Genetic Dissection Of Complex Traits Research Articles

Computational tools for plant genomics and breeding.

Plant genomics and crop breeding are at the intersection of biotechnology and information technology. Driven by a combination of high-throughput sequencing, molecular biology and data science, great advances have been made in omics technologies at every step along the central dogma, especially in genome assembling, genome annotation, epigenomic profiling, and transcriptome profiling. These advances further revolutionized three directions of development. One is genetic dissection of complex traits in crops, along with genomic prediction and selection. The second is comparative genomics and evolution, which open up new opportunities to depict the evolutionary constraints of biological sequences for deleterious variant discovery. The third direction is the development of deep learning approaches for the rational design of biological sequences, especially proteins, for synthetic biology. All three directions of development serve as the foundation for a new era of crop breeding where agronomic traits are enhanced by genome design.

Genetic dissection of complex traits in citrus: additive and non-additive genetic variances, inbreeding depression, and single-chromosome heritability

Genetic evaluation in breeding programs generally considers only additive genetic effects; however, non-additive genetic effects may also contribute to phenotypic and genotypic values. Furthermore, the distributions of causal variants in target traits are associated with the efficiency of accumulation of favorable alleles and are therefore important for plant breeding. Despite this, non-additive effects remain to be fully investigated in citrus. Moreover, although quantitative trait loci in citrus have been previously identified, they cannot adequately explain the genetic variance. Therefore, we attempted to estimate non-additive effects, such as dominance and additive-by-additive effects, together with directional dominance as an indicator of inbreeding depression and with chromosome heritability, which reflects the distributions of causal variants for fruit-quality traits in citrus. Phenotypic records of the fruit weight, sugar content, and acid content of 455 cultivars and their progeny were analyzed. Genomic relationship matrices for non-additive effects and single-chromosome genetic effects were constructed using 2319 genome-wide single nucleotide polymorphism loci, which were also used to evaluate directional dominance. These phenotype and genotype records were analyzed using genomic best linear unbiased prediction models. Through this analysis, we showed (1) overestimation of narrow-sense heritability due to substantial contributions of non-additive effects in the tested traits, (2) evidence of inbreeding depression in fruit weight, and (3) highly polygenic architectures in the tested traits. These findings could contribute to precise evaluation of genotypic values and the development of efficient breeding strategies.

QTL Analysis of Yield and End-Use Quality Traits in Texas Hard Red Winter Wheat

Genetic dissection of complex traits by quantitative trait locus (QTL) analysis permits the understanding of the genotypic effects of QTL, interactions between QTLs, and QTL-by-environment interactions in wheat. This study aimed to identify the QTL linked to yield, its components, end-use quality traits including kernel, flour, and dough rheology, and related agronomic traits under dryland and irrigated conditions. A mapping population of 179 F2:6 recombinant inbred lines (RILs) derived from ‘TAM 111’/‘TX05A001822’ was evaluated for these traits to investigate their genetic stability and phenotypic plasticity using 2658 single nucleotide polymorphisms (SNPs) with 35 linkage groups. Traits associated with chromosome regions were detected for individual and across-environment QTL by inclusive composite interval mapping. A total of 30 QTL regions were identified, including 14 consistent QTLs mapped on 11 chromosomes and six pleiotropic QTLs mapped on 5 chromosomes. Three consistent QTLs in chromosomes 1A, 3B, and 6D might be novel. Three major QTLs with both consistent and pleiotropic effects were co-localized with known genes. The first QTL for dough mixing properties was physically clustered around Glu-D1 and had an phenotypic variation explained (PVE) up to 31.3%. The second QTL for kernel-related traits was physically close to the TaCWI-4A (cell wall invertase) gene, which influences the thousand kernel weight, heading date, and harvest index, with a PVE of up to 12.3%. The third QTL, which was colocalized with the TaCWI-5D gene for kernel traits, was identified with a PVE of 6.7%. Epistasis was also detected, but major QTLs were not involved in significant epistasis or interactions with environmental effects. The current study provided new information that is useful for enhanced wheat breeding, which will benefit from the deployment of the favorable alleles for end-use quality, yield, and other agronomic traits in wheat-breeding programs through marker-assisted selection.

Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.

Quantitative trait nucleotide (QTN)-by-environment interactions (QEIs) play an increasingly essential role in the genetic dissection of complex traits in crops as global climate change accelerates. The abiotic stresses, such as drought and heat, are the major constraints on maize yields. Multi-environment joint analysis can improve statistical power in QTN and QEI detection, and further help us to understand the genetic basis and provide implications for maize improvement. In this study, 3VmrMLM was applied to identify QTNs and QEIs for three yield-related traits (grain yield, anthesis date, and anthesis-silking interval) of 300 tropical and subtropical maize inbred lines with 332,641 SNPs under well-watered and drought and heat stresses. Among the total 321 genes around 76 QTNs and 73 QEIs identified in this study, 34 known genes were reported in previous maize studies to be truly associated with these traits, such as ereb53 (GRMZM2G141638) and thx12 (GRMZM2G016649) associated with drought stress tolerance, and hsftf27 (GRMZM2G025685) and myb60 (GRMZM2G312419) associated with heat stress. In addition, among 127 homologs in Arabidopsis out of 287 unreported genes, 46 and 47 were found to be significantly and differentially expressed under drought vs well-watered treatments, and high vs. normal temperature treatments, respectively. Using functional enrichment analysis, 37 of these differentially expressed genes were involved in various biological processes. Tissue-specific expression and haplotype difference analysis further revealed 24 candidate genes with significantly phenotypic differences across gene haplotypes under different environments, of which the candidate genes GRMZM2G064159, GRMZM2G146192, and GRMZM2G114789 around QEIs may have gene-by-environment interactions for maize yield. All these findings may provide new insights for breeding in maize for yield-related traits adapted to abiotic stresses.

A multi-locus linear mixed model methodology for detecting small-effect QTLs for quantitative traits in MAGIC, NAM, and ROAM populations

Although multi-parent populations (MPPs) integrate the advantages of linkage and association mapping populations in the genetic dissection of complex traits and especially combine genetic analysis with crop breeding, it is difficult to detect small-effect quantitative trait loci (QTL) for complex traits in multiparent advanced generation intercross (MAGIC), nested association mapping (NAM), and random-open-parent association mapping (ROAM) populations. To address this issue, here we proposed a multi-locus linear mixed model method, namely mppQTL, to detect QTLs, especially small-effect QTLs, in these MPPs. The new method includes two steps. The first is genome-wide scanning based on a single-locus linear mixed model; the P-values are obtained from likelihood-ratio test, the peaks of negative logarithm P-value curve are selected by group-lasso, and all the selected peaks are regarded as potential QTLs. In the second step, all the potential QTLs are placed on a multi-locus linear mixed model, all the effects are estimated using expectation-maximization empirical Bayes algorithm, and all the non-zero effect vectors are further evaluated via likelihood-ratio test for significant QTLs. In Monte Carlo simulation studies, the new method has higher power in QTL detection, lower false positive rate, lower mean absolute deviation for QTL position estimate, and lower mean squared error for the estimate of QTL size (r2) than existing methods because the new method increases the power of detecting small-effect QTLs. In real dataset analysis, the new method (19) identified five more known genes than the existing three methods (14). This study provides an effective method for detecting small-effect QTLs in any MPPs.

Association analysis revealed loci linked to post-drought recovery and traits related to persistence of smooth bromegrass (Bromus inermis).

Association analysis has been proven as a powerful tool for the genetic dissection of complex traits. This study was conducted to identify association of recovery, persistence, and summer dormancy with sequence related amplified polymorphism (SRAP) markers in 36 smooth bromegrass genotypes under two moisture conditions and find stable associations. In this study, a diverse panel of polycross-derived progenies of smooth bromegrass was phenotyped under normal and water deficit regimes for three consecutive years. Under water deficit, dry matter yield of cut 1 was approximately reduced by 36, 39, and 37% during 2013, 2014, and 2015, respectively, compared with the normal regime. For dry matter yield of cut 2, these reductions were approximately 38, 60, and 56% in the same three consecutive years relative to normal regime. Moreover, water deficit decreased the RY and PER of the genotypes by 35 and 28%, respectively. Thirty primer combinations were screened by polymerase chain reaction (PCR). From these, 541 polymorphic bands were developed and subjected to association analysis using the mixed linear model (MLM). Population structure analysis identified five main subpopulations possessing significant genetic differences. Association analysis identified 69 and 46 marker-trait associations under normal and water deficit regimes, respectively. Some of these markers were associated with more than one trait; which can be attributed to pleiotropic effects or tightly linked genes affecting several traits. In normal and water-deficit regimes, these markers could potentially be incorporated into marker-assisted selection and targeted trait introgression for the improvement of drought tolerance of smooth bromegrass.

Introgression Lines: Valuable Resources for Functional Genomics Research and Breeding in Rice (Oryza sativa L.).

The narrow base of genetic diversity of modern rice varieties is mainly attributed to the overuse of the common backbone parents that leads to the lack of varied favorable alleles in the process of breeding new varieties. Introgression lines (ILs) developed by a backcross strategy combined with marker-assisted selection (MAS) are powerful prebreeding tools for broadening the genetic base of existing cultivars. They have high power for mapping quantitative trait loci (QTLs) either with major or minor effects, and are used for precisely evaluating the genetic effects of QTLs and detecting the gene-by-gene or gene-by-environment interactions due to their low genetic background noise. ILs developed from multiple donors in a fixed background can be used as an IL platform to identify the best alleles or allele combinations for breeding by design. In the present paper, we reviewed the recent achievements from ILs in rice functional genomics research and breeding, including the genetic dissection of complex traits, identification of elite alleles and background-independent and epistatic QTLs, analysis of genetic interaction, and genetic improvement of single and multiple target traits. We also discussed how to develop ILs for further identification of new elite alleles, and how to utilize IL platforms for rice genetic improvement.

Genetic dissection of flowering time in flax (Linum usitatissimum L.) through single- and multi-locus genome-wide association studies.

In a rapidly changing climate, flowering time (FL) adaptation is important to maximize seed yield in flax (Linum usitatissimum L.). However, our understanding of the genetic mechanism underlying FL in this multipurpose crop remains limited. With the aim of dissecting the genetic architecture of FL in flax, a genome-wide association study (GWAS) was performed on 200 accessions of the flax core collection evaluated in four environments. Two single-locus and six multi-locus models were applied using 70,935 curated single nucleotide polymorphism (SNP) markers. A total of 40 quantitative trait nucleotides (QTNs) associated with 27 quantitative trait loci (QTL) were identified in at least two environments. The number of QTL with positive-effect alleles in accessions was significantly correlated with FL (r = 0.77 to 0.82), indicating principally additive gene actions. Nine QTL were significant in at least three of the four environments accounting for 3.06-14.71% of FL variation. These stable QTL spanned regions that harbored 27 Arabidopsis thaliana and Oryza sativa FL-related orthologous genes including FLOWERING LOCUS T (Lus10013532), FLOWERING LOCUS D (Lus10028817), transcriptional regulator SUPERMAN (Lus10021215), and gibberellin 2-beta-dioxygenase 2 (Lus10037816). In silico gene expression analysis of the 27 FL candidate gene orthologous suggested that they might play roles in the transition from vegetative to reproductive phase, flower development and fertilization. Our results provide new insights into the QTL architecture of flowering time in flax, identify potential candidate genes for further studies, and demonstrate the effectiveness of combining different GWAS models for the genetic dissection of complex traits.

Nested-association mapping (NAM)-based genetic dissection uncovers candidate genes for seed and pod weights in peanut (Arachis hypogaea).

SummaryMultiparental genetic mapping populations such as nested‐association mapping (NAM) have great potential for investigating quantitative traits and associated genomic regions leading to rapid discovery of candidate genes and markers. To demonstrate the utility and power of this approach, two NAM populations, NAM_Tifrunner and NAM_Florida‐07, were used for dissecting genetic control of 100‐pod weight (PW) and 100‐seed weight (SW) in peanut. Two high‐density SNP‐based genetic maps were constructed with 3341 loci and 2668 loci for NAM_Tifrunner and NAM_Florida‐07, respectively. The quantitative trait locus (QTL) analysis identified 12 and 8 major effect QTLs for PW and SW, respectively, in NAM_Tifrunner, and 13 and 11 major effect QTLs for PW and SW, respectively, in NAM_Florida‐07. Most of the QTLs associated with PW and SW were mapped on the chromosomes A05, A06, B05 and B06. A genomewide association study (GWAS) analysis identified 19 and 28 highly significant SNP–trait associations (STAs) in NAM_Tifrunner and 11 and 17 STAs in NAM_Florida‐07 for PW and SW, respectively. These significant STAs were co‐localized, suggesting that PW and SW are co‐regulated by several candidate genes identified on chromosomes A05, A06, B05, and B06. This study demonstrates the utility of NAM population for genetic dissection of complex traits and performing high‐resolution trait mapping in peanut.

Using Plant Phenomics to Exploit the Gains of Genomics

Agricultural scientists face the dual challenge of breeding input-responsive, widely adoptable and climate-resilient varieties of crop plants and developing such varieties at a faster pace. Integrating the gains of genomics with modern-day phenomics will lead to increased breeding efficiency which in turn offers great promise to develop such varieties rapidly. Plant phenotyping techniques have impressively evolved during the last two decades. The low-cost, automated and semi-automated methods for data acquisition, storage and analysis are now available which allow precise quantitative analysis of plant structure and function; and genetic dissection of complex traits. Appropriate plant types can now be quickly developed that respond favorably to low input and resource-limited environments and address the challenges of subsistence agriculture. The present review focuses on the need of systematic, rapid, minimal invasive and low-cost plant phenotyping. It also discusses its evolution to modern day high throughput phenotyping (HTP), traits amenable to HTP, integration of HTP with genomics and the scope of utilizing these tools for crop improvement.

Genome-wide association studies and meta-analysis uncovers new candidate genes for growth and carcass traits in pigs.

Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. As more genomic data is being generated within different commercial or resource pig populations, the challenge which arises is how to collectively investigate the data with the purpose to increase sample size and implicitly the statistical power. This study performs an individual population GWAS, a joint population GWAS and a meta-analysis in three pig F2 populations. D1 is derived from European type breeds (Piétrain, Large White and Landrace), D2 is obtained from an Asian breed (Meishan) and Piétrain, and D3 stems from a European Wild Boar and Piétrain, which is the common founder breed. The traits investigated are average daily gain, backfat thickness, meat to fat ratio and carcass length. The joint and the meta-analysis did not identify additional genomic clusters besides the ones discovered via the individual population GWAS. However, the benefit was an increased mapping resolution which pinpointed to narrower clusters harboring causative variants. The joint analysis identified a higher number of clusters as compared to the meta-analysis; nevertheless, the significance levels and the number of significant variants in the meta-analysis were generally higher. Both types of analysis had similar outputs suggesting that the two strategies can complement each other and that the meta-analysis approach can be a valuable tool whenever access to raw datasets is limited. Overall, a total of 20 genomic clusters that predominantly overlapped at various extents, were identified on chromosomes 2, 7 and 17, many confirming previously identified quantitative trait loci. Several new candidate genes are being proposed and, among them, a strong candidate gene to be taken into account for subsequent analysis is BMP2 (bone morphogenetic protein 2).

Comprehensive Arrayed Transposon Mutant Library of Klebsiella pneumoniae Outbreak Strain KPNIH1.

Klebsiella pneumoniae and other carbapenem-resistant members of the family Enterobacteriaceae are a major cause of hospital-acquired infections, yet the basis of their success as nosocomial pathogens is poorly understood. To help provide a foundation for genetic analysis of K. pneumoniae, we created an arrayed, sequence-defined transposon mutant library of an isolate from the 2011 outbreak of infections at the U.S. National Institutes of Health Clinical Center. The library is made up of 12,000 individually arrayed mutants of a carbapenemase deletion parent strain and provides coverage of 85% of the predicted genes. The library includes an average of 2.5 mutants per gene, with most insertion locations identified and confirmed in two independent rounds of Sanger sequencing. On the basis of an independent transposon sequencing assay, about half of the genes lacking representatives in this "two-allele" library are essential for growth on nutrient agar. To validate the use of the library for phenotyping, we screened candidate mutants for increased antibiotic sensitivity by using custom phenotypic microarray plates. This screening identified several mutations increasing sensitivity to β-lactams (in acrB1, mcrB, ompR, phoP1, and slt1) and found that two-component regulator cpxAR mutations increased multiple sensitivities (to an aminoglycoside, a fluoroquinolone, and several β-lactams). Strains making up the two-allele mutant library are available through a web-based request mechanism.IMPORTANCE K. pneumoniae and other carbapenem-resistant members of the family Enterobacteriaceae are recognized as a top public health threat by the Centers for Disease Control and Prevention. The analysis of these major nosocomial pathogens has been limited by the experimental resources available for studying them. The work presented here describes a sequence-defined mutant library of a K. pneumoniae strain (KPNIH1) that represents an attractive model for studies of this pathogen because it is a recent isolate of the major sequence type that causes infection, the epidemiology of the outbreak it caused is well characterized, and an annotated genome sequence is available. The ready availability of defined mutants deficient in nearly all of the nonessential genes of the model strain should facilitate the genetic dissection of complex traits like pathogenesis and antibiotic resistance.

Simultaneous Improvement and Genetic Dissection of Salt Tolerance of Rice (Oryza sativa L.) by Designed QTL Pyramiding.

Breeding of multi-stress tolerant rice varieties with higher grain yields is the best option to enhance the rice productivity of abiotic stresses prone areas. It also poses the greatest challenge to plant breeders to breed rice varieties for such stress prone conditions. Here, we carried out a designed QTL pyramiding experiment to develop high yielding “Green Super Rice” varieties with significantly improved tolerance to salt stress and grain yield. Using the F4 population derived from a cross between two selected introgression lines, we were able to develop six mostly homozygous promising high yielding lines with significantly improved salt tolerance and grain yield under optimal and/or saline conditions in 3 years. Simultaneous mapping using the same breeding population and tunable genotyping-by-sequencing technology, we identified three QTL affecting salt injury score and leaf chlorophyll content. By analyzing 32M SNP data of the grandparents and graphical genotypes of the parents, we discovered 87 positional candidate genes for salt tolerant QTL. According to their functional annotation, we inferred the most likely candidate genes. We demonstrated that designed QTL pyramiding is a powerful strategy for simultaneous improvement and genetic dissection of complex traits in rice.

Reduced representation genome sequencing reveals patterns of genetic diversity and selection in apple.

Identifying DNA sequence variations is a fundamental step towards deciphering the genetic basis of traits of interest. Here, a total of 20 cultivated and 10 wild apples were genotyped using specific-locus amplified fragment sequencing, and 39,635 single nucleotide polymorphisms with no missing genotypes and evenly distributed along the genome were selected to investigate patterns of genome-wide genetic variations between cultivated and wild apples. Overall, wild apples displayed higher levels of genetic diversity than cultivated apples. Linkage disequilibrium (LD) decays were observed quite rapidly in cultivated and wild apples, with an r2 -value below 0.2 at 440 and 280 bp, respectively. Moreover, bidirectional gene flow and different distribution patterns of LD blocks were detected between domesticated and wild apples. Most LD blocks unique to cultivated apples were located within QTL regions controlling fruit quality, thus suggesting that fruit quality had probably undergone selection during apple domestication. The genome of the earliest cultivated apple in China, Nai, was highly similar to that of Malus sieversii, and contained a small portion of genetic material from other wild apple species. This suggested that introgression could have been an important driving force during initial domestication of apple. These findings will facilitate future breeding and genetic dissection of complex traits in apple.

Environmental and hormonal control of cambial stem cell dynamics.

Perennial trees have the amazing ability to adjust their growth rate to both adverse and favorable seasonally reoccurring environmental conditions over hundreds of years. In trunks and stems, the basis for the tuning of seasonal growth rate is the regulation of cambial stem cell activity. Cambial stem cell quiescence and dormancy protect the tree from potential physiological and genomic damage caused by adverse growing conditions and may permit a long lifespan. Cambial dormancy and longevity are both aspects of a tree's life for which the study of cambial stem cell behavior in the annual model plant Arabidopsis is inadequate. Recent functional analyses of hormone perception and catabolism mutants in Populus indicate that shoot-derived long-range signals, as well as local cues, steer cambial activity. Auxin is central to the regulation of cambial activity and probably also maintenance. Emerging genome editing and phenotyping technologies will enable the identification of down-stream targets of hormonal action and facilitate the genetic dissection of complex traits of cambial biology.

Towards developing a genetic linkage map of isabgol ( Plantago ovata Forsk.), a medicinal plant with potent laxative properties

Genetic linkage maps facilitate the genetic dissection of complex traits and comparative analyses of genome structure, as well as molecular breeding in species of economic importance. Isabgol [ Plantago ovata (Forsk.)], a medicinal plant with potent laxative properties is used in several tradi-tional systems of Medicines and cultivated in India. We explored the DNA sequences of Isabgol in the Genbank (NCBI) and developed over 1500 simple sequence repeats (SSR) markers. Some of them were validated through DNA amplification. Transferability of SSRs from wild Plantago species viz., P. major, P. coronopus, P. lancelolata, P. maritina and P. intermida into Plantago ovata was stud-ied. We developed a genetic linkage map using recombinant inbred lines (RILs) population which comprises of 30 random amplified polymorphic DNA (RAPD) markers spreading across 11 linkage groups (PO-1 to PO-11) with a total map distance of 75.6 cM. The SSR markers developed will have applications in assessing the functional diversity, comparative mapping and other applications in isabgol.

The walnut (Juglans regia) genome sequence reveals diversity in genes coding for the biosynthesis of non‐structural polyphenols

The Persian walnut (Juglans regia L.), a diploid species native to the mountainous regions of Central Asia, is the major walnut species cultivated for nut production and is one of the most widespread tree nut species in the world. The high nutritional value of J.regia nuts is associated with a rich array of polyphenolic compounds, whose complete biosynthetic pathways are still unknown. A J.regia genome sequence was obtained from the cultivar 'Chandler' to discover target genes and additional unknown genes. The 667-Mbp genome was assembled using two different methods (SOAPdenovo2 and MaSuRCA), with an N50 scaffold size of 464955bp (based on a genome size of 606 Mbp), 221640 contigs and a GC content of 37%. Annotation with MAKER-P and other genomic resources yielded 32498 gene models. Previous studies in walnut relying on tissue-specific methods have only identified a single polyphenol oxidase (PPO) gene (JrPPO1). Enabled by the J.regia genome sequence, a second homolog of PPO (JrPPO2) was discovered. In addition, about 130 genes in the large gallate 1-β-glucosyltransferase (GGT) superfamily were detected. Specifically, two genes, JrGGT1 and JrGGT2, were significantly homologous to the GGT from Quercus robur (QrGGT), which is involved in the synthesis of 1-O-galloyl-β-d-glucose, a precursor for the synthesis of hydrolysable tannins. The reference genome for J.regia provides meaningful insight into the complex pathways required for the synthesis of polyphenols. The walnut genome sequence provides important tools and methods to accelerate breeding and to facilitate the genetic dissection of complex traits.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology.

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Rice research in the high-throughput sequencing era: Genomic breeding Rice breeding for better health

Rice [ Oryza sativa L.] is the most important cereal crop belongs to the family Poaceae (Grass) which provide staple food for half of the World's population (>3.3 billion). This staple food grain (rice) supplies the main energy resource providing 40-75% of the daily calorie intake to the world's poor people. It is equ ivalent to the proposition that 'Rice is life' in Asian continent because 90% people dependent on for their sustainable livelihood. Simultaneously Asia is considered as 'Rice Basket' because it produces 90% of the world's production (662 million tons, paddy rice, Mt). Total world production was 729 Mt from '154.3 million hectares with productivity of 4.1 tons/hectare (t/ha) in 2012 of which 662 million tons produced by Asian countries. Rice production has been doubled in the recent decades (1960s-1990s) during the tim~ of Green Revolution (1960s) primarily as the result of genetic improvement. It was factual that the varieties released in the· last 30 years in the farmers field, had a narrow genetic base in-spite of high genetic diversity prevailed in the rice germplasm, and yield enhancing capacity has reached to plateau. We need more production of rice to feed 9 Billion people in 2050. Breeder could manage the yield increase over released varieties through genetic gain by combining the yield related genes/QTLs from various genetic resources of rice germplasms either from cultivated local landraces or from wild varieties. Germplasm diversity is the mainstay for crop improvement and genetic dissection of complex traits. Rice germplasm shows tremendous genetic diversity in both within the species and among the varietal groups. This genetic diversity may be associated with the diverse allel~ of important traits and can be exploited to introgress these traits using knowledge of molecular breeding techniques such as marker assisted breeding (MAB) or marker assisted selection (MAS). The Next Generation Sequencing based technology is used for whole genome analysis to unveil the genetic and genomic infor'mation pertaining to important traits for advancing the molecular breeding procedures to increase the production. That ultimately leads to the development of genomic breeding and genomic selection to accelerate the breeding process.

Construction of high‐throughput genotyped chromosome segment substitution lines in rice (Oryza sativa L.) and QTL mapping for heading date

AbstractChromosome segment substitution lines (CSSLs) provide ideal materials for quantitative trait loci (QTLs) mapping and genetic dissection of complex traits. In this study, we developed a set of CSSL population consisting of 175 lines, which were derived between the recipient ‘Guangluai 4’ and the donor ‘Nipponbare’. Based on 260 molecular markers, we firstly constructed a physical map of core 97 lines. Then, these 97 lines were further genotyped based on resequencing data, and a resequencing‐based physical map was constructed. Compared with the molecular marker‐based physical map, the resequencing‐based physical map of 97 lines contained 367 substituted segments with 252 newly discovered segments. The total size of the 367 substituted segments was 1,074 Mb, which was 2.81 times the size of rice genome. Using the 97 CSSLs as materials, we identified nine QTLs for heading date and three of them were firstly reported. All the QTLs had positive additive effects, ranging from 9.50 to 16.50 days. These CSSLs may greatly help forge a new resource for functional genomics studies and molecular breeding in rice.