Evidence map›Paper›PMID 35939073›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2022

Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits.

Harsimardeep S Gill, Jyotirmoy Halder, Jinfeng Zhang, Anshul Rana, Jonathan Kleinjan, Paul St Amand, Amy Bernardo, Guihua Bai, Sunish K Sehgal

Abstract read
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In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Harsimardeep S GillDepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.ORCID http://orcid.org/0000-0002-3067-6912
Jyotirmoy HalderDepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.
Jinfeng ZhangDepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.
Anshul RanaDepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.
Jonathan KleinjanDepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.
Paul St AmandUSDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA.
Amy BernardoUSDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA.
Guihua BaiUSDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, KS, 66506, USA.
Sunish K SehgalDepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA. sunish.sehgal@sdstate.edu.ORCID http://orcid.org/0000-0001-5644-7547

Funding

National Institute of Food and Agriculture 2022-68013-36439South Dakota Wheat Commission 3X1340U.S. Department of Agriculture SD00H695-20
6 · The paper itself

Abstract

Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, most of these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practical wheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs) were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by the breeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.

Indexed as

Genome-Wide Association StudyTriticumGenomicsNucleotidesPhenotypePlant BreedingPolymorphism, Single NucleotideNucleotides

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.