Cloned genes/QTLs regulating various yield-related traits in wheat.
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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"7624",leadTitle:null,fullTitle:"Smart Urban Development",title:"Smart Urban Development",subtitle:null,reviewType:"peer-reviewed",abstract:'Debates about the future of urban development in many countries have been increasingly influenced by discussions of smart cities. Despite numerous examples of this "urban labelling" phenomenon, we know surprisingly little about so-called smart cities. This book provides a preliminary critical discussion of some of the more important aspects of smart cities. Its primary focus is on the experience of some designated smart cities, with a view to problematizing a range of elements that supposedly characterize this new urban form. It also questions some of the underlying assumptions and contradictions hidden within the concept.',isbn:"978-1-78985-042-0",printIsbn:"978-1-78985-041-3",pdfIsbn:"978-1-78985-851-8",doi:"10.5772/intechopen.77428",price:119,priceEur:129,priceUsd:155,slug:"smart-urban-development",numberOfPages:234,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"455e3fe68e90610076558c6db2a591e1",bookSignature:"Vito Bobek",publishedDate:"February 19th 2020",coverURL:"https://cdn.intechopen.com/books/images_new/7624.jpg",numberOfDownloads:11885,numberOfWosCitations:0,numberOfCrossrefCitations:9,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:21,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:30,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"January 7th 2019",dateEndSecondStepPublish:"February 19th 2019",dateEndThirdStepPublish:"April 20th 2019",dateEndFourthStepPublish:"July 9th 2019",dateEndFifthStepPublish:"September 7th 2019",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"128342",title:"Prof.",name:"Vito",middleName:null,surname:"Bobek",slug:"vito-bobek",fullName:"Vito Bobek",profilePictureURL:"https://mts.intechopen.com/storage/users/128342/images/system/128342.jpg",biography:"Dr. Vito Bobek works as an international management professor at the University of Applied Sciences FH Joanneum, Graz, Austria. He has published more than 400 works in his academic career and visited twenty-two universities worldwide as a visiting professor. Dr. Bobek is a member of the editorial boards of six international journals and a member of the Strategic Council of the Minister of Foreign Affairs of the Republic of Slovenia. He has a long history in academia, consulting, and entrepreneurship. His own consulting firm, Palemid, has managed twenty significant projects, such as Cooperation Program Interreg V-A (Slovenia-Austria) and Capacity Building for the Serbian Chamber of Enforcement Agents. He has also participated in many international projects in Italy, Germany, Great Britain, the United States, Spain, Turkey, France, Romania, Croatia, Montenegro, Malaysia, and China. Dr. Bobek is also a co-founder of the Academy of Regional Management in Slovenia.",institutionString:"Universities of Applied Sciences FH Joanneum, Austria",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"6",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"477",title:"Urban Development",slug:"urban-development"}],chapters:[{id:"66676",title:"Towards a Generic Framework for Smart Cities",doi:"10.5772/intechopen.85820",slug:"towards-a-generic-framework-for-smart-cities",totalDownloads:1050,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Cities are formidable drivers of economic, social and cultural development but face a rising multitude of challenges: urban sprawl, transportation problems and climate change to mention but a few. Evolving concepts such as smart cities, sustainable communities and low carbon cities have been employed to formulate initiatives to tackle these challenges. Smart cities appear to address efficiency in reducing time, cost, and energy in delivering services-smart transportation, intelligent buildings, and green infrastructure with a view to reaching low carbon city development and eventually sustainability. This article attempts to construct a general framework for smart cities. First, the overall smart city system is depicted. Second, the dynamics of urban sector drivers in smart and low carbon cities are elucidated. Third, the performance of smart cities is measured in relation to low carbon development. By applying the smart city framework to the cities of Vienna, London, New York and Tokyo, the model proved robust and flexible. The investigation is concluded with policies to realign city plan and development policies.",signatures:"Hossny Azizalrahman and Valid Hasyimi",downloadPdfUrl:"/chapter/pdf-download/66676",previewPdfUrl:"/chapter/pdf-preview/66676",authors:[null],corrections:null},{id:"67740",title:"The Impact of Institutional and Political Factors on Timely Adoption of Local Community Budgets",doi:"10.5772/intechopen.86950",slug:"the-impact-of-institutional-and-political-factors-on-timely-adoption-of-local-community-budgets",totalDownloads:756,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"When preparing a budget, local authorities are faced with a problem of implementing all statutory tasks while maintaining a balanced budget both from a financial point of view and from the aspect of satisfying common needs and interests of citizens. All these factors are reflected in the timely adoption of a budget. Our fundamental hypothesis is that in their efforts for timely adoption of a budget, local communities face institutional and political factors. If the budget of the local community is not adopted on time, local communities, in the case of Slovenia, are financed only on a temporary basis. An example of an institutional factor is the cooperation between a mayor and a finance manager in preparation of a budget (the first factor). An example of a political factor is the clarity of informing a municipal council (the second factor) which is the decision-taking body of a local community, since both the mayor and municipal council are elected politically. To this end, we have set two hypotheses. The first hypothesis is that the first mentioned factor is an important factor for timely adoption of a local community budget. We checked it with the discriminatory analysis. The second hypothesis is that the clarity of informing a municipal council by a mayor is an important factor for the timely adoption of a local community budget. We checked it by testing the difference between the arithmetic mean for two independent samples. The sample consisted of 122 local communities out of 212 population. Based on theoretical background and research, we have drawn recommendations to local communities for timely adoption of budget which consequently allows financing and performance of municipalities’ tasks.",signatures:"Tatjana Horvat, Nataša Gaber Sivka and Vito Bobek",downloadPdfUrl:"/chapter/pdf-download/67740",previewPdfUrl:"/chapter/pdf-preview/67740",authors:[null],corrections:null},{id:"67106",title:"Symmetrical Aspects of Urban Regeneration in Seoul",doi:"10.5772/intechopen.86331",slug:"symmetrical-aspects-of-urban-regeneration-in-seoul",totalDownloads:879,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Korea has developed very rapidly since 1980s highlighted with Seoul olympic, and urbanization necessarily incurred. Population grew with increasing housing demands, but old towns could not provide enough land. The old town was already congested, and living conditions fell off. Therefore, new towns outside the old town were planned and built through three sequential phases. This suburbanization brought about heavy load on commuter transportation and air pollution. At the same time, improper infrastructure and amenities turned new towns into bedtowns. To escape from bedtowns, people returned to the old town, and urban remodeling was needed to accommodate adequate living conditions. In doing so, local characteristics were lost. Urban regeneration aroused as a countermeasure to this mishap. In this study, urban regeneration reinforced with smart technologies is suggested to revive lost placeness, communal connectivity, and urban orientation. Gentrification is another important issue to be resolved for the sustainable urbanization. This study focused on symmetrical aspects of the successful urban regeneration.",signatures:"Mi-Sun Park, Seunghee Lee and Uk Kim",downloadPdfUrl:"/chapter/pdf-download/67106",previewPdfUrl:"/chapter/pdf-preview/67106",authors:[null],corrections:null},{id:"68033",title:"Application of a Metabolic Thinking Driven Sustainability Framework in Early-Stage Planning of Eco-City",doi:"10.5772/intechopen.87137",slug:"application-of-a-metabolic-thinking-driven-sustainability-framework-in-early-stage-planning-of-eco-c",totalDownloads:811,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The fast urbanization rate together with increasing global population and consumption is challenging the long-term sustainability of our social systems and supporting ecosystems on earth. The signs of instability can be seen in environmental degradation, e.g., climate change and loss of biodiversity. Also, the increasing use of materials and energy creates competition and international conflicts. The success of international agreements to handle the global problems has been limited. This is because deeply entrenched economic and political interests are involved. Political leaders are locked up to promises of economic growth and increasing welfare. Through globalization, resources and products are transported long distances and it is becoming hard to distinguish between local and global effects. This makes people feel that the overall situation is so complicated, so they cannot affect it. Bringing things closer to people will create more awareness and can create enormous opportunities for new ideas and business to solve the existing problems. The United Nations 2030 Sustainable Development Goals are focused on reducing poverty in the world. China has succeeded in reducing poverty on a massive scale through fast economic growth but to the price of increased use of virgin resources and environmental degradation. It seems more and more urgent to develop support models for urban development on a local scale focusing on urban metabolism. As sustainable development involves many normative decisions, participatory planning and cross-sectoral planning will be needed to ensure that conflicts between goals can be resolved. The Swedish Green Building Council has, together with more than one thousand actors, developed a recent model for the support of sustainable urban planning called CITYLAB. This has been used in a case study in the city of Changzhou in China. The case study reveals several barriers in Chinese planning when it comes to implementing more of horizontal planning practices.",signatures:"Ronald Wennersten and Yunzhu Ji",downloadPdfUrl:"/chapter/pdf-download/68033",previewPdfUrl:"/chapter/pdf-preview/68033",authors:[null],corrections:null},{id:"69799",title:"Analysis of Urban Environment Sustainability in Kurdish Cities of Iran Using the Future Study Approach (Case Study: Saqqez City)",doi:"10.5772/intechopen.86009",slug:"analysis-of-urban-environment-sustainability-in-kurdish-cities-of-iran-using-the-future-study-approa",totalDownloads:928,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The present study attempts to analysis the spatial transformations in the urban environment scale by utilizing the natural step foresight approach in the context of urban environment indicators. To obtain this goal, the methods applied herein included descriptive-analytical studies, document and questionnaire in the frame of Delphi model and software analyzes. Initial discussions were held with 50 academic elites and executives in Saqqez city as the statistical population, followed by the identification of 78 variables in the frame of 16 general classifications. The results showed that the obtained fill rate was equal to 95.79% with two data iterations, which represented the highest level of variables influencing each other. According to the findings, the integrated urban environmental management index (ME4) with 188 scores had uppermost direct impact on other variables. Moreover, the index of development and promotion of urban recycling regulations with 5,585,944 calculated raw values presented the most indirect impact on other variables. Finally, the use of SMIC resulted in favorable, intermediate and catastrophic scenarios by considering the identified key driving forces.",signatures:"Akbar Heydari, Mohammad Rahim Rahnama and Shadieh Heydari",downloadPdfUrl:"/chapter/pdf-download/69799",previewPdfUrl:"/chapter/pdf-preview/69799",authors:[null],corrections:null},{id:"69772",title:"Smart Rainwater Management: New Technologies and Innovation",doi:"10.5772/intechopen.86336",slug:"smart-rainwater-management-new-technologies-and-innovation",totalDownloads:2055,totalCrossrefCites:2,totalDimensionsCites:4,hasAltmetrics:1,abstract:"In a smart city, the following factors are very vital such as smart grid and e-health. A smart city is one of the burning topics of research. Although there is no particular definition of a smart city, it means smart grid, e-health, e-environmental monitoring, smart home, smart water quality, smart air quality, etc. integrated into a single application. Human civilization can’t be sustained and prosper with shortage of usable water. Hence, water has a vital share in human life even for those living in smart cities. This chapter describes about the smart water quality issues in a smart city and some of the research advances in handling those issues. Among them it investigates the rainwater harvesting technologies and some of their practical applications.",signatures:"Raseswari Pradhan and Jayaprakash Sahoo",downloadPdfUrl:"/chapter/pdf-download/69772",previewPdfUrl:"/chapter/pdf-preview/69772",authors:[null],corrections:null},{id:"66984",title:"Mapping Smart Mobility Technologies at Istanbul New Airport Using the Customer Journey",doi:"10.5772/intechopen.86135",slug:"mapping-smart-mobility-technologies-at-istanbul-new-airport-using-the-customer-journey",totalDownloads:803,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"We are in an era in which urban populations exceed rural populations for the first time in history. Therefore, it is becoming more difficult to manage cities due to overcrowding. On the other hand, developing technology enables city administrations to benefit from citizens’ data and serve them in smarter ways. A component of this management tool, smart mobility refers to beneficial technology that improves individuals’ mobility. Technology is also an important tool for providing customer experiences in smart cities. This study is focused on Istanbul New Airport as a case for smart mobility in which various technologies are implemented to create memorable experiences for passengers. These experiences were mapped with a strategic management tool, customer journey mapping (CJM), which is increasingly popular with both academics and urban administration because it helps to identify customer touch points. Using this tool, passenger experiences are matched with technological applications, and some suggestions are provided based on customers’ experiences.",signatures:"Taşkın Dirsehan",downloadPdfUrl:"/chapter/pdf-download/66984",previewPdfUrl:"/chapter/pdf-preview/66984",authors:[null],corrections:null},{id:"68541",title:"Environmental Noise Mapping as a Smart Urban Tool Development",doi:"10.5772/intechopen.88449",slug:"environmental-noise-mapping-as-a-smart-urban-tool-development",totalDownloads:1016,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:1,abstract:"Since the European Directive 2002/49, large transportation infrastructure along with large urban areas should have completed strategic noise maps (SNM) and the relative noise action plans (NAP). The majority of European Member States (MS) has enforced this directive and completed fully or, in some cases, partially, with European smart cities to use and share the same criteria and methodologies and along with transport operators to communicate to the public the relevant results and respective action plans by ensuring the citizen’s awareness about the environmental noise, the quality acoustic environment, and their effect to their professional and everyday lifestyle. Today, 18 years after its first edition, the European Directive 2002/49/EC is needed to be reformulated to take into account all defects that have been identified and to adapt as well as possible to contemporary constraints. New methodology tools have been developed especially regarding soundscaping and environmental acoustic rehabilitation of urban areas, and the respective chapter will describe the progress being made on these smart developments of cities and infrastructures. This chapter will also evoke criticisms of these smart tools and will present results from several—state of the art—case studies especially regarding the practical and theoretical limits they face.",signatures:"Konstantinos Vogiatzis and Nicolas Remy",downloadPdfUrl:"/chapter/pdf-download/68541",previewPdfUrl:"/chapter/pdf-preview/68541",authors:[null],corrections:null},{id:"67808",title:"Understanding Urban Mobility and Pedestrian Movement",doi:"10.5772/intechopen.86801",slug:"understanding-urban-mobility-and-pedestrian-movement",totalDownloads:1398,totalCrossrefCites:2,totalDimensionsCites:4,hasAltmetrics:1,abstract:"Urban environments continue to expand and mutate, both in terms of size of urban area and number of people commuting daily as well as the number of options for personal mobility. City layouts and infrastructure also change constantly, subject to both short-term and long-term imperatives. Transportation networks have attracted particular attention in recent years, due to efforts to incorporate “green” options, enabling positive lifestyle choices such as walking or cycling commutes. In this chapter we explore the pedestrian viewpoint, aids to familiarity with and ease of navigation in the urban environment, and the impact of novel modes of individual transport (as options such as smart urban bicycles and electric scooters increasingly become the norm). We discuss principal factors influencing rapid transit to daily and leisure destinations, such as schools, offices, parks, and entertainment venues, but also those which facilitate rapid evacuation and movement of large crowds from these locations, characterized by high occupation density or throughput. The focus of the chapter is on understanding and representing pedestrian behavior through the agent-based modeling paradigm, allowing both large numbers of individual actions with active awareness of the environment to be simulated and pedestrian group movements to be modeled on real urban networks, together with congestion and evacuation pattern visualization.",signatures:"Marija Bezbradica and Heather J. Ruskin",downloadPdfUrl:"/chapter/pdf-download/67808",previewPdfUrl:"/chapter/pdf-preview/67808",authors:[null],corrections:null},{id:"67089",title:"Dynamic Street Parking Space Using Memetic Algorithm for Optimization",doi:"10.5772/intechopen.86010",slug:"dynamic-street-parking-space-using-memetic-algorithm-for-optimization",totalDownloads:876,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"In recent years, there have been an increasing number of automobiles in cities around the world. This is due to more people living and working in cities as a result of urbanization. Street parking remains a common option for motorists, due to it being cheap and convenient. However, this option leads to a high concentration of vehicles causing congestion and obstruction of traffic. This problem is compounded as motorists wait for others to pull out of parking bays or look for empty parking spaces. In order to provide relief to this problem, an intelligent approach is proposed that generates an optimal parking space based on the vehicle location and desired destination. The proposed approach applies its operators adaptively and it derives optimality from the synergy between genetic algorithm and a local search technique in the search optimization process. The proposed method exhibits superior performance when compared with the existing methods over multiple iterations.",signatures:"Stephen Akandwanaho and Irene Govender",downloadPdfUrl:"/chapter/pdf-download/67089",previewPdfUrl:"/chapter/pdf-preview/67089",authors:[null],corrections:null},{id:"68046",title:"Cost-Benefit Evaluation Tools on the Impacts of Transport Infrastructure Projects on Urban Form and Development",doi:"10.5772/intechopen.86447",slug:"cost-benefit-evaluation-tools-on-the-impacts-of-transport-infrastructure-projects-on-urban-form-and-",totalDownloads:1313,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"This study reviews literature for identifying the methods in order to evaluate the impacts of key transport infrastructure provisions on urban form and peri-urban development in European Union (EU) member countries. Key impacts and linkages of transportation provision on urban development trends are identified through the international literature. These include direct impacts of transportation infrastructure provision, socio-economic impacts, transportation network effects and energy and environmental impacts. Among the evaluation methodologies, cost-benefit analysis (CBA) is the most common approach for transport policy impact assessments both in the national project appraisal guidelines and in scientific analysis and research. Considering its extensive usage in the appraisal work, the main focus will be on the evaluation tools used within the CBA approach. The corresponding data requirements for the valuation of indicators will be also discussed in order to assess the impacts of costs and benefits of transport investments, particularly rapid rail investments, on urban form and development.",signatures:"Eda Ustaoglu and Brendan Williams",downloadPdfUrl:"/chapter/pdf-download/68046",previewPdfUrl:"/chapter/pdf-preview/68046",authors:[null],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"2355",title:"International Trade from Economic and Policy Perspective",subtitle:null,isOpenForSubmission:!1,hash:"8fe6804794ddc1a7f4202db20aed5985",slug:"international-trade-from-economic-and-policy-perspective",bookSignature:"Vito Bobek",coverURL:"https://cdn.intechopen.com/books/images_new/2355.jpg",editedByType:"Edited by",editors:[{id:"128342",title:"Prof.",name:"Vito",surname:"Bobek",slug:"vito-bobek",fullName:"Vito 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\r\n\tSeagrass species are densely represented by Posidonia oceanica, Cymodocea nodosa and Zostera noltii. Seagrass meadows are macroalgae that spread over a wide area around the world, are shaped in the form of roots, stems, and leaves at the bottom of the sea, and live by clinging to the seabed with their roots, and can produce their food by photosynthesis with the help of sunlight. In addition to being a source of oxygen and nutrients in the seas as a result of photosynthesis, they are important spawning areas for many fish species that lay their eggs on these plants.
\r\n\tThe formation and development of seagrass meadows take many years. Among all the plant habitats in the world, the most carbon storage feature belongs to seagrass with 2000 tons/ha. Posidonia oceanica is the most important seagrass species for primary production and is endemic to the Mediterranean. This species is a perennial herb that spreads to a depth of 45 meters on the Mediterranean coast and can live up to 30 years. Their presence is indicative of clean seas.
Wheat (
Grain yield is the final result of plant growth and development and hence most, if not all, genes are supposed to contribute towards yield either indirectly or directly. Consequently, achieving increased grain yield is a non-trivial task, and the accumulative knowledge from wheat breeding suggests that we would require concurrent improvements of both the ‘source’ and ‘sink’ tissues. Traditional breeding largely depends on empirical phenotypic selection, which has already resulted in the development and release of a large number of high-yielding varieties. However, time consumption, labour intensity, environmental dependence, and low efficiency are prime barriers that nowadays hinder conventional/traditional wheat breeding. High-yielding wheat varieties can result from the uncovering of novel genetic variation, better selection techniques, or the identification of superior genotypes with novel or improved characteristics caused by favourable combinations of superior alleles at multiple loci. In recent years, an impressive number of advancements in genetics and genomics have been made in wheat. Owing to the tremendous effort of IWGSC, the ‘gold standard’ reference genome has become available for wheat cultivar ‘Chinese Spring’. The most comprehensive assembly of this reference line has been recently released in 2018 which gave access to a total of 107,891 high-confidence genes [9]. The genome sequences may assist the identification of important genes at an unprecedented level which is a key aspect in wheat breeding. Different types of molecular markers, such as RFLP, AFLP, SCAR, STS, SSR, CAPS, and GBS-SNPs, have been identified and mapped on the different chromosomes of wheat and highly dense genetic maps have also been developed (available at https://wheat.pw.usda.gov/GG3/) which are being utilised in various genetic studies in wheat [10, 11]. To date, more than 15 different high-throughput GBS strategies have been developed and utilised in various crops including wheat [12]. Moreover, several SNP arrays/assays have also been developed which are flexible in terms of data point and sample number customization, which contributes to its high-density scanning and robust call rates compared to PCR and NGS-based markers. Several high-density SNP genotyping arrays have been utilised for genetic dissection of different traits and marker-assisted breeding in wheat namely the Illumina Wheat 9 K iSelect SNP array [13], the Illumina Wheat 90 K iSelect SNP genotyping array [14], the Wheat 15 K SNP array [15], the Wheat 55 K SNP array, the Axiom Wheat 660 K SNP array, the Axiom HD Wheat genotyping (820 K) array [16], the Wheat Breeders’ 35 K Axiom array [17], and the Wheat 50 K
Here in this chapter, we summarise the recent progress in understanding the genetics of grain yield and other related traits together with the new strategies, such as gene cloning and mining of superior alleles, transgenic technologies, genome editing technologies, genomic selection (GS), genome-wide association studies (GWAS)-assisted GS, and haplotype-based breeding (including haplotype-based GWAS and haplotype-based GS), which altogether make it available for genomics-assisted breeding (GAB) in crop improvement and to break the yield ceiling in wheat.
Grain yield is a complex polygenic trait, significantly associated with grain number per spike, grain weight, harvest index, number of productive tillers, plant height, days to heading/flowering, etc. The trait is also influenced by the environment and shows a significant level of genotype × environment interaction with low heritability. Previous studies showed that increased yield potential in the major wheat-growing countries was largely associated with increased grains per square meter, harvest index, and biomass, and reduced plant height [4, 5]. Moreover, it has been revealed that the use of dwarfing genes (
As discussed above, several studies have reported hundreds of QTLs in different mapping populations evaluated under different environments. An innovative approach i.e., meta-QTL analysis has emerged which helps in refining the QTL positions by combining the QTL results from independent studies and identifying the most stable and consensus QTLs [34]. The power of this approach lies in detecting regions of the genome that are most often involved in trait variation and reducing the QTL confidence intervals, thus facilitating the identification and characterisation of underlying candidate genes. For the first time in 2010, Zhang and his colleagues [35] conducted a meta-QTL analysis of major QTLs for grain yield and yield-related traits and identified 12 significant MQTLs on chromosomes 1A, 1B, 2A, 2D, 3B, 4A, 4B, 4D, and 5A, few of which also included important known genes, such as
MAS allows a more effective selection of target genotypes which further enable certain traits to be ‘fast-tracked’, resulting in faster line development and variety release. MAS is a more cost-effective approach that can replace phenotyping and thereby allows selection in off-season nurseries as well. Another advantage of using MAS is that the total number of genotypes that need to be tested can be reduced significantly in early generations which allow more efficient use of field or glasshouse space which is generally limited [48]. MAS remains a valid option for major gene or QTL, whereas QTL cloning or gene cloning may become a more routine activity assisted by increased utilisation of high-throughput phenotyping techniques [49], sequencing [50], and identification of high-confidence candidate genes through ‘omics’ profiling [51]. Cloned QTL/gene may provide new opportunities for a more targeted search for novel alleles in wild wheat germplasm and mutants (Table 1).
Genes/QTLs | Chromosome | Products/enzymes | Associated yield-related traits | References |
---|---|---|---|---|
2A, 2B, 2D | Sucrose synthase | Endosperm development | [52] | |
2A | Cell wall invertase | Kernel weight | [53] | |
5D | Cell wall invertase | Kernel weight | [54] | |
7A | Zinc-finger protein | Thousand grain weight, number of grains per spike, spike length, peduncle length and spikelet’s per spike | [55] | |
6D | Glutamine synthetase | Mineral nutrient and grain size | [56] | |
7A | Indole-3-glycerol-phosphate synthase | Thousand grain weight | [57] | |
7A | Snakin/GASA protein | Grain length | [58] | |
7D | Glutamine synthetase | Thousand grain weight, grain length | [59] | |
3D | Cytokinin oxidase/dehydrogenase | Grain size, grain filling rate, grain weight | [60] | |
3A | Cytokinin oxidase | Grain weight and leaf chlorophyll content | [61] | |
6A | Trehalose 6-phosphate phosphatase | Grain weight | [62] | |
2A | FLO2 protein | Thousand grain weight, grain size | [63] | |
1A, 1B, 1D | Plant-specific protein kinase | Plant height, length of peduncle, penultimate node, thousand grain weight | [64] | |
4A, 4B,4D | Sucrose non-fermenting 1-related protein kinases | Thousand grain weight, spike length | [65] | |
4A | Fructan 6-fructosyltransferase | Thousand grain weight | [66] | |
6A | E3 ubiquitin ligase | Grain weight, grain size | [25] | |
3D | Cytokinin oxidase/dehydrogenase | Thousand grain weight | [67] | |
5A | Putative protein phosphatase | Grain length | [68] | |
7A | F-box protein of 429 amino acids | Total spikelet number per spike | [69] | |
3A | Indole-3- acetic acid-glucose hydrolase | Thousand grain weight | [24] | |
7B | E3 ubiquitin ligase | Kernel size | [70] | |
3A | Tryptophan amino transferase | Plant height, spike number | [71] | |
5A | NAC transcription factor | Spike number, grain number per spike, and thousand grain weight | [72] | |
3A | Serine carboxypeptidases | Grain size, grain weight | [73] | |
7A | Transcript elongation factor | Grain number | [74] | |
7A | Pheophytin pheophorbide hydrolase | Thousand grain weight, grain filling | [75] | |
3B | Histone-like transcription factor | Number of spikes per plant | [76] | |
6B | Histone-like transcription factor | Number of spikes per plant | [77] | |
7A, 7B, 7D | Cytochrome P450 CYP78A3 | Seed size | [78] |
Cloned genes/QTLs regulating various yield-related traits in wheat.
At present, tremendous sequence information is available in public databases as a result of the sequencing of diverse wheat crop genomes, including reference lines and wild progenitors. This information can be used for mining the novel and superior alleles of agronomically important genes from gene pools to appropriately deploy for the development of high-yielding cultivars. Allele mining also provides insights into the molecular basis of trait variations and identifies the sequence variants associated with superior alleles. Moreover, it helps in the development of allele-specific molecular markers, assisting the introgression of novel alleles via MAS.
Considerable progress has been made in the past for manipulation of genes from diverse sources, including wild relatives and progenitors, and transferring them into wheat to confer increased grain yield, transgenesis can be employed as a powerful alternative for increasing the grain yield through exploiting the genes/traits which does not occur naturally in the wheat species. Transgenic plants refer to plants that contain a gene(s) that has been artificially inserted from an unrelated plant or a completely different species. The increase in grain yield potential through transgenesis involves an ideotypic detail of potential targets for transformation. In 2017, Nadolska-Orczyk and his colleagues [79] reported potential targets for transgenesis which can result in the increased grain yield in wheat. These include ‘transcription factors, regulating spike development, which mainly affect grain number; genes involved in metabolism or signalling of growth regulators—cytokinins, gibberellins, and brassinosteroids—which control plant architecture and consequently stem hardiness and grain yield; genes determining cell division and proliferation mainly impacting grain size; floral regulators influencing inflorescence architecture and consequently seed number, and genes involved in carbohydrate metabolism having an impact on plant architecture and grain yield’. Furthermore, modulated expression of flowering genes, which control vernalization and photoperiod-dependent floral induction, may be good for winter or spring wheat varieties [79, 80]. Besides, augmenting photosynthetic rates of laminar and non-laminar organs and the capability to access and utilise a greater amount of resources, such as nutrients or water, may also be potential targets for transgenesis in wheat for grain yield improvement [81, 82]. Besides, information about specific genotypes as well as climatic and agronomic conditions and consideration of the fact that the majority of the genes are members of multigene families is required for successful implementation of selected potential genes in breeding programs [79].
Transgenic wheat has the capacity to transform agriculture, but progress has been very limited as no transgenic wheat cultivar could be commercially approved so far because of consumers’ concerns. Few promising reports are available where newly developed transgenic wheat showed a significant grain yield advantage [72, 83]. Over-expression of a nitrate-inducible transcription factor (NAC TF) in wheat enhanced root growth and the ability to uptake nitrogen, therefore, increased nitrogen accumulation and grain yield by 10% (on a single plant basis) [72]. In another study, Gonzalez and his colleagues [83] reported that transgenic wheat lines carrying a mutated version of the sunflower TF (
Targeted genome editing has emerged as a powerful tool for studying gene function, correcting defective genes, or introducing novel functionality. Its mechanism involves sequence-specific double-strand breaks (DSBs) in the target DNA, with edits incorporated during the endogenous repair. In the earlier phase of genome editing, to induce the desired double-strand breaks at the target site, the engineering for zinc-finger nucleases (ZFNs) [85] or meganucleases [86] attracted the attention of the researcher community. These genome-editing systems needed specialised competence to produce artificial proteins consisting of customizable DNA-binding domains (sequence-specific), each linked to a non-specific nuclease for target DNA cleavage, and offered researchers with extraordinary tools to perform genetic manipulation. Later, the identification of a novel class of a
In 2012, an inexpensive, simple, easy to use, and effective genome-editing system that is clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) was introduced which revolutionised the field of genome editing [89]. The use of this powerful tool allows producing genome-edited plants in a very short period. CRISPR technology can be efficiently utilised for both precisely eliminating the negative regulator genes and augmenting the activity of positive-regulator genes that affect the trait of interest. Nevertheless, there are only a couple of reports available for validation of the CRISPR technique in wheat compared to other crops, such as rice [90]. In these reports, different genes were targeted by CRISPR/Cas9 to address the major biotic, and abiotic stresses along with improving a few agronomic traits in wheat [90]. An exciting advantage of using the CRISPR/Cas9 technology is the possibility of simultaneously editing multiple target genes using a single CRISPR construct. For instance, Wang and his colleagues [91] practiced this multiplexed genome editing in hexaploid wheat for targeting three different genes viz.
Many crucial agronomic traits are determined by a few base changes or point mutations in a gene [97, 98, 99]. CRISPR/Cas9 mediated gene replacements or gene modifications through homology-directed repair (HDR) has been reported as a practicable approach to correct the point mutations in the target DNA/gene and has the capability for accelerating crop improvement [100, 101]. Yet, the low efficiency of template DNA delivery and the rare occurrence of HDR (endogenous) has always been a difficult task in attaining success in plants. Furthermore, the CRISPR/Cas9 system is amenable for gene knock-in or knock-out, but cannot covert base into another. These challenges highlighted the demand for alternative powerful approaches that can result in precise and stable genome editing in crops. In 2016, a novel approach that is ‘Base editing’ was emerged which allows precise base (nucleotide) substitutions in a programmable manner, without requiring a donor template or disruption of a gene [102]. A base editor is a fusion of catalytically inactive Cas9 domain (Cas9 variants, Cas9 nickase, or dCas9) and an adenosine or cytosine domain that converts one base to another. Nucleotide substitutions or single-base changes may generate elite trait variations in crops which assist in accelerating crop improvement. The base-editing system can revert an SNP or single-base change without gene disruption. In recent years, many adenine and cytosine base editors have emerged as powerful tools for precise genome modifications (A to G or C to T) in eukaryotic genomes [102]. The potential of this approach has been demonstrated in several crops, including wheat [103, 104, 105, 106]. As aforementioned, HDR efficiency is comparatively low in plant cells, so knock-ins of DNA fragments to target sites are challenging. Recently in 2019, Anzalone and co-workers developed a more efficient genome-editing technology that is ‘Prime editing’ which consists of CRISPR-Cas9 nickase–reverse transcriptase fusions programmed with pegRNAs (prime-editing guide RNAs) that enable precise genome editing without inducing DSBs or requiring a donor DNA template (mandatory for genome editing via HDR) in mammalian cells [107]. The prime editors have been adapted for use in wheat via optimization of the codon, promoter, and editing conditions [108]. This optimised suite of prime editors enabled InDels and point mutations in wheat and rice at higher frequencies [108]. Development of new technologies and tools, newly discovered CRISPR/Cas systems, are being continuously reported, inferring that the CRISPR toolbox for wheat genome engineering would expand further in the near future. Researchers have also focused on the development of efficient approaches for eliminating transgenes from genome-edited plants, such as (a) transient expression of DNA and RNA [109], (b) use of CRISPR/Cas9 ribonucleoprotein complexes [110], (c) use of CRISPR-S—an active interference element [111], and (d) programmed self-elimination of the CRISPR/Cas9 constructs [112] to generate transgene-free genome-edited plants. The elimination of transgenes offers the following two advantages—(i) elimination of Cas9 construct from genome-edited plants prevents the induction of genetic changes at undesired loci, (ii) elimination of the transgenes is likely a prerequisite for getting regulatory approval of genome-edited crops for commercial applications. In the future, CRISPR technology may be supposed to accelerate wheat biology research, ultimately facilitating the development of high-yielding wheat varieties.
The genetic complexity of grain yield and other yield-related traits limit the power of QTL mapping and association mapping in identifying small effect loci [113]. A powerful breeding strategy that is genomic selection (GS) has been introduced to circumvent this problem which implements whole-genome markers for predictions, and thus can efficiently complement QTL mapping and association analysis in dissecting the complex genetic base of grain yield-related traits in wheat [114, 115]. High-throughput/next-generation genotyping technologies have accelerated the adoption of GS by enabling the development of large sets of DNA marker data at reasonable costs [116]. GS is a potential GAB tool that predicts genomic-estimated breeding values (GEBVs) of individuals (from the breeding population) with genotypic data available via prediction models constructed based on a training population (TP) with available phenotypic and genotypic information [117]. As aforementioned, using the prediction models, the GEBVs of unobserved individuals are predicted, circumventing the omission of the small-effect genomic region (markers) that would fail a threshold (significance) test. Though the effect of each marker is small, a large volume of genotypic information covering the whole genome still has the power to explain all the genetic variance. GS complements conventional breeding approaches and can potentially decrease the requirement of large-scale phenotyping and hasten the rate of genetic gain via shorter breeding cycles [118, 119]. The performance of GS relies mainly on the prediction accuracy, defined as the ‘Pearson’s correlation between the selection criterion and the true breeding value to select individuals with unknown phenotypes’ [120, 121]. Other factors that affect the GS accuracy include gene effects, level of linkage disequilibrium (LD), statistical models, the genetic composition of the TP, relationship between validation population (VP) or selection individuals and TP, and heritability of the target traits [120]. The major objective of GS is to decrease the cost of phenotyping and hasten genetic gains, use of high-throughput phenotyping tools and platforms that enable high-density phenotyping of hundreds to thousands of individuals across time and space using proximal or remote sensing, can increase the intensity and accuracy of selection and, eventually the selection response, as well as reduce phenotyping costs. The main idea of high-throughput phenotyping is to exploit secondary traits, such as canopy temperature, and green normalised difference vegetation index (NDVI) are closely related to grain yield that may be advantageous in early-generation testing of individuals. Data recorded on secondary traits (genetically correlated to grain yield) can be incorporated in multivariate pedigree and GS models, improving indirect selection for GY [122, 123, 124]. Moreover, GS can also be applied to gene bank accessions for germplasm enhancement. Accessions stored in germplasm bank represents an under-exploited rich genetic resource for wheat breeders, superior alleles can be extracted from these accessions which may be exploited for grain yield improvement in wheat [125, 126]. In general, lengthy pre-breeding programs are needed to develop lines that possess favourable alleles/genes from the wild accessions with superior agronomic performance and that may be utilised as parents in breeding programs. Using GS, germplasm enhancement breeding programs can be directly started using wild accessions and landraces. In a recent GS-based study, NGS technologies with multi-environment phenotyping were used to study the contribution of exotic genomes to 984 pre-breeding lines. Significant positive contributions of exotic germplasm to pre-breeding lines derived from crosses of CIMMYT’s best elite lines with exotics were reported [127]. Genomic selection studies conducted in wheat for grain yield and related traits are presented in Table 1. The prediction accuracy of GS for different grain yield-related traits has varied from 0 to 0.98% in wheat (Table 2).
Population type and size* | Number of genotyped markers | Traits | Accuracy of GEBV used | References |
---|---|---|---|---|
Advanced breeding lines from CIMMYT (254) | 41,371 GBS-SNPs | TGW, DTH, and GY | 0.28–0.45 | [128] |
Two DH populations (165 and 159) | 1975 and 1483 SNPs (90K SNP) | GNPS | 0.10–0.42 | [129] |
European winter wheat lines (2325) | 12,642 SNPs (9K SNP) | GY | 0.5–0.65 | [130] |
Winter wheat population (273) | 40,267 SNPs (90K SNP) | GY, TGW, PH and DTH | 0.33–0.67 | [131] |
Inbred breeding lines (557) | 12,083 GBS-SNPs | DTH and GY | 0.57 | [132] |
Advanced elite spring wheat lines (287) | 15,000 SNPs (90 K SNP) | GY, TGW and GN | 0.38–0.63 | [133] |
Lines from multiple families (659) | 9500 DArT-GBS-SNPs | GY | 0.38–0.41 | [134] |
Winter wheat breeding population from multiple families (861) | 6600 DArT-GBS-SNPs | GY | 0.39–0.48 | [135] |
Inbred breeding lines (557) | 12,083 GBS-SNPs | GY | 0.65–0.76 | [136] |
Hybrids obtained by crossing 18 males and 667 females (1888) | 13,005 SNPs (90 K and 15 K) | GY, DTH and PH | 0.5–0.55 | [137] |
Winter wheat lines (1100) | 27,000 GBS-SNPs | GY | 0.23–0.55 | [138] |
European winter and spring cultivars (210) | GBS-SNPs | 44 spike morphology traits | 0.2–0.5 | [139] |
Elite wheat lines (4368) | 2038 GBS-SNPs | DTH, DTM, PH and GY | 0.35–0.44 | [140] |
Bread wheat lines (10375) | 18,101 GBS-SNPs | GY and TGW | 0.59–0.98 | [141] |
Double haploid lines (282) | 7426 GBS-SNPs | GY and TGW | 0.47–0.54 | [142] |
Bread wheat lines (3771) | 8519 GBS-SNPs | DTH, DTM and GY | 0–0.75 | [143] |
Soft red winter wheat lines (239), Double haploid (100), and Recombinant inbred lines (156) | 2721 SNPs (9 and 90K) | GY, DTH, TGW, GNPS, and PH | − 0.14-0.43 | [144] |
F4:6 generation and double haploid winter wheat breeding lines (1114) | 7300 DArT-GBS-SNPs | GY | 0.45 | [145] |
Winter wheat lines (3282) | 18,728 GBS-SNPs | GY | 0.25 | [122] |
>6400 breeding lines | 78,662 GBS-SNPs | GY | 0.41 | [146] |
Advanced breeding lines (456) | 11,089 GBS-SNPs | GY | 0.33–0.66 | [147] |
Association mapping panel (456), two F5 populations (61 and 501), two DH populations (447 and 759) | 16,233 GBS-SNPs | GY | 0.21 | [148] |
Advanced bread wheat lines (4302) | 8443 GBS-SNPs | GY | 0.35–0.43 | [149] |
Winter wheat lines (1325) | 11,154 SNPs (15 K) | GY | 0.57 | [150] |
Genomic selection studies conducted in wheat for grain yield and related traits.
Figures in parenthesis are the population size.
GY, GNPS, DTH, DTM, PH, and TGW refer to grain yield, grain number per spike, days to heading, days to maturity, plant height, and thousand grain weight, respectively.
As discussed above, GWAS estimates marker effects throughout the genome on the target association panel (diverse germplasm) based on prediction models. Based on LD, GWAS may identify new functional variants, including novel MTAs and genes for many agronomically important traits in diverse germplasm. According to a comprehensive simulation study in plants, the use of a few major MTAs/QTLs/genes (each explaining ≥ 10% of the phenotypic variance) as fixed effects in GS models can increase the accuracy of GS for complex quantitative traits [151]. Although, the potential to combine robust and consistent associations identified from GWAS as fixed effects in GS models to increase prediction accuracy for complex traits such as grain yield has not been investigated comprehensively in wheat. The first report of integrating the genetic architecture of GY (revealed through GWAS) into prediction models in wheat has come from the work by Sehgal and co-workers, most recently in 2020 [149]. Firstly, using a haplotype-based genome-wide association study, they identified 58 MTAs for GY. Out of these 58 MTAs, 16 were ‘environment-specific’ with large effects and eight MTAs were consistent across trials and environments. These consistent MTAs were then used as fixed effects in the prediction models which resulted in a 9–10% increase in prediction accuracy for GY [149]. It is suggested that the utility of GS incorporating GWAS results may be noteworthy for GY when GWAS results detect highly robust and significant genomic regions.
Due to low heritability and persistent ‘genotype × environment’ interactions, improving grain yield (GY) is a difficult task for the global plant breeding community, especially under stressful environmental conditions [152, 153, 154]. As discussed earlier, GWAS-assisted GS has proven to be an effective method for deciphering the genetic architecture of complex traits, population improvement, and the development of better varieties with a higher yield. However, the problem of ‘missing heritability’, which is widespread in single marker-based GWAS, is not addressed by this approach. The alternative approach to boost the power of GWAS is by constructing haplotypes between neighbouring SNPs on a chromosome. As specific sets of alleles are observed on a single chromosome, haplotypes are inherited jointly with the limited probability of contemporaneous recombination. Haplotypes are implemented in crop improvement in two ways—retrospective and prospective [155]. Plant breeders have to choose the advantageous haplotypes that lead to desirable phenotype(s) for the trait(s) of interest during the long-term selection process. As a result, these advantageous haplotypes in elite crop germplasm can be found utilising the genome resequencing technique to sequence an elite gene pool [156]. Later, molecular markers that characterise these beneficial haplotypes can be produced, and all of these haplotype-defining markers can then be utilised to pick the most ideal combination of haplotypes that govern a certain phenotype. Furthermore, by identifying lines with unique recombination in chromosomal blocks of relevance, these haplotype-related markers can be utilised to distinguish between favourable and unfavourable genetic variation. On the other hand, haplotypes can be employed in a prospective approach, in which a vast collection of ancestral and wild germplasm of specific crop species (not just elite breeding pools) is re-sequenced to find haplotypes with a wider range of genetic variation [153, 155]. The genome-wide haplotypes are employed in this strategy to find novel haplotypes in a wide variety of natural germplasm. For the discovery of QTLs/genes, recent GWA studies based on empirical and simulation data (i.e., better p-values) and allelic effect estimation have demonstrated that haplotype blocks have higher mapping accuracy and power than individual SNPs [153, 155, 156, 157, 158, 159, 160]. Haplotype superiority can be explained by a number of factors. Stephens and his colleagues [161] showed that haplotype blocks are more informative than SNP markers because of their multi-allelic character in nature. The scientists found that haplotype variants were more common than SNPs, implying that recombination and recurrent mutation events occurred within and among haplotype genes (Figure 1). In addition, as compared to individual SNPs, haplotype-based analysis is predicted to reduce the false positives and shows the intricate mechanism of causal haplotypes [162]. Similarly, the haplotype-assisted GS depicts the complex relationships between genotypic information and phenotypes more accurately than individual SNPs. As a result, this method could eventually aid in improving selection gain per unit of time. Because haplotypes can better capture LD and genomic similarities in various lines and may capture local high-order allelic interactions, they may improve the accuracy of genomic prediction [163]. Furthermore, by depicting population structure in the calibration set, prediction accuracy might be enhanced. The superiority of haplotype-based predictions over SNP-based predictions for all studied traits, including yield, test weight, and protein content, was established in a recent GS study that compared the prediction ability computed from haplotypes and SNPs in a set of 383 advanced lines and cultivars of wheat [164]. Based on evidence revealing higher haplotype-assisted genomic prediction efficiency than SNPs, researchers are increasingly embracing haplotype-assisted genomic prediction in crop development programmes.
Flow diagram indicating how haplotype-based GWAS and haplotype-based GS, when combined with high-throughput genotyping, have the potential to improve gene identification precision and accuracy (modified from Bhat et al. [
Significant progress has been made in wheat in developing various genomics resources, including high-throughput molecular markers, dense genetic maps, and next-generation genotyping platforms. The availability of high-quality wheat genome information has also enabled many next-generation sequencing-based approaches for genetic mapping, allele mining, and identification of candidate genes which have enhanced the precision, pace, and efficiency of trait mapping. At present, trait-associated markers, high-throughput genotyping platforms, and expertise are available for deploying genomics-assisted breeding in wheat. We believe that in the coming years, extensive deployment of genome editing, transgenic technology, genomic selection, haplotype-based breeding in combination or alone would be undertaken for crop improvement and breaking the yield ceiling. Various steps involved in generating high-yielding wheat genotypes using genomics-assisted breeding technologies are represented in Figure 2.
Flowchart demonstrating the steps involved in generating high-yielding wheat genotypes using different genomics-assisted breeding strategies.
Thanks are due to the Head, Department of Molecular Biology and Genetic Engineering, G. B. Pant University of Agriculture and Technology, Pantnagar, (India) for providing necessary facilities.
The authors declare no conflict of interest.
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"June 29th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:318,numberOfPublishedBooks:32,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/164957",hash:"",query:{},params:{id:"164957"},fullPath:"/profiles/164957",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()