DOI: 10.5061/dryad.nk98sf80k
title: Chromosome-level assembly of two pearl millet (Cenchrus americanus) genomes, functional annotation and transcriptomes

description: We present platinum-grade reference genome assemblies, featuring gapless
 chromosomes, for two pearl millet lines: the Striga-susceptible
 SOSAT-C88-P10 (P10) and the resistant 29Aw (Aw). This study was motivated
 by the severe impact of the root parasitic weed Striga hermontica on pearl
 millet yield, with Striga relying on host-released strigolactones (SLs)
 for seed germination. These resources enable advanced genomic
 investigations in pearl millet, facilitating research on phenotypic
 traits, diversity, and adaptation. Additionally, comparative analysis
 between P10 and 29Aw genomes can pave the way for identifying genetic
 determinants of Striga resistance, contributing to the development of
 resilient pearl millet lines.
description: For a detailed workflow of the genome annotation part of the
 work, please refer to the following github repo:
 https://github.com/mjfi2sb3/millet-genome-annotation
description: # Chromosome-level assembly of two pearl millet (*Cenchrus americanus*)
 genomes, functional annotation and transcriptomes.
 ## Description of the data
 and file structure **Genome assemblies & data** The final assemblies
 are: **Awk_genome_assmb_FINAL_v1.fasta.gz** and
 **P10K_genome_assmb_FINAL_v1.fasta.gz** for AwK and P10K, respectively.
 These are the assemblies (with finalised chromosome names) that were used
 in the gene structure annotation using the MAKER pipeline. ***Other
 assembly related files:*** **Awk_assmb_files.tar.gz** and
 **P10k_assmb_files.tar.gz** are tarballs that contain the output from the
 juicer tool that we used to scaffold the initial hifiasm (assembler tool)
 HiFi-based assemblies using OmniC data. These tarballs contain: an agp
 file, an equivalent bed file, a break point report, and the fasta file
 with the original chromosome names (do not use with gene structure
 annotation). ***Genomic Raw Data:*** ***AwK:*** * PacBio HiFi (SequelII):
 1. AWK_2.r64068_20220308_035507.2_D01.ccs.fastq.gz 2.
 AWK_2.r64068_20220227_080231.4_D01.ccs.fastq.gz 3.
 AWK_2.r64068_20220227_080231.3_C01.ccs.fastq.gz * OmniC (Illumina) 1.
 AWK_DTG-OmniC-419_R1_001.fastq.gz 2. AWK_DTG-OmniC-419_R2_001.fastq.gz
 ***P10K*** * PacBio HiFi (SequelII) 1.
 P10_1A.r64068_20220227_080231.6_F01.ccs.fastq.gz 2.
 P10_1A.r64068_20220227_080231.5_E01.ccs.fastq.gz 3.
 P10_1A.r64068_20220220_071613.3_C01.ccs.fastq.gz * OmniC (Illumina) 1.
 P10K_DTG-OmniC-420_R1_001.fastq.gz 2. P10K_DTG-OmniC-420_R2_001.fastq.gz
 **Transcriptome** ***AWK:*** ***Isoseq:*** Raw Data:
 **AWK.r64068_20220831_124330_2_B01.ccs.bam** Analysis:
 **awk_isoseq.tar.gz** tarball has the following:
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) * barcodes.awk.tsv: has barcoding info * awk.isoseq.collapse.[gff|fasta]: final collapsed full-length isoseq transcripts. ***RNA-Seq:*** ***Raw Data:*** the raw can be downloaded from ENA under study PRJEB71762. We attach **AWK_rawdata_info.txt** and **P10K_rawdata_info.txt** which have some information about the RNA-Seq experiments. **Assembled transcripts:** **AWK_assmb_transcripts.tar.gz**: this tarball contains individual transcripts for each of the 16 samples as well as the merged transcripts file which collapses transcripts from all samples using StringTie merge mode. ***P10K:*** ***Isoseq:*** Raw Data: **P10K.r64068_20220831_124330_1_A01.ccs.bam** Analysis: **p10k_isoseq.tar.gz** is a tarball that contains 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) * barcode.p10k.tsv: barcode info * p10k.collapsed.gff|fasta is the final full-length transcripts ***RNA-Seq:*** ***Raw Data:*** the raw can be downloaded from ENA under study PRJEB71762. We attach **AWK_rawdata_info.txt** and **P10K_rawdata_info.txt** which have some information about the RNA-Seq experiments. **Assembled transcripts:** **P10K_assmb_transcripts.tar.gz**: this tarball contains individual transcripts for each of the 16 samples as well as the merged transcripts file which collapses transcripts from all samples using StringTie merge mode. **Genome Annotation** The genome annotation files (bed, predicted transcripts and proteins, repeat content, and evidence) are attached in AWK_MAKER_Annotation.tar.gz and P10K_MAKER_Annotation.tar.gz. See screenshot below as an example for P10K genome annotation tarball. ![](data:image/png;base64,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)\ *EV:* Mapped evidence from assembled RNA-seq and Iso-Seq data as well as homology evidence. refer to for details.\ *HC*: High Confidence genes. For details on how a gene is assigned as HC refer to the annotation GitHub\ *LC*: Low Confidence\ *proteins.fasta*: protein sequence of predicted mRNAs\ *transcripts.fasta*: DNA sequence of predicted mRNA.\ *XXX.MAKER.gff.gz*: main MAKER GFF file which has everything including HC, LC and EV. ## Sharing/Access information Another copy of the raw data (including RNA-Seq) and assemblies is available on ENA under study PRJEB71762.\ Details About the annotation pipeline can be found in the manuscript or our GitHub repo at