International association-mapping studies of various traits using various markers in rice.
\r\n\tThis book will aim to present outcomes and novelties in essential oils treatments.
\r\n\tTherefore, it will collect the most recent scientific research on essential oils treatments and usage as well growth conditions, structure.
Rice is a traditional staple food crop in Korea and many other countries. Although the center of rice origin is still unclear, it is believed to be introduced from China to the Korean Peninsula in the early Bronze Age via one of two possible routes—across the West Sea or along the northeastern seashore from China according to Hammer (2005) and Vavilov (1935). Rice germplasm has evolved through several millennia of cultivation and selection by our farming ancestors. An important consequence of the domestication of both plants and animals is a reduction of genetic variability (Hancock, 2004). Maintaining biodiversity is an important worldwide problem and different countries have various policies intended to preserve biodiversity. Because conservation of biodiversity and ecosystems is closely linked to the quality of human life, the preservation and improvement of ecosystems are problematic for agriculture.
Genetic diversity in a crop species is essential for sustained high productivity. Breeding efforts have been devoted to improving grain quality, yield potential, resistance to diseases and insect pests, and environmental stress tolerance. Progress in plant breeding requires a continuous supply of genes or gene-complexes. In this respect, the researcher is often handicapped by the limited availability of germplasm resources. The assembly of large varietal collections, systematic screening for desired traits and subsequent incorporation of the relevant genes into existing cultivars is imperative to meet these needs. The use of landrace varieties has increased in recent years. Wild rice accessions have contributed greatly to rice breeding as a source of resistance genes (e.g., Xa21, BPH14, BPH15) (Ronald et al., 1992; Song et al., 1995; Yang et al., 2004; Du et al., 2009; Hu et al., 2012). Much of the diversity in the rice gene pool is contained in gene banks around the world. Molecular biology has contributed significantly to an increased understanding of many aspects of plant biology by generating technologies and methods of analysis that provide new approaches or supplement classical methods of analysis. Plant genetic resource scientists and other researchers are increasingly aware of the potential benefits of applying new technologies to germplasm conservation and research.
The integration of genetic data with molecular biotechnology will help breeders produce new rice varieties with the desired traits and make the conservation of rice genetic resources more efficient. Because of newly developed methods for association mapping of genes or QTLs related to desired traits, many genome-wide association analyses have been conducted in rice and resulted in valuable genome-wide association maps to describe the genetic architecture of complex traits. However, further efforts are needed to obtain more genomic information to fill in the gaps of our knowledge and meet the needs and challenges of rice breeding. This chapter will focus on the status of rice germplasm preservation activities, research programs, and outcomes of association mapping in rice in Korea.
The Ministry of Foreign Affairs and Trade (2009) had outlined eight major environmental issues as current threats to Korea; global warming, desertification, wildlife extinction, rain forest reduction, acid rain, depletion of the ozone layer, marine pollution, and air pollution. The rate of climate change is faster in Korea than the global average, leading to a rapid reduction in national biodiversity. One hundred and ninety families comprising 4000 species of vascular plants and ferns occur in Korea (Lee and Yim, 1978). Approximately 3700 different kinds of flowering plants are estimated to occur naturally (Chung, 1957; Lee, 1980). Four hundred and seven different endemic taxa in six genera are distributed throughout Korea (Lee, 1982). However, some plant species are on the verge of extinction because of pollution and a wide range of developmental activities during the last 20 years in Korea (Ministry of Environment, 1994), highlighting the importance of conservation efforts (Ahn et al., 1994). Conservation programs usually involve activities such as collection, characterization, evaluation, regeneration, documentation, and storage of each germplasm accession.
The National Biodiversity Strategy was implemented in 1997 to integrate and consolidate plans formulated by various ministries and government institutes, including Comprehensive Biological Resources Conservation Plans. The Rural Development Administration (RDA) Gene Bank is one of the institutions responsible for these plans. Rice research programs covering agronomic practices, physiology, post-harvest technology, grain quality evaluation, rice breeding and genetics, and biotechnology, are led by the National Institute of Crop Science (NICS) under the RDA. Other institutions affiliated with NICS carry out rice research programs to target specific problems in various regions of Korea. From 1980 to 1990, rice sheath blight (Acrocylindirum oryzae) was the most destructive disease affecting production from damaging approximately 555,000 hectares of rice paddy fields in Korea. Furthermore, rice pests including brown plant hopper, white-backed plant hopper, and small brown plant hopper attacked 586,000 hectares of rice nationwide during the same period (NASTI, 1996). A continuous cultivation of only five or six cultivars countrywide should be responsible to the extensive losses from the pests.
Rice season normally begins in mid-April and ends in mid-October in Korea. The lowest temperature in both April and October is 13°C. Because of the unprecedented yield loss due to cold damage in 1980 (damage to 80% of total rice hectarage and a yield reduction of 3.9 tons per hectare), cultivation of high-yielding “Tongil-type” rice cultivars declined rapidly, and only high-yielding japonica cultivars have been grown since 1990. In 2010, 20 mid- to late- maturing japonica cultivars were grown on 891,493 hectares, accounting for 92.9% of the total rice production area (Kang and Kim, 2012). Large decrease of temperature also occurred in 1971 and 2003, causing damage to 17% and 20% of total rice hectarage, respectively. Preharvest sprouting may become a serious problem for rice production, as well as for other crops, because of the trend in recent years for frequent and unusually heavy rain at harvest time. Breeders are making efforts to address this problem.
Rice breeders see the development of genetically improved cultivars using modern breeding techniques as an efficient way to reduce the losses in rice production caused by biotic and abiotic stresses. Sequencing the rice genome for genotyping and developing marker-assisted selection (MAS) system have fast-tracked research efforts. In the past, most national programs gave a lower priority to collecting wild relatives of rice than to collecting rice cultivars. Wild rice resources are agronomically unattractive, relatively expensive to conserve, and difficult to use. However, wild rice germplasms are known to contain a broad array of useful genes (Hodgkin, 1991). The benefits for the landrace germplasms to be used in breeding new cultivars in response to climate and environment changes in Korea are resistances to diseases in order to maintain superior qualities suited to consumers’ preferences. Plant germplasm resource activities in Korea are performed by The Basic Conservation Programme for Nature and Environment (1994–2003) under the Ministry of Environment (NASTI, 1996).
The RDA Gene Bank conserves 24,673 rice accessions, including Korean landraces and wild types. Many gene banks are having financial difficulty to maintain germplasm collections due to a rapid increase of accession number. These problems may restrict a full exploitation, evaluation, and utilization of these accessions, thus managing such collections presents major challenges (Holden, 1984). The concept of a core collection for resolving these problems has received increased attention over the last few years. Germplasm sampling methods include sequential, stratified, biased (for example, by ecology or country), and random sampling. An understanding of factors underlying the traits being sought will help reduce the time required for identification of useful genes. For very rare traits, such as some associated with resistance to virus infection, searching among wild Oryza species and O. glaberrima may be most appropriate. Efficient methods for evaluation of germplasm to identify genes for crop improvement will promote the use of conserved germplasm. Frankel and Brown (1984) proposed the concept of a core set of lines to resolve such problems. A desire core set should include the maximum genetic diversity in a crop species including its wild relatives with minimum repetition and provide a manageable set of accessions to gene bank managers, plant breeders, and research scientists. Such a core collection would become the focus of the search for desirable new characteristics, detailed evaluation, and development of new techniques. An initial set of 4406 rice accessions was selected based on ecological types and accession passport information, including their countries of origin. Using simple sequence repeat (SSR) genotype information, a final core set comprising the 166 conserved accessions currently used by the RDA was generated by a heuristic approach using the PowerCore software developed by Kim et al. (2007). Based on this resulted core set, some association mapping studies have been conducted and further researches are still being undertaken.
Association mapping analyzes loci in diverse populations and associates them with both one another and with phenotypes. It is a powerful genetic mapping tool for crops and provides high-resolution, broad allele coverage, and cost-effective gene tagging for the evaluation of plant germplasm resources. Genetic mapping of QTL can be performed in two main ways (Ross-Ibarra et al., 2007): (1) Linkage-mapping as well as “gene tagging” using experimental populations (also referred to as “biparental” mapping populations) and (2) LD-mapping or “association mapping” using diverse lines from the natural populations or germplasm collections (Abdurakhmonov and Abdukarimov, 2008). LD mapping is based on identification of associations between phenotype and allele frequencies. The advantage of LD mapping for the breeder is that mapping and commercial variety development can be conducted simultaneously (Langridge and Chalmers, 2005). For phenotypes or traits that are governed by multiple genes or QTLs, diverse alleles or advantageous allele combinations should be mined by association mapping followed by gene-tagging efforts using biparental crosses.
The localization of alleles relies on creating a statistical association between markers and QTL alleles and on the efficacy of markers. For markers to be effective, they must be closely linked to the target locus and be able to detect polymorphisms in material likely to be used in a breeding program. Improvements in marker screening techniques have facilitated the tracking of genes (Subudhi et al., 2006). Isoenzyme and other protein-based marker systems had in wide long been used before DNA markers became popular (Langridge and Chalmers, 2005). Since then, a variety of DNA-based molecular markers have been developed, including restriction fragment length polymorphisms (RFLPs), random amplified polymorphic DNAs (RAPDs) (Williams et al., 1990), amplified fragment length polymorphisms (AFLPs) (Vos et al., 1995), SSRs (Litt and Luty, 1989), single-strand conformational polymorphisms (SSCPs), cleaved amplified polymorphic sequence (CAPS) markers (Koniecyzn and Asubel, 1993), sequence tagged sites (STSs) (Olson et al. 1989), sequence-characterized amplified region (SCAR) markers (Martin et al., 1991), and single nucleotide polymorphisms (SNPs) (Brookes, 1999). A total of 2740 SSRs were experimentally confirmed for rice in 2002 or approximately one SSR for every 157 kb (McCouch, 2002). The highly polymorphic nature of many microsatellites is of particular value (Banni et al., 2012, Yoon et al., 2012, Moe and Park, 2012, Zhao et al., 2012a; Khaing et al., 2013) for analysis of closely related genotypes or within narrowly adapted gene pools. Thus, the availability of a high-density SSR map is a valuable public resource for interpretation of the functional significance of the rapidly emerging rice genome sequence information.
The next generation of genetic markers is based on SNPs, which provide an attractive tool for QTL mapping studies and marker-assisted selection in plant breeding programs (Mohler and Schwarz, 2005). SNP discovery is performed primarily in silico or using new sequencing approaches (Henry and Edwards, 2009). Large-scale SNP analysis is now possible in plants using a range of platforms. The increasing ease of sequencing and automated genotyping has made association mapping in plants a more attractive option by altering the conventional plant genome mapping method, which involves linkage analysis in a segregating population. This trend is likely to continue as the sequencing of genomes increases. Recently, genome-wide association studies (GWAS) with SNP variants have been conducted using new sequencing platforms (Table 1).
Genome mapping of rice was first attempted using linkage analysis of appearance or phenotype (Nagao and Takahashi, 1963). Nowadays, improvement of the linkage map has been achieved using isozymes (Nakagahra, 1977) and RFLPs and SSRs (McCouch et al., 1988; Saito et al., 1991; McCouch et al., 1991 and Yu et al., 1991, Tanksley et al., 1991, Causse et al., 1994; Kurata et al., 1994; Harushima et al., 1998; McCouch et al., 2002). Relatively few association-mapping studies in rice have been performed. Some rice association-mapping studies using various populations and molecular markers are summarized in Table 1 in which most are conducted using SSR markers.
Whole-genome resequencing is a promising strategy to identify the relationship between sequence variation and normal or mutant phenotypes. High-throughput genome resequencing - if accurate - has the advantage of allowing researchers to identify the specific nucleotides associated with a given phenotype, and allowing the effective detection and analysis of genetic variations important for molecular breeding. An important application of NGS is the resequencing of targeted regions for the identification of mutant alleles, and we believe that mapping by sequencing will become a centerpiece in efforts to discover the genes responsible for QTLs. Generally speaking, the availability of a wide range of low- and high-multiplex single nucleotide polymorphism (SNP) assay methods (sequencing accuracy and depth of coverage relies on the experimental design) makes SNPs an ideal marker option for QTL mapping, association analysis, MAS, and the construction of high-density genetic maps for fine mapping and cloning of agronomically important genes (McCouch et al., 2010).
SNP discovery by resequencing whole-genome or subgenome of sample materials is often among the first use of a reference genome sequence. For inbreeding species such as rice, lines to be resequenced are normally purified through 1 or 2 generations of inbreeding (via single seed descent). After a DNA sample is resequenced using NGS technology, SNPs can be identified by comparing the sequenced genome with a reference genome like Nipponbare for japonica rice. For example, using information on the features of the B73, Gore et al. (2009) targeted the gene fraction of the maize genome for resequencing in the founder inbred lines of the nested association mapping population. Two data sets comprising 3.3 million SNPs were used to produce a first haplotype map (“HapMap”) and to analyze the distribution of recombination and diversity along the maize chromosomes.
A suitable example is the construction of a comprehensive HapMap for rice that was used for the genome-wide associate study of 14 agronomic traits, such as heading date and tillering (Huang et al., 2010). The researchers made use of low-coverage (1-fold per rice line) sequence data across lines, for a combined coverage of ~508-fold, and detected 3.6 million SNPs which can explain ~36% of the phenotypic variance for 14 agronomic traits. This work provided a new approach to low-fold sequence coverage, which can be used to detect not only SNPs but also more complex polymorphisms, and partially overcome the need for deeper sequence coverage (Clark, 2010). Further study was performed with the similar strategy for 950 worldwide rice varieties by Huang et al. (2012) and thirty-two novel loci associated with flowering time and ten grain-related traits were identified. Additionally, 40 cultivated accessions selected from the major groups of rice and 10 from their wild progenitors (O. rufipogon and O. nivara) were resequenced to >15X raw data coverage (Xu et al., 2012). After mapping the sequence read back to an IRGSP reference genome, the authors investigated the genome-wide variation pattern in a comparative analysis. The data revealed examples of structural variation in genomes and included 6.5 million high-quality SNPs after excluding sites with missing data in any accession. Using these population and SNP data, the authors also identified thousands of new rice genes and tracked down those with a significantly lower diversity in cultivated, but not wild rice. These variants represent a valuable resource for those interested in improving rice cultivars.
Preferences in terms of the processing, cooking, and eating qualities of rice differ globally. Plant breeders are attempting to fulfill consumer demand for rice varieties with specific qualities. The major components of rice grain quality include appearance, milling, cooking, eating, and nutritional aspects. The chemical composition of rice grain is important because of its relationship with eating quality of rice. Amylose content is one of the most important traits that determine cooking quality, which is controlled by a major locus waxy (Wx) on chromosome 6 (Wang et al., 1992; He et al., 1999; Tan et al., 1999). Genes associated with amylose content, such as starch synthase IIa (SSIIa) and Wx, are of particular interest. Sano et al. (1986) identified two alleles of the Wx locus using RFLP markers that correspond to the indica and japonica subspecies. Most grain quality mapping studies have used the O. sativa germplasm (He et al., 1999; Tan et al., 1999, 2000, 2001; Zhou et al., 2003). Borba et al. (2010) conducted association mapping study on yield traits and grain quality traits including amylose content, and the significant association detected between amylose content and RM190 was in agreement with previous QTL analyses. Zhao et al. (2011) identified 44,100 SNP variants across 413 diverse rice accessions collected from 82 countries and observed GWAS for six categories of traits covering morphology related traits; yield-related traits; seed and grain morphology related traits; stress-related phenotypes; cooking, eating and nutritional-quality-related traits; and plant development, represented by flowering time. This study demonstrated that different traits have different genetic architectures.
Olsen and Purugganan (2002) elucidated the origin and evolution of glutinous rice based on the haplotype of the Wx gene. By using dCAPS markers, waxy mutations and waxy rice cultivation were shown to have occurred predominantly in the japonica line during the evolution of domestic rice cultivation (Yamanaka et al., 2004). Genetic polymorphisms of starch-synthesis genes have been demonstrated to be associated with starch physicochemical properties using molecular markers such as SSRs, SNPs, and STSs. These markers can be extremely useful in marker-assisted breeding (Bao et al., 2002; Bao et al., 2006a). SSIIa was identified as the major gene responsible for determination of gelatinization temperature (GT). Among four SNPs in the SSIIa gene, some that cause amino acid substitutions have been identified. The GC/TT SNP is strongly associated with GT (Bao et al., 2006b; Nakamura et al., 2005; Umemoto and Aoki, 2005; Waters et al., 2006).
Rice nutritional quality is another important factor for consumer acceptance. In developing countries where rice is the main food, its nutrient content makes a significant contribution to the intake of some essential nutrients. Interest in natural antioxidants in rice is growing due to their role in preventing oxidative stress-related diseases (Aguilar-Garcia et al., 2007; Willcox et al., 2004; Zhang et al., 2013). Rice contains antioxidant compounds such as γ-oryzanols, tocols, and polyphenols, which are associated with a reduced risk of developing chronic diseases such as cardio vascular disease, type 2 diabetes, and some cancers (Liu, 2007; Tan et al., 2001; Toyokuni et al., 2002). Pigments and flavonoids in colored rice are positively correlated with the antioxidant capacity (Xia et al., 2003; Yawadio et al., 2007). Association mapping of pigments and flavonoid contents was carried out in brown rice using SSR markers. Significant correlations between phytochemical content and marker loci were found and markers associated with multi-phenotypic traits such as grain color, phenolic content and antioxidant capacity were identified (Shao et al., 2011).
The amino acid composition of rice grain is an important characteristic related to nutrient quality. Environmental conditions, potash, and nitrogen dramatically influence the amino acid and protein contents of rice (Wu et al., 2004). Few reports of mapping of QTLs for the contents of protein and amino acids in rice grain have been published. Twelve main effect QTLs (M-QTLs) were identified for 10 components of amino acid content in milled rice. Most of the main effect QTLs for amino acid content tended to co-localize within the genome (Lu et al., 2009).
Although many QTL analyses and genetic mapping studies of grain quality have been conducted, association-mapping studies of biotic and abiotic traits in rice are few in number. The genes or QTLs related to these traits are complex. Genetic mapping, including association mapping and linkage mapping, are useful methods of identifying alleles for these traits. As shown in Table 1, most association-mapping studies focused on morphological and agronomic characteristics. Four studies were related to grain and eating quality and only one addressed disease resistance and aluminum tolerance. Biotic and abiotic stress-tolerance traits remain to be explored by association mapping.
\n\t\t\t\tReference\n\t\t\t | \n\t\t\t\n\t\t\t\tNumber of accessions and population type\n\t\t\t | \n\t\t\t\n\t\t\t\tNumber and types of markers used\n\t\t\t | \n\t\t\t\n\t\t\t\tTraits\n\t\t\t | \n\t\t
Virk et al., 1996 | \n\t\t\t200 rice accessions | \n\t\t\t7 RAPD | \n\t\t\tTen morphological traits; culm number, culm length, culm diameter, grain length, grain width, leaf length, leaf width, days to 50% flowering, panicle length and seedling height | \n\t\t
Zhang et al., 2005 | \n\t\t\t218 inbred lines, worldwide germplasms | \n\t\t\t60 SSR, 114 RFLPs | \n\t\t\tMultiple agronomic traits such as plant height, heading date, flag leaf length and width, tiller number, stem diameter, panicle length, grain length and width, grain length/width ratio, grain thickness, 1000-grain weight | \n\t\t
Iwata et al., 2007 | \n\t\t\t332 rice accessions | \n\t\t\t179 RFLPs | \n\t\t\tSize and shape of milled rice grains | \n\t\t
Agrama et al., 2007 | \n\t\t\t183 rice accessions | \n\t\t\t123 SSRs | \n\t\t\tGrain length and width, grain length/width ratio, 100 grain weight, grain thickness | \n\t\t
Yan et al., 2009 | \n\t\t\t90 accessions | \n\t\t\t108 SSRs + 1 indel | \n\t\t\tSingle, dual and total stigma exsertions and spikelet characteristics | \n\t\t
Wen et al., 2009 | \n\t\t\t170 rice accessions | \n\t\t\t126 SSRs, 6 indels | \n\t\t\tHeading date, plant height, panicle length | \n\t\t
Borba et al., 2010 | \n\t\t\t242 inbred lines, worldwide germplasms | \n\t\t\t86 SSRs | \n\t\t\tYield, amylose content, head-milled rice | \n\t\t
Huang et al., 2010 | \n\t\t\t517 landraces including japonica and indica | \n\t\t\t~3.6 million SNPs | \n\t\t\tFourteen agronomic traits | \n\t\t
Iwata et al., 2010 | \n\t\t\t332 rice accessions | \n\t\t\t179 RFLPs | \n\t\t\tGrain shape variation | \n\t\t
Jin et al., 2010 | \n\t\t\t416 rice accessions | \n\t\t\t100 SSRs | \n\t\t\tGrain color | \n\t\t
Ordonez Jr. et al., 2010 | \n\t\t\t192 elite rice breeding lines and tropical japonica germplasm base | \n\t\t\t97 SSRs | \n\t\t\tGrain quality and flowering time | \n\t\t
Zhao et al., 2010 | \n\t\t\t395 diverse O. sativa accessions | \n\t\t\t1,536 SNPs | \n\t\t\tAmylose content | \n\t\t
Famoso et al., 2011 | \n\t\t\t373 diverse O. sativa accessions | \n\t\t\t36,901 SNPs | \n\t\t\tAl tolerance | \n\t\t
Hu et al., 2011 | \n\t\t\t303 O. sativa accessions | \n\t\t\t24 SSRs | \n\t\t\tAwness | \n\t\t
Zhao et al., 2011 | \n\t\t\t413 diverse accessions of O. sativa\n\t\t\t | \n\t\t\t44,100 SNPs | \n\t\t\tThirty-four traits of agronomic characteristics, cooking and eating quality, disease resistance | \n\t\t
Bryant et al., 2011 | \n\t\t\t174 accessions | \n\t\t\t156 SSRs | \n\t\t\tSilica concentration in rice hulls | \n\t\t
Li et al., 2011 | \n\t\t\t217 accessions | \n\t\t\t154 SSRs and 1 indel | \n\t\t\tYield and yield components among 14 traits | \n\t\t
Lou et al., 2011 | \n\t\t\t48 accessions | \n\t\t\t218 markers (SSRs + indels) | \n\t\t\tGrain metabolites | \n\t\t
Shao et al., 2011 | \n\t\t\t416 rice accessions including 361 white rice, 50 red rice, and 6 black rice | \n\t\t\t100 SSRs | \n\t\t\tColor parameters of brown rice grain, phenolic content, flavonoid content and antioxidant activity | \n\t\t
Zhang et al., 2011 | \n\t\t\tA core collection consisting of 150 rice varieties | \n\t\t\t274 SSRs | \n\t\t\tSix morphological traits: glume hair, phenol reaction, length of 1st-2nd rachis internode, glume color at heading, leaf hair, and grain length/width | \n\t\t
Zhou et al., 2012 | \n\t\t\t128 japonica rice varieties | \n\t\t\t152 SSRs | \n\t\t\tEleven quantitative traits of agronomic and economic importance | \n\t\t
Huang et al., 2012 | \n\t\t\t950 worldwide rice cultivars | \n\t\t\t1,345,417 SNPs | \n\t\t\tFlowering time and grain yield traits | \n\t\t
Jia et al., 2012 | \n\t\t\t217 entries | \n\t\t\t154 SSR markers and 1 indel marker | \n\t\t\tSheath blight resistance | \n\t\t
Li et al., 2012 | \n\t\t\t203 accessions | \n\t\t\t154 SSRs and 1 indel | \n\t\t\tHarvest index and related components among 14 traits | \n\t\t
Clark et al., 2013 | \n\t\t\t233 rice (Oryza sativa) accessions | \n\t\t\t36,901 SNPs | \n\t\t\tRoot growth and development | \n\t\t
International association-mapping studies of various traits using various markers in rice.
To identify useful alleles from a representative core set of rice lines for transferring into elite lines, an allele-mining set of 166 accessions (Zhao et al., 2010) was successfully developed from 4046 rice accessions which were selected from 10368 accessions in the Korea RDA Gene Bank by 39 phenotype traits (Chung and Park, 2009), through a modified heuristic algorithm approach based on 15 SSR markers using the PowerCore software (Kim et al., 2007). Chung et al. also employed the PowerCore software of Kim et al. to develop the first preliminary core set by phenotypes. The gene diversity and population structure (Q) were analyzed using PowerMarker 3.25 (Liu and Muse, 2005) and Structure 2.2 (Evanno et al., 2005) based on 170 SSR markers. Analysis of these data identified the major substructure groups when the number of populations was set at four (Fig. 1).
Association mapping was conducted on this core set of lines over the past 2 years (as shown in Table 2). Zhao et al. (2012b) analyzed 130 accessions from the core set using 170 SSR markers for association analysis of physicochemical traits related to eating quality. Linkage disequilibrium (LD) patterns and distributions are of fundamental importance for genome-wide mapping associations. The mean r2 value for all intrachromosomal loci pairs was 0.0940. LD between linked markers decreased with distance. Marker–trait associations were investigated using the unified mixed-model approach considering both Q and kinship (K). In total, 101 marker–trait associations (P <0.05) were identified using 52 SSR markers covering 12 chromosomes (Fig. 2.). Although direct comparisons of the chromosomal locations of marker–trait associations with previously reported QTLs are difficult because different materials and mapping molecular markers were used, most marker–trait associations were located in regions containing QTLs associated with a given trait. Indeed, some were located in similar or proximal regions related to starch synthesis. The new markers related to eating quality will facilitate the understanding of QTLs and marker-assisted selection (Zhao et al., 2012b).
Values of ΔK, with its modal value used to detect the true K of four groups (K = 4). For each K value, five independent runs (blue diamonds) were considered and averaged over the replicates (Zhao et al., 2012b).
\n\t\t\t\tReference\n\t\t\t | \n\t\t\t\n\t\t\t\tNumbers of lines and population type\n\t\t\t | \n\t\t\t\n\t\t\t\tNumber and types of markers used\n\t\t\t | \n\t\t\t\n\t\t\t\tTraits\n\t\t\t | \n\t\t
Zhao et al., 2009 | \n\t\t\t84 accessions from land race core set | \n\t\t\t25 SSRs | \n\t\t\t16 amino acids | \n\t\t
Zhao et al., 2012 | \n\t\t\t130 accessions from core set | \n\t\t\t170 SSRs | \n\t\t\tEating quality | \n\t\t
Lu et al., 2012a | \n\t\t\t104 accessions from core set | \n\t\t\t86 SNPs and indels | \n\t\t\tAmylose content, RVA | \n\t\t
Lu et al., 2012b | \n\t\t\t107 accessions from core set | \n\t\t\t83 SNPs, indels, and SSRs | \n\t\t\tAmylose content, RVA | \n\t\t
Rice association-mapping studies for various traits and marker types in Korea.
The positions of markers used and marker–trait associations on 12 chromosomes except unmapped markers. Genetic distances are indicated as cM on the left of each map and the corresponding trait-marker names are indicated on the right. AC, amylase content; PKV, peak viscosity; TV, trough viscosity; BD, breakdown viscosity; FV, final viscosity; SBV, setback viscosity; PKT, peak time; fa, degree of polymerization (DP) ≤12; fb2, 24<DP ≤36; fb3, DP<36 (Zhao et al., 2012b).
Association analysis of candidate genes has been used to trace the origin of agronomically important traits. Lu et al. (2012a) used the rice core lines for association-mapping to investigate the relationship between sequence variations from parts of 10 SSRGs and the amylose content (AC) and rapid viscosity analysis (RVA) profiles. Eighty-six sequence variations were found in 10 sequenced amplicons including 79 SNPs, six insertion-deletions (indels), and one polymorphic SSR. Among them, 61 variations were exon-based, of which 41 should lead to amino acid changes. The association mapping results showed a sum of four significant associations between three phenotypic indices and three sequence variations. An ADP - glucose pyrophosphorylase small subunit 1 (OsAGPS1) SNP (A to G) was significantly associated with increased AC (P <0.001, r2 = 15.6%) while a 12-bp deletion of an AGPase large subunit 4 (OsAGPL4) (Table 3) was significantly related to decreased breakdown viscosity (P <0.001, r2 = 16.6%) in both general linear model (GLM) and mixed linear model (MLM) (Lu et al., 2012a). One SNP with a g/c transversion at the 63rd nucleotide downstream of the OsBEIIb gene termination codon on rice chromosome 2 was significantly associated with multiple trait indices in both the GLM and MLM, including the final viscosity (P <0.001, r2 = 23.87%), in both 2009 and 2010, and AC (P <0.01, r2 = 11.25%) and trough viscosity (P <0.01, r2 = 20.43) in 2010 (Table 4). This study provided a new perspective on the use of allele mining in breeding strategies based on marker-assisted selection (Lu et al., 2012b).
\n\t\t\t\t | \n\t\t
Association between sequence variations and phenotype
AAc, amino acid changes; P_GLM, adjusted P-values with 1000 permutations; P_MLM, P-values significant in the FDR test; amino acid code: S, serine; A, alanine; N, asparagine; D, aspartic acid; BDV, breakdown viscosity; AC, amylase content; FV, final viscosity (Lu and Park, 2012a).
\n\t\t\t\t | \n\t\t
Associations between sequence variations and eating quality indicators.
P_GLM: adjusted P-values with 10,000 permutations in GLM; P_MLM: nominal P-values in MLM; Q value: adjusted nominal P-value in MLM by false discovery rate; AC: amylose content; PV: peak viscosity; TV: trough viscosity; FV: final viscosity (Lu and Park, 2012b).
Zhao et al. (2009) evaluated the contents of 16 amino acids in brown rice by genotyping using 25 SSR markers. A total of 42 marker-trait associations for amino acid content covering three chromosomes (P <0.05) were identified by the MLM model (Fig. 4), which accounted for more than 40% of the total variation (Zhao et al., 2009). In our research group, association mapping of rice traits related to cold-stress tolerance during germination, preharvest sprouting resistance, salt tolerance, blast disease resistance, and grain physicochemical properties are undertaken using SSRs and SNP variants on advanced resequencing platforms.
Three regions of putative marker–trait associations on three chromosomes (3, 7, and 8) for amino acid content in brown rice. Genetic distances are indicated in cM on the left of each map and the corresponding marker names are indicated on the right. Ala, alanine; Arg, arginine; Asp, aspartic acid; Glu, glutamine; Gly, glycine; His, histidine; Ile, isoleucine; Leu, leucine; Lys, lysine; Met, methionine; Phe, phenylalanine; Pro, proline; Ser, serine; Thr, threonine; Tyr, tyrosine; Val, valine (Zhao et al., 2009).
In conclusion, association mapping is a promising approach to overcoming the limitations of conventional linkage mapping in plant breeding. Recent research has demonstrated the significant potential of LD-based association mapping of physicochemical traits and other important agronomic traits in rice accessions using SSR/SNP markers. This type of mapping could be a useful alternative to linkage mapping for the detection of marker–trait associations, and lead to implementation of marker-assisted selection in rice breeding programs.
With the development of next- and third-generation sequencing technologies, the whole genomes of individual rice accessions can now be sequenced with less than $ 1000 (US dollar). Also, new efficient genotyping technologies, such as RADs (Restriction Associated DNAs) (Baird et al., 2008) and GBS (Genotyping-by-Sequencing) allow the generation of genotyping data for up to 40,000 genes at low cost in few days.
Natural alleles and alleles obtained from artificially mutagenized populations provide an important resource for crop breeding. By using all available alleles and detailed phenotypic data from core sets of rice lines, new genes and useful traits can be identified. Molecular tags for useful traits developed using GWASs based on genotypic and phenotypic information can be used to track target traits during segregation of populations in rice breeding (Figure 4).
A schematic illustration of inter-disciplinary relationships between genomic research and other fields in the breeding of crop species.
To identify new alleles from a representative core set of rice lines and transfer them into elite lines, we finally selected 166 from ~25,000 accessions in the RDA Gene Bank. We completed whole-genome resequencing of 84 core accessions with 7x coverage in 2012. We plan to resequence the whole genomes of the remaining 82 core accessions in addition to 84 bred varieties from a validation set in 2013. We are currently undertaking the phenotyping of the core accessions for agronomic traits, and chemical composition for the GWAS analysis with the resequence information. We are also planning to improve the software algorithm for the association analysis to increase the ability to identify alleles from the core set of lines using whole genomic SNP or indel genotype data and phenotypic information. More precise characterization of rice traits that confer resistance to stress from climate change is required to screen useful alleles using GWASs. Using whole-genome genotype information, we are able to develop large numbers of molecular tags across 12 different rice linkage groups based on their contributions to specific phenotypes.
The core accessions are highly diverse with many traits useful for rice breeding. Upon selection of an accession with a desirable trait, bi-parental mapping populations will be developed using two japonica varieties (Shindongjinbyeo and Junambyeo) and one indica variety (Hanareumbyeo). Major QTLs will be surveyed with an F8 RIL-segregating population using whole-genome resequencing of 96 samples for first mapping, and then, we can resequence this target region using the expanded 3000 to 5000 samples for fine mapping till the targeted gene can be cloned. We expect that all major QTLs will contribute more than 10% to target traits. To identify minor QTLs that contribute less than 10% to a target trait, BC4F1 population will be first developed, and then, selfing will be done till BC4F8. The recurrent parent will be an elite line for the purposes of QTL mapping and for transferring target traits into the elite lines. Mapping of minor QTLs will be performed using a BC4F8 segregating population (as shown in Fig. 5).
Natural variation results from the expression of different alleles during evolution. As a result of the contributions to farmers over the past ~8000 years, many important traits have been accumulated in the natural germplasm collections currently maintained in seed banks. Whole genome resequencing allows efficient identification of unused alleles from conserved germplasm. We are at present developing a platform for allele mining in rice breeding systems using GWAS approaches and diverse germplasm accessions with the support of the Next-Generation BioGreen 21 Program (No.PJ009099) from Rural Development Administration, Republic of Korea. We believe our effort will facilitate the molecular breeding of rice.
Strategies for identification of major and minor QTLs in rice from selected accessions carrying useful traits through GWAS. The major QTLs will be localized and tagged by molecular markers in the F8 generation. Minor QTLs will be localized using a BC4F8 population.
Scars are a natural part of dermal healing following lacerations, incisions, or tissue loss. Wound healing, which is a natural process of tissue repair, consists of three phases: inflammation, fibroplasia, and maturation. The healing tissue generates changes in the cutaneous architecture, which renders the skin surrounding the scar different from the rest of the skin in terms of color, thickness, elasticity, texture, and degree of contraction [1]. In surgical procedures, scars, which are the only visible sequela of the intervention, result from the reparation process undergone by the skin to heal the wounds caused by surgery or trauma. Because of its impact in scarring, considerable importance is placed on the closure of a surgical incision, which is the final phase of the intervention [2]. The ideal scar is narrow, flat, level with surrounding tissue, and difficult for the untrained eye to see due to color match and placement parallel to relaxed skin tension lines. In contrast, hypertrophic, keloidal, dyspigmented, widened, contracted, or atrophic scars can be unsightly and/or cause functional limitations, which patients often perceive as a problem.
\nThus, when the scar has unfavorable characteristics, scar revision is often indicated. Furthermore, as poor-quality healing of an incision can constitute a disabling pathology [3], scar treatment should not be considered as a trivial part of the intervention. On the contrary, wound treatment and care after surgery of any kind, including esthetic or reconstructive interventions, should be initiated early. In order to arrive at an effective esthetic and functional outcome, surgeons must be familiar with the different scar treatments available, and they must also know how to prevent scars and how to reduce them after surgery. In this sense, it should be borne in mind that, while there exist multiple treatment modalities, none of them guarantees a 100% success rate. Current guidelines suggest a multimodal approach to treating scars but there is no gold standard for their treatment. In this chapter, we will present two new ways to treat scars following plastic surgery. As explained in the following sections, these techniques were successfully implemented in a number of cases, and their comparative advantages regarding other methods were also evaluated. We hope that our contribution will help point in the direction toward an effective, uniform standard.
\nThe first part of our research deals with cosmetic surgery scars, which generally receive different topical treatments that help maintain the moisture and the plasticity of the wound. Besides, these treatments prevent wound contamination or infection, which would delay healing. We have analyzed and compared the results of two of these treatment options and found that the best functional and esthetic results are obtained when using a cream with active ingredients. The second part of our research revolves around the combined use of two skin substitutes, cadaver skin and artificial skin, so as to obtain improved results in reconstructive surgery after trauma injuries with abnormal wound healing in response to skin trauma or inflammation. Employing dermal substitutes result in a better regeneration of the dermis and in dermal fibroblast optimization. In the next sections, we will present a detailed account of the two studies we have carried out, which will allow us to further discuss the aforementioned techniques to optimize surgical scars.
\nAs we have already mentioned, the first study involved the comparison and evaluation of two topical treatments applied to scars resulting from cosmetic surgery. One was a cream containing 1 g of silver sulfadiazine, 248,000 IU of vitamin A and 0.666 g of lidocaine in each 100 g of product (Platsul-A®, Soubeiran Chobet Laboratory, Autonomous City of Buenos Aires, Argentina) (cream A), and the other was a moisturizing cream based on petrolatum, keto-stearyl alcohol, glycerin, and water without any active ingredient (cream B). About 32 patients participated in the study; 24 with bilateral breast implants and 8 with face and neck lifts, hence totaling 64 scars. The study included patients of both sexes: 31 women and 1 man, with ages ranging from 22 to 64 years (mean of 41 years). All patients received both topical treatments under study, each of their postsurgical scars (right and left) being applied one of the creams at random. We monitored patients for 1 month after the beginning of treatment, meeting them at an initial appointment and at subsequent appointments after 3, 6, 9, 16, 23, and 30 days from the intervention. Each patient’s progress was checked by the same medical examiner.
\nIn these appointments, we measured the length and width of the scars to determine their total surface and assessed them in accordance with the Vancouver scar scale (VSS) and the patient and observer objective assessment scale (POSAS). We evaluated (1) the surface area of each scar by multiplying its length by its width, as measured with a ruler with graduation, (2) the quality of each scar as assessed by the VSS, [4] taking into account the parameters of pigmentation, vascularity, and thickness, and (3) the patient’s perception of each scar as appraised by the POSAS, [5] by having them rank a series of symptomatic and esthetic parameters. The results are reported as follows, discriminated on the basis of the type of surgery performed.
\nIn the group of patients with breast implants, the percentage of change did not differ significantly between the two treatments studied in the appointments of days 3, 6, 9, 16, and 23. On day 30, however, we detected a statistically significant difference (P = 0.017). The percentage of decrease was significantly higher in the scars treated with the cream with silver sulfadiazine, vitamin A, and lidocaine (cream A) than in those treated with the cream without active ingredients (cream B) (18.6 and 9.5%, respectively) (Table 1). In the group of patients with face and neck lift, there was no significant difference between the percentage of change achieved due to the two treatments on days 3, 6, 9, and 16. Nevertheless, on days 23 and 30, we encountered a statistically significant difference (P = 0.026 and P = 0.007, respectively). The percentage of decrease was significantly higher in the scars treated with cream A than in those that had been treated with cream B. On day 23, the surface area of the scars treated with cream A had decreased, on average, by 14.8%, while that of the scars treated with cream B had increased, on average, by 24.9%. On day 30, the surface area of the scars treated with cream A had decreased, on average, by 19.1%, whereas that of the scars treated with cream B had increased, on average, by 22.2% (Table 2). Figure 1 shows the changes in the surface area of each patient’s scars on days 23 and 30 with respect to the initial appointment and classifies the results according to the type of surgery undergone and the treatment received. As we can see, more favorable results were obtained with cream A than with cream B, except in the case of two patients with breast implants (patients No. 7 and 12).
\nDays | \nAverage percentage of change of the surface area as from treatment onset (breast implant) | \nP | \n|
---|---|---|---|
Cream A (%) | \nCream B (%) | \n||
3 | \n4.2 | \n0.0 | \n0.97 (NS) | \n
9 | \n2.6 | \n3.7 | \n0.37 (NS) | \n
16 | \n−1.8 | \n−6.0 | \n0.40 (NS) | \n
23 | \n−12.8 | \n−7.2 | \n0.089 (NS) | \n
30 | \n−18.6 | \n−9.5 | \n0.017* | \n
Average percentage of change of the surface area of the scars treated with silver sulfadiazine, vitamin A, and lidocaine (cream A) and with a cream without active ingredients (cream B) in patients with breast implants after 3, 6, 9, 16, 23, and 30 days from the onset of the topical treatment.
Significant: at 5%.
NS: not significant.
Days | \nAverage percentage of change of the surface area as from treatment onset (face and neck lift) | \nP | \n|
---|---|---|---|
Cream A (%) | \nCream B (%) | \n||
3 | \n12.5 | \n12.5 | \n+ | \n
6 | \n12.5 | \n12.5 | \n+ | \n
9 | \n12.3 | \n12.4 | \n0.60 (NS) | \n
16 | \n2.1 | \n24.9 | \n0.07 (NS) | \n
23 | \n−14.8 | \n24.9 | \n0.026* | \n
30 | \n−19.1 | \n22.2 | \n0.007** | \n
Average percentage of change of the surface area of the scars treated with silver sulfadiazine, vitamin A, and lidocaine (cream A) and with a cream without active ingredients (cream B) in patients with face lift after 3, 6, 9, 16, 23, and 30 days from the onset of the topical treatment.
Significant at 5%.
Significant at 1%.
No surface area changes were perceived in any patient in either of the treatments.
NS: not significant.
Percentage changes of the scar surface area, per patient after 23 and 30 days from treatment onset.
The VSS assigns values to the scar pigmentation, vascularity, and thickness, which are then added to obtain a total. Although the score may vary between 0 and 10, the average of the initial scores in our study was 2.7 and the maximum value observed throughout the study was 5. We conducted the analysis taking into account the absolute change in the VSS score with respect to the initiation of treatment (day 0). Results are expressed in absolute values. The analysis is carried out separately for each group of patients, depending on the type of surgery, on days 3, 6, 9, 16, 23, and 30.
\nIn the breast implant patient group, the VSS score change did not differ significantly between treatments on days 3, 6, 9, and 16. On days 23 and 30, nonetheless, we noticed a statistically significant difference (P = 0.02 and P = 0.006, respectively). The decrease was significantly higher in the scars treated with cream A in comparison with those treated with cream B. On day 23, the score of the scars treated with cream A decreased by 1.13 points average, while that of the scars treated with cream B increased by 0.04 points average. On day 30, the average score decrease was of 1.88 points in those treated with cream A and of 0.42 points in those treated with cream B (Table 3).
\nDays | \nAverage change in the VSS score as from treatment onset (breast implant) | \nP | \n|
---|---|---|---|
Cream A | \nCream B | \n||
3 | \n0.33 | \n0.21 | \n0.80 (NS) | \n
6 | \n0.13 | \n0.29 | \n0.30 (NS) | \n
9 | \n−0.21 | \n0.46 | \n0.10 (NS) | \n
16 | \n−0.42 | \n0.29 | \n0.09 (NS) | \n
23 | \n−1.13 | \n0.04 | \n0.02* | \n
30 | \n−1.88 | \n−0.42 | \n0.006** | \n
Average change in the VSS score of scars treated with silver sulfadiazine, vitamin A, and lidocaine (cream A) and with a cream without active ingredients (cream B) in patients with breast implants after 3, 6, 9, 16, 23, and 30 days from the onset of the topical treatment.
Significant at 5%.
Significant at 1%.
VSS: Vancouver scar scale.
NS: not significant.
In the group of patients with face and neck lift, the change in the VSS score did not differ significantly between treatments after 3 days. Yet, in all of the following appointments, a statistically significant difference (P ˂ 0.05) was observed. The reduction of the score was significantly higher in scars treated with cream A than in those treated with cream B. On day 23, scars treated with cream A had decreased by 0.86 points average, while those treated with cream B had increased by 1.75 points average. On day 30, the average score decrease of scars treated with cream A was 1.88 points, while the score of scars treated with cream B increased by 1.88 average points (Table 4). Figure 2 displays the changes in the VSS scores for each patient with breast implants on 23 and 30 days, compared to the initial control. In a majority of patients, we see a favorable effect with the cream A treatment compared to cream B, except for three cases (patients No. 16, 28, and 30). Figure 3 illustrates the changes in the VSS scores for each patient with face and neck lifts on days 6, 9, 16, 23, and 30 with respect to the initial appointment. In most cases, cream A shows a more favorable effect in comparison with cream B. Regardless of whether cream A or B had been used, in general, the changes observed in the VSS, either increase or decrease, were homogeneous in the three variables that make up this scale: pigmentation, vascularity, and thickness of the scar. Figures 4–6 illustrate the different results obtained when applying each cream.
\nDays | \nAverage change in the VSS score as from treatment onset (face and neck lift) | \nP | \n|
---|---|---|---|
Cream A | \nCream B | \n||
3 | \n0.50 | \n1.50 | \n0.17 (NS) | \n
6 | \n0.13 | \n1.50 | \n0. 048* | \n
9 | \n−0.13 | \n2.00 | \n0.029* | \n
16 | \n−0.50 | \n1.88 | \n0.029* | \n
23 | \n−0.86 | \n1.75 | \n0.020* | \n
30 | \n−1.88 | \n1.88 | \n0.007** | \n
Average change in the VSS score of scars treated with silver sulfadiazine, vitamin A, and lidocaine (cream A) and with a cream without active ingredients (cream B) in patients with face lift after 3, 6, 9, 16, 23, and 30 days from the onset of the topical treatment.
Significant at 5%.
Significant at 1%.
VSS: Vancouver scar scale.
NS: not significant.
Changes in VSS scores for each patient with breast implants after 23 and 30 days from treatment onset of treatment. VSS: Vancouver scar scale.
Changes in VSS scores for each patient with cervical-facial stretch and after 6, 9, 16, 23, and 30 days from treatment onset. VSS: Vancouver scar scale.
Same patient’s evolution with cream A (left) versus cream B (right) following a breast implant intervention (submammary incision).
Same patient’s evolution with cream A (left) versus cream B (right) following a face lift intervention.
Same patient’s evolution with cream A (left) versus cream B (right) following a breast implant intervention (periareolar incision).
This scale allowed us to evaluate numerically, based on the patient’s own answers, scar characteristics related to pain, itching, color, stiffness, and thickness. The treating physician recorded the data reported for each variable and for each scar during the corresponding appointments. Although the score may vary between 0 and 60, the average of the initial scores was 16 and the maximum value observed throughout the study was 25. We carried out the analysis taking into account the percentage change in the score of the scale with respect to that of the beginning of the treatment (day 0). We evaluated the results separately for each group of patients, depending on the type of surgery performed, and we considered the results obtained on days 3, 6, 9, 16, 23, and 30 of the postoperative period.
\nIn the group of patients with breast implants, the percentage change of the score of the POSAS did not differ significantly between the treatments on days 3 and 6, but in the remaining appointments, we found a statistically significant difference (P < 0.05) in favor of cream A. The percentage decrease in the score was significantly higher in those scars treated with cream A than in those treated with cream B. On day 23, the score of scars treated with cream A decreased by 21.8 points average, while that of the scars treated with cream B did so by 1.3 points average. On day 30, the average score decrease was of 37.7 points in scars treated with cream A while, in those treated with cream B, the decrease was 7.3 points average (Table 5).
\nDays | \nAverage change in the POSAS score as from treatment onset (face and neck lift) | \nP | \n|
---|---|---|---|
Cream A | \nCream B | \n||
3 | \n2.5 | \n8.5 | \n1.0 (NS) | \n
6 | \n1.7 | \n7.8 | \n0.129 (NS) | \n
9 | \n−6.2 | \n7.1 | \n0.026* | \n
16 | \n−9.9 | \n6.6 | \n0.037* | \n
23 | \n−21.8 | \n−1.3 | \n0.005** | \n
30 | \n−37.7 | \n−7.3 | \n0.0007** | \n
Average POSAS score change rate for scars with silver sulfadiazine, vitamin A, and lidocaine (cream A) and with a cream without active ingredients (cream B) in patients with breast implants after 3, 6, 9, 16, 23, and 30 days from the onset of the topical treatment.
Significant at 5%.
Significant at 1%.
POSAS: patient and observer scar assessment scale.
NS: not significant.
In the group of patients with face and neck lifts, the percentage change in the POSAS score did not differ significantly between the treatments on days 3, 6, 9, 16, and 23. On day 30, however, we detected a statistically significant difference (P = 0.021) in favor of cream A. The percentage decrease was significantly higher in cases treated with cream A versus those treated with cream B. On day 30, the score of scars treated with cream A decreased, on average, by 14.4%, while that of the scars treated with cream B increased, on average, by 26.6% (Table 6). Figure 7 presents the percentage changes of the POSAS scores for each patient with breast implants on days 9, 16, 23, and 30 with respect to the initial appointment, differentiated according to the treatment applied. In most patients, we see that the treatment with cream A resulted in a more favorable effect than that obtained with cream B, except for two cases (patient No. 15, days 9 and 16; and patient No. 13, day 16). Figure 8 shows the percentage changes of the POSAS scores for each patient with face and neck lift between the onset of the treatment and day 30 and organizes the results based on the cream employed. In most cases, a better outcome was reached with cream A than with cream B. Irrespective of the cream applied, in general, the changes observed, either increase or decrease, reflected homogeneous changes in the variables that constitute this scale.
\nDays | \nAverage change in the POSAS score as from treatment onset (breast implant) | \nP | \n|
---|---|---|---|
Cream A | \nCream B | \n||
3 | \n22.1 | \n18.2 | \n0.66 (NS) | \n
6 | \n18.2 | \n20.2 | \n0.40 (NS) | \n
9 | \n19.0 | \n26.3 | \n0.26 (NS) | \n
16 | \n18.0 | \n23.9 | \n0.36 (NS) | \n
23 | \n−1.4 | \n32.7 | \n0.07 (NS) | \n
30 | \n−14.4 | \n26.6 | \n0.021* | \n
Average POSAS score change rate for scars with silver sulfadiazine, vitamin A, and lidocaine (cream A) and with a cream without active ingredients (cream B) in patients with face lift after 3, 6, 9, 16, 23, and 30 days from the onset of the topical treatment.
Significant at 5%.
POSAS: patient and observer scar assessment scale.
NS: not significant.
Percentage POSAS score changes for each patient with breast implants after 9, 16, 23, and 30 days from the beginning of treatment. POSAS: patient and observer objective evaluation scale.
POSAS score changes for each patient with face lift after 30 days from treatment onset. POSAS: patient and observer objective evaluation scale.
The results showed an improvement of all the evaluated variables when we used the cream with silver sulfadiazine, vitamin A, and lidocaine as treatment [6]. In all the scars treated in this way, we observed a greater percentage decrease of the surface area as compared with those treated with the cream without active principles. In addition, the scars treated with silver sulfadiazine, vitamin A, and lidocaine obtained a lower POSAS score, associated with a better scar quality. Such decrease in the POSAS score throughout the treatment is indicative not only of a more positive perception by the patient of the healing process but also of improvement of all the parameters evaluated: pain, itching, color, stiffness, thickness, and irregular scarring [7]. Therefore, our results indicate that performing a topical treatment with a cream containing silver sulfadiazine, vitamin A, and lidocaine from the beginning of treatment decreases wound size faster, improves the quality of the scar and the overall perception of the patients. In other words, such a treatment of postcosmetic surgery scars yields better esthetic and functional outcomes [8].
\nThe other treatment we are concerned with involves using different dermal substitutes in reconstructive surgery. Soft tissue impairment after an accident requires fast radical treatment and often multiple surgical procedures related to necrotic and poorly perfused tissue. Traditionally, dermal reconstruction meant harvesting grafts and flaps, which left major sequelae in donor sites. However, modern understanding of the composition of the skin has enabled researchers to develop numerous cutaneous substitutes which allow for the reconstruction of the dermis by providing a scaffold that promotes new tissue growth, thus compensating for the functional and physiological impairments caused by damaged tissue. Moreover, they offer the attractive possibility of employing grafts to treat large burns.
\nSkin substitutes are biomatrices that may be used to replace the damaged epidermis or dermis (or both) partially or totally, transitory or definitively. Although they can be classified in different ways [9], they fall broadly into two groups, either decellularized dermis derived from human or animal sources or artificially constructed scaffolds comprised of highly purified biomaterials or synthetic polymers. Many of these substitutes act by guiding the patient’s own cells to form a neodermis, both reducing pain and improving healing by avoiding excessive scarring [10]. They allow practitioners to create a controlled environment appropriate for physiology and cellular function, as well as to identify and properly manipulate the cells so that parenchyma, stroma, and vascular components are generated, and to produce materials malleable by the cells.
\nOne such cutaneous substitute is Integra®, which consists of a matrix of purified collagen from bovine tendon cross-linked with glycosaminoglycan obtained from shark cartilage and a silicone layer that functions as a temporary epidermis. It is a bilayer membrane system, consisting of an inner dermal substitute layer and a temporary outer epidermal substance layer. The inner layer is composed of a three-dimensional matrix of cross-linked bovine tendon collagen plus a glycosaminoglycan, and the outer layer is made of silicone. Integra® was introduced by Burke and Yannas in the early 1980s. The aim of their research was to find a substitute for the skin of patients with massive burns [11]. Nowadays, Integra® is a fundamental part of the “reconstructive ladder” and is utilized for treating skin loss resulting from burns, trauma and oncologic and pressure sore surgery [12]. After application of Integra®, the patient’s native fibroblasts, macrophages, and lymphocytes infiltrate and new capillary growth occurs into the matrix of the inner layer. The inner layer becomes degraded and an endogenous collagen matrix is deposited by the patient’s own fibroblasts, forming a neodermis. Once engraftment is complete, 2–3 weeks after application, the outer silicone layer needs to be removed and an epidermal autograft must be placed over the neodermis. One of the advantages of this process is that successful neodermis formation requires only a thin skin graft which provides epidermal coverage which also prevents infections. Furthermore, as no donor site is created, it eliminates the risk of donor site wound complications.
\nAnother skin substitute is cadaver skin or homograft, which was included in protocols for the first time in the year 1981 in Philadelphia, United States. By virtue of the processing of cadaver skin through a skin bank, a suitable substitute is obtained and distributed to potential receptors [13]. Depending on the way in which they are processed, these “acellular dermal homografts” (as Takami describes them [14]) can be used transiently or permanently. To reduce the probability of graft rejection, cadaveric grafts undergo a cell-removal process and the resulting acellular tissue is irradiated with gamma rays, which destroy the immunogenic potential of the tissue. Employing cadaver skin to treat severe trauma of lower limbs with skin impairment has a number of advantages. To begin with, this treatment produces a biological closure after escharectomy. Furthermore, it helps reduce the loss of fluids, proteins, and electrolytes, as well as the pain experienced by the patient. Apart from this, it prevents the desiccation of the wound bed, since it functions as a biological cover for complex wounds, ultimately improving the preparation of the wound bed before definite reconstruction [15]. Finally, the addition of artificial skin over the vascularized homologous dermis creates a dermal structure of greater thickness and elasticity.
\nAnother recent development which is of great importance for reconstructive surgery is vacuum therapy (VAC), which improves wound healing by means of two main mechanisms. In the first place, it acts on the interstitial level eliminating edema, inflammatory mediators, and bacteria. It thus combats the vicious cycle of increased interstitial edema and pressure, cell death, and necrosis which is begotten by the inflammatory response triggered after a lesion. In addition, this treatment promotes mitogenesis and granulation tissue formation [16]. VAC is relevant to our research since, as Morykwas explains, it can be used to help incorporate Integra® and skin grafts as permanent replacements. Using a vacuum system after the escharectomy and the homograft placement and 1 week after positioning the artificial skin and the ultrathin autograft favors the arrest of these two substitutes. Moreover, negative pressure wound therapy can help augment the healing process and prepare the wound for definitive closure. A review published in Cochrane in 2007 [21] reported that, after 6 months of treatment, a 71% success rate had been observed in wounds treated with both artificial skin and negative pressure through a vacuum system, whereas the success rate of wounds treated solely with negative pressure had been, at 37%, significantly lower. In terms of wound healing, even better results were obtained when Integra® was used as a dermal substitute [22].
\nAs a consequence of the benefits we have mentioned, dermal substitutes have now been extended to treat other pathologies. Furthermore, the use of cutaneous substitutes added to the vacuum therapy has been incorporated into the “Modified Ladder of Reconstruction” [17]. However, the usefulness of treating large wounds with deep skin impairment with both cadaver skin and artificial skins has not been, to date, exhaustively studied. Therefore, we wish to contribute to this line of research by reporting the successful esthetic and functional results we have obtained when treating extensive skin lesions with both substitutes. Our study involved the follow-up of the wound healing of four patients (N:4) who had suffered high impact trauma in their lower limbs (Figure 9) and who were treated at Hospital Alemán in the city of Buenos Aires. All of them were females with ages ranging from 19 to 73 years (median: 32 years). All of their lesions belonged to Group 4 of Benaim’s severity classification and ranked as full-thickness burns in Benaim’s depth classification [18]. The affected body surface was calculated based on the rule of nines described by Pulaski and Tennison in 1949 [19] (Figure 10) with the following results: 8% in the 19-year-old patient, 24% in the 22-year-old, 28% in the 43-year-old, and 8% in the 73-year-old (Table 4).
\nFull-thickness trauma in lower limbs.
Pulaski and Tennison’s Rules of Nines.
In all cases, escharectomy was performed on fascia within the first 48 h of the accident. Immediately afterward, the wounds were covered with cadaver skin from the tissue bank. Over the next 5–9 days, epidermolysis was observed (i.e., spontaneous removal of the epidermis), as well as vascularization and arrest of the homologous dermis on the receptor bed. In the second stage, the artificial skin was placed on the built-in vascularized homologous dermis. Once the artificial skin had been placed, we waited for 21 days before removing the silicone layer and completing the third and last surgical stage with the placement of a 1/4-thick autograft, obtained with an electric dermatome, over the heterologous vascularized neodermis. Figure 11 illustrates the procedure we followed and the results we obtained.
\n(1) Escharectomy, (2) cadaver skin, (3) vacuum system, (4) epidermolysis, (5) neovascularized homodermis, and (6) artificial skin over vascularized homodermis—final result with autograft.
We used a grid of manual design to evaluate the arrest of the cadaver and artificial skin (expressed in percentages). The arrest of the cadaver skin was of 95% and the placement of the heterologous matrix with an ultrathin autograft was of 94%. The average hospital time was 46 days. No major complications were present, but only minimal difficulties belonging to grades 3b, 4, and 5 of the Dindo and Clavien table [20] (Table 7). After a year of follow-up, we observed that favorable functional results had been obtained in highly complex articular areas such as ankles or knees due to the contribution of homologous and heterologous matrixes that provided adequate scaffolding. With respect to the esthetic results, no depression of the covered surfaces was observed with respect to the adjacent normal dermal tissue. Furthermore, there was no evidence of pathological scarring (such as keloids or hypertrophic scars).
\nGrade | \nDefinition | \n
---|---|
Grade 1 | \nAny deviation from the normal postoperative course without the need for pharmacological treatment or surgical, endoscopic, and radiological interventions Allowed therapeutic regiments are: drugs and antiemetics, antipyretics, analgetics, diuretics, electrolytes, and physiotherapy. This grade also includes wound infections opened at the bedside | \n
Grade 2 | \nRequiring pharmacological treatment with drugs other than such allowed for grade 1 complications. Blood transfusions and total parenteral nutrition are also included | \n
Grade 3 | \nRequiring surgical, endoscopic, or radiological intervention | \n
Grade 3a | \nIntervention not under general anesthesia | \n
Grade 3b | \nIntervention under general anesthesia | \n
Grade 4 | \nLife-threatening complications including brain hemorrhage, ischemic stroke, subarachnoid bleeding, and central nervous system complications (but excluding transient ischemic attacks) requiring intermediate care or intensive care unit management | \n
Grade 4a | \nSingle organ dysfunction (including dialysis) | \n
Grade 4b | \nMultiorgan dysfunction | \n
Grade 5 | \nDeath of a patient | \n
Suffix “d” | \nIf the patient suffers from a complication at the time of discharge, the suffix “d” (for “disability”) is added to the respective grade of complication. This label indicates the need for a follow-up to fully evaluate the complication | \n
Dindo classification of surgical complications.
The goal of any healing process is not only that the scar does not bring about functional disruptions, but also that it is as inconspicuous as possible. Patients of both cosmetic and reconstructive surgery expect scars that do not stand out from the normal surrounding skin, yet there is no consensus among medical practitioners as to which healing methods can achieve both functional and esthetic goals most effectively. In this chapter, we have accounted for two studies carried out at Hospital Alemán in the city of Buenos Aires, the promising results of which may help practitioners arrive at a standard for treating scars resulting from cosmetic and reconstructive surgery.
\nRegarding postcosmetic surgery scars, we have tested the progress of the scars of 32 patients, each having two postsurgical scars that were treated with two different creams. The results of our research show that performing a topical treatment with a cream that contains silver sulfadiazine, vitamin A, and lidocaine from the onset of the treatment decreases the size of the wound more quickly, improves the quality of the scar and the patient’s perception of it. These findings contrast with the less positive outcome of the scars treated with a moisturizing cream without active ingredients [23]. Thus, we conclude that using creams with active ingredients should be promoted as a common practice.
\nIn turn, in our study related to reconstructive surgery, we followed the progress of four patients whose massive skin loss was treated with a combination of artificial and cadaveric dermal substitutes. Using modern biotechnology to reconstruct damaged structures and to provide a new extracellular matrix constitutes the greatest breakthrough in reconstructive surgery of recent times. The development of homografts and artificial skin has allowed professionals to accelerate healing by covering wounds transitorily or permanently. At the same time, they work as a barrier against infections, help maintain the hydroelectrolytic balance [24], and improve esthetic and functional results. As we explained in the previous section, the quality of the scar and the properties of the neodermis depend on the use of an appropriate extracellular matrix [25].
\nAs part of our research, we assessed the progress of the four patients’ scars, focusing on such characteristics as color, thickness, volume, and pain, as well as on the restoration of function at affected sites. We noted positive outcomes in all evaluated parameters, which points at the advantages entailed in implementing this technique. Moreover, the number of hypertrophic scars was lower than the average. Our method fulfilled the ultimate goal of tissue engineering, namely, to restore damaged or lost tissue in traumatic wounds that result in a functional barrier, providing, at the same time, for rapid closure to prevent dehydration and bacterial infection. As attested by our results, the advantages of combining both dermal substitutes include better functional and esthetic outcomes, pain relief, and enhancement of the overall quality of the scar.
\nAll in all, the results of both studies are indicative of the direction that modern scar treatment can take in order to achieve the desired goals in both cosmetic and reconstructive surgery. In the case of the former, achieving an esthetically pleasing scar has long been recognized as a fundamental requirement of a successful intervention. Here, the most optimal results can be achieved if wound treatment and care are initiated early. However, the esthetic factor should not be limited to this type of procedures. Our work on reconstructive surgery centers around the concept that such surgery should not only merely aim at “rebuilding” but also at obtaining the best functional and esthetic outcome with the least possible number of interventions. Recent advances in biotechnology offer us effective skin substitutes, which can be combined so as to achieve a better evolution of the wounds. [26] Such improved esthetic and functional results in posttraumatic reconstructive surgery ensure an ad integrum recovery of the affected areas, which, ultimately, enhances the quality of patients’ lives.
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