Functional allele of a MATE gene selected during domestication modulates seed color in chickpea.

Seed color is one of the key target traits of domestication and artificial selection in chickpeas due to its implications on consumer preference and market value. The complex seed color trait has been well dissected in several crop species; however, the genetic mechanism underlying seed color variation in chickpea remains poorly understood. Here, we employed an integrated genomics strategy involving QTL mapping, high-density mapping, map-based cloning, association analysis, and molecular haplotyping in an inter-specific RIL mapping population, association panel, wild accessions, and introgression lines (ILs) of Cicer gene pool. This delineated a MATE gene, CaMATE23, encoding a Transparent Testa (TT) and its natural allele (8-bp insertion) and haplotype underlying a major QTL governing seed color on chickpea chromosome 4. Signatures of selective sweep and a strong purifying selection reflected that CaMATE23, especially its 8-bp insertion natural allelic variant, underwent selection during chickpea domestication. Functional investigations revealed that the 8-bp insertion containing the third cis-regulatory RY-motif element in the CaMATE23 promoter is critical for enhanced binding of CaFUSCA3 transcription factor, a key regulator of seed development and flavonoid biosynthesis, thereby affecting CaMATE23 expression and proanthocyanidin (PA) accumulation in the seed coat to impart varied seed color in chickpea. Consequently, overexpression of CaMATE23 in Arabidopsis tt12 mutant partially restored the seed color phenotype to brown pigmentation, ascertaining its functional role in PA accumulation in the seed coat. These findings shed new light on the seed color regulation and evolutionary history, and highlight the transcriptional regulation of CaMATE23 by CaFUSCA3 in modulating seed color in chickpea. The functionally relevant InDel variation, natural allele, and haplotype from CaMATE23 are vital for translational genomic research, including marker-assisted breeding, for developing chickpea cultivars with desirable seed color that appeal to consumers and meet global market demand.

Rice Pangenome Genotyping Array: an efficient genotyping solution for pangenome-based accelerated genetic improvement in rice.

The advent of the pangenome era has unraveled previously unknown genetic variation existing within diverse crop plants, including rice. This untapped genetic variation is believed to account for a major portion of phenotypic variation existing in crop plants. However, the use of conventional single reference-guided genotyping often fails to capture a large portion of this genetic variation leading to a reference bias. This makes it difficult to identify and utilize novel population/cultivar-specific genes for crop improvement. Thus, we developed a Rice Pangenome Genotyping Array (RPGA) harboring probes assaying 80K single-nucleotide polymorphisms (SNPs) and presence-absence variants spanning the entire 3K rice pangenome. This array provides a simple, user-friendly and cost-effective (60-80 USD per sample) solution for rapid pangenome-based genotyping in rice. The genome-wide association study (GWAS) conducted using RPGA-SNP genotyping data of a rice diversity panel detected a total of 42 loci, including previously known as well as novel genomic loci regulating grain size/weight traits in rice. Eight of these identified trait-associated loci (dispensable loci) could not be detected with conventional single reference genome-based GWAS. A WD repeat-containing PROTEIN 12 gene underlying one of such dispensable locus on chromosome 7 (qLWR7) along with other non-dispensable loci were subsequently detected using high-resolution quantitative trait loci mapping confirming authenticity of RPGA-led GWAS. This demonstrates the potential of RPGA-based genotyping to overcome reference bias. The application of RPGA-based genotyping for population structure analysis, hybridity testing, ultra-high-density genetic map construction and chromosome-level genome assembly, and marker-assisted selection was also demonstrated. A web application (http://www.rpgaweb.com) was further developed to provide an easy to use platform for the imputation of RPGA-based genotyping data using 3K rice reference panel and subsequent GWAS.

A superior gene allele involved in abscisic acid signaling enhances drought tolerance and yield in chickpea.

Identifying potential molecular tags for drought tolerance is essential for achieving higher crop productivity under drought stress. We employed an integrated genomics-assisted breeding and functional genomics strategy involving association mapping, fine mapping, map-based cloning, molecular haplotyping and transcript profiling in the introgression lines (ILs)- and near isogenic lines (NILs)-based association panel and mapping population of chickpea (Cicer arietinum). This combinatorial approach delineated a bHLH (basic helix-loop-helix) transcription factor, CabHLH10 (Cicer arietinum bHLH10) underlying a major QTL, along with its derived natural alleles/haplotypes governing yield traits under drought stress in chickpea. CabHLH10 binds to a cis-regulatory G-box promoter element to modulate the expression of RD22 (responsive to desiccation 22), a drought/abscisic acid (ABA)-responsive gene (via a trans-expression QTL), and two strong yield-enhancement photosynthetic efficiency (PE) genes. This, in turn, upregulates other downstream drought-responsive and ABA signaling genes, as well as yield-enhancing PE genes, thus increasing plant adaptation to drought with reduced yield penalty. We showed that a superior allele of CabHLH10 introgressed into the NILs improved root and shoot biomass and PE, thereby enhancing yield and productivity during drought without compromising agronomic performance. Furthermore, overexpression of CabHLH10 in chickpea and Arabidopsis (Arabidopsis thaliana) conferred enhanced drought tolerance by improving root and shoot agro-morphological traits. These findings facilitate translational genomics for crop improvement and the development of genetically tailored, climate-resilient, high-yielding chickpea cultivars.

Transcriptome landscape of early inflorescence developmental stages identifies key flowering time regulators in chickpea.

KEY MESSAGE: Transcriptome landscape during early inflorescence developmental stages identified candidate flowering time regulators including Early Flowering 3a. Further genomics approaches validated the role of this gene in flowering time regulation. The early stages of inflorescence development in plants are as crucial as the later floral developmental stages. Several traits, such as inflorescence architecture and flower developmental timings, are determined during those early stages. In chickpea, diverse forms of inflorescence architectures regarding meristem determinacy and the number of flowers per node are observed within the germplasm. Transcriptome analysis in four desi chickpea accessions with such unique inflorescence characteristics identifies the underlying shared regulatory events leading to inflorescence development. The vegetative to reproductive stage transition brings about major changes in the transcriptome landscape. The inflorescence development progression associated genes identified through co-expression network analysis includes both protein-coding genes and long non-coding RNAs (lncRNAs). Few lncRNAs identified in our study positively regulate flowering-related mRNA stability by acting competitively with miRNAs. Bulk segregrant analysis and association mapping narrowed down an InDel marker regulating flowering time in chickpea. Deletion of 11 bp in first exon of a negative flowering time regulator, Early Flowering 3a gene, leads to early flowering phenotype in chickpea. Understanding the key players involved in vegetative to reproductive stage transition and floral meristem development will be useful in manipulating flowering time and inflorescence architecture in chickpea and other legumes.

Genome-wide analysis of polymorphisms identified domestication-associated long low-diversity region carrying important rice grain size/weight quantitative trait loci.

Rice grain size and weight are major determinants of grain quality and yield and so have been under rigorous selection since domestication. However, the genetic basis for contrasting grain size/weight trait among Indian germplasms and their association with domestication-driven evolution is not well understood. In this study, two long (LGG) and two short grain (SGG) genotypes were resequenced. LGG (LGR and PB 1121) differentiated from SGG (Sonasal and Bindli) by 504 439 single nucleotide polymorphisms (SNPs) and 78 166 insertion-and-deletion polymorphisms. The LRK gene cluster was different and a truncation mutation in the LRK8 kinase domain was associated with LGG. Phylogeny with 3000 diverse rice accessions revealed that the four sequenced genotypes belonged to the japonica group and were at the edge of the clades indicating them to be the potential source of genetic diversity available in Indian rice germplasm. Six SNPs were significantly associated with grain size/weight and the top four of these could be validated in mapping a population, suggesting this study as a valuable resource for high-throughput genotyping. A contiguous long low-diversity region (LDR) of approximately 6 Mb carrying a major grain weight quantitative trait loci (harbouring OsTOR gene) was identified on Chromosome 5. This LDR was identified as an evolutionary important site with significant positive selection and multiple selection sweeps, and showed association with many domestication-related traits, including grain size/weight. The aus population retained more allelic variations in the LDR than the japonica and indica populations, suggesting it to be one of the divergence loci. All the data and analyses can be accessed from the RiceSzWtBase database.

Transcriptional signatures modulating shoot apical meristem morphometric and plant architectural traits enhance yield and productivity in chickpea.

Plant height (PH) and plant width (PW), two of the major plant architectural traits determining the yield and productivity of a crop, are defined by diverse morphometric characteristics of the shoot apical meristem (SAM). The identification of potential molecular tags from a single gene that simultaneously modulates these plant/SAM architectural traits is therefore prerequisite to achieve enhanced yield and productivity in crop plants, including chickpea. Large-scale multienvironment phenotyping of the association panel and mapping population have ascertained the efficacy of three vital SAM morphometric trait parameters, SAM width, SAM height and SAM area, as key indicators to unravel the genetic basis of the wide PW and PH trait variations observed in desi chickpea. This study integrated a genome-wide association study (GWAS); quantitative trait locus (QTL)/fine-mapping and map-based cloning with molecular haplotyping; transcript profiling; and protein-DNA interaction assays for the dissection of plant architectural traits in chickpea. These exertions delineated natural alleles and superior haplotypes from a CabHLH121 transcription factor (TF) gene within the major QTL governing PW, PH and SAM morphometric traits. A genome-wide protein-DNA interaction assay assured the direct binding of a known stem cell master regulator, CaWUS, to the WOX-homeodomain TF binding sites of a CabHLH121 gene and its constituted haplotypes. The differential expression of CaWUS and transcriptional regulation of its target CabHLH121 gene/haplotypes were apparent, suggesting their collective role in altering SAM morphometric characteristics and plant architectural traits in the contrasting near isogenic lines (NILs). The NILs introgressed with a superior haplotype of a CabHLH121 exhibited optimal PW and desirable PH as well as enhanced yield and productivity without compromising any component of agronomic performance. These molecular signatures of the CabHLH121 TF gene have the potential to regulate both PW and PH traits through the modulation of proliferation, differentiation and maintenance of the meristematic stem cell population in the SAM; therefore, these signatures will be useful in the translational genomic study of chickpea genetic enhancement. The restructured cultivars with desirable PH (semidwarf) and PW will ensure maximal planting density in a specified cultivable field area, thereby enhancing the overall yield and productivity of chickpea. This can essentially facilitate the achievement of better remunerative outputs by farmers with rational land use, therefore ensuring global food security in the present scenario of an increasing population density and shrinking per capita land area.

ABC Transporter-Mediated Transport of Glutathione Conjugates Enhances Seed Yield and Quality in Chickpea.

The identification of functionally relevant molecular tags is vital for genomics-assisted crop improvement and enhancement of seed yield, quality, and productivity in chickpea (Cicer arietinum). The simultaneous improvement of yield/productivity as well as quality traits often requires pyramiding of multiple genes, which remains a major hurdle given various associated epistatic and pleotropic effects. Unfortunately, no single gene that can improve yield/productivity along with quality and other desirable agromorphological traits is known, hampering the genetic enhancement of chickpea. Using a combinatorial genomics-assisted breeding and functional genomics strategy, this study identified natural alleles and haplotypes of an ABCC3-type transporter gene that regulates seed weight, an important domestication trait, by transcriptional regulation and modulation of the transport of glutathione conjugates in seeds of desi and kabuli chickpea. The superior allele/haplotype of this gene introgressed in desi and kabuli near-isogenic lines enhances the seed weight, yield, productivity, and multiple desirable plant architecture and seed-quality traits without compromising agronomic performance. These salient findings can expedite crop improvement endeavors and the development of nutritionally enriched high-yielding cultivars in chickpea.

Genome-wide cis-regulatory signatures for modulation of agronomic traits as exemplified by drought yield index (DYI) in chickpea.

Developing functional molecular tags from the cis-regulatory sequence components of genes is vital for their deployment in efficient genetic dissection of complex quantitative traits in crop plants including chickpea. The current study identified 431,194 conserved non-coding SNP (CNSNP) from the cis-regulatory element regions of genes which were annotated on a chickpea genome. These genome-wide CNSNP marker resources are made publicly accessible through a user-friendly web-database ( http://www.cnsnpcicarbase.com ). The CNSNP-based quantitative trait loci (QTL) and expression QTL (eQTL) mapping and genome-wide association study (GWAS) were further integrated with global gene expression landscapes, molecular haplotyping, and DNA-protein interaction study in the association panel and recombinant inbred lines (RIL) mapping population to decode complex genetic architecture of one of the vital seed yield trait under drought stress, drought yield index (DYI), in chickpea. This delineated two constituted natural haplotypes and alleles from a histone H3 protein-coding gene and its transcriptional regulator NAC transcription factor (TF) harboring the major QTLs and trans-acting eQTL governing DYI in chickpea. The effect of CNSNPs in TF-binding cis-element of a histone H3 gene in altering the binding affinity and transcriptional activity of NAC TF based on chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) assay was evident. The CNSNP-led promising molecular tags scanned will essentially have functional significance to decode transcriptional gene regulatory function and thus can drive translational genomic analysis in chickpea.

Genetic dissection of photosynthetic efficiency traits for enhancing seed yield in chickpea.

Understanding the genetic basis of photosynthetic efficiency (PE) contributing to enhanced seed yield per plant (SYP) is vital for genomics-assisted crop improvement of chickpea. The current study employed an integrated genomic strategy involving photosynthesis pathway gene-based association mapping, genome-wide association study, quantitative trait loci (QTL) mapping, and expression profiling. This identified 16 potential single nucleotide polymorphism loci linked to major QTLs underlying 16 candidate genes significantly associated with PE and SYP traits in chickpea. The allelic variants were tightly linked to positively interacting QTLs regulating both enhanced PE and SYP traits as exemplified by a chlorophyll A-B binding protein-coding gene. The leaf tissue-specific pronounced up-regulated expression of 16 associated genes in germplasm accessions and homozygous individuals of mapping population was evident. Such combinatorial genomic strategy coupled with gene haplotype-specific association and in silico protein-protein interaction study delineated natural alleles and superior haplotypes from a chlorophyll A-B binding (CAB) protein-coding gene and its interacting gene, Timing of CAB Expression 1 (TOC1), which appear to be most promising candidates in modulating chickpea PE and SYP traits. These functionally pertinent molecular signatures identified have efficacy to drive marker-assisted selection for developing PE-enriched cultivars with high seed yield in chickpea.

CLAVATA signaling pathway genes modulating flowering time and flower number in chickpea.

KEY MESSAGE: A combinatorial genomic strategy delineated functionally relevant natural allele of a CLAVATA gene and its marker (haplotype)-assisted introgression led to development of the early-flowering chickpea cultivars with high flower number and enhanced yield/productivity. Unraveling the genetic components involved in CLAVATA (CLV) signaling is crucial for modulating important shoot apical meristem (SAM) characteristics and ultimately regulating diverse SAM-regulated agromorphological traits in crop plants. A genome-wide scan identified 142 CLV1-, 28 CLV2- and 6 CLV3-like genes, and their comprehensive genomic constitution and phylogenetic relationships were deciphered in chickpea. The QTL/fine mapping and map-based cloning integrated with high-resolution association analysis identified SNP loci from CaCLV3_01 gene within a major CaqDTF1.1/CaqFN1.1 QTL associated with DTF (days to 50% flowering) and FN (flower number) traits in chickpea, which was further ascertained by quantitative expression profiling. Molecular haplotyping of CaCLV3_01 gene, expressed specifically in SAM, constituted two major haplotypes that differentiated the early-DTF and high-FN chickpea accessions from late-DTF and low-FN. Enhanced accumulation of transcripts of superior CaCLV3_01 gene haplotype and known flowering promoting genes was observed in the corresponding haplotype-introgressed early-DTF and high-FN near-isogenic lines (NILs) with narrow SAM width. The superior haplotype-introgressed NILs exhibited early-flowering, high-FN and enhanced seed yield/productivity without compromising agronomic performance. These delineated molecular signatures can regulate DTF and FN traits through SAM proliferation and differentiation and thereby will be useful for translational genomic study to develop early-flowering cultivars with enhanced yield/productivity.

Genetic dissection of plant growth habit in chickpea.

A combinatorial genomics-assisted breeding strategy encompassing association analysis, genetic mapping and expression profiling is found most promising for quantitative dissection of complex traits in crop plants. The present study employed GWAS (genome-wide association study) using 24,405 SNPs (single nucleotide polymorphisms) obtained with genotyping-by-sequencing (GBS) of 92 sequenced desi and kabuli accessions of chickpea. This identified eight significant genomic loci associated with erect (E)/semi-erect (SE) vs. spreading (S)/semi-spreading (SS)/prostrate (P) plant growth habit (PGH) trait differentiation regardless of diverse desi and kabuli genetic backgrounds of chickpea. These associated SNPs in combination explained 23.8% phenotypic variation for PGH in chickpea. Five PGH-associated genes were validated successfully in E/SE and SS/S/P PGH-bearing parental accessions and homozygous individuals of three intra- and interspecific RIL (recombinant inbred line) mapping populations as well as 12 contrasting desi and kabuli chickpea germplasm accessions by selective genotyping through Sequenom MassARRAY. The shoot apical, inflorescence and floral meristems-specific expression, including upregulation (seven-fold) of five PGH-associated genes especially in germplasm accessions and homozygous RIL mapping individuals contrasting with E/SE PGH traits was apparent. Collectively, this integrated genomic strategy delineated diverse non-synonymous SNPs from five candidate genes with strong allelic effects on PGH trait variation in chickpea. Of these, two vernalization-responsive non-synonymous SNP alleles carrying SNF2 protein-coding gene and B3 transcription factor associated with PGH traits were found to be the most promising in chickpea. The SNP allelic variants associated with E/SE/SS/S PGH trait differentiation were exclusively present in all cultivated desi and kabuli chickpea accessions while wild species/accessions belonging to primary, secondary and tertiary gene pools mostly contained prostrate PGH-associated SNP alleles. This indicates strong adaptive natural/artificial selection pressure (Tajima's D 3.15 to 4.57) on PGH-associated target genomic loci during chickpea domestication. These vital leads thus have potential to decipher complex transcriptional regulatory gene function of PGH trait differentiation and for understanding the selective sweep-based PGH trait evolution and domestication pattern in cultivated and wild chickpea accessions adapted to diverse agroclimatic conditions. Collectively, the essential inputs generated will be of profound use in marker-assisted genetic enhancement to develop cultivars with desirable plant architecture of erect growth habit types in chickpea.

Uncovering DNA methylation landscapes to decipher evolutionary footprints of phenotypic diversity in chickpea.

Genetic diversity and environmental factors are long believed to be the dominant contributors to phenotypic diversity in crop plants. However, it has been recently established that, besides genetic variation, epigenetic variation, especially variation in DNA methylation, plays a significant role in determining phenotypic diversity in crop plants. Therefore, assessing DNA methylation diversity in crop plants becomes vital, especially in the case of crops like chickpea, which has a narrow genetic base. Thus, in the present study, we employed whole-genome bisulfite sequencing to assess DNA methylation diversity in wild and cultivated (desi and kabuli) chickpea. This revealed extensive DNA methylation diversity in both wild and cultivated chickpea. Interestingly, the methylation diversity was found to be significantly higher than genetic diversity, suggesting its potential role in providing vital phenotypic diversity for the evolution and domestication of the Cicer gene pool. The phylogeny based on DNA methylation variation also indicates a potential complementary role of DNA methylation variation in addition to DNA sequence variation in shaping chickpea evolution. Besides, the study also identified diverse epi-alleles of many previously known genes of agronomic importance. The Cicer MethVarMap database developed in this study enables researchers to readily visualize methylation variation within the genes and genomic regions of their interest (http://223.31.159.7/cicer/public/). Therefore, epigenetic variation like DNA methylation variation can potentially explain the paradox of high phenotypic diversity despite the narrow genetic base in chickpea and can potentially be employed for crop improvement.

Integrated Genomic Strategies for Cereal Genetic Enhancement: Combining QTL and Association Mapping.

Identification of genetic basis for important agronomic traits is essential for marker-assisted crop improvement. Linkage mapping is one of the most popular approaches utilized for identification of major quantitative trait loci (QTLs) governing important agronomic traits in cereals. However, the identified QTLs usually span large genomic intervals and very few of these are subsequently fine mapped to single major effect gene. This hinders application of these QTLs in marker-aided breeding and crop genetic enhancement. On the contrary, association mapping, another popular approach for identification of QTLs, provides very high resolution but suffers from high level of false positives. Joint linkage-association analysis provides a way to combine advantages and avoid the pitfalls associated with both these methods. In this context, we recently developed MetaQTL specific regional association analysis and demonstrated its utility to rapidly narrow down previously identified QTL intervals to few candidate genes. Here, we describe the detailed step-by-step guide for performing MetaQTL specific regional association analysis to identify important genomic regions and underlying potential major effect genes governing traits of agronomic importance in cereals.

Genome-wide generation and genotyping of informative SNPs to scan molecular signatures for seed yield in chickpea.

We discovered 2150 desi and 2199 kabuli accessions-derived SNPs by cultivar-wise individual assembling of sequence-reads generated through genotyping-by-sequencing of 92 chickpea accessions. Subsequent large-scale validation and genotyping of these SNPs discovered 619 desi accessions-derived (DAD) SNPs, 531 kabuli accessions-derived (KAD) SNPs, 884 multiple accessions-derived (MAD) SNPs and 1083 two accessions (desi ICC 4958 and kabuli CDC Frontier)-derived (TAD) SNPs that were mapped on eight chromosomes. These informative SNPs were annotated in coding/non-coding regulatory sequence components of genes. The MAD-SNPs were efficient to detect high intra-specific polymorphic potential and wide natural allelic diversity level including high-resolution admixed-population genetic structure and precise phylogenetic relationship among 291 desi and kabuli accessions. This signifies their effectiveness in introgression breeding and varietal improvement studies targeting useful agronomic traits of chickpea. Six trait-associated genes with SNPs including quantitative trait nucleotides (QTNs) in combination explained 27.5% phenotypic variation for seed yield per plant (SYP). A pentatricopeptide repeat (PPR) gene with a synonymous-coding SNP/QTN significantly associated with SYP trait was found most-promising in chickpea. The essential information delineated can be of immense utility in genomics-assisted breeding applications to develop high-yielding chickpea cultivars.

Regional Association Analysis of MetaQTLs Delineates Candidate Grain Size Genes in Rice.

Molecular mapping studies which aim to identify genetic basis of diverse agronomic traits are vital for marker-assisted crop improvement. Numerous Quantitative Trait Loci (QTLs) mapped in rice span long genomic intervals with hundreds to thousands of genes, which limits their utilization for marker-assisted genetic enhancement of rice. Although potent, fine mapping of QTLs is challenging task as it requires screening of large number of segregants to identify suitable recombination events. Association mapping offers much higher resolution as compared to QTL mapping, but detects considerable number of spurious QTLs. Therefore, combined use of QTL and association mapping strategies can provide advantages associated with both these methods. In the current study, we utilized meta-analysis approach to identify metaQTLs associated with grain size/weight in diverse Indian indica and aromatic rice accessions. Subsequently, attempt has been made to narrow-down identified grain size/weight metaQTLs through individual SNP- as well as haplotype-based regional association analysis. The study identified six different metaQTL regions, three of which were successfully revalidated, and substantially scaled-down along with GS3 QTL interval (positive control) by regional association analysis. Consequently, two potential candidate genes within two reduced metaQTLs were identified based on their differential expression profiles in different tissues/stages of rice accessions during seed development. The developed strategy has broader practical utility for rapid delineation of candidate genes and natural alleles underlying QTLs associated with complex agronomic traits in rice as well as major crop plants enriched with useful genetic and genomic information.

A Multiple QTL-Seq Strategy Delineates Potential Genomic Loci Governing Flowering Time in Chickpea.

Identification of functionally relevant potential genomic loci using an economical, simpler and user-friendly genomics-assisted breeding strategy is vital for rapid genetic dissection of complex flowering time quantitative trait in chickpea. A high-throughput multiple QTL-seq strategy was employed in two inter (Cicer arietinum desi accession ICC 4958 × C reticulatum wild accession ICC 17160)- and intra (ICC 4958 × C. arietinum kabuli accession ICC 8261)-specific RIL mapping populations to identify the major QTL genomic regions governing flowering time in chickpea. The whole genome resequencing discovered 1635117 and 592486 SNPs exhibiting differentiation between early- and late-flowering mapping parents and bulks, constituted by pooling the homozygous individuals of extreme flowering time phenotypic trait from each of two aforesaid RIL populations. The multiple QTL-seq analysis using these mined SNPs in two RIL mapping populations narrowed-down two longer (907.1 kb and 1.99 Mb) major flowering time QTL genomic regions into the high-resolution shorter (757.7 kb and 1.39 Mb) QTL intervals on chickpea chromosome 4. This essentially identified regulatory as well as coding (non-synonymous/synonymous) novel SNP allelic variants from two efl1 (early flowering 1) and GI (GIGANTEA) genes regulating flowering time in chickpea. Interestingly, strong natural allelic diversity reduction (88-91%) of two known flowering genes especially mapped at major QTL intervals as compared to that of background genomic regions (where no flowering time QTLs were mapped; 61.8%) in cultivated vis-à-vis wild Cicer gene pools was evident inferring the significant impact of evolutionary bottlenecks on these loci during chickpea domestication. Higher association potential of coding non-synonymous and regulatory SNP alleles mined from efl1 (36-49%) and GI (33-42%) flowering genes for early and late flowering time differentiation among chickpea accessions was evident. The robustness and validity of two functional allelic variants-containing genes localized at major flowering time QTLs was apparent by their identification from multiple intra-/inter-specific mapping populations of chickpea. The functionally relevant molecular tags delineated can be of immense use for deciphering the natural allelic diversity-based domestication pattern of flowering time and expediting genomics-aided crop improvement to develop early flowering cultivars of chickpea.

An Efficient Strategy Combining SSR Markers- and Advanced QTL-seq-driven QTL Mapping Unravels Candidate Genes Regulating Grain Weight in Rice.

Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study developed 6244 genome-wide informative SSR markers exhibiting in silico fragment length polymorphism based on repeat-unit variations among genomic sequences of 11 indica, japonica, aus, and wild rice accessions. These markers were mapped on diverse coding and non-coding sequence components of known cloned/candidate genes annotated from 12 chromosomes and revealed a much higher amplification (97%) and polymorphic potential (88%) along with wider genetic/functional diversity level (16-74% with a mean 53%) especially among accessions belonging to indica cultivar group, suggesting their utility in large-scale genomics-assisted breeding applications in rice. A high-density 3791 SSR markers-anchored genetic linkage map (IR 64 × Sonasal) spanning 2060 cM total map-length with an average inter-marker distance of 0.54 cM was generated. This reference genetic map identified six major genomic regions harboring robust QTLs (31% combined phenotypic variation explained with a 5.7-8.7 LOD) governing grain weight on six rice chromosomes. One strong grain weight major QTL region (OsqGW5.1) was narrowed-down by integrating traditional QTL mapping with high-resolution QTL region-specific integrated SSR and single nucleotide polymorphism markers-based QTL-seq analysis and differential expression profiling. This led us to delineate two natural allelic variants in two known cis-regulatory elements (RAV1AAT and CARGCW8GAT) of glycosyl hydrolase and serine carboxypeptidase genes exhibiting pronounced seed-specific differential regulation in low (Sonasal) and high (IR 64) grain weight mapping parental accessions. Our genome-wide SSR marker resource (polymorphic within/between diverse cultivar groups) and integrated genomic strategy can efficiently scan functionally relevant potential molecular tags (markers, candidate genes and alleles) regulating complex agronomic traits (grain weight) and expedite marker-assisted genetic enhancement in rice.