MutMap Approach Enables Rapid Identification of Candidate Genes and Development of Markers Associated With Early Flowering and Enhanced Seed Size in Chickpea (Cicer arietinum L.)

Abstract

Globally terminal drought is one of the major constraints to chickpea (Cicer arietinum L.) production. Early flowering genotypes escape terminal drought, and the increase in seed size compensates for yield losses arising from terminal drought. A MutMap population for early flowering and large seed size was developed by crossing the mutant line ICC4958-M3-2828 with wild-type ICC 4958. Based on the phenotyping of MutMap population, extreme bulks for days to flowering and 100-seed weight were sequenced using Hi-Seq2500 at 10X coverage. On aligning 47.41 million filtered reads to the CDC Frontier reference genome, 31.41 million reads were mapped and 332,395 single nucleotide polymorphisms (SNPs) were called. A reference genome assembly for ICC 4958 was developed replacing these SNPs in particular positions of the CDC Frontier genome. SNPs specific for each mutant bulk ranged from 3,993 to 5,771. We report a single unique genomic region on Ca6 (between 9.76 and 12.96 Mb) harboring 31, 22, 17, and 32 SNPs with a peak of SNP index = 1 for low bulk for flowering time, high bulk for flowering time, high bulk for 100-seed weight, and low bulk for 100-seed weight, respectively. Among these, 22 SNPs are present in 20 candidate genes and had a moderate allelic impact on the genes. Two markers, Ca6EF10509893 for early flowering and Ca6HSDW10099486 for 100-seed weight, were developed and validated using the candidate SNPs. Thus, the associated genes, candidate SNPs, and markers developed in this study are useful for breeding chickpea varieties that mitigate yield losses under drought stress.

Mutation mapping of a variegated EMS tomato reveals an FtsH-like protein precursor potentially causing patches of four phenotype classes in the leaves with distinctive internal morphology

“…The DG segments clearly differ from the WT green, making five classes to compare their histological, physiological, and microscopical features. The Mutmap analysis based on genomic comparisons of pooled DNA from plants with mutant and wildtype phenotypes [ 51 , 53 , 54 ] revealed that an FtsH-like protein precursor located on chromosome 4 is the most likely candidate. Taking these results into account, we concluded that this FtsH variegation mutant is dissimilar from the previously published tomato mutants with variegated leaves, including studies of a maternally inherited variegated tomato [ 23 ]; the Woolly mutant [ 25 ]; a recessive allele of yv ( yv mut ) [ 29 ], a cytoplasmic or mitochondrial mutation [ 55 ].…”

High confidence QTLs and key genes identified using Meta-QTL analysis for enhancing heat tolerance in chickpea (Cicer arietinum L.)

“…This indicates that the Meta-QTL1 harbor genes that control both flower initiation as well as repression of the flowering. In general, the genotypes with early flowering feature record higher yield by escaping the reproductive stage heat stress as well as end season drought (Manchikatla et al, 2021). In Meta-QTL1 and 6, we identified genes (Ca_18341, Ca_18590 and Ca_18924), that code for heat shock proteins or heat stress transcription factor A-5 referred as CaHsfsA5.…”

A novel regulator of wheat tillering LT1 identified by using an innovative BSA method

“…Current breakthroughs using high-throughput sequencing techniques have accelerated the identi cation of genes linked to agronomic traits and made gene isolation more feasible and e cient. For instance, the adaptable method MutMap (Abe et al 2012) has been widely used in identifying genes associated with a variety of traits, including but not limited to salt tolerance (Takagi et al 2015), endosperm development (Wang et al 2018b), owering and seed size (Manchikatla et al 2021), height and spikelet (Huang et al 2022) and more. MutMap-derived methods, such as MutMap+ (Fekih et al 2013), MutMap-Gap (Takagi et al 2013b), and QTL-seq (Takagi et al 2013a), have also been developed to improve the e ciency and accuracy of gene mapping.…”