Evidence map›Paper›PMID 37968867›Full record

ArticleThe plant genome2024

HaploCatcher: An R package for prediction of haplotypes.

Zachary James Winn, Emily Hudson-Arns, Mikayla Hammers, Noah DeWitt, Jeanette Lyerly, Guihua Bai, Paul St Amand, Punya Nachappa, Scott Haley, Richard Esten Mason

Abstract read
In one paragraph

Article in The plant genome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

Zachary James WinnDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, USA.ORCID 0000-0003-1543-1527
Emily Hudson-ArnsDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, USA.
Mikayla HammersDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, USA.
Noah DeWittSchool of Plant, Environmental, and Soil Sciences, Louisiana State University, Baton Rouge, Louisiana, USA.ORCID 0000-0001-9055-993X
Jeanette LyerlyDepartment of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina, USA.ORCID 0000-0003-3853-9581
Guihua BaiUSDA Agricultural Research Service, Hard Winter Wheat Genetics Research Unit, Manhattan, Kansas, USA.ORCID 0000-0002-1194-319X
Paul St AmandUSDA Agricultural Research Service, Hard Winter Wheat Genetics Research Unit, Manhattan, Kansas, USA.
Punya NachappaDepartment of Agricultural Biology, Colorado State University, Fort Collins, Colorado, USA.
Scott HaleyDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, USA.
Richard Esten MasonDepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, USA.

Funding

WheatCap 2022-68013-36439
6 · The paper itself

Abstract

Wheat (Triticum aestivum L.) is crucial to global food security but is often threatened by diseases, pests, and environmental stresses. Wheat-stem sawfly (Cephus cinctus Norton) poses a major threat to food security in the United States, and solid-stem varieties, which carry the stem-solidness locus (Sst1), are the main source of genetic resistance against sawfly. Marker-assisted selection uses molecular markers to identify lines possessing beneficial haplotypes, like that of the Sst1 locus. In this study, an R package titled "HaploCatcher" was developed to predict specific haplotypes of interest in genome-wide genotyped lines. A training population of 1056 lines genotyped for the Sst1 locus, known to confer stem solidness, and genome-wide markers was curated to make predictions of the Sst1 haplotypes for 292 lines from the Colorado State University wheat breeding program. Predicted Sst1 haplotypes were compared to marker-derived haplotypes. Our results indicated that the training set was substantially predictive, with kappa scores of 0.83 for k-nearest neighbors and 0.88 for random forest models. Forward validation on newly developed breeding lines demonstrated that a random forest model, trained on the total available training data, had comparable accuracy between forward and cross-validation. Estimated group means of lines classified by haplotypes from PCR-derived markers and predictive modeling did not significantly differ. The HaploCatcher package is freely available and may be utilized by breeding programs, using their own training populations, to predict haplotypes for whole-genome sequenced early generation material.

Indexed as

HymenopteraPlant BreedingAnimalsGenotypeHaplotypesHumansTriticum

Identifiers

PMID37968867
PMCPMC12807199

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.