Evolution of the Grain Dispersal System in Barley.

About 12,000 years ago in the Near East, humans began the transition from hunter-gathering to agriculture-based societies. Barley was a founder crop in this process, and the most important steps in its domestication were mutations in two adjacent, dominant, and complementary genes, through which grains were retained on the inflorescence at maturity, enabling effective harvesting. Independent recessive mutations in each of these genes caused cell wall thickening in a highly specific grain "disarticulation zone," converting the brittle floral axis (the rachis) of the wild-type into a tough, non-brittle form that promoted grain retention. By tracing the evolutionary history of allelic variation in both genes, we conclude that spatially and temporally independent selections of germplasm with a non-brittle rachis were made during the domestication of barley by farmers in the southern and northern regions of the Levant, actions that made a major contribution to the emergence of early agrarian societies.

Insights into maydis leaf blight resistance in maize: a comprehensive genome-wide association study in sub-tropics of India.

BACKGROUND: In the face of contemporary climatic vulnerabilities and escalating global temperatures, the prevalence of maydis leaf blight (MLB) poses a potential threat to maize production. This study endeavours to discern marker-trait associations and elucidate the candidate genes that underlie resistance to MLB in maize by employing a diverse panel comprising 336 lines. The panel was screening for MLB across four environments, employing standard artificial inoculation techniques. Genome-wide association studies (GWAS) and haplotype analysis were conducted utilizing a total of 128,490 SNPs obtained from genotyping-by-sequencing (GBS). RESULTS: GWAS identified 26 highly significant SNPs associated with MLB resistance, among the markers examined. Seven of these SNPs, reported in novel chromosomal bins (9.06, 5.01, 9.01, 7.04, 4.06, 1.04, and 6.05) were associated with genes: bzip23, NAGS1, CDPK7, aspartic proteinase NEP-2, VQ4, and Wun1, which were characterized for their roles in diminishing fungal activity, fortifying defence mechanisms against necrotrophic pathogens, modulating phyto-hormone signalling, and orchestrating oxidative burst responses. Gene mining approach identified 22 potential candidate genes associated with SNPs due to their functional relevance to resistance against necrotrophic pathogens. Notably, bin 8.06, which hosts five SNPs, showed a connection to defense-regulating genes against MLB, indicating the potential formation of a functional gene cluster that triggers a cascade of reactions against MLB. In silico studies revealed gene expression levels exceeding ten fragments per kilobase million (FPKM) for most genes and demonstrated coexpression among all candidate genes in the coexpression network. Haplotype regression analysis revealed the association of 13 common significant haplotypes at Bonferroni ≤ 0.05. The phenotypic variance explained by these significant haplotypes ranged from low to moderate, suggesting a breeding strategy that combines multiple resistance alleles to enhance resistance to MLB. Additionally, one particular haplotype block (Hap_8.3) was found to consist of two SNPs (S8_152715134, S8_152460815) identified in GWAS with 9.45% variation explained (PVE). CONCLUSION: The identified SNPs/ haplotypes associated with the trait of interest contribute to the enrichment of allelic diversity and hold direct applicability in Genomics Assisted Breeding for enhancing MLB resistance in maize.

Identification and validation of a key genomic region on chromosome 6 for resistance to Fusarium stalk rot in tropical maize.

KEY MESSAGE: A key genomic region was identified for resistance to FSR at 168 Mb on chromosome 6 in GWAS and haplotype regression analysis, which was validated by QTL mapping in two populations. Fusarium stalk rot (FSR) of maize is an economically important post-flowering stalk rot (PFSR) disease caused by Fusarium verticillioides. The pathogen invades the plant individually, or in combination with other stalk rot pathogens or secondary colonizers, thereby making it difficult to make accurate selection for resistance. For identification and validation of genomic regions associated with FSR resistance, a genome-wide association study (GWAS) was conducted with 342 maize lines. The panel was screened for FSR in three environments using standard artificial inoculation methodology. GWAS using the mixed linear model corrected for population structure and kinship was done, in which 290,626 SNPs from genotyping-by-sequencing were used. A total of 7 SNPs, five on chromosome 6 showing strong LD at 168 Mb, were identified to be associated with FSR. Haplotype regression analysis identified 32 haplotypes with a significant effect on the trait. In a QTL mapping experiment in two populations for validating the identified variants, QTLs were identified with confidence intervals having overlapped physical coordinates in both the populations on chromosome 6, which was closely located to the GWAS-identified variants on chromosome 6. It makes this genomic region a crucial one to further investigate the possibility of developing trait markers for deployment in breeding pipelines. It was noted that previously reported QTLs for other stalk rots in maize mapped within the same physical intervals of several haplotypes identified for FSR resistance in this study. The possibility of QTLs controlling broad-spectrum resistance for PFSR in general requires further investigation.

Genome wide association mapping for heat tolerance in sub-tropical maize.

BACKGROUND: Heat tolerance is becoming increasingly important where maize is grown under spring season in India which coincide with grain filling stage of crop resulting in tassel blast, reduced pollen viability, pollination failure and barren ears that causes devastating yield losses. So, there is need to identify the genomic regions associated with heat tolerance component traits which could be further employed in maize breeding program. RESULTS: An association mapping panel, consisting of 662 doubled haploid (DH) lines, was evaluated for yield contributing traits under normal and natural heat stress conditions. Genome wide association studies (GWAS) carried out using 187,000 SNPs and 130 SNPs significantly associated for grain yield (GY), days to 50% anthesis (AD), days to 50% silking (SD), anthesis-silking interval (ASI), plant height (PH), ear height (EH) and ear position (EPO) were identified under normal conditions. A total of 46 SNPs strongly associated with GY, ASI, EH and EPO were detected under heat stress conditions. Fifteen of the SNPs was found to have common association with more than one trait such as two SNPs viz. S10_1,905,273 and S10_1,905,274 showed colocalization with GY, PH and EH whereas S10_7,132,845 SNP associated with GY, AD and SD under normal conditions. No such colocalization of SNP markers with multiple traits was observed under heat stress conditions. Haplotypes trend regression analysis revealed 122 and 85 haplotype blocks, out of which, 20 and 6 haplotype blocks were associated with more than one trait under normal and heat stress conditions, respectively. Based on SNP association and haplotype mapping, nine and seven candidate genes were identified respectively, which belongs to different gene models having different biological functions in stress biology. CONCLUSIONS: The present study identified significant SNPs and haplotype blocks associated with yield contributing traits that help in selection of donor lines with favorable alleles for multiple traits. These results provided insights of genetics of heat stress tolerance. The genomic regions detected in the present study need further validation before being applied in the breeding pipelines.

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments.

KEY MESSAGE: Intensive public sector breeding efforts and public-private partnerships have led to the increase in genetic gains, and deployment of elite climate-resilient maize cultivars for the stress-prone environments in the tropics. Maize (Zea mays L.) plays a critical role in ensuring food and nutritional security, and livelihoods of millions of resource-constrained smallholders. However, maize yields in the tropical rainfed environments are now increasingly vulnerable to various climate-induced stresses, especially drought, heat, waterlogging, salinity, cold, diseases, and insect pests, which often come in combinations to severely impact maize crops. The International Maize and Wheat Improvement Center (CIMMYT), in partnership with several public and private sector institutions, has been intensively engaged over the last four decades in breeding elite tropical maize germplasm with tolerance to key abiotic and biotic stresses, using an extensive managed stress screening network and on-farm testing system. This has led to the successful development and deployment of an array of elite stress-tolerant maize cultivars across sub-Saharan Africa, Asia, and Latin America. Further increasing genetic gains in the tropical maize breeding programs demands judicious integration of doubled haploidy, high-throughput and precise phenotyping, genomics-assisted breeding, breeding data management, and more effective decision support tools. Multi-institutional efforts, especially public-private alliances, are key to ensure that the improved maize varieties effectively reach the climate-vulnerable farming communities in the tropics, including accelerated replacement of old/obsolete varieties.

Combination of Linkage Mapping, GWAS, and GP to Dissect the Genetic Basis of Common Rust Resistance in Tropical Maize Germplasm.

Common rust (CR) caused by Puccina sorghi is one of the destructive fungal foliar diseases of maize and has been reported to cause moderate to high yield losses. Providing CR resistant germplasm has the potential to increase yields. To dissect the genetic architecture of CR resistance in maize, association mapping, in conjunction with linkage mapping, joint linkage association mapping (JLAM), and genomic prediction (GP) was conducted on an association-mapping panel and five F3 biparental populations using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). Analysis of variance for the biparental populations and the association panel showed significant genotypic and genotype x environment (GXE) interaction variances except for GXE of Pop4. Heritability (h2) estimates were moderate with 0.37-0.45 for the individual F3 populations, 0.45 across five populations and 0.65 for the association panel. Genome-wide association study (GWAS) analyses revealed 14 significant marker-trait associations which individually explained 6-10% of the total phenotypic variances. Individual population-based linkage analysis revealed 26 QTLs associated with CR resistance and together explained 14-40% of the total phenotypic variances. Linkage mapping revealed seven QTLs in pop1, nine QTL in pop2, four QTL in pop3, five QTL in pop4, and one QTL in pop5, distributed on all chromosomes except chromosome 10. JLAM for the 921 F3 families from five populations detected 18 QTLs distributed in all chromosomes except on chromosome 8. These QTLs individually explained 0.3 to 3.1% and together explained 45% of the total phenotypic variance. Among the 18 QTL detected through JLAM, six QTLs, qCR1-78, qCR1-227, qCR3-172, qCR3-186, qCR4-171, and qCR7-137 were also detected in linkage mapping. GP within population revealed low to moderate correlations with a range from 0.19 to 0.51. Prediction correlation was high with r = 0.78 for combined analysis of the five F3 populations. Prediction of biparental populations by using association panel as training set reveals positive correlations ranging from 0.05 to 0.22, which encourages to develop an independent but related population as a training set which can be used to predict diverse but related populations. The findings of this study provide valuable information on understanding the genetic basis of CR resistance and the obtained information can be used for developing functional molecular markers for marker-assisted selection and for implementing GP to improve CR resistance in tropical maize.

Identification and validation of genomic regions influencing kernel zinc and iron in maize.

KEY MESSAGE: Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize. Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world's poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P ≤ 5.03 × 10-05) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P ≤ 1 × 10-03) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P ≤ 0.01, R2 ≥ 0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

Dissection of a major QTL qhir1 conferring maternal haploid induction ability in maize.

KEY MESSAGE: Among the qhir11 and qhir12 sub-regions of a major QTL qhir1, only qhir11 has significant effect on maternal haploid induction, segregation distortion and kernel abortion. In vivo haploid induction in maize can be triggered in high frequencies by pollination with special genetic stocks called haploid inducers. Several genetic studies with segregating populations from non-inducer x inducer crosses identified a major QTL, qhir1, on chromosome 1.04 contributing to in vivo haploid induction. A recent Genome Wide Association Study using 51 inducers and 1482 non-inducers also identified two sub-regions within the qhir1 QTL region, named qhir11 and qhir12; qhir12 was proposed to be mandatory for haploid induction because the haplotype of qhir11 was also present in some non-inducers and putative candidate genes coding for DNA and amino acid binding proteins were identified in the qhir12 region. To characterize the effects of each sub-region of qhir1 on haploid induction rate, F2 recombinants segregating for one of the sub-regions and fixed for the other were identified in a cross between CML269 (non-inducer) and a tropicalized haploid inducer TAIL8. To quantify the haploid induction effects of qhir11 and qhir12, selfed progenies of recombinants between these sub-regions were genotyped. F3 plants homozygous for qhir11 and/or qhir12 were identified, and crossed to a ligueless tester to determine their haploid induction rates. The study revealed that only the qhir11 sub-region has a significant effect on haploid induction ability, besides causing significant segregation distortion and kernel abortion, traits that are strongly associated with maternal haploid induction. The results presented in this study can guide fine mapping efforts of qhir1 and in developing new inducers efficiently using marker assisted selection.

Analysis of effectiveness of R1-nj anthocyanin marker for in vivo haploid identification in maize and molecular markers for predicting the inhibition of R1-nj expression.

KEY MESSAGE: R1-nj anthocyanin marker inhibition is highly frequent in tropical maize germplasm considerably affecting efficiency of haploid identification. Molecular markers reliably differentiating germplasm with anthocyanin color inhibitor have been identified in this study. The R1-Navajo (R1-nj) color marker facilitates easy and quick identification of haploid kernels at the seed stage during in vivo haploid induction process in maize. However, the Navajo phenotype can be completely suppressed or poorly expressed in some germplasm, making it impossible or inefficient to identify haploids at the seed stage. In this study, we characterized the expression of R1-nj marker in a large array of tropical/subtropical inbred lines, breeding populations and landraces by crossing with the R1-nj-based tropicalized haploid inducer. There was a high frequency of inhibition of the Navajo phenotype in the maize inbred lines, which are used in tropical breeding programs. Genome-wide association mapping showed that the C1 anthocyanin regulatory locus is the most significant genetic factor influencing inhibition of the Navajo phenotype. Molecular marker assays were designed based on polymorphism in the C1 vs C1-I alleles. Analysis of a set of 714 inbred lines demonstrated that a combination of two gene-specific markers--8 bp C1-I InDel and C1-I SNP--could predict with high accuracy the presence of anthocyanin color inhibition in the germplasm analyzed. Information generated in this study aids in making informed decisions on the constitution of source populations for doubled haploid (DH) line development in tropical germplasm, particularly those derived from elite maize lines from CIMMYT. The C1-I gene-specific molecular markers identified and validated will facilitate high-throughput and cost-effective evaluation of a large pool of germplasm for the presence of the dominant color inhibitor in maize germplasm.

Fine mapping of Msv1, a major QTL for resistance to Maize Streak Virus leads to development of production markers for breeding pipelines.

Msv1 , the major QTL for MSV resistance was delimited to an interval of 0.87 cM on chromosome 1 at 87 Mb and production markers with high prediction accuracy were developed. Maize streak virus (MSV) disease is a devastating disease in the Sub-Saharan Africa (SSA), which causes significant yield loss in maize. Resistance to MSV has previously been mapped to a major QTL (Msv1) on chromosome 1 that is germplasm and environment independent and to several minor loci elsewhere in the genome. In this study, Msv1 was fine-mapped through QTL isogenic recombinant strategy using a large F 2 population of CML206 × CML312 to an interval of 0.87 cM on chromosome 1. Genome-wide association study was conducted in the DTMA (Drought Tolerant Maize for Africa)-Association mapping panel with 278 tropical/sub-tropical breeding lines from CIMMYT using the high-density genotyping-by-sequencing (GBS) markers. This study identified 19 SNPs in the region between 82 and 93 Mb on chromosome 1(B73 RefGen_V2) at a P < 1.00E-04, which coincided with the fine-mapped region of Msv1. Haplotype trend regression identified a haplotype block significantly associated with response to MSV. Three SNPs in this haplotype block at 87 Mb on chromosome 1 had an accuracy of 0.94 in predicting the disease reaction in a collection of breeding lines with known responses to MSV infection. In two biparental populations, selection for resistant Msv1 haplotype demonstrated a reduction of 1.03-1.39 units on a rating scale of 1-5, compared to the susceptible haplotype. High-throughput KASP assays have been developed for these three SNPs to enable routine marker screening in the breeding pipeline for MSV resistance.

LC-MS/MS analysis of differentially expressed glioblastoma membrane proteome reveals altered calcium signaling and other protein groups of regulatory functions.

Membrane proteins play key roles in the development and progression of cancer. We have studied differentially expressed membrane proteins in glioblastoma multiforme (GBM), the most common and aggressive type of primary brain tumor, by high resolution LC-MS/MS mass spectrometry and quantitation by iTRAQ. A total of 1834 membrane proteins were identified with high confidence, of which 356 proteins were found to be altered by 2-fold change or more (198 up- and 158 down-regulated); 56% of them are known membrane proteins associated with major cellular processes. Mass spectrometry results were confirmed for representative proteins on individual specimens by immunohistochemistry. On mapping of the differentially expressed proteins to cellular pathways and functional networks, we notably observed many calcium-binding proteins to be altered, implicating deregulation of calcium signaling and homeostasis in GBM, a pathway also found to be enriched in the report (Dong, H., Luo, L., Hong, S., Siu, H., Xiao, Y., Jin, L., Chen, R., and Xiong, M. (2010) Integrated analysis of mutations, miRNA and mRNA expression in glioblastoma. BMC Syst. Biol. 4, 163) based on The Cancer Genome Atlas analysis of GBMs. Annotations of the 356 proteins identified by us with The Cancer Genome Atlas transcriptome data set indicated overlap with 295 corresponding transcripts, which included 49 potential miRNA targets; many transcripts correlated with proteins in their expression status. Nearly 50% of the differentially expressed proteins could be classified as transmembrane domain or signal sequence-containing proteins (159 of 356) with potential of appearance in cerebrospinal fluid or plasma. Interestingly, 75 of them have been already reported in normal cerebrospinal fluid or plasma along with other proteins. This first, in-depth analysis of the differentially expressed membrane proteome of GBM confirms genes/proteins that have been implicated in earlier studies, as well as reveals novel candidates that are being reported for the first time in GBM or any other cancer that could be investigated further for clinical applications.

An ATP-binding cassette subfamily G full transporter is essential for the retention of leaf water in both wild barley and rice.

Land plants have developed a cuticle preventing uncontrolled water loss. Here we report that an ATP-binding cassette (ABC) subfamily G (ABCG) full transporter is required for leaf water conservation in both wild barley and rice. A spontaneous mutation, eibi1.b, in wild barley has a low capacity to retain leaf water, a phenotype associated with reduced cutin deposition and a thin cuticle. Map-based cloning revealed that Eibi1 encodes an HvABCG31 full transporter. The gene was highly expressed in the elongation zone of a growing leaf (the site of cutin synthesis), and its gene product also was localized in developing, but not in mature tissue. A de novo wild barley mutant named "eibi1.c," along with two transposon insertion lines of rice mutated in the ortholog of HvABCG31 also were unable to restrict water loss from detached leaves. HvABCG31 is hypothesized to function as a transporter involved in cutin formation. Homologs of HvABCG31 were found in green algae, moss, and lycopods, indicating that this full transporter is highly conserved in the evolution of land plants.

Exploring Metabolomics to Innovate Management Approaches for Fall Armyworm (Spodoptera frugiperda [J.E. Smith]) Infestation in Maize (Zea mays L.).

The Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), is a highly destructive lepidopteran pest known for its extensive feeding on maize (Zea mays L.) and other crops, resulting in a substantial reduction in crop yields. Understanding the metabolic response of maize to FAW infestation is essential for effective pest management and crop protection. Metabolomics, a powerful analytical tool, provides insights into the dynamic changes in maize's metabolic profile in response to FAW infestation. This review synthesizes recent advancements in metabolomics research focused on elucidating maize's metabolic responses to FAW and other lepidopteran pests. It discusses the methodologies used in metabolomics studies and highlights significant findings related to the identification of specific metabolites involved in FAW defense mechanisms. Additionally, it explores the roles of various metabolites, including phytohormones, secondary metabolites, and signaling molecules, in mediating plant-FAW interactions. The review also examines potential applications of metabolomics data in developing innovative strategies for integrated pest management and breeding maize cultivars resistant to FAW by identifying key metabolites and associated metabolic pathways involved in plant-FAW interactions. To ensure global food security and maximize the potential of using metabolomics in enhancing maize resistance to FAW infestation, further research integrating metabolomics with other omics techniques and field studies is necessary.

QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance.

Despite numerous published reports of quantitative trait loci (QTL) for drought-related traits, practical applications of such QTL in maize improvement are scarce. Identifying QTL of sizeable effects that express more or less uniformly in diverse genetic backgrounds across contrasting water regimes could significantly complement conventional breeding efforts to improve drought tolerance. We evaluated three tropical bi-parental populations under water-stress (WS) and well-watered (WW) regimes in Mexico, Kenya and Zimbabwe to identify genomic regions responsible for grain yield (GY) and anthesis-silking interval (ASI) across multiple environments and diverse genetic backgrounds. Across the three populations, on average, drought stress reduced GY by more than 50 % and increased ASI by 3.2 days. We identified a total of 83 and 62 QTL through individual environment analyses for GY and ASI, respectively. In each population, most QTL consistently showed up in each water regime. Across the three populations, the phenotypic variance explained by various individual QTL ranged from 2.6 to 17.8 % for GY and 1.7 to 17.8 % for ASI under WS environments and from 5 to 19.5 % for GY under WW environments. Meta-QTL (mQTL) analysis across the three populations and multiple environments identified seven genomic regions for GY and one for ASI, of which six mQTL on chr.1, 4, 5 and 10 for GY were constitutively expressed across WS and WW environments. One mQTL on chr.7 for GY and one on chr.3 for ASI were found to be 'adaptive' to WS conditions. High throughput assays were developed for SNPs that delimit the physical intervals of these mQTL. At most of the QTL, almost equal number of favorable alleles was donated by either of the parents within each cross, thereby demonstrating the potential of drought tolerant × drought tolerant crosses to identify QTL under contrasting water regimes.

Cleistogamous flowering in barley arises from the suppression of microRNA-guided HvAP2 mRNA cleavage.

The cleistogamous flower sheds its pollen before opening, forcing plants with this habit to be almost entirely autogamous. Cleistogamy also provides a means of escape from cereal head blight infection and minimizes pollen-mediated gene flow. The lodicule in cleistogamous barley is atrophied. We have isolated cleistogamy 1 (Cly1) by positional cloning and show that it encodes a transcription factor containing two AP2 domains and a putative microRNA miR172 targeting site, which is an ortholog of Arabidopsis thaliana AP2. The expression of Cly1 was concentrated within the lodicule primordia. We established a perfect association between a synonymous nucleotide substitution at the miR172 targeting site and cleistogamy. Cleavage of mRNA directed by miR172 was detectable only in a noncleistogamous background. We conclude that the miR172-derived down-regulation of Cly1 promotes the development of the lodicules, thereby ensuring noncleistogamy, although the single nucleotide change at the miR172 targeting site results in the failure of the lodicules to develop properly, producing the cleistogamous phenotype.

Genomic-regions associated with cold stress tolerance in Asia-adapted tropical maize germplasm.

Maize is gaining impetus in non-traditional and non-conventional seasons such as off-season, primarily due to higher demand and economic returns. Maize varieties directed for growing in the winter season of South Asia must have cold resilience as an important trait due to the low prevailing temperatures and frequent cold snaps observed during this season in most parts of the lowland tropics of Asia. The current study involved screening of a panel of advanced tropically adapted maize lines to cold stress during vegetative and flowering stage under field conditions. A suite of significant genomic loci (28) associated with grain yield along and agronomic traits such as flowering (15) and plant height (6) under cold stress environments. The haplotype regression revealed 6 significant haplotype blocks for grain yield under cold stress across the test environments. Haplotype blocks particularly on chromosomes 5 (bin5.07), 6 (bin6.02), and 9 (9.03) co-located to regions/bins that have been identified to contain candidate genes involved in membrane transport system that would provide essential tolerance to the plant. The regions on chromosome 1 (bin1.04), 2 (bin 2.07), 3 (bin 3.05-3.06), 5 (bin5.03), 8 (bin8.05-8.06) also harboured significant SNPs for the other agronomic traits. In addition, the study also looked at the plausibility of identifying tropically adapted maize lines from the working germplasm with cold resilience across growth stages and identified four lines that could be used as breeding starts in the tropical maize breeding pipelines.

Low-Density Reference Fingerprinting SNP Dataset of CIMMYT Maize Lines for Quality Control and Genetic Diversity Analyses.

CIMMYT maize lines (CMLs), which represent the tropical maize germplasm, are freely available worldwide. All currently released 615 CMLs and fourteen temperate maize inbred lines were genotyped with 180 kompetitive allele-specific PCR single nucleotide polymorphisms to develop a reference fingerprinting SNP dataset that can be used to perform quality control (QC) and genetic diversity analyses. The QC analysis identified 25 CMLs with purity, identity, or mislabeling issues. Further field observation, purification, and re-genotyping of these CMLs are required. The reference fingerprinting SNP dataset was developed for all of the currently released CMLs with 152 high-quality SNPs. The results of principal component analysis and average genetic distances between subgroups showed a clear genetic divergence between temperate and tropical maize, whereas the three tropical subgroups partially overlapped with one another. More than 99% of the pairs of CMLs had genetic distances greater than 0.30, showing their high genetic diversity, and most CMLs are distantly related. The heterotic patterns, estimated with the molecular markers, are consistent with those estimated using pedigree information in two major maize breeding programs at CIMMYT. These research findings are helpful for ensuring the regeneration and distribution of the true CMLs, via QC analysis, and for facilitating the effective utilization of the CMLs, globally.

GBS-Based SNP Map Pinpoints the QTL Associated With Sorghum Downy Mildew Resistance in Maize (Zea mays L.).

Sorghum downy mildew (SDM), caused by the biotrophic fungi Peronosclerospora sorghi , threatens maize production worldwide, including India. To identify quantitative trait loci (QTL) associated with resistance to SDM, we used a recombinant inbred line (RIL) population derived from a cross between resistant inbred line UMI936 (w) and susceptible inbred line UMI79. The RIL population was phenotyped for SDM resistance in three environments [E1-field (Coimbatore), E2-greenhouse (Coimbatore), and E3-field (Mandya)] and also utilized to construct the genetic linkage map by genotyping by sequencing (GBS) approach. The map comprises 1516 SNP markers in 10 linkage groups (LGs) with a total length of 6924.7 cM and an average marker distance of 4.57 cM. The QTL analysis with the phenotype and marker data detected nine QTL on chromosome 1, 2, 3, 5, 6, and 7 across three environments. Of these, QTL namely qDMR1.2, qDMR3.1, qDMR5.1, and qDMR6.1 were notable due to their high phenotypic variance. qDMR3.1 from chromosome 3 was detected in more than one environment (E1 and E2), explaining the 10.3% and 13.1% phenotypic variance. Three QTL, qDMR1.2, qDMR5.1, and qDMR6.1 from chromosomes 1, 5, and 6 were identified in either E1 or E3, explaining 15.2%-18% phenotypic variance. Moreover, genome mining on three QTL (qDMR3.1, qDMR5.1, and qDMR6.1) reveals the putative candidate genes related to SDM resistance. The information generated in this study will be helpful for map-based cloning and marker-assisted selection in maize breeding programs.

Identification and Validation of Genomic Regions Associated With Charcoal Rot Resistance in Tropical Maize by Genome-Wide Association and Linkage Mapping.

Charcoal rot is a post-flowering stalk rot (PFSR) disease of maize caused by the fungal pathogen, Macrophomina phaseolina. It is a serious concern for smallholder maize cultivation, due to significant yield loss and plant lodging at harvest, and this disease is expected to surge with climate change effects like drought and high soil temperature. For identification and validation of genomic variants associated with charcoal rot resistance, a genome-wide association study (GWAS) was conducted on CIMMYT Asia association mapping panel comprising 396 tropical-adapted lines, especially to Asian environments. The panel was phenotyped for disease severity across two locations with high disease prevalence in India. A subset of 296,497 high-quality SNPs filtered from genotyping by sequencing was correcting for population structure and kinship matrices for single locus mixed linear model (MLM) of GWAS analysis. A total of 19 SNPs were identified to be associated with charcoal rot resistance with P-value ranging from 5.88 × 10-06 to 4.80 × 10-05. Haplotype regression analysis identified 21 significant haplotypes for the trait with Bonferroni corrected P ≤ 0.05. For validating the associated variants and identifying novel QTLs, QTL mapping was conducted using two F2:3 populations. Two QTLs with overlapping physical intervals, qMSR6 and qFMSR6 on chromosome 6, identified from two different mapping populations and contributed by two different resistant parents, were co-located with the SNPs and haplotypes identified at 103.51 Mb on chromosome 6. Similarly, several SNPs/haplotypes identified on chromosomes 3, 6 and 8 were also found to be physically co-located within QTL intervals detected in one of the two mapping populations. The study also noted that several SNPs/haplotypes for resistance to charcoal rot were located within physical intervals of previously reported QTLs for Gibberella stalk rot resistance, which opens up a new possibility for common disease resistance mechanisms for multiple stalk rots.

Genome wide association study and genomic prediction for stover quality traits in tropical maize (Zea mays L.).

Maize is rapidly replacing traditionally cultivated dual purpose crops of South Asia, primarily due to the better economic remuneration. This has created an impetus for improving maize for both grain productivity and stover traits. Molecular techniques can largely assist breeders in determining approaches for effectively integrating stover trait improvement in their existing breeding pipeline. In the current study we identified a suite of potential genomic regions associated to the two major stover quality traits-in-vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) through genome wide association study. However, considering the fact that the loci identified for these complex traits all had smaller effects and accounted only a small portion of phenotypic variation, the effectiveness of following a genomic selection approach for these traits was evaluated. The testing set consists of breeding lines recently developed within the program and the training set consists of a panel of lines from the working germplasm comprising the founder lines of the newly developed breeding lines and also an unrelated diversity set. The prediction accuracy as determined by the Pearson's correlation coefficient between observed and predicted values of these breeding lines were high even at lower marker density (200 random SNPs), when the training and testing set were related. However, the accuracies were dismal, when there was no relationship between the training and the testing set.