# iKISS: A Reference-Free Pipeline for Inferring diversity, structuration, selection and genotype-phenotype association

Julie Orjuela, Yves Vigouroux

► To cite this version:

Julie Orjuela, Yves Vigouroux. iKISS: A Reference-Free Pipeline for Inferring diversity, structuration, selection and genotype-phenotype association. Journées Ouvertes en Biologie, Informatique et Mathématique 2025, Jul 2025, Bordeaux, France. 2025. [hal-05144683](https://hal.science/hal-05144683v1)

HAL Id: hal-05144683

https://hal.science/hal-05144683v1

Submitted on 4 Jul 2025

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Distributed under a Creative Commons Attribution 4.0 International License
# iKISS: A Reference-Free Pipeline for Inferring diversity, structuration, selection and genotype-phenotype association

Julie Orjuela, Yves Vigouroux

DIADE Unit, French National Research Institute for Sustainable Development IRD - Montpellier France

julie.orjuela@ird.fr

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## Introduction

Reference-free approaches are increasingly used to characterize genetic diversity without the need for genome or pangenome assembly. K-mer analysis, common in clinical genomics for pathogen detection and variant identification, has also proven effective in plants (Voichek Weigel, 2020), showing stronger phenotype associations than traditional SNP methods. However, a tool is needed to link k-mer analysis with population genomics. iKISS addresses this by enabling the use of k-mers to explore species diversity, ancestry, and genotype-phenotype/environment associations, offering a comprehensive approach to genetic variation and adaptation.

## iKISS pipeline

iKISS is a Python package that decomposes reads into k-mers, constructs a binary presence/absence table, and detects genetic markers associated with biological and environmental adaptation. It infers population structure and identifies genetic polymorphisms linked to traits (e.g., phenotype, climate) using multivariate approaches (LFMM, SNMF, and PCAdapt).

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## Diversity indices using k-mers

We assessed genetic diversity between *O. glaber-rima* and *O. barthii* using Jaccard dissimilarity based on kmers presence/absence. Results were compared with nucleotide diversity $π$ (using SNPs), and both methods revealed consistent patterns of variation between the two populations.

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## African Rice Diversity

### 1 Detection of selection

Analysis of the genetic structure of African populations using data from a random k-mer subset (10M) yielded results that were highly consistent with the analysis of SNP data. Genetic markers involved in adaptation were identified using the **PCADAPT** module. We detected a gene implicated in plant architecture domestication (*PROG1*) in African rice, confirming the effectiveness of the k-mer approach.

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### 2 Population structure analysis

Ancestry proportions and ancestral allelic frequencies in populations can be estimated directly using k-mers with the **SNMF** module. Similar ancestry patterns were observed using both SNP and k-mer approaches in cultivated African rice (*O. glaberrima*) compared to its wild ancestor (*O. barthii*).

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## Sex-linked associations in date palm

### 3 Genotype-phenotype linked associations

Using iKISS with **LFMM**, we detected regions associated with the sex determination of date palm (*Phoenix dactylifera*) on LG12. The outliers identified were mapped to the date palm genome, confirming previous findings based on SNPs.

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Additionally, by assembling these outlier k-mers, we were able to tag male and female haplotypes using an approach based on k-mer allele frequencies, as well as k-mer coverage along the contigs.

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## Conclusions and Future Work

iKISS can be applied to a variety of fields, including diversity studies, detection of selection, population structure analysis, and genome-wide association studies (GWAS). It provides valuable insights for several plant species, including foreign genera.

In the future, we plan to explore k-mers for studying the impact of future climate scenarios on genetic diversity and adaptation.

## Code availability

PyPI: https://pypi.org/project/ikiss/

GitLab: https://forge.ird.fr/diade/iKISS.git

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