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Summary Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high‐throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker‐assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.

Botrytis grey mould (BGM), caused by Botrytis cinerea, is emerging as an important disease of chickpea in the northern and eastern parts of the Indian Subcontinent, including Nepal, Bangladesh, Pakistan, and in Australia. This fungus has a very broad host range, and sources of complete resistance to the disease have not been found in Cicer arietinum L. germplasm. Resistance to this pathogen has been identified in some wild Cicer species. A set of 371 lines, including 164 landraces and 207 interspecific derivative lines (derived from crosses of cultivated chickpea with C. pinnatifidum, C. judaicum or C. reticulatum) have been screened against Botrytis grey mould under field conditions, and using the cut twig method at the Punjab Agricultural University (PAU), Ludhiana, in 2015-16 and 2016—17. Strong correlations between the two screening methods were indicated by paired-t tests. The Bulked Sample Analysis (BSA) approach was used to screen DNA of the five most resistant and five most susceptible host lines using 300 simple sequence repeat (SSR) markers. Eighty-eight markers were polymorphic. Chi-square statistic values showed strong correlations of TA144, GA102, TA194, TA140 and TR2 with the resistant bulks, signifying their usability as putative markers linked to BGM resistance, and for development of BGM tolerant genotypes in chickpea. Future studies should rapidly ascertain marker trait associations, and identify and develop diagnostic markers that provide an accurate method of molecular tagging BGM resistant genes in chickpea.

Kernel size-related traits, including kernel length, kernel width, and kernel thickness, are critical components in determining yield and kernel quality in maize (Zea mays L.). Dissecting the phenotypic characteristics of these traits, and discovering the candidate chromosomal regions for these traits, are of potential importance for maize yield and quality improvement. In this study, a total of 139 F2:3 family lines derived from EHel and B73, a distinct line with extremely low ear height (EHel), was used for phenotyping and QTL mapping of three kernel size-related traits, including 10-kernel length (KL), 10-kernel width (KWid), and 10-kernel thickness (KT). The results showed that only one QTL for KWid, i.e., qKWid9 on Chr9, with a phenotypic variation explained (PVE) of 13.4% was detected between SNPs of AX-86298371 and AX-86298372, while no QTLs were detected for KL and KT across all 10 chromosomes. Four bulked groups of family lines, i.e., Groups I to IV, were constructed with F2:3 family lines according to the phenotypic comparisons of KWid between EHel and B73. Among these four groups, Group I possessed a significantly lower KWid than EHel (P = 0.0455), Group II was similar to EHel (P = 0.34), while both Group III and Group IV were statistically higher than EHel (P < 0.05). Besides, except Group IV exhibited a similar KWid to B73 (P = 0.11), KWid of Groups I to III were statistically lower than B73 (P < 0.00). By comparing the bulked genotypes of the four groups to EHel and B73, a stable chromosomal region on Chr9 between SNPs of AX-86298372 to AX-86263154, entirely covered by qKWid9, was identified to link KWid with the positive allele of increasing phenotypic effect to KWid from B73, similar to that of qKWid9. A large amount of enzyme activity and macromolecule binding-related genes were annotated within this chromosomal region, suggesting qKWid9 as a potential QTL for KWid in maize.

Landraces and wild populations of red clover (Trifolium pratense L.) may represent a significant yet poorly characterized genetic resource of temperate grasslands. A bulking strategy with amplified fragment length polymorphism (AFLP) markers was optimized to characterize 120 red clover populations in 6 different groups: Swiss wild clover populations, Mattenklee landraces, Mattenklee cultivars, field clover cultivars, Dutch wild clover populations, and Dutch landraces. Analysis of 2 bulked samples/population consisting of 20 plants each with12 AFLP primer combinations was found optimal for determining genetic diversity and relationships within and among red clover populations and groups. Swiss wild clover populations were clearly separated from all other red clover groups and variability within and among populations was shown to be particularly high in wild clover populations and Mattenklee landraces, emphasising their value as genetic resources for improvement of red clover cultivars, as well as for conservation and restoration of biodiversity. This study shows that the ancestry of red clover landraces is primarily found in introduced cultivars rather than in natural wild clover populations. In addition, the methodological considerations presented here may help improve diversity analyses using bulked samples.

Applications of bulking procedures have played an increasingly important role in molecular characterization of plant germplasm, but little attention has been made to address the effectiveness of detecting genetic variation and inferring genetic relationships via bulking. An analysis was performed here to compare the genetic variation detected and genetic relationships inferred via bulking and single-plant sampling of five oat (Avena sativa L.), wheat (Triticum aestivum L.), and barley (Hordeum vulgare L.) cultivars with known pedigrees using amplified fragment length polymorphism (AFLP) markers. Three AFLP primer pairs were applied to screen one bulk and eight single-plant samples of each cultivar and up to 140 AFLP bands were scored for each sample. Analyses of these AFLP data showed bulking revealed AFLP variation up to 21.4% less than corresponding single-plant sampling for these crop species and also introduced up to 2.2% upward and 5.1% downward biases in detecting AFLP variations for each cultivar. The genetic relationships inferred by bulking using the Dice's coefficient, the simple matching coefficient, and the Jaccard's coefficient were largely the same, but differed from those in single-plant samples employing average Dice's coefficient, average simple matching coefficient, and AMOVA-based distance method. All of the inferred genetic relationships were not congruent to the known pedigrees. Clearly, substantial biases could exist in detection of AFLP variation and in inference of genetic relationships from bulk samples, even for closely related germplasm, and more efforts to assess the effectiveness of bulking in inferring genetic variation and relationships are needed for more informative molecular characterization of plant germplasm.

PCR-based markers are used for targeting plant genes. However, mapping these markers requires laborious and expensive analysis of individual genotypes. We propose here a sequential procedure for fine mapping of PCR markers relative to a target gene. Stepwise bulked analysis is employed to get a censored estimation of the recombination rate. The sequential estimation is compared to fixed sample size design. In both cases, the proposed procedure can achieve a substantial reduction in the number of PCR runs (up to 90-97% for close linkage) as compared to the standard individual-by-individual analysis.