given node is good or not. Furthermore, displaying nodal support bootstrap values is difficult for large datasets84, which are typical of large-scale germplasm curation and characterization studies.Both Robinson-Foulds and SPR distances computed as measures of disagreements between a pair of phylogenies revealed that the phylogenetic tree constructed from the 15 individuals in Set-2 had the highest concordance with those in Set-12 , followed by Set-11 . All other values suggest a low to moderate concordance among pairs of phylogenies , which returns between 22,000 to 47,000 polymorphic SNPs in rice. A small sample size can underestimate genetic diversity parameters, and excessive sampling inflates costs2. Sampling 5–15 plants per accession instead of one provides more intra-accession information, but it does inflate sampling, DNA extraction, and genotyping cost 4–14-fold. In the present study, for example, genotyping of 5, 10, and 15 individuals incurred an additional cost per accession of US $88, $198, and $308, respectively. Currently, the AfricaRice genebank holds 21,300 accessions (https://www.genesys-pgr.org/), which would cost ~ US $2.4 and $7.1 million for genotyping 5 and 15 individuals per accession, respectively, compared to $468,600 for genotyping either a single individual or a bulk. Because we arrived at broadly similar conclusions regardless of sampling methods for most applications, we do not believe the additional information obtained by genotyping 5–15 individuals justify the multi-fold increase in cost. Furthermore, sampling of 5–15 individuals per accession across thousands of accessions raises another concern in that the technical feasibility of sampling, processing, and tracking so many individuals, followed by managing the high-density genotypic data, will be extremely challenging87. Recently, our team genotyped 4,115 rice accessions with ~ 32,000 SNPs using DArTseq, which generated 650-megabytes of data. If each accession had been represented by 5–15 individuals, the total number of samples would have been 21–62 thousands and approximately 3.2–9.8 gigabytes of data, and data analysis with existing statistical programs would have been extremely challenging. Genotyping of all 21,300 accessions with 5–15 individuals could lead to a daunting file size of 16.8 to 50.5-gigabytes.The availability of high throughput and relatively low-cost NGS technologies have provided genebank researchers a better opportunity to explore the genetic potential of their collectionsUsing high-density DArTseq genotype data generated with the Illumina NGS technology, we assessed six leaf (DNA) sampling methods to determine if an obvious advantage in genotyping multiple individuals per accessions existed to justify the multi-fold increase in cost and technical complexity of handling/managing large number of samples per accession as compared to genotyping either a randomly selected individual or a bulk. Overall, we arrived at broadly similar conclusions in terms of overall SNPs polymorphism and heterozygosity/heterogeneity; molecular diversity indices within and between accessions and groups; the genetic dissimilarity between accessions and groups; population structure; and genetic differentiation. Genotyping 5–15 individuals per accession provided better information for understanding not only the level of intra-accession genetic diversity but also for detecting outliers over genotyping a randomly selected individual; however, the additional information obtained was not enough to justify the 4–14-fold increase in cost and technical challenges in managing the large-sample size associated with genebank genomics studies. Both Robinson-Foulds and SPR distances computed as measures of disagreements between a pair of phylogenies revealed that the phylogenetic tree constructed from the 15 individuals in Set-2 had the highest concordance with those in Set-12 , followed by Set-11 , suggesting that at least 5–10 plants should be genotyped per accession individually or in a bulk. Furthermore, the identification of suspected outliers in 26 of the 90 accessions, which accounted for 3.5–10.0% of the single DNA samples in Set-2, lead us to recommend genotyping of 5–10 plants individually or in a bulk instead of a single individual per accession. Results from this study provide highly useful information to other researchers involved in genetic resources characterization using genebank genomics.Supplementary FiguresSupplementary Table S1Supplementary Table S2Supplementary Table S3Supplementary Table S4Supplementary Table S5Supplementary Table S6Supplementary Table S7Supplementary Table S8Supplementary Table S9Supplementary Table S10Supplementary Table S11Supplementary Table S12Supplementary information title


Oryza sativa L) is a most important staple food crop of the world because more than half of the World’s population is dependent on it for their livelihood. Global rice production must be doubled by 2050 to cope up with the situation of population growth. Narrow genetic base in the released varieties has made the improvement in plateaus. Widening the genetic base is necessary to overcome the yield barrier. Hybridization and pre-breeding has been carried out to broaden the genetic base. Heritability and genetic advances were measured in the F5 lines (Tulaipanji × IR64), F3 lines (Tulaipanji × IR64 × PB1460), and F3 lines (Badshabhog × Swarna sub1). Some of the breeding lines were showing promising field performance with high yield potentiality. Wide crosses were performed to widen the genetic base between (Ranjit × O. rufipogon) and (Badshabhog × O. rufipogon) and the heritability pattern of the morphological characteristics in the progeny lines was evaluated. Nutritional quality of the rice grain is totally dependent on the morphology and histological characteristics of the caryopsis which are genetically determined. Caryopses ultrastructural analyses were carried out in seventeen different rice breeding lines through SEM. SEM analysis showed distinguishing ultrastructure in respect to pericarp, testa, aleurone layer, protein bodies and starchy endosperm in the breeding lines with distinctive inheritance pattern. This study provides information about the cross compatibility of the wide hybridization and heritability measures of the morphological traits which may supplement the breeding program to break the yield plateaus.Rice ( Oryza sativa L.) is most important and staple food crop because more than half of the world’s population (>3.5 billion) depends on it for their livelihood3. It is cultivated in more than 100 countries worldwide4. The genus Oryza (including both cultivated and wild rice species) can grow in diverse climatic conditions and locations from the wettest areas to the driest deserts in the world ranging 53° north to 40° south latitude, from sea level to an altitude of 3000 m above sea level5. Due to this wide range of growing habitat under diversified climatic conditions, the genus Oryza shows a wide range of genetic and phenotypic diversity6 with a maximum diversity existing in wild rice species because they have not undergone rigorous human selection11. The production of double the amount of rice by 2050 is urgently needed to feed more than 9 billion people in this world13. The production rate in the released varieties has plateaued due to narrow genetic base in the parental lines used in breeding programs15. Genetic bottleneck during domestication also causes erosion of the genetic diversity in the well adapted cultivars which leads to yield stagnation15. Yield plateaus can be surmounted through genetic gain by combining the yield related genes/QTLs from different genetic resources of rice germplasm both from local landraces and crop wild relatives. Wild species are the reservoir of genetic diversity and wide adaptability. Therefore, germplasm diversity is considered as the mainstay for crop improvement. Breeder can introgress these genetic gain related genes/QTLs using knowledge of molecular breeding techniques such as marker assisted selection19. The rice germplasm is a rich reservoir of valuable genes which has accumulated over a period of time and is yet to be exploited fully by plant breeders for varietal improvement20. Highly recombined populations such as MAGIC (Multi-parent Advanced Intercross) has been developed to maximize the genotypic diversity in order to increase genetic enhancement23. Genetic variability, heritability and genetic advance and QTLs mapping in rice has been studied28 to analyse the yield and yield components for crop improvement.Rice  in the grains33. One of the components of yield increase is the grain weight. Hence, an understanding about the ultrastructure and histology of the caryopsis and its relationship to grain weight is needed34. Structure and developmental stages of the caryopsis has been studied through histochemical staining and scanning electron microscopy (SEM) to understand their developmental characterstics36. Histologically, rice caryopsis is composed of cuticular layer (CL), Aleurone layer (AL), and endosperm layer (EL), in centripetal order38. Both the layer (CL and AL) together is termed as bran layer and are generally removed during milling and polishing. Consumption of unpolished rice  may conserve about 43–54 million tonnes rice every year39. Brown rice has greater human health benefits as well as increase in grain yield due to the presence of bran layer40. These layers  plays vital role in cooking behaviour of the rice grains too41.Rice fruit is a caryopsis in which the single seed is fused with the wall of the ripened ovary (pericarp) forming a seed-like grain. The rice grain (rough rice) consists of an edible part, the rice caryopsis, which is protected by a covering known as hull (husk). Husk contains the larger lemma and smaller palea jacketing the rice caryopsisO. rufipogon; Badshabhog × O. rufipogon for broadening the genetic base. Therefore, the objectives of this study was to assess the genetic variability, heritability and genetic advance (GA) of yield and yield associated traits in some promising breeding lines (Tulaipanji × IR64); (Tulaipanji × IR64 × PB1460); (Badshabhog × Swarna Sub1); and pre-breeding lines (Ranjit × O. rufipogon) and (Badshabhog × O. rufipogon) to assist the future breeding programs for yield improvement by widening the genetic base and genetic recombination. Morpho-histological (ultrastructure) characteristics of the rice caryopsis have also been investigated in situ conditions before and after cooking (retrograded stage) through scanning electron microscope (SEM) to trace the inheritance patterns of these traits in the breeding lines.There is no report about the improvement of rice cultivars Tulaipanji and Badshabhog through breeding and also no report regarding the pre-breeding between Ranjit × 5:6, (Tulaipanji × IR64 × PB1460) having progeny lines in F2:3; and (Badshabhog × Swarna sub1) having progeny lines in F2:3 stage. Two wide cross combinations were established in the pre-breeding program for the introgression of agronomically important traits (gene/QTLs) into the cultivars. These prebreeding lines were at F2:3 populations between (Ranjit × O. rufipogon) and between (Badshabhog × O. rufipogon) and maintained for genetic evaluation purpose  having progeny generation lines in F5:6 (Tulaipanji and IR64), in Table 2:3 (Tulaipanji × IR64 × PB1460), in Table 2:3 progeny lines. Results of the interspecific hybridization (pre-breeding) were summarized in Table 2:3 progeny lines (Ranjit × O. rufipogon) and in Table 2:3 progeny lines (Badshabhog × O. rufipogon).The ANOVA revealed that there is highly significant differences existed among the breeding lines considering the agro-morphological traits  were analyzed in all the breeding lines Tables –5. The P2:3 mapping populations , heritability calculation was high for the traits plant height, panicle length, grain length, grain breadth and 1000 grain weight but less in the trait for grain number per panicle (Table High heritability was observed in the breeding lines of the cross (Tulaipanji × IR64 × PB1460) in the Fs Tables . Low herle Table .in situ condition by SEM and morpho-histological changes were detected. Histological ultrastructural architecture of the outer most pericarp layer, then testa (seed coat), aleurone layer and endosperm layer in centripetal manner were clearly observed in situ by SEM in different rice varieties and breeding lines before and after cooking . Histological characteristics of the cooked retrograded caryopsis were studied at ng Figs. . Summaryng Figs. . Physicoin situ conditions . The outer most pericarp was thick and dense without any porous structure like pinhole porosity. Underneath to the pericarp layer is a testa that is a seed coat. Immediately beneath the testa was the aleurone layer (AL), a single layer of cuboidal aleurone cells, sometimes multi cell layer , surrounded by many numbers of small size protein bodies (PB) (1.40 μm to 4.30 μm) more than that of Tulaipanji rice and also impression of PB in the marginal side   Fig. . Starch on) Fig. . Retrogron) Fig. .O. rufipogon) and impression of PB in the marginal region but less than the O. rufipogon . Impression of PB with moderate pinholes was also observed in this BGSF2A line  in F2i line (Tulaipanji × IR64 × PB1460) with variation in size and less angularity. The CSG are mostly polyhedral in shape (5.16 μm to 22.36 μm) with less angularity in F2ii line (Tulaipanji × IR64 × PB1460) . More than 10 μm thick layer was recorded in the following genotypes- IR64 and RRF2. Aleurone cell layer area was recorded highest in F2ii line (675.41 μm) and lowest in the breeding line BGSF2B (183.70 μm), followed by 592.05 μm in RRF2. Bran thickness highest was observed in breeding line F5AN (79.52 μm), then 62.71 μm in F5AL (Tulaipanji × IR64), minimum thickness was 24.24 μm in Tulaipanji, 24.36 μm in Badshabhog, and 23.33 μm in F2ii line (lowest). Smallest AG was found in IR64 (0.32 μm) , medium abundance in three rice lines  and lowest abundance in eight rice lines . Sensory based aroma content was measured in the varieties with high, medium and low range index. Rice varieties such as –Tulaipanji, Badshabhog, PB1460, wild rice are aromatic, but IR64, Ranjit, Swarna sub1 are non aromatic , medium (10.1–20%) and high (>20.1%)49. The heritability estimates alone cannot furnish complete practical importance unless it is studied with genetic advance. Since heritability do not always indicate genetic gain, therefore heritability estimation coupled with genetic advance is more effective for selection. High genetic advance with high heritability was observed in all the traits considered in the present investigation which indicated that these traits were less influenced by the environmental fluctuations. Instead these traits are governed by additive gene action and can easily be selected through phenotypic selection , indicating that the environment interacted to express the traits . Comparison was done between the uncooked and cooked (retrograded) rice caryopsis to judge the quality of rice grain in terms of cellular components maintenance before and after cooking. Rice grain starches are two categories- hot water soluble and insoluble. During cooking hot water soluble components leach out from the endosperm layer and may form thin film covering around the caryopsis and giving cooked rice individuality. Endosperm cell wall was so thin that it cannot be resolved clearly under SEM, it was consistent with those of earlier finding66. Inheritance pattern of caryopsis histological ultrastructure components were investigated in this present study. It was observed that one of the F5 progeny lines (Tulaipanji × IR64 = F5AN) with awn trait showed better parent value in respect to bran thickness in the caryopsis, which was 79.52 μm whereas in the parental lines Tulaipanji and IR64, these were 24.24 μm and 34.87 μm respectively. Other F5 lines of the same cross showed bran thickness below the parental value  to reveal the histological ultrastructural architecture in the rice caryopsis in different varieties and breeding lines in its original location and form , which was 13.48 μm thick in RRF2 breeding line, whereas parental line with 6.83 μm (O. rufipogon) and 8.56 μm in Ranjit  and Ranjit respectively  compared to 8.66 μm in Badshabhog and 6.83 μm in wild rice O. rufipogon  such as F5AL ( 29.37 g) and F5AN ( 28.37 g) compared to parental lines  and consisting of amylose and amylopectin molecules developed in the amyloplast of the endosperm. Grains with well developed starch granule with angular polyhedral appearance make grain transparent and non-chalky with good milling characteristics69. But amyloplast spherical in shape with large spaces between plastid, resulted in chalky grains of poor milling quality. Protein bodies were found in the endosperm layer and vary in quantity. Some of the breeding lines  contain high amount (+++) of PB in their endosperm which indicating that nutrient quality and medicinal property has been improved by breeding and selection and confirmed through ultrastructural observation under SEM  if accumulated in higher numbers, leads to a higher nutrient value and medicinal property but taste is poor68. The developmental status of amyloplasts and protein bodies determines the quality and quantity of rice grains71. High or low temperature affects the sequence and pattern of enzyme changes during grain filling, resulting in increased rice chalkiness72. In a rice breeding program, gelatinization temperature (GT) may be measured by the alkali spreading value (ASV) test based on standard protocol51, value ranges from 1 to 7. Rice cultivars with higher GT  must be cooked a few minutes longer that those with lower values . Low gelatinization temperature rice tend to start absorbing water and swell at lower temperature during cooking than those with starch of higher gelatinization temperature. Breeding lines F5AL showed ASV-4, aroma index-3 and medium GT value 3, but F5AN showed aroma index 3, ASV-3, and GT value 5. Results of GT value are inversely proportional to the value of ASV  of the rice cultivars (Oryza sativa) by introgressing agronomically important unadapted gene/QTLs from their wild relatives (O. rufipogon) to develop climate ready crop varieties. This is the most demanding breeding strategy in this climate change scenario. The back crossing was performed to develop chromosome segment substitution lines (CSSL) for the generation of near isogenic lines (NIL) with unique specific trait to be used as mapping population to identify gene/QTLs for the important traits.Two promising lines were selected from the cross Tulaipanji × IR64 and one line from triparental cross (Tulaipanji × IR64 × PB1460) with high yield potentiality. Maturity duration has been reduced to 130 days instead of 150 days in parental line Tulaipanji. These breeding lines were photoinsensitive and may grow during summer season as Boro rice. Farmers can cultivate these lines in both the season kharif as well as summer. These promising lines showed high heritability with additive gene action of the phenotypic traits under study and showed immense scopes to improve the varieties through selection. Selection could be effective for the traits grain number, panicle length under present investigation. High heritability along with high genetic advance as percent of mean was observed for grain number per panicle, 1000 grain weight which signifies the selection of these traits may helpful for further crop improvement. Breeding lines of the cross Badshabhog × Swarna Sub1 was conducted to develop high quality improved Swarna Sub1 by transferring aroma and nutritional quality genes from Badshabhog to fulfil the SDG for nutritional security. Caryopsis ultrastructural features  can be used as phenotypic marker to observe the inheritance of grain traits directly . SEM ultrastructural study has provided morpho-anatomical distinguishing features of caryopsis Oryza sativa L.) cultivars such as Tulaipanji, Badshabhog, Ranjit, IR64, PB1460, Swarna Sub1 and one wild rice genotype [Oryza rufipogon Griff.] were used for the present breeding program to improve the agronomically important traits  using a bunch of 200 male panicles with mature extrusion anthers which was collected from the field in the previous day and kept in water bucket. After pollination with this bunch of panicles to the emasculated female flowers were bagged again with the paper bag and tagged properly. After 25 days of pollination F1 seeds were collected from the parent plant (October 2012) and then subsequently maintained the lines for the development of F5 populations.Breeding lines were developed by artificial pollination and maintained for the present work. Hybridization was done in the year 2012 (October) based on standard protocol of artificial pollinationMorpho-agronomic traits were recorded according to DUS test protocol  for characteristics evaluation of the rice lines. The 21 days old seedlings of each line were transplanted with spacing 20 cm × 20 cm in randomized complete block design (RCBD) with 3 replications  of the grain. Caryopsis with the fractured surface (solid round ring) facing upwards were mounted on a specimen stub and coated with thin film of gold by means of a sputter coater (Jeol Model Smart Coater PF 18001006–2) about 2 minutes at high vacuum evaporator condition. Then ultra-structure was viewed with a scanning electron microscope (SEM)  at various magnification with an accelerating voltage of 10 kV32. The selected regions were then captured for further characterization of the morphological and histological properties using software InTouchScope of microscope control (Jeol). Total seventeen (17) rice caryopses of different breeding lines were used to reveal their morphological and histological characteristics at the in situ position of the microstructural components through scanning electron microscope (SEM) before and after cooking (retrograded).Mature grains were manually de-husked to take out the caryopsis. About ¼ th portion of both ends of the caryopses were removed and then fractured by applying slight pressure on the middle of the caryopsis with a razor blade for making solid round ring to get whole inner surface (50. Unpolished rice grain (caryopsis) in boiling water were taken out at a specific time interval during cooking and pressed between two glass slides until no opaque core or uncooked region was left. Then the cooked grain caryopsis was kept on glass slide for naturally retrogradation for 24 hours before SEM observation.The optimum cooking time was determined according to standard protocol51. A low ASV corresponds to a high gelatinization temperature (GT), conversely, a high ASV indicates a low GT. Sensory based aroma  was evaluated using standard procedure52.Alkali spreading value (ASV)  was measured according to the standard method45, and GCV, PCV were calculated by the formula of Burton46 and heritability as suggested48 and genetic advance (GA) computation based on the formula of Johnson et al.49.The data were recorded in MS excel for the kharif crop 2016, 2017 and 2018. The data recorded for all the agronomic characters were subjected to ANOVA and then calculation for GCV (genotypic coefficient of variation), PCV (phenotypic coefficient of variation), heritability and genetic advance (GA) and genetic advance as percent of mean (GAM) analysis. Statistical analysis was done by using SPSS v.16.0. Genotypic and phenotypic variance was calculated using the formula of LushSupplementary information.


P = 0.020), progression-free survival , and better recurrence-free survival . Subgroup analysis implied that STAT3/p-STAT3 overexpression was associated with worse OS in standard treatment , and in China , and metaregression analysis indicated countries (P = 0.001) may be the source of heterogeneity in our study. In conclusion, we suggested STAT3/p-STAT3 was associated with poor prognosis in patients with glioma, which indicated that STAT3/p-STAT3 might be a valuable prognostic biomarker and a promising therapeutic target for glioma.Glioma is defined as a common brain tumor which causes severe disability or death. As many genes are reported to relate with glioma's occurrence and development, their prognostic and therapeutic value still remains uncertain. This study aimed at investigating the association between STAT3/p-STAT3 and glioma prognosis. Nine studies  scored ≥5 on the Newcastle-Ottawa scale were meta-analysed from the Medline, Embase, and Web of Science databases. We found that STAT3/p-STAT3 overexpression in glioma patients was associated with worse overall survival (hazard  ratio  (HR) = 1.40, 95%confidence  interval  (CI) = 1.05 ~ 1.86,  TERT ) OR (((((((APRF Transcription Factor) OR ) OR IL6 Response Factor) OR LIF Response Factor) OR STAT3b Transcription Factor) OR STAT3a Transcription Factor) OR Transcription Factor, STAT3 [All fields]) OR ) OR phosphorylated stat3 transcription factor) OR phospho-STAT3 [All fields])) AND ((Glioma [Mesh]) OR  OR Glial Cell Tumor [All fields]) OR Mixed Glioma [All fields]) OR Tumor, Glial Cell [All fields]) OR Malignant Glioma [All fields]) OR Malignant Gliomas [All fields])).Studies included in this analysis must meet some criteria. The participants must have been diagnosed with glioma via imaging, pathology, or the latest clinical diagnostic criteria. There was immunohistochemical analysis with the expression of STAT3/p-STAT3 in the glioma tissue. The association between STAT3/p-STAT3 and patients' prognosis, regardless overall survival (OS), progression-free survival (PFS), or recurrence-free survival (RFS), was investigated, and the adjusted or crude hazard ratio (HR) values could be calculated. Only studies with a sample size more than 60 were included. When the overlapping or even same data appears in different studies, the most complete or up-to-date study was included. The review and abstract were excluded .Two reviewers independently extracted the following data from remaining studies: the information about study characteristics , demographic characteristics , the expression of STAT3/p-STAT3, and outcomes. Then, another two reviewers checked the received data. Inconsistent data were addressed by open discussion, and consensus was achieved. Finally, all extracted data were stored in the predesigned excel spreadsheet.Two investigators conducted studies quality assessments of the included studies according to the Newcastle-Ottawa scale (NOS) developed for nonrandomized controlled trials . The NOSI2 values of 25%, 50%, and 75% as described previously [For all analyses, we used fixed and random effect models to reduce heterogeneity through Stata 14.0 . Depending on the type of extracted data, we applied subgroup analysis by country, sample size, study subject (STAT3 or p-STAT3), treatment, and HR estimate. Moreover, sensitivity analysis was conducted to assess heterogeneity. We would assign adjectives of low, moderate, and high to eviously , 40, 42.eviously .The combined search yielded 1,509 potentially relevant studies after removing 753 duplicates, and 12 were retained while the title and abstract were screened. Three studies were close to meet the threshold but still excluded due to their lack of detailed data and sample size. Nine studies –51 12 t, among wP = 0.020) , so we conducted subgroup and metaregression analysis to investigate the possible source of the heterogeneity. As for STAT3 and its phosphorylation, there was no association with OS (P = 0.030), and there was no significant association in nonstandard treatment  (P < 0.001), but no evidences in other countries  (P = 0.001) may be the source of heterogeneity in this study, while STAT3/p-STAT3 (P = 0.863), treatment (P = 0.423), and sample size (P = 0.996) were not.The combined analysis of 12 trials showed that STAT3/p-STAT3 overexpression in glioma was associated with worse OS  = 1.05 ~ 1.86, = 0.020) . Obvious with OS . Further with OS . Treatme= 0.095) . As for = 0.852) . Subgrou= 0.852) . MoreoveP < 0.001)   . It is c= 0.938) .P < 0.039)   . It is c= 0.713) .We removed each trial and reanalysed the data, and the main findings were unchanged .PBegg's  test = 0.631 and PEgger's  test = 0.290, respectively)  .Few known risk factors are associated with the brain and central nervous system cancer, including glioma , and theOur study also inevitably has some limitations. Summarized population-level data, rather than individual patient-level data, was only extracted from the included 9 studies. The expression and positive rate of STAT3/p-STAT3 were diverse in different studies while immunohistochemical analysis was used to detect STAT3/p-STAT3. In addition, the scope of our research results may be limited as most of included studies were from China, while our results indicated that STAT3/p-STAT3 overexpression was associated with worse OS in China. Unfortunately, this limitation cannot be improved, given the chosen inclusion criteria. Last of all, HR and 95% CI were not directly available in some included studies and we had to apply Engauge Digitizer to obtain them from the survival curve, and heterogeneity under such circumstances was so substantial that random effect models and subgroup analysis could not diminish it; thus, additional analysis is necessary to clarify these confusing problems. Glioma is classified by cell type, by grade, and by location, but we failed to conduct subgroup analysis of classification due to the limited data included in this study, as well as meta-analysis of RFS or PFS. Moreover, during the analysis, we combined STAT3 and p-STAT3 together to analyse. It is precisely for this reason that this study cannot be more in-depth and thorough.In conclusion, our study suggested that STAT3/p-STAT3 is associated with poor prognosis in patients with glioma, which indicated that STAT3/p-STAT3 might be a valuable prognostic biomarker and a promising therapeutic target for glioma. Further studies with larger sample sizes and multicenter/countries are needed to shed more light on the more precise correlation between STAT3/p-STAT3 and glioma.