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Genomic convergence underlying high‐altitude adaptation in alpine plants

Journal of Integrative Plant Biology

April 2023
65(7)

DOI:10.1111/jipb.13485

Authors:

Xu Zhang

Chinese Academy of Sciences

Tianhui Kuang

Chinese Academy of Sciences

Zhihao Qian

Chinese Academy of Sciences

Show all 13 authorsHide

Evolutionary convergence is one of the most striking examples of adaptation driven by natural selection. However, genomic evidence for convergent adaptation to extreme environments remains scarce. Here, we assembled reference genomes of two alpine plants, Saussurea obvallata (Asteraceae) and Rheum alexandrae (Polygonaceae), with 37,938 and 61,463 annotated protein‐coding genes. By integrating an additional five alpine genomes, we elucidated genomic convergence underlying high‐altitude adaptation in alpine plants. Our results detected convergent contractions of disease‐resistance genes in alpine genomes, which might be an energy‐saving strategy for surviving in hostile environments with only a few pathogens present. We identified signatures of positive selection on a set of genes involved in reproduction and respiration (e.g., MMD1, NBS1, and HPR), and revealed signatures of molecular convergence on genes involved in self‐incompatibility, cell wall modification, DNA repair and stress resistance, which may underlie adaptation to extreme cold, high ultraviolet radiation and hypoxia environments. Incorporating transcriptomic data, we further demonstrated that genes associated with cuticular wax and flavonoid biosynthetic pathways exhibit higher expression levels in leafy bracts, shedding light on the genetic mechanisms of the adaptive “greenhouse” morphology. Our integrative data provide novel insights into convergent evolution at a high‐taxonomic level, aiding in a deep understanding of genetic adaptation to complex environments.

Evolutionary history of alpine plants (A) Chronogram showing divergence times among alpine plants (cyan background) with their lowland relatives (orange background) with node age and 95% confidence intervals (blue bars). The red and blue numbers above the branches represent significant expansion and contraction events, respectively. (B) Bar plot showing gene number identified by OrthorFinder, including unassigned genes which were not put into an orthogroup with any other genes, genes in orthogroup, and genes in species‐specific orthogroups which consist entirely of genes from one species. (C) Significantly enriched Gene Ontology (GO) terms for convergently expended (CoEx) gene families in alpine plant genomes. Each bubble represents a summarized GO term from the full GO list by reducing functional redundancies, and their closeness on the plot reflects their closeness in the GO graph, that is, the semantic similarity. (D) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of CoEx gene families in alpine plant genomes. “p‐adj” refers to the adjusted P‐value using the Benjamini–Hochberg method.

…

Function enrichment of gene families undergoing convergently evolutionary rate acceleration in alpine plant genomes (A) Significantly enriched Gene Ontology (GO) terms. Each bubble represents a summarized GO term from the full GO list by reducing functional redundancies, and their closeness on the plot reflects their closeness in the GO graph, that is, the semantic similarity. (B) Top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. “p‐adj” refers to the adjusted P‐value using the Benjamini–Hochberg method.

…

Four representative cases of alpine‐accelerated genes Signatures of convergent evolutionary rate shifts were detected using the RERconverge method (P < 0.05, Wilcoxon‐rank sum test). Each panel represents the estimated relative evolutionary rates (RERs) for a gene in alpine species (point in cyan labeled with species names) as well as in their lowland relatives (points in orange labeled with species names) and ancestral branches (plotted in a single row at the base of the y‐axis). A gene's RER for a given branch represents how quickly or slowly the gene is evolving on that branch relative to its overall rate of evolution throughout the tree.

…

Highly expressed genes in bract leaves of Saussurea obvallata (A) Sampling information of S. obvallata transcriptome data. Five tissues including three from leaves, basal leaves (JL), middle leaves (ML) and bract leaves (BL) as well as two from flowers (F) and stems (S), were sampled. (B) Top 20 KEGG pathways of significantly upregulated genes in bract leaves. “p‐adj” refers to the adjusted P‐value using the Benjamini–Hochberg method. Expression profiles of genes involved in cuticular wax (C) and flavonoid biosynthetic pathways (D) in different tissues of S. obvallata. High expressed genes in BL are shown in red in the simplified pathway models. The bar represents the gene expression level of each gene (z‐score) (4CL, 4‐coumarate: CoA ligase; CER, protein eceriferum; CHI, chalcone isomerase; CHS, chalcone synthase; DFR, dihydroflavonol 4‐reductase; F3H, flavanone 3‐hydroxylase; F3″H, flavonoid 3″‐hydroxylase; FA‐CoA, fatty acyl‐coenzyme A; FAR, fatty acid synthetase; FLS, flavonol synthase; LDOX/ANS, leucoanthocyanidin dioxygenase/anthocyanidin synthase; MAH1, midchain alkane hydroxylase 1; OMT, O‐methyltransferase; TT7, transparent testa 7; VLC, very‐long‐chain; WSD1, diacylglycerol acyltransferase 1).

…

of convergent adaptation to high‐altitude environments for seven alpine species The outer circle shows examples of enriched Gene Ontology (GO)‐terms (biological pathways). The middle circle shows examples of candidate genes named after the A. thaliana orthologs. The inner gray circle shows environmental stresses from high altitudes. Species names are provided below the picture. *Genes having undergone convergent contraction.

…

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IPB Journal of Integrative

Plant Biology New Resource

https://doi.org/10.1111/jipb.13485

Genomic convergence underlying high‐altitude

adaptation in alpine plants

Xu Zhang

1,2

, Tianhui Kuang

, Wenlin Dong

1,2,4

,ZhihaoQian

1,2,4

, Huajie Zhang

1,2

, Jacob B. Landis

5,6

Tao Feng

1,2

, Lijuan Li

1,2,4

, Yanxia Sun

1,2

,JinlingHuang

3,7,8

,TaoDeng

*, Hengchang Wang

1,2

* and Hang Sun

1. CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture, The Chinese Academy of Sciences, Wuhan

Botanical Garden, Wuhan 430074, China

2. Center of Conservation Biology, Core Botanical Gardens, The Chinese Academy of Sciences, Wuhan 430074, China

3. Yunnan International Joint Laboratory for Biodiversity of Central Asia, Key Laboratory for Plant Diversity and Biogeography of East

Asia, Kunming Institute of Botany, The Chinese Academy of Sciences, Kunming 650201, China

4. University of Chinese Academy of Sciences, Beijing 100049, China

5. School of Integrative Plant Science, Section of Plant Biology and the L. H. Bailey Hortorium, Cornell University, Ithaca, New York

14850, USA

6. BTI Computational Biology Center, Boyce Thompson Institute, Ithaca, New York 14853, USA

7. State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China

8. Department of Biology, East Carolina University, Greenville, North Carolina 27858, USA

*Correspondences: Tao Deng (dengtao@mail.kib.ac.cn); Hengchang Wang (hcwang@wbgcas.cn); Hang Sun (sunhang@mail.kib.ac.cn,

Dr. Sun is fully responsible for the distributions of the materials associated with this article)

Xu Zhang Hang Sun

ABSTRACT

Evolutionary convergence is one of the most striking

examples of adaptation driven by natural selection.

However, genomic evidence for convergent adap-

tation to extreme environments remains scarce.

Here, we assembled reference genomes of two

alpine plants, Saussurea obvallata (Asteraceae)

and Rheum alexandrae (Polygonaceae), with 37,938

and 61,463 annotated protein‐coding genes. By

integrating an additional ﬁve alpine genomes,

we elucidated genomic convergence underlying

high‐altitude adaptation in alpine plants. Our results

detected convergent contractions of disease‐

resistance genes in alpine genomes, which might be

an energy‐saving strategy for surviving in hostile

environments with only a few pathogens present.

We identiﬁed signatures of positive selection on a

set of genes involved in reproduction and respira-

tion (e.g., MMD1, NBS1,andHPR), and revealed

signatures of molecular convergence on genes in-

volved in self‐incompatibility, cell wall modiﬁcation,

DNA repair and stress resistance, which may un-

derlie adaptation to extreme cold, high ultraviolet

radiation and hypoxia environments. Incorporating

transcriptomic data, we further demonstrated that

genes associated with cuticular wax and ﬂavonoid

biosynthetic pathways exhibit higher expression

levels in leafy bracts, shedding light on the genetic

mechanisms of the adaptive “greenhouse”mor-

phology. Our integrative data provide novel insights

into convergent evolution at a high‐taxonomic level,

aiding in a deep understanding of genetic adapta-

tion to complex environments.

Keywords: adaptation, alpine plants, evolutionary rates, genomic

convergence, “greenhouse”morphology, high altitude

Zhang, X., Kuang, T., Dong, W., Qian, Z., Zhang, H., Landis,

J. B., Feng, T., Li, L., Sun, Y., Huang, J., et al. (2023). Genomic

convergence underlying high‐altitude adaptation in alpine plants.

J. Integr. Plant Biol. 00: 1–16.

INTRODUCTION

Evolutionary biologists have long aimed to understand the

extent that evolutionary trajectories are predictable, that

is, the extent to which convergent adaptation in distinct lin-

eages is driven by conserved molecular changes (Zhang and

Kumar, 1997;Stern and Orgogozo, 2009;Zhen et al.,

2012;Storz, 2016). Evolutionary convergence in settings

where different species repeatedly face common selective

pressures offers a powerful opportunity to address this issue

(Yeaman et al., 2016;Birkeland et al., 2020;Xu et al., 2020).

An ideal system for investigating the genetic underpinnings of

convergent evolution is the independent adaptation of

divergent lineages to high‐altitude environments.

The Himalaya‐Hengduan Mountains (HHMs) represent the

world's most species‐rich temperate alpine biota, providing

an ideal natural laboratory for studying convergent adapta-

tion to high altitudes (Spicer et al., 2020). In the subnival

summits of the HHMs (elevation above 4,500 m), usually

characterized by freezing temperatures, high ultraviolet (UV)

radiation, and hypoxia, plants typically possess suites of

similar morphological and physiological adaptations to allow

them to survive and reproduce in these hostile environments

(Tsukaya and Tsuge, 2001). In comparison with plants of

lowland areas, plants living in the subnival summits of the

HHMs (and other high‐altitude areas) have dwarf stems,

smaller leaves and higher densities of branches, and often

exhibit a specialized morphology such as leafy bracts, woolly

coverings and cushion forms (Nagy and Grabherr, 2009;Sun

et al., 2014). Under similar stressful environmental conditions

of high altitudes, one would predict similar genetic compo-

nents underpinning adaptive evolution in alpine plants.

Genomewide studies have documented some genomic

footprints of high‐altitude adaptation by testing for positive

selection and mining expanded gene families, often involving

functional pathways such as DNA repair, abiotic stress re-

sponse, reproductive processes, as well as secondary me-

tabolite biosynthesis (Zeng et al., 2015;Zhang et al.,

2019;Wang et al., 2021). However, the limited availability of

reference genomes for alpine plants restricts further under-

standing of the genomic evolution of high‐altitude adaptation;

in particular, the underlying genomic convergence of alpine

adaptation has not been examined.

In this study, we newly assembled and annotated a

reference‐quality genome of Saussurea obvallata (Aster-

aceae) and a draft genome of Rheum alexandrae (Polygo-

naceae). These two species are primarily found in mountain

slopes and alpine meadows of the HHMs and are renowned

for their “glasshouse”morphology, that is, the upper leaves

of which have developed into large semitranslucent leafy

bracts that cover the inﬂorescences, which have been shown

to have signiﬁcant ecological beneﬁts to the plant (Song

et al., 2015). We integrated an additional ﬁve available

genomes of alpine plants [Crucihimalaya himalaica (Brassi-

caceae) (Zhang et al., 2019), Eutrema heterophyllum (Bras-

sicaceae) (Guo et al., 2018), Hordeum vulgare var. nudum

(Poaceae) (Zeng et al., 2015), Prunus mira (Rosaceae) (Wang

et al., 2021) and Salix brachista (Salicaceae) (Chen et al.,

2019)] as well as their lowland relatives for comparative

genomic analyses (Table S1). These seven alpine species

represent major clades of angiosperms that independently

colonized high‐altitude environments. Different from previous

case studies of plant genomes, we take advantage of a

comprehensive genomic data set of alpine plants to

characterize genomewide signatures of convergent evolu-

tion. Speciﬁcally, we intend to address three main questions:

(i) Do expanded or contracted gene families show convergent

patterns in alpine plants and effect high‐altitude adaptation?

(ii) Determine which genes have undergone convergent mo-

lecular evolution and are involved in adaptation to freezing,

high UV radiation and hypoxia environments? (iii) Last, what

are the genomic bases underlying the adaptive “greenhouse”

morphology? In addressing these questions, our study allows

for comprehensive genomic insights into convergent adap-

tation to high‐altitude environments.

RESULTS AND DISCUSSION

Assembly and annotation of two reference genomes

of alpine plants

Using a k‐mer analysis method, we ﬁrst estimated the ge-

nome size of S. obvallata and R. alexandrae to be ~2,251 and

~2,137 Mb, respectively (Figures S1,S2;Table S2). We then

generated a chromosome‐level genome of S. obvallata and a

contig‐level genome of R. alexandrae using Illumina, Oxford

Nanopore, and high‐throughput chromatin conformation

contact (Hi‐C) sequencing technologies (Table S3). For the

S. obvallata genome, in total ~95 Gb Illumina short reads,

~143 Gb Nanopore long reads and ~206 Gb Hi‐C data were

obtained. For the R. alexandrae genome, in total ~104 Gb

Illumina short reads and ~144 Gb Nanopore long reads were

generated. Additionally, transcriptomic data for R. alexandrae

(~25 Gb) and S. obvallata (~157 Gb) were obtained for

transcript‐based gene annotation (Table S3). Tissue‐speciﬁc

transcriptomic data for S. obvallata were also used for further

gene expression analysis (Table S4).

Ade novo assembly pipeline allowed us to achieve initial

genome assemblies that captured 2,044 and 2,040 Mb in 145

and 129 contigs for S. obvallata and R. alexandrae genomes,

with contig N50 of 36.96 and 36.32 Mb, respectively

(Table 1,S5). Using a Hi‐C assisted assembly pipeline, 1,952

Mb which accounted for 95.5% of the assembled S. obvallata

genome were anchored on 16 chromosomes (Tables 1,

S6;Figure S3), in line with previous cytological evidence

(Fujikawa et al., 2004). We further evaluated the completeness

of the assembled genomes and found high completeness rates

(94.6% of S. obvallata and 96.6% of R. alexandrae) of both

assemblies as supported by BUSCO (Benchmarking Universal

Single‐Copy Orthologs) assessments using the Embry-

ophyta_odb10 database (Tables 1,S7,S8)(Manni et al., 2021).

The long terminal repeat (LTR) assembly index (LAI), which

evaluates the contiguity of intergenic and repetitive regions of

genome assemblies based on the intactness of LTR retro-

transposons (Ou and Chen, and Jiang, 2018), was 19.68 for S.

obvallata and was 4.97 for R. alexandrae, respectively.

Transposable elements (TEs) and other repeat sequences

accounted for 81.88% and 81.65% of the S. obvallata

and R. alexandrae assemblies, respectively (Table 1).

In S. obvallata, LTR retrotransposons (43.95%), followed by

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DNA TEs (2.03%) and LINEs (0.93%), were most abundant,

with LTR‐Gypsy and LTR‐Copia retrotransposons accounting

for 18.19% and 25.76% of the LTRs, respectively (Table S9).

LTR retrotransposons (44.31%), LINES (2.73%), and DNA

TEs (4.08%) accounted for most of the R. alexandrae repeats,

with LTR‐Gypsy (37.98%) and LTR‐Copia (6.33%) retro-

transposons predominant among the LTRs (Table S10). A

combination of transcript‐based, de novo and homology‐

based prediction methods yielded 37,938 and 61,463 high‐

conﬁdence protein‐coding gene models (Table 1;Figures

S4,S5). By comparing with public protein databases, in total

36,542 (96.32%) and 47,535 (77.34%) predicted genes of

S. obvallata and R. alexandrae were functionally annotated

(Table S11). For the annotated genes, 93.5% and 96.1% of

the complete BUSCO genes in the Embryophyta_odb10 da-

tabase could be identiﬁed in S. obvallata and R. alexandrae

(Tables S7,S8), respectively. Overall, our newly assembled

and annotated genomes of S. obvallata and R. alexandrae are

high quality, providing valuable genomic resources for un-

derstanding the convergent adaptation of alpine plants to

high‐altitude environments.

Convergent changes in gene family number

We downloaded annotated protein sequences from genomes

of ﬁve additional alpine species as well as 13 representative

sister species living in low elevations (Table S1). Included

species were phylogenetically placed in seven families of an-

giosperms, including 17 eudicots and three monocots. In total

6,711 gene orthologs were identiﬁed in all 20 species (Table

S12), of which 195 single‐copy orthogroups were used for

phylogeny reconstruction. The obtained phylogeny was con-

sistent with the known phylogenetic relationships within an-

giosperms, in which the alpine taxa included in our study oc-

curred in seven independent lineages placed in six families, and

the time tree inferred from MCMCtree showed a wide di-

vergence history between alpine species and their sampled

sisters, ranging from 2 million years ago (Mya) to 31.81 Mya

(Figure 1A). We then determined convergent changes in gene

family number when a gene family showed signiﬁcant ex-

pansion or contraction in more than three alpine species. In

total 56 convergently expanded (CoEx) gene families were

identiﬁed. Biological Process (BP) of Gene Ontology (GO) and

Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses

of CoEx families found 68 signiﬁcantly enriched GO terms and

seven KEGG pathways (P‐adjust <0.05) (Tables S13,S14).

Enriched pathways of CoEx gene families were mainly related

to abiotic resistance, such as response to hypoxia, regulation of

hormone levels and hormone transports (Figure 1C, D;Tables

S13,S14). Intriguingly, we found a greater number of con-

vergently contracted (CoCo) families than CoEx families, with

1,193 gene families convergently contracted, involving 390

signiﬁcantly enriched GO terms and 27 KEGG pathways

(P‐adjust <0.05) (Tables S15,S16). Most of these pathways

included genes involved in the response to biotic stresses, such

as defense against pathogens and toxicants (Tables S15,S16).

A unique stress at high altitudes is hypobaric hypoxia

(Beall, 2014). In plants, an oxygen deﬁciency dramatically

reduces the efﬁciency of cellular ATP production, which has

diverse ramiﬁcations for cellular metabolism and devel-

opmental processes (Fukao and Bailey‐Serres, 2004). Var-

ious oxygen‐sensing mechanisms have been described that

are thought to trigger plant responses to low‐level oxygen

and thus adaptation to high altitudes (Abbas et al., 2022). In

our analysis, we found that many signiﬁcantly enriched GO

terms of CoEx families were functionally related to the re-

sponse to oxygen levels, such as response to hypoxia, re-

sponse to decreased oxygen level and response to hydrogen

peroxide (Figure 1C). These pathways included genes en-

coding alcohol dehydrogenase (ADH) (Peng et al., 2001), and

the HSP20‐like chaperones superfamily proteins that are

functionally enriched in the GO term Cellular response to

hypoxia. In A. thaliana, the oxygen‐sensing system is medi-

ated by the plant cysteine oxidase (PCO) N‐degron pathway

substrates group VII ethylene response factors (ERF‐VIIs)

(Licausi et al., 2011), which are involved in modulating eth-

ylene response activating the expression of ADH1 (Yang

et al., 2011). While we did not discover the convergent ex-

pansion of ERF‐VIIs in alpine plants, we found genes that are

signiﬁcantly enriched GO terms related to response to eth-

ylene, such as ADH1, ERF1 (ETHYLENE RESPONSE

FACTOR 1) and EER1 (ENHANCED ETHYLENE RESPONSE

1). Nonetheless, the expansion of genes involved in the re-

sponse to hypoxia is necessary for the adaptation of alpine

plants to low‐level oxygen in high‐altitude environments.

In addition, multiple CoEx families were found to be sig-

niﬁcantly enriched in plant hormone pathways. Examples in-

clude genes encoding the probable indole‐3‐pyruvate mono-

oxygenases (YUC) involved in auxin biosynthesis (Cao et al.,

2019), and the small auxin upregulated RNAs (SAUR) and the

D6 protein kinase (D6PK) involved in auxin polar transport (van

Berkel et al., 2013). Auxin regulates a series of developmental

processes such as apical dominance, plant organogenesis,

and reproductive development by affecting cell growth, dif-

ferentiation, and patterning (Mockaitis and Estelle, 2008).

Other developmental regulation pathways including leaf sen-

escence, phototropism and plant organ senescence were also

Table 1. Statistics of genome assembly and annonta-

tion of Saussurea obvallata and Rheum alexandrae

Statistic S. obvallata R. alexandrae

Total length (bp) 2,044,030,733 2,039,881,226

Number of contigs 145 129

Largest contig (bp) 126,457,859 160,815,976

Anchored length (bp) 1,951,503,694 ‐

GC (%) 37.94 41.41

Contig N50 (bp) 36,958,263 36,323,674

Complete BUSCOs (%) 94.6 96.6

Repeat content (%) 81.88 81.65

Number of genes 37,938 61,463

BUSCO, Benchmarking Universal Single‐Copy Orthologs. GC (%),

the percent of Guanine and Cytosine.

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detected to be signiﬁcantly enriched in CoEx families. This

result, coupled with the commonly observed morphological

divergence between alpine plants and lowland relatives (Sun

et al., 2014), indicates that morphological regulation can be a

pivotal path for plant adaptation to high‐altitude environments.

Convergent contractions of disease‐resistance genes

Several CoCo families in alpine plants were found to be

functionally related to response to pathogens or toxicants,

involving GO terms of response to toxic substances

and oomycetes, xenobiotic transport, and detoxiﬁcation

Figure 1. Evolutionary history of alpine plants

(A) Chronogram showing divergence times among alpine plants (cyan background) with their lowland relatives (orange background) with node age and

95% conﬁdence intervals (blue bars). The red and blue numbers above the branches represent signiﬁcant expansion and contraction events, respectively.

(B) Bar plot showing gene number identiﬁed by OrthorFinder, including unassigned genes which were not put into an orthogroup with any other genes,

genes in orthogroup, and genes in species‐speciﬁc orthogroups which consist entirely of genes from one species. (C) Signiﬁcantly enriched Gene Ontology

(GO) terms for convergently expended (CoEx) gene families in alpine plant genomes. Each bubble represents a summarized GO term from the full GO list by

reducing functional redundancies, and their closeness on the plot reﬂects their closeness in the GO graph, that is, the semantic similarity. (D) Kyoto

Encyclopedia of Genes and Genomes (KEGG) pathways of CoEx gene families in alpine plant genomes. “p‐adj”refers to the adjusted P‐value using the

Benjamini–Hochberg method.

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(Tables S15,S16). Related gene families include the cysteine‐

rich receptor‐like kinases (CRKs), a large subfamily of

receptor‐like protein kinases (RLKs) that play vital roles in

defense responses and programmed cell death in plants

(Chen et al., 2004), the malectin‐like receptor kinases (MLRs)

orchestrating the plant immune responses and the accom-

modation of fungal and bacterial symbionts (Ortiz‐Morea

et al., 2022), the multidrug and toxic compound extrusion

(MATE) proteins involved in xenobiotic detoxiﬁcation and

multidrug resistance (Diener et al., 2001), as well as the

ubiquitin‐conjugating (E2) enzymes emerging in recent years

as an important regulatory factor underlying plant innate im-

munity (Zhou et al., 2017). Moreover, the results also showed

that genes encoding receptors for tyrosine‐sulfated glyco-

peptide (PSY1Rs) and phytosulfokine (PSKRs), belonging to

the leucine‐rich repeat receptor kinases (LRR‐RKs), have

been undergoing contraction in all alpine species. PSKR1

and PSY1R have been shown to be involved in plant im-

munity, with antagonistic effects on bacterial and fungal re-

sistances (Mosher et al., 2013).

The largest disease‐resistance genes comprise genes

encoding nucleotide‐binding site and leucine‐rich‐repeat

domain receptors (NBS‐LRRs). Three NBS‐LRR gene sub-

classes, TIR‐NBS‐LRR (TNL), CC‐NBS‐LRR (CNL), and

RPW8‐NBS‐LRR (RNL), have been characterized based on

the N‐terminal domains (McHale et al., 2006). We manually

annotated NBS‐LRR genes in the sampled genomes using

the HMMER search with the Pfam database (Wheeler and

Eddy, 2013). In total 5,655 NBS‐LRR genes, including 4,058

CNLs, 1,024 TNLs and 173 RNLs were identiﬁed among all

analyzed genomes (Figure S6). Additionally, we inferred the

NBS‐LRR gene tree to examine the gains and losses of NBS‐

LRR genes in alpine species. The results showed that,

compared with lowland relatives, most alpine species tend to

lose more NBS‐LRR genes and exhibit a reduced copy

number, while E. heterophyllum,S. obvallata and R. alexan-

drae have similar numbers compared with their closest rela-

tives (Figure S7). In addition, genes functioning in cellular

transport pathways, including cytoskeleton organization,

actin ﬁlament‐based process, export across the plasma

membrane and export from the cell, were shown to be con-

tracted in alpine plants (Figure 1D;Table S15). These proc-

esses may be a component of the plant immune system and

possibly have undergone simpliﬁcation due to the pathogen‐

depauperate environments of high altitudes.

A similar phenomenon was also described in the case

study of the C. himalaica genome, in which the most sig-

niﬁcantly contracted gene families were functionally enriched

for disease and immune response pathways (Zhang et al.,

2019). Due to the harsh environments characterized by

freezing temperatures, aridity, and high UV radiation, a rea-

sonable hypothesis is that gene families involved in pathogen

or toxicant defense have undergone contraction in alpine

plants, as fewer microorganisms exist. These results suggest

that the contraction of immune system genes might be an

energy‐saving strategy to mitigate genetic loads for surviving

in hostile environments with few pathogens present. In con-

trast, the contraction of disease‐resistance genes also im-

plies that alpine plants may not adapt to the “comfortable”

environments of lowland areas where normal pathogens are

present. Therefore, with a faster pace of global warming

leading to the loss or destruction of alpine habitats, in situ

conservation for alpine biodiversity is necessary and pref-

erable to ex‐situ preservation.

Tests for convergent positive selection

In harsh environments, positive selection is expected to be

common in genes controlling early life history stages, such as

genes involved in reproduction and development (Cui et al.,

2019). Our branch‐site tests identiﬁed 36 convergently se-

lected genes that show signatures of positive selection in

more than three alpine species (Table S17). These genes

were functionally related to basic life processes involving

reproduction and respiration, such as carpel, gynoecium,

ovule and endosperm development and photorespiration

pathways (Tables S18,S19). Examples include the SE-

PALLATA (SEP) MADS‐box genes required in ﬂoral organ and

meristem identity (Pelaz et al., 2000), the MALE MEIOCYTE

DEATH 1 (MMD1) gene regulating cell‐cycle transitions

during male meiosis (Yang et al., 2003), the NIJMEGEN

BREAKAGE SYNDROME 1 (NBS1) gene involved in double‐

stranded break repair, DNA recombination and maintenance

of telomere integrity in the early stages of meiosis (Zhang

et al., 2006), and the HYDROXYPYRUVATE REDUCTASE

(HPR) gene localized in leaf peroxisomes functioning in the

glycolate pathway of photorespiration (Mano et al., 1999). In

addition, glyoxylate and dicarboxylate metabolism, the most

signiﬁcantly enriched KEGG pathways (Table S19), are fun-

damental biochemical processes that ensure a constant

supply of energy to living cells. These convergently selected

genes detected in our analyses are likely to contribute to the

primary adaptation of alpine plants to similar extreme envi-

ronments.

Detection of molecular convergence

We investigated signatures of genes undergoing molecular

convergence among alpine species using a combination of

approaches for the detection of convergent evolutionary rate

shifts and site‐based estimation of convergent amino acid

(AA) evolution. These approaches have been commonly used

to investigate the genomic signatures of convergent evolu-

tion, including convergent adaptation to seasonal habitat

desiccation in African killiﬁshes (Cui et al., 2019), convergent

regulatory evolution and loss of ﬂight in paleognathous birds

(Sackton et al., 2019), and convergent evolution of extreme

lifespan in Paciﬁc Ocean rockﬁshes (Kolora et al., 2021).

Convergent shifts in evolutionary rates were detected using

the RERconverge method (Kowalczyk et al., 2019), which

estimates the correlation between relative evolutionary rates

(RERs) of protein sequences and the evolution of a con-

vergent binary or continuous trait across a phylogeny. Our

analysis focused on positive correlations, representing genes

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with faster evolutionary rates in alpine species relative to

species living in low elevations. An increased RER could arise

due to the relaxation of a constraint or positive selection,

which could be adaptive to habitat‐related changes

(Kowalczyk et al., 2020). We identiﬁed 69 gene families un-

dergoing convergently accelerated RERs in alpine species,

signiﬁcantly enriched in 93 GO terms and 12 KEGG pathways

(P‐adjust <0.05) (Tables S20,S21), involving pathways for

self‐incompatibility, cell wall modiﬁcation, DNA repair and

stress resistance (Figure 2). Among them, 26 gene families

were found to have convergent AA shifts by a PCOC analysis

(Figure S8). The PCOC method considers shifts in AA pref-

erence instead of identical substitutions (Rey et al., 2018).

Given the relatively large phylogenetic distances among our

analyzed species, selecting only sites that converged to the

exact same AA in all species is quite strict and is bound to

capture only a subset of the substitutions associated with the

convergent trait change. Below, we demonstrate three main

aspects of BPs that have undergone molecular convergence

contributing to the adaptation to high altitudes.

Self‐incompatibility (SI) system

Self‐incompatibility in many ﬂowering plants is controlled by

the S(sterility) locus (Takayama and Isogai, 2005). The loss of

SI genes in A. thaliana is responsible for the evolutionary

transition to the self‐fertile mating system (Sherman‐Broyles

et al., 2007). Although self‐fertilization is often thought to lead

to the decreased ﬁtness of homozygous offspring, this mode

ensures reproduction in the absence of pollinators or suitable

mates, and therefore can be advantageous for plants to oc-

cupy niches in harsh environments (Goodwillie et al., 2005).

Our results revealed the biggest orthogroup (OG0000000),

which includes the Arabidopsis S‐receptor kinase (SRK)

genes and the S‐locus ﬂanking gene ARK3 (RECEPTOR

KINASE 3), undergoing evolutionary rate acceleration and

convergent AA shifts in alpine species (Figures 3,S9). Gene

Ontology analysis showed that these genes were functionally

enriched for the process of reproduction (recognition of

pollen, recognition of pollen, and pollination) and the immune

system (immune response). Furthermore, we identiﬁed the

functional domain using NCBI's conserved domain database

(CDD) (Lu et al., 2020). The result showed that these proteins

contained the S‐locus glycoprotein domain (Pfam00954),

conﬁrming their functions in the SI system. Two sites located

on the S‐locus glycoprotein domain were found to have un-

dergone a convergent AA shift (Figure S9).

Loss of function at the S‐locus in alpine Crucihimalaya

genomes, possibly due to relaxed selection, has been re-

ported (Zhang et al., 2019;Feng et al., 2022), with a similar

phenomenon found in the high‐altitude Andes maca (Lepi-

dium meyenii) genome (Zhang et al., 2016). Our branch‐site

tests did not detect any signatures of positive selection on

these genes, suggesting that the acceleration of evolutionary

rates may be the result of relaxed constraints. Relaxation of

selection on the S‐locus genes was tested using the RELAX

model (Wertheim et al., 2015), which estimates the relaxation

Figure 2. Function enrichment of gene families undergoing convergently evolutionary rate acceleration in alpine plant genomes

(A) Signiﬁcantly enriched Gene Ontology (GO) terms. Each bubble represents a summarized GO term from the full GO list by reducing functional

redundancies, and their closeness on the plot reﬂects their closeness in the GO graph, that is, the semantic similarity. (B) Top 20 enriched Kyoto

Encyclopedia of Genes and Genomes (KEGG) pathways. “p‐adj”refers to the adjusted P‐value using the Benjamini–Hochberg method.

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intensity parameter k, with k>1 indicating intensiﬁed

selection (i.e., positive or purifying selection) and k<1in-

dicating relaxed selection. The results showed that ﬁve

(C. himalaica,E. heterophyllum,H. vulgare var. nudum,

S. brachista and S. obvallata) of the seven alpine plants ex-

hibited signiﬁcantly relaxed selection on S‐locus genes

(P‐value <0.05; Table S22). Bingham and Ort (1998) reported

that low levels of insect diversity, abundance and activity

often occurred in alpine ecosystems and hypothesized that

these factors might limit the pollination of alpine plants.

Species living in isolated habitats like alpine environments or

ocean islands are thus less likely to be SI, in line with “Baker's

Law,”which assumes that pollen limitation may be an im-

portant force driving the transition of mating systems

(Cheptou, 2012). Pollination biology studies have shown

several cases of autonomous selﬁng in various taxonomically

distant species within HHM communities, although the pro-

portion of self‐pollinated species has not yet been calculated

to test the hypothesis (Sun et al., 2014). The convergent

acceleration of evolutionary rates of S‐locus genes due to

Figure 3. Four representative cases of alpine‐accelerated genes

Signatures of convergent evolutionary rate shifts were detected using the RERconverge method (P<0.05, Wilcoxon‐rank sum test). Each panel represents

the estimated relative evolutionary rates (RERs) for a gene in alpine species (point in cyan labeled with species names) as well as in their lowland relatives

(points in orange labeled with species names) and ancestral branches (plotted in a single row at the base of the y‐axis). A gene's RER for a given branch

represents how quickly or slowly the gene is evolving on that branch relative to its overall rate of evolution throughout the tree.

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relaxed selection provides convincing genetic evidence of the

evolutionary transition from SI to the self‐compatibility mating

system of alpine plants, which is potentially a convergently

adaptive process for alpine plants to facilitate their re-

production and the occupation of alpine niches.

Cell wall modiﬁcation

The cuticle membrane lies over and merges into the outer

wall of epidermal cells (Martin and Juniper, 1970). The pri-

mary role of the cuticle, composed of cutin and cuticular

waxes, is to mitigate water loss and excessive UV radiation

by functioning as a physical barrier between the plant surface

and its external environment (Kerstiens, 1996). Cuticular

waxes are composed of a variety of organic solvent‐soluble

lipids, consisting of very‐long‐chain (VLC) fatty acids and

their derivatives, as well as secondary metabolites like ﬂa-

vonoids (Pollard et al., 2008). The cell wall modiﬁcation

pathway was found to be signiﬁcantly enriched in genes

undergoing convergent positive selection (Table S18). Addi-

tionally, in the examination of convergent changes in gene

family number, we found the most signiﬁcantly enriched

KEGG pathway of co‐expanded genes to be cutin, suberine

and wax biosynthesis (Table S14), corresponding to the en-

riched suberin biosynthetic process in the GO analysis (Table

S13), including genes encoding fatty acyl‐CoA reductases

(FARs). Fatty acyl‐CoA reductases catalyze the formation of

fatty alcohols, which are common components of plant sur-

face lipids (i.e., cutin, suberin, and associated waxes). We did

not detect convergent acceleration of the evolutionary rate of

FARs, suggesting possible modiﬁcations of FARs through the

increase in gene copy number. The results show that an al-

dehyde decarbonylase enzyme CER1 underwent a con-

vergent acceleration of the evolutionary rate in alpine plants.

Overexpression of the A. thaliana CER1 gene was reported to

promote wax VCL alkane biosynthesis and inﬂuences plant

response to biotic and abiotic stresses (Bourdenx et al.,

2011). The convergent evolution of genes involved in the

cutin, suberine and wax biosynthesis implies that cuticular

waxes may function as protective screens against UV radia-

tion to protect anatomical structures and dissipate excess

light energy for alpine plants.

In addition, we detected positive selection and molecular

convergence of three MYB transcription factors, including

MYB27, MYB48, and MYB59 (Table S17). Among them,

MYB27 was reported to play a role in regulating the accumu-

lation of anthocyanins (Albert et al., 2014), a class of ﬂavonoids.

In the STRING database (Szklarczyk et al., 2021), MYB48 was

predicted to interact with proteins that are involved in ﬂavonoid

biosynthesis, including F3H (naringenin, 2‐oxoglutarate 3‐

dioxygenase), catalyzing the 3‐β‐hydroxylation of 2S‐

ﬂavanones to 2R,3R‐dihydroﬂavonols which are intermediates

in the biosynthesis of ﬂavonols and anthocyanidins, FLS1

(ﬂavonol synthase/ﬂavanone 3‐hydroxylase), catalyzing the

formation of ﬂavonols from dihydroﬂavonols, DFR

(dihydroﬂavonol reductase), catalyzing the conversion of

dihydroquercetin to leucocyanidin, and TT5, a member of

chalcone‐ﬂavanone isomerase family protein (Figure S10;

Table S23). Flavonoids function as antioxidants that reduce

DNA damage induced by abiotic stresses such as extreme

temperatures, UV radiation and drought, and thus play critical

roles in species adapting to high‐altitude environments (Agati

et al., 2012). Many examples of whole genome studies of alpine

plants have shown that expansion and/or positive selection of

genes involved in ﬂavonoid biosynthesis constitute an im-

portant part of the genomic footprint of alpine adaptation (Zeng

et al., 2015;Chen et al., 2019;Wang et al., 2021). Taken to-

gether, modiﬁcations of the cell wall in alpine plants through

evolutionary expansion and adaptive convergence of genes

involved in the biosynthesis of cuticular waxes and ﬂavonoids

might be vital strategies for adaptation to dramatic weather

changes and extensive UV radiation in high altitudes.

With the newly generated transcriptomic data of S. ob-

vallata, we were able to investigate expression patterns of

genes related to the biosynthesis of cuticular waxes and

ﬂavonoids. Five tissues with three biological replicates, in-

cluding three from leaves (basal leaves [JL], middle leaves

[ML], and bract leaves [BL]) and two from ﬂowers and stems,

were sampled (Figure 4A;Table S3). After mapping the RNA‐

seq data to the assembled genome of S. obvallata, 25,096

genes had expression proﬁles and were retained for differ-

ential gene expression (DEG) analysis. The results show that,

compared with basal and ML, BL exhibit 1,071 signiﬁcant

upregulated genes and 798 signiﬁcant downregulated genes

(Figure S11). Upregulated genes were signiﬁcantly enriched

in cytochrome P450, cutin, suberine and wax biosynthesis

and isoﬂavonoid biosynthesis KEGG pathways (Figure 4B),

and downregulated genes were functionally related to pho-

tosynthesis, energy metabolism as well as plant−pathogen

interaction pathways (Figure S12). Furthermore, we analyzed

expression proﬁles of genes involved in the biosynthesis of

cuticular waxes and ﬂavonoids. The results showed that

many genes had higher expression levels in BL than in other

leaf tissues. For example, CER1, CER3, CER4, and MAH1 in

the cuticular wax biosynthetic pathway (Figure 4C), and 4CL,

CHS, CHI, F3”H, TT7 and OMT in the ﬂavonoid biosynthetic

pathway (Figure 4D). These results suggest that the accu-

mulation of cuticular waxes and ﬂavonoids is an important

genetic pathway from normal leaves to leafy bracts. Our

ﬁndings provide new insights into the genetic basis of the

specialized “glasshouse”morphology for a better under-

standing of plant morphological adaptation.

DNA repair and stress resistance pathways

The hypoxia and intense UV radiation in alpine environments

exert high abiotic stress that can cause DNA, RNA, and protein

damage. DNA repair processes thus play an important role in

the high‐altitude adaptation of plants, similar to evidence in

alpine animals (Li et al., 2018). The NBS1 gene, involved in DNA

repair, cellular response to DNA damage stimulus and double‐

stranded break repair, was found to be under convergent se-

lection in alpine genomes (Table S17). Moreover, several sig-

niﬁcantly enriched GO terms related to DNA repair and protein

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ubiquitination were detected undergoing convergent evolution

in alpine plants (Figure 2A,Table S17). Similar KEGG pathways

were also identiﬁed, including mismatch repair, homologous

recombination and nucleotide excision repair (Figure 2B,Table

S18). Examples include the UEV1 genes, enriched in protein

K63‐linked ubiquitination pathway that reportedly play a role in

DNA damage responses and error‐free post‐replicative DNA

repair by participating in lysine‐63‐based polyubiquitination re-

actions (Wen et al., 2008), and genes encoding OB‐fold pro-

teins which were found to be important for genomic stability

including DNA replication, recombination, repair, and telomere

homeostasis (Flynn and Zou, 2010).

In addition to low oxygen levels and excessive UV radia-

tion, high‐altitude environments pose various threats to living

organisms from an unpredictable climate. We found that

many genes with convergent evolutionary rate shifts were

signiﬁcantly enriched in stress resistance pathways, such as

genes involved in the hormone signal transduction (cell rec-

ognition, intracellular signal transduction, and cytokinin‐

activated signaling pathway), the cell rhythm system (circa-

dian rhythm, cell‐cycle phase transition, and programmed

cell death), and the regulation of enzyme activity pathways

(regulation of kinase activity, regulation of GTPase activity,

and regulation of transferase activity) (Figure 2A,Table S17).

Also, some KEGG pathways were found to be signiﬁcantly

enriched in metabolic pathways that may contribute to stress

resistance, such as plant hormone signal transduction, phe-

nylpropanoid biosynthesis, and glycine, serine, and threonine

Figure 4. Highly expressed genes in bract leaves of Saussurea obvallata

(A) Sampling information of S. obvallata transcriptome data. Five tissues including three from leaves, basal leaves (JL), middle leaves (ML) and bract leaves

(BL) as well as two from ﬂowers (F) and stems (S), were sampled. (B) Top 20 KEGG pathways of signiﬁcantly upregulated genes in bract leaves. “p‐adj”

refers to the adjusted P‐value using the Benjamini–Hochberg method. Expression proﬁles of genes involved in cuticular wax (C) and ﬂavonoid biosynthetic

pathways (D) in different tissues of S. obvallata. High expressed genes in BL are shown in red in the simpliﬁed pathway models. The bar represents the

gene expression level of each gene (z‐score) (4CL, 4‐coumarate: CoA ligase; CER, protein eceriferum; CHI, chalcone isomerase; CHS, chalcone synthase;

DFR, dihydroﬂavonol 4‐reductase; F3H, ﬂavanone 3‐hydroxylase; F3″H, ﬂavonoid 3″‐hydroxylase; FA‐CoA, fatty acyl‐coenzyme A; FAR, fatty acid syn-

thetase; FLS, ﬂavonol synthase; LDOX/ANS, leucoanthocyanidin dioxygenase/anthocyanidin synthase; MAH1, midchain alkane hydroxylase 1; OMT,

O‐methyltransferase; TT7, transparent testa 7; VLC, very‐long‐chain; WSD1, diacylglycerol acyltransferase 1).

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metabolism (Figure 2B;Table S18). Plant hormones like cy-

tokinin and ethylene play pivotal regulatory roles in plant

growth and development, including cell division, shoot ini-

tiation, light responses, and leaf senescence. We found that

the type‐AArabidopsis response regulator (ARR) protein

family, involved in response to cytokinin and cytokinin signal

transduction, undergoes molecular convergence in alpine

plants. An experimental study revealed that arr mutants show

altered red‐light sensitivity, indicating an important role of

type‐A ARRs in light adaptation (To et al., 2004). The circa-

dian clock was selected as a mechanism in the control of

cell‐cycle progression to avoid sunlight‐induced DNA

damage in ancient unicellular organisms (Hut and Beersma,

2011). Circadian rhythms in plants regulate multiple proc-

esses such as photosynthesis, ﬂowering, seed germination,

and senescence (Srivastava et al., 2019). Genes involved in

the regulation of the circadian rhythm were found to have

convergently accelerated evolutionary rates in alpine plants,

such as the transcription factor MYB59, which participates in

the regulation of the cell cycle, mitosis and root growth by

controlling the duration of metaphase. The myb59 mutant

was found to have longer roots, smaller leaves and smaller

cells than wild‐type plants (Fasani et al., 2019), which are

commonly observed in alpine plants. Taken together, these

results suggested that adaptation to high altitude requires the

participation of multiple BPs.

Summary and perspectives

Taking advantage of an integrative genomic data set of alpine

plants, our study unraveled the convergent genetic changes

that confer high‐altitude adaptation (Figure 5). Both molecular

convergence in changes of gene copy number and accel-

erated evolutionary rates are consequences of selective

pressures posed by the surrounding environment. Thus, ge-

nomic signatures of convergent evolution detected here are

direct evidence for alpine plants associated with in-

dependently colonizing, evolving and adapting to extreme

cold, high UV radiation and hypoxia environments of the

HHMs. The alpine plants included in this study belong to

taxonomically distant plant families, hence standing genetic

variation and localized introgression of regions of the genome

can be ruled out as probable causes of genomic

Figure 5. Summary of convergent adaptation to high‐altitude environments for seven alpine species

The outer circle shows examples of enriched Gene Ontology (GO)‐terms (biological pathways). The middle circle shows examples of candidate genes

named after the A. thaliana orthologs. The inner gray circle shows environmental stresses from high altitudes. Species names are provided below the

picture. *Genes having undergone convergent contraction.

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convergence. Identical de novo mutations must therefore

have occurred independently in each taxon during evolution

from a low‐altitude ancestor. In addition to molecular con-

vergence, some results that do not cover all alpine plants

may imply the existence of species‐speciﬁc adaptation

strategies, which provide the foundation for further inves-

tigations into high‐altitude adaptation. Notably, our study is

limited by a lack of functional validation on the identiﬁed

molecular changes since transgene experiments are yet un-

realistic for most alpine plants. Nonetheless, verifying the role

of MYB transcription factors in the development of speci-

alized “glasshouse”morphology by quantitative real‐time

PCR is feasible in future studies. Collectively, our results

generated novel insights into genomic bases of adaptation to

extreme environments at high‐taxonomic levels of angio-

sperms, while providing valuable genomic resources for

plants living in specialized habitats. Further genomic study of

high‐altitude adaptation should provide detailed evidence

related to morphological and physiological specializations

using updated data, such as proteome and metabolome,

while also referring to discoveries from phylogenetically dis-

tant taxon to evaluate the evolutionary convergence in similar

environments.

MATERIALS AND METHODS

Plant material, DNA extraction, and sequencing

Fresh leaves of wild S. obvallata and R. alexandrae individuals

were collected from Songpan county, Sichuan Province, China

(102°45′E, 30°23′N) and Linzhi county, Tibet Province, China

(102°45′E, 30°23′N), respectively. All samples were sent to

Wuhan Benagen Technology Company Limited (Wuhan,

China) for genome sequencing. Total genomic DNA was ex-

tracted using the Qiagen DNeasy Plant Mini Kit. For the Illu-

mina short reads, DNA libraries with 500‐bp insert sizes were

constructed and sequenced using an Illumina HiSeq 4000

platform (Illumina Inc. USA). For Oxford Nanopore sequencing,

libraries were prepared using the SQKLSK109 ligation kit using

the standard protocol, and the puriﬁed library was loaded onto

primed R9.4 Spot‐On Flow Cells and sequenced using a

PromethION sequencer (Oxford Nanopore Technologies,

Oxford, UK). The Hi‐C sequencing was performed as follows:

extracted DNA was ﬁrst crosslinked by 40 mL of 2% form-

aldehyde solution to capture interacting DNA segments, the

chromatin DNA was then digested with the DpnII restriction

enzyme, and libraries were constructed and sequenced using

Illumina HiSeq 4000 instrument with 2 ×150 bp reads.

For RNA sequencing, fresh tissue samples were collected

and immediately frozen in liquid nitrogen. Three biological

replicates of ﬁve tissues of S. obvallata were sampled. Total

RNA was extracted using the TRIzol® Reagent (Invitrogen,

Shanghai, China). Paired‐end cDNA libraries were con-

structed using TruSeq Stranded mRNA Library Prep Kit

(Illumina) and were sequenced using the Illumina HiSeq

4000 platform.

Genome assembly and quality control

Prior to genome assembly, Kmerfreq (https://github.com/

fanagislab/kmerfreq) was used for counting k‐mer frequency

with the k‐mer set to 19, and GCE v1.0 was used for esti-

mating the genome size (Liu et al., 2013). The ONT long reads

were corrected and assembled using NextDenovo v2.3.1

(https://github.com/Nextomics/NextDenovo) with default pa-

rameters. Assembled contigs were polished using NextPolish

v1.4.1 (Hu et al., 2020) with the long reads and Pilon v1.23

(Walker et al., 2014) with Illumina short reads for three rounds.

Hi‐C data were used to infer chromosome conformation using

the 3D‐DNA pipeline with default parameters. The accuracy of

the Hi‐C‐based chromosomal assembly was improved using

Juicebox' s chromatin contact matrix (Dudchenko et al., 2017).

The completeness and continuity of the assemblies were

evaluated by the statistics of BUSCO and LAI, respectively.

Genome annotation

Repeat annotation

TEs were identiﬁed based on de novo and homology‐based

strategies. RepeatMasker v4.0.7 was used to run a homology

search for known repeat sequences against the Repbase

database v22.11 (Tarailo‐Graovac and Chen, 2009). Re-

peatModeler v2.0.10 was used to predict the TEs based on

the de novo method (Flynn et al., 2020). LTRharvest v1.5.10,

LTR_FINDER v1.05 and LTR_retriever v1.8.0 were used to

build an LTR library with default parameters (Xu and Wang,

2007;Ellinghaus et al., 2008;Ou and Jiang, 2018). Finally,

RepeatMasker was used to merge the library ﬁles of the two

methods and to identify the repeat contents.

Gene prediction

A combination of de novo‐, homology‐, and transcript‐based

methods were used for gene prediction in both genomes. RNA‐

seq reads were assembled using Trinity v2.1.1 using the de

novo‐based and genome‐guided modes, respectively. Coding

DNA sequences (CDS) and protein sequences were predicted

with TransDecoder (http://transdecoder.github.io). Homologues

were predicted by mapping protein sequences using GeMoMa

v1.6.1 (Keilwagenetal.,2016). Sequences of Arabidopsis

thaliana, Oryza sativa and Solanum tuberosum were mapped to

both genomes. Additionally, sequences of Helianthus annuus,

Lactuca sativa, Cynara cardunculus and Mikania micrantha

were mapped to S. obvallata, and sequences of Fagopyrum

tataricum and Rumex hastatus were mapped to R. alexandrae,

respectively. A de novo gene prediction was performed with

Braker2 v2.1.5 and GlimmerHMM v3.0.4 (Majoros et al.,

2004;Bruna et al., 2021). Assembled transcripts were used for

training gene models in Braker2. Gene models from the three

main sources were merged to produce consensus models

using EVidenceModeler v1.1.1 (Haas et al., 2008).

Gene functional annotation

The annotated protein‐coding genes were used for a BLAST

search against the UniProt and NCBI nonredundant protein

databases to predict gene functions. The functional domains

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of protein sequences were identiﬁed by InterProScan v5.51‐

85.0 using data from Pfam (Jones et al., 2014). Kyoto Ency-

clopedia of Genes and Genomes and GO terms of the

gene models were obtained using eggNOG‐mapper v2.0.1

(Cantalapiedra et al., 2021).

Orthogroup inference and alignment

Protein sequences from the seven alpine genomes, as well as

13 relatives living at low altitudes, were used for subsequent

comparative analyses. OrthoFinder v2.5.4 was used to construct

orthogroups for all species with default settings (Emms and

Kelly, 2019). Because the included species are phylogenetically

distant (widely dispersed across the eudicots and monocots),

OrthoFinder recovered an extremely low number of strictly

single‐copy orthogroups. We therefore reduced orthogroups

that contained multiple gene copies per species to one copy per

species based on the smallest genetic distance following the

study of Birkeland et al. (2020).Brieﬂy, all orthogroups were

aligned based on protein sequence using MAFFT v7.3 (Katoh

and Standley, 2013), and genetic distances between all pairs of

genes were calculated as Kimura protein distances (Kimura,

1980). One gene copy per species was retained based on the

smallest genetic distance to the longest protein sequence of A.

thaliana in each orthogroup. The rationale is that the annotation

of the A. thaliana genome is complete and reliable, and our

subsequent functional analyses of candidate genes were based

on the A. thaliana orthologs. The resulting orthogroup se-

quences that contained only one protein sequence per species

were realigned using PRANK v170427 (Löytynoja, 2014). Coding

sequences of genes in orthogroups were extracted based on

the same gene identiﬁer of protein sequences and were aligned

using PRANK with the codon mode.

Phylogeny and estimation of divergence time

Protein sequences of 195 single‐copy orthogroups were

used for phylogenetic inference with RAxML v8.2.12 using

the PROTGAMMAAUTO substitution model with 500 boot-

strap replicates (Stamatakis, 2014). Divergence time was

estimated in the MCMCtree program from PAML v4.9j (Yang,

2007), using the approximate likelihood method with the tree

topology inferred with RAxML, an independent substitution

rate (clock =2), and the HKY85 +GAMMA model. Three

calibration points were assigned based on the TimeTree

database (Kumar et al., 2017)(http://www.timetree.org/,ac-

cessed on May 1, 2022): the MRCA (most recent common

ancestor) of rosids (95% HPD 105–115 Mya), the MRCA of

Pentapetalae (95% HPD 110–124 Mya), and the MRCA of

Mesangiospermae (95% HPD 148–173 Mya). Samples were

drawn every 1,000 MCMC steps from a total of 10

steps,

with a burn‐in of 10

steps. Convergence was assessed by

comparing parameter estimates from two independent runs,

with all effective sample sizes >200.

Gene family evolution

Changes in gene family number were examined using CAFÉ5

(Mendes et al., 2020). In addition to the base model, the

number of gamma categories (‐k) was set to estimate sepa-

rate lambda values for different lineages in the tree (Gamma

model). The highest likelihood was found using k=2 rate

categories (−lnL =286114), with λ=0.00553 and α=1.58.

Gene family expansions or contractions were identiﬁed only

when the change in gene count was signiﬁcant with a

P‐value <0.05. Genomewide NBS‐LRR genes were manually

identiﬁed using HMMER v3.2 with an e‐value 1e−05 (Wheeler

and Eddy, 2013). The NBS‐LRR protein domains (NB‐ARC:

PF00931; RPW8: PF05659; TIR: PF01582; LRR: PF00560,

PF07723, PF07725 and PF12799) were retrieved from Pfam

(http://pfam.xfam.org) and were used to identify conserved

motif of NBS‐LRR genes in sampled genomes. The ML

phylogenetic tree of NBS‐LRR was constructed using

RAxML. Then, Notung v2.9 was used to recover gains and

losses of NBS‐LRR genes by reconciling the NBS‐LRR gene

tree (Chen et al., 2000). The concatenated tree reconstructed

by RAxML was used as input topology.

Functional enrichment analysis

Gene Ontology and KEGG over‐representation tests were

performed using clusterProﬁler v4.3.4 implemented in R to

identify signiﬁcantly enriched pathways (Wu et al., 2021).

Gene Ontology and KEGG terms were assigned according to

the orthologous genes of the A. thaliana genome. In the

“enrichGO”function, we set “ont =BP”to only search for

enriched BPs. The resulting P‐values were corrected for

multiple comparisons using a Benjamini–Hochberg FDR

correction. A criterion of P‐adjust <0.05 was used to assess

the signiﬁcance of enrichment analyses.

Tests for positive selection and relaxation of selection

The branch‐site model implemented in CodeML (PAML

package) was performed to test for positive selection. In this

test, an alternative model allowing sites to be under positive

selection on the foreground branch was contrasted to a null

model limiting sites to evolve neutrally or under purifying

selection using a likelihood ratio test (LRT). LRT P‐values

were computed based on chi‐squared distribution (df =2)

and were corrected for multiple tests at a P‐adjust <0.05

threshold using a Benjamini–Hochberg FDR correction. A

gene showing a signature of positive selection in more than

three alpine species was identiﬁed as a convergently se-

lected gene. Additionally, RELAX was used to test for the

relaxation of selection on S‐locus genes using the LRT by

comparing the model ﬁxing k=1 and the model allowing kto

be estimated (Wertheim et al., 2015). In both analyses, seven

tests were conducted separately by setting each alpine

species as the foreground branch.

Convergent evolutionary rate shifts

To perform the RERconverge analysis, we ﬁrst used PAML to

estimate maximum‐likelihood gene trees whose branch

lengths represent evolutionary rates using the number of AA

substitutions. RERs were calculated using “getAllResiduals”

function with weight =T, scale =T and cut‐off =0.001

Alpine plant genomes Journal of Integrative Plant Biology

12 Month 2023

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1–16 www.jipb.net

(Kowalczyk et al., 2019). We set alpine species as foreground

branches (branches of the tree with the trait of interest) and ran

“foreground2Paths”function to estimate RERs for all genes

and to correlate them with trait evolution (i.e., alpine habitats in

our study). We then used “correlateWithBinaryPhenotype”

function to test for a signiﬁcant association between RERs and

traits across all branches of the tree with a P‐value <0.05.

Convergent AA evolution

Two models were compared in PCOC analysis: the con-

vergent model in which a site on convergent branches evolves

under a proﬁle different from that of the nonconvergent

branches, and the nonconvergent (null) model in which a site

evolves under a single AA proﬁle throughout the phylogeny

(Rey et al., 2018). PCOC then detected convergent sites by

identifying the better ﬁt between the two models. To ﬁlter for

only sites with strong evidence for convergent proﬁle shifts, we

set a posterior probability threshold of >0.9 in the analysis.

Differential gene expression analysis

RNA‐seq data for S. obvallata were mapped to the as-

sembled genome using HISAT2 v2.2.1 (Kim et al., 2019). Only

uniquely mapped paired‐end reads were retained for read

counting by featureCounts v2.0.3 (Liao et al., 2014) to gen-

erate the count and transcripts per kilobase million (TPM)

Tables. DEG analyses among the ﬁve tissues were performed

in DESeq. 2 v1.36.0 (Love et al., 2014), with a P‐value <0.05

as a cut‐off and a log

fold change cut‐off of 1.

Data availability statement

The genomic data generated and analyzed in this study including

the raw sequencing data of Oxford Nanopore, Illumina, Hi‐Cand

RNA‐seq, as well as genome assembly have been deposited in

China National GeneBank DataBase (CNGBd, https://db.cngb.

org/) under accession number CNP0003451. All the custom

scripts and speciﬁc command lines have been deposited at

GitHub (https://github.com/ZhangXu-CAS/Alpine_genome).

ACKNOWLEDGEMENTS

This work was supported by the Second Tibetan Plateau Sci-

entiﬁc Expedition and Research program (2019QZKK0502), the

Strategic Priority Research Program of the Chinese Academy of

Sciences (XDA20050203), the Key Projects of the Joint Fund of

the National Natural Science Foundation of China (U1802232),

the Youth Innovation Promotion Association of Chinese

Academy of Sciences (2019382), the Yunnan Young & Elite

Talents Project (YNWR‐QNBJ‐2019‐033) and the Ten Thousand

Talents Program of Yunnan Province (202005AB160005).

CONFLICTS OF INTEREST

The authors declare that they have no conﬂicts of interest

associated with this work.

AUTHOR CONTRIBUTIONS

T.D., H.W. and H.S. conceived and led the project. X.Z., T.K.,

W.D. and Z.Q. processed data, performed analyses, and

drew ﬁgures. X.Z., H.Z., T.F., L.L. and T.D. collected mate-

rials. X.Z. wrote the manuscript. J.B.L., Y.S., J.H., T.D., H.W.

and H.S. revised the manuscript. All authors read and ap-

prove of the manuscript.

Edited by: Hongzhi Kong, Institute of Botany, CAS, China

Received Nov. 18, 2022; Accepted Mar. 21, 2023; Published Mar.

24, 2023

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SUPPORTING INFORMATION

Additional Supporting Information may be found online in the supporting

information tab for this article: http://onlinelibrary.wiley.com/doi/10.1111/

jipb.13485/suppinfo

Figure S1.K‐mer‐based analysis to estimate the genome size of Saus-

surea obvallata

Figure S2.K‐mer‐based analysis to estimate the genome size of Rheum

alexandrae

Figure S3. The Hi‐C assisted assembly of Saussurea obvallata pseudo-

molecules

Figure S4. The distribution of sequence length of predicted protein‐coding

genes in Saussurea obvallata genome

Figure S5. The distribution of sequence length of predicted protein‐coding

genes in Rheum alexandrae genome

Figure S6. Gene tree of the nucleotide‐binding site and leucine‐rich‐repeat

domain receptor (NBS‐LRR) genes

Figure S7. Loss and gain events of NBS‐LRR genes in sampled species

Figure S8. Veen plot showing the number of genes undergoing molecular

convergence detected by RERconverge and PCOC analysis

Figure S9. Site‐based estimation of convergent amino acid evolution on

S‐locus genes using PCOC method

Figure S10. The predicted STRING network of Arabidopsis MYB48

Figure S11. Volcano plot of differentially expressed genes between bract

leaves and normal leaves

Figure S12. Kyoto Encyclopedia of Genes and Genomes (KEGG) path-

ways of signiﬁcantly downregulated genes in bract leaves

Table S1. Genome sequences of 20 species used for comparative analysis

Table S2. Estimation of genome sizes for Saussurea obvallata and Rheum

alexandrae based on K‐mer statistics

Table S3. The total sequencing data for genome assembly

Table S4. The information of transcriptomic data of Saussurea obvallata

used in the study

Table S5. Statistics of initial genome assembly of Saussurea obvallata and

Rheum alexandrae

Table S6. Summary of the chromosome lengths of the Saussurea ob-

vallata genome

Table S7. Genome completeness measured of Saussurea obvallata ge-

nome and proteome by Benchmarking Universal Single‐Copy Orthologs

(BUSCO)

Table S8. Genome completeness of Rheum alexandrae genome and

proteome measured by Benchmarking Universal Single‐Copy Orthologs

(BUSCO)

Table S9. Prediction of repetitive elements in the assembled Saussurea

obvallata genome

Table S10. Prediction of repetitive elements in the assembled Rheum

alexandrae genome

Table S11. Functional annotation of predicted genes of Saussurea ob-

vallata and Rheum alexandrae genomes

Table S12. Summary of gene family clustering among the 20 species used

Table S13. Signiﬁcantly enriched Gene Ontology (GO) terms of con-

vergently expanded gene families in alpine plant genomes based on the

hypergeometric test

Table S14. Signiﬁcantly enriched Kyoto Encyclopedia of Genes and Ge-

nomes (KEGG) pathways of convergently expanded gene families in alpine

plant genomes based on the hypergeometric test

Table S15. Signiﬁcantly enriched Gene Ontology (GO) terms of con-

vergently contracted gene families in alpine plant genomes based on the

hypergeometric test

Table S16. Signiﬁcantly enriched Kyoto Encyclopedia of Genes and Ge-

nomes (KEGG) pathways of convergently contracted gene families in al-

pine plant genomes based on the hypergeometric test

Table S17. Annotation information of 36 convergent selected genes

Table S18. Signiﬁcantly enriched Gene Ontology (GO) terms of genes

undergoing convergent positive selection in alpine plant genomes

Table S19. Signiﬁcantly enriched Kyoto Encyclopedia of Genes and Ge-

nomes (KEGG) pathways of genes undergoing convergent positive se-

lection in alpine plant genomes

Table S20. Signiﬁcantly enriched Gene Ontology (GO) terms of gene

families undergoing convergently accelerated evolutionary rate in alpine

plant genomes

Table S21. Signiﬁcantly enriched Kyoto Encyclopedia of Genes and Ge-

nomes (KEGG) pathways of gene families undergoing convergently ac-

celerated evolutionary rate in alpine plant genomes

Table S22. Tests for relaxed selection on S‐locus genes of alpine plants

using RELAX model

Table S23. Functional annotation of genes predicted to interact with

MYB48

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Motivation Genome sequencing projects have revealed frequent gains and losses of genes between species. Previous versions of our software, CAFE (Computational Analysis of gene Family Evolution), have allowed researchers to estimate parameters of gene gain and loss across a phylogenetic tree. However, the underlying model assumed that all gene families had the same rate of evolution, despite evidence suggesting a large amount of variation in rates among families. Results Here we present CAFE 5, a completely re-written software package with numerous performance and user-interface enhancements over previous versions. These include improved support for multithreading, the explicit modelling of rate variation among families using gamma-distributed rate categories, and command-line arguments that preclude the use of accessory scripts. Availability CAFE 5 source code, documentation, test data, and a detailed manual with examples are freely available at https://github.com/hahnlab/CAFE5/releases.

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