Marker-assisted Selection Strategies Research Articles

Identification of candidate single-nucleotide polymorphisms (SNPs) and genes associated with sugarcane leaf scald disease

Leaf scald, caused by Xanthomonas albilineans, is a severe disease affecting sugarcane worldwide. One of the most practical ways to control it is by developing resistant sugarcane cultivars. It is essential to identify genes associated with the response to leaf scald. A panel of 170 sugarcane genotypes was evaluated for resistance to leaf scald in field conditions for 2 years, followed by a 1-year greenhouse experiment. The phenotypic evaluation data showed a wide continuous distribution, with heritability values ranging from 0.58 to 0.84. Thirteen single nucleotide polymorphisms (SNPs) were identified, significantly associated with leaf scald resistance. Among these, eight were stable across multiple environments and association models. The candidate genes identified and validated based on RNA-seq and qRT-PCR included two genes that encode NB-ARC leucine-rich repeat (LRR)-containing domain disease-resistance protein. These findings provide a basis for developing marker-assisted selection strategies in sugarcane breeding programs.

Genome-Wide Association Study and Genomic Prediction of Fusarium Wilt Resistance in Common Bean Core Collection.

The common bean (Phaseolus vulgaris L.) is a globally cultivated leguminous crop. Fusarium wilt (FW), caused by Fusarium oxysporum f. sp. phaseoli (Fop), is a significant disease leading to substantial yield loss in common beans. Disease-resistant cultivars are recommended to counteract this. The objective of this investigation was to identify single nucleotide polymorphism (SNP) markers associated with FW resistance and to pinpoint potential resistant common bean accessions within a core collection, utilizing a panel of 157 accessions through the Genome-wide association study (GWAS) approach with TASSEL 5 and GAPIT 3. Phenotypes for Fop race 1 and race 4 were matched with genotypic data from 4740 SNPs of BARCBean6K_3 Infinium Bea Chips. After ranking the 157-accession panel and revealing 21 Fusarium wilt-resistant accessions, the GWAS pinpointed 16 SNPs on chromosomes Pv04, Pv05, Pv07, Pv8, and Pv09 linked to Fop race 1 resistance, 23 SNPs on chromosomes Pv03, Pv04, Pv05, Pv07, Pv09, Pv10, and Pv11 associated with Fop race 4 resistance, and 7 SNPs on chromosomes Pv04 and Pv09 correlated with both Fop race 1 and race 4 resistances. Furthermore, within a 30 kb flanking region of these associated SNPs, a total of 17 candidate genes were identified. Some of these genes were annotated as classical disease resistance protein/enzymes, including NB-ARC domain proteins, Leucine-rich repeat protein kinase family proteins, zinc finger family proteins, P-loopcontaining nucleoside triphosphate hydrolase superfamily, etc. Genomic prediction (GP) accuracy for Fop race resistances ranged from 0.26 to 0.55. This study advanced common bean genetic enhancement through marker-assisted selection (MAS) and genomic selection (GS) strategies, paving the way for improved Fop resistance.

Genome-wide association mapping in a sweet cherry germplasm collection (Prunus avium L.) reveals candidate genes for fruit quality traits.

In sweet cherry (Prunus avium L.), large variability exists for various traits related to fruit quality. There is a need to discover the genetic architecture of these traits in order to enhance the efficiency of breeding strategies for consumer and producer demands. With this objective, a germplasm collection consisting of 116 sweet cherry accessions was evaluated for 23 agronomic fruit quality traits over 2-6 years, and characterized using a genotyping-by-sequencing approach. The SNP coverage collected was used to conduct a genome-wide association study using two multilocus models and three reference genomes. We identified numerous SNP-trait associations for global fruit size (weight, width, and thickness), fruit cracking, fruit firmness, and stone size, and we pinpointed several candidate genes involved in phytohormone, calcium, and cell wall metabolisms. Finally, we conducted a precise literature review focusing on the genetic architecture of fruit quality traits in sweet cherry to compare our results with potential colocalizations of marker-trait associations. This study brings new knowledge of the genetic control of important agronomic traits related to fruit quality, and to the development of marker-assisted selection strategies targeted towards the facilitation of breeding efforts.

A genome-wide association study to identify the genes associated with growth-related traits in Tegillarca granosa

The blood clam Tegillarca granosa is a commercially important bivalve species that is extensively cultivated worldwide. However, understanding of the molecular mechanisms underlying the growth of this species remains limited. In this study, we conducted genome-wide association studies on the growth traits of T. granosa, including shell and body weight characteristics, using a population of 300 T. granosa individuals. Correlation analysis revealed strong positive associations among the growth traits, with the exception of dressing percentage, suggesting that selective breeding for any of these traits can contribute to overall growth enhancement in T. granosa. A total of 39 single nucleotide polymorphism (SNP) markers associated with the seven growth traits were identified. Further investigation led to the identification of 27 candidate genes located within a 100 kb region upstream or downstream of these SNPs, which are potentially involved in T. granosa growth. Enrichment analysis of the candidate genes highlighted the biological process of transmembrane transport and the pathways related to immune system function, protein family metabolism, and JAK-STAT signaling as potential contributors to T. granosa growth. Furthermore, we discovered a haploblock associated with shell width, and validated the differential expression of four genes (Vha26, Ptprt, Stat5b, and Kmt2c) between fast and slow growing groups, which may play important roles in the growth of T. granosa. Overall, our study presents valuable genetic resources and serves as a reference for future marker-assisted selection strategies for enhancing the growth performance of T. granosa.

Integrating genetic markers and adiabatic quantum machine learning to improve disease resistance-based marker assisted plant selection

The goal of this research was to create a more accurate and efficient method for selecting plants with disease resistance using a combination of genetic markers and advanced machine learning algorithms. A multi-disciplinary approach incorporating genomic data, machine learning algorithms and high-performance computing was employed. First, genetic markers highly associated with disease resistance were identified using next-generation sequencing data and statistical analysis. Then, an adiabatic quantum machine learning algorithm was developed to integrate these markers into a single predictor of disease susceptibility. The results demonstrate that the integrative use of genetic markers and adiabatic quantum machine learning significantly improved the accuracy and efficiency of disease resistance-based marker-assisted plant selection. By leveraging the power of adiabatic quantum computing and genetic markers, more effective and efficient strategies for disease resistance-based marker-assisted plant selection can be developed.

Single-step genome-wide association study for susceptibility to Teratosphaeria nubilosa and precocity of vegetative phase change in Eucalyptus globulus.

Mycosphaerella leaf disease (MLD) is one of the most prevalent foliar diseases of Eucalyptus globulus plantations around the world. Since resistance management strategies have not been effective in commercial plantations, breeding to develop more resistant genotypes is the most promising strategy. Available genomic information can be used to detect genomic regions associated with resistance to MLD, which could significantly speed up the process of genetic improvement. We investigated the genetic basis of MLD resistance in a breeding population of E. globulus which was genotyped with the EUChip60K SNP array. Resistance to MLD was evaluated through resistance of the juvenile foliage, as defoliation and leaf spot severity, and through precocity of change to resistant adult foliage. Genome-wide association studies (GWAS) were carried out applying four Single-SNP models, a Genomic Best Linear Unbiased Prediction (GBLUP-GWAS) approach, and a Single-step genome-wide association study (ssGWAS). The Single-SNP (model K) and GBLUP-GWAS models detected 13 and 16 SNP-trait associations in chromosomes 2, 3 y 11; whereas the ssGWAS detected 66 SNP-trait associations in the same chromosomes, and additional significant SNP-trait associations in chromosomes 5 to 9 for the precocity of phase change (proportion of adult foliage). For this trait, the two main regions in chromosomes 3 and 11 were identified for the three approaches. The SNPs identified in these regions were positioned near the key miRNA genes, miR156.5 and miR157.4, which have a main role in the regulation of the timing of vegetative change, and also in the response to environmental stresses in plants. Our results demonstrated that ssGWAS was more powerful in detecting regions that affect resistance than conventional GWAS approaches. Additionally, the results suggest a polygenic genetic architecture for the heteroblastic transition in E. globulus and identified useful SNP markers for the development of marker-assisted selection strategies for resistance to MLD.

Bovine HOXA11 Gene Identified from RNA-Seq: mRNA Profile Analysis and Genetic Variation Detection Using ME Method and Their Associations with Carcass Traits.

The Homeobox A11 (HOXA11) gene regulates limb skeletal development and muscle growth, thus, it was selected as a candidate gene for bovine carcass traits. In this study, we analyzed the mRNA expression level of HOXA11 in various tissues and cells, and determined the genetic variations in the HOXA11 gene, which might be used as molecular markers for cattle breeding. The mRNA expression profiles of HOXA11 in bovine different tissues showed that HOXA11 was highly expressed in both fat and muscle. The gene expression trend of HOXA11 in myoblasts and adipocytes indicated that HOXA11 might be involved in the differentiation of bovine myoblasts and adipocytes. The data in the Ensembl database showed that there are two putative insertion/deletion (InDel) polymorphisms in the bovine HOXA11 gene. The insertion site (rs515880802) was located in the upstream region (NC_037331.1: g. 68853364-68853365) and named as P1-Ins-4-bp, and the deletion site (rs517582703) was located in the intronic region (NC_037331.1: g. 68859510-68859517) and named as P2-Del-8-bp. These polymorphisms within the HOXA11 gene were identified and genotyped by PCR amplification, agarose gel electrophoresis and DNA sequencing in the 640 Shandong Black Cattle Genetic Resource (SDBCGR) population. Moreover, the mutation frequency was very low after detection, so the mathematical expectation (ME) method was used for detection. Statistical analysis demonstrated that P1-Ins-4-bp was significantly correlated with the beef shoulder (p = 0.012) and tongue root (p = 0.004). Meanwhile, P2-Del-8-bp displayed a significant correlation with the back tendon (p = 0.008), money tendon (p = 2.84 × 10-4), thick flank (p = 0.034), beef shin (p = 9.09 × 10-7), triangle thick flank (p = 0.04), triangle flank (p = 1.00 × 10-6), rump (p = 0.018) and small tenderloin (p = 0.043) in the female SDBCGR population. In summary, these outcomes may provide a new perspective for accelerating the molecular breeding of cattle through marker-assisted selection (MAS) strategies.

Introgression of Drought Tolerance into Elite Basmati Rice Variety through Marker-Assisted Backcrossing

Drought is one of the major abiotic threat to rice production in the context of climate change. Super Basmati is an elite, fine grain basmati rice variety grown in Punjab, Pakistan. Due to drought sensitive in nature, its yield has been facing an alarming situation in production because of gradual decrease in irrigated water for a couple of years. Three reported novel QTLs for drought tolerance were selected for incorporation into Super Basmati by employing marker assisted selection strategy. IR55419-04 with novel QTLs was used as a donor parent. Foreground selection was performed by applying PCR based QTL linked SSR markers followed by recombinant selection by using 2–4 flanking markers. Background selection was exercised by using polymorphic SSR markers for maximum genome recovery of the Super Basmati. The individuals homozygous at the target QTLs and with maximum background of Super Basmati at the rest of the non-target genome was selected for evaluation of drought tolerance. Under drought stress conditions, the yields of all introgressed lines (ILs) were 44.2%–125.7% higher than recurrent parent. Six superior ILs that are drought tolerant and very similar to Super Basmati in terms of agronomic and grain quality traits are marked for release as drought-tolerant varieties in arid regions or for use in breeding programs of high grain quality and drought-tolerant parents.

Characterization of a new splicing variant of powdery mildew resistance gene Pm4 in synthetic hexaploid wheat YAV249

Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a destructive fungal disease of wheat throughout the world. Utilization of effective powdery mildew resistance genes and cultivars is considered as the most economic, efficient, and environmental-friendly method to control this disease. Synthetic hexaploid wheat (SHW), which was developed through hybridization of diploid Aegilops and tetraploid wheat, is a valuable genetic resource for resistance to powdery mildew. SHW line YAV249 showed high levels of resistance to powdery mildew at both the seedling and adult stages. Genetic analysis indicated that the resistance was controlled by a single dominant gene, temporarily designated PmYAV. Bulked segregant analysis with wheat 660K single nucleotide polymorphism (SNP) array scanning and marker analysis showed that PmYAV was located on chromosome 2AL and flanked by markers Xgdm93 and Xwgrc763, respectively, with genetic distances of 0.8 cM and 1.2 cM corresponding to a physic interval of 1.89 Mb on the Chinese Spring reference genome sequence v1.0. Sequence alignment analysis demonstrated that the sequence of PmYAV was consistent with that of Pm4a but generated an extra splicing event. When inoculated with different Bgt isolates, PmYAV showed a significantly different spectrum from Pm4a, hence it might be a new resistant resource for improvement of powdery mildew resistance. The flanked markers GDM93 and WGRC763, and the co-segregated markers BCD1231 and JS717/JS718 were confirmed to be easily performed in marker-assisted selection (MAS) of PmYAV. Using MAS strategy, PmYAV was transferred into the commercial cultivar Kenong 199 (KN199) and a wheat line YK13 was derived at generation BC3F3 from the population of YAV249/4*KN199 due to its excellent agronomic traits and resistance to powdery mildew. In conclusion, an alternative splicing variant of Pm4 was identified in this study, which informed the regulation of Pm4 gene function.

SNP discovery and association study for growth, fatness and meat quality traits in Iberian crossbred pigs

Iberian pigs and its crosses are produced to obtain high-quality meat products. The objective of this work was to evaluate a wide panel of DNA markers, selected by biological and functional criteria, for association with traits related to muscle growth, fatness, meat quality and metabolism. We used 18 crossbred Iberian pigs with divergent postnatal growth patterns for whole genome sequencing and SNP discovery, with over 13 million variants being detected. We selected 1023 missense SNPs located on annotated genes and showing different allele frequencies between pigs with makerdly different growth patterns. We complemented this panel with 192 candidate SNPs obtained from literature mining and from muscle RNAseq data. The selected markers were genotyped in 480 Iberian × Duroc pigs from a commercial population, in which phenotypes were obtained, and an association study was performed for the 1005 successfully genotyped SNPs showing segregation. The results confirmed the effects of several known SNPs in candidate genes (such as LEPR, ACACA, FTO, LIPE or SCD on fatness, growth and fatty acid composition) and also disclosed interesting effects of new SNPs in less known genes such as LRIG3, DENND1B, SOWAHB, EPHX1 or NFE2L2 affecting body weight, average daily gain and adiposity at different ages, or KRT10, NLE1, KCNH2 or AHNAK affecting fatness and FA composition. The results provide a valuable basis for future implementation of marker-assisted selection strategies in swine and contribute to a better understanding of the genetic architecture of relevant traits.

A joint learning approach for genomic prediction in polyploid grasses

Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in different cross-validation scenarios. By combining classification and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains.

Linking Multi-Omics to Wheat Resistance Types to Fusarium Head Blight to Reveal the Underlying Mechanisms.

Fusarium head blight (FHB) caused by Fusarium graminearum is a worldwide disease which has destructive effects on wheat production, resulting in severe yield reduction and quality deterioration, while FHB-infected wheat grains are toxic to people and animals due to accumulation of fungal toxins. Although impressive progress towards understanding host resistance has been achieved, our knowledge of the mechanism underlying host resistance is still quite limited due to the complexity of wheat–pathogen interactions. In recent years, disease epidemics, the resistance germplasms and components, the genetic mechanism of FHB, and disease management and control, etc., have been well reviewed. However, the resistance mechanism of FHB is quite complex with Type I, II to V resistances. In this review, we focus on the potential resistance mechanisms by linking different resistance types to multi-omics and emphasize the pathways or genes that may play significant roles in the different types of resistance. Deciphering the complicated mechanism of FHB resistance types in wheat at the integral levels based on multi-omics may help discover the genes or pathways that are critical for different FHB resistance, which could then be utilized and manipulated to improve FHB resistance in wheat breeding programs by using transgenic approaches, gene editing, or marker assisted selection strategies.

Genotypic characterization of meat-type lambs expressing the callipyge gene in Turkey: II. Effect on body indexes

This study is set out to examine the relationship between the callipyge (CLPG) gene, attributed to sheep affecting growth and meat quality, and body indexes of meat-type sheep breeds to assess its feasibility in using it genomic selection programs. For this purpose, blood samples were collected from 177 lambs (66 male, 111 female) of five different sheep breeds (Kivircik, Karacabey Merino, Ramlic, German Black-Head Mutton × Kivircik, Hampshire Down × Merino) to identify M (mutant) and N (normal) alleles and genotypes. Live weight (LW) and morphometric measurements were taken on the 90th, 180th, and 360th day of the study. The principal component analysis results show that four morphometric measurements (body length, BL; chest circumference, CC; chest width, CW; withers height, WH) and two body indexes (index of body weight, IBF; Baron-Crevat index, BCI) with LW could be used to the morphometric characterization. It was found that the cannon bone perimeter (CBP) was the differentiation point of CLPG genotypes. While a lower to moderate correlation was observed between CBP to CC, LW, CW, chest depth (CD), and rump width (RW) in the NN genotype, no significant correlation was observed in the MN genotype. This investigation also revealed that BCI and IBF were the two body indexes that should be adopted into breeding schemes as a performance and etiological comparison of animals, especially in marker-assisted selection schemes due to well-reflecting animal current status.

Novel InDel variations of the Cry2 gene are associated with litter size in Australian White sheep

Cryptochrome 2 (Cry2) gene regulates circadian rhythm and affects reproduction and pregnancy. Therefore, this study aimed to explore polymorphisms of the Cry2 gene and their associations with litter size at different parity in Australian White (AuW) ewes. Five putative insertion or deletion mutations within the Cry2 gene were selected to study their association with litter size. Two novel deletion mutations were identified in intronic region of Cry2 gene and were genotyped by agarose gel electrophoresis and DNA sequencing. The polymorphism information content (PIC) indicated that both mutations were low polymorphism in tested groups. Statistical analysis revealed that the P1-Del-6-bp was significantly correlated with litter size at third parity (P = 0.010), in which individuals with insertion/deletion (ID) genotype had larger litter size than insertion/insertion (II) genotype (P < 0.05). Whereas, the P2-Del-6-bp was significantly correlated with litter size at first parity (P = 0.036), in which individuals with insertion/insertion (II) genotype had larger litter size than insertion/deletion (ID) genotype (P < 0.05). Collectively, these findings may provide new insights to expedite molecular breeding in sheep through marker-assisted selection strategies (MAS).

Fine Mapping of a New Major QTL-qGLS8 for Gray Leaf Spot Resistance in Maize.

Gray leaf spot (GLS), caused by different species of Cercospora, is a fungal, non-soil-borne disease that causes serious reductions in maize yield worldwide. The identification of major quantitative trait loci (QTLs) for GLS resistance in maize is essential for developing marker-assisted selection strategies in maize breeding. Previous research found a significant difference (P < 0.01) in GLS resistance between T32 (highly resistant) and J51 (highly susceptible) genotypes of maize. Initial QTL analysis was conducted in an F2 : 3 population of 189 individuals utilizing genetic maps that were constructed using 181 simple sequence repeat (SSR) markers. One QTL (qGLS8) was detected, defined by the markers umc1130 and umc2354 in three environments. The qGLS8 QTL detected in the initial analysis was located in a 51.96-Mb genomic region of chromosome 8 and explained 7.89–14.71% of the phenotypic variation in GLS resistance in different environments. We also developed a near isogenic line (NIL) BC3F2 population with 1,468 individuals and a BC3F2-Micro population with 180 individuals for fine mapping. High-resolution genetic and physical maps were constructed using six newly developed SSRs. The QTL-qGLS8 was narrowed down to a 124-kb region flanked by the markers ym20 and ym51 and explained up to 17.46% of the phenotypic variation in GLS resistance. The QTL-qGLS8 contained seven candidate genes, such as an MYB-related transcription factor 24 and a C3H transcription factor 347), and long intergenic non-coding RNAs (lincRNAs). The present study aimed to provide a foundation for the identification of candidate genes for GLS resistance in maize.

Multi-year analyses on three populations reveal the first stable QTLs for tolerance to rain-induced fruit cracking in sweet cherry (Prunus avium L.)

Rain-induced fruit cracking is a major problem in sweet cherry cultivation. Basic research has been conducted to disentangle the physiological and mechanistic bases of this complex phenomenon, whereas genetic studies have lagged behind. The objective of this work was to disentangle the genetic determinism of rain-induced fruit cracking. We hypothesized that a large genetic variation would be revealed, by visual field observations conducted on mapping populations derived from well-contrasted cultivars for cracking tolerance. Three populations were evaluated over 7–8 years by estimating the proportion of cracked fruits for each genotype at maturity, at three different areas of the sweet cherry fruit: pistillar end, stem end, and fruit side. An original approach was adopted to integrate, within simple linear models, covariates potentially related to cracking, such as rainfall accumulation before harvest, fruit weight, and firmness. We found the first stable quantitative trait loci (QTLs) for cherry fruit cracking, explaining percentages of phenotypic variance above 20%, for each of these three types of cracking tolerance, in different linkage groups, confirming the high complexity of this trait. For these and other QTLs, further analyses suggested the existence of at least two-linked QTLs in each linkage group, some of which showed confidence intervals close to 5 cM. These promising results open the possibility of developing marker-assisted selection strategies to select cracking-tolerant sweet cherry cultivars. Further studies are needed to confirm the stability of the reported QTLs over different genetic backgrounds and environments and to narrow down the QTL confidence intervals, allowing the exploration of underlying candidate genes.

Biotechnological Approaches for Genetic Improvement of Lemon (Citrus limon (L.) Burm. f.) against Mal Secco Disease.

Among Citrus species, lemon is one of the most susceptible to mal secco disease, a tracheomycosis caused by the mitosporic fungus Plenodomus tracheiphilus, which induces chlorosis followed by leaf drop and progressive desiccation of twigs and branches. Severe infection can cause the death of the plant. Since no effective control strategies are available to efficiently control the pathogen spread, host tolerance is the most desirable goal in the struggle against mal secco disease. To date, both traditional breeding programs and biotechnological techniques were not efficient in developing novel varieties coupling tolerance to mal secco with optimal fruit quality. Furthermore, the genetic basis of host resistance has not been fully deciphered yet, hampering the set-up of marker-assisted selection (MAS) schemes. This paper provides an overview of the biotechnological approaches adopted so far for the selection of mal secco tolerant lemon varieties and emphasizes the promising contribution of marker-trait association analysis techniques for both unraveling the genetic determinism of the resistance to mal secco and detecting molecular markers that can be readily used for MAS. Such an approach has already proved its efficiency in several crops and could represent a valuable tool to select novel lemon varieties coupling superior fruit quality traits and resistance to mal secco.

Fine mapping of the major QTLs for biochemical variation of sulforaphane in broccoli florets using a DH population

Glucoraphanin is a major secondary metabolite found in Brassicaceae vegetables, especially broccoli, and its degradation product sulforaphane plays an essential role in anticancer. The fine mapping of sulforaphane metabolism quantitative trait loci (QTLs) in broccoli florets is necessary for future marker-assisted selection strategies. In this study, we utilized a doubled haploid population consisting of 176 lines derived from two inbred lines (86,101 and 90,196) with significant differences in sulforaphane content, coupled with extensive genotypic and phenotypic data from two independent environments. A linkage map consisting of 438 simple sequence repeats markers was constructed, covering a length of 1168.26 cM. A total of 18 QTLs for sulforaphane metabolism in broccoli florets were detected, 10 were detected in 2017, and the other 8 were detected in 2018. The LOD values of all QTLs ranged from 3.06 to 14.47, explaining 1.74–7.03% of the biochemical variation between two years. Finally, 6 QTLs (qSF-C3-1, qSF-C3-2, qSF-C3-3, qSF-C3-5, qSF-C3-6 and qSF-C7) were stably detected in more than one environment, each accounting for 4.54–7.03% of the phenotypic variation explained (PVE) and a total of 30.88–34.86% of PVE. Our study provides new insights into sulforaphane metabolism in broccoli florets and marker-assisted selection breeding in Brassica oleracea crops.

Application of Markers Assisted Selection for Striga Hermonthica Resistance on Sorghum (Sorghum bicolor (L.) Moench

Sorghum (Sorghum bicolor L. [Moench]) is a staple food crop for smallholder farmers in arid and semi-arid(ASALs) regions worldwide, feeding over 500 million of the world's most resource-poor. Development of Striga Hermonthica resistant cultivars by conventional breeding is slow and have been hampered by the lack of efficient and reliable screening techniques in breeding programs. Molecular markers that are linked to witchweed resistance can expedite the development of resistant cultivars through the adoption of appropriate marker-assisted selection (MAS) strategies. Marker-assisted selection involves the selection of genotypes carrying a desirable gene(s) via linked markers; through MAS more rapid transfer of traits from donor parents to more elite locally adapted crop cultivars is possible with simple-sequence repeat (SSR) markers which have been initially used to detect polymorphism between the parent cultivars. Although costly to develop relative to some other classes of genetic markers, once developed, analysis by SSR markers is both easy and inexpensive. The highly polymorphic nature (high information content) and other favorable characteristics make them excellent genetic markers for a number of studies including marker-assisted selection and fingerprinting of germplasm collections. In this review, we summarize the molecular markers that are linked to the inheritance trait or low germination stimulant production is one of the recognized mechanisms of witch weed resistance.

Challenges and Progresses of Molecular Plant Breeding in Crop Improvement

Molecular marker is applicable to many aspects of plant improvement and crop production. The main objective of plant breeding to produce crops with improved characteristics with the utilization of the available genetic variability and producing sufficient genetic variability of crops by different breeding techniques. There are possibilities to improve the desired traits through conventional breeding methods in the presence of genetic diversities. However, there are several challenges to make the significant improvement on the crop through conventional breeding. Conventional breeding is almost always based on phenotypic variation of the crops, which is affected by environments (non-heritable components) and crop improvement cycle takes long time. However, molecular marker is designed to meet this challenges regardless of its cost and it’s not affected by environment where ever the experiment is conducted either in laboratory or field condition. Molecular marker procedures are playing a significant role to increase the effectiveness in breeding and shorten the development crop improvement stages. Molecular markers also used develop resistant crop to pests and diseases, develop tolerant crop to environmental conditions and improve the crop in required quality. In facing the challenge of improving several lines for quantitative traits, marker assisted selection strategies use DNA markers in one key selection step to maximize their impact. With the development of molecular marker technology, the fate of plant breeding has changed. Different types of molecular markers have been developed in identification and characterization germplasm, DNA sequences in identification of the genomic regions involved in the expression of the target traits, to analysis the genetic variation, cytogenetic, quantitative genetics, biotechnology and genomics and it’s applied in genetic diversity analysis in crop improvement. It is possible to increase agricultural productivity through addressing the problems of yield reduction and its links with pest management and climate change using advanced breeding technologies. There are several major challenges in the application of molecular markers to agronomically important traits. Some of them are: economic factors, lack of grants to researchers, lack of adequately trained personnel. Generally, the integrating molecular marker technologies with the conventional breeding strategies are increasingly important to realize genetic gains with greater speed and precision. Keywords: Molecular marker; Marker assisted breeding; quantitative traits; Plant breeding DOI: 10.7176/JNSR/11-21-04 Publication date: November 30 th 2020