Morphology and genic-SSRs-based diversity analysis and georeferencing of economic traits in natural populations of Jack (Artocarpus heterophyllus Lam.) from Eastern India

Choudhary, Shashi Bhushan; Gurjar, Suresh Chandra; Singh, B. K.; Singh, Devendra Kumar; Sharma, Hariom Kumar; Horo, Seema; Kumari, Neetu; Amrapali, Shephalika; Ahlawat, S. P.; Singh, Kuldeep

doi:10.1016/j.scienta.2021.110852

Cited by 2 publications

(1 citation statement)

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“…These descriptor traits may be more valuable in ranges where cotton production and specific environmental factors ranges overlap, such as native insect ranges. Assessment of accession geographic collection information, or georeferencing, has led to valuable insights particularly in botanical studies ( Swenson et al, 2012 ; Choudhary et al, 2022 ). Crop species have a particular difficulty in utilizing geographic data as many accessions were obtained outside of collection expeditions thus contain uninformative or inaccurate geographic data, extensive data filtering would be required to even potentially utilize that data ( Feeley and Silman, 2010 ), but may be worth investigating in the future to potentially add value to the germplasm collection ( Volk and Richards, 2011 ).…”

Section: Discussionmentioning

confidence: 99%

Leveraging National Germplasm Collections to Determine Significantly Associated Categorical Traits in Crops: Upland and Pima Cotton as a Case Study

et al. 2022

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Observable qualitative traits are relatively stable across environments and are commonly used to evaluate crop genetic diversity. Recently, molecular markers have largely superseded describing phenotypes in diversity surveys. However, qualitative descriptors are useful in cataloging germplasm collections and for describing new germplasm in patents, publications, and/or the Plant Variety Protection (PVP) system. This research focused on the comparative analysis of standardized cotton traits as represented within the National Cotton Germplasm Collection (NCGC). The cotton traits are named by ‘descriptors’ that have non-numerical sub-categories (descriptor states) reflecting the details of how each trait manifests or is absent in the plant. We statistically assessed selected accessions from three major groups of Gossypium as defined by the NCGC curator: (1) “Stoneville accessions (SA),” containing mainly Upland cotton (Gossypium hirsutum) cultivars; (2) “Texas accessions (TEX),” containing mainly G. hirsutum landraces; and (3) Gossypium barbadense (Gb), containing cultivars or landraces of Pima cotton (Gossypium barbadense). For 33 cotton descriptors we: (a) revealed distributions of character states for each descriptor within each group; (b) analyzed bivariate associations between paired descriptors; and (c) clustered accessions based on their descriptors. The fewest significant associations between descriptors occurred in the SA dataset, likely reflecting extensive breeding for cultivar development. In contrast, the TEX and Gb datasets showed a higher number of significant associations between descriptors, likely correlating with less impact from breeding efforts. Three significant bivariate associations were identified for all three groups, bract nectaries:boll nectaries, leaf hair:stem hair, and lint color:seed fuzz color. Unsupervised clustering analysis recapitulated the species labels for about 97% of the accessions. Unexpected clustering results indicated accessions that may benefit from potential further investigation. In the future, the significant associations between standardized descriptors can be used by curators to determine whether new exotic/unusual accessions most closely resemble Upland or Pima cotton. In addition, the study shows how existing descriptors for large germplasm datasets can be useful to inform downstream goals in breeding and research, such as identifying rare individuals with specific trait combinations and targeting breakdown of remaining trait associations through breeding, thus demonstrating the utility of the analytical methods employed in categorizing germplasm diversity within the collection.

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